The Fly River, Papua New Guinea, Volume 9: Environmental Studies in an Impacted Tropical River System (Developments in Earth and Environmental Sciences)

Developments in Earth & Environmental Sciences, 9 THE FLY RIVER, PAPUA NEW GUINEA: ENVIRONMENTAL STUDIES IN AN IMPACTED...

Author: Barrie R. Bolton

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Developments in Earth & Environmental Sciences, 9

THE FLY RIVER, PAPUA NEW GUINEA: ENVIRONMENTAL STUDIES IN AN IMPACTED TROPICAL RIVER SYSTEM Edited by

BARRIE BOLTON Environment Department, Ok Tedi Mining Limited, Tabubil, W.P., Papua New Guinea

Amsterdam – Boston – Heidelberg – London – New York – Oxford Paris – San Diego – San Francisco – Singapore – Sydney – Tokyo

Elsevier 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands Linacre House, Jordan Hill, Oxford OX28DP, UK First edition 2009 Copyright r 2009 Elsevier B.V. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (þ44) (0) 1865 843830; fax (þ44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://www.elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-444-52964-0 ISSN: 1571-9197 For information on all Elsevier publications visit our website at books.elsevier.com

Printed and bound in Hungary 09 10 11 12 13

10 9 8 7 6 5 4 3 2 1

List of Contributors Simon C. Apte

Centre for Environmental Contaminants Research, CSIRO Land and Water, PMB 7, Bangor Sydney, New South Wales 2234, Australia

Stephen J. M. Blaber

CSIRO Marine & Atmospheric Research, PO Box 120, Cleveland, Queensland 4163, Australia

Barrie R. Bolton

Environment Department, Ok Tedi Mining Limited, PO Box 1, Tabubil, Western Province, Papua New Guinea; Barrie Bolton Consulting Pty Ltd., PO Box 3053, Ripponlea, Victoria 3185, Australia, and School of Geosciences and Water Studies Centre, Monash University, Clayton, Victoria 3800, Australia

Gregg J. Brunskill

84 Alligator Creek Road, Alligator Creek, Queensland 4816, Australia

John S. Crockett

School of Oceanography, University of Washington, Seattle, WA 98195, USA

Yantao Cui

Consulting Geomorphologist, Stillwater Sciences, 2855 Telegraph Avenue, Berkeley, CA 94705, USA

Geoff Day

Newcrest Mining Ltd., Level 8, 600 St Kilda Road, Melbourne, Victoria, 3004, Australia

William E. Dietrich

Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA

Boga Figa

Livelihood Programs Department, Ok Tedi Mining Limited, PO Box 1, Tabubil, Western Province, Papua New Guinea

Miguel A. Goni

College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA

Henry Kundapen

Environment Department, Ok Tedi Mining Limited, PO Box 1, Tabubil, Western Province, Papua New Guinea

Jessica Lynas

School of Animal Biology (M092), The University of Western Australia, Crawley, Western Australia 6009, Australia

xiv

List of Contributors

Andrew R. Marshall

Andrew Marshall & Associates Pty Ltd., 43 Warrangarree Drive, Woronora Heights, New South Wales 2233, Australia

David A. Milton


Max S. Moulds

Entomology Section, Australian Museum, 6 College Street, Sydney, New South Wales 2010, Australia

Charles A. Nittrouer


Andrea S. Ogston


John Pfitzner

Australian Institute of Marine Science PMB 3, Townsville MC, Queensland 4810, Australia

Geoff Pickup

Consulting Geomorphologist, 1538 Sutton Road, Sutton, New South Wales 2620, Australia

Jesse L. Pile


Monica T. Rau

Community Relations Department, Ok Tedi Mining Limited, PO Box 1, Tabubil, Western Province, Papua New Guinea

Douglas P. Reagan

Doug Reagan & Associates, 350 Gordon Drive, Castle Rock, CO 80104, USA

Peter V. Ridd

Marine Geophysics Laboratory, School of Mathematical; and Physical Sciences, James Cook University, Townsville, Queensland 4811, Australia

Nicola J. Rogers


Joel C. Rowland

Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA

John P. Salini


Jenny L. Stauber


List of Contributors

xv

Andrew W. Storey

School of Animal Biology (M092), The University of Western Australia, Crawley, Western Australia 6009, Australia

Charles Tenakanai

Livelihood Programs Department, Ok Tedi Mining Limited, PO Box 1, Tabubil, Western Province, Papua New Guinea

John P. Walsh

Department of Geological Sciences and the Institute for Coastal Science and Policy and Coastal Resources Management Program, 301B Graham Building, East Carolina University, Greenville, NC 27858, USA

Markson Yarrao


Irena Zagorskis

Australian Institute of Marine Science PMB 3, Townsville MC, Queensland 4810, Australia

Preface Ever since the discovery of rich copper and gold mineralization under Mount Fubilan in the rugged central highlands of western Papua New Guinea there have been concerns about the potential for environmental impacts on the nearby Fly River and in particular its tributary, the Ok Tedi. These concerns prompted a wide-ranging and comprehensive series of studies of the river system designed, in the first instance, to develop an understanding of the premine environmental setting, and then following the initiation of mining in 1984, the nature and extent of mine-related impacts. Through the combined efforts of various universities, government departments, individuals and in particular, the management of Ok Tedi Mining Limited, the owner and operator of the Ok Tedi mine, this on-going attempt to monitor environmental impact has resulted in the assembly of an enormous body of work on this important river system. While much of the data acquired from these studies has been presented in workshops, conferences, and a wide range of specialist publications, there have been few attempts at bringing together the results of this work into a single volume. The 17 chapters comprising this volume are intended to summarize aspects of the natural history of the system as well as provide a multidisciplinary appraisal of the nature and extent of mine-related impacts. They provide in most instances both a synthesis of existing knowledge and a review of the status of current research and development in the respective fields addressed. The chapters have been grouped under five main themes. The first group includes six chapters that deal with aspects of the physical environment. The first chapter describes the geomorphology, hydrology, and climate of the river system. It also provides an account of the changes in the geomorphology that have occurred as a result of the release of overburden and tailings from the Ok Tedi mine. This is followed by a chapter that examines the changes that have occurred to the texture, geochemistry, and mineralogy of the sediments carried down the river system before and after the start of mining at Mount Fubilan. Another explores the impact of mine tailings and waste rock on the river floodplain and particularly the speed of these changes as evidenced by the concentrations of copper in floodplain sediments. The remaining chapters in this group examine the processes,

xviii

Preface

sediments, and stratigraphy of the Fly River delta, the fate of mine-derived copper in the sediments of the shallow Gulf of Papua adjacent to the mouth of the Fly River and finally, the variable styles of sedimentation, including material from the Fly River, in the clinoform developing at the mouth of the river. The two chapters of the second group deal with predicting the impact of mining on the physical environment. The first presents the results of efforts to model the changes in the rate of river bed aggradation brought about mainly by the discharge of waste rock and tailings from the Ok Tedi mine, while the second focuses on the resultant increase in the incidence of floodplain inundation and how this is likely to change in the future. The two papers of the third group discuss aspects of the mine’s influence on the chemistry and biotoxicity of river waters. The first provides a review of the processes controlling the fate of copper, the main metal contaminate originating from the mine, in the river system while the second discusses the considerable research into the speciation, bioavailability, and toxicity of copper. The fourth group of three chapters deals with the fish population of the river and how it has been affected by mining. The first of these chapters’ focuses on the biology of barramundi in the river, one of the main food sources for the communities living along the river’s edge. A second chapter examines the effects of mine-derived waste materials on fish habitat while the third and last explores the spatial and temporal changes in fish assemblage to assess the impact of the mine. The last group of four chapters deals with the fauna of the region, the riparian vegetation, and the development of a food web for the system. It is hoped that publication of these contributions will stimulate further discussion and research on the impact of mining on riverine and their adjacent near-coastal environments. Finally, the job of an editor of a volume such as this would be impossible without the help and support of a lot of people. First I wish to thank Keith Faulkner, a former Managing Director of Ok Tedi Mining Limited (OTML) and Jim Veness, current Manager of the OTML Environment Department, for their unfailing support and encouragement throughout this project. OTML Board members, Allan Roberts, Ross Garnaut, Jochen Tilk, Dick Zandee, and Simon Tosali are also thanked for their support and encouragement in the production of this volume. The financial support provided by Ok Tedi Mining Limited for the publication of this book is also gratefully acknowledged. I would also like to acknowledge the efforts of the following people who provided critical reviews and many editorial improvements to the

Preface

xix

contributions of this volume: Geoff Pickup, Len Murray, Barry Hart, Mead Allison, Simon Apte, Ted Edwards, David Heggie, Kent Hottle, Paul Humphries, Denis Mackey, Alan Orpin, Max Moulds, John Chapman, Wade Hadwen, Robert Hughes, Peter Teasdale, Franc- ois Edwards, Scott Markich, Susan Adams, John Rinne, Katie Farnsworth, Robert Dalrymple, Scott Miller, Jim Veness, Jacky Croke, Ian Cowx, Alan Whitfield, and H. Gill. And finally, I wish to thank the support of the very patient staff at Elsevier for this project and specifically, Linda Versteeg-Buschman, Suja Narayana and Femke Wallien.

Barrie Bolton Environment Department, Ok Tedi Mining Limited

Developments in Earth & Environmental Sciences, 9 B. Bolton (Editor) r 2009 Elsevier B.V. All rights reserved DOI 10.1016/S1571-9197(08)00401-1

Chapter 1

Geomorphology, Hydrology, and Climate of the Fly River System Geoff Pickup1, and Andrew R. Marshall2 1

Consulting Geomorphologist, 1538 Sutton Road, Sutton, New South Wales 2620, Australia 2 Andrew Marshall & Associates Pty Ltd., 43 Warrangarree Drive, Woronora Heights, New South Wales 2233, Australia

1.1. Introduction The Fly River system drains an area of about 75,000 km2 in western Papua New Guinea (Fig. 1.1). There are three major rivers in the system: the Ok Tedi, which drains the Hindenburg Ranges; the Upper Fly, which drains the southern part of the Victor Emanuel Range; and the Strickland, which drains the Victor Emanuel and Central Ranges. The Upper Fly and the Ok Tedi meet at D’Albertis Junction to form the Middle Fly, which meanders down a 400-km-long floodplain with extensive scroll bar complexes, cutoffs, and blocked valley lakes. The Middle Fly and the Strickland meet at Everill Junction before entering the Fly Delta. The delta covers about 10,000 km2 and extends downstream for another 400 km before entering the ocean in the Gulf of Papua. The Ok Tedi receives waste rock and tailings from Ok Tedi while the Strickland receives sediment load from mining operations at Porgera. This chapter covers the climate, geomorphology, and hydrology of the Fly. It examines rainfall distribution and basin hydrology. It describes the river system from the mountains to the lower end of the floodplain, including linkages between the river channel and the many off-river water bodies (ORWBs) in tributary valleys and on the floodplain. It concludes with a summary of mine-related impacts on the river system. Corresponding author. Tel.: þ61 26238 3427;

E-mail: [email protected] (G. Pickup).

4

G. Pickup and A. R. Marshall

Figure 1.1: Location map. Mining operations at Tabubil and Porgera are shown by arrows.

Geomorphology, Hydrology, and Climate of the Fly River System

5

1.2. Climate The Fly basin has a humid tropical climate. Average rainfall varies with elevation (Moi et al., 2001). Falls in excess of 10,000 mm/year occur at the Ok Tedi mine site (1,500–2,000 m), declining to about 8,000 mm/year along the upper and middle Ok Tedi. Further decreases occur downstream with values of 5,250 mm/year being recorded at Kuambit just downstream of D’Albertis Junction, 3,869 mm/year at Manda about two-thirds of the way down the Middle Fly floodplain, and 1,847 mm/year at Obo near Everill Junction. Heavy rainfall occurs throughout the year in the mountains, but there is a slightly less wet period from September to November. Seasonal variations are also stronger over the southern part of the floodplain, where rainfalls are lower than in the mountains. Based on other stations in lowland Papua (McAlpine et al., 1975), annual evaporation is probably within the range 1,500–2,000 mm, which is less than annual rainfall in many areas. Rainfall not only varies between seasons. The region experiences both El Ninõ and La Ninã events, including severe drought episodes in 1972, 1983, and 1997. There may also be longer-term variations in rainfall. For example, Moi et al. (2001) report that rainfalls for 1999–2000 exceeded long-term averages across the region, with the largest percentage increases occurring in lowland areas. The rainfall record for Tabubil, just below the mine site, shows some connection with the Southern Oscillation Index (SOI) (Fig. 1.2) but mainly during severe droughts. There is no obvious relationship at other times, making it difficult to use the SOI as a predictive tool.

1.3. River System Geomorphology In its upper reaches, the Ok Tedi and its tributaries drain a heavily dissected ridge and ravine landscape. The ridges rise to over 2,000 m in the north, but most of the basin lies between 200 and 800 m. The eastern part of the basin is karst country, including the massive Hindenburg Wall escarpment, and contains large areas of landslide debris and old debris flow deposits. In the west, igneous rocks are exposed on high mountains, but much of the area consists of shales, limestones, and sandstones. Slopes are unstable in spite of a dense rain forest cover, and landslides and debris flows are common. Mine waste is disposed of into two tributaries of the Ok Tedi: Sulphide Creek (which joins the Ok Gilor, and then the Ok Mabiong in its lower section)

6


1200

30

1000

10 SOI Value

800 0 600 -10 400 -20 200

-30 -40 1970

Tabubil Monthly Rainfall (mm)

20

0 1980

1990

2000

Figure 1.2: Monthly rainfalls for Tabubil compared with the Southern Oscillation Index. Both datasets have been smoothed using a five-point moving average. and the Ok Mani (Fig. 1.3). These tributaries are referred as the Mine Area Creeks. These systems occupy steep, narrow valleys and, prior to mining, were cut down to bedrock for most of their length. Sediment deposits were restricted to local boulder chokes and short reaches with thin layers of armored cobbles. Sulphide Creek contains a waterfall, as does Harvey Creek, a small tributary of the Ok Mani that now receives waste rock from dumps on the southern side of the mine. These creeks are typical of the supply zone (Table 1.1) and were transporting virtually all delivered load before mining operations started. The Upper Ok Tedi is a fast-flowing river capable of transporting large quantities of coarse sediment, including boulders. For much of its length, it occupies a bedrock gorge less than 200 m wide at its base, although there are wider sections with a few islands developing in the lower sections. Debris flow deposits flank the upper reaches of the gorge, and bed levels have fluctuated over time in response to massive landslides from the Hindenburg Wall and other areas, including one of 7 km3 about 8,800 BP (e.g., Pickup et al., 1979; Blong, 1991). Prior to mining, this reach of the river was classified as a supply zone (Table 1.1). However, unlike the Mine Area Creeks, the bed had a veneer of coarse sediment in transit, much of which probably came from the 1977 Hindenburg Wall landslide. Just upstream from Ningerum, the Lower Ok Tedi emerges from its gorge into a gradually widening valley filled with what are probably Pleistocene


7

Figure 1.3: A SPOT image of the Ok Tedi mine and the Mine Area Creeks. alluvial deposits. These include weathered and indurated sand and gravel deposits topped by distinctive red soils. Initially, these ‘‘red beds’’ form valley edges and confine the channel but, as the valley widens, form terraces or terrace remnants, and the Ok Tedi develops a currently active floodplain within them. A braided channel develops, and forested islands have formed on some of the more stable braid bars. Before mining increased sediment input to the river, this reach was classified as an armored zone merging into a gravel–sand transition zone (Table 1.1). Finer material, including a large volume of sand, is now being deposited in this area. Prior to mining, the armored zone ended upstream of the junction with the Ok Mart where braiding ceases, and there was a distinctive gravel front. Beyond this point, there was a gravel–sand transition zone (Table 1.1). Flow in the gravel–sand transition zone was (and still largely is) concentrated in a single channel, and meandering begins to develop. However, although there are several meander cutoffs and some channel traces, the floodplain is confined to a narrow belt, 1–4 km wide within the alluvial piedmont, and shows some traces of minor incision. The outer sections of some meanders also cut into Pleistocene terrace remnants, and lateral movement is restricted by indurated and highly weathered soils developed on former fluvial sediments.

8

Zone

Supply

Armored

Gravel–sand transition

Sand

Backwater

Location

Mountain tributaries and upper gorges. Mine Area Creeks, Ok Tedi to Ningerum

Sediments

250 mm–W1.0 m 100–200 mm at but mainly coarse surface, mixed sand and gravel below

Bimodal Well-sorted sands distribution with mainly in 0.2- to gravels in 15- to 0.4-mm range 60-mm range and well-sorted sands

Channel form

Bedrock gorges Wide, shallow and boulder-lined channels, often torrents in braided but with confined reaches. many stable bars Wide, shallow and islands channels, in wider sections, often braided but connected by steeper reaches. Few deposits

Varies from wide, Meandering with Meandering with shallow, and levees, welllow levees, scroll straight to deep developed bars, and and sinuous. floodplains and frequently Confined by off-channel water inundated valley walls, bodies backswamps. terraces and (backswamps and Sand and silt clay terrace remnants, cutoffs). Terrace bed deposits although there is remnants restrict depending on some floodplain meandering local variations in development locally flow velocity

Middle and lower Upper floodplains. Floodplains. gorges to gravel Bige to Atkamba Atkamba to front upstream of Manda Bige

Fly upstream of the Strickland between Manda and Everill Junction. Minor floodplain tributaries Well-sorted very fine-medium sand alternating with silts and clays


Table 1.1: Classification scheme for river reaches on the Fly River System prior to mining.

Sediment regime

Controlling factors Underlying Behavior is Possibly an Supply controlled, Backwater effects bedrock controls sediment supply armored reach at mainly by sand. force deposition slope, valley walls controlled but by lower sea levels. Local controls on but local scour confine channel material in armor Channel forms lateral movement may occur when layer typical of a mixed imposed by backwater effects load sediment terrace remnants are temporarily regime removed Source: Adapted from Pickup (1984) and Higgins et al. (1987).


Transport capacity Transport capacity Transport capacity Mobile sandy Unable to usually greater greater than just greater than bedload and fine transport all load than supply, supply, except for supply for sand. suspended load. when backed up except after major sizes in the armor Gravels rarely Close to shortlandslides. Bed layer that are only move and may be term equilibrium covered by a transported in locally derived with respect to veneer of material large flows from Pleistocene bed material load. in transit or swept terraces as well as Often below clean. Material upstream reaches capacity for wash often moves in load slugs or waves

9

10


The Middle Fly extends for about 420 km from D’Albertis Junction to Everill Junction, where it meets the Strickland. There are two distinct reaches: a sand zone and a backwater zone (Table 1.1). Prior to mining, the sand zone had a riverbed consisting of well-sorted fine-to-medium sand and extended as far downstream as Manda. This reach has a steeper water surface slope than the backwater zone that extends from Manda downstream to Everill Junction. The pre-mining backwater zone had a bed composed of mainly fine sand but with an increasing proportion of silt clay particles further downstream until less than 20% sand was present. A localized body of medium sand occurred downstream from Bosset and is probably associated with the slightly steeper river long profile there. It may have originated from the catchment of the blocked valley lake of Bosset Lagoon. The evolution of the Middle Fly may be as follows. During the Pleistocene, the river repeatedly entrenched and dissected surrounding hills during periods of low sea level (Loffler, 1977). As sea level rose, reaching its current height around 5,000 BP, the river aggraded at about 1 mm/year (Pickup et al., 1979), declining to about 0.1 mm/year (Dietrich et al., 1999). The aggradation process created a number of distinctive landforms (Paijmans et al., 1971) (Figs. 1.4 and 1.5). First, there is a central meander belt made up of the river channel, a wide and sometimes discontinuous levee, scroll bar complexes, Pleistocene terrace remnants, and partly filled meander cutoffs, often connected to the main river by tie channels. This system forms an inner floodplain, accumulates most of the sediment from upstream that is deposited, and is perched above the surrounding outer floodplain. Second, the aggradation and levee buildup of the inner floodplain was sufficient to block off or back up most of the lowland tributary systems. This created a system of blocked valley lakes, backswamps, flood basins, and drowned tributary channel systems on each side of the central meander belt. These systems may be up to 7 m lower than the levees that border the main river channel. The elevation difference decreases downstream and is smallest in the backwater zone upstream of Everill Junction (Dietrich, 2000). However, it remains a significant feature in determining both floodplain behavior and landforms down as far as the Fly Delta. While the Middle Fly contains spectacular evidence of meandering in the form of cutoffs and scroll complexes, it has not experienced rapid lateral migration. Pickup et al. (1979) found that only three loops were cut off between 1899 and 1979. More extensive analyses by Barr Engineering (1995) and Dietrich et al. (1999) found that bank erosion and meander migration rates were highest close to D’Albertis Junction and decreased by a factor of three, downstream to the backwater-affected reach.


11

Figure 1.4: A LANDSAT TM image showing the floodplain systems of the upper Middle Fly during low-flow conditions. Flooded off-river water bodies are shown in black or blue. Dried-out areas that are normally flooded are pink or purple. Green areas are mainly rain forest. Yellow squares are gauging stations or sampling sites. The vegetation of the floodplain corresponds fairly closely with the steepness of the long profile. Rain forest extends from D’Albertis Junction to a point beyond Mabaduam, entering a transitional reach close to the junction with the Agu. The lower, backwater-affected reach, beyond Manda,

12


Figure 1.5: A LANDSAT TM image showing the floodplain systems of the lower Middle Fly and lower Strickland during low flow conditions. Flooded off-river water bodies are shown in black or blue. Dried-out areas that are normally flooded are pink or purple. Green areas are mainly rain forest. Meander cutoffs, blocked valley lakes, and swamps behind the main channel levees are all clearly visible. Yellow squares are gauging stations or sampling sites. largely consists swamp grass or riparian vegetation (Day et al., 1993). The low gradients down the Middle Fly and the small transverse differences in floodplain elevation make floodplain vegetation systems sensitive to changes in water level on the Fly if they are of sufficient duration.


13

It is likely that the Fly has evolved only slowly since the sea level reached its present level. Before sediment load increased due to mining, the levee system was probably growing upward and extending downstream through deposition of sediment. However, given the limited sediment load reaching the Middle Fly, the rate of progress was very slow. For example, Pickup (1984) estimates that it would take somewhere between 1,400 and 27,000 years for the sand zone in the Middle Fly to extend as far as Everill Junction, provided that the bed level of the Strickland remained constant. The backswamps receive limited amounts of material from the main channel, apart from close in to the levees, and may grow upward more by accumulation of organic material than by deposition of sediment. Studies using copper as a marker show that most of the sediment leaving the main river channel is deposited on the levees, in off-channel water bodies with tie channels to the main river, and by backflow up tributaries (Day et al., 1993; Dietrich, 2000). The Strickland has a catchment area of 36,740 km2 at Everill Junction and is a much larger river than the Fly (catchment area of 18,400 km2). It is also closer to the main sources of natural sediment load in the mountains. Like the pre-mining Ok Tedi and the Middle Fly, the Strickland has an armored zone, a gravel–sand transition zone, and a sand zone, but these extend much further down the system. The Strickland has a steeper gradient than the Fly, and its floodplain probably had more active channel shifting. The Strickland backs up some very large off-channel water bodies, including Lake Murray. It is separated from the Middle Fly floodplain by a 10- to 30-km-wide preHolocene former floodplain surface that forms an extensive set of terraces. Once the Strickland and the Middle Fly join, river characteristics change. Prior to mining, the Strickland transported perhaps 8–10 times the natural load of the Fly. Even now, it probably contributes more than 60% of the total load (Moi et al., 2001). Also, the bed material of the Strickland and the Lower Fly contain much more sand than the Middle Fly. The Fly Delta is a funnel-shaped system dominated by tidal action. The tidal range is about 3.5 m at the mouth and 5 m at the apex (Wolanski and Eagle, 1991). Channel bed material is mainly sand, and the majority of fine material is advected offshore (Harris et al., 1993). Terrace remnants in the delta are substantially higher than those surviving in the Middle Fly. The channel also seems to become more confined downstream and does not have the extensive floodplains and backswamps of the Middle Fly. This may suggest minor uplift due to tectonic activity or isostatic adjustment. The confined channel, increased river discharges, and tidal flushing all limit the deposition of mine-related sediment reaching the delta.

14


1.4. Hydrology 1.4.1. Runoff and Flooding Most of the runoff in the Fly River originates in the mountains. Runoff at Kuambit just below the junction of the Ok Tedi and the Upper Fly is about 6,600 mm/year or about 70–80% of the total rainfall. However, once runoff enters the floodplain reach of the Middle Fly, flow patterns change (Fig. 1.6). At the upstream end of the floodplain, water levels vary rapidly as floods from the Ok Tedi and the Upper Fly enter the system. By the time flow reaches Manda, about 230 km downstream, much of the short-term variability has disappeared, and most of the changes in water level occur at a scale of weeks to months. The main cause of this flood wave attenuation is exchange of water between the main river and many off-river floodplain storages through tie channels, levee breaches, and, if water levels are high enough, directly across the floodplain. Dietrich (2000) describes the floodplain storages as follows: There are 38 oxbow lakes within the scroll complex of the study area, 25 of which have well maintained tie channels which transport water and sediment over a large range of main channel stage. A further 8 of the oxbows have smaller tie channels which transport water and sediment only over the upper ranges of main channel flow with the remainder (5 oxbows) having no apparent tie channel. There are at least 35 blocked valley lake systems within the backswamp areas of the floodplain ranging in size from o0.1 km2 to W 50 km2. The off-river water bodies (ORWB) (oxbow and blocked valley lakes) comprise 10% of the total area of the floodplain or approximately 350 km2.

20

Elevation (m)

15

10

5

0 1/1/95

1/1/96

1/1/97

1/1/98

1/1/99

1/1/00

1/1/01

Figure 1.6: Water levels on the Middle Fly 1995–2000.


15

The ORWBs can hold 2–3% of the annual flow of the Fly before general flooding occupies most of the floodplain. However, because there is continuous inflow and outflow between the floodplain storages and the main channel during floods, a much larger proportion of flow is cycled through them. Dietrich and Day (2004) has suggested that at least 20%, and possibly up to 40%, of the Fly River water passes through the floodplain. Model calculations (see Pickup, 2009) suggest that the value is closer to 10% but could increase to between 14 and 16% by 2050, depending on the level of bedload extraction by dredging from the Lower Ok Tedi. Most of the transfer between the main river channel and the floodplain is inflow and outflow to and from storages rather than flow down backplains between levee breaches. However, there is evidence on satellite imagery of backplain flow on the west side of the Fly near Bosset. Dietrich and Day (2004) have suggested that water may leave the middle reaches of the Middle Fly via tie channels and flow into the Agu River. This water then returns to the lower Middle Fly via the Agu junction below Manda. It is not clear how important this effect is. Three small tie channels connect ORWBs to both the Fly and the Agu, and it is possible for water to flow into the Agu across the floodplain at high water levels. At the same time, flood levels on the Fly propagate up the lower Agu very quickly, so the flow path from the Fly via the upper Agu would soon be restricted by rising water levels. 1.4.2. Links between the River and its Floodplain – The Fly River Tie Channels The term ‘‘tie channel’’ was coined by Blake and Ollier (1971) to describe the narrow channels that link the main river channel and the oxbow lakes that occupy meander cutoffs on the Fly floodplain. These channels experience bidirectional flow, depending on differences in water level between the oxbow lake and the main river. Typically, water flows into the oxbow on the rising stage of floods in the main river and out of it as floodwater levels recede (Fig. 1.7). Hydraulic gradients therefore vary with time but may be steep, and flow velocities of 1–2 m/sec are quite common at times of rapidly changing water levels. This is enough to keep many tie channels clear of sediment and some have functioned for hundreds and perhaps thousands of years (Rowland et al., 2005). It is likely that tie channels play a crucial role in the ecology of ORWBs. They provide a route for the transfer of water and sediment, transport contaminants, and allow the exchange of carbon. They may also serve as refugia and breeding sites for fish species, especially during drought.

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Figure 1.7: Some features of tie channels. Upper left shows rapid and turbulent flow through a narrow vegetation-lined tie channel. This is sufficient to move sandy bed material from the Middle Fly into the receiving water body. Upper right shows a tie channel when water levels on the main river and the connected water body are similar. Virtually no flow is occurring. Lower left shows a tie channel draining clean water from the ORWB into the Fly. Lower right shows what occurs when water levels in the river and the ORWB have equalized during a large flood. The levee breach tie channel is completely submerged and contains still, clear water.

Water circulation through tie channels may have a role in maintaining water quality in many ORWBs, especially if they are small. Most ORWBs will be replenished by rainfall, and virtually all become connected with the main river during major floods. However, during periods of low-medium flow on the main river, flow through tie channels will be the main process of water circulation. This may be a factor limiting eutrophication in the smaller ORWBs, where tie channel flow could replace 5–10% of the total water volume in a day. In larger water bodies, input from rainfall, inflows from the surrounding catchment, and outflow to the main river would play a greater role in water circulation. However, inflow and outflow of main channel water is still likely to be the dominant process.


17

If we define a tie channel as one that links the main river channel and an ORWB and experiences bidirectional flow, then there are at least seven types on the Lower Ok Tedi and the Middle Fly (see Fig. 1.8 for examples). Each type may have evolved in a different way, and there may be variations in the potential for silting up. The main types are: Cutoff tie channels that connect oxbow lakes of meander cutoffs to the main river. The oxbows are the deepest ORWBs on the floodplain and usually hold water during drought, even if water levels fall below the elevation of the tie channel bed. They are therefore likely to be important refugia for a whole range of aquatic species. Several subtypes occur. The most common form drains through a sediment plug at one or both ends of the former meander channel. Several others exit closer to the middle of the cutoff through the swales between adjacent former point bars. A third variation occurs where the tie channel links with a tributary, and there are even cases where the tributary crosses the cutoff and functions as the cutoff tie channel as well as draining its own catchment. Levee breach channels. These may vary in size and usually connect the river to areas of standing water in the backswamps behind the levee. These backswamp lakes vary in depth and area over time and may dry out completely when river water levels are low during drought. Levee breach channels are usually short and may develop when localized levee collapses occur and open a path for water to flow. There are shallower and probably more short lived than the cutoff tie channels. Many levee breach channels may have silted up, as levee deposition has accelerated in response to deposition of mine waste. Tributary tie channels. Over the last 5,000–7,000 years, the central meander belt of the Fly has grown in height faster than the outer edges of the floodplain and the floors of tributary valleys. This has created a set of blocked valleys often containing permanent or ephemeral lakes that provide the largest areas of standing water on the floodplain. The blocked valley lakes cover a large area, and some of the larger ones may have water depths similar to the meander cutoff oxbows close to the main river. The larger lakes hold water during drought, and many are distant from the main river channel. The more distant lakes are largely unaffected by deposition of sediment from the main river. Tributary tie channels can be highly sinuous and often have well-developed levees. While no dating has been done, it is likely that most of these channels are hundreds to thousands of years old, especially in areas distant from the main Fly River channel. Drowned tributary tie channels. The backwater zone of the Middle Fly extends from Manda to Everill Junction. Backwater from the Strickland

18


A

B

C

D

E

F

Figure 1.8: Examples of tie channel types. (A) A blocked valley tie channel with typically sinuous form entering the Lower Ok Tedi through a levee breach. (B) A cutoff tie channel. (C) A levee breach into a flooded backswamp. (D) A levee breech into a flooded area in an old scroll bar/swale complex. (E) Submerged former channel levees in a blocked valley lake. (F) A complex tie channel system at D’Albertis Junction. The large tie channel in the foreground connects the upper Fly and the Ok Tedi along a meander trace. The smaller tie channel above it connects a meander cutoff.


19

keeps large areas of the floodplain inundated for long periods. The tie channels that originally linked ORWBs to the river are now flooded for most of the time, and only their levees may be visible. These channels may offer a faster path for water flowing from the river to the inundated area when water levels rise after a drought, but for most of the time, they behave as part of the lake. Again, they are likely to be hundreds to thousands of years old. Meander neck channels. A few meanders on the Fly and the Lower Ok Tedi have narrow channels that cut across the meander neck. Typically, they occupy a swale between adjacent scroll bars. Some provide a shortcut for canoe and small-boat traffic. They may experience bidirectional flow if they provide access to large areas of intermittently flooded backswamps behind levees. Fossil tie channels. The floodplain contains traces of tie channels of all types that are no longer functional or only operate intermittently. Many of the blocked valley lakes show sinuous channel traces that are only visible at low water. Many disappear well before they reach the main river. Others appear to have been blocked by long-term levee development on the main channel. There are also some abandoned tie channels connecting the main river with meander cutoff oxbows. In at least one case, the cutoff tie channel has been abandoned when meander migration on the main river has intersected the oxbow and opened up a new path for water flow (Rowland et al., 2005). Composite forms consisting of more than one tie channel type are fairly common. Both cutoff and tributary tie channels often have levee breaches that drain adjacent backswamps. Cutoff and tributary channels also sometimes capture each other and intersect. Very little work has been done on tie channel behavior. The most detailed information in the literature comes from Rowland et al. (2005) and Rowland and Dietrich (2006). These papers describe the forms, sedimentology, and evolution of meander cutoff tie channels, together with deposition rates in associated oxbow lakes. Rowland describes tie channel evolution as follows. Sediment-laden water from the main river enters the cutoff as a jet that extends a small delta outward into the cutoff water body and advects sediment laterally to its margins. This allows a set of submerged levees to build up. Over time, the levees extend upward and outward, gradually filling up the river end of the cutoff with sediment. Flow is usually sufficient to keep the bed of the tie channels scoured, and finer sediment deposited on the banks when flow velocities are low tends to collapse into the channel during more active periods. Flow from the cutoff water body back to the river, as water levels

20


recede after a flood, also plays a role in keeping the tie channel open since it scours sediment that may be deposited when water levels are similar in both the main river and the cutoff, and tie channel flow velocities are low. An example of tie channel evolution from the Fly floodplain is shown in a series of satellite images in Fig. 1.9. Several factors govern the rate of tie channel extension into the cutoff oxbow lake and whether a tie channel is likely to be maintained. First, there is the amount of water flowing into and out of the oxbow. This is a function of lake size and water level variations on the main river channel. More water will flow into larger oxbows. Also, inflow and outflow will occur more frequently when river levels are more variable. Second, the sediment concentration in river water will affect delta growth rates since most of it will settle out as the jet enters the still water of the lake. Sediment concentration will also influence tie channel levee growth and backfilling of areas behind these levees. Tie channels not only grow outward into meander cutoffs but may also extend toward the river if meander migration moves the channel away from the original tie channel mouth (Rowland et al., 2005). Many of the long, straight tie channel sections on the Middle Fly floodplain have developed in this way. Rowland et al. (2005) have dated two active tie channels connecting the Fly with meander cutoffs. One was 347744 years old while the other proved to be at least 9287128 years old. This indicates how persistent tie channel features can be. It also suggests caution in interpreting ‘‘blocked’’ tie channels. They may, in fact, have been blocked for hundreds of years and long before mine sediments were added to the river. Rowland’s model can be applied to levee breach tie channels as well as those connecting meander cutoffs to the river. However, the tie channel levee complex and the delta will not develop to any great extent. This occurs because the floor of the levee breach remains close to the elevation of the backswamp behind the main channel levee. This limits the water surface slope that can develop between the ORWB and the river and keeps flow velocities lower than in cutoff tie channels. It also prevents much of the sandy main riverbed material from getting into tie channel flow. Most of the sediment reaching the ORWB will therefore be fine main river wash load that settles out slowly and disperses more widely in the ORWB. Blocked valley tributary tie channels may also evolve differently from cutoff tie channels. Many of these systems have long reaches with welldeveloped levees that have built up over thousands of years in response to bidirectional flow. However, because these channels are much longer than the cutoff tie channels, they do not tend to develop the steep water surface

Jan 1998

Feb 2000

Oct 2002

Feb 2004

Jul 2005

Figure 1.9: Evolution of a cutoff on the Middle Fly. Infilling and tie channel development begins very quickly once the cutoff has occurred. Initially, both ends of the cutoff remain open to water from the river, but one arm of the former meander develops a tie channel. Eventually, a tie channel begins to develop in the other meander arm. Imagery includes LANDSAT TM, PACRIM 2000 SAR, and ENVISAT SAR.

22


slopes that occur in cutoff tie channels during rising and falling flood stages. Deposition therefore tends to be dispersed over a longer distance, and the jetdeposited fans of cutoff oxbow lakes are less likely to occur. Many of the blocked valley tributaries also drain and fill very large ORWBs and have sufficient flow to remain open. 1.4.3. Backwater Effects from the Strickland Backwater effects from the Strickland partly determine water levels in the lower reaches of the Middle Fly. The backwater effect extends upstream for about 200 km, and the gauging record at Manda (FLY16) closely follows that of Obo (FLY15) (Fig. 1.6). Lack of data makes it difficult to determine the precise influence of the Strickland. Gauging stations on the Lower Fly at Ogwa (FLY22) and the lower Strickland (STR01 and more recently SG4) have only operated for short periods, and there are many missing records. Obo (FLY15) has a longer record, but gaps in the data frequently coincide with periods when the other gauges were operating. There is a common dataset for Obo (FLY15) and the lower Strickland (STR01) with few missing records for 1989–1992 (Fig. 1.10). STR01 is 73 km upstream of Everill Junction and below Massey Baker Junction, where the 16 14

Elevation (m)

12 10 8

STR01 (LOWER STRICKLAND) FLY15 (OBO)

6 4 2 0 1/1/88

1/1/89

1/1/90

1/1/91

1/1/92

1/1/93

1/1/94

Figure 1.10: Water levels on the lower Middle Fly and the lower Strickland. Strickland height datum is arbitrary.


23

flows from Lake Murray join the Strickland. There are no major inflow points between Station STR01 and Everill Junction, so the STR01 record should give a reasonable indication of flows in the Strickland at Everill Junction. The datasets show both differences and similarities among stations. Some of the low water levels at Obo (FLY15) and on the lower Strickland (STR01) coincide, but this is not always the case. There is also some matching of flood peaks but, again, not in every case. A very crude multiple-regression analysis for a short period shows that, after adjusting for lag, Stations FLY10 (Kuambit) and STR01 have a similar degree of influence on water levels at Obo (FLY15). However, these results do not cover a wide enough range of water levels to be definitive. They show that water surface elevations on the lower Middle Fly are a product of flows coming down both the Fly and the Strickland. 1.4.4. Tidal Effects Very few data are available to show the influence of tidal cycles on Middle Fly water levels. A tide gauge operated at Daru, southwest of the Fly Delta for short periods in mid-1983, but no water level data are available in the OTML database for the lower Middle Fly. The JTides model (http:// www.arachnoid.com/JTides/) gives a good reproduction of the limited Daru Roads dataset. This model may be used to calculate tidal variation for other periods, including those when lower river system gauges were operating. The longest gauging record for the lower river system is for Station FLY15 at Obo. However, this station is affected by backwater from the Strickland as well as weak tidal effects. A Lower Fly station (FLY22) operated at Ogwa, just downstream of Everill Junction (Fig. 1.1) in late 1996 and early 1997. This station measures water levels for the combined flows from the Middle Fly and the Strickland and gives a clearer picture of tidal influences. Ogwa (FLY22) water levels are compared with the modeled tidal variation in Fig. 1.11. Daily tidal variation can be seen on the lower graph. By the time tidal influence reaches Ogwa, there is only about 0.1-m variation at low water and less during medium flows. At high flow, daily tidal variation is almost indistinguishable. Longer-term tidal variation (upper graph) is also difficult to identify, but during periods of steady flow, it may possibly reach 0.3–0.5 m at Ogwa. However, some of this variation could be due to small floods coming downriver rather than tidal effects.

24


3

6

2

5

1

4

0

3

-1

2

-2 1/09/1996

1/10/1996

1/11/1996

1/12/1996

1/01/1997

Elevation at FLY22 (m)

Tide Elevation (m)

DARU TIDES (MODEL) FLY22 (OGWA )

1 1/02/1997

3

6

2

5

1

4

0

3

-1

2

-2 2/12/1996

9/12/1996

16/12/1996

23/12/1996

Elevation at FLY22 (m)

Tide Elevation (m)

DARU TIDES (MODEL) FLY22 (OGWA )

1 30/12/1996

Figure 1.11: Modeled tidal variation at Daru compared with water levels at Station FLY22 (Ogwa) on the Lower Fly just downstream of Everill Junction. The upper graph shows medium-term tidal variation. The lower graph compares FLY22 water levels with individual tidal cycles over a period of low-medium river flow. The tide gauge datum is arbitrary.


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1.5. Geomorphic Changes Associated with Mining The Ok Tedi mine is located close to the headwaters of the Ok Tedi on what was formerly Mount Fubilan, although much of the mountain has now been removed (Fig. 1.12). The operation is open cut, producing an average of 83,000 tonnes/day of ore and a peak of 152,000 tonnes/day of overburden. About 80 million tonnes of waste rock and tailings are discharged into the Fly River system each year. The original mine design incorporated a tailings dam, and construction of a tailings dam began. However, the foundations collapsed in a landslide in 1984. An Interim Tailings Scheme contained tailings at start-up. Since this storage area is filled, tailings have been discharged directly to the river system (Ok Tedi Mining Ltd., 1999). The discharge of waste rock and tailings has greatly increased the sediment load of the river. While much of the waste rock consists of coarse material, about 60% of it breaks down during transport into finer material in the sand–silt size range. While the gravels are not transported beyond the middle reaches of the Ok Tedi, the finer material can pass into the Fly. Prior to mining, the natural load of the Ok Tedi at D’Albertis Junction was 3–5 Mt/ year with a similar amount coming from the Upper Fly (Higgins et al., 1987). Over the period 1985–2000, the load of the Ok Tedi has increased to an

Figure 1.12: The Ok Tedi mine and the Ok Mani in early 2004 (photo: Andrew Marshall).

26


average about 45 Mt/year. Some reaches of the river have experienced extensive deposition, raising the riverbed, adding material to levees and floodplains, and increasing water levels.

1.5.1. Mine Area Creeks Waste rock is disposed of in failing dumps on the north and south sides of the mine. These dumps feed a range of sediment sizes, from boulders to clay, into Sulphide Creek (which becomes the Ok Gilor, and then the Ok Mabiong in its lower section) and the Ok Mani. Mill tailings with a median size of about 75 mm are discharged directly into the Ok Mani downstream of the dump inputs. A summary of inputs is presented in Table 1.2. The Sulphide Creek system, on the north side of the mine, receives material from the northern dumps. This material accumulates in a steep fan at the dump toe, filling the whole valley of Sulphide Creek. The creek then enters a steep and narrow slot with waterfalls. All sediment delivered from upstream passes through this reach. Beyond the slot, a second valley-wide fan develops, extending down to the junction with the Ok Tedi. This system experienced a major landslide in 1989, adding about 125 Mt of hillslope material to the system. This is equivalent to about 80% of the waste rock dumped into Sulphide Creek between 1985 and 2000.

1.5.1.1. Ok Mani and the southern dump system The southern dumps feed Harvey Creek, a small, very steep northern tributary of the Ok Mani. The middle section of Harvey Creek is too steep to hold dumped material, so the dump toe ends abruptly in cliffs and there are several waterfalls. There is also substantial erosion and landsliding in this area, with cliff retreat of 25–50 m between November 1998 and November Table 1.2: Major sediment inputs to mine area creeks during mining operations. Location

Ok Mani Sulphide Creek

Quantity (Mt) 1985–2005 Waste rock

Tailings

Slides & erosion

292 163

490 –

190 125


27

2000 (Marshall, 2001). Beyond the waterfalls, much of the dumped material accumulates in a large alluvial fan that extends out from Harvey Creek (Fig. 1.13). This fan blocks the valley of the Ok Mani, creating a small upstream lake, and pushes the channel of the Ok Mani against its southern valley wall, causing undercutting and erosion. Below the Harvey Creek fan, the valley of the Ok Mani is filled with deposited waste rock as far as the Ok Tedi junction (Fig. 1.14). Mill tailings enter the Ok Mani downstream of the Harvey Creek fan. These mix with the waste rock, adding to both stream discharge and valley fill. Harvey Creek, which currently receives most of the waste rock, behaves as a typical alluvial fan in its lower reaches (Fig. 1.13). As material accumulates, the fan builds up, gradually increasing both its elevation and slope until the rate of transport equals the rate of removal from the fan base. The rate of removal is largely governed by the sediment transport capacity of the Ok Mani. At present, not all delivered material is being removed, so the fan base is building up, blocking the valley of the Ok Mani and diverting its channel toward its southern valley wall. This wall is presently being undercut and eroded intermittently. The Harvey Creek channel is also being pushed against its western valley wall, causing erosion.

Figure 1.13: The southern dumps and the Harvey Creek fan (photo: Barrie Bolton).

28


Figure 1.14: The Ok Mani and the middle Ok Tedi showing changes between 1979 and 2004. The behavior of the Ok Mani is typical of a river where the rate of sediment delivery exceeds transport capacity. The original concave long profile is gradually building up and becoming less concave. The bulk of deposition is occurring in the middle reaches. There is less deposition at the lower end of the system because the Ok Tedi removes most, if not all, of the delivered load from the Ok Mani and sets a local base level. 1.5.1.2. Patterns of erosion and deposition on the Ok Mani Over the period 1996–2000, the Ok Mani experienced large variations in rates of sediment delivery from the southern dump area in response to variations in rainfall, valley wall erosion, and dumping rates (Marshall, 2001). In total, 172 Mt of waste rock, 50.7 Mt of valley wall material, and 112.2 Mt of tailings entered the system, and of this, 201.7 Mt reached the Ok Mani. Figure 1.15 shows maps of the spatial pattern of erosion and deposition from digital elevation models for March 1996, March 1997, November 1998,


29

Figure 1.15: Patterns of erosion and deposition through time on the Ok Mani and the lower Harvey Creek fan. and November 2000. The pattern of erosion and deposition suggests that the Ok Mani may be divided into four reaches, each of which is separated by a reduction in valley width. These reaches are shown in Fig. 1.15 as: A–B: the toe of the Harvey Creek fan to the first valley constriction. B–C: a relatively steep and narrow valley section of fairly constant width. C–D: a section in which the valley doubles in width and then narrows again. D–E: a reach of variable width ending at the junction with the Ok Tedi. Reach A–B shows patterns largely related to sediment delivery rates from the Harvey Creek fan. When delivery is lower, the toe of the fan experiences

30


scour, but there is rapid fill at high delivery rates. There also seems to be erosion and deposition related to shifts in position of the main channels on the fan itself. Reach B–C has experienced consistent buildup over time, both during the dry period in 1997 and in the wetter period since then. This reach probably restricts supply to the reaches downstream but is likely to be increasing its slope and sediment transport capacity. Reach C–D has also experienced consistent buildup in elevation but at a lesser rate than upstream. The narrower section at the lower end of the reach probably also restricts outflow. Reach D–E is affected by the local base level imposed by the Ok Tedi. Deposition rates are lower than upstream reaches, and there was net erosion during 1997–1998. This shows that the Ok Tedi was able to remove delivered material and generate a wave of incision that progressed up the system as far as the first main valley constriction. These patterns of behavior suggest that the rate of transport through each of the reaches is a function not only of slope but also of valley width, with more rapid buildup of material in the narrow sections. It also seems that rates and locations of incision during periods of lower sediment delivery from Harvey Creek are affected by the valley width. Projecting 1996–2000 deposition rates forward for 10 years suggests a further 40–50 m of deposition in the upper Ok Mani (Sections A–B and B–C in Fig. 1.15), decreasing to about 20 m in the middle section (C–D), and to about 10 m in the D–E section. Deposition rates will be lower close to the Ok Tedi junction, which sets the local base level. Channel forms will remain similar, and there will be significant sidewall erosion, particularly in the upper reaches and in valley constrictions. The Harvey Creek fan will continue to grow upward and outward, and further significant sidewall erosion can be expected, particularly during phases when fan growth pushes watercourses against valley walls. While the general trend in both Harvey Creek and the Ok Mani is for material to accumulate, progressively over time, several other types of behavior may be expected in future: The rate of accumulation of material will decrease over time as gradients become steeper, and sediment transport capacity increases. Marshall (2001) reports a decline in sediment retention from about 40% in 1992 to 30–35% currently. The retention rate will vary with the amount and characteristics of dumped material. Higher dumping rates will result in more sediment being retained. However, this may be offset by the removal of material during periods when


31

the dumping rate is lower. As a rough guide, it may take 3–12 months for a large slug of dumped material to pass down the system to the Ok Tedi junction. Waves of erosion that may develop during times of limited dumping may take longer to propagate through the system. Rates of retention and sediment movement will vary with rainfall and stream discharge. During periods of low rainfall, dumped material may be held higher up the system, and lower reaches may scour in response to reduced supply of sediment from upstream. Nick points may also develop and travel upstream from the Ok Tedi junction. Seismic activity and landslides/debris flows will affect sediment retention rates, especially in upper parts of the system. There will be considerable local variation in erosion and deposition within the system as channels migrate laterally and are diverted by localized accumulation, particularly close to the lower reaches of the Harvey Creek fan. Individual landslides/debris flows may cause quite dramatic shifts in channel locations. The Harvey Creek fan, the Ok Mani, and the Sulphide Creek system show extreme forms of channel braiding, with up to 10 active channels operating, as waves of material pass through the system. Channels transporting high sediment loads are wide, shallow, and may experience rapid lateral shifting. Where sediment supply is reduced, flows may be confined to a single channel that may incise and develop some degree of bed armoring. The lake that is developing as the valley of the Ok Mani is blocked by the toe of the Harvey Creek fan will increase in depth and extend further upstream. There may also be periodic dam-break floods down the Ok Mani at times of high flow.

1.5.1.3. Sulphide Creek/Ok Gilor/Ok Mabiong system and the northern dumps The northern dump system received much less material than the southern dumps between the 1996 and 2000 surveys with the bulk of dumping after 1998. Marshall (2001) cites 44 Mt of waste rock and 9.7 Mt of valley wall erosion. Of this, only 0.18 Mt of material remained in Sulphide Creek and 2.55 Mt in the Ok Mabiong and the Ok Gilor. The Sulphide Creek system is much steeper than the Ok Mani. In the reach upstream of the waterfall, at the toe of the dumps (F–G in Fig. 1.16), there is a mass of material, but it is basically in transit. Most would be removed if dumping ceased. Indeed, the F–G reach shows extensive sidewall erosion as well as little potential to store waste rock. The F–G reach ends in a narrow slot with a waterfall, and all delivered material goes

32


Figure 1.16: Patterns of erosion and deposition on the Sulphide Creek system. through. Beyond that, the system has a gradient similar to the upper Ok Mani that is maintained right down to the Ok Tedi junction. This reach has experienced buildup of sediment in the section marked G–H on Fig. 1.16, possibly related to several valley constrictions. Beyond that, the reach H–J shows erosion of previously deposited material down as far as the Ok Tedi junction. Unlike the Ok Mani, which has a concave long profile, the Sulphide Creek system long profile is virtually straight downstream of the waterfall. This means that there is little capacity to store waste rock over the long term. Delivered material will accumulate over time, but it is essentially in transit, and given time, or a reduction in the rate of dumping, it will be scoured out fairly rapidly. Base level reduction due to scour on the Ok Tedi will also be transmitted up the lower reaches of the Sulphide Creek system fairly rapidly, inducing erosion. These patterns of behavior are evident in the H–J reach. The future behavior of the Sulphide Creek system will very much depend on dumping rates. The area appears to be less stable than the valley of the Ok Mani (excluding Harvey Creek) and is relatively narrow. The upper catchment appears highly unstable where forest cover has been lost. High dumping rates would induce rapid deposition, especially in constricted reaches, even though material would flush out fairly rapidly once dumping ceased. This would generate significant sidewall erosion and landsliding. The retention rate would be less than that of the Ok Mani. The lower dumping rates that prevailed between 1996 and 2000 have allowed the system to erode over much of its length and remove previously deposited material. This trend will continue at low dumping rates.


33

The waterfall at G (Fig. 1.16) is experiencing erosion and may become unstable. If so, the storage area upstream, beyond the dump toe, could be undermined.

1.5.2. Upper Ok Tedi 1.5.2.1. Deposition and river behavior The Upper Ok Tedi has a steep, concave long profile with some local irregularities, often associated with gorge constrictions and openings. Steeper sections of the river that are confined by valley walls have a single channel scoured to bedrock or lined with boulders while wider sections have braided channels with central and lateral bars. Flow is often critical or supercritical, and the river has a high sediment transport capacity. It is also capable of transporting virtually all sediment sizes delivered both from landslides and the mine. For most of its length, the river behaves as a source zone system, transporting a large quantity of delivered sediment. Some of this sediment breaks down into finer particles during transit. Most of the deposition in the Upper Ok Tedi is actually bed material in transit and can be expected to pass downstream fairly quickly, especially in the steep upper reaches. For example, the zone between the Ok Mabiong junction and the Ok Mani junction experienced net erosion in the 1996–2000 period (Marshall, 2001) in response to reduced input from the northern dump system. The lower section of the long profile is flatter, and deposits here are likely to persist for longer, with some being long term. Patterns of erosion and deposition in the Upper Ok Tedi are highly variable (see Fig. 1.5 of Pickup and Cui, 2009). Close to the Ok Mani junction, bed levels have increased by 6–8 m since 1984, but there are periods of occasional scour of 2–3 m. There is also extensive lateral erosion and deposition as the channel shifts (Moi et al., 2001). Further down the system, especially in the steeper reaches, changes in bed level are minimal. Close to the end of the gorge, the gradient becomes flatter and sediment begins to accumulate with about 4 m of deposition at its downstream end. Much of this deposition is in wider, flatter reaches, and there are still sections where deposition is limited. The Upper Ok Tedi is unlikely to experience major changes in its current behavior in the period up to 2010. Projecting current trends forward suggests another 2–4 m of deposition in some areas, but periods of scour and fill are likely, and the channel will continue to shift within the confines of its valley. Bed levels may rise locally, especially in lower reaches, or if there is a major

34


landslide in the mine area or elsewhere. There may also be some terrace and island formation in wider reaches.

1.5.3. Middle and Lower Ok Tedi 1.5.3.1. Deposition and river behavior Extensive deposition of mine-derived material has occurred in the Middle and Lower Ok Tedi. Minimum bed levels in this reach (Fig. 1.17) show little change over time, close to where the Lower Ok Tedi begins. By Ningerum, there is a bed-level rise of about 2 m, increasing to about 8 m at Konkonda, and remaining high (at about 5 m) down to D’Albertis Junction. The impact of dredging that began in March 1998 can also be seen with falls in bed level of 2–3 m at the TED25 and TED36 cross sections, which lie just upstream and downstream of the Ok Mart/Ok Tedi junction. The impact of dredging is examined in more detail below.

98 96 94 92 1980

18

TED20 NINGERUM

TED58 LOWER OK TEDI GORGE

68

Elevation (m)

Elevation (m)

100

1985

1990

1995

62

TED25 KONKONDA

1985

1990

1995

2000

TED36 NEAR D'ALBERTIS JUNCTION 16 14 Elevation (m)

Elevation (m)

64

60 1980

2000

16 14 12 10 8 6 1980

66

12 10 8 6

1985

1990

1995

2000

4 1980

1985

1990

1995

2000

Figure 1.17: Changes in minimum bed levels over time in measured cross sections from the lower end of the Ok Tedi gorge to D’Albertis Junction.


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There are three distinct patterns of river behavior within the Lower Ok Tedi: What was originally the armored zone (from the end of the Ok Tedi gorge to the former gravel front near Bige) is now a broad sand bed river with extensive central and lateral bars. Many of the former gravel islands are now partially or fully buried. In the upper section of this reach, the river is confined by Pleistocene terrace material, so its capacity to widen is limited. Further downstream, where the valley opens out, the channel has become wider, and there is extensive overbank deposition. Much of the floodplain below the confined reach is affected by rain forest dieback, although there has been some recovery since dredging commenced. The former gravel–sand transition zone (from the gravel front near Bige through the Konkonda meander to Atkamba) has remained as a single channel, but there has been major deposition on the channel bed. Water levels have risen and flow has gone through the neck of the Konkonda meander, leaving overbank deposits. Lateral shifting of the channel has been limited by indurated Pleistocene terrace material, but water levels have been high enough to stress rain forest on all but the highest terrace remnants and to cause dieback in backswamps in lower areas between the terrace remnants. The floodplain below Atkamba contains few terrace remnants, and the river is able to migrate laterally. It is also affected by backwater from the Middle Fly. There has been major deposition on the channel bed, overbank deposition, lateral shifting of channel cross sections, and one meander cutoff. Some meander cutoffs that predate the mining operation are now being used as floodwater channels and are filling with sediment. A large bar has formed just upstream of D’Albertis Junction that is currently diverting flow to the east across the floodplain into the Upper Fly. This reach shows extensive forest dieback.

1.5.3.2. Impact of dredging Future behavior of the Lower Ok Tedi largely depends on whether current dredging operation continues. Without dredging, the pre-1998 trends would continue, suggesting perhaps 2 m of additional deposition in the upper section near Ningerum, rising to 4–6 m in the riverbed at Konkonda and 2–4 m in the reach between Atkamba and D’Albertis Junction by 2010. This would mean: Channel widening throughout the reach upstream of the Konkonda meander. Extensive floodplain deposition in that reach but especially around Bige.

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Possible cutoff of the Konkonda meander. Continued high and probably rising water levels (subject to no change in present rainfall conditions). Continuing forest dieback throughout the reach. Active meandering, floodplain deposition, and possible changes in river course between Atkamba and D’Albertis Junction. Evidence from cross section surveys suggests that dredging has slowed, halted, or begun to reverse some of these effects but not everywhere in the Lower Ok Tedi. In the dredge slot itself and upstream, bed levels have been reduced by about 1 m between the 1997 and 2000 cross section surveys. Immediately downstream of the dredge, there is a short zone of deposition. This is common in dredging operations and develops as material thrown into suspension by the dredging operation settles on the bed once more. In the former gravel–sand transition zone between Bige and Atkamba, average bed levels have been reduced by about 1 m between 1997 and 2000. Between D’Albertis Junction and Atkamba, bed levels have fluctuated, and there is both erosion and deposition, with the deposition concentrated close to the junction with the Fly.

1.5.4. Middle Fly River 1.5.4.1. Major trends in river behavior Several physical changes have occurred in this reach of the river since waste rock and tailings have been discharged into the Upper Ok Tedi. These include: A gradual increase in bed elevation or partial constriction of the channel by enlarged point bars or other lateral deposits in the upper reaches of the Middle Fly. A substantial increase in levee elevation that either began, or has accelerated, with the increase in rainfall after the 1997 El Ninõ drought. An increase in the rate of meander migration in some reaches of the river. Blocking of tie channels to some off-channel water bodies. Higher water levels in the period after the 1997 El Ninõ drought. Backup of the lower reaches of the Upper Fly, resulting in higher water levels. Possible increase in the size of riverbed sediments. Very rapid weathering of material deposited in levees.


37

The increase in bed elevation and partial channel constriction can be seen in Fig. 1.18. It is most severe in the upper reaches of the river with losses of more than 1,000 m2 of channel capacity at Kuambit and Niukamba, declining to about 750 m2 at Wygerin. Further downstream, the effect is minor, with no obvious changes at Mabaduan and only minor rates of decline at Bosset and Manda. This may be because backwater effects from the Strickland and tidal effects in the delta limit downstream transport and, therefore, prevent the coarser fractions of both mine-derived and natural sediment on the bed from reaching this far downstream. The location of, and downstream decline in the amount of channel filling/constriction suggests a mine-related impact. However, there is also substantial short-term variability about the central trend that may be due to variations in flow, such as scour during floods and fill during low flows, and localized scour and fill as large bars move through the system. There may also be some measurement error, given the difficulties of depth measurement using sounding weights in deep, fast-flowing rivers.

1.5.4.2. Bed-level changes since 1997 On first inspection, the long-term trends in channel area (Fig. 1.18) point to a mass of deposition moving gradually downstream. However, there is considerable local variation over time, and the deposition is not a clear-cut feature. The long-term cross section survey network is also very sparse, considering the complexity of the Middle Fly. A more densely spaced network of cross sections has been surveyed since 1997. Patterns are beginning to emerge (Fig. 1.19), and these may be used to make some rough estimates of future behavior on the Middle Fly. The upper graph of Fig. 1.19 shows the trend from December 1997 to March 2002. This period spans a time of river readjustment after the 1997 drought, a period of high flows, and a period with closer-to-average flows. Clear trends may be partially masked by this variability in hydrologic conditions. The pattern of bed-level change shows channel scour in the dredge slot gradually decreasing downstream until deposition begins in the backwater-affected reach of the Lower Ok Tedi. On the Middle Fly, there is deposition down to the start of the backwater zone close to the 180 km point and then substantial fluctuations in bed level. If the survey data are divided into El Ninõ/wet period conditions and closer-to-average flow conditions, two different patterns emerge. Between 1997 and 1999, sediment supply to the Middle Fly was reduced by low flows in the Ok Tedi and interruptions to mine operations. A wet period

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immediately followed the El Ninõ. In this phase, the middle graph of Fig. 1.19 shows that scour associated with dredging occurred at the upstream end of the Lower Ok Tedi, but there was deposition closer to D’Albertis Junction. Scour occurred on the upper Middle Fly as the sediment supply from upstream was reduced. The scoured material then moved down to the upper end of the backwater zone where it seems to have lodged. With a return to more average conditions (lower graph of Fig. 1.19), the main wave of deposition stays in the upper Middle Fly and ends close to the 300 km point. A second, smaller wave of deposition occurs in the lowest 100 km of the river. This deposition gradually increases downstream until it is truncated upstream of Everill Junction, presumably by periodic drawdown and increased velocities associated with low tide and low water on the Strickland.

1.5.4.3. Changes to banks and levees Channel cross section surveys carried out between 1997 and 2002 (Marshall, 2002) show that levee heights have increased over much of the Middle Fly, and many of the low points have been filled in. The process may have been occurring earlier, but there are not enough measured cross sections in the database to demonstrate this. While there is much variation between cross sections (Fig. 1.20), the regression lines suggest a rise of about 1 m over the whole of the Middle Fly from Everill Junction to D’Albertis Junction. This means that many levee breaches connecting the floodplain surface to the channel are now blocked. It is also likely that tie channels to off-channel water bodies are being blocked more frequently and for longer periods. Field inspection shows that much of the sediment is very fresh, and it often occurs unconformably on top of much older bank material. This implies an unusually rapid period of levee buildup. The increase in levee heights may be attributed to: Rising bed levels (and therefore floodwater levels) in the upper part of the Middle Fly, associated with the deposition of mine-related sediments. Higher water levels associated with the increase in rainfall since 1997. Increased suspended sediment concentrations, making more material available for deposition once flow velocities decrease at the floodplain– channel boundary. There does not seem to be any downstream decline in the rate of levee construction. Indeed, it may be slightly greater in the backwater zone of the Middle Fly.


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Figure 1.20: Levee top elevations between D’Albertis Junction and Ogwa, 1997–2002. 1.5.4.4. Changes in water levels The effect of deposition on water levels in the Middle Fly is shown in Fig. 1.21. At Kuambit, mean daily values have increased by about 3 m, with most of the changes occurring since 1992. Minimum values have also increased, as would be expected with rising bed levels. Some of the increase in water level is related to the higher rainfalls since 1997, but the upward trend was apparent before that. Fewer data are available for Manda at the upstream end of the backwater zone, but a weak upward trend in water level seems to be present. Water levels alone make it difficult to say when this trend began, and there is a case for relating it to the higher rainfalls after 1997. Water levels on the Upper Fly River have been high since the 1997 drought and associated with dieback of rain forest along the floodplain and backed up tributary drainage basins. The dieback is extensive along the reach between D’Albertis Junction and Kiunga, where the river is subject to backwater from the Middle Fly. There has been some debate over whether high water levels in this part of the river are the result of downstream deposition of mining waste, higher rainfalls since the 1997 drought, or both. Cross section surveys show that there is little deposition in the Upper Fly except very close to D’Albertis

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Figure 1.21: Daily water levels for Middle Fly gauging stations. Junction, so the dieback is not the result of local changes in the channel in the reach upstream toward Kiunga. The record of water levels for the Upper Fly at Kiunga (Fig. 1.22) provides useful evidence suggesting that: The consistently high water levels since 1997 have no parallel in the record of the last 30 years at Kiunga. Not only has the average level remained high, but also there have been fewer periods of low water than in the past. The 1997 drought and the period of higher minimum water levels that followed it bear some similarities to the drought of 1972. However, after 1972, although water levels were high, the river fell to low levels much more frequently. The density of points at high water levels seems to increase from about 1994 or 1995. This precedes the change in rainfall, strongly suggesting that the underlying cause of the high levels is not a climatic shift. 1.5.4.5. Deposition and tie channel blocking Tie channels are long-term features in the landscape and largely selfsustaining. Indeed, virtually all recent meander cutoffs maintain a tie channel


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Figure 1.23: An abandoned tie channel on the Middle Fly. The tie channel has ceased to operate because flow from a blocked valley tributary has entered the cutoff and overflowed down the swale behind the old levee on the right-hand side of the cutoff. This has opened a path to the river and created a new tie channel. A delta has formed where the tributary crosses the cutoff.


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While there is plenty of evidence that deposition rates in cutoffs and other ORWBs have increased, reports of tie channel blocking are less clear. Some tie channels have become blocked to small boats but have subsequently cleared. This may be a cyclic process whereby sediment is deposited in tie channels during periods of extensive flooding (e.g., the 2000 La Ninã event) when both river and ORWB water levels remain high and water surface slopes between the two are low. The sediment then clears when river heights become more variable and tie channel water surface slopes and flow velocities become greater. Perhaps the best known case of a blocked tie channel is the one at Pangua on the lower Middle Fly, which seems to have become blocked during the extended flooding of 1999–2000. Figure 1.24 shows how this may have occurred. In the 1998 image, the tie channel can be seen connecting the southern end of the cutoff closest to the channel. During 1999 or 2000, much of this area remained inundated, and there was 0.5–1 m of deposition on the main channel levees. It is likely that this deposition also blocked the tie channel entrance, which was not regularly scoured out because of continuously high water. High water levels and backwater from the Strickland forced some of the floodwater out of the Middle Fly, and a major flood path developed through backswamps on the western edge of the floodplain over a distance of about 30 km. Flow down this flood path was far greater than the amount the Pangua tie channel could handle even if it had remained open. Instead, a whole series of breaches were cut through the levee, and some of these have remained open since then, replacing the original tie channel. More evidence that the principal cause of natural cutoff tie channel blockage is lack of flow comes from the maps of tie channels and ORWBs in Pickup (2006). Most upper Middle Fly meander cutoffs have tie channels linking them to the main river. However, in the backwater zone of the Middle Fly, water level variation has greatly decreased as Strickland water levels have risen over several thousand years. The area now remains flooded for much of the time. Many of the backwater zone cutoffs now have no obvious active tie channels. The major difference between the upper and lower Middle Fly is water level variability (Fig. 1.22). Tie channel inflows and outflows have therefore decreased to the point that active channels can no longer be maintained in many cases. The foregoing discussion shows that tie channels are self-forming and, once developed, are a largely self-sustaining feature of the landscape. While they may be subject to occasional blocking by sediment during high flows, they can also reopen when fluctuating river levels create large differences between the main river and the connected ORWB. Rapid, sediment-scouring

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Figure 1.24: The Pangua tie channel. The upper PACRIM 2000 Synthetic Aperture Radar image shows the major floodway that developed through backswamps on the western margin of the Middle Fly floodplain. The lower two images show how a meander cutoff tie channel had been replaced by broader multiple-levee breaches by February 2000.


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flows then occur in both directions along the tie channel. Tie channels only seem to become permanently blocked under natural conditions when their water supply is removed or reduced. Many of the tie channels that are connected to large ORWBs are unlikely to become blocked because enough water flows through them to maintain an opening. Connections with smaller ORWBs are more likely to be subject to intermittent blockages because of increased sediment concentration in the Fly. Levee breach channels may be particularly affected because of recently increased levee deposition. However, they may be replaced by outflows through other low points in the levee. The main threat to all upper Middle Fly tie channels comes from rising water levels in response to deposition on the bed of the main river channel. Until the early 1990s, water levels on the upper Middle Fly fluctuated rapidly and covered a range of about 12 m. From about 1999 onward, the range has decreased and, for most of the time, is 6 m or less. This means that there is less scouring of tie channels because flow velocities are reduced. Also, local base levels, which are set by main river flow heights and govern tie channel depth, have risen. Taken together, these two processes will mean smaller and shallower tie channels. It is also likely to occur along the whole length of cutoff tie channels. The larger tributary tie channels will be less affected but could show some shallowing close to the river. Predictions of deposition and water level rise (see Pickup and Cui, 2009) show that a wave of deposition and water level increase will move down the Middle Fly over the next 40–50 years. The reduction in water level variation at Kuambit will affect much of the upper Middle Fly, although it will decrease in intensity downstream. The backwater zone of the Middle Fly will also experience higher water levels, but flow variability will still be largely determined by the Strickland. Overall, this means less scouring potential in tie channels but more overbank connections between the Fly and its floodplain.

REFERENCES Barr Engineering Company (1995). Investigation of the effect of mine tailings on meander rate of the Fly River. Report to Ok Tedi Mining Ltd. Blake, D. H., & Ollier, C. D. (1971). Alluvial plains of the Fly River, Papua. Zeitschrift fur Geomorphologie, Supplementband, 12, 1–17. Blong, R. J. (1991). The magnitude and frequency of large landslides in the Ok Tedi catchment. Report to Ok Tedi Mining Ltd. Day, G. M., Dietrich, W. E., Apte, S. C., Batley, G. E., & Markham, A. J. (1993). The fate of mine-derived sediments deposited on the middle Fly River

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flood-plain of Papua New Guinea. In: R. J. Allen, & J. O. Nriaugu (Eds). International Conference on Heavy Metals in the Environment, Vol. 1. CEP Consultants Ltd, Edinburgh, pp. 423–426. Dietrich, W. E. (2000). Quarterly and fourth monthly report – Middle Fly Sedimentation Project. Ok Tedi Mining Ltd. and University of California, Berkeley. Dietrich, W. E., & Day, G. (2004). Rates and patterns of floodplain sedimentation, middle Fly floodplain (1985–1994). Presentation at the Sediment Transport Model Workshop, Cairns, Australia, January 2004. Environment Department, OK Tedi Mining Ltd. Dietrich, W. E., Day, G., & Parker, G. (1999). The Fly River, Papua New Guinea: Inferences about river dynamics, floodplain sedimentation and fate of sediment. In: A. Miller, & A. Gupta (Eds). Varieties of Fluvial Form. Wiley, New York, pp. 345–376. Harris, P. T., Baker, E. K., Cole, A. R., & Short, A. S. (1993). A preliminary study of sedimentation in the tidally dominated Fly River Delta, Gulf of Papua. Continental Shelf Research, 13, 441–472. Higgins, R. J., Pickup, G., & Cloke, P. S. (1987). Estimating the transport and deposition of mining waste at Ok Tedi. In: C. R. Thorne, J. C. Bathurst, & R. D. Hey (Eds). Sediment Transport in Gravel Bed Rivers. Wiley, Chichester, pp. 949–976. Loffler, E. (1977). Geomorphology of Papua New Guinea. ANU Press, Canberra. Marshall, A. R. (2001). Upper Ok Tedi sediment storage analysis – November 2000. Environment Department, Ok Tedi Mining Ltd. Marshall, A. R. (2002). Ok Tedi–Middle Fly bed aggradation survey. Epoch 6 – March 2002. Environment Department, Ok Tedi Mining Ltd. (and associated spreadsheets). McAlpine, J. R., Keig, G., & Short, K. (1975). Climatic tables for Papua New Guinea. CSIRO Division of Land Use Research Technical Paper 37. Moi, A. S., Dremdap, T., & Simbina, P. (2001). APL compliance and additional monitoring program. 1999/2000 Annual Report. Appendix 1 – Hydrology. Report ENV01-02, Environment Department, Ok Tedi Mining Ltd. Ok Tedi Mining Ltd. (1999). Community and environment programs. Paijmans, K., Blake, D. H., Bleeker, P., & McAlpine, J. R. (1971). Land resources of the Morehead-Kiunga area, territory of Papua New Guinea. CSIRO Land Research Series 29. Pickup, G. (1984). Geomorphology of tropical rivers. 1. Landforms, hydrology and sedimentation on the Fly and lower Purari, Papua New Guinea. Catena Supplement, 5, 19–41. Pickup, G. (2006). Comments on a possible program for maintaining tie channel openings by hydraulic cleaning. Report to Environment Section, Ok Tedi Mining Ltd. Pickup, G. (2009). Floodplain inundation modeling and forecasting for the Middle Fly. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 291–318.


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Pickup, G., & Cui, Y. (2009). Modeling the impact of tailings and waste rock disposal on the Fly River system. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 257–289. Pickup, G., Higgins, R. J., & Warner, R. F. (1979). Impact of Waste Rock Disposal from the Proposed Ok Tedi Mine on the Fly River and its Tributaries. Department of Minerals and Energy and Office of Environment and Conservation, Papua New Guinea. Rowland, J. C., & Dietrich, W. E. (2006). The evolution of a tie channel. In: G. Parker & M. Garcia (Eds). River Coastal and Estuarine Morphodynamics: RCEM 2005, Vol. 2. Taylor & Francis/Balkema, London, pp. 725–736. In: Proceedings of the 4th IAHR Symposium on River, Coastal and Estuarine Morphodynamics. Rowland, J. C., Lepper, K., Dietrich, W. E., Wilson, C., & Sheldon, R. (2005). Tie channel sedimentation rates, oxbow formation age, and channel migration rate from optically stimulated luminescence (OSL) analysis of floodplain deposits. Earth Surface Processes and Landforms, 30(9), 1161–1179. Wolanski, E., & Eagle, A. M. (1991). Oceanography and sediment transport, Fly River estuary and Gulf of Papua. 10th Australasian Conference on Coastal and Ocean Engineering, Auckland, New Zealand.


Chapter 2

Texture, Geochemistry, and Mineralogy of Sediments of the Fly River System Barrie R. Bolton, Jesse L. Pile and Henry Kundapen Environment Department, Ok Tedi Mining Limited, PO Box 1, Tabubil, W.P., Papua New Guinea

2.1. Introduction In May 1984 mining began at the Mount Fubilan copper and gold mine located in the remote Star Mountains of western Papua New Guinea (PNG) (Fig. 2.1). The mine, which is owned and operated by Ok Tedi Mining Limited (OTML), commenced operations with a 24,000 tpd gold plant that has since been expanded to a 90,000 tpd copper plant. Waste materials from mining operations, at present comprising approximately 55 Mt of overburden and 30 Mt of tailings, are discharged annually into the headwaters of mine area creeks where erosion and sediment transport processes carry significant proportions of the total waste produced into the Ok Tedi and Fly River system. The potential for adverse impacts to the fluvial environments downstream of the mine resulting from these waste materials has been of concern since before the start of mining. These impacts include the release of copper and other metals from these sediments and their toxicity to aquatic organisms (Apte, 2009) and riverbed aggradation and its potential to cause an increase in the frequency and duration of floodplain inundation (Pickup, and Pickup and Cui, 2009). In response to these concerns OTML has commissioned numerous studies and ongoing monitoring of a range

Corresponding author. Tel.: +61-3-9769-6099; Fax: +61-3-9769-6099;

E-mail: [email protected] (B.R. Bolton).

Figure 2.1: Maps showing the location of the Fly River System in western PNG (A) and drainage around the Mount Fubilan (Ok Tedi) mine (B).

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of environmental parameters throughout the river system to assess the extent and nature of these impacts. This chapter examines the temporal and spatial impact of these mine waste materials on the texture, geochemistry, and mineralogy of the sediments deposited in the channel and on the banks of the downstream riverine environment, from the mine to the Fly River delta. We also present information on the distribution of heavy minerals in the river system and discuss the implications of these data for the potential for the development of environmental issues such as acid rock drainage (ARD).

2.2. Texture of River Sediments This section describes how bed and bank sediment textural characteristics have changed in the Ok Tedi and Fly River system as a result of mining at Mount Fubilan, in terms of sediment particle size, sediment type, and the degree of sorting that has occurred.

2.2.1. Before Mining An extensive investigation of river behavior and sediment characteristics was undertaken prior to mining and is reported by Pickup et al. (1979), Pickup (1984), and Higgins et al. (1987). The following description draws heavily on these works as well as the detailed description of the geomorphology, hydrology, and climate of the Fly River system provided elsewhere in this volume (Pickup and Marshall, 2009). Before mining began in 1984, the steep, fast-flowing streams draining Mount Fubilan at the headwaters of the Ok Tedi (Fig. 2.1) displayed many of the features typical of source-area streams including narrow bed-rock and coarse-grained channels lying within steep valley walls with the river largely occupying the entire valley floor at peak discharges (Fig. 2.2A) (Pickup and Marshall, 2009). These streams, known locally as the mine area creeks, comprise Harvey Creek and Ok Mani, to the south of the mine and Sulfide Creek, Ok Gilor, and Ok Mabiong to the north (Fig. 2.1). Together they form part of a ‘‘supply’’ zone in which mine-derived materials, along with natural sediments, are delivered to the river system through a range of processes including massive landslides and debris flows. One such landslide that occurred about 8,800 BP from the Hindenburg Wall, a limestone escarpment

54 B. R. Bolton et al.

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Figure 2.2: (A) Upper Ok Tedi at Bukrumdaing. Note the steep valley walls and coarse-bedded river channel. (B) Aerial view looking west up Ok Mani toward the mine (upper right). (C) Poorly sorted, massive debris flow deposits typical of upper reaches of mine area creeks. Section seen here is just over 1 m thick. (D) Gravel-bedded chute typical of armored zone of Ok Tedi about 70 km downstream of the mine. (E) Alternating massive, poorly sorted gravels and cross-bedded sands typical of the gravel–sand transition zone of upper Ok Tedi after the start of mining. Note the presence of dark-colored sulfide-rich laminae partially oxidized in places to form reddish colored secondary reaction products. (F) Lateral gravel-sand bars in upper Ok Tedi located approximately 45 km downstream of the mine. Note the gravel deposits adjacent to the active channel and more distal sand deposits characterized in part by elongate, darker colored heavy mineral segregations.


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300–1,000 m in height, resulted in the addition of an estimated 7 km3 of material into the headwaters of the Ok Tedi system (Blong, 1991). The transport capacities of the streams in this part of the system typically exceeded supply and therefore stream beds were generally either covered by a thin bed of sediment ranging in size from boulders to silts and clays, or clean bed rock was exposed. The grain size, sediment type, and sorting characteristics of material from this zone are well illustrated in Figs. 2.3, 2.4, and 2.5. The supply zone is represented on Fig. 2.3A by samples collected within 15 km of the mine and has a median (d50) particle size of less than 1 mm but a d90 particle size of almost 100 mm. Sediment types present in this zone include medium sand (up to 50%) and lesser amounts of gravel (up to 35%) (Fig. 2.3A). Figure 2.5(A–E) illustrates the bimodal distribution of these sediments with finer material typically filling the interstices of accompanying gravels. Furthermore, sediments in this zone, which mostly occurred as a series of channel bar deposits, typically fluctuated widely in grain size distribution with time, as shown in Fig. 2.5A and E, as material was transported downstream. The supply reach passed downstream into a zone referred to by Pickup and Marshall (2009) as the ‘‘armored’’ zone. The moderate-to-well-sorted coarse gravels characteristic of this zone formed a distinctive protective pavement or ‘‘armor’’ over finer grained sands (see Bar 2, Fig. 2.5A, B, and C). In the Ok Tedi/Fly system before mining began, the armored zone was located about 50–110 km downstream of the mine. Further downstream the river entered a reach characterized by a mixed sand/gravel bed referred to by Pickup (2009) as the ‘‘gravel–sand transition zone.’’ Located 110–160 km downstream of the mine, grain size in this zone fluctuated widely (Fig. 2.3A), as did the degree of sorting (e.g., Fig. 2.5D). At some sampling localities in this zone sediments displayed bimodal size distribution patterns (e.g., Fig. 2.5A, Bars 4, 5, and 6), while elsewhere sediments were well sorted and composed of either sand (e.g., Fig. 2.5D, site 64) or coarse gravels, such as at site 6 (Fig. 2.5A), in the lower part of the Ok Tedi. Figure 2.5A shows grain size distribution curves for samples collected in June 1981 for the supply, armored, and gravel–sand transition zones. This shows that generally there is very little sediment in the size range 1–10 mm at sites within these reaches, as observed previously by others (Maunsell and Partners, 1982; Higgins et al., 1987). Sediments in this size range are infrequent in most fluvial deposits and probably reflect a tendency for gravels, which may contain a range of minerals, to break down into sizes more closely related to the size of the individual constituent minerals (Pickup, pers. comm.). Furthermore, Fig. 2.5E shows the distribution of

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Figure 2.3: Downstream variation in size of riverbed material below the Mount Fubilan mine. (A) Pre-mine (Pickup et al., 1979; Maunsell and Partners, 1982; OTML, 1986) and (B) for period 2001–2003, after the start of mining operations (OTML, 2004). Symbols d50 and d90 describe median grain size and the size for which 50 and 90% of the bed is finer, respectively.

Figure 2.4: Downstream variation in grain size distribution. (A) Bed samples collected before the start of mining operations (Pickup et al., 1979; Maunsell and Partners, 1982; OTML, 1986); (B) bed samples collected in 2001–2003 during mining operations (OTML, 2004); (C) bank samples collected before mining (Pickup et al., 1979); (D) bank samples collected in 2003 (OTML, 2004). Vertical arrows at top of plots mark confluence with major tributaries. Note change in horizontal scale.

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10

0 0.01

60 50 40 30

Bar 2

Bar 3

100.00

Bar 4

Bar 5

1000.00 Bar 6

Upper Middle Fly (Upstream of D'albertis Junction: 0 - 38 km)

60 50 40 30

20

20

10

Sand Only (< 15 mm) - June 1981

0 0.01

0.10

1.00

10.00

100.00

10

Bar 1

Bar 2

Bar 3

0 0.01

1000.00

0.10

F

Particle Size (mm)

B

Bar 4

Bar 5

S1 ( 0 km) S5 (24 km)

Bar 6

1.00 10.00 Particle Size (mm) S2 (6 km) S3 (12 km) S6 (33 km) S7 (38 km)

100.00 S4 (17 km)

100

100 90

Coarse Only (>15 mm) - June 1981 80

80 70 Percent finer


January 1984 (Pre-mine)

90 Percent Passing Sieve Size (%)


100

60 50 40

60 Upper Middle Fly (44 - 225 km)

40

30 20

20 10 0 0.01

0.10


C Bar 2

Bar 3

0 0.01

1000.00

0.10

G

Bar 4

Bar 5

S9 (51 km) S17 (152 km)

Bar 6

100

100

90

90

80

80

70

70 Percent finer


Bar 1

100.00

60 50 40

1.00 10.00 Particle Size (mm) S11 (70 km) T10 (107 km) S18 (162 km) S22 (225 km)

60 50 Lower Middle Fly 'Backwater Zone' (308 - 456 km)

40 30

30

100.00 S15 (127 km)

20

20 Lower Ok Tedi - 1979

10 0 0.01

0.10

D 41 64

42.5 64.5

1.00 Particle Size (mm) 44

46

10.00

10 0 0.01

100.00 H

54.5

62.5

S28 (308km) S33 (386km)

0.10

1.00 Particle Size (mm) S29 (323 km) S34 (400 km)

10.00

S30 (335km) S37 (456km)

100.00 S32 (370 km)

Figure 2.5: Bed material size distributions for Ok Tedi and Fly River before the start of mining (Pickup et al., 1979; Maunsell and Partners, 1982; OTML, 1986).


59

grain size for the same six bars in January 1984, again before the start of mining. This plot shows a significant decrease in the amount of finer grained material (up to 10%) and near-uniform median sizes through the entire length of the upper Ok Tedi. The gravel–sand transition zone passed in turn downstream into a long reach dominated by a sand bed – the ‘‘sand zone’’ of Pickup (1984). Premine, the sand zone extended from the midway down the Ok Tedi to about midway down the Fly River. Sediments deposited on the bed of the river along this reach are dominantly composed of medium–fine sands with lesser amounts of silts and clays (Figs. 2.3A, 2.4A, and 2.5D). Figure 2.6 shows in detail the variation in grain size of both bed and bank material from the Fly River between Kiunga and Everill Junction together with regression analyses of grain size against distance for pre-mine data collected by Pickup et al. (1979). In general, grain size decreases in the bed with increasing distance downstream (as evidenced by the slope of the regression line), while the correlation coefficient of 0.60 for the d50 highlights the significant amount of variability in the data. It also shows local areas of coarser-grained sediment deposition, such as at 335 km, where the upper 10% of bed material approaches 0.6 mm or coarse sand when very little material of this size was found downstream of D’Albertis Junction at 41 km (Pickup et al., 1979). Figure 2.6A also shows a significant decrease in grain size, as reflected in both the d50 and d90 curves, between about 270 and 415 km, with the exception of the coarse-grained sampled at 335 km, noted above. The sorting characteristics of sediments deposited in the sand zone are illustrated in Fig. 2.5G. This figure indicates that sediments are in general well sorted (as evidenced by the steepness of the distribution curve), differ little in the degree of sorting downstream, and vary somewhat in median grain size from 0.09 to 0.3 mm, as shown by the spread of distribution curves along the 50% finer horizontal line. Still further downstream the median grain size abruptly decreases to the lowest values seen anywhere in the system, particularly between about 430 and 600 km downstream of the mine (280–452 km downstream of Kiunga) (Figs. 2.3A and 2.6A). Sediments in this reach are composed of a mixture of well-sorted fine sands and finer-grained silts and clays (Fig. 2.4A). Grain size distribution plots for this reach show two distinct sets of curves representing the two size classes and suggest the presence of alternating sand and silt/clay beds in channel deposits which formed in response to changing flow conditions (Fig. 2.5H). Pickup et al. (1979), Pickup (1984), and Higgins et al. (1987) referred to this zone as the ‘‘backwater zone.’’ Textural data in the pre-mine period for the Fly River downstream of Everill Junction are rare. Spencer (1974), in a study mainly devoted to

0.70

0.35 Bank Material - 1979 0.30

y = -0.0005x + 0.293 R2 = 0.6076 d90

0.40 0.30 0.20 0.10

d90

0.25 0.20

d90

y = -0.0002x + 0.1601 R2 = 0.1801

d50

y = -0.0001x + 0.0682 R2 = 0.3613

0.15 0.10 0.05

d50

d50

0.00

0.00 0

100

A

200

300

400

500

0

100

B

Distance downstream from Kiunga, km

0.70

200

300

d90 d90

0.50

d50

Bank Material - 2003

y = -0.0007x + 0.4221 R2 = 0.5151 y = -0.0004x + 0.2337 R2 = 0.6325

0.40 0.30 0.20 0.10

0.30 Particle size, mm

0.60 Particle size, mm

500

0.35 Bed Material - 2003

d90

0.25 0.20

y = -0.0002x + 0.153 R2 = 0.2191

d50

y = -0.0002x + 0.0952 R2 = 0.2945

0.10 0.05

0.00

d90

0.15

d50

d50

0.00 0

C

400


100

200

300

400


500

0 D

100

200

300

400

500

Distance downsream from Kiunga, km

Figure 2.6: Downstream variation in particle size from Kiunga on the Upper Fly River to Everill Junction. (A) Pre-mine bed material from Fly River (Pickup et al., 1979); (B) pre-mine bank material from Fly River (Pickup et al., 1979); (C) bed material from Fly River collected in May 2003 (OTML, 2003, 2004); (D) bank material from Fly River collected in May 2003 (OTML, 2003b, 2004). Symbols d50 and d90 designate median grain size and the size for which 50% and 90% of the bed is finer, respectively.

B. R. Bolton et al.

Particle size, mm

d50

0.50

Bed Material - 1979

60

0.60

y = -0.0007x + 0.4831 R2 = 0.5895

Particle size, mm

d90


61

understanding the sedimentation history of the Fly River delta, reported on the results of 16 riverbed samples taken from the Fly and Strickland Rivers. Spencer noted that the single sample from the bed of the Strickland was slightly coarser (fine to very fine sand) than those samples collected from the bed of the lower Middle Fly (upstream of Everill Junction) and that grain size initially increased in the Fly downstream of Everill Junction in response to the larger sediment load in the Strickland before fining again toward the delta (Spencer, 1974) (Table 2.4). Similar findings were also reported by (Everett and Associates, 1980) based on four samples collected from the riverbed downstream of Everill Junction. We know of no grain size data for the banks of the Ok Tedi; however, Pickup et al. (1979) provide a comprehensive data set for sediments deposited on the levees of the Fly River between Kiunga and Everill Junction. These workers noted that the grain size of material collected from the top of the river bank is considerably smaller than from the adjacent channel bed and that grain size generally decreases downstream (Fig. 2.6B). They also noted that bank top material shows marked variability in size (d50 of 0.01–0.1 mm; d90 of 0.06–0.15 mm) through the first 250 km then progressively fines but with much less variability (d50 of 0.01–0.02 mm; d90 of 0.06–0.15) over the remaining 200 km down to Everill Junction. Figure 2.4C shows the sediment types for the bank material from Kiunga to Everill Junction before mining began (Pickup et al., 1979). This plot shows that in the upper 270 km the bank is mostly composed of clays and silts (26–91%) alternating with fine sand (9–74%). Coarser material occurs only spasmodically and mainly comprises medium sand which, as seen on this plot, was recorded over the first 17 km and then at locations 51 km (18%), 103 km (4%), 127 km (9%), 203 km (6% medium sand and 4% coarse sand), and 225 km (27%) downstream of Kiunga. From 270 km to Everill Junction (452 km) clays and silts dominate with fine sand relatively steady at around 15%. 2.2.2. After the Start of Mining The grain size and grain size distribution of sediments in both the channel bed and on the levees of the Ok Tedi and Fly River is a function of the following: (1) source material characteristics; (2) distance from source; and (3) river energy. In general terms, faster flowing waters transport all sizes but the finer material passes through as wash load and is rarely present in bed material in large quantity. In contrast, finer grained material tends to be deposited in quieter water. The degree of sorting, another important measure

62

B. R. Bolton et al.

frequently used in describing sediment characteristics, reflects what is supplied from upstream and the competence of the flow to transport sediment. Assuming that all size fractions are supplied, the upper-size limit is set as the maximum size the flow can transport. The lower limit is determined by the washload/suspended bed material load cutoff. This is a function of the river’s energy and sediment particle fall velocity. Fall velocity is largely determined by sediment size, shape, and density. The sediment presently found in the channel beds and levees of the Ok Tedi and Fly Rivers is derived from a number of sources: (1) reworked bed and bank material; (2) material eroded from late Pleistocene and Holocene terraces cut by the active river channel; (3) material supplied from presentday erosion of the upland catchment areas particularly by major tributaries such as the Ok Tedi and Strickland River; and (4) mine wastes discharged from the Mount Fubilan copper-gold mine located in the headwaters of the Ok Tedi. Since the start of mining OTML has monitored sediment grain size, in both the Ok Tedi and Fly Rivers, to assess the impact of waste materials released from the mine on the downstream fluvial environment (e.g., OTML, 1986, 1997, 2000, 2001, 2002, 2003a, 2003b, 2004). Figures 2.3, 2.4, and 2.6 summarize the results of selected parts of this work as a basis for comparison with pre-mine conditions. With the riverine deposition of mine wastes, the mine area creeks changed rapidly from those typical of source-area streams to streams in which sediment supply clearly exceeds the transport capacity. Rather than being mostly swept clean of sediment, as was characteristic during pre-mine times, sediment, now unable to be transported downstream, was deposited resulting in bed aggradation. It has been estimated that between 30 and 35% of all material entering the southern mine area creeks is retained and that bed levels have increased up to 70 m or more in their headwaters close to the mine (Marshall, 2000, 2003). Marshall (2000) estimated that up to November 2000 in excess of 200 Mt of mine waste materials had accumulated in the Harvey Creek–Ok Mani network and that new material was being added at an annualized rate of around 25 Mt and that approximately 66 Mt is delivered to the upper reaches of the Ok Tedi, each year. The material now being deposited in the mine area creeks is coarse-grained with a median grain size generally between 40 and 60 mm while the d90 is consistently close to 100 mm (Fig. 2.3B). These sediments are mainly composed of coarse sands (typically 50%) with lesser amounts of gravel and finer fractions (Fig. 2.4B). They are also poorly sorted and in most cases show bimodal size distributions with finer sands infilling intergranular spaces in gravels (Fig. 2.6A and B). Exposed deposits in this area reveal a sediment


63

profile that is typically massive and largely devoid of internal structure (Fig. 2.2C). These features are typical of fluvial environments where deposition is rapid and subject to mass-flow processes. The sediments delivered to, and deposited in, the upper reaches of the Ok Tedi continue to be mainly coarse grained with median sizes in excess of 40 mm, for at least the first 100 km downstream of the mine (Fig. 2.3B). While sediments deposited in this reach are comparable to pre-mine sediments in terms of grain size, a well-defined armored zone is present but only to a minor extent (Fig. 2.2D). Near absent also is the gravel–sand transition zone of pre-mine times. As shown in Fig. 2.4B, at around 100 km downstream from the mine the composition of the bed changes abruptly from coarse sand and gravels to being almost entirely composed of medium to fine sands and silts. This change in the nature of these sediments is also reflected in the sorting characteristics, as shown in Fig. 2.6(C–E). This figure shows a transition from bimodal sediments typical of the upper reaches of the Ok Tedi downstream of the mine area creeks, through to a relatively short reach in which sediments deposit in segregated gravel and sand bars, to well-sorted sands in the lower reaches of the river. This change is in contrast to the much longer zone of gravel riffles and discontinuous sand bars typical of pre-mine conditions, as described above (Pickup, 1984) (Figs. 2.2A, 2.4A). The Ok Tedi joins the Fly River at D’Albertis Junction, about 190 km downstream of the mine (Fig. 2.1). While there have been regular campaigns to characterize the texture of sediments deposited on the bed and banks of the Fly River, very few of these campaigns have employed the same sampling methodologies, making direct comparisons difficult. Earlier studies have typically analyzed particle size in single samples collected from the thalweg, mid-channel, or from specified locations across the channel (usually, 0.25, 0.5, and 0.75 channel width). We are aware of only two studies that have adopted a similar approach to sampling: the comprehensive survey undertaken by Pickup et al. (1979) before the start of mining and an intensive survey of sediment properties carried out by OTML in May 2003 (OTML, 2004). Both studies collected samples from the levees at either end of river transects. Figure 2.6 is a plot of the d50 (median grain size) and d90 for the 1979 and 2003 surveys. This figure shows a high degree of similarity between the two surveys. Both data sets show that d50 and d90 decrease downstream with increasing distance from Kiunga. Furthermore, these plots show that very little difference exists in the rate of change in grain size in both bed and bank sediments, based on the slope of the lines of best fit. Pre-mine and post-mine plots are also similar in that while grain size does appear to decrease

64

B. R. Bolton et al.

downstream the trend is not systematic; rather, the data show change mostly occurs over short distances separated by longer intervals with relatively little change. Both data sets also show a pronounced fining in grain size in the bed sediment in the lower Middle Fly upstream of Everill Junction (Fig. 2.6A, C). These similarities are also reflected in the downstream variation in size distributions in the increase in proportion of finer size fractions with distance from Kiunga, in both bed and bank sediments (Fig. 2.4). The most noticeable difference between the 1979 and 2003 is in bed material grain size; the sediments of the more recent survey are significantly finer. This is reflected not only in the d50 and d90 (Fig. 2.6A and C) plots but also the increase in finer size fractions as shown in the size distribution plots (Fig. 2.4A and B). Significantly, the opposite trend is shown in sediments of the bank where overall there appears to be a slight increase in grain size and the proportion of coarser size fractions, compared to the pre-mine survey (Figs. 2.4 and 2.6). This may be because deposition of finer mine sediments is greater in upstream reaches (Geoff Pickup, pers. comm.). Another significant difference to emerge from Figs. 2.4 and 2.6 is the rapid change in grain size and the proportion of medium and fine sand immediately downstream of D’Albertis Junction. While not shown for the 1979 survey, there is a similar dramatic change in both grain size and grain size distribution downstream of Everill Junction reflecting the input of coarser material carried by the Strickland. We interpret the sudden change in grain size characteristics of the Fly channel bed sediment, compared to the 1979 survey, to largely reflect the addition of Mount Fubilan mine waste. OTML studies have shown that there has been at least a 5-fold increase in the sediment load entering the Middle Fly from the Ok Tedi as a result of mining (Markham and Repp, 1992). Pile et al. (2003) has also shown that mine wastes supplied to the lower reaches of the Ok Tedi as bed load are dominantly composed of finer sandand silt-sized materials that now also characterize the Middle Fly downstream of D’Albertis Junction. We suggest therefore, that the dominant source of sediment to the Middle Fly and in turn the main control on sediment texture, are waste materials released from the mine. Input from previously deposited sediments while important, is considered to be of secondary importance and are estimated to comprise only a small fraction of sediment released into the active channel (OTML, 2001). Similarly, while perhaps locally important (Pickup et al., 1979), contributions to the sediment load from erosion of bedrock are considered minor. Tributaries, other than the Ok Tedi and Strickland River, appear to play no significant role in influencing the grain size characteristics of either the bed or bank sediments in the Fly River.


65

2.2.2.1. Cause of downstream fining in grain size Downstream fining of grain size is a feature typical of many gravel- and sand-bedded rivers around the world, including rivers elsewhere in PNG (Leopold et al., 1964; Pickup, 1984; Parker, 1991a, 1991b; Paola et al., 1992; Gomez et al., 2001). Grain size investigations on the Fly River system mostly conform to this pattern, but with some variation. As discussed above, median grain size in the Fly decreases rapidly over the first 45 km downstream from Kiunga then remains relatively constant for the next 250 km before again decreasing rapidly over the next 50 km. Grain size remains relatively constant until Everill Junction where it increases over just a few kilometers before decreasing as the river enters the delta (Figs. 2.3B and 2.4B). It is generally agreed that three factors, often in combination, control the textural characteristics of riverbed materials: (1) the nature and location of material delivered to the catchment from the surrounding hinterland; (2) the ability of the river to sort and transport delivered sediment; and (3) the susceptibility of delivered material to abrasion and breakdown (i.e., chemical and physical weathering) (e.g., Gomez et al., 2001; Knighton, 1998; Paola et al., 1992; Pickup, 1984). As previously described, the main source of sediment to the Fly River system (along with most river systems in PNG) is the headwater streams located in the central cordillera. This natural supply of sediment has been greatly supplemented in recent times by the discharge of waste materials from the Mount Fubilan mine at the headwaters of the Ok Tedi and, to a far lesser extent, the Porgera mine which discharges waste materials into the Lagaip River, an upland tributary of the Strickland River. Downstream grain size variation diagrams (Figs. 2.3 and 2.6) indicate sediment supplied by the Ok Tedi and the Strickland River greatly influences the textural characteristics of the Fly River bed. As for the other factors that might influence downstream grain size variation, there appears to be little evidence that selective sorting and deposition of coarser material plays a major role in downstream fining. As shown in Fig. 2.7, the degree of sorting in bed material (as evidenced by the slope of the distribution curve) does not increase systematically downstream as might be expected in a river in which coarser material is progressively removed by deposition. Indeed, the data presented here suggest the degree of sorting deteriorates between D’Albertis and Everill Junctions, before increasing again in the upper Lower Fly under the influence of the greater flow competence of the combined Strickland/Fly Rivers. The deterioration in the degree of sorting as well as the pronounced decrease in grain size and

100

100

80 Percent finer

Percent Finer

Harvey Creek December 2000 (0.5 - 2.5 km downstream of mine) 80

60

40

60

40

0 0.01

0 1

10

A

100

1000

10.00

100.00

80 Percent finer

Percent Finer

1.00 Particle Size (mm)

100

Ok Mani October 2003 2.5 - 9 km downstream of mine 80 60 40

60 40

20

20

0 1

10

B

100

0 0.01

1000

Particle Size (mm)

1.00

10.00

100.00

Particle Size (mm)

80

60

40

60

40

20

20

0 0.01

Lower Middle Fly (296 - 441 km) 0.10

C


10.00

0 0.01

100.00

0.10

1.00

10.00

100.00

Particle Size (mm)

H 100

100

Upper Ok Tedi (Braided Reach: 120 km downstream of mine)

60

80

Percent finer

80

40

60

40

20

0 0.01

0.10

100 Upper Ok Tedi (Gorge Reach: 21 km downstream of mine)

Percent finer

80

Upper Middle Fly (58 -107 km)

G

100

Percent finer

0.10

F

Particle Size (mm)

100

Percent finer

Upper Fly (Upstream of D'albertis Junction: 0 - 38 km)

20

20

20

0.10

1.00

10.00

0 0.01

100.00 I

Particle Size (mm)

D

Lower Fly (482 - 700 km) 0.10


10.00

100.00

100

Percent finer

80

60

40 Lower Ok Tedi (Meander Reach: 130 kmdownstream of mine)

20

0 0.01 E

0.10

1.00

10.00

100.00

Particle Size(mm)

Figure 2.7: Bed material size distribution for Ok Tedi and Fly River after the start of mining (OTML, 2001, 2004).


67

increase in proportion of silts and clays observed in the lower Middle Fly (296–450 km) may in part be due to the backwater effect from the Strickland River (Pickup et al., 1979; Pickup, 1984; Dietrich et al., 1999). Under this scenario episodic backup of the Fly River waters above Everill Junction due to higher flows in the Strickland cause changes in flow velocity which in turn cause a decrease in the transport capacity of the river and its competence. Alternating deposition of fine and coarse materials in this reach of the river, in response to this mechanism (Pickup, pers. comm.), would explain the increased spread of grain size distribution curves, deterioration in the degree of sorting, increase in the proportion of silts and clays, and the overall decrease in grain size, compared to river reaches both upstream and downstream of this part of the river. Downstream fining of bed material in the sand-bedded Fly River as a result of selective deposition of coarser material was recently proposed by Dietrich et al. (1999). This team suggested that rather than a large loss of coarser grained materials and a significant decrease in the river’s ability to transport sediment, fining can occur with only modest loss of coarser grained material (15%), either through deposition on a slowly aggrading riverbed, or, on the adjacent levees and floodplain. The presence of medium sand (B60%) in bank crest sediment of the upper Middle Fly would appear to support this idea. While there are no detailed quantitative studies of particle shape for the Fly River system as a whole, abrasion is known to occur in bed sediments, as evidenced by the increase in the degree of roundness of sediment particles, along the upper reaches of the Ok Tedi (Pile et al., 2003). In contrast, Day and Associates (1996), in a study of bed sediments from the Fly River found no evidence of a measurable change in grain shape from samples taken in the upper reaches of the Fly above D’Albertis Junction. A similar observation was noted by OTML (2003b). In this study visual classification of grain shape and roundness indicated little systematic change downstream. Quartz and feldspar particles, the dominant mineral components of the bed material, were consistently well rounded and of high sphericity throughout the entire 700 km length of the river sampled in this survey. Furthermore, between D’Albertis and Everill Junctions, there was little change in the proportion of mineral and rock fragments that might indicate abrasion and breakdown of less-resistant components (see discussion on sediment mineralogy below). Weathering, as suggested by Knighton (1998), for rivers in general, probably only plays a minor role in determining grain size characteristics in the Fly River. To be effective as a means of bringing about particle disintegration this mechanism requires prolonged exposure to weathering agents. While this might be true for some of the sediments stored in terraces,

68

B. R. Bolton et al.

channel bars and the floodplain environments of the lower reaches of the system, evidence from sediment transport studies show that supply of material from these sources are relatively minor. It is estimated that erosion of ‘‘natural’’ material along the river course supplies about 10% of the total transported load entering the Fly downstream of D’Albertis Junction (OTML, 2001). If grain size reduction was due to chemical weathering of sediment temporarily stored in the channel bar and floodplain deposits then it might also be expected that the clay mineralogy of the bed material might also reflect this contribution. As discussed below, no observable change in the proportion of clay mineral species was observed in the Middle Fly reach. In summary, while downstream fining of bed material is apparent in the data, this trend is complicated by input from tributaries (mainly the Ok Tedi, with its substantial load of Mount Fubilan mine wastes, and the Strickland), and the backwater effect in the lower Middle Fly during period of high flow in the Strickland. In light of these factors it may be more useful to examine changes in particle size on the basis of individual samples, major geomorphic elements, and the source of supply, as first suggested by Pickup (1984). According to this approach the Fly River system can be divided into at least five separate zones each with its own characteristic grain size distribution. While three of these zones are restricted to the gravel-bedded upper reaches of the Ok Tedi, it is significant that the remaining two zones – named by Pickup the ‘‘sand’’ and ‘‘backwater’’ zones, respectively – continue to be well represented despite the large increase in overall sediment load in the system resulting from mining at Mount Fubilan. It would appear that the only major difference between the 1979 and 2003 surveys in terms of the grain size distribution is an overall decrease in grain size in bed materials in both zones as a result of mine inputs. Furthermore, it is apparent from the data that the boundary between the sand and finer grained sediments of the lower Middle Fly is migrating upstream. A comparison between the 1979 and 2003 surveys (Fig. 2.4) shows that this boundary has moved from about 330 km downstream of Kiunga to about 260 km – a shift of approximately 70 km upstream. This shift might be best explained in terms of the continuing influence of the Strickland River and the backwater effect and the finer nature of mine inputs.

2.3. Metal Geochemistry of River-Deposited Sediments In this section we look at what is known about the abundance of selected metals in sediments deposited in the channel bars and levees of the Ok Tedi


69

and Fly River from before the start of mining at Mount Fubilan in 1984 through to 2004. For reviews of metal geochemistry in sediments carried in suspension, and deposited on the Fly River floodplain and in the Fly Estuary and the Gulf of Papua, the reader is referred to companion chapters in this volume by Apte et al., Brunskill et al., and Nittrouer et al. 2.3.1. Before Mining Information on the geochemistry of pre-mine river-deposited sediments in the Fly River system is scarce. Table 2.1 summarizes these data but it should be pointed out that the paucity of data together with variation in sampling methodology, the size fractions analyzed, and the analysis method used, makes comparisons between surveys and estimates of baseline or background metal concentration difficult. One of the earliest studies dealing with the geochemistry of river sediments was conducted by the Cambridge Expedition of 1974 (Boyden et al., 1974). This study presented the results of trace metal determinations on 39 samples (o 200 mm fraction) collected from the Ok Tedi, six of its tributaries (Ok Gilor, Ok Mani, Ok Ningi, Ok Mabiong, Ok Menga, and Ok Ma), and the Fly River near the township of Kiunga (Fig. 2.1) (Table 2.1). While the samples of this data set are too sparse to provide an accurate picture of baseline sediment geochemistry in this region, the results do identify the presence of anomalously high copper, lead, zinc, manganese, and possibly cadmium, in the creeks surrounding the mine and upper reaches of the Ok Tedi, compared with downstream tributaries, Ok Menga (except in Cd), and the Ok Ma, as well as the lower Ok Tedi (Ningerum), and the Fly River at Kiunga. Pre-mine copper values, for example, averaged about 173 ppm in deposited sediments of the Ok Tedi tributaries compared to an average of 62 ppm in the Ok Tedi itself. Figure 2.8, which shows the variation in elemental abundance from the mine to D’Albertis Junction, indicates that trace metal concentrations generally decreased downstream from the Mount Fubilan. Interestingly, the highest average values for Co, Fe, Mn, as well as Ni and Zn, were all recorded at D’Albertis Junction. It was the anomalous geochemistry of these river sediment samples, together with more intensive studies carried out by the Kennecott Australian Explorations Pty Ltd beginning in 1968, which in large part led to the discovery of the Mount Fubilan copper-gold ore body (Davies et al., 1978; Rush and Seegers, 1990). Everett and Associates (1980), as part of a series of government-sponsored studies of the river system in 1979, prior to the start of mining, provide

70

Table 2.1: Geochemistry of pre-mine river bed and bank sediments.

Mine area creeks Ok Mani Ok Mani

Al (%) Fe (%) S (%)

As (ppm)

Cd (ppm)

Co (ppm)

Cu (ppm)

Mn (ppm)

Ni (ppm)

Pb (ppm)

Zn (ppm)

Type

Fraction

– –

3.6 3.3

– –

11 –

– 2.2

9 19

36 30

620 380

135 32

25 34

88 82

Bed Bed

Clay o200 mm

Ok Kam Ok Gilor

– –

– 9.7

– –

– –

1.0 5.5

– 29

15 852

308 1680

– 38

40 185

30 267

Bed Bed

? o200 mm

Ok Ningi

–

4.9

–

–

3.1

17

233

677

24

60

274

Bed

o200 mm

Ok Mabiong

–

4.6

–

–

2.4

24

198

768

36

69

252

Bed

o200 mm

Mean Median

– –

4.7 4.1

– –

– –

2.9 2.4

20 19

173 33

661 586

47 36

58 37

145 88

–

2.8

–

–

4.1

17

9

305

29

24

79

Bed

o200 mm

Ok Ma

–

4.1

–

–

2.2

26

9

552

38

26

87

Bed

o200 mm

Mean Median

– –

3.5 3.5

– –

– –

3.2 3.2

22 22

9 9

429 429

34 34

25 25

83 83

–

4.0

–

–

2.4

20

90

553

31

49

149

Bed

o200 mm

–

4.7

–

–

2.3

28

34

528

28

27

98

Bed

o200 mm

– –

– 2.9

– –

– 8

1.0 –

– 7

19 23

485 310

– 170

43 23

31 61

Bed Bed

NG Clay

Ok Tedi tributaries Ok Menga

Ok Tedi Upper Ok Tedi (Tabubil) Upper Ok Tedi (Ningerum) Upper Ok Tedi Upper Ok Tedi (Tabubil)

Source

Everett (1980) Boyden et al. (1974) Maunsell (1982) Boyden et al. (1974) Boyden et al. (1974) Boyden et al. (1974)

Boyden et al. (1974) Boyden et al. (1974)

Boyden et al. (1974) Boyden et al. (1974) Maunsell (1982) Everett (1980)

B. R. Bolton et al.

Location

–

4.6

–

–

–

38

120

697

53

72

–

Bank

Clay

Everett (1980)

–

6.8

–

–

–

44

120

1162

52

73

–

Bank

Clay

Everett (1980)

–

4.6

–

–

–

19

17

1239

142

25

–

Bed

Clay

Everett (1980)

–

3.9

–

–

–

35

92

697

53

70

–

Bed

Clay

Everett (1980)

–

29.6

–

–

4.2

88

44

2352

46

24

453

Bed

o200 mm

Boyden et al. (1974)

Mean Median

– –

7.6 4.6

– –

– –

2.5 2.4

35 32

62 44

891 697

72 53

45 43

158 98

Fly River U Fly

–

6.0

–

–

2.2

22

17

787

35

29.8

132

Bed?

o200 mm

U Fly U. Middle Fly L. Middle Fly

– – 8.6

4.5 5.3 3.7

– – 0.14

– – 4.6

– – 0.3

39 38 13

100 95 45

775 775 289

65 56 33

80 65 18

– – 142

Bank Bank Bed

Clay Clay o100 mm

L. Middle Fly L. Middle Fly

–

– 4.9

–

– –

2.6 –

– 42

28 99

– 697

– 58

25 73

88 –

Bed Bank

Clay Clay

Boyden et al. (1974) Everett (1980) Everett (1980) Hettler et al. (1997) Maunsell (1982) Everett (1980)

Bed Bank Bank

Silt/clay Clay Clay

Maunsell (1982) Everett (1980) Everett (1980)

Bank

Clay

Everett (1980) Bowen, 1979

Mean Median

4.9 4.9

– –

– –

1.7 2.2

31 38

64 70

665 775

49 56

48 47

121 132

– 8.2 7.9

– 4.8 4.9

– 0.06 0.05

– – –

2.5 – –

– 39 39

20 110 98

– 775 813

– 88 78

33 73 76

57 – –

Mean Median

8.1 8.1

4.9 4.9

0.06 0.06

– –

– –

39 39

76 98

794 794

83 83

61 73

– –

L. Fly Av. crustal abundance

– 8.2

4.8 4.1

– 0.03

– 1.5

– 0.1

41

100 50

852 852

63 80

71 14

– 75

Strickland River Strickland R. Strickland R. Strickland R.

71

– –


Lower Ok Tedi (Konkonda) Lower Ok Tedi (Aran) Lower Ok Tedi (D’Albertis Jct) Lower Ok Tedi (D’Albertis Jct) Lower Ok Tedi

72

B. R. Bolton et al.

Metal concentration (ppm)

10000

1000

100

10

ga un

D

'a

lb

Ki

Jc

t.

m er

in

tis

ge

ru

bi

l

a

bu

M k O

Ta

ga

i

en

an

M

N

O

O

k

O

k

ab M

M

io

in N k

O

k

gi

r ilo G k O

ng

1

Sample location Cd

Co

Cu

Fe%

Mn

Ni

Pb

Zn

Figure 2.8: Variation in metal concentration in sediment samples collected from the Ok Tedi and selected tributaries (data from Boyden et al., 1974). additional baseline geochemical data on the clay-sized fraction of a small number of river-deposited sediments. Table 2.1 which includes the results of this work, shows that Cu concentrations in the clay-sized fraction were generally higher in the samples collected from the river banks compared to those collected from the bed; whether in the higher energy environments of the Ok Tedi or the more sedate reaches of the Fly and Strickland Rivers. A similar trend appears to be typical for Pb, Co, and possibly Cr while Ni showed an opposite trend with highest concentrations occurring in the sandrich channel-bar deposits of the upper reaches of the Ok Tedi and the Ok Mani. The results presented by Everett and Associates (1980) for the Ok Mani, one of the creeks located immediately downstream of the mine, are broadly similar to those reported by Boyden et al. (1974). In detail however, the concentrations of Co, as shown in Table 2.1, are considerably higher in the 1974 survey. Nickel by contrast, is significantly higher in the 1980 survey; a similar result can also be seen when comparing riverbed samples from the Ok Tedi near Tabubil. Furthermore, the samples collected from the banks of the Ok Tedi just upstream of D’Albertis Junction during the 1980 survey generally had lower metal concentrations than those collected in the 1974


73

survey except for Cu. The finer grained sample from the 1980 survey gave a copper concentration of 92 ppm compared to 44 ppm recorded in the earlier study. Additional pre-mine sediment geochemistry is presented by Maunsell and Partners (1982) as part of an OTML-sponsored environmental study to examine potential impacts of the mine on the Fly River system. In this study, results of analysis of four grab samples collected from the bed of the active channels of the lower Middle Fly and Strickland Rivers were presented, along with data on four samples from the upper reaches of the Ok Tedi, upstream of the mine and one sample from the Ok Kam, a headwater tributary of the Ok Tedi. Table 2.1 shows metal concentrations were broadly in line with those previously determined in the 1974 and 1980 studies. Hettler (1995), as part of a UNDEP study of the environmental impacts of mining at Mount Fubilan, reported the results of a comprehensive study of cores collected from the bed of the Fly River and adjacent floodplain environments. Using probability plots of copper distribution, this worker concluded that average metal abundance of riverbed sediments present at Obo, on the lower Middle Fly, at about 45 ppm, were broadly similar to those presented by Everett and Associates (1980) and Maunsell and Partners (1982). Table 2.1 also shows that pre-mine metal concentrations in sediments, when compared to average crustal abundance, were enriched in Fe, As, Cd, Cu, Pb, and Zn, as well as Al, S, Ag, Mo, V, and Sc, based on the average background metal concentrations for the Middle Fly determined by Hettler (1995). The table also shows that pre-mine sediments of the Strickland were enriched relative to average crustal abundance, in Fe, S, As, Cd, Cu, Pb, and Zn. Figure 2.9 shows box plots of elemental abundance in the various river reaches as well as average crustal abundance of each element. This plot summarizes pre-mine metal geochemistry for the river system. It shows that most elements maintain relatively constant concentration down the river system except for Cd, which appears to increase downstream, and Mn, which shows the reverse trend. Zn, Cd, Cu, Fe, and Pb generally occur in concentration above average crustal abundance while Mn and Ni are generally below. 2.3.2. After the Start of Mining Since the start of mining at Mount Fubilan in 1984 various sampling campaigns have been conducted mainly to monitor the impact of mining on downstream environments. The results of these sampling campaigns are

B. R. Bolton et al.

Cd (ppm)

3 2 1 0 Ok Tedi Tributaries Ok Tedi Upper Fly Middle Fly Lower Fly Strickland Av. Crustal Abund.

Ok Tedi Tributaries Ok Tedi Upper Fly Middle Fly Lower Fly Strickland Av. Crustal Abund.

-1

Ni (ppm)


Total Fe (%)

Pb (ppm) 200 180 160 140 120 100 80 60 40 20 0

Ok Tedi Tributaries Ok Tedi Upper Fly Middle Fly Lower Fly Strickland Av. CrustalAbund.

4

Mn (ppm) 2600 2400 2200 2000 1800 1600 1400 1200 1000 800 600 400 200

Ok Tedi Tributaries Ok Tedi Upper Fly Middle Fly Lower Fly Strickland Av. Crustgal Abund.

5

180 160 140 120 100 80 60 40 20 0

Cu (ppm) 900 800 700 600 500 400 300 200 100 0 -100

6

35 30 25 20 15 10 5 0 Ok Teditributaries Ok Tedi Upper Fly Middle Fly Lower Fly Strickland Av Crustal Abund.

Zn (ppm) 500 450 400 350 300 250 200 150 100 50 0


74

Figure 2.9: Box plots showing metal variation in river deposited sediments for selected reaches of the Ok Tedi/Fly River system downstream of Mount Fubilan mine. Also shown for comparative purposes is average crustal abundance (from Bowen, 1979). summarized in Table 2.2 along with the geochemistry of the Mount Fubilan orebody and its waste products. The earliest report on the geochemistry of river-deposited sediment after the start of mining is by Kyle (1988). The single riverbed sample analyzed in this work was collected from the lower Middle Fly and perhaps not surprisingly, given that it was collected only about six months after the start of mining, gave metal concentrations similar to those recorded in the premine (Maunsell and Partners, 1982) study for the same region. The first major attempt at characterizing the geochemistry of riverdeposited sediment throughout the river system is presented in OTML (1994). This study, which only deals with copper abundance, was completed about 10 years after the start of mining and includes samples collected along

Table 2.2: Geochemistry of deposited river sediments after the start of mining at Mount Fubilan. Location

Fe (%)

S (%)

As (ppm)

Cd (ppm)

Cu (ppm)

Mn (ppm)

Ni (ppm)

products 8.6 3.2 6.6 13.8 – 16.4 6.1 14.6 8.4 3.1

0.94 3.54 1.76 2.36 0.86

3 – 135 5 5

5.60 – 5.00 0.51 92.40

2,050 1,461 7,100 8,083 2,030

520 – 555 451 629

12 – 14 52 15.5

Pb (ppm)

Zn (ppm)

Source

26 114 27 57 140

42 117 94 415 66

EGi (1996) OTML OTML EGi (1991) EGi (1996)

Mine area creeks Harvey creek Harvey creek Ok Mani

– 0.8 1.1

– 2.2 3.9

– 1.08 1.95

– 13 12

– 0.94 0.67

5,510 819 1,143

– 442 410

– 11 12

– 71 58

– 330 290

OTML (1993) OTML (2004) OTML (2004)

Ok Tedi Upper Ok Tedi Upper Ok Tedi

– 6.1

– 4.8

– 1.52

– 30

– 1.60

1917 1523

– 700

– 17

– 463

– 541

Upper Ok Tedi Lower Ok Tedi

0.8 –

4.7 –

2.05 –

20 –

0.59 –

893 864

377 –

7 –

36 –

163 –

OTML (1993) Hettler et al. (1997) OTML (2004) OTML (1993)

0.8

2.0

0.003

3

0.04

8

269

9

4

29

OTML (2004)

–

–

–

–

–

415

–

–

–

–

OTML (1993)

1.4

4.9

0.64

10

0.69

479

668

10

43

219

OTML (2004)

9.3

4.3

–

12

–

o83

621

o74

–

129

Delft (1987) 75

Fly River Upper Fly River Upper Middle Fly Upper Middle Fly Lower Middle Fly


Orebody and waste Ex-mill tailings Ex-mill tailings Orebodya Orebody Waste rock

Al (%)

76

Location

Al (%)

Fe (%)

S (%)

As (ppm)

Cd (ppm)

Cu (ppm)

Middle

–

5.8

–

–

1.70

Middle

–

–

–

–

Middle

7.4

4.6

0.22

Middle

8.1

4.0

Middle

1.6

Lower Fly Lower Fly Strickland River Strickland Strickland

Lower Fly Lower Fly Lower Fly Lower Fly Lower Fly

Mn (ppm)

Ni (ppm)

Pb (ppm)

Zn (ppm)

58

515

–

15

120

–

314

–

–

–

–

15

1.80

760

520

15

50

185

EGi (1996)

0.25

8

0.50

530

528

21

79

211

3.8

0.64

11

0.79

740

543

11

68

298

Hettler et al. (1997) OTML (2004)

– 1.7

– 4.1

– 0.04

– 11

– 0.30

60 103

– 540

– 50

– 23

– 124

OTML (1993) OTML (2004)

8.6 1.7

4.4 3.8

– 0.02

12 13

– 0.35

o190 28

735 548

o35 45

– 24

107 122

Delft (1987) OTML (2003a, 2003b)

Note: Also given are typical metal concentrations for tailings, Mount Fubilan orebody, and waste rock. ¼ Not determined. a Median values given.

Source Kyle (1988) OTML (1993)

B. R. Bolton et al.

Table 2.2: (Continued ).


77

the entire length of the river system – a total river distance of about 1,000 km (Table 2.2). Figure 2.10, from OTML (1994), plots copper abundance, along with particle size distribution and copper distribution against distance downstream from the mine for riverbed (deposited) and suspended sediment load. The plots also show how each of these parameters change according to the size fraction analyzed. It is clear from these plots that copper concentrations in both deposited and suspended sediments decreases downstream from the mine (Fig. 2.10A and D). It is also apparent that this change is not progressive but characterized by sudden decrease at both D’Albertis and Everill Junctions (190 and 598 km downstream of the mine, respectively). Furthermore, the plots show these changes across all particle size fractions and bulk samples. The pronounced change at Everill Junction is thought to be the result of dilution by sediment input from the Strickland River. Figure 2.10 also shows that the highest copper concentrations, irrespective of location or sample type, typically occur in the finer grain size fractions (see also Pile et al., 2005). The only significant variation from this pattern appears in deposited sediment of the Ok Tedi and in the Middle Fly immediately downstream of D’Albertis Junction. Here the coarser fractions (W 63 mm) typically contain about 80% of the total copper content of sediments (Fig. 2.10F). Furthermore, this figure shows that the o5 mm fraction consistently contributes about 50% of total copper compared to the contributions by the W63 mm fraction which consistently contributed less than 2% of the total copper. A similar trend was described for benthic sediment; however, in this case, it was found that closer to the mine the largest size fraction (W63 mm) contributed the highest percentage of total copper while in the Middle Fly, and in particular downstream of about 400 km from the mine, this pattern was reversed with the finest fraction (o5 mm) contributing consistently over 50% of the total copper (except for a brief interval just downstream of Everill Junction). The increase in copper concentration, in the first instance between about 10 and 100 km from the mine then again from about 400 to 600 km from the mine, described above, may be related to the varying role of a particular grain size fraction in controlling copper chemistry in sediments. In this interpretation the peak in copper concentration observed in the upper reaches of the Ok Tedi may relate to the preferential deposition of copper contained in the larger size fractions while the second peak observed in the lower Middle Fly may relate to the higher copper content of the finer fractions dominant in this reach (see section of grain size variation above). Significant also is the observation that, at least for the Ok Tedi copper peak as defined in the 2003 survey, heavy mineral studies have shown that the

5000 4000 3000 2000 1000 0 200

90 80 70 60 50 40 30 20 10 0

400 600 800 Distance from the mine (km)

1000

D. Copper concentration 10000 1000 100 10 1

1200

0

B. Particle size distribution

0

200

400

600

200

800

1000

1200

200

400

600

800

0

200

63 um -20 um

20 um -10 um

Percent of total copper

Percent of total copper

1000

1200

400

600

800

1000

1200

1000

1200

1000

1200

F. Percent of total copper

100 80 60 40 20 0 0

200

Distance from mine (km) >63 um

800

Distance from the mine (km)

C. Percent of total copper contributed

0

600

E. Particle size distribution

100 90 80 70 60 50 40 30 20 10 0

Distance from the mine (km) 80 70 60 50 40 30 20 10 0

400

Distance from the mine (km)

Percent

Percent of total sediments

0

100000

400

600

800

Distance from the mine (km) 10 um -5 um

63 um

63 um - 20 um

20 um -10 um

10 um - 5 um

Figure 2.10: Downstream variation in copper concentration, particle size distribution, and copper distribution for suspended sediment (A, B, C) and deposited bed load sediment (D, E, F) from the Fly River (data from OTML, 1994).

B. R. Bolton et al.

Copper concentration (ug/g)

A. Copper concentration

6000

78

Copper concentration (ug/g)

7000


79

largest percentage of heavy minerals as a percentage of the total sediment, occurs coincident with the copper peak (i.e., just upstream of Bige). A similar increase in the lower Middle Fly in the relative abundance of sulfide minerals (mainly pyrite) may also explain the sudden increase in copper concentration, at least for the interval between 392 and 600 km (Everill Junction). A second system-wide survey of deposited sediment geochemistry was undertaken in 2004 by OTML to better understand the chemical impact of mine operations on the river (OTML, 2004). Summary statistics for metal analysis of composite samples from a total of 85 river channel transects completed in this survey are given in Table 2.2. Table 2.2 indicates that significant differences occur in the metal geochemistry of riverbed sediments according to river reach. Downstream of D’Albertis Junction, the Fly Riverbed sediments are relatively enriched in Al, Fe, As, Cd, Cu, Mn, Pb, and Zn, when compared to sediments of the Upper Fly. Sulfur, also low in the Upper Fly, increases dramatically downstream of D’Albertis Junction and then decreases again to relatively low concentrations below Everill Junction. Nickel is relatively low throughout the Upper and Middle Fly reaches but increases significantly below Everill Junction. These trends become even more clearly defined when these data are examined in terms of enrichment. Figure 2.11 plots metal enrichment for the Ok Tedi/Fly River system downstream of the mine relative to average Upper Fly concentrations and average crustal abundance, respectively. Figure 2.11A shows that most of the elements covered in this survey are enriched relative to concentrations in the deposited sediments of the Fly River upstream of D’Albertis Junction, with greatest enrichment occurring in copper and sulfur. Sulfur concentrations, in all but the sediments of the Lower Fly, downstream of Everill Junction, show the greatest enrichment compared to the Upper Fly sediment with enrichment factors typically in excess of 100. This, as is discussed below, has important environmental implications related to the increased risk of acid generation wherever these sediments might become exposed to the atmosphere. Figure 2.11B shows that since the start of mining, sediments deposited downstream of the mine are enriched in Se, S, Cu, As, Cd, Zn, Pb, and Fe, relative to average crustal abundance. The figure also shows these sediments are depleted in Mn, Ni, and Al, when compared to average crustal abundance. Figure 2.11A also shows that there is very little dilution of metal abundance from the mine (Harvey Creek) to Everill Junction. Relative metal abundance is almost constant down the river system until the junction with the Strickland at which point dilution by the sediment carried by the later causes a sudden decrease in relative abundance of most metals. Figure 2.12 shows the variation in element abundance in composite riverbed samples downstream from Kiunga based on the closely spaced

80

B. R. Bolton et al.

Enrichment Factor (compared to av. U. Fly River sediment)

1000.0

Al (%) Fe (%)

100.0

S (%) As (ppm) Cd (ppm) Cu (ppm)

10.0

Mn (ppm) Ni (ppm) Pb (ppm) Se (ppm)

1.0

Zn (ppm)

0.1 Harvey Creek

Ok Mani

Enrichment Factor (compared to av. crustal abundance)

A

B

Upper Ok Tedi Reach

Middle Fly

Lower Fly

100.0

Al (%) 10.0

Fe (%) S (%) As (ppm) Cd (ppm)

1.0

Cu (ppm) Mn (ppm) Ni (ppm) Pb (ppm)

0.1

Se (ppm) Zn (ppm)

0.0 Harvey Creek

Ok Mani

Upper Ok Tedi Reach

Middle Fly

Lower Fly

Figure 2.11: Downstream variation in elemental abundance relative to (A) average concentration in sediments of the Upper Fly River (i.e., above D’Albertis Junction) and (B) average crustal abundance (data from Bowen, 1979). Sediment input from the Strickland River, which marks the boundary between the Middle and Lower Fly, is the major cause of the sudden change in enrichment factor seen in both plots.


D'albertis Jct.

Everill Jct.

D'albertis Jct.

Total Cu (mg/kg)

1200 800 400

Concentration

Concentration

1600

0 0

200

400

600

800

Total S (%S)

1000

0

200

400

D'albertis Jct.

Everill Jct. Concentration

Concentration

0.8 0.6 0.4 0.2

Everill Jct. As (ppm)

25 20 15 10

200

400

600

800

5

1000

0

200

400

Distance from Mine (km) D'albertis Jct.

600

800

1000


Everill Jct.

Everill Jct.

0.08

2.0 Cd (ppm)

1.5 1.0 0.5

Hg (ppm)*

Concentration

Concentration

1000

0 0

0.0

0.06 0.04 0.02 0.00

0

200

400

600

800

0

1000

200

400


600

800

1000


Everill Jct.

14 12 10 8 6 4 2 0

Everill Jct.

1000 Fe (%)

Concentration

Concentration

800

30 Ag (ppm)

1.0

0.0

Mn (ppm)

800 600 400 200 0

0

200

400

600

800

1000

0

200

400


140 120 100 80 60 40 20 0

600

800

1000

Distance from Mine (km)

Everill Jct.

D'albertis Jct.

600 Pb (ppm)

Concentration

Concentration

600


1.2

Everill Jct.

500

Zn (ppm)

400 300 200 100 0

0

200

400

600

800

0

1000

200

400

D'albertis Jct.

D'albertis Jct.

Everill Jct.

2.0 1.5 1.0 0.5

Al (%)

Concentration

2.5

0.0 0

200

400

600

800

1000

800

1000

Everill Jct.

70 60 50 40 30 20 10 0

Ni (ppm)

0

200


600



Concentration

Everill Jct.

3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0


81

400

600

800

1000


Everill Jct.

D'albertis Jct.

Everill Jct.

Se (ppm)

5 4 3 2 1 0

Concentration

Concentration

6 d50 (mm)

10.00 1.00 0.10 0.01

0

200

400

600


800

1000

0

200

400

600

800

1000


Figure 2.12: Variation in concentration of selected metals and the d50 in river deposited sediments downstream of the Mount Fubilan mine (OTML, 2004).

82

B. R. Bolton et al.

transects sampled by OTML in 2003 (OTML, 2004). This figure shows Cu increases rapidly in concentration downstream of D’Albertis Junction from a value consistently less than 15 mg/kg to concentrations in excess of 600 mg/kg. In detail, while the data are noisy, the Cu concentration after rising to about 800 mg/kg generally decreases to about 100 mg/kg. At 237 km downstream of Kiunga it then increases to levels marking the highest recorded during this survey at around 1200 mg/kg (at 315 km, just downstream of Bosset Lagoon). Copper levels remain relatively high (350–1,000 mg/kg) until Everill Junction where they decrease rapidly over a short distance to concentrations generally less than 200 mg/kg. Zinc, lead, selenium, and to a slightly lesser extent, arsenic, silver, cadmium, and sulfur show a similar pattern of variation to that of copper. Manganese differs from copper in that after increasing rapidly at D’Albertis Junction it then, with some scatter, progressively decreases downstream to the delta without any apparent increase in the lower Middle Fly. Iron also increases at D’Albertis Junction and while showing considerable scatter between transects, relatively high concentrations (4–7%) are maintained through to about 161 km downstream of Kiunga. At this location, concentrations then decrease rapidly to between 3.8 and 4.1% with a slight rise discernible below Everill Junction before decreasing again toward the delta. Aluminum, unique among the elements discussed here, shows a progressive but noisy increase downstream from Kiunga to the delta. Mercury, for the first 250 km or so downstream of Kiunga, hovers close to the detection limit. From just downstream of Manda (at approximately 282 km) concentrations of this element then increase substantially and remain at an elevated level (0.02–0.06 mg/kg), until the river enters the delta. Nickel remains at relatively constant concentrations throughout the middle and upper reaches of the Fly and then, downstream of Everill Junction, increases dramatically before decreasing rapidly again as the river enters the delta.

2.3.2.1. Source of metals Sediments deposited on the bed of the Fly River downstream of D’Albertis Junction are enriched in As, Cd, Cu, Fe, S, Se, and Zn when compared to average crustal abundance as well as Al, Mn, Ni, and Pb, when compared to the average composition of the riverbed in the Upper Fly (i.e., upstream of D’Albertis Junction) (Fig. 2.11A). Earlier work by EGi (1996) based on multi-element analysis of a single sample from the Fly River at Obo indicated enrichment in Ag, As, Bi, Cd, Cu, Mo, S, and Se with respect to average crustal abundance (see also Hettler et al., 1997).


83

It has long been argued that the source of metals that causes the metal enrichment now observed in the Ok Tedi and Middle Fly is most likely the waste materials from the Mount Fubilan porphyry copper-gold mine (e.g., Hettler et al., 1997). This interpretation has been largely based on the similarity between the chemical composition of river sediments deposited downstream of the mine along the Ok Tedi and Fly Rivers and the trace metal composition of the Mount Fubilan orebody. A comparison between the abundance of trace metals found in these sediments, the orebody, and the mine’s waste materials highlights this similarity (Table 2.2). The trends described for trace metal distribution and abundance in the river system described above (Figs. 2.11 and 2.12) (Table 2.2) are interpreted to reflect the following: (1) the trace metal enrichment in Mount Fubilan orebody (primary control); (2) the distribution pattern of heavy minerals (particularly pyrite and associated Cu-bearing minerals such as chalcopyrite); and (3) the proportion of finer fractions in deposited sediment. The concentration maxima for Cu, Ag, Cd, Pb, Se, Zn, Mn, and S, within river-deposited sediments located in the upper reaches of the Ok Tedi is generally thought to reflect preferential deposition of mine-derived heavy minerals in this reach (Fig. 2.12). The presence of river channel bar deposits with up to 13wt% heavy mineral (mainly, magnetite, pyrite, and a range of Cu-bearing sulfide minerals) provides support for this interpretation (Pile et al., 2005). A similar concentration maxima for most of these elements in the lower Middle Fly (between 392 and 460 km, Fig. 12), while probably due in part to deposition of metal-bearing sulfide minerals (Fig. 2.18), may also in part reflect preferential deposition of metal-enriched finer grained silts and muds in the backwater zone upstream of Everill Junction (see discussion on sediment texture above and Fig. 2.4). The large increase in mercury in the lower Middle Fly and Lower Fly is thought to be the result of runoff from Hg-bearing geologic units in the ridge dividing the Fly River and basin from Lake Murray. Anomalous mercury has been identified in the Lake Murray region for some time and while we are aware of no previous geochemical evidence for enrichment in the Middle Fly region, high levels of mercury have been described from hair samples collected from people living in villages along the Middle Fly (Kyle and Ghani, 1982). The rapid increase in nickel downstream of Everill Junction is interpreted to be the result of influx of Ni-bearing sands and silts from the Strickland River. The source of these Ni-bearing sediments is not known with certainty; however, the Strickland traverses in its middle reaches the western flank of Mount Bosavi, an extinct volcano comprised in part of alkaline and transitional olivine basalts known to have anomalously high Ni (Mackenzie and Johnson, 1984).

84

B. R. Bolton et al.

The abrupt decrease in most metal concentrations in bed material downstream of Everill Junction is in large part due to dilution by the much larger sediment load of the Strickland, which is also considerably coarser in grain size. The important role of the Strickland (and even more so the Ok Tedi) in influencing the geochemistry of Middle Fly deposited sediments is in contrast to the other tributaries of the Middle Fly, which appear to have little or no influence in this regard. The progressive increase in aluminum downstream from the mine including the Lower Fly reach is not understood. It may reflect increasing Al-bearing clay input to bed load as a result of weathering. Certainly the dominant clay mineral of the numerous off-river water bodies (and entering via the main tributaries of the Middle Fly) is kaolinite. This may in turn say something about exposure times to chemical weathering processes across the Fly alluvial plain.

2.3.2.2. Temporal and spatial changes in geochemistry In this section we examine how metal concentrations in river-deposited sediments vary with time and space. Comparison of Tables 2.1 and 2.2 indicates a dramatic increase in the concentrations of most elements after the commencement of mining in 1984 along much of the Ok Tedi/Fly River system. For example, copper concentrations in Ok Mani, just to the south of the mine, have increased in bulk sediments from around 30 ppm in 1974 to in excess of 1,000 ppm in 1993. By 2004, metal concentrations in Ok Mani and Harvey Creek, even closer to the mine, were consistently close to those seen in mine waste or even the orebody. Further downstream in the lower Middle Fly metal concentrations show a similar rapid increase with time. Near Obo, for example, just upstream of Everill Junction, copper concentrations in riverbed sediments has increased approximately 12-fold from background concentrations of around 45 ppm to over 500 ppm. This increase in copper concentration, both with increasing distance from the mine and with time, can also be seen in Fig. 2.13 which compares the variation in copper concentration in river-deposited sediments collected from various sampling campaigns before the start of mining and detailed surveys conducted by OTML in 1993 and 2003. In detail, this figure shows copper concentrations, though highly variable, decrease from the mine to the confluence of the Ok Tedi and Fly, in both the 1993 and 2003 data sets. It is interesting to note however, that there is a pronounced increase in concentration of copper peaking at 65 km in the 1993 survey (upstream of Ningerum in the gorge reach of Ok Tedi) and 117 km in


Copper concentration (mg/kg)

10000

D'albertis Jct.

Everill Jct.

85

1993 2003

1000

Pre-mine

100

10

1 0

200

400 600 800 Distance from the mine (km)

1000

1200

Figure 2.13: Variation in copper concentration (note log-scale) downstream from Mount Fubilan mine for samples collected in 1979 (Data from Everett and Associates, 1980; Hettler et al., 1997), 1993 (OTML, 1994), and 2003 (OTML, 2003b).

the later survey. Downstream of D’Albertis Junction (at 187 km from the mine), copper concentrations again increase rapidly in both of the more recent data sets and then, with some scatter, decrease to relatively low concentrations at around 448 km from the mine for the 1993 survey and 392 km for the 2003 survey. Downstream of these locations copper concentrations then increase rapidly to form zones of relatively elevated levels until Everill Junction. Comparison of the 1993 and 2003 data sets suggest that this zone of elevated copper has shifted upstream with time by some 50 km or so and, increased in concentration from an average of 314–695 mg/kg, an increase of 121% over the 10-year period. Downstream of Everill Junction, copper concentrations decrease rapidly to the lowest levels recorded in either survey and continue, with some minor fluctuations, to remain either constant or decrease further through to the estuary. While data are again scarce and often highly variable, it is also illuminating to compare the downstream variation in copper abundance in sediments from the Fly River levees with time. Figure 2.14, which shows the results of two surveys conducted on the levees of the Middle Fly between D’Albertis and Everill Junctions, indicates a substantial increase in the copper content of river-deposited bank sediments with time particularly in the upper part of this 411 km long reach. The plot also indicates that while copper concentrations are highly variable during the mid-90s they typically oscillate around an average of about 890 mg/kg with possibly a trend toward a slight increase in concentration downstream toward the junction with the

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2500 1994 2003 Linear (1994) 5 per. Mov. Avg. (2003) Linear (2003)

Cu concentration (mg/kg)

D'albertis Jct.

2000

Everill Jct.

1500

1000

500

0 0

50

100

150

200

250

300

350

400

450

500


Figure 2.14: Variation in copper concentration in levee sediments along the Middle Fly River between D’Albertis and Everill Junctions for surveys conducted in 1994 and 2003 (data from OTML 1994, 2003b). Strickland. By contrast, the 2003 data set is again highly variable but with a pronounced decreasing trend in concentration downstream. The average concentration of copper in the levees of the Middle Fly from the 2003 survey is 1083 mg/kg – an increase of over 20% compared to the 1993 survey results. The trend lines for both data sets have been plotted on this figure to support these observations. Also shown on this figure is the rolling average for the 2003 data set. This curve, while again giving support to the overall downstream decrease in copper concentration in levee sediments, appears to indicate a bimodal distribution pattern with concentration peaks about 160 and 400 km downstream of Kiunga. This distribution pattern is similar to that described above in relation to the copper concentration in the riverbed sediments and may again reflect the dual role of preferential deposition of Cu-bearing sulfide minerals in the upper part of the reach and the tendency for increased deposition of silt and finer grained sediments on the levees in the lower Middle Fly in response to the Strickland backwater effect described earlier to explain the prominent textural changes in sediments in this region. We are aware of only two geochemical assays for sediments collected from the levees of the Middle Fly before the start of mining; both reported by Everett and Associates (1980) (Table 2.1). These samples, collected from the upper Middle and lower Middle Fly gave copper concentrations of 95 and 99 mg/kg, respectively. Compared to the 2003 results this represents an increase in the copper content in the order of almost 1000%.


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2.3.2.3. Implications for the risk of acid rock drainage Since mining began sulfur concentrations have progressively increased in sediments deposited from the Ok Tedi and Fly Rivers (Tables 2.1 and 2.2) (Fig. 2.12). This increase in sulfur content has long been predicted as a consequence of the variable but generally high sulfur grade of the Mount Fubilan orebody and the riverine disposal of the mine’s waste (e.g., Pickup et al., 1979). Of particular concern has been the tailings generated by the copper recovery plant located near the mine. Sulfur grades in tailings between late 1999 and mid-2006 averaged close to 3%S, varying on the type of ore being fed to the mill (Table 2.2). Most of the sulfur present in these sediments is derived from pyrite (FeS2), along with generally lesser amounts of other sulfur-bearing minerals such as chalcopyrite and chalcocite, discharged from the mine in both waste rocks and tailings (see following section on sediment mineralogy). Whenever these minerals are deposited from the river in areas that may become exposed to atmospheric oxygen and water, such as river point bars and the crests of levees, there is a risk that they will be oxidized in a process that generates a solution equivalent to dilute sulfuric acid and other potentially harmful metal-rich liquids that are collectively known as ARD. Environmental damage resulting from ARD is well known from many parts of the world and may occur not only with mining activities but anywhere where sulfur-bearing minerals are exposed to the air (Parker and Robertson, 1999). Since 2000 OTML has conducted intensive monitoring of the riverdeposited mine wastes throughout the river system (including the mine wastes recovered from the bed of the Ok Tedi through its dredging operation at Bige) to assess the potential for the development of ARD. This monitoring includes determination of the sulfur content of sediments together with that of a parameter known as the acid neutralizing capacity (ANC) – essentially a measure, in this instance, of the amount of carbonate in the sediment that is available to neutralize any acid formed. With this information it is possible to calculate a third parameter known as the net acid producing potential (NAPP) (usually expressed in units of kg H2SO4/t), which is simply derived according to the following equation: NAPP ¼ MPA ANC where the maximum potential acidity (MPA) is equal to the sulfur content in %S multiplied by a conversion factor of 30.6, commonly used in acid–base accounting (AMIRA, 2002). When the NAPP is a negative number ANC exceeds the MPA and the resultant material is thought to be unlikely to

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generate acid. In contrast if the NAPP is a positive number then acid generation is considered likely (AMIRA, 2002). Figure 2.15A shows how sulfur concentrations in river-deposited sediment on the levees of the Fly River downstream of D’Albertis Junction have changed with time. In order to improve interpretation of this data the trend lines shown in this plot represent running averages of sulfur concentration in samples collected every 5 nautical miles (9.3 km), in the Middle Fly, or either 5 (2005), 10 (B18.5 km; 2001) or 20 nautical miles (B37 km; 2003) in the Lower Fly. This figure indicates that sulfur concentrations increased from 2001 to 2003 with the later samples showing concentrations consistently greater than 1%S between D’Albertis and Everill Junctions. By contrast, the trend for samples collected in 2005 indicates sulfur concentrations continued at high levels (in excess of 1%S) in the upper Middle Fly (between about 350 and 436 nautical miles upstream from the estuary mouth) while decreasing, sometimes below 2001 concentrations, in the lower Middle Fly (between about 350 and 214 nautical miles). Downstream of Everill Junction sulfur concentrations in the three surveys depicted in this plot decrease progressively toward the estuary. Figure 2.15B shows the running average for ANC for the three surveys discussed here. While all three surveys show a general trend of decreasing ANC with distance downstream, the ANC of levee sediments has decreased markedly in the Middle Fly, between about 370 and 200 nautical miles, to levels consistently below those of earlier years. Interestingly, peaks in ANC are also apparent at about 430 and 170 nautical mile marks with implications for ARD risk. This change in the acid–base balance with time in the levee sediments is in turn reflected in the increase in the number and distribution of NAPP positive samples, along much of the Middle Fly, as shown in Fig. 2.15C. Figure 2.16 is an acid–base plot for samples collected from the levee (right bank only) of the Fly River downstream from D’Albertis Junction from 2001 to 2005 and shows the total sulfur content compared to the ANC. The NAPP positive and NAPP negative zones are identified on this plot. The plot shows that with time, more samples are plotting in the NAPP positive field indicating they are increasingly likely to generate acid. Analyses of these data indicate that since 2003 in excess of 20% of the samples collected from the Fly River levees gave NAPP positive results, peaking at almost 40% in 2004. The results of recent water quality testing of drainage and pore waters from several locations in the sand bars of the upper reaches of the Ok Tedi as well as the levee environments of the lower Middle Fly confirms that sulfide oxidation is occurring. Oxidation and neutralizing

A

Everill Jct.

D'albertis Jct.

2.0 1.5 1.0 0.5

percent sulphur

2.5

0.0 50

150

250

350

450

n. miles from mouth of Fly River estuary Mouth

B

D'albertis Jct.

Everill Jct.

120 100 80 60 40

ANC (kg H2SO4/t)

140

20 0 50

150

250

350

450

n. miles from mouth of Fly River estuary

Everill Jct.

D'albertis Jct.

20 10 0 -10 -20 -30 -40 -50 -60 -70 -80 -90

NAPP positive/ potentially acid generating

NAPP negative/ unlikely to generate acid

50

150

250

350

NAPP (kg H2SO4 /t)

C

450

n. miles from mouth of Fly River estuary 4 per. Mov. Avg. (Right Bank (2001)) 4 per. Mov. Avg. (Right Bank (2003)) 4 per. Mov. Avg. (Right Bank (2005))

Figure 2.15: (A) Moving average sulfur concentration. (B) Moving average ANC. (C) Moving average NAPP for levee sediments collected from the right bank of Fly River for surveys conducted in 2001, 2003, and 2005 (data from OTML, 2001, 2003a, 2003b, 2005). Also shown in (C) are the NAPPpositive and NAPP-negative fields.

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3.0 NAPP positive

Sulphur (%)

2.5

NAPP=0

2.0 1.5 1.0 NAPP negative 0.5 0.0 0

50 100 ANC (kg H2SO4 /t) 2001 (RB)

2003 (RB)

2004 (RB)

150

2005 (RB)

Figure 2.16: Acid-base plot for sediment collected from the levee of the Fly River right bank (RB) only between D’Albertis Junction and the delta (data from OTML 2001, 2003b, 2004, 2005). Also shown is a line representing NAPP ¼ 0 and the NAPP-positive and NAPP-negative fields.

products including sulfate and manganese are elevated along with metals such as copper, aluminum, and zinc. pH values as low as 2.6 have been measured in several of these areas together with high levels of acidity, and again indicates acid generation is locally and intermittently produced. Overall, the results to date of monitoring suggest that there is a high risk of widespread acid drainage and elevated copper (and other metals) from the deposited sediments in the longer term. Although high ANC in places is likely to buffer acid generation from most parts of the river system and particularly the levees, for a number of years, observed pyrite and carbonate segregation suggests that localized hot spots could develop in the short term, as has been observed with river-deposited sediments in the upper reaches of the Ok Tedi (Pile et al., 2005) and the lower Middle Fly (OTML, 2005), as described above. In recognition of the risks posed by ARD to the Fly River system ecology, including the communities who live along its length, OTML has recently initiated plans to recover sulfide minerals from mine tailings together with other measures, to significantly mitigate this risk.


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2.4. Sediment Mineralogy In this section we examine the impact of mining on the mineralogical composition of sediments deposited in the bed and levees of the Ok Tedi and Fly rivers.

2.4.1. Before Mining Prior to the onset of mining, very little work was undertaken on the mineralogy of the Fly River sediments. Everett and Associates (1980) conducted mineralogical analysis on a small number of samples collected in 1979. This study presented information on the distribution of clastic sediment components, quartz, volcanic rock fragments, carbonate rock fragments, mudstone and soil zone clasts from the Kiunga, D’Albertis Junction, and Everill Junction regions of the river system. These data showed that components were variably distributed in the three regions sampled. The Upper Fly contained the highest percentage of quartz in the bed load, while breakup of mudstone rock fragments and soil zone clasts during transport was suggested as the main source of matrix present in both sediments of the bed and levees of the Middle and Lower Fly. These workers also documented the presence of volcanic rock fragments in sand-sized material of the Upper Fly and the Strickland Rivers. They suggested that volcanic ashes from andesitic central PNG volcanoes may also be a local source in the Fly River system due to the presence of orthopyroxene and clinopyroxene, strongly zoned plagioclase phenocrysts, and a general absence of olivine.

2.4.2. After the Start of Mining Mineralogical studies of river sediments since mining began in 1984 are given by Hettler (1995) as part of a study of the environmental impact of mining on the river system (see also Hettler and Lehmann, 1995; Hettler et al., 1997). This work mainly targeted the heavy mineral and clay fractions of floodplain sediments from the Middle Fly region. These workers note the similarity of the heavy mineral component from the Middle Fly and in particular the sulfide component, to that of the sulfide mineral assemblage in the Mount Fubilan orebody as well as in riverdeposited tailings in the upper reaches of the Ok Tedi and mine area creeks (Hettler et al., 1997).

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The clay fraction was also the focus of mineralogical studies conducted on river-deposited sediments by Delft on behalf of OTML in 1987 (Delft, 1987; Salomon and Eagle, 1990). The results of these studies are presented below. However, it is work conducted by OTML as part of its monitoring activities along the river system, which is the basis for the most detailed mineralogical analysis of the system’s sediments and most of this is drawn from the results of a research cruise of the M.V. Western Venturer in May 2003 (OTML, 2003b).

2.4.2.1. Mineralogy of riverbed sediments Quartz (48%) and feldspar (37%) are the dominant minerals of the contemporary riverbed. They occur with generally minor amounts (o10%) of clay, carbonate, mica, hornblende, and opaque minerals (Table 2.3). Also present in trace amounts in some samples, mainly from the Upper and Middle Fly, are clinopyroxene, andalusite, staurolite, and tourmaline. Significantly, the sediments of the bed (OTML, 2003b) are typically monomineralic in nature. Particles composed of two or more different minerals or rock fragments were generally rare or absent. Figure 2.17 is a plot of the variation in the estimated proportions of these minerals downstream from Kiunga in both the sediments of the bed and levee. Figure 2.17A shows that between Kiunga and the confluence with the Ok Tedi (D’Albertis Junction), quartz is the dominant mineral of the riverbed (over 80%) with lesser amounts of feldspar (plagioclase mainly but with moderate to trace amounts of K-feldspar in some samples), clays (mostly chlorite), and opaques. Downstream of D’Albertis Junction there is a rapid increase in the relative abundance of feldspar (mainly plagioclase) at the expense of quartz such that within just a few kilometers of the junction Table 2.3: Estimated mineral percentages for o3.32 Sp. Gr. component of Fly River bed sediments during research cruise WV03-11.

n Mean Median SD Min Max

Quartz

Feldspar

43 48 45 13 30 90

43 38 40 11 5 55

Source: OTML (2003b).

Carbonate Hornblende Mica/chlorite 43 2 2 2 0 5

43 o1 o1 o1 0 1

43 3 3 1 1 6

Clay Opaques 43 5 5 3 1 10

43 3 3 2 2 10

60

40

40 30

Strickland R.

10

Agu R.

Ok Tedi

20

Binge R.

30

50

20 10

0

0

A Feldspar

Carbonate

Hornblende

Mica/Chlorite

404

482

589

2

700

Clay

Distance downstream from Kiunga (km)

Opaques

Pyrite

100

100

90

90

80

80

70

70

60

60

50 40

Chalcopyrite

Goethite

Magnetite

Hematite

Ti minerals

Non-Opaques

50 40 30

Strickland R.

10

Agu R.

Ok Tedi

Binge R.

30 20

39 54 73 93 107 123 141 163 176 200 219 237 282 315 348 387 424 482 552 633 700

B

% Mineral

% Mineral

Quartz

123 154 176 209 237 296 348 Distance downstream from Kiunga (km)

Strickland R.

99

Agu R.

73

Binge R.

45

Ok Tedi

2

20 10

0

0 2

44

73

98

124

154

180

209

237

296

348

404

552


C Quartz

Feldspar

Carbonate

Hornblende

Mica/Chlorite

2

659

44

73

98

Clay

Opaques

124

154

180

209

237

296

348

404

552

659


D Pyrite

Chalcopyrite

Goethite

Magnetite

Hematite

Ti minerals

Non-Opaques

93

Figure 2.17: Variation in mineral composition in Fly River sediments collected during WV03-11 (OTML, 2003b). (A) Variation in bed material; (B) variation in heavy mineral component of bed material; (C) variation in mineralogy of bank material; (D) variation in heavy mineral component of bank material.


50

Strickland R.

70

60

Agu R.

70

Binge R.

80

Ok Tedi

90

80

% Mineral

100

90

% Mineral

100

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these two minerals occur in almost equal quantities. Chlorite, biotite, amphibole, and traces of calcite and muscovite are also present in this reach. With some minor fluctuation, as evidenced by the scatter on the distribution diagram, mineral abundances thereafter remain more-or-less constant through to the Fly River delta. There is a suggestion in the data of a slight increase in the relative abundance of quartz with respect to feldspar in the reaches between the Binge and Agu Rivers and in the Lower Fly. Heavy minerals are an important component of the river-deposited sediments. Heavy liquid separation test work on bed sediments indicates that heavy minerals vary considerably from reach to reach (Table 2.4) but consistently exceed 2% of the total sediment. Table 2.4 shows that average heavy mineral content of the total sediment is just over 2% in the Upper Fly, almost 7% in the Middle Fly, and 2.7% in the Lower Fly. Significantly, one sample from the Middle Fly has a heavy mineral content of close to 30%. Figure 2.18 illustrates the downstream variation in the relative abundance of heavy minerals in the bed material of the Fly River. This plot shows that Table 2.4: Summary statistics for heavy mineral component of Fly River deposited sediment collected during research cruise WV03-11. Reach

n

Mean

Median

SD

Min

Max

Upper Fly Middle Fly Lower Fly

3 33 7

2.2 6.9 2.8

2.0 4.7 2.6

0.7 5.4 0.8

1.6 2.3 1.6

3.0 27.3 4.1

Wt% >3.32 Sp. Gr.Product


D'albertis Junction

30

Everill Junction

25 20 15 10 5 0 0

50 100 150 200 250 300 350 400 450 500 550 600 650 700 Distance downstream of Kiunga, km

Figure 2.18: Variation in the percent total heavy mineral content of bed sediments from Kiunga to the delta.


95

heavy mineral content is relatively low in the Upper Fly at between 1.6 and 3%. Just below D’Albertis Junction the heavy mineral content increases over the next few kilometers to a maximum value of 27% (near the village of Nukumba). Heavy mineral abundance then remains high (generally above 5%) for the next 100 km at which point it abruptly decreases to about 5 wt% and then progressively decreases to the river delta. Downstream of Everill Junction heavy mineral content is relatively constant averaging 2.7 wt% – a concentration similar to that seen in a single composite sample collected from the Strickland River (2.6 wt%). Table 2.5 presents a statistical summary of the estimated relative abundance of the heavy minerals identified in bed materials collected during the May 2003 research cruise (OTML, 2003b). This table indicates that the main heavy minerals present are magnetite (av. 27%) followed by hematite (13%), and the iron sulfide mineral, pyrite (9%). The ‘‘non-opaques,’’ which form the dominant component in the greater than 3.32 Specific Gravity (Sp. Gr.) product, is mainly composed of epidote, augite, and hypersthene. Samples collected from the Middle Fly are usually dominated by epidote while augite is the dominant non-opaque mineral in the Strickland River sample. In addition to the minerals noted above trace amounts of marcasite were observed in almost all samples collected and in the Middle Fly, trace amounts of copper minerals, bornite, chalcopyrite, idaite, covellite, and chalcocite were also identified. Molybdenite, galena, and pyrrhotite also occur in trace amounts in samples from the Middle Fly. Figure 2.17 above also demonstrates the variation in the proportions of heavy minerals in bed sediments. Figure 2.17B shows that pyrite, and to a lesser extent magnetite and hematite, increase abruptly in abundance over a short distance downstream of D’Albertis Junction reflecting input from the Ok Tedi. The relative proportions of these minerals are then maintained, Table 2.5: Estimated heavy mineral percentages for Fly River bed sediments collected during research cruise WV03-11. Pyrite Chalcopyrite Goethite Magnetite Hematite Ti-minerals Non-opaques n Mean Median SD Min Max

43 9 10 6 0 25


43 0 0 0 0 1

43 3 2 3 1 15

43 27 25 5 18 40

43 13 15 4 5 20

42 0 0 0 0 2

43 47 45 10 25 73

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with some minor fluctuations, over the next 315 km downstream from Kiunga. At this point there is a sudden increase in the relative proportion of pyrite (up to 25%), and to a lesser extent, goethite, mainly at the expense of non-opaque minerals. These high levels are maintained until Everill Junction where there is a rapid decrease, particularly in regard to pyrite, to levels not seen since the Upper Fly (at around 1–3%). The size of pyrite grains, the most important mineral in terms of ARD risk, varies downstream and is clearly influenced by input of material from the Ok Tedi mine. Figure 2.19 indicates that the maximum size of pyrite after decreasing along the Upper Fly suddenly increases at D’Albertis Junction to a maximum of about 200 mm at 58 km from Kiunga. The size of particles then progressively decreases over the next 200 km and thereafter remains more-or-less constant through to the delta. In addition to the visual estimation of pyrite particle size reported above, the o3.32 and W3.32 Sp. Gr. products of heavy liquid separation test work of some of the samples collected in the WV03-11 cruise (OTML, 2003b) were dry-screened at 500, 355, 250, 212, 150, 106, 75, 53, and 38 mm to determine their size distributions. The results of this work are shown in Figs. 2.20 and 2.21. The size distributions of the W3.32 Sp. Gr. and o3.32 Sp. Gr. fractions were found to be different. The o3.32 Sp. Gr. fraction was coarser than the ‘‘heavies’’ and covered a greater size range. This bimodal distribution 250 Maximum size of Pyrite (microns)

D'albertis Junction

Everill Junction

200

150

100

50

0 0

100

200

300

400

500

600

700

Distance downstream of Kiunga (km)

Figure 2.19: Variation in the size of the largest pyrite grains downstream from Kiunga.


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0119/CB - T13 (124 km)

100.0 Cumulative % Passing

90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 0.01

0.1 Particle Size (microns) Floats

1

Sinks

Figure 2.20: Size distribution plot showing characteristic curves for ‘‘sinks’’ (W3.32 Sp.Gr.) and ‘‘floats’’ (o3.32 Sp. Gr.) for a sample from the upper Middle Fly, 124 km downstream of Kiunga. between density fractions is not unexpected given that the sample is river sediment and, as such, has undergone natural hydraulic classification resulting in co-deposition of particles possessing similar settling velocities. The higher density material is balanced by a finer particle size compared to the lower density particles having coarser particle size. The disparity in size distributions and specific gravity of the two fractions are typical of mineral mixtures that have similar hydraulic settling velocities during co-deposition. Figure 2.20 is a typical size distribution plot illustrating the characteristic curve for light and heavy fractions found in the Middle Fly. Figure 2.21A shows that for the W3.32 Sp. Gr. products the d50 decreases in the Upper Fly until D’Albertis Junction at which point it increases over a short distance, as seen in Fig. 2.19 above, for maximum pyrite size. Median particle size continues to remain at relatively high levels for the next 200 km or so and then decreases rapidly to about 0.1 mm or less and remains at this level until Everill Junction. Downstream of Everill the d50 increases again under the influence of sediment from the Strickland River. A similar distribution pattern is also reflected in the curves for the d10, d80, and d95, indicating variations are consistent across both fine and coarse fractions. Figure 2.21B also shows the variation in grain size for the o3.32 Sp. Gr. separation products. An almost identical pattern of variation to that seen for the ‘‘heavy’’ products is clearly apparent.

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0.6 D'albertis Jct.

Grain Size (mm)

0.5

Everill Jct.

0.4

d10 d50

0.3

d80

0.2

d95

0.1 0 0

A

100

200

300

400

600

D'albertis Jct.

0.3

Everill Jct.

0.25 Grain Size (mm)

500


0.2

d10 d50

0.15

d80 d95

0.1 0.05 0 0

B

100

200

300

400

500

600


Figure 2.21: (A) Downstream variation in grain size for heavy minerals (W3.32 Sp. Gr.) in bed sediments from Fly River. (B) Downstream variation in the grain size of ‘‘floats’’ (o3.32 Sp. Gr.).

2.4.2.2. Mineralogy of the levees The mineralogy of samples collected from the crest of the levees during the 2003 research cruise (OTML, 2003b) is presented in Tables 2.6 and 2.7 and the variation in relative abundance of mineral species is shown in Fig. 2.17. Table 2.6 shows that the banks, consistent with the channel material, are dominantly composed of feldspar (49%) and quartz (33%) with minor amounts of clay, carbonate, and mica. Figure 2.17 shows the variation in mineral composition of levee sediments from Kiunga to the delta. As described for the bed sediments the most obvious feature of this plot is the


99

Table 2.6: Estimated mineral percentages for o3.32 Sp. Gr. component of levee crest sediments from WV03-11. Quartz Feldspar Carbonate Hornblende Mica/Chlorite Clay Opaques n Mean Median SD Min Max

28 33 30 11 20 65

28 49 55 14 24 65

28 4 3 3 0 10

28 0 0 0 0 1

28 3 2 2 1 10

28 7 5 6 2 30

28 5 4 3 2 15


Table 2.7: Estimated heavy mineral percentages for levee sediments from WV03-11. Pyrite Chalcopyrite Goethite Magnetite Hematite Ti-minerals n Mean Median SD Min Max Strickland

43 27 30 10 0.5 40 25

43 2 1 1 0 3 Tr

43 10 10 4 5 15 10

43 26 25 5 20 40 25

43 5 4.5 4 0 15 10

42 1 0 1 0 5 0

Nonopaques 43 31 30 5 20 40 30

Note: Strickland data from a single sample (OTML, 2003b). Tr ¼ trace.

large increase in relative proportion of feldspar with respect to quartz downstream of D’Albertis Junction. This trend persists as far as Everill Junction at which point the proportion of feldspar rapidly decreases coincident with an increase in the proportion of quartz and clay. The other major feature of the mineral distribution plot is the remarkable uniformity of the composition of the sediments overall, particularly between D’Albertis and Everill Junctions. The relative abundance and distribution of heavy minerals in the levee crests was also examined in this study. Analysis of the overall heavy mineral content of these sediments shows that heavy minerals comprise about 4 wt% of the total bulk sediments. Figure 2.22 shows the variation in total heavy mineral content of the left bank levee sediments collected in the 2003 research cruise (OTML, 2003b), from Kiunga to the delta. As shown for heavy minerals in the bed sediments,

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D'albertis Junction

Wt% >3.32 Sp. Gr. Product

9

Everill junction

8 7 6 5 4 3 2 1 0 0

50

100 150

200

250

300

350 400

450

500

550 600

650

700


Figure 2.22: Variation in the percent total heavy mineral content of left bank levee sediments from Kiunga to the delta. there is a sudden increase in their content downstream of D’Albertis Junction. This high proportion of heavy minerals persists (over 8% at 237 km downstream of Kiunga), except for a sustained decrease between about 150 and just over 200 km downstream of Kiunga, until about 300 km (just downstream of the confluence between the Agu and Fly Rivers). Thereafter the heavy mineral content progressively decreases, through Everill Junction and onward to a location close to the headwaters of the delta. Table 2.7 presents a summary of the relative abundance of the main heavy minerals identified in Fly River levee sediments in 2003 (OTML, 2003b). These data show that pyrite and magnetite are the major heavy minerals present in levee crest sediments. Non-opaque minerals such as epidote and augite, together account for the bulk of the heavy minerals in these deposits. This table also indicates that the relative abundance of heavy minerals in the Fly is similar to those seen in the banks of the Strickland River upstream of Everill Junction. The downstream variation in the relative abundance of heavy mineral species in sediments deposited on the levee of the Fly River in 2003 is shown in Fig. 2.18D. This figure shows that pyrite and hematite increase rapidly downstream of D’Albertis Junction and are maintained at relatively high levels through to a location near the Agu River confluence. Pyrite abundance then slowly decreases at the expense of non-opaque minerals. There appears to be no measurable change to this pattern downstream of Everill Junction under the influence of the Strickland. As noted above for bed sediments, the heavy mineral fraction of the levee crests also contain trace amounts of a distinctive suite of copper minerals


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including chalcocite, covellite, bornite, and idaite. Marcasite occurs in trace amounts throughout the system, including the single sample from the Strickland River bank.

2.4.2.3. Clay mineralogy

Relative abundance

Clay minerals constitute an important component of both the riverbed and levee deposits. Figure 2.23 shows the variation in clay mineral distribution in bed sediments from Kiunga to the Fly River delta, as determined from samples collected during OTML research cruise WV03-11 (OTML, 2003b). This figure indicates that clay/phyllosilicate mineralogy in bed sediments, while highly variable over relatively short distances, appears to characterize several river reaches. The Upper Fly is characterized by approximately equal amounts of illite-smectite, chlorite, and mica. Downstream of D’Albertis Junction, while the proportion of each mineral type varies widely over short distances, overall illite-smectite and mica dominate, with lesser and approximately equal amounts of the remaining clay mineral groups. Downstream of Everill Junction the dominant mineral is mica (up to about 60%; mainly biotite) and chlorite (20–30%). This shift toward increasing amounts of mica and chlorite reflects the input from the Strickland River. Samples analyzed from the single transect investigated during this cruise averaged 54% mica and 27% chlorite; the composite sample averaged 45% mica and 30% chlorite. One sample contained 80% mica and 20% chlorite. 100 90 80 70 60 50 40 30 20 10 0

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Figure 2.23: Distribution of clay minerals in bed sediments collected during WV03-11 (OTML, 2003b).

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Clay analyses were also performed on the samples collected from the levee crest. The results of this work are shown in Fig. 2.24. This figure shows that upstream of D’Albertis Junction the illite-smectite group of minerals dominates the clay fraction of the river bank sediments. Downstream of D’Albertis Junction, however, the proportion of mica minerals, together with kaolinite increase at the expense of illite-smectite minerals and this trend continues to about 200 km downstream of Kiunga. At this point micas account for approximately 50% of the clay fraction and chlorite replaces kaolinite as the second most abundant clay mineral. These proportions are then maintained, with some variation, through to the delta. Below Everill Junction there is an increase in the proportion of illite-smectite at the expense of kaolinite and smectite as the river approaches the delta. 2.4.2.4. Controls on mineralogical composition

Relative abundance

The composition of the Fly Riverbed sediments is controlled mainly by the composition of sediments delivered by its main tributaries, the Ok Tedi and the Strickland River. Upstream of D’Albertis Junction (confluence with the Ok Tedi), the Fly Riverbed is almost entirely composed of quartz with minor–trace amounts of feldspar, clay, and opaque minerals such as epidote, augite and hypersthene, heavy minerals, mainly magnetite and hematite (Fig. 2.17A). This composition is consistent with an upstream source area dominated by the sandstone, siltstone, mudstone, and limestone units of Mesozoic to Tertiary age found in the Blucher and Victor Emanuel Ranges. 100 90 80 70 60 50 40 30 20 10 0

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Figure 2.24: Distribution of clay minerals in bank (left) sediments collected during WV03-11 (OTML, 2003b).


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Downstream of D’Albertis Junction the composition abruptly changes. Plagioclase feldspar rapidly becomes the dominant mineral species in bed sediments together with slightly less abundant quartz. This composition is maintained, with some minor variation, through to the junction with the Strickland River, a further 410 km downstream (Fig. 2.17A). Bed sediments of the Middle Fly are further characterized by the presence of accessory chlorite, biotite, amphibole, and traces of calcite and muscovite. A suite of heavy minerals including magnetite, pyrite, and a variety of copper sulfide minerals are also characteristic of this reach (Fig. 2.17B). Significantly, this heavy mineral suite, after rapidly increasing at D’Albertis Junction, is maintained at elevated levels relative to both the Upper Fly and Lower Fly reaches. Also significant is a sudden increase in the relative proportions of pyrite and goethite, mainly at the expense of non-opaque minerals such as epidote and augite, in the reach between 282 and 456 km downstream from Kiunga. This change in the composition of the heavy mineral fraction coincides with a pronounced change in the grain size characteristics of the bed sediments in this reach with a sudden and persistent decrease in grain size (Fig. 2.6) and the grain size distribution (Fig. 2.7). We interpret this change in the proportion of heavy minerals to reflect a decrease in the flow conditions in this reach such that a greater proportion of pyrite along with magnetite are deposited in the riverbed. The mineral assemblage observed in the Middle Fly is very similar to that found in the Mount Fubilan orebody. The orebody is largely composed of a mesothermal stockwork and disseminated copper-gold mineralization hosted in an altered quartz monzonite porphyry stock of Plio-Pleistocene age (Rush and Seegers, 1990). High-grade mineralization also occurs in calc-silicate sulfide and magnetite skarns that have formed at the contact between intrusives and host sediments. Overburden which is released into the river system is dominantly composed of limestone and hornfelsed sandstones, siltstones, mudstones. The porphyries are characterized by large and approximately equal amounts of potassium (orthoclase) and sodic (andesine, oligoclase) feldspar, quartz, hydrothermal biotite, hornblende, and accessory apatite, sphene, rutile after sphene, and magnetite. Mineralized areas include a range of opaques, including pyrite, marcasite and pyrrhotite, a variety of copper sulfides (chalcopyrite, bornite, covellite, chalcocite), and hydrocarbonates (malachite, azurite), with the sulfides in various stages of oxidation (digenite, chalcocite, native copper, covellite, goethite, and cuprite). The limestones are predominantly calcitic in composition. Therefore, consistent with earlier workers (e.g., Hettler and Lehmann, 1995), we interpret the composition of bed sediments in the Middle Fly to largely reflect the input of Mount Fubilan mine wastes via the Ok Tedi.

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The main control on the distribution of these minerals along the Fly, downstream of the junction with the Ok Tedi, is the progressive decrease in carrying capacity of the river in the upper part of the Middle Fly resulting from a decrease in the slope of the riverbed brought about by sediment aggradation, and, for the lower Middle Fly, by reduced carrying capacity brought about by the backwater effect during times of high flow in the Strickland. The decrease in carrying capacity in the upper Middle Fly is further evidenced by the coincident decrease in heavy mineral abundance and the maximum size of pyrite grains (Fig. 2.19), as well as the overall d50 of the heavy mineral fraction (Fig. 2.21). Downstream of Everill Junction the composition of the bed sediment varies once more. As shown in Fig. 2.17A, there is a small but persistent increase in the amount of quartz relative to feldspar and more characteristically, a sudden decrease in the proportion of pyrite (and to a lesser extent goethite) at the expense of non-opaque minerals (Fig. 2.17B). The influence of the main tributaries, the Ok Tedi and Strickland, is also apparent in the composition of the levee sediments. Figure 2.17C shows the banks of the Upper Fly mainly composed of quartz and to a slightly lesser extent, plagioclase feldspar as well as minor amounts of carbonate (mainly calcite) and trace amounts of phyllosilicate (mica and chlorite) and nonopaques such as epidote. Again this is consistent with an upland source area dominated by terrigenous clastic sediments and limestone. Downstream of D’Albertis Junction the composition of the levee crest again changes abruptly with a sudden increase in the proportion of feldspar, mainly at the expense of quartz. Feldspar continues to dominate these sediments (B55–60%) through to Everill Junction where there is a sudden increase in quartz and most noticeably, clay content through to about half way to the estuary. From this location downstream, quartz continues to increase in abundance but mainly at the expense of clay minerals (Fig. 2.17C). The influence of the Ok Tedi and therefore the mine on the sediment composition is also reflected in the heavy mineral composition of the levee crests sediments. Fig. 2.17D shows a rapid increase in the proportion of pyrite as well as goethite downstream of D’Albertis Junction, largely at the expense of magnetite, hematite, and Ti-minerals. These mineral proportions are then maintained more or less, through to about 180 km downstream of Kiunga in the middle part of the Middle Fly. Thereafter the proportion of pyrite progressively decreases at the expense of goethite and non-opaque minerals. In contrast to bed sediments, there does not appear to be a sudden change in levee crest sediment composition due to influx of material from the Strickland River. Close examination of mineralogy variation plots from both the riverbed and levee crests (Fig. 2.17) indicates that apart from the Ok Tedi and


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Strickland River, there appears to be little evidence for significant input from the other tributaries joining the Fly, particularly in the Middle Fly reach. The clay mineralogy of deposited sediments collected is largely controlled by input from tributaries, mainly the Ok Tedi and Strickland. As noted above the dominant clay minerals of the Upper Fly are chlorite and mixed species, illite-smectite. Downstream of D’Albertis Junction, following input from the Ok Tedi, there is a rapid increase in the relative amount of smectite at the expense of the illite-smectite group of minerals. Further downstream the clay mineral shows considerable variation over short distances mainly reflected in the relative abundance of illite-smectite minerals as a component of the clay fraction (Fig. 2.23). The cause of this high degree of variability is uncertain; however, input from both smaller tributaries entering the Middle Fly together with erosion of deeply weathered bank material including older sediments, may be a factor. The influence of input of clay minerals from the Strickland River is evident downstream of Everill Junction with the sudden increase in the relative amount of chlorite in bed sediments together with mica at the expense of kaolinite, and illite-smectite group of minerals (Fig. 2.23). Kaolinite is largely restricted to the Upper and Middle Fly in its distribution in bed sediments. This pattern of clay mineral distribution is broadly mirrored in the clay mineral assemblages observed for the Fly River levees (Fig. 2.24). The Upper Fly is again dominantly composed of illite-smectite and chlorite. Downstream of D’Albertis Junction there is a rapid increase in the relative amount of smectite, mainly at the expense of illite-smectite, as seen with the bed sediments, at least in the upper Middle Fly (to about 150 km downstream of Kiunga). Further downstream the clay mineralogy of the levees is relatively constant and dominated by chlorite, smectite, and to a lesser extent kaolinite. Micas are the dominant phyllosilicate from D’Albertis Junction to the delta, averaging about 30–40% of the total. Downstream of Everill Junction, chlorite and to a lesser extent, illite-smectite minerals gradually increase at the expense of kaolinite and smectite. Again, most kaolinite is deposited in the Upper and Middle Fly.

2.4.2.5. Comparison with earlier studies Figure 2.25 shows a comparison between the estimated mineral abundances in data from 1979 and 2003 (Everett and Associates, 1980; OTML, 2003b). This figure shows that the composition of sediments in the bed of the Upper Fly has changed little with time. These sediments were, and continue to be, dominantly composed of quartz sand. The upper Middle Fly, in contrast,

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Figure 2.25: Plots of relative mineral abundance in bed sediments from the Fly and Strickland Rivers collected during the 1979 and 2003 (Everett and Associates, 1980; OTML, 2003b).


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shows considerable variation with time as evidenced by the change in the relative abundance of quartz and feldspar. In the 1979 survey this reach of the riverbed was dominated by quartz and to a far lesser extent, feldspar and opaques. In 2003 the bed was dominated by feldspar grains with moderate but lesser amounts of quartz particles. The amount of opaque mineral has also increased slightly in the most recent survey. In the lower Middle Fly and Lower Fly, while the proportion of feldspar has increased significantly relative to quartz, it is the large decrease in the abundance of clay minerals that characterize these two reaches. This change is interpreted to reflect the changing grain size distribution of the lower Middle Fly discussed above. The trend toward increasing amounts of silt-sized quartzo-felspathic material deposited, particularly under the influence of the Strickland River ‘‘backwater effect,’’ has diluted the dominant clay mineral deposition of pre-mine conditions. As might be expected, there is little evidence of any significant change in the composition of the bed materials in the Strickland River. Figure 2.25 shows that while feldspar has increased slightly, along with mica/chlorite and clay, in 2003 compared to 1979, the relative amounts of quartz and carbonate have decreased. What this comparison has shown is that the mineralogy of bed sediments has become dominantly feldspathic in the Middle Fly. Interestingly, there also appears to be an increase in the feldspathic component in the Strickland over the same time interval as well. In terms of the heavy mineral component the 2003 data show a small but significant increase in content in the upper Middle Fly as well as the lower Middle Fly. The Lower Fly and Strickland Rivers show a small decrease in the relative abundance of the heavy mineral component. The increase in the relative proportion of heavy mineral in the 2003 survey is consistent with the increasing impact of mine-derived materials on the composition of the bed sediments. The distribution of clay minerals as determined from the 2003 survey compared with that in Delft (1987) is shown in Fig. 2.26. This figure shows that clay mineralogy has changed considerably since the 1987 survey. The dominant clay of the Upper Fly (and lower Middle Fly) in 1987 was smectite. In 2003 the dominant clay was illite with slightly lesser amounts of chlorite (for the lower Middle Fly also). In 1987, under the influence of sediment input from the Strickland, the Lower Fly was dominated by illite. This is in contrast to 2003 when the dominant clay was found to be chlorite. Both surveys show illite and to a lesser extent, chlorite to be the most abundant clay minerals of the Strickland. The cause of the change in the Upper and Middle Fly from a clay mineral assemblage dominated by smectite to illite is

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80 70 60 50 40 30 20 10 0 Upper Fly (1987)

Upper Fly L. Middle L. Middle (2003) Fly (1987) Fly (2003) Smectite

Illite

L. Fly (1987) Kaolinite

L. Fly (2003)

Strickland Strickland (1987) (2003)

Chlorite

Figure 2.26: Comparative plot showing relative clay mineral content in o2 micron fraction of river sediments collected in 1987 (Delft, 1987; Salomon and Eagle, 1990) and 2003 (OTML, 2003b). unclear as is the change from illite to chlorite in the Lower Fly. Further work on the nature and distribution of these clay minerals is required to better understand the controlling processes.

2.5. Conclusions This review has shown that the texture, geochemistry, and mineralogy of the sediments deposited in the channel and on the levee banks of the Fly River system have been distinctly affected by the release of waste rock and tailings from the Mount Fubilan mine. Texturally, the sediments deposited in the channel of the Ok Tedi and Middle Fly have generally become finer since the start of mining in 1984 while levee sediments have coarsened slightly, particularly in the lower reaches of the Middle Fly. Metal concentrations and in particular that of copper, have increased markedly in deposited sediments, in some places by up to an order of magnitude above background levels. Similar increases have also been observed in sulfur abundance in levee sediments down through the system. This has largely been due to an increase in the proportion of mine-derived pyrite and other sulfide-bearing heavy minerals deposited during flooding events. This increase in sulfide minerals has led in turn to an increase in the risk of acid generation and metal leaching in periodically exposed levee sediments with a subsequent risk of adverse ecological impacts in downstream environments. These impacts, while varying in intensity, can be traced from the creeks surrounding the mine, down through the Ok Tedi and Middle Fly, to the Fly


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River delta – a total river distance of over 1,000 km. The lack of periodic monitoring of sediment characteristics prohibits a clear understanding of the rate of these changes but available data indicate substantial change, particularly in regard to sediment geochemistry, occurring within 10 years of the start of mining and near-pervasive change in all three parameters in the Ok Tedi and Middle Fly by 2003.

ACKNOWLEDGMENTS The authors wish to thank the management of Ok Tedi Mining Limited for their support in the preparation and publication of this chapter. We also wish to thank past and present staff members of the OTML Environment Department who are too many to name individually but without whose tireless efforts in often very trying conditions, the telling of this story would not be possible. Geoff Pickup and Jim Veness are thanked for providing constructive comments on an earlier version of the manuscript.

REFERENCES AMIRA (2002). ARD Test Handbook. AMIRA International, Melbourne. Apte, S. C. (2009). Biogeochemistry of copper in the Fly River. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 321–373. Blong, R. J. (1991). The magnitude and frequency of large landslides in the Ok Tedi catchment, Report to Ok Tedi Mining Ltd, Tabubil, Papua New Guinea, 62 pp. Bowen, H. J. M. (1979). Environmental Chemistry of the Elements. Academic Press, London, 333 pp. Boyden, C. R., Brown, B. E., Drucker, R. F., & Tuft, S. J. (1974). Report of the 1974 Cambridge Expedition to the Western District, Papua New Guinea. 42 pp. Davies, H., Howell, W. J. S., Fardon, R. S., Carter, R. J., & Bumstead, E. D. (1978). History of the Ok Tedi porphyry copper prospect. Economic Geology, 73(5), 796–809. Delft. (1987). The contribution of the Ok Tedi, Fly and Strickland river to sediments deposited in the delta. A feasibility study. Unpublished Report to Ok Tedi Mining Limited, dated July 1987, 11 pp. Dietrich, W. E., Day, G., & Parker, G. (1999). The Fly River, Papua New Guinea: Inferences about river dynamics, floodplain sedimentation and fate of sediment. In: A. J. Miller, & A. Gupta (Eds). Varieties of Fluvial Forms. John Wiley and Sons, New York, US, pp. 346–376. EGi (1991). Mine Rock Geochemistry and Acid Mine Drainage, Letter Report to Ok Tedi Mining Limited, Tabubil, Papua New Guinea.

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EGi (1996). Tailings Geochemistry, Unpublished Memorandum to Ok Tedi Mining Limited, dated 14 May, 1996, 6 pp. Everett & Associates (1980). Estimate of geochemical processes and chemical concentrations in the Fly River drainage that may result from development of the Ok Tedi project, Western Province, Papua New Guinea (2 volumes), Unpublished Report to Ok Tedi Mining Limited, Tabubil, Papua New Guinea. Geoff Day & Associates (1996). Particle size and shape of characteristics of deposited sediments in the Middle Fly River, and sediment deposition rates in the tie-channels and off-river water bodies: Volume one – main report, Unpublished Report to Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 20 pp. Gomez, B., Rosser, B. J., Peacock, D. H., Hicks, D. M., & Palmer, J. A. (2001). Downstream fining in a rapidly aggrading gravel bed river. Water Resources Research, 37, 1813–1823. Hettler, J. (1995). Bergbau und umwelt in Papua-Neuguinea: Die Pk Tedi-mine und das Fly River-Flubokosystem. Berliner Geowissenschaftliche Abhandlungen, Reihe A Reihe A, B, 176, 110. Hettler, J., & Lehmann, B. (1995). Environmental impact of large-scale mining in Papua New Guinea: Sedimentology and potential mobilisation of trace metals from mine-derived material deposited in the Fly River floodplain. South Pacific Regional Environment Programme, SPREP Reports and Studies Series 90: 1–71, Apia, Western Samoa. Hettler, J., Irion, G., & Lehmann, B. (1997). Environmental impact of mining waste disposal on a tropical lowland river system: A case study on the Ok Tedi mine, Papua New Guinea. Mineralium Deposita, 32, 280–291. Higgins, R. J., Pickup, G., & Cloke, P. S. (1987). Estimating the transport and deposition of mining waste at Ok Tedi. In: C. R. Thorne, J. C. Bathurst, & R. D. Hey (Eds). Sediment Transport in Gravel Bed Rivers. Wiley, London, pp. 949–976. Knighton, D. (1998). Fluvial Forms & Processes: A New Perspective. Arnold Publishing, London, 383 pp. Kyle, J. (1988). Water quality and sediment chemistry of Lakes Bosset, Pangua and Daviumbu. In: J. C. Pernetta (Ed.). Potential Impacts of Mining on the Fly River. United Nations Environment Programme Regional Seas Reports and Studies 99 and SPREP Topic Review 33, Nairobi, pp. 9–18. Kyle, J. H., & Ghani, H. (1982). Mercury concentrations in ten species of fish from Lake Murray. Science in New Guinea, 9, 48–58. Leopold, L. B., Wolman, M. G., & Miller, J. P. (1964). Fluvial Processes in Geomorphology. Freeman, San Francisco. Mackenzie, D. E., & Johnson, R. W. (1984). Pleistocene volcanoes of western Papua New Guinea highlands: Morphology, geology, petrography, and modal and chemical analyses. BMR Report 246, Microform 200. Markham, A. J., & Repp, K. (1992). Erosion and sediment transport in Papua New Guinea. Network design and monitoring. Case study: Ok Tedi copper mine: Erosion and sediment transport monitoring programmes in river basins, Proceedings of the Oslo Symposium, August 1992, pp. 517–526.


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Marshall, A. R. (2000). Ok Tedi-Fly River cross-section survey & sediment storage analysis. Epoch 3-June 2000, Unpublished Report to Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 17 pp. Marshall, A. R. (2003). Ok Mani storage estimate, Unpublished Memorandum Report to Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 3 pp. Maunsell & Partners (1982). Ok Tedi Environmental Study: Supporting Studies, Volume 4, Sedimentation analysis and results; chemical effects, Unpublished Report to Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 245 pp. OTML (1986). Ok Tedi mining limited sixth supplemental agreement environmental study: Review of hydrologic data for the Ok Tedi and Fly River catchments, Ok Tedi Mining Limited, Environment Department Report ENV/86-07, Tabubil, Papua New Guinea, 41 pp. OTML (1993). Fly River floodplain copper monitor (Addendum to the APL Compliance and Additional Environmental Monitoring Report 1993 Annual Report). OTML (1994). Fly River floodplain copper monitor (Addendum to the APL Compliance and Additional Environmental Monitoring Program: 1993/1994 Annual Report). OTML Report No. ENV 94-14 dated 1994. OTML (1997). APL compliance and additional monitoring program annual report1995/96, OTML Report ENV 97-01. Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 119 pp. OTML (2000). Hydrology Annual APL Report 1998–1999, Ok Tedi Mining Limited, Environment Department Report ENV2000-02, Tabubil, Papua New Guinea, 57 pp. OTML (2001). Hydrology Annual APL Report 1999–2000, Ok Tedi Mining Limited, Environment Department Report ENV2001-02, Tabubil, Papua New Guinea. OTML (2002). Annual Environmental Report FY02, OTML Report ENV020923. Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 155 pp. OTML (2003a). Annual Environmental Report FY03, OTML Report ENV030927. Ok Tedi Mining Limited, Tabubil, Papua New Guinea, 207 pp. OTML (2003b). WV03-11 Cruise Report: Sampling bed and suspended sediment load and levee bank deposits of Fly between Kiunga and ARM 80, OK Tedi Mining Limited, Environment Department Report ENV030530, Tabubil, Papua New Guinea, 13 pp. OTML (2004). WV03-11 Cruise Report: A report on the results of sediment sampling conducted during R.V. Western Venturer research cruise WV03-11 on the Fly River, May 2003, Ok Tedi Mining Limited, Environment Department Report ENV040919, dated 10th September 2004, 80 pp. OTML (2005). TC05-04 Report of Investigation: A Report on the Results of Sediment and Water Sampling and Ecological Soil, Plant, and Fish Sampling Conducted during R.V. Tahua Chief Research cruise TC05-04 on the Fly River, March 2005, 100 pp. Paola, C., Parker, G., Seal, R., Sinha, S. K., Southard, J. B., & Wilcock, P. R. (1992). Downstream fining by selective deposition in a laboratory flume. Science, 258, 1757–1760.

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Parker, G. (1991a). Selective sorting and abrasion of river gravel: Theory. Journal of Hydraulic Engineering, 117(2), 131–149. Parker, G. (1991b). Selective sorting and abrasion of river gravel: Applications. Journal of Hydraulic Engineering, 117(2), 150–171. Parker, G. K., & Robertson, A. (1999). Acid Drainage. Australian Minerals & Energy Environment Foundation, Melbourne, 227 pp. Pickup, G. (1984). Geomorphology of tropical rivers: 1. Landforms, hydrology and sedimentation in the Fly and lower Purari, Papua New Guinea. In: A. P. Schick (Ed.). Channel Processes – Water, Sediments, Catchment Controls. Catena Verlag, pp. 1–17. Catena Supplement 5: Cremlingen-Destedt. Pickup, G. (2009). Floodplain inundation modeling and forecasting for the Middle Fly. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 291–318. Pickup, G., & Cui, Y. (2009). Modeling the impact of tailings and waste rock disposal on the Fly River system. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 257–289. Pickup, G., & Marshall, A. R. (2009). Geomorphology, hydrology and climate of the Fly River System. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 3–49. Pickup, G., Higgins, R. J., & Warner, R. F. (1979). Impact of Waste Rock Disposal from the Proposed Ok Tedi Mine on the Fly River and Its Tributaries. Papua New Guinea Department of Minerals and Energy and Office of Environment and Conservation, Port Moresby, 139 pp. Pile, J. L., Bolton, B. R., Kundapen, H., & Davies, H. (2003). Geochemical characteristics of river deposited mine wastes and associated contact waters downstream of the Ok Tedi mine, Papua New Guinea – Implications for ARD management. In: Proceedings of 6th International Conference on Acid Rock Drainage, The Australian Institute of Mining and Metallurgy, Melbourne, pp. 163–172. Pile, J. L., Bolton, B. R., & Kundapen, H. (2005). Acid forming characteristics, hydrogeochemistry and sedimentology of gravel and sand bars in the upper Ok Tedi, Papua New Guinea. In: 7th Geology, Exploration and Mining Conference, Lae, Morobe Province, Papua New Guinea, May 2005. Rush, P. M., & Seegers, H. J. (1990). Ok Tedi copper-gold deposits. In: F. E. Hughes (Ed.). Geology of the Mineral Deposits of Australia and Papua New Guinea. The Australian Institute of Mining and Metallurgy, Melbourne, Australia, pp. 1747–1754. Salomon, W., & Eagle, A. M. (1990). Hydrology, sedimentology and the fate and distribution of copper in mine-related discharges in the Fly River system, Papua New Guinea. The Science of the Total Environment, 97/98, 315–334. Spencer, L. K. (1974). Sedimentation and geological history of the Fly River region, Papua, MSc. Preliminary Thesis, University of Sydney, Sydney, Australia, 72 pp.


Chapter 3

The Rapid Spread of Mine-Derived Sediment across the Middle Fly River Floodplain Geoff Day1, William E. Dietrich2,�, Joel C. Rowland2 and Andrew R. Marshall3 1

Newcrest Mining Ltd., Level 8, 600 St Kilda Road, Melbourne, Victoria, 3004, Australia 2 Department of Earth & Planetary Science, University of California, Berkeley, CA 94720, USA 3 Andrew Marshall & Associates Pty Ltd., 43 Warrangarree Drive, Woronora Heights, New South Wales 2233, Australia

3.1. Introduction The introduction of mining-related waste into the Fly River system by Ok Tedi Mining Limited (starting in 1985) suddenly elevated both the total amount of sediment and the concentration of copper in that sediment. Most of the tailings and the rock waste that was ground to fine sediment during transport traveled rapidly down the Ok Tedi, and entered the Middle Fly River (Fig. 3.1). Annual sediment load on the Fly increased approximately fivefold (Day et al., 2008). Concerns about the consequences of this sediment loading on the system led to several requirements in the 1989 Applied Particulate Level monitoring agreement with the Papua New Guinea government (OTML, 1990). Beginning in 1990 and continuing annually until 1994, a floodplain sampling program was conducted to quantify the deposition rate and copper concentration of sediments dispersed across the Middle Fly River floodplain. Given the very low background copper levels in the sediment, the detection of elevated copper not only demonstrated arrival of mine-derived sediment �Corresponding author. Tel.: 510-642-2633; Fax: 510-643-9980;

E-mail: [email protected] (W.E. Dietrich).

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Figure 3.1: Generalized depositional environments of the Fly River and

lower Strickland area (From Day et al., 2008; Journal of Geophysical Research,

American Geophysical Union).

Rapid Spread of Mine-Derived Sediment across Middle Fly River Floodplain

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but also gave us a time marker (1985, i.e., start of dumping) for the sediment accumulation. The initial sampling program called for 200 samples to be taken: 100 from the floodplain and 100 from off-river water bodies (ORWB) (OTML, 1993a, b). Previous estimates of historical sedimentation rates suggested that the deposition rate on average was about 1 mm yr�1 for the past 10,000 years (Pickup et al., 1979; Dietrich et al., 1999). This was suggested by the presence of pre-Holocene bright red sediment exposed in deep sections of the Fly River bed, the widespread preservation of scroll bars across the floodplain (Fig. 3.2), and the extensive regions of low elevation (backswamps) bordering the lower Middle Fly. Furthermore, the common observation of brown, sediment-rich flow along the mainstem Fly channel constrained by sediment-free black waters on the floodplain, even when the river was well above bankfull, suggested that advection of sediment-laden flows across the floodplain was prevented by the chronically flooded state of the surrounding floodplain (Dietrich et al., 1999; Day et al., 2008). These expectations of low sedimentation rates led the initial sampling program to collect and analyze only the first 1 cm of floodplain sediments.

Figure 3.2: Aerial view of the forested upper Middle Fly in 1990. Flow is from top to bottom, average channel width is about 320 m, and horizontal distance from top to bottom of the scene is about 4 km (north is at top of image). River entering from east is the Binge (see Fig. 3.1). Note the tie channels connecting the mainstem to oxbows and blocked valley lakes, and the extensive areas of scroll bars.

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Early findings, however, revealed that the rate and extent of floodplain deposition of mine-derived sediment was much greater than expected. Hence, we had to modify and amplify our sampling program. We added a systematic survey along 17 transects and took cores up to 1 m deep which allowed us to document the spatial pattern of deposition and the rate more reliably. Our observations also prompted a hydrologic study to document outflows and water levels across the floodplain. Here we report the findings of the sedimentation study which demonstrate that suspended sediment on the Fly is dispersed over a surprisingly large distance via tie channels and tributaries. This creates what Day et al. (2008) have called a ‘‘depositional web.’’ Many of the detailed observations reported here are summarized in the recent Day et al. (2008) publication. Sedimentation is influenced by sea-level rise, and Lauer et al. (2008) use numerical modeling to infer that the Fly aggraded only about 10 m from low sea stand during the glacial maximum to present levels. Aalto et al. (2008) report floodplain deposition rates for the Strickland River based on 210Pb analysis of core samples which compare favorably with rates documented over a shorter time-scale from mine tracer studies (Swanson et al. 2008). These rates are locally much faster than that found on the Fly. This chapter on the Fly River provides more detailed reporting of the sampling strategy and documented sedimentation patterns and then considers the environmental consequences of these observations.

3.2. Methods 3.2.1. APL 200 Sampling Program The annual coring program between 1990 and 1994 was established according to the protocol detailed in the ‘‘Floodplain Copper Monitor’’ section of the ‘‘Acceptable Particulate Level (APL) And Additional Environmental Monitoring Program’’ (OTML, 1990) which describes Ok Tedi Mining Limited’s (OTML) monitoring program on the physical, biological, and geochemical effects of the mine’s fluvial waste disposal. The APL protocol involved establishing a grid cell network dividing the floodplain into 10 equal-area reaches, or river-zones, by adjusting the north– south dimensions of each zone. This procedure produced river-zones with short north–south extent where the floodplain is widest. Within each riverzone, five equal area zone-bands were delineated across the floodplain by dividing each 1 km northing into five equidistant units across the floodplain


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and joining them downriver by interpolation. This created five zone-bands per river-zone, giving a total of 50 floodplain zone-bands, or grid cells, between D’Albertis and Everill junctions. From within each of the 50 zonebands, two sediment cores were collected from floodplain sites and two from ORWB sites (total of 200 samples) and the particulate copper (pCu) in the top 5–10 mm analyzed. Figure 3.3 shows the layout of the zone-band sampling grid along with the site codes for the 200 zone-band core locations; the coordinates of each sample location and the measured pCu are reported in Appendix 1. Samples were only collected within those areas of the zonebands that were east of the Papua New Guinea border with Indonesia. Core samples were collected from a float-equipped helicopter due to the difficult access throughout the Middle Fly resulting from the thick vegetation and the large floodplain area to be sampled. An early model single-frequency GPS receiver (JRL model) with position accuracy of approximately 100 m radius, and visual observation were used to relocate the 200 zone-band sample locations each year. The selection of the two floodplain sites within each zone-band was governed primarily by helicopter access and where this was not a constraint, cores were generally collected 0.25 and 0.75 of the distance along the length of each zone-band, as close as possible to the middle of the zone-band. Cores from oxbows were generally collected about halfway along the length and in the middle of each oxbow; blocked valley lakes (BVL) were usually sampled in the center of the lake. Depending on water depth at each location, cores were collected using a specially made hand corer or a commercially available KBTM gravity corer. Both corers were constructed of 50 mm diameter stainless-steel tube with interchangeable polycarbonate core liners to aid in sampling and to avoid contamination between cores. The length of cores collected ranged from 0.05 to 1 m. In 1993, the polycarbonate core liners were modified with a series of 6 mm slits every 20 mm along the length of the liner to achieve greater control over the thickness of collected subsamples. 3.2.2. Transect Sampling Starting in 1992, sampling along prescribed transects was initiated. One transect was located in each of the river-zones defined in the APL survey. Where helicopter access was possible, the spacing of cores along each transect was generally equidistant. Review of the 1992 pCu results showed that the equidistant core spacing did not adequately capture the higher deposition occurring closer to the channel, so the transect program was further modified in 1993 and repeated in 1994.

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Oxbow lake sample Floodplain sample

PNG

Irian Jaya

Zone 10

Zone 9

Zone 8

Zone 7

Irian Jaya

Zone 6

PNG

Figure 3.3: Floodplain sample locations for the initial APL program. This

shows the APL system of zones and sample strips (delineated by dashed lines).


119

Oxbow lake sample Floodplain sample

Zone 5

Zone 4

Zone 3

Zone 2

Papua New Guinea Irian Jaya

Zone 1

Figure 3.3: (Continued).

The 1993 and 1994 revised transect program involved closer core spacing nearer to channels and increasing the spacing between cores further from the channels. Seventeen transects were established, one approximately every 10 km (down valley) along the Middle Fly (Fig. 3.4). Where helicopter access permitted, cores were collected from: the top of the main channel levee, 50, 100, 250, 500, and then every 500 m to the floodplain boundary along each transect. Depending on floodplain width and helicopter access, between 5 and 30 cores were collected along each of the 17 transects in addition to the

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Figure 3.4: Map of entire Middle Fly River showing APL points and transect sample locations. Labels (T1, T2, etc.) indicate transect identifica tion numbers. Sample sites not along transects record the location of the original 200 APL sites and the additional oxbows analyzed (reproduced from Day et al., 2008 with permission from the American Geophysical Union). 200 cores from the APL zone-band program. Extra cores were also collected from within the ORWB. Within each oxbow, three cores (in the middle and 10 m from each bank) were collected from three transects across each oxbow (both ends and the center of the oxbow), resulting in nine cores per oxbow. BVL vary significantly in size and shape, and additional cores collected from these lakes were based arbitrarily on increasing the number of cores according to lake size. In 1993 and 1994, the transect cores as well as each of the 200 APL zoneband cores were sampled from several horizons to determine the thickness of copper-rich sediment. While the core sample locations remained the same over the 2 years, the horizons from which subsamples were collected varied. In 1993, each core was sampled from, on average, three horizons including: 0–6, 95–101 mm, and the base of the core. If the core was less than 100 mm long,


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then the top and bottom 6 mm was sampled. The pCu results from the 1993 cores revealed that spacing between these horizons was too coarse, and in 1994 the horizons sampled generally included 0–6, 20–26, 60–66, 100–106 mm, and the base of the core. In some instances, particularly at the bottom of the deeper oxbow lakes, the retrieved core was poorly consolidated and comprised a slurry of water and sediment. In such cases, a subsample of the entire slurry was analyzed, representing an average pCu over the length of the collected core. 3.2.3. Sample Variance Test The 840 core locations represent only about 1.5 m2 of the W3 � 109 m2 of floodplain surface. To determine how representative the core samples were from this low sampling density, in 1991 multiple cores were collected from 10 of the 200 APL zone-band sites sampled in 1990. Based on the 1990 results, five floodplain and five ORWB sites were chosen covering a range of pCu, and at each site 10 cores were collected randomly within a 3 m radius. 3.2.4. Cu Analyses With the various modifications made to the sampling program between 1990 and 1994, cores were collected from a total of 423 floodplain and 420 ORWB sites with approximately 4,000 samples being analyzed for pCu. Samples were thawed and wet-sieved through a 100 mm mesh nylon sieve as per the OTML APL protocol (OTML, 1990). The purpose of the sieving was to ensure that the analysis specifically targeted copper-rich sediment from the mine, given the maximum grain size of the copper-rich mine-derived sediment was o100 mm (OTML, 1989). The sediment passing the sieve was dried at 1041C, digested with hot acid and the pCu analyzed by flame atomic absorption spectroscopy using standard analytical procedures and quality control protocols. All pCu results were reported on a microgram copper per gram of sediment dry weight basis. Note that the 1994 pCu results from the 200 APL zone-band sites are not reported due to an unresolved analytical problem at the OTML Laboratory. 3.2.5. Grain-Size Analysis In 1995, transect cores were collected and used for grain-size analysis. Grainsize analysis of deposited floodplain sediment was performed using a Coulter

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LS130 Laser Diffraction Analyzer (Beckman–Coulter Corporation). The LS130 calculates grain-size distribution based on the laser diffraction pattern of a sample for all particles in the effective diameter range of 0.4–940 mm. The method is not a direct measurement of sediment grain size, rather it is a statistical approximation based on the diffraction pattern of the whole sample. The method is based on several important operational assumptions in relation to sample homogeneity, shape, and refractive index. It also does not take into account particle density, other than in the pump speed used to keep all particles fully suspended during analysis. Results are reported as volume percent of sediment within 74 size classes, rather than the traditional weight percent within a size class. Operational efficiency was a consideration in the choice of using laser diffraction for the grain-size analysis. Other methods of grain-size analysis, such as pipette sedimentation or Sedigraph analysis which may provide more physically relevant information in relation to deposition, were found to be too time consuming for the number of samples analyzed. One of the most critical factors in using the LS130 is sample preparation. Sample pretreatment and analysis required extensive test-work to ensure: (1) particle segregation during sample preparation and analysis, and (2) the subsample analyzed was representative of what was collected in the field. During the initial test-work, it was determined that chemical dispersants, which are sometimes used for grain-size analysis to disaggregate cohesive fine-grained sediments, were not required. Extensive testing by the manufacturer and ongoing quality control analysis as part of the floodplain sample analyses (including certified reference materials) provided reasonable confidence that the method produced a good approximation to the grain-size distribution of the sediments analyzed. Microscopy of core sample thin sections was also performed as a check on the LS130 results and provided qualitative confirmation on the grain sizes reported. Initial results of floodplain samples often showed distinctive tails at the upper grain sizes of the distribution. In such cases, the reported grain sizes were so large that it was extremely unlikely that sediment of the size indicated were transported under known hydrodynamic conditions across the flood plain. These same samples also had observable quantities of coarse particulate organic matter (CPOM) consisting of leaf litter, twigs and grass fragments, only some of which could be removed by sieving the sample. These samples were subsequently combusted at 5501C for 8–12 h to determine the quantity of CPOM present and assess if the distribution tails were removed by this process. A large number of floodplain samples required combustion based on either visual presence of CPOM or where tails in the size distribution plots


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were evident. Combustion was not required for ORWB and river sediment as they generally had insignificant amounts of CPOM. Suspended sediment and core samples were prepared differently for grainsize analysis. Core samples were air dried, or combusted as required, and transferred to plastic bags where large aggregates were broken apart by hand or by gentle crushing with a roller and then thoroughly mixed in the plastic bag. An aliquot of water was added and a portion of the sediment suspension was transferred to a 50 ml beaker and made up to approximately 40 ml with water. The beakers were then placed in an ultrasonic bath for between 5 and 10 min to disaggregate further the sediment particles immediately prior to analysis. The sediment concentration in the river and tie channel suspended sediment samples was generally too low for the LS130 to measure grain size directly and required preconcentration prior to analysis. The samples, collected in 500 and 1,000 ml plastic bottles, were transferred to 1,000 ml plastic separating funnels and allowed to settle. About every 6–8 h, the settled sediment at the base of the funnel was collected in 50 ml plastic vials. The funnels were then swirled to resuspend particles adhered to the funnel surface, which were then allowed to settle again. This process was repeated 3–5 times. 3.2.6. Calculation of Deposition Rate As described by Swanson et al. (2008) and Day et al. (2008), there are two ways to use vertical profiles of tracer metal concentration. The simplest is to assume that the deepest occurrence of elevated metal records the arrival of mine-derived sediment. Dividing the thickness of the overlying core by the time since start of mine-waste discharge gives an annual deposition rate. This was the preferred approach by Swanson et al. (2008) for samples collected on the Strickland floodplain upstream of the junction with the Fly River. The alternative is to allow for the possibility that sediment, once deposited, may be subjected to bioturbation and physical mixing (associated with mud cracking), leading to anomalously deep penetration of mine-derived sediment and to metal concentrations well below that arriving in the suspended sediment. Vertical variation in metal concentration could also arise from postdeposition dissolution or by temporal variation in arriving suspended sediment concentration. As reported by Day et al. (2008), these latter two effects appear to be unimportant on the Fly. Suspended samples collected near the Ok Tedi Junction indicate pCu values of 800 mg g�1 by the late 1980s, and from 1990 to 1994 more intense sampling of suspended load documented a systematic increase from 900 to 1300 mg g�1. These values, however, are all greatly in excess of the elevated values typically found at

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depth in the core samples. Also, for this period of observation, field measurements of pore waters did not indicate copper remobilization post deposition (Day et al., 2008). Hence, we consider profiles of pCu that decline significantly with depth to be a result of bioturbation. Here we summarize the method described by Day et al. (2008) for calculating deposition rates in which bioturbation is assumed to occur. Day et al. (2008) derive the following expression for calculating the total thickness of copper-rich sediment (LCu) from a vertical profile of pCu measurements (Fig. 3.5): LCu ¼

n X i¼1

zi � rb ð�si � �b Þ rc ð�ci � �si Þ � rb ð�b � �si Þ

(3.1)

εs1 εs2

εs3

z1 z2

Lcu

ρc

z3

Lcu = ∑ ni=1 εs4

zi · ρb (εsi − εb) (ρc (εci − εsi ) − ρb (ρc (εb − εsi )

z4 ρb, εb

Figure 3.5: Schematic diagram of a sediment core with mixing between incoming Cu-rich (green) and pre-mine, Cu-poor (brown) floodplain sediments. The diagram on the left shows graphically the effect of mixing on measured pCu (color gradation). The diagram on the right provides definitions of the components of the mass balance calculations used to determine floodplain deposition rates based on the Cu inventory of the core as described in the text.


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In essence, for each of the subsample length zi, the ratio of the other terms range from zero (when measured sample concentration, �si , equals back ground concentration, eb) to 1.0 (when measured concentration equals the concentration of the incoming contaminated sediment, �ci ). In Eq. (3.1), the background bulk density is rb and the bulk density of copper-enriched sediment is rc. The average bulk density of five core subsamples from different locations (each 5 cm in length) of both entirely copper-rich sediment deposits and background floodplain sediments was measured. A mean value of 1.2 g cm�3 was obtained for the copper-rich sediment deposits. Back ground bulk density, varied depending on whether the deposits were mineralsediment dominated or organic-sediment dominated (such as occurs extensively throughout much of the backswamp areas). The average bulk densities of mineral and organic sediments were 1.1 and 0.5 g cm�3, respectively. Based on deep and distant samples, eb for mineral-rich samples is approximately 31 mg g�1 and for organic-rich samples it is 15 mg g�1. To account for variations in suspended sediment concentrations with distance downstream and in time, we varied the value of �ci based on location and depth. The samples nearest to the surface were assigned �ci values corresponding to the year of sample collection and location along the river (Table 3.1). Deeper samples were assigned earlier values, with suspended load concentrations measured in 1991 assigned to all deep samples (Table 3.1). If �sn 4�b (i.e., the core had not sampled all the way through the copper-rich sediment), a value of zi for this particular horizon subsample was rounded up to the next 50 or 100 mm based on a review of the [pCu] through the core profile. In 20 cases, the measured core concentration exceeded the assigned incoming concentration. For these cases, the incoming concentration was used for the core concentration in the sediment. 3.2.7. Topographic Surveys Additional floodplain cross-sections and spot height surveys were performed in 1997 using dual frequency ZXII Ashtech Global Positioning System Table 3.1: pCu mg g�1 in suspended load samples during the period 1990–1994 at two OTML monitoring stations just downstream from the Ok Tedi River (Nukumba) and just upstream from the junction with the Strickland (Obo). Stations

1990

1991

1992

1993

1994

Nukumba Obo

900 700

900 700

1000 800

1100 1000

1300

1200

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(GPS) receivers in kinematic and static modes. High-resolution static GPS measurements were made for ground control of the aerial photography and at 69 water level recorder sites throughout the floodplain used to examine floodplain hydrodynamics (Day et al., 2008). Kinematic GPS measurements were made along each of the 17 floodplain coring transects. The detailed GPS and aerial survey work for this project was performed by Andrew Marshall & Associates, Sydney, Australia. The satellite imagery used for the GIS base map was a Landsat TM image (path 100; rows 64 and 65; and bands 3, 4, and 5) captured on January 10, 1998. Two sets of aerial photography (1984 and 1992) were conducted by BHP Engineering, Australia on behalf of OTML. The accuracy of each type of survey varied. Vertical accuracy ranged from: 72.0 m (aerial photography); 70.3 to 70.5 m (laser surveys); 70.1 to 70.2 m (kinematic GPS); 70.01 m (locally) to 70.05 m (regionally) for static DGPS; and 70.001 m locally for the level and staff surveys. Horizontal accuracy for each was 50–75% of the vertical accuracy. The GIS was used to examine: (i) the distribution of copper-rich sediment across the floodplain; and (ii) to model the results of copper-rich sediment thickness from which the total flux of sediment across the floodplain was calculated. For this GIS work ArcView GIS 3.2 (Environmental Systems Research Institute, Inc.) was used. The first step in establishing the GIS was to define: (i) the floodplain boundary; and (ii) delineate high-elevation areas within the floodplain boundary above the level of maximum inundation. A mask (a theme or layer within the GIS) was draped over high-elevation areas above the level of maximum inundation where deposition does not occur. The floodplain boundary was assigned based on a combination of satellite imagery, aerial photography, and field observations of maximum sediment-laden Fly River water inundation. The mask areas were delineated based on field observations and elevation data from the 1992 aerial photography. Masked areas included the remnant Pleistocene terraces (e.g., Kuambit and Manda) and the high-elevation areas to the east of the Agu River in the vicinity of Kuem Village, for example. Excluding the boundary and masked regions, the floodplain area was calculated to be 3,300 km2, which is larger than the 2,600 km2 reported by Pickup et al. (1979).

3.3. Patterns and Rates of Floodplain Deposition of Mine-Derived Sediment The two core sampling protocols described above provide two data sets. Data from the 1990–1993 surface samples from the APL zone-band program


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were used to construct histograms of the number of samples with elevated pCu over time. These data were also used to document the spatial distribution (not total sediment deposition) of copper-rich sediment using the GIS. The 1993 zone-band and the 1993 and 1994 transect depth profile samples provided the data to determine, both numerically and by GIS, the rate of sediment deposition and the percentage of the river’s suspended sediment load deposited across the floodplain. These analyses are based on pCu samples which had sampling uncertainty associated with each collection. Table 3.2 shows the results of 10 replicate samples at various ORWB and floodplain samples taken at 10 different locations at the time of the original APL coring program. The coefficient of variation ranged from 2 to 108% with an average of 42%. This is a significant uncertainty, but as subsequent analysis shows, this variance does not obscure strong spatial and temporal trends; hence, we think our conclusions are quantitatively sound.

3.3.1. Spatial and Temporal Pattern of the Spread of Mine-Elevated pCu Figure 3.6 shows the frequency of occurrence of pCu for samples in the ORWB sites and across the floodplain for the 200 APL samples collected annually during the period 1990–1993. In 1990, about 70% of the floodplain samples were at, or close to, background pCu (o30 mg g�1) values, reflecting the early stages of copper-rich sediment deposition across the floodplain even though the mine had been operating since 1984 (Fig. 3.6a). Between 1990 and 1993, the left-skewed distribution progressively shifted to a strongly rightskewed distribution as copper-contaminated sediment spread throughout the floodplain. In contrast, the initial 1990 ORWB data show a clear bimodal distribution of pCu reflecting background (pre-mine) sediment and copperrich sediment (Fig. 3.6b). Even by 1990, approximately 75% of ORWB sites had pCu elevated above pre-mine conditions and this increased to more than 95% by 1992. This records the rapid dispersion via tie and tributary channels. The temporal change in the spatial distribution of copper-rich sediment is mapped in Fig. 3.7. The data shown are for pCu at the sediment surface (approximately first 6 mm), not the deposition thickness or rate. The data show that in 1990, elevated pCu sediments were generally confined to core locations in the forest reach and sites close to the river (Fig. 3.7a). In just three years (by 1993), this pattern of deposition changed dramatically (Fig. 3.7b). Mine-derived sediment by this time had traveled great distances, in some cases tens of kilometers up tributary channels and out tie channels, dispersing widely across the floodplain. Note that for the upper half of the

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Table 3.2: Results from the analyses of 10 replicate samples from 10 different locations from the Original APL

Floodplain Coring Program throughout the Middle Fly River floodplain.

Site

Raw data (mg/g) dry weight

Mean

s.d.

c.v. (%)

W10 W87 W42 W24 W25 16 98 95 31 42

547, 1003, 1011, 318, 953, 1237, 1441, 792, 1321, 722 306, 972, 744, 884, 832, 1018, 1032, 719, 260, 258 8, 55, 86, 10, 34, 26, 46, 77, 26, 40 52, 427, 117, 112, 41, 36, 111, 161, 566, 55 777, 844, 783, 476, 319, 838, 882, 856, 242, 746 818, 774, 792, 781, 777, 768, 806, 747, 792, 780 272, 322, 380, 55, 669, 235, 603, 326, 84, 1162 1256, 1287, 1311, 1318, 1277, 1294, 1291, 1269, 1280, 1149, 1229 52, 52, 84, 67, 75, 80, 53, 69, 60, 73 10, 8, 17, 14, 14, 22, 10, 14, 18, 18

934 702 41 168 676 784 411 1269 66 14

350 313 26 180 238 20 328 49 12 4

38 45 64 108 35 2 80 4 18 30

Note: The water body (ORWB) site numbers are preceded by W.


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40 a. 35

Floodplain samples

Number of samples

30

90 91 92 93

25 20 15 10 5 0 10

100

1000

pCu (ug/g) 40

b.

35

Number of samples

30

90 91 92 93

ORWB samples

25 20 15 10 5 0 10

100

1000

pCu (ug/g)

Figure 3.6: Histograms of pCu in (a) shallow floodplain cores and (b) offriver water bodies (ORWB) between 1990 and 1993. maps shown in Fig. 3.7, the western side of the Fly, lying in Indonesian territory, was inaccessible and no samples were collected. Note, too, that the 1994 pCu results from the 200 APL zone-band sites are not reported due to an unresolved analytical problem at the OTML Laboratory.

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Figure 3.7: Distribution and magnitude of pCu in floodplain surface samples along the Middle Fly River in 1990 and 1993. Comparison of the two maps highlights both the downstream progression of pCu distribution along the Middle Fly and the increase in pCu across the entire floodplain system. The junction of the Middle Fly and Strickland rivers is located in the bottom right of each image.

3.3.2. Rates of Deposition Across the Floodplain The average pCu of core surface samples decreased exponentially as a function of distance over the first 1 km from the nearest channel bank (mainstem, tie channel, tributary, or ORWB) for the transect samples collected in 1993 and 1994 (Fig. 3.8). At the channel bank, the concentra tions were similar to the incoming values of the suspended load. By 1 km from the bank, values approached background concentrations, but remained above estimated background values of 15–31 mg g�1 well across the


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10000 1993 Transect data 1994 Transect data

pCu (ug/g)

1000

100

10

1 0.0

5.0

10.0

15.0

20.0

25.0

30.0

Shortest distance to channel bank, km

Figure 3.8: Surface pCu in samples collected along the 17 transects in 1993 and 1994. Data from distal tie channels are not included. floodplain. The data plotted in Fig. 3.8 do not include low values found near tie channels, which are at great distance from the mainstem Fly. For the 1993 and 1994 transect surveys, deposition rate of sediment based on the application of Eq. (3.1) also decreases exponentially for the first 1 km (Fig. 3.9). The exponential fit was chosen in part due to its use in other studies of overbank deposition rates (Bridge, 2003). The data shown represent cumulative deposition from the start of mining to 1993 and 1994, respectively, and not an annual rate. For the distance beyond 1 km from the nearest bank, the cumulative deposition shown in Fig. 3.9 is between 0 and 1 mm since mining commenced with an average cumulative deposition of 0.5 and 0.7 mm by 1993 and 1994, respectively. We grouped deposition thickness versus distance data into two classifications (reach types and nearest channel types) and tested for significance of regression statistics for the first 1 km of deposition. The reach type consisted of forest, transition, or swamp (Fig. 3.1). We hypothesized that the forest reach may experience the greatest deposition rate because of visibly stronger overbank flows across the floodplain, although one could also argue that the swamp reach, with longer periods of flooding might trap more sediment. Our second grouping was by the channel type closest to the sample site: the mainstem Fly River, a tie or tributary channel or any channel type (no distinction made). We expected the overbank deposition rate to be less on tie and tributary channels because they carry sediment away from the mainstem source. Separate exponential functions for the first 1 km of rapid decline were derived for each of

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Equivalent depth of mine-derived sediment (mm)

132

1000

1993

100

10

1

0.1 0.01 0.001 0

1

2

3

4

5

6

7

8

9

10

Equivalent depth of mine-derived sediment (mm)

Shortest distance from a source channel (km) (a)

1000 1994 100 10

1

0.1 0.01 0.001 0

1

2

3

4

5

6

7

8

9

10

Shortest distance from a source channel (km) (b)

Figure 3.9: Cumulative deposition of sediment by (a) 1993 and (b) 1994, based on the 17 transect samples. the sorted datasets for both 1993 and 1994 data. Linear regression analysis of each of the above test variables (reach and channel type) was performed by comparing the slope and intercept of the exponential functions using the one-tailed t test for slope and two-tailed t test for the intercept (Zar, 1984, Chapter 18). Significance was determined at the Po0.05 level. Table 3.3 summarizes the regression statistics of exponential fits for the first 1 km distance from the channel. The exponential functions describe the


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Table 3.3: Regression results of fits of exponential function, d ¼ ae�bx , for all samples collected in 1993 and 1994 distinguished by floodplain type (forest, transition, swamp) and closest channel (mainstem Fly or floodplain channel, i.e., tie channels, tributaries, TC, and off-river water bodies, ORWB). a (mm)

R2

b (1/km)

Forest Trans. Swamp Forest Trans. Swamp Forest Trans. Swamp 1993 Data All channels Fly R. only TC/ORWB only

243 243 245

165 169 159

139 128 179

3.79 3.78 3.82

3.69 3.66 3.60

3.23 2.92 3.77

0.96 0.95 0.94

0.97 0.96 0.98

0.85 0.81 0.89

1994 Data All channels Fly R. only TC/ORWB only

288 307 204

169 187 119

122 113 187

3.64 3.62 3.36

3.18 3.20 2.70

2.45 2.04 3.59

0.92 0.91 0.94

0.90 0.87 0.93

0.75 0.70 0.93

Note: The distance from the channel, x, is in kilometers, and a is deposition in millimeters since start of mine loading.

rate of decline in deposition with distance from a channel. The expression takes the form, d ¼ ae�bx , in which d is the total sediment deposition (in millimeters) since the start of elevated mine-derived sediments delivered to the system, a is the deposition at the bank (x ¼ 0), b has units of km�1, and x is the distance from the channel bank (in kilometers). Deposition decreases more rapidly with larger values of b (due to the negative sign). Linear regression analysis comparing the slopes and intercepts of the exponential functions were used to determine if differences existed between the test variables (reach and channel type). The regression tests for 1993 showed significant differences in deposition between floodplain reach type, i.e., deposition in each reach is described by a separate exponential function, and the rate of deposition decreases from forested reach to swamp grass. Tests for channel type showed no significant difference between any of the channel groups in the forest or transition reach. In the swamp reach, however, the exponential function representing the tie channels differed from that for mainstem Fly River. If accurate, this difference indicates that the amount of floodplain deposition from the tie channels is greater than that from the mainstem Fly as indicated by the higher values of the exponential constants for the tie channel compared to the mainstem Fly (Table 3.3).

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In comparison, the regression tests for 1994 showed no significant differences between any of the test groups (reach or channel type). The reasons for the apparent difference between 1993 and 1994 statistical results may be due to the decreased sample size in 1994 (n ¼ 146) compared to 1993 (n ¼ 276), and the resultant decreased statistical power of the analysis (note ‘‘n’’ represents the number of floodplain samples within 1 km of a channel and does not include oxbow samples or samples W1 km from a channel). The decreased sample number in 1994 is a consequence of an unresolved analytical problem in the 1994 APL zone-band samples. To calculate the total deposition on the floodplain based on the best-fit exponential relationships, we use a GIS model in which the appropriate deposition-distance function is applied to each reach of the floodplain. Based on the regression analysis of the 1993 data, the following exponential functions were used as input to the GIS model for calculating the deposition thickness within 1 km of any channel: d ¼ 243e�3.79x d ¼ 165e�3.69x d ¼ 128e�2.92x d ¼ 179e�3.77x tributary.

for the forest reach, for the transition reach, for the swamp reach within 1 km of the Fly River, and for the swamp reach within 1 km of a tie channel or

While no significant difference existed in deposition between reach or channel type in the 1994 data, the same groups used for the 1993 calculations were used for 1994 to ensure consistency between years. The GIS model was run using the following exponentials for 1994: d ¼ 288e�3.64x d ¼ 169e�3.18x d ¼ 113e�2.04x d ¼ 187e�3.59x tributary.

for the forest reach, for the transition reach, for the swamp reach within 1 km of the Fly River, and for the swamp reach within 1 km of a tie channel or

Beyond 1 km from a channel, uniform deposition thicknesses of 0.5 and 0.7 mm were used for 1993 and 1994, respectively. Figure 3.10 shows the calculated pattern of sediment deposition and sample locations that were used to derive the local regressions. A graded color scheme is applied to illuminate the exponential function, which ends at 1 km. The figure highlights how channel paths across the floodplain dictate the pattern of sediment deposition. The cumulative volume of copper-rich sediment deposited on the flood plain between the commencement of mining and 1993 calculated from the GIS model was 1.11 � 108 m3 (133 Mt based on the bulk density of 1.2 t m�3

Figure 3.10: Predicted pattern of deposition from the GIS model of the exponential functions (1993) for the Middle Fly floodplain. The magnitude of deposition decreases from dark orange to light orange with distance from the channel; white areas are regions of the floodplain outside the influence of the depositional web or the channel system. Sample locations are shown as crosses. The margins of ORWB are outlined in gray. The channel network is shown at low water level to reveal the extensive network that extends into the blocked valley lakes (as shown in Fig. 3.1).

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Figure 3.10: (Continued)


137

for copper-rich sediment deposits). For the 1994 model, the calculated volume was 1.37 � 108 m3 (164 Mt). A sensitivity analysis was performed to determine how these loads varied in response to minor changes in the exponential functions. Using the forest reach exponential as an example and adjusting the deposition value at the levee, either higher (to 275 mm) or lower (to 200 mm), such that the R2 value of the exponential function changed by no more than 0.05, the GIS model recalculated the deposition volumes. For 1993 the sensitivity range was 0.97 � 108 to 1.30 � 108 m3, and for 1994 the range was 1.21 � 108 to 1.57 � 108 m3. The sensitivity analysis shows that these small changes in the exponential functions alter the GIS-calculated copper-rich sediment load by about 10–15%. We propose that this error is equal to or greater than that caused by local variance in individual samples, though the coefficient of variation is larger (Table 3.2). The values of 1.11 � 108 m3 and 1.37 � 108 m3 deposited up to 1993 and 1994 equate to an average deposition across the floodplain within 1 km of a channel of 42 and 52 mm, respectively, or approximately 5–6 mm yr�1 from 1986 which is the year when the mine-waste input exceeded the natural sediment load of the Middle Fly (Day et al., 2008). As a check on the deposition values derived from the GIS model, estimates of the total volume of deposition were calculated manually. Using the appropriate constants from Table 3.3 for each reach and channel type, and integrating the exponential function from 0 to 1 km, we can estimate an average deposition thickness ðDCu Þ for each reach. Multiplying DCu by twice the measured channel lengths in each reach (to account for deposition from each bank) provides the total thickness of copper-rich sediment deposited across the floodplain. The results of the above calculations are presented in Table 3.4 and show the calculated volumes deposited up to 1993 and 1994 as 1.56 � 108 and 1.81 � 108 m3, respectively, i.e., approximately 25% higher than the value derived from the GIS model. The average deposition ranged from 9.6 mm yr�1 in the forested reach to 6.0 mm yr�1 in the swamp grass reach. The higher rate arises for at least two reasons: (1) this calculation does not take into account those areas of the floodplain above the level of maximum inundation (i.e., the masked areas in the GIS) where deposition does not occur, and (2) in the GIS model, where curvature causes projected deposition to overlap, only one value is chosen, whereas this calculation essentially assumes the channels are straight. Given these differences, the similarity of values supports the GIS results. Sediment deposited directly into the ORWB (and blocked valley lakes) via tie and tributary channels is not accounted for in this GIS analysis. Measured copper-rich thickness from all cores in each oxbow were averaged and applied

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Table 3.4: Calculation of total floodplain deposition based on the product of the 1 km average deposition rate (from integration of exponential expressions whose coefficients a and b are reported). Reach

Channel Exp. constants DCu (mm) from Table 3.4 (a)

Channel length (km)

Deposition (m6 � 106)

(b)

1993 Data Forest Transition Swamp Swamp Total

Closest Closest Fly River TC & OB

243 165 128 179

3.79 3.69 2.92 3.77

63 44 42 46

1,120 1,150 320 410

70 51 13 19 153

1994 Data Forest Transition Swamp Swamp Total

Closest Closest Fly River TC & OB

2.88 169 113 187

3.64 3.18 2.04 3.59

77 51 48 51

1120 1150 320 410

86 59 15 21 181

over the oxbow area. This volume multiplied by a bulk density of 1.1 t m�3 results in an estimate of 6 Mt of sediment deposited across those oxbows that were cored up to 1994. The cored oxbows cover an area of approximately 24.9 km2 of the approximately 34.3 km2 of total area occupied by oxbows across the Middle Fly. Therefore, including the additional area of oxbows not cored, the estimate for the total mass of copper-rich sediment in all oxbows is about 8.5 Mt by 1994. As a check on this estimate, we alternatively calculate oxbow deposition by assuming that Fly River water with an average sediment concentration of 500 mg l�1 enters oxbows at an average flow of 25 m3 s�1 10– 20% of the time (Day et al., 2008), to obtain an estimate of 11–19 Mt by 1994. The oxbows cores under sample the extent of deposition because the samples rarely penetrated beyond the mine-contaminated level while the flux calculation estimate is crude. As such, the agreement between the two approaches is encouraging. The estimated range of oxbow deposition (11– 19 Mt) represents an average deposition thickness over the 34.3 km2 of oxbows of between 32 and 55 mm yr�1, which is approximately an order of magnitude higher than that reported for the floodplain core sites. Adding the copper-rich sediment thickness from the floodplain, BVL and oxbow core results (164 Mt from the floodplain and BVL cores and between 8.5 and 19 Mt into oxbows) equates to a total mass of copper-rich sediment


139

Table 3.5: Sediment budget of the Fly River. Tailings, waste rock, and wall erosion (erosion due to waste dumping) define the input to the Ok Tedi River. Year

Tailing (t � 106)

Waste rock (t � 106)

Wall erosion (t � 106)

Sediment loada (t � 106)

Sediment loadb (t � 106)

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 Total

2.38 3.10 9.72 14.93 23.60 27.42 27.01 26.74 28.62 29.71 193

3.80 9.50 11.80 23.40 29.70 27.80 27.80 21.96 14.03 27.47 197

0 0 0 0 0 1 19 24 16 22 82

17 22 32 51 53 62 49 51 56 62 455

7 12 22 41 43 52 39 41 46 52 355

Source: Data supplied by Ok Tedi Mining, Ltd.

a The total suspended sediment load entering the Middle Fly at D’Albertis Junction from the Ok Tedi and

Upper Fly.

b The total mine-derived sediment input to the Middle Fly (assuming an annual background load to the

Middle Fly of 5 � 106 t each from the Ok Tedi and Upper Fly).

deposited across the entire floodplain system up to 1994 of between 172 and 183 Mt. Table 3.5 shows the amount of sediment discharged to the fluvial system from the mine between 1985 and 1994, and the calculated suspended sediment load entering the Middle Fly River at D’Albertis Junction (Day et al., 2008). If we simply divide the range of values by the total load since 1985 (455 Mt), the fraction of the suspended load that is deposited on the Middle Fly floodplain is about 38–40%. Delivery of significant mine-derived sediment did not begin until 1987, so dividing by this shorter duration, instead of the ten-year total, gives a 41–44% deposition in the floodplain. The difference between the total sediment deposited on the floodplain between 1993 and 1994 of 31 Mt is the estimated deposition rate for the year 1994. According to Table 3.5, the suspended load entering the Middle Fly River in 1994 was 62 Mt; hence, our measurements suggest that as much as 50% of the suspended load was deposited on the floodplain. About half of the floodplain deposition occurs via overbank flows from the floodplain channels (and injection into ORWB) and the other half from overbank flows from the mainstem channel. Rate of floodplain deposition may have been increasing during this first half of the 1990s. Table 3.5 shows that from 1988, the delivery of mine waste

140

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to the system has been 4–5 times that of the natural load, whereas prior to 1988 it was less than or equal to twice the natural load. Channel bed aggradation along the Fly River was occurring at this time and advancing downstream from Kuambit. By 1994, the bed of the Fly River had aggraded from approximately 2–3 m at Kuambit to 1–2 m at Wygerin. Beyond Wygerin, by 1994, the amount of aggradation was apparently minimal (o1 m). While the timing of the onset of aggradation in the Middle Fly is not known with any certainty, it appears reasonable to assume that it was low in the early years of mining, perhaps until at least 1988 to 1990, coinciding with the increased delivery of mine waste to the system. The effect of aggradation of the Fly River bed would be to increase the frequency of overbank flow events and the frequency at which Fly River water is directed out along tie channels. Aggradation between Kuambit and Wygerin (both within the forest reach) leading to increased overbank transfer of water and sediment is also consistent with the results of the exponential functions. Between 1993 and 1994, the greatest change in deposition was observed in the forest reach as evident from the relatively higher increase in the exponential constant a (the intercept), which increased by approximately 14% compared to the transition and swamp reach, which only increased by 3–5% between 1993 and 1994. 3.3.3. The Grain Size of Floodplain Sediment Figure 3.11 summarizes the size distribution of sediment in the suspended load and in surface sediment from the channel bank top to well across the floodplain. Several striking features are apparent. As expected, the levee is sand-rich (about 22%) relative to either the suspended load or to sediments farther across the floodplain. The sand content drops immediately away from the levee, but unexpectedly, does not drop to zero, but instead remains around 5%. We made thin sections of distal samples and confirmed the presence of this sand. The sand content on the channel banks of the mainstem Fly is greater than the banks of its tie and ORWB. Also, surprisingly, the fine silt and clay content (o8 mm) is greatest within the first 10–50 m of the channel bank and then progressively declines across the floodplain. This decline is compensated by a progressive increase in coarse silt (16–32 mm). The high o8 mm concentration near the channel bank and decline across the floodplain may influence the calculated sediment deposi tion rate, as the pCu is greatest on the finer particles (Fig. 3.12). This may cause the calculated sediment deposition rate near the channel bank to be somewhat overestimated.


141

Figure 3.11: Plots of grain-size distributions of surface floodplain deposits (first B10 mm) with distance from channels. Measured grain sizes are plotted in five bin classes from o8 mm to sand size. The first panel presents data for all channel types and presents a representative size distribution of the suspended sediment load of the Middle Fly River. The other two panels present data separated by whether samples bordered the Fly River or tie channels and ORWBs. The greatest percentage of sand are found closest to the channel (0–0.01 km), though sand is present at all distances from the channel. There is surprisingly little change in the size distribution with distance from the channel, and the data suggest that a slight coarsening of the distribution may occur away from the channel. Samples were collected in 1995, and depending on the proximity to channels they are a mixture of background and mine-derived sediments.

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Figure 3.12: Variation in pCu as a function of grain size in samples collected at various locations along the Middle Fly.

3.4. Discussion As Day et al. (2008) propose, and as illustrated in Fig. 3.10, suspended sediment is spread great distances across the Fly River floodplain via tie and tributary channels, forming a depositional web. This network of floodplain channels is over 900 km and creates an efficient trap for sediment. Rates of dispersion and deposition far exceed expectations when the original 1989 APL sampling program was designed. While similar processes likely occur on other rivers, as Day et al. (2008) review, this appears to be the first systematic documentation of it. The trapping efficiency of 40% or more of the total suspended load by the middle Fly floodplain is equivalent to about 0.09% sediment deposition per kilometer of mainstem channel length, but drops to 0.03% if the length of the full channel dispersal system is used. As Day et al. (2008) report, this number is less than on the Strickland (0.05%), Brahmaputra–Jamuna (0.07%), Amazon (0.065–0.1%) but is comparable to that on the Mississippi (0.02%). So the rate loss per unit length is modest, but the extensive floodplain channel system leads to large net loss. Importantly, Day et al. (2008) report a multiyear hydrologic study of the middle Fly floodplain system which concluded that as much as 40% of


143

the total annual discharge of the Fly may enter the floodplain system (approximately one-half via floodplain channel outflow). This finding adds considerable support to the sediment deposition rate analysis. Based on suspended sediment measurements on the middle Fly before mining and during this monitoring period, the ten-year average load increase was about 4.6 times relative to pre-mining rates. Given the modest amount of channel aggradation by 1994, we infer that the deposition rate on the floodplain was probably increased by a comparable amount. Hence, if the mean aggradation per year across the first 1 km of floodplain was 5–6 mm in 1994, then the background was about 1 mm yr�1, supporting previous interpretations by Pickup et al. (1979) and Dietrich et al. (1999). The exponential decline in deposition rate occurs over 1 km, but the levee banks are much narrower, typically 56–93 m on the mainstem and 43–58 m on the tie and tributary channels (with heights of less than 2 m). Furthermore, the grain size across the floodplain does not systematically decline from the channel bank, but instead has a peak silt and clay content close to the bank. As Day et al. (2008) summarize, these observations contradict theory for levee formation and grain-size distribution across the floodplain (James, 1985). There are several implications of our findings for predicting the long-term fate of the Fly River floodplain in response to sustained mine-waste discharge to the system. First, mine-derived sediment will be widely dispersed across the system, with greatest deposition bordering the mainstem and floodplain channels (as well as in the ORWB). Significant amounts of metals will be deposited on the floodplain. For example, by 1994, perhaps as much as 131,000 tonnes of copper had been delivered to the floodplain (164 Mt times a mean pCu of 800 mg g�1). The greatest deposition rate will be on the levees. Subsequent topographic monitoring of levee heights by OTML between 1997 and 2002 (OTML, 2004) showed that the height increased by 1 m in 6 years, which means that the rate of levee growth increased significantly after our monitoring program ended. The fastest average levee growth we documented occurred between 1993 and 1994 and was only 45 mm in 1 year or 270 mm in 6 years, a much slower rate. The acceleration recorded in the repeat topographic surveys may be due to a combination of increased mine-waste loading, La Nina flooding, and channel aggradation (causing more frequent and higher flooding levels). It is not clear how levee growth may affect floodplain channel dynamics, or whether, it may lead to new processes, such as frequent crevasse splay formation. Rowland et al. (2005) used OSL dating to document that in two oxbows the rate of tie channel advancement into the oxbows increased by 6–17 times since the early 1980s to mid 1990s. This increase in rate corresponds to

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increased mine loading. By 2005, at least one major tie channel (just upstream from Obo) had completely plugged with sediment. Given the crucial role the tie channels play in connecting the mainstem to floodplain ecosystems, the fate of these channels and the rapid accumulation of minederived sediment in the oxbows should be a concern. Modeling of bed material transport on the Fly suggests that there will be a slow migration of a mine-derived sediment aggradational front downstream. Frequency of overbank deposition and flushing of sediment out of tie and tributary channels should increase with aggradation. As Dietrich et al. (1999) pointed out, the lower Middle Fly channels, despite having meandering form, showed no evidence of lateral bank migration for decades. If the aggradational front persists through this reach, and forces the development of bars, lateral migration may be reactivated. Bank migration will cut into overbank sediment rich in mine-derived sediment. Hence, in this lower reach, as well as along the entire upstream Middle Fly River, lateral migration will cause mine-derived sediment to remain a significant load in the river well after mine closure. Given the active distributary-like floodplain channel network, it is also a concern that progressive bed aggradation could lead to the potential for channel avulsion. Figure 3.13 shows the pattern of elevation along the east side of 4 of the 17 transects (also see Fig. 3.4). The floodplain generally decreases in height away from the channel, especially once it leaves the elevated scroll-bar zone (Fig. 3.1). Note that there are some very low elevations in the peripheral 14 transect 4

Elevation (m AHD)

12

transect 9 transect 12

10

transect 15 8

6

4

2

0

5,000

10,000

15,000

20,000

25,000

30,000

Distance from channel bank (m)

Figure 3.13: Elevation profiles along four of the transects shown in Fig. 3.4.


145

floodplain zone. For example, along the distal portions of transect 9, elevations reach as low just 4 m above sea level. Such significant crossfloodplain topographic gradients set up favorable conditions for avulsion (Slingerland and Smith, 2004) and the potential for this happening on the Fly, given continued bed aggradation, deserves consideration.

3.5. Conclusions During the first 10 years of mine operation, mine-derived sediment, enriched in pCu traveled quickly down the Ok Tedi and spread rapidly over great distances across the Fly River floodplain. This rapid and extensive dispersal of sediment was caused by the over 900 km of tie and tributary channels which serve as avenues for suspended sediment pumped out from the mainstem Fly. The sediment traveled along the channels and then spilled out across their banks. By 1994, mine-derived sediment was found across the entire floodplain in areas adjacent to channel sources. This overbank deposition decreased exponentially from levee top out to 1 km, beyond which very little mine-sediment arrived, and whose deposition showed no spatial pattern. This depositional web of sediment had dispersed about 180 Mt of sediment to the floodplain by 1994, depositing over 130,000 tonnes of copper, with about half deposition occurring via outflow along the flood plain channels. All ORWB connected to the mainstem via tie or tributary channels were immediate recipients of mine-derived sediment. The consequence of this broad and efficient dispersal system is that about 40% (or more) of the total load delivered to the middle Fly River was deposited on its floodplain before reaching the junction with the Strickland. The environmental legacy of this deposition is manyfold. Nearly all ORWB have large amounts of mine-derived sediment. Levee heights have grown significantly with potential morphodynamic consequences. Minederived sediment has traveled tens of kilometers up tributaries, dispersing the sediment widely. An exponentially thinning package of mine-derived sediment borders the channels and will remain a source of mine-related sediment due to lateral migration long after mine closure. Tie channel advance has quickened and plugging has occurred. Lateral migration is accelerated by bar growth due to increased sediment supply (Dietrich et al., 1999). The combination of a propensity for outflow on tie channels and tributaries, large areas of low elevation, accelerated channel shifting, and channel bed aggradation driven by mine-derived sediments may create the potential for channel avulsion.

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ACKNOWLEDGMENTS

This work was supported by Ok Tedi Mining Limited (OTML). We especially thank OTML environment managers, Murray Eagle and Eric Woods. Cliff Riebe assisted in fieldwork. Analysis of the data was also supported in part by the National Center for Earth-Surface Dynamics and an NSF Margins Source to Sink grant. Deanna Sereno and Dino Bellugi performed GIS analysis of floodplain deposition and Mark Stacey provided valuable guidance. The paper benefited from a review by Geoff Pickup and careful editing by Barrie Bolton.

REFERENCES Aalto, R., Lauer, J. W., & Dietrich, W. E. (2008). Spatial and temporal dynamics of sediment accumulation and exchange along Strickland River floodplains (PNG), over decadal-to-centennial time scales. Journal of Geophysical Research, 113, F01S04. doi:10.1029/2006JF000627. Bridge, J. S. (2003). Rivers and floodplains: Forms, processes, and sedimentary record. Blackwell Publishers, UK, 491 pp. Day, G., Dietrich, W. E., Rowland, J. C., & Marshall, A. (2008). The depositional web on the floodplain of the Fly River, Papua New Guinea. Journal of Geophysical Research, 113, F01S02. doi:10.1029/2006JF000622. Dietrich, W. E., Day, G., & Parker, G. (1999). The Fly River, Papua New Guinea: Inferences about river dynamics, floodplain sedimentation and fate of sediment. In: A. J. Miller, et al., (Eds). Varieties in Fluvial Form. Wiley, New York, pp. 345–376. James, C. S. (1985). Sediment transfer to overbank sections. Journal of Hydraulic Research, 23(5), 435–452. Lauer, J. W., Parker, G., & Dietrich, W. E. (2008). Response of the Strickland and Fly River confluence to post-glacial sea-level rise. Journal of Geophysical Research, 113, doi:10.1029/2006JF000626. Ok Tedi Mining Ltd (OTML) (1989). Supplemental Environmental Investigations. OTML, Tabubil, Papua New Guinea. Ok Tedi Mining Ltd (OTML) (1990). APL Compliance and Additional Environ mental Monitoring Program. OTML, Tabubil, Papua New Guinea. Ok Tedi Mining Ltd (OTML) (1993a). APL compliance and additional environmental monitoring program: 1992 annual report. OTML Report ENV 93-04. Ok Tedi Mining Ltd (OTML) (1993b). Fly River flood-plain copper monitor. June, ENV 93-06.


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Ok Tedi Mining Ltd (OTML) (2004). Summary report: Effects of mine life extensions and dredging on the Ok Tedi and Fly River–A sediment transport model study. Environment Section, September 10, 68 pp. Pickup, G., Higgins, R. J., & Warner, R. F. (1979). Impact of waste rock disposal from the proposed Ok Tedi mine on sedimentation processes in the Fly River and its tributaries. Report to Department of Minerals and Energy and Office of Environment and Conservation, Papua New Guinea, 138 pp. Rowland, J. C., Lepper, K., Dietrich, W. E., Wilson, C. J., & Sheldon, R. (2005). Tie channel sedimentation rates, oxbow formation age and channel migration rate from optically stimulated luminescence (OSL) analysis of floodplain deposits. Earth Surface Processes and Landforms, 30(9), 1161–1179. Slingerland, R., & Smith, N. D. (2004). River avulsions and their deposits. Annual Review in Earth and Planetary Sciences, 32, 257–285. Swanson, K. M., Watson, E., Dietrich, W. E., Apte, S., Lauer, J. W., Aalto, R., Bera, M., Marshall, A., & Taylor, M. (2008). Decadal sedimentation rates on the floodplain of the Strickland River, Papua New Guinea, Journal of Geophysical Research, 113, F01S03, doi:10.1029/2006JF000623. Zar, J. H. (1984) Biostatistical Analysis. 2nd Edn., Prentice Hall, New Jersey.

Appendix: Results of Applied Particulate Level (APL) Annual Survey. Analyses are from Shallow Cores on the Floodplain and in Off-River Water Bodies (Sample Code Starts with W) Sample code 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Sampling location

Benthic Cu (mg Cu/g of sediment)

Latitude 1S

Longitude 1E

1990

1991

1992

1993

1994

6-10.43 6-22.96 6-20.89 6-21.15 6-13.02 6-16.37 6-16.88 6-16.30 6-16.72 6-17.14 6-22.45 6-26.77 6-26.01 6-25.72 6-30.68 6-26.20 6-36.82

141-10.16 141-06.93 141-04.28 141-04.28 141-04.74 141-02.88 141-00.78 141-03.76 141-04.65 141-05.80 140-58.61 140-56.69 140-55.38 140-55.64 140-56.68 140-57.24 140-55.17

26 31 19 18 592 26 30 193 48 30 112 50 64 56 46 800 61

19 61 30 45 610 41 21 548 13 82 200 578 167 47 34 736 88

17 350 38 42 n/s 125 47 564 280 194 611 341 434 53 171 649 236

23 826 75 24 n/s 475 40 950 500 716 456 680 456 523 137 692 670

32 691 30 36 1455 1019 48 987 772 526 983 693 591 370 102 1312 165

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Appendix 1: (Continued ) Sample code 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59

Sampling location


Latitude 1S

Longitude 1E

1990

1991

1992

1993

1994

6-36.61 6-36.63 6-36.62 6-25.70 6-31.08 6-34.09 6-38.13 6-41.61 6-51.79 6-52.62 6-52.37 6-51.60 6-55.49 6-56.55 6-58.11 7-33.06 7-35.31 7-34.43 7-33.12 7-32.41 7-30.06 7-30.95 7-32.18 7-30.82 7-29.51 7-26.88 7-27.06 7-24.13 7-21.90 7-21.61 7-21.78 7-24.04 7-22.53 7-23.03 7-19.76 7-19.02 7-17.48 7-18.22 7-17.21 7-17.08 7-17.01 7-16.73

140-52.66 140-50.79 140-52.52 141-00.26 140-59.97 140-58.43 140-53.04 140-51.28 140-54.79 140-58.55 140-59.67 141-01.03 141-02.22 141-02.26 141-02.12 141-21.37 141-18.77 141-16.73 141-17.06 141-17.48 141-16.53 141-18.26 141-14.73 141-11.80 141-08.57 141-10.57 141-11.86 141-16.36 141-16.75 141-14.56 141-13.86 141-15.20 141-10.16 141-09.43 141-08.86 141-13.11 141-15.28 141-16.57 141-17.15 141-13.92 141-12.44 141-10.26

71 679 49 39 61 54 80 65 67 63 71 113 40 112 30 52 10 9 10 42 63 83 10 19 10 10 10 30 32 58 62 21 10 10 19 157 21 19 20 20 22 21

42 n/s 37 33 43 60 331 124 233 182 93 163 658 213 72 43 23 36 62 174 248 319 37 23 35 20 13 105 63 119 103 68 25 52 75 124 34 59 19 30 264 475

221 724 165 41 96 61 545 151 478 213 539 265 536 321 625 84 43 95 64 227 570 383 34 61 40 42 42 66 94 227 151 177 100 38 50 149 71 41 49 107 187 149

444 837 356 164 41 50 236 427 737 225 688 1116 1109 233 1066 351 321 110 135 192 30 688 193 116 1109 15 18 27 69 340 95 49 137 33 91 93 247 63 166 37 619 708

41 1009 126 n/s 95 41 269 150 1011 266 274 64 1199 725 58 38 39 32 35 184 859 1550 39 12 16 18 17 26 54 97 134 75 105 17 61 140 20 18 29 26 614 1265


149

Appendix 1: (Continued ) Sample code 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101

Sampling location


Latitude 1S

Longitude 1E

1990

1991

1992

1993

1994

7-14.65 7-15.59 7-10.65 7-12.63 7-12.45 7-12.95 7-12.78 7-07.72 7-06.59 7-10.14 7-07.68 7-08.96 7-05.43 7-05.36 7-04.91 7-03.63 7-02.58 6-59.26 7-00.16 7-02.28 7-00.15 7-00.64 6-56.53 6-55.52 6-56.65 6-51.15 6-51.04 6-51.13 6-50.77 6-50.84 6-46.72 6-45.92 6-47.77 6-47.78 7-24.22 6-44.18 6-40.35 6-31.30 6-32.90 6-28.68 6-17.03 6-14.43

141-07.26 141-05.29 141-04.34 141-06.28 141-08.70 141-12.13 141-13.59 141-12.79 141-11.05 141-13.26 141-07.59 141-07.69 141-03.67 141-02.84 141-05.69 141-08.59 141-10.79 141-09.34 141-08.42 141-06.09 141-01.99 141-04.19 141-06.57 141-07.20 141-07.62 141-04.12 141-00.40 140-58.86 140-56.68 140-54.07 140-55.92 140-54.83 140-52.89 140-53.54 141-12.39 140-53.67 140-55.11 140-56.00 140-55.71 140-57.42 141-00.86 141-04.36

10 20 10 20 14 14 27 12 15 14 28 25 11 13 12 73 13 13 9 50 20 31 20 21 20 32 63 20 32 135 21 21 36 264 29 443 108 42 233 64 301 598

26 43 23 23 45 27 48 75 33 51 69 56 22 28 75 68 63 51 114 120 37 340 70 61 48 63 91 114 27 210 42 91 144 77 37 61 141 160 350 180 75 392

27 48 41 36 45 36 52 45 24 50 54 107 77 41 752 39 60 87 292 132 104 301 575 108 175 191 85 176 188 63 300 188 671 591 62 81 155 963 941 562 234 310

28 343 49 120 673 444 109 168 58 695 s/s 86 139 220 684 215 179 212 213 417 218 1911 1119 706 190 116 139 286 334 58 635 635 920 845 96 1122 169 147 836 569 564 628

29 10 18 21 39 31 20 36 10 23 58 119 15 6 38 90 47 85 n/s 414 33 185 114 40 29 231 142 93 205 438 652 110 88 47 61 91 234 78 1193 1330 70 908

150

G. Day et al.

Appendix 1: (Continued ) Sample code W-1 W-2 W-3 W-4 W-5 W-6 W-7 W-8 W-9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30 W-31 W-32 W-33 W-34 W-35 W-36 W-37 W-38 W-39 W-40 W-41 W-42

Sampling location


Latitude 1S

Longitude 1E

1990

1991

1992

1993

1994

6-11.55 6-12.58 6-14.86 6-18.07 6-21.25 6-20.81 6-20.38 6-20.92 6-17.55 6-11.12 6-16.52 6-17.33 6-20.41 6-21.28 6-24.43 6-24.65 6-25.00 6-30.05 6-28.02 6-35.52 6-36.41 6-36.63 6-35.57 7-32.80 7-32.39 7-32.50 7-31.77 7-31.41 7-32.53 7-30.52 7-30.41 7-29.42 7-29.01 7-25.89 7-27.91 7-27.58 7-27.44 7-22.31 7-21.85 7-22.01 7-22.53 7-22.77

141-08.53 141-07.47 141-07.69 141-04.51 141-02.79 140-59.59 140-59.40 140-59.29 141-00.38 141-01.68 141-02.01 141-02.28 140-58.59 140-58.97 140-58.37 140-58.35 140-58.48 141-00.98 141-03.15 140-54.62 140-54.27 140-54.78 140-55.35 141-18.37 141-17.04 141-15.92 141-13.15 141-11.52 141-07.50 141-09.73 141-11.96 141-15.67 141-16.19 141-15.87 141-12.55 141-11.96 141-11.77 141-11.55 141-11.35 141-10.52 141-10.57 141-10.05

302 854 35 994 57 205 617 70 933 521 716 717 931 115 642 640 641 31 30 767 535 417 1134 146 912 43 43 24 33 19 33 54 553 540 52 44 10 105 189 65 65 10

1066 671 50 923 48 36 888 954 1401 51 709 751 938 637 632 659 701 39 43 67 38 1021 941 528 215 334 43 32 42 29 188 215 484 634 390 31 29 698 199 342 605 48

1268 828 62 748 1009 838 1564 1264 519 1399 995 843 898 460 975 896 831 46 36 1009 649 1084 1061 998 1002 466 107 154 72 70 359 49 750 734 78 55 51 776 895 143 687 18

1240 683 38 1334 206 543 963 1321 912 1443 963 1095 1152 1857 1087 885 11041 28 130 230 620 784 1031 827 468 299 352 183 37 160 424 525 876 876 238 154 306 1027 326 716 478 40

1622 1276 127 1015 64 520 299 1734 75 1345 1556 1487 1239 795 1267 781 866 52 44 105 505 96 1286 1107 1218 185 40 43 32 35 131 361 1368 47 173 37 40 1131 640 642 919 144


151

Appendix 1: (Continued ) Sample code W-43 W-44 W-45 W-46 W-47 W-48 W-49 W-50 W-51 W-52 W-53 W-54 W-55 W-56 W-57 W-58 W-59 W-60 W-61 W-62 W-63 W-64 W-65 W-66 W-67 W-68 W-69 W-70 W-71 W-72 W-73 W-74 W-75 W-76 W-77 W-78 W-79 W-80 W-81 W-82 W-83 W-84

Sampling location


Latitude 1S

Longitude 1E

1990

1991

1992

1993

1994

7-21.96 7-14.51 7-15.16 7-14.29 7-14.54 7-19.40 7-18.18 7-18.42 7-15.16 7-14.78 7-14.13 7-12.55 7-12.31 7-10.49 7-11.74 7-10.16 7-09.05 7-09.62 7-07.15 7-07.64 7-07.99 7-03.83 7-02.50 7-02.79 7-01.96 7-03.15 7-00.13 7-01.28 7-03.21 7-05.54 7-06.22 6-58.18 6-57.66 6-56.79 6-54.51 6-53.75 6-52.69 6-53.26 6-54.56 6-57.45 6-58.64 6-43.02

141-09.35 141-02.85 141-05.11 141-04.95 141-05.81 141-15.54 141-15.20 141-16.96 141-14.07 141-09.89 141-07.22 141-05.00 141-09.95 141-12.34 141-14.78 141-14.51 141-15.87 141-10.01 141-10.04 141-07.66 141-05.59 141-11.60 141-09.94 141-09.84 141-07.83 141-06.63 141-06.20 141-01.60 141-03.31 141-02.04 141-05.00 141-05.14 141-05.56 141-04.81 141-03.40 141-02.55 141-01.38 141-05.22 141-08.42 141-06.66 141-08.42 140-51.68

17 51 29 39 125 28 33 21 31 810 40 40 220 109 74 64 36 39 524 304 42 53 119 81 289 52 712 222 88 230 127 72 66 994 n/s 47 60 209 556 492 908 671

33 44 70 224 503 152 23 23 550 958 625 127 68 42 757 533 155 29 294 708 161 127 95 618 747 689 611 63 145 172 682 35 77 158 69 42 100 259 548 325 206 150

150 50 150 100 563 299 52 28 605 916 849 97 492 105 542 591 88 109 636 45 150 869 389 654 831 811 803 476 693 666 864 50 151 1285 202 81 150 211 479 374 783 586

363 60 179 340 670 1050 333 62 1362 1889 323 93 1492 115 476 354 61 97 427 1306 763 557 488 766 846 947 820 1695 n/s 727 285 146 104 1867 294 240 146 503 460 365 485 483

145 68 130 127 127 358 36 65 841 965 640 201 204 76 330 511 66 101 602 1432 169 88 659 875 640 480 1135 758 320 825 868 70 136 1311 65 65 83 201 852 339 519 105

152

G. Day et al.

Appendix 1: (Continued ) Sample code W-85 W-86 W-87 W-88 W-89 W-90 W-91 W-92 W-93 W-94 W-95 W-96 W-97 W-98 W-99 W-100

Sampling location


Latitude 1S

Longitude 1E

1990

1991

1992

1993

1994

6-43.48 6-45.16 6-46.60 6-48.09 6-51.19 6-51.03 6-51.80 6-50.98 6-44.24 6-24.75 6-31.90 6-32.50 6-36.63 6-37.01 6-42.09 6-42.25

140-54.08 140-58.26 140-53.80 140-53.56 140-56.68 141-00.68 141-02.99 141-04.86 140-53.42 140-57.69 140-58.97 140-56.19 140-53.15 140-52.88 140-52.01 140-52.50

192 192 1446 692 41 244 64 117 815 600 30 158 998 61 82 126

251 78 988 635 856 99 174 389 622 681 45 41 988 491 183 59

990 161 635 683 923 199 116 244 938 1009 29 504 871 952 321 494

813 191 s/s 978 1210 167 75 282 493 1233 153 72 1042 82 170 732

1450 412 1606 1288 1037 100 168 533 1055 1012 38 1024 1188 998 256 719

43 22

69 34

101 50

126 64

92 46

Number of samples W200 mg/g % Samples W200 mg/g Notes: n/s, not sampled; s/s, spilled sample.


Chapter 4

Processes, Sediments, and Stratigraphy of the Fly River Delta John P. Walsh1,� and Peter V. Ridd2 1

Department of Geological Sciences and the Institute for Coastal Science and Policy and Coastal Resources Management Program, 301B Graham Building, East Carolina University, Greenville, NC 27858, USA 2 Marine Geophysics Laboratory, School of Mathematical; and Physical Sciences, James Cook University, Townsville, Queensland 4811, Australia

4.1. Introduction Voluminous rainfall and rugged, tectonically active mountains are two primary ingredients that make Indo-Pacific islands incredible suppliers of sediment to the ocean. It is estimated that six islands alone (Papua New Guinea (PNG), Sulawesi, Borneo, Sumatra, Java, Timor) supply 20–25% of the total annual sediment load transported to the ocean globally (Milliman et al., 1999). Many rivers draining these islands discharge onto broad, low-gradient continental shelves characterized by large tidal ranges, and these are locations for tide-dominated deltas. The Fly River of PNG is one example. The Fly River delta is a large funnel-shaped estuary with three major distributary channels; its morphology is a classic example of a tidedominated delta (Fig. 4.1; Coleman and Wright, 1975; Galloway, 1975; Wright, 1985). The delta is approximately 100-km wide at the coast and its three main distributary channels merge at Sumogi Island around 100 km inland. Although the Fly River and its delta are not as large as the Amazon or Ganges–Brahmaputra rivers, it is significant by world standards. The system has a high sediment yield (1,118 t km�2 year�1, Harris et al., 1993), �Corresponding author. Tel.: (252) 328-5431; Fax: (252) 328-4391;

E-mail: [email protected] (J.P. Walsh).

154

J. P. Walsh and P. V. Ridd

Figure 4.1: Map of the Fly River drainage basin. The Fly River drains the Papuan Fold Belt with mountains exceeding 4,000 m in elevation, and it flows across the Papuan Foreland Basin in southwestern Papua New Guinea. Note, the location of Fig. 4.2 is shown.

and the delta receives a large natural annual sediment load (85 � 106 tonnes; 17th in the world). In fact, the Fly River carries more sediment to the sea than all the rivers draining Australia combined (Harris et al., 1993). Interestingly, the average daily tidal water flux within the estuary is about 18 times greater than the river discharge (Spencer, 1978). Sediment transport associated with tidal, fluvial, and marine processes is responsible for the complex erosion and deposition patterns throughout the delta, making portions of this environment highly dynamic. Because of the large size and energetic tidal nature of the delta, the signal of sediment preserved in the stratigraphic record and leaving this part of the dispersal system is altered considerably in space and time. This paper is a digestion of the research conducted in the Fly River delta, much of which was supported by Ok Tedi Mining Limited. In this review of the physical processes and sediments of the Fly River delta, we will discuss the geologic setting, fluvial characteristics, hydrodynamic processes, sediment transport, and the resulting stratigraphy. Also, this overview identifies and discusses topics for future research.

The Fly River Delta

155

4.2. Geologic Setting and Fluvial Characteristics The island of New Guinea is located immediately north and only a short distance from the Cape York Peninsula of northeastern Australia (Fig. 4.1). The Fly River drainage basin lies on the southern side of the island. Between 1842 and 1846, Captain F.P. Blackwood aboard the H.M.S. Fly first surveyed the mouth of the river (Jukes, 1847), and D’Albertis (for whom the junction of the Ok Tedi and Fly rivers is named) was the first explorer to travel the full navigable length of the Fly River in 1876 (Harris et al., 1993). Geologically, the Fly River drains a foreland basin that lies immediately southwest of the Papua Fold Belt. The basin has developed since the Oligocene in response to loading of material onto the Australian plate associated with subduction of the Pacific plate; evidence for variable subsidence in the basin is provided by thickness differences in sediments across the Papuan Basin (Veevers, 1984; Pigram et al., 1989). Approximately 30% of the drainage basin is in the mountains of the Papuan Fold Belt (Dietrich et al., 1999). This portion of the basin is extensively faulted and has rocks of varied lithology including, partly metamorphosed Jurassic volcanics and clastics, metamorphosed and unmetamorphosed Cretaceous sediments, Miocene limestones, and Quaternary volcanics (D’Addario et al., 1976). After leaving the mountains, the Fly River flows across a long, lowgradient flood plain, B850 km to the delta mouth (Dietrich et al., 1999). En route, the Fly River meets the larger Strickland River at Everill Junction. The mean annual discharge of the Strickland River is about 1.4 times that of the Fly River at Obo (2,244 m3 s�1), and the Strickland River contributes as much as 80% to the total Fly River sediment load (Harris et al., 1993). Nonetheless, the Fly River keeps its name below the junction. As river flow increases downstream, the hydrograph is more stable and less sensitive to individual rain events. Annually, the hydrograph remains relatively steady; greatest discharge variability is associated with interannual climate change associated with the El Ninõ Southern Oscillation (Walsh et al., 2004). For example, in 1996 the discharge fluctuated roughly between 2,000 and 3,000 m3 s�1 while in 1997 the river was below 2,000 m3 s�1 for about three-quarters of the year and below gauge level (o1,000 m s�1) for about 50% of the year (Walsh et al., 2004). Tidal influence on the river can be observed upstream of Everill Junction (Dietrich et al., 1999). The gravel–sand transition in fluvial sedimentation is located near the confluence of the Ok Tedi and Fly Rivers. The majority of the system is bedded with medium sand. Bed grain size generally becomes finer along its course as the river slope decreases (Pickup, 1984; Dietrich et al., 1999;

156


Bolton et al., 2009). However, finer sediments are observed on the bed in a backwater region just above the confluence with the Strickland River. Sediment is carried to the delta mainly (B90%) in suspension (finer than 100 mm) with the remaining 10% carried as bed load (Ok Tedi Mining Limited, 1988). The natural annual sediment load of the Fly River is thought to be 85 million t y�1, and sediment discharge is estimated to have reached 125 million t y�1 in the early 1990s after the height of mining (Ok Tedi Mining Limited, 1988). Modern sediment discharge lies between these values.

4.3. Delta Geomorphology The term ‘‘delta’’ includes the subaerial and subaqueous river-sediment accumulations near a source stream, including all that is reworked by oceanographic processes (Wright, 1985). The Fly River delta can be subdivided into four regions: (1) tidal-fluvial channel, (2) distributary channels and islands, (3) distributary mouth bars, and (4) delta front and prodelta (Dalrymple et al., 2003). Of course, the four regions are inherently connected by processes and lateral stratigraphy. This paper focuses primarily on the second deltaic region (i.e., the portion with distributary channels and islands). For the remainder of this paper, the term ‘‘delta’’ will refer to this region unless specified otherwise. This region also behaves as an estuary (following Pritchard, 1967), and may be (and has been) referred to as such. The Fly River delta has the classic morphology of a tide-dominated delta with seaward-radiating, straight, and funnel-shaped distributary channels creating a triangular shape (Coleman and Wright, 1975; Galloway, 1975; Wright, 1985). It is worth noting that because of its sheer size and dynamic nature, a comprehensive, detailed bathymetric dataset is lacking for the delta. More recently, as part of the National Science Foundation, MARGINS Source-to-Sink initiative, portions of the delta front and prodelta have been mapped at high resolution with multibeam (Crockett et al., 2005). But in the delta, only single-beam methods have been used over discrete areas at different times, and seabed dynamics are poorly known. The apex of the delta lies near Sumogi Island (Fig. 4.2B), and below this point three major distributaries exist: the Far Northern Entrance, the Northern Entrance, and the Southern Entrance. The tidal-fluvial channel region above the delta apex has one primary channel and a few islands, with morphological characteristics of a meandering stream, e.g., point bars, cut banks, and a thalweg on the outside of meander bends. Channel width and

The Fly River Delta

157

Figure 4.2: Maps of Fly River delta. Unprocessed SRTM elevation data obtained from the Jet Propulsion Lab are shown in (A). Although meters of error are characteristic of these data, the data nicely illustrate that the head of the Fly River delta is regionally incised. The distribution of mangroves in the Fly River delta as determined by Robertson et al. (1991) are presented in (B). The absence of mangroves from Kiwai Island and the heads of several of the other islands, especially in the southern part of the delta, might indicate that these islands are covered by pre-Holocene sediments.

158


meander wavelength increase seaward towards the delta apex (Dalrymple et al., 2003). Here the channel is most dynamic, experiencing regular morphological change (Hughes and Baker, 1996). The major distributaries between the apex and the mouth are generally broad, shallow, and relatively straight channels, usually o10-m and rarely W12-m deep, and range from a few kilometers wide at the upstream end to tens of kilometers wide near the mouth (Spencer, 1974). Long subtidal bars with relief of 5–8 m, widths of 0.5–2 km, and up to several kilometers long subdivide the main channels (Dalrymple et al., 2003). These are maintained by energetic flood- and ebb-tidal flows. Many flood and ebb channels pinch out in the landward or seaward direction, and these are referred to as flood and ebb barbs, respectively. A significant portion of the shorelines are steep, eroding banks, but elsewhere prograding shorelines are evident, at least temporarily (Fig. 4.3). Colonization of the long subtidal bars and prograding shorelines by vegetation is a means of forming elongate islands and

Figure 4.3: Photographs of sedimentary environments in the Fly River delta. The following are shown: (A) an eroding bank, (B) the accretionary bank of an emergent island, (C) a prograding bank, and (D) an island interior. Note, data in Fig. 4.4 are from cores collected in an island interior (D).

The Fly River Delta

159

increasing land area. In some cases, it appears that islands are rooted to preHolocene strata (Spencer, 1978). Seaward of the delta islands on the delta front is a region characterized by linear bars (referred to as ‘‘distributary mouth bars’’) which in some cases look to be a continuation of distributary islands (Dalrymple et al., 2003). Bars are 1–6 km wide and are evident up to 15–20 km offshore. Dalrymple et al. (2003) explain that the interfingering of flood and ebb channels in this region reflects a zone of bed load convergence. Bathymetric contours also reveal that this zone is dissected by at least one submarine channel that extends into the Far Northern Channel (Harris et al., 1993). Interestingly, this channel, referred to as Umuda Channel, is aligned with an underlying paleochannel, suggesting the geologic framework may exert some control (Walsh et al., 2003). The delta front is a gently sloping, sandy region on the inner shelf of the Gulf of Papua (Harris et al., 1993). This region is part of a large depositional feature which has been constructed on the continental shelf, known as a subaqueous delta clinoform (Walsh et al., 2004). The delta front is also the location for the topset beds of the subaqueous delta clinoform. Seaward of the delta front is the prodelta and distal delta which includes the more steeply dipping foreset beds and the nearly flat-lying bottomset beds of the subaqueous delta clinoform, respectively. Details and dynamics of the delta front, prodelta, and distal delta portions of the Fly River delta system are discussed in Harris et al. (1993, 2004), Walsh et al. (2004), Palinkas et al. (2006), and Crockett et al. (2009).

4.4. Hydrodynamics 4.4.1. Tides The tides in the delta are semidiurnal with a large diurnal inequality. Spring tide variations up to 4 m are reduced to around 1 m during the neap tides. The effect of bottom friction in generating higher order tidal harmonics (Aubrey and Friedrichs, 1988) is evident with the M4, S4, and M8 constituents accounting for up to 0.65 m of the tidal range at Lewada (Fig. 4.2). During spring tides, the tidal variation deviates grossly from a sinusoidal pattern. Aubrey and Friedrichs (1988) have indicated that a tidal bore is generated upstream of Lewada (near the delta apex), but personal experiences of the lead author indicate a bore can form closer to the river mouth (i.e., in the central portion of the delta).

160


4.4.2. Low-Frequency Water-Level Fluctuations Water-level oscillations up to 0.1 m occur at the mouth of the delta with periods from days to weeks, and these are forced by sea-level oscillations in the Coral Sea and the Gulf of Papua. In addition to this external forcing, considerable variations in the longitudinal water-level slope occur within the delta. The water-level difference between the mouth and apex of the delta varies by as much as 0.2 m in conditions when river discharge remains constant. This effect has been attributed by Wolanski et al. (1997) to two causes: (1) an increase in the bottom friction coefficient with spring tides (Provis and Lennon, 1983; Wolanski, 1994), requiring a larger water slope to maintain a constant freshwater discharge, and (2) trade winds from the southeast, which fluctuate at periods of 1–2 weeks and have speeds averaging around 12 m s�1, causing a set up at the coast and an increase in water level within the delta.

4.4.3. Currents Currents within the delta are dominated by the tides (Wolanski et al., 1995). The net flow velocity due to the freshwater discharge is relatively small, i.e., on the order of 1–2 cm s�1 at the mouth and 10 cm s�1 at Sumogi Island. This compares with tidal currents commonly reaching 1 m s�1 and up to 2 m s�1 in the apex of the delta and 1.5 m s�1 at the mouth. The net discharge of freshwater is highly asymmetrical with up to 80% of the discharge being diverted to the south of Sumogi Island. In addition, high-salinity seawater intrudes further upstream in the Northern Entrance than the other two channels. It is estimated that the Southern Entrance channel carries between 55% and 80% of the freshwater and river-supplied sediment flux. The tidal currents show little vertical shear except near the bed due to bottom friction (Wolanski et al., 1995; Harris et al., 2004). Vertical current shear due to buoyancy is small and difficult to measure, and the water column is often well mixed by the strong tidal currents. It should be noted that while buoyancy currents are small compared to the tidal currents, they are doubtless present and are responsible in part for the formation of the turbidity maximum zone in the central delta. Hydrodynamic modeling of the delta by Wolanski et al. (1995) duplicates well the observed currents, but requires a smaller than expected Manning coefficient (0.15). It is postulated that this is due to the presence of a nearbottom fluid–mud layer which decreases bottom frictional stresses (Wolanski et al., 1995).

The Fly River Delta

161

4.4.4. Waves Because the delta faces the east–southeast it is directly exposed to waves generated by the southeast trade winds between April and November. The fetch for these waves is on the order of a thousand kilometers, and thus the genera tion of long period waves that impinge on the sea bed is expected. The gently shoaling continental shelf offshore from the delta is about 150-km wide and is expected to modify the wave spectrum as waves propagate towards the shore. Unlike other oceanographic parameters such as current and tides, no published data examining the systematics of waves in the delta are known to the authors, though Harris et al. (2004) has modeled the waves at the mouth of the estuary. Wave-rider buoy measurements at Kerema (B200 km to the northeast of the Fly River delta in the Gulf of Papua) indicate significant wave heights exceed 0.25 m for 90%, 0.7 m for 50%, 1.5 m for 10%, and 2.0 m for 1% on an annual basis (Thom and Wright, 1983). The wave climate offshore of the delta is likely to be more energetic than that at Kerema due to the aspect of the coastline with respect to the wave direction. The affect of waves generated in the Coral Sea on sediment transport at the mouth of the delta and across the delta front is thought to be significant (Harris et al., 2004; Walsh et al., 2004). Furthermore, there is considerable seasonality in the winds and waves; Thom and Wright (1983) determine the median significant wave height to be 1.3 m during the SE trade-wind period (December–March) and 0.3 m during the NW monsoon season (March–November). This seasonal cycle in waves has been hypothesized to be important to across-shelf transport of fluvial sediments (Harris et al., 1993, 2004; Walsh et al., 2004). In conditions of strong winds that generally blow along the axis of the three main distributary channels, there is a considerable generation of short-period waves within the delta. Although the magnitude of these waves has not been directly studied, they likely influence suspended-sediment concentration (SSC)s. This is hypothesized as these waves, though short in wavelength and typically of less than 0.5 m in height, probably can resuspend bottom sediment on the shores of the numerous unconsolidated mudbanks and islands within the delta. Observations of Wolanski et al. (1995) support this notion.

4.5. Sediment Dynamics 4.5.1. Suspended-Sediment Concentrations Tidal currents are the primary control on SSC within the delta (Wolanski et al., 1995). During spring tides, near bed maximum concentrations may

162


briefly exceed 30 g l�1 and are persistently above 2 g l�1. In contrast, during neap tides, the SSC is generally less than 0.5 g l�1 (Wolanski et al., 1995). There are considerable variations of SSC within a tidal cycle with resuspension occurring during accelerating strong currents and deposition occurring when currents are decelerating, particularly at slack tides. Some SSC data was collected by Wolanski et al. (1995) during a rough weather event (winds exceeding 30 knots from the southeast). These data from the mouth of the Southern Entrance during spring tides show a short-lived (a few hours) factor-of-two increase in SSC. A very pronounced turbidity maximum is present in the delta and is located approximately 20 km from the mouth of the delta in the southern channel at salinities of 5–10 (Wolanski et al., 1995). Water entering the head of the delta typically has an SSC of ca. 0.5–1.0 g l�1 (Salomons and Eagle, 1990) but SSCs at the turbidity maximum may reach an average value of 3 g l�1 during spring tides. It is interesting to note that during the neap tides, the SSCs in the delta are apparently comparable to, or lower than the average SSCs in the river above the delta. The physics behind turbidity maximums is relatively well described as they are a common feature of many estuaries. In the case of the Fly River delta, Wolanski et al. (1995) suggest that tidal pumping and baroclinic circulation are both responsible for the turbidity maximum. The baroclinic circulation is particularly effective at transporting sediment upstream during spring tides due to the very high near bed SSC and strong vertical SSC gradients. 4.5.2. Particle Size and Flocculation The particle-size distribution of the suspended sediment changes markedly from the head of the delta to the ocean. The freshwater entering the delta has a typical d50 of 5 mm, i.e., fine silt, with corresponding d10 and d90 of 1 and 18 mm respectively (Wolanski and Gibbs, 1995). Clay-sized particles accounted for only 20% of the suspended sediment. Within the delta, the particle size is smaller, for example in the Southern Entrance, approximately 20 km from the ocean where the salinity averages about 5, the particle size d50 is about 2 mm at the surface (i.e. clay-size) and 4 mm at the bottom (Wolanski and Gibbs, 1995). The process of flocculation is a fundamental process affecting fine-grained particles and sedimentation in most estuaries, and the Fly River delta is no exception. Sediment enters the delta in an unflocculated form but flocs between 30 and 60 mm are commonly found in the delta (Wolanski and Gibbs, 1995). Because of the significant fraction of fine silt (as opposed to clay), many of the flocs are relatively weak and easily break-up with strong tidal

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currents. Typically flocs at slack tide during the neap cycles may reach 60 mm but are smaller, only 30 mm in size, during spring tides. Floc size also varies significantly within a tidal cycle; they are partially destroyed during peak currents, and reform during slack water periods. Flocculation is very important in the formation of the turbidity maximum zone as large flocs have larger fall velocities, allowing an appreciable vertical SSC gradient to form. Flocculation settling rates in saline waters are non-linear (Wolanski et al., 1995). This relationship affects the water-column suspended-sediment profile, and thus is important to modeling sediment fluxes and the turbidity maximum in the delta (Wolanski et al., 1995). Wolanski and Gibbs (1995) suggested that the reduction in mean particle size from fine silt in the freshwater zone to clay in the delta is at least partially caused by the weakness of the flocs composed of fine silt compared with flocs composed of clay. Flocs composed of clays are more likely to hold together in periods of high flow and thus are more likely to settle to the bed where they may be advected upstream by the density-driven current. Silt particles may thus preferentially bypass the delta. 4.5.3. Biological Processes Affecting Sediment Dynamics Biological factors also have a significant influence on the dispersal and ultimate fate of sediments. Once over the continental shelf, the Fly River surface plume loses sediment by a process which is heavily influenced by biological process. Ayukai and Wolanski (1997) studied the sediments, nutrients, and organic material in the plume on an occasion when the plume was partially impinging upon the coral reefs to the south west of the river mouth. It was found that high concentrations remained in the plume until the salinity was about 23 after which there was an abrupt loss of sediment from the plume. It was found that in areas experiencing the sudden loss of sediment, the settling particles were dominated by colonies of phytoplank ton, fecal pellets, and macroscopic aggregates. Blooms of phytoplankton and other biological components are determined by the availability of light and nutrients. In the delta and immediately seaward of the delta mouth, although nutrient levels are high, biological production is limited by the availability of light caused by very high turbidity. Indeed, in the delta, the photic zone is limited to only the top few centimeters of the water column much of the time. As a result of low food availability and dynamic seabed conditions, infaunal abundances within the delta are low (Alongi, 1991; Alongi et al., 1992), and for these reasons, bioturbation is limited in most areas of the delta (Alongi, 1991; Alongi et al., 1992; Dalrymple et al., 2003; Walsh and Nittrouer, 2004).

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The prograding character of numerous coastlines along the delta gives the impression that mangroves play a key role in trapping a considerable amount of muddy Fly River sediments. However, remote-sensing work suggests most islands are relatively persistent features, and there is little net accretion in the delta (Harris et al., 1993). This topic is discussed further below.

4.6. Sediments and Stratigraphy 4.6.1. Sediment Lithology and Facies Most of the sediment (90%) reaching the Fly River delta is fine-grained (i.e., o63 mm), so not surprisingly, a considerable amount of mud comprises the sediments and strata of the delta. Compared to others, the Fly River delta can be viewed as a muddy system (Dalrymple et al., 2003). However, the large tidal range and strong fluvial discharges produce rapid flows in the distri butary channels, particularly during spring flood and ebb tides. Consequently, surficial sediments of distributary channels (at least the major ones) are 80–90% sand; locally, mud percentages are W80% (Harris et al., 1993). Close examination of delta cores reveals considerable variation in lithological characteristics which are related to controlling processes. The modern facies indicate that heterolithic (i.e., composed of alternating sand and mud layers) sediments are widely present, but with varying sand/mud content and structural configuration. The sands are black in color because of their source and immature nature; the most common petrology of sand grains in decreasing order are lithic fragments, quartz, plagioclase feldspar, pyroxene, and hornblende (Spencer, 1974; Baker, 1998). Earlier clay mineralogical work indicated that the smectite-rich Fly River sediment load was overwhelmed by illite-rich sediments of the Strickland River in the delta (Salomons and Eagle, 1990), but more recent research reveals chlorite-group minerals now appear to dominate (Bolton et al., 2009). Using core lithology, geophysical, and sediment transport data from four discrete areas in the delta, in combination with insights from previous work, Dalrymple et al. (2003) describe 10 facies that characterize the entire deltaic system (including the delta front and prodelta; Table 4.1). It should be noted that the facies of Dalrymple et al. (2003) are not numbered in the order they would be anticipated to occur stratigraphically, and considerable variation in the vertical succession and thickness of the facies (i.e., in a deep core) is expected. The spatial arrangement of facies in the modern system is summarized below; these insights can be used to

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Table 4.1: Discrete facies that characterize the Fly River deltaic system (after Dalrymple et al., 2003). Facies 1: Channel-floor sands

Facies 2: Mud–pebble conglomerates

Facies 3: Channel-floor muds Facies 4: Thin-bedded heterolithic stratification deposited on tidal bars and point bars Facies 5: Thinly laminated heterolithic tidal-flat deposits Facies 6: Rooted tidal-flat deposits

Facies 7: Distributary–Mouth–Bar Sands Facies 8: Bioturbated, heterolithic stratification Facies 9: Interbedded heterolithic stratification Facies 10: Prodelta sandy muds

Massive (appearing) sand beds with occasional cross stratification and thin mud layers Mud pebbles (generally 0.5–1 cm in diameter), shell fragments, and wood mixed with sand Composed of thick, homogenous mud layers commonly W0.5 cm thick Mud layers typically thinner than in Facies 3, interbedded with sand layers Laminae generally 1–2 mm where pinstripe lamination and lenticular bedding can be observed Usually muddy, mottled sediments containing mangrove roots, oxidized zones, and dessication cracks Clean, well-sorted sand, averaging 5% clay, and containing cross-bedding and laminations Similar in appearance to Facies 4 and 5 but with increased evidence of bioturbation Thick beds (5–15 cm) of sand and mud generally form the stratification Bioturbated mud-rich sediments, carbonate content increases seaward

Note: These facies are not numbered in the order they anticipated stratigraphically. See text for additional information.

construct an idealized view of stratigraphic development by the application of Walther’s law (see Dalrymple et al., 2003). A facies model of coastal strata in the Fly, Kikori, and Purari area was created by Walsh and Nittrouer (2004) from vibracores, and it agrees well with the upper facies (facies 4–6) of Dalrymple et al. (2003; Table 4.1). Work across the region suggests a consistent stratigraphy is preserved in the intertidal and shallow subtidal zone throughout the western Gulf of Papua, and the characteristics of the deposits are analogous to those of other intertidal areas (with and without mangroves) experiencing a large tidal range (W2 m) and sediment supply (e.g., Ganges–Brahmaputra and Yangtze

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river deltas; Walsh and Nittrouer, 2004). Missing from both of these facies models is representation of pre-Holocene strata. Spencer (1974) identified pre-Holocene strata on the northern end of Kiwai Island and near the southern mainland shoreline of the delta (Fig. 4.2). Based upon these observations, it was hypothesized that some distributary islands may be nucleated on pre-Holocene topographic highs. Walsh and Nittrouer (2004) collected (after much effort) a 65-cm-long vibracore (core ‘‘D’’) on a mainland bank near the apex of the delta. It was composed of indurated, oxidized sediments, which are likely pre-Holocene in age. 4.6.2. Distribution of Pre-Holocene and Modern Facies It is difficult to be certain of the depth to pre-Holocene strata in the delta. Pre-Holocene exposures include the northern end of Kiwai Island (Spencer, 1974) and the southern bank near the delta apex (Walsh and Nittrouer, 2004), and the sequence boundary (i.e., the unconformity between the preHolocene and Holocene sediments) has been identified in seismics in several locations (Dalrymple et al., 2003). Mapping efforts by Lo¨ffler (1977) and Robertson et al. (1991) indicate that a number of the islands in the central Fly River delta (including Kiwai) are vegetated by freshwater plants (non-mangrove species), suggesting these areas may be composed of preHolocene strata (note the distribution of mangroves in Fig. 4.2 following Robertson et al., 1991). The relative sea-level curve for northern Australia (and presumably southern PNG) indicates a sea-level peak (W1 m above modern sea level) in the mid-Holocene (Larcombe et al., 1995), providing another possible explanation for their non-marine nature. Nevertheless, welldefined channels are evident in seismic profiles farther offshore (Harris et al., 1993, 1996; Harris, 1994; Crockett et al., 2005), and it is reasonable to expect that pre-Holocene fluvially derived relief (i.e., a paleovalley) extends throughout the delta. Although an isopach map cannot be created with the existing data, it is noted that the Holocene sediment thickness likely ranges from zero to tens of meters where pre-Holocene lows existed. 4.6.3. Modern Facies Distributions The deepest facies (i.e., Facies 7–10; Table 4.1) are accumulating in reverse order on the prodelta, delta front, and distributary mouth bar (Dalrymple et al., 2003). Detail on the nature of the strata accumulating offshore is described in Harris et al. (1993, 1996), Harris (1994), Walsh et al.

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(2004), and Palinkas et al. (2006). Within the delta, distributary channels typically contain Facies 1–4. The prevalence of mud beds in Facies 3 and 4, mud layers in Facies 1, and mud pebbles in Facies 2 can be explained by the accumulation and reworking of fluid muds in the delta (Dalrymple et al., 2003). During periods of energetic flows (i.e., spring tides) considerable resuspension occurs, resulting in the development of very high SSCs and near bed fluid muds (Wolanski et al., 1995). During periods of slack water, mud layers are deposited in the distributary channels, particularly in deeper areas where the highest sediment concentrations are found (Dalrymple et al., 2003). As a result, mud beds (Facies 3) are expected to deposit at deeper sites and mud pebbles (Facies 2) in erosional areas. The sandy beds of Facies 1 and the thinly bedded mud and sand of Facies 4 are anticipated in shallower subtidal depths and in low- to mid-tidal areas of banks where energetic currents are found. But, in fact, Facies 1 is common in all channel areas, including the deepest portions (Dalrymple et al., 2003). The facies succession moving vertically from an erosional surface in a distributary channel is likely to proceed in the following manner: Facies 2 may mark the erosional boundary. Facies 1 strata may overlie or underlie these sediments for 0.5–1 m, and these will transition gradually into Facies 3 (for 1–3 m) and 4 (Dalrymple et al., 2003). Note, Facies 4 contains beds of mud and sand, generating a coarsening-upward sequence from Facies 3–4. Finally, moving from the upper subtidal to supratidal strata, a fining-upward trend is produced (including a decreasing mud-layer thickness; Facies 4–6). This transition (common to many intertidal areas) is likely a result of decreasing inundation time and SSCs. Facies 6, composed of muddy, mottled mangrove sediments, marks the limit of regular inundation by tidal and fluvial processes. However, at the most seaward islands of the delta, the fining-upward trend into mangrove strata may be less obvious or absent because of winnowing by wave processes (Walsh and Nittrouer, 2004). 4.6.4. Sedimentation Rates A few studies have attempted to quantify sedimentation rates in the Fly River delta. Unfortunately, 210Pb methods do not work well within the delta. 210 Pb activities are low and often variable with depth (i.e., non-steady state), likely because of water, sediment, and scavenging dynamics (Baker et al., 1995; Walsh and Nittrouer, 2004). Also, 137Cs activities are low and variable in the Indo-Pacific region (Kineke and Sternberg, 2000); this coupled with the concern of mobility of 137Cs precludes its use as a radiochemical marker and reliable measure of sedimentation in the delta.

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In a few cases, 210Pb profiles from cores have produced trends which may be interpreted as steady state and from which sediment accumulation rates may be estimated (Fig. 4.4), but as with any profiles without independent verification (e.g., from 137Cs), they must be viewed with caution. A rate of 8–10 cm y�1 was apparent from one core collected from a subtidal area, near an island in the Southern Entrance (Baker et al., 1995). Although very rapid, such rates are conceivable in this deltaic setting and are supported by lithologic evidence. Cycles (10–30 cm thick) of sand–mud lamination couplets are preserved in many delta cores, and are likely deposited by

Figure 4.4: Two 210Pb profiles from cores collected among mangroves in the interior of islands. The supported activity (226Ra) was estimated to be 1 dpm g�1 for both cores. Data are normalized by clay content. Methods are described in Walsh and Nittrouer (2004). Apparent accumulation rates are indicated, but these rates must be viewed with caution, considering the low activities and non-steady-state nature of the sediment supply. See Fig. 4.3d for a photograph near VCR; VCN was collected in a similar mangrove environment.

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complex interaction of fluvial and tidal processes, with neap–spring changes in current velocities playing an important role, such as in the Amazon system (Baker et al., 1995; Jaeger and Nittrouer, 1995; Dalrymple et al., 2003; Walsh and Nittrouer, 2004). In most cases, the number of couplets present in these cycles is less than an ideal semidiurnal tidal sequence (28 couplets over a neap–spring cycle). Nevertheless, the strata provide strong evidence for the impact of tides, and furthermore, suggest that at least portions of the sedimentary strata accumulate at rates on the order of 1–W4 mm d�1, lending credence to high measured accumulation rates (Chappell, 1992; Baker et al., 1995; Dalrymple et al., 2003). Operation of Ok Tedi Mine in the head waters of the Fly River began in 1984. More information about the nature, history, and impacts of the Ok Tedi Mine can be found in other chapters of this book. Copper concentrations above pre-mine levels in the Fly River system provide a useful new tool for quantifying sedimentation, yet limited research has used this approach in the delta. Chappell (1992) and Baker (1998) report that a pronounced post-mine signal is preserved in discrete areas near the delta apex; a peak concentration (144 mg g�1) was found at 80-cm depth in a core collected on a mudbank west of Kiwai Island (Chappell, 1992; Baker, 1998). Farther seaward, the copper signal was less prominent in 1990, presumably because of dilution. It is hypothesized that given more time a post-mine copper signal will be prevalent in sediments over a greater extent of the delta (Chappell, 1992). Accumulation rates can be calculated using the profiles of copper, assuming an approximate time for the local copper concentration increase. Also, sedimentation rates can be compared with lamination cycles, remotely sensed data, and mangrove forest age estimates. Rates from vibracores in shallow, subtidal areas on mud banks in the apex region are estimated to be 1.75–3.5 m y�1 from lamination thickness, and copper profiles reveal sedimentation at these sites likely was deposited within 3 years (prior to sampling). Due to the shallow nature of the sample sites, these rates cannot be sustained for long. Ephemeral deposition over multiannual and shorter timescales is undoubtedly important in the delta, and consequently, storage over this large system is difficult to estimate. Two cores collected in mangrove areas in the interior of inlands have accumulation rates of B1 cm y�1, estimated from 210Pb (Fig. 4.4). If these rates are valid and are assumed to represent sedimentation across the mangrove portions of the islands, the delta may be storing more sediment than previously estimated based on shoreline progradation rates alone (480,000 m3; Harris et al., 1993). For example, if sediment accumulation rates in mangrove areas (covering 874 km2; Robertson et al., 1991) occurs sympathetically with the average the rate of eustatic sea level rise

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(B0.2 cm y�1), commensurate with creation of new accommodation space, storage of an additional 1.8 � 106 t y�1 may be possible. In fact, this estimate can be increased if a similar assumption is made for channel areas. Nevertheless, when compared to the large load of the Fly River (B1.0 � 108 t y�1), modern storage is likely o10% of the total sediment discharge. Although numerous back-of-the-envelope calculations like this can be made, a true budget of sediment sequestered in the delta is elusive (and perhaps is impossible to determine) due to the sheer size of the system and its dynamic nature.

4.7. Shoreline Change Rates Aerial photograph and remotely sensed data have been used to examine shoreline changes in the delta over periods of decades (Chappell, 1992; Hughes and Baker, 1996; Baker, 1998; Walsh and Nittrouer, 2004). Conclusions from this research include: (1) little net change in island area (Baker, 1998); (2) a complex pattern of minor erosion and accretion is evident along many discrete shoreline segments throughout the delta; and (3) a number of small islands have appeared and disappeared over time, particularly near the delta apex. Rates of progradation and erosion in isolated locations are reported up to hundreds of meters per year. More work is needed to quantify this change and understand controlling factors. It is likely that channel migration has an important impact on distributary channel switching and thus on the modern dispersal of sediment seaward. The reader is directed to Dalrymple et al. (2003) for more insights on this topic.

4.8. Topics for Further Study 4.8.1. Fluid–Mud Dynamics Fluid muds have been observed within the Fly River delta (Wolanski and Eagle, 1991; Wolanski et al., 1995) and are hypothesized to be important in moving sediment across the prodelta (topset and foreset beds of the subaqueous shelf clinoform) (Harris et al., 1993, 2004; Dalrymple et al., 2003; Walsh et al., 2004). The low 210Pb and high clay content of deposits on the foreset region of the clinoform imply a fluid–mud transport mechanism on the shelf (Walsh et al., 2004), which may be an important process enhancing terrestrial carbon storage. Formation of fluid muds in the delta by tidal

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processes is reasonably well documented (Wolanski and Eagle, 1991; Wolanski et al., 1995), but it is not clear if and how these fluid muds traverse the shelf (Harris et al., 2004; Walsh et al., 2004). Tidal currents alone do not appear to be sufficient to transport fluid muds from the delta to the foreset region, suggesting seasonal wave dynamics also must be important (Harris et al., 1993, 2004; Walsh et al., 2004). More research is needed to examine fluid-mud formation, transport, and accumulation throughout the Fly River dispersal system. Sediment and carbon dynamics on the shelf actively are being examined by Chuck Nittrouer, Andrea Ogston, Miguel Goni, John Crockett, and others as part of the Source to Sink (S2S) Initiative of the US National Science Foundation Margins Program (Crockett et al., 2009). 4.8.2. A Field, Remote Sensing and Modeling Approach to Understand Delta Sedimentation The elevated copper signal produced by mining upstream of the delta provides a unique tool to quantify sedimentary processes in the delta. A core collection effort guided by a detailed remote-sensing analysis and geophysical survey work (chirp and multibeam) could provide an improved understanding of modern sediment dynamics in the delta and insight on how the geologic history (e.g., delta switching or allocyclic factors like sediment supply) may have influenced it. However, the sheer size and dynamic nature of this system precludes a field study from thoroughly characterizing the system. For this reason, any field-based study should run concurrently with (or at least be guided by) a modeling effort. Sergio Fargherazzi (Florida State University), Irina Overeem, and Scott Peckham (University of Colorado at Boulder) are currently using a modeling approach to evaluate the morphological and stratigraphic evolution of this delta system, also as part S2S. 4.8.3. Tectonic Control on Delta Evolution The Fly River flows across a tectonically active foreland basin, experiencing spatially varying rates of subsidence (Veevers, 1984; Pigram et al., 1989). The ‘‘Oriomo Uplift’’ 36,000 y.b.p. is hypothesized to have shifted the Fly River from flowing southwestward to its present course (Blake and Ollier, 1971; Torgersen et al., 1985). It is unknown how this tectonic history has impacted the evolution and stratigraphy of the delta. A comprehensive seismic, coring, and drilling expedition is needed to determine the evolution of the delta and evaluate the degree to which the past is the key to the present.

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4.9. Conclusions Based on insights from studies cited above, we understand the modern Fly River delta is a region of great and complex sediment transport and ephemeral deposition, yet it experiences relatively little modern sediment accumulation and storage. Through lithologic and transport data, it appears the delta behaves primarily as a discharge signal filter for sediments accumu lating in the delta seabed and those on route to the Gulf of Papua shelf. This concept is captured in a cartoon which illustrates the major forcing factors for sedimentation in the Fly River dispersal system (Fig. 4.5; Walsh et al., 2004). The large, interannually varying discharge of water and sediment to the Fly River delta is met by strong, semidiurnal tides propagating landward from the ocean. Here, energetic tidal currents produce the morphological characteristics of a tide-dominated delta and a muddy stratigraphy dominated by associated signatures (e.g., cyclic, interlaminated mud and sand deposits). Ultimately, these tides with help from river discharge and seasonal wave processes are thought to control the transfer of sediment farther along the dispersal, across the continental shelf. More work is needed to better understand sediment dispersal processes today and those recorded in delta strata.

Figure 4.5: Forcing functions driving sedimentation processes in the Fly River dispersal system (edited from Walsh et al., 2004, with permission from Elsevier). Note, the river-discharge, tidal and wave signals of sediment transport converge and are convolved at the Fly River delta.

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ACKNOWLEDGMENTS

This paper is dedicated to Bruce Parker who passed away from cancer in 2003. Bruce, an employee of the Australian Institution of Marine Science assisted J.P. Walsh and Pete Swarzenski (USGS) with the collection of vibracores in the Fly River delta during September 1997. Bruce, who was head of the coral drilling program at the Australian Institute of Marine Science, was baffled by our desire to work in the delta, an extremely muddy habitat for crocodiles. But, he provided invaluable knowledge, unwavering support, and great companionship to help make the research successful. Many others are acknowledged for enabling our research in this area, especially, Gregg Brunskill, Chuck Nittrouer, Dick Sternberg, and Irena Zagorskis. Funding from a MARGINS S2S National Science Foundation grant (OCE-0452166) helped support the writing of this paper.

REFERENCES Alongi, D. M. (1991). The role of intertidal mudbanks in the diagenesis and export of dissolved particulate materials from the Fly Delta, Papua New Guinea. Journal of Experimental Marine Biology and Ecology, 149, 81–107. Alongi, D. M., Christofferson, P., Tirendi, F., & Robertson, A. I. (1992). The influence of freshwater and material export on sedimentary facies and benthic processes within the Fly Delta and adjacent Gulf of Papua (PNG). Continental Shelf Research, 12, 287–326. Aubrey, D. G., & Friedrichs, C. T. (1988). Seasonal climatology of tidal non linearities in a shallow estuary. In: D. G. Aubrey, & L. Weishar (Eds). Hydrodynamics and Sediment Dynamics of Tidal Inlets. Springer, Berlin, pp. 103–124. Ayukai, T., & Wolanski, E. (1997). Importance of biologically mediated removal of fine sediments from the Fly River plume, Papua New Guinea. Estuarine, Coastal and Shelf Science, 44, 629–639. Baker, E.K. (1998). Sedimentation in a tidally dominated delta and the impact of upstream mining: Fly River, Papua New Guinea. Unpublished Ph.D. Thesis, University of Sydney. Baker, E. K., Harris, P. T., Short, S. A., & Keene, J. B. (1995). Patterns of sedimentation in the Fly River Delta. In: B. W. Fleming & A. Bartholoma (Eds). Tidal Signatures in Modern and Ancient Sediments: International Association of Sedimentologists Special Publication, Wiley Blackwell Publishing, Oxford, Vol. 24, pp. 122–193. Blake, D. H., & Ollier, C. D. (1971). Alluvial plains of the Fly River delta. Z. Geomorph. Zeitschrift fu¨r Geomorphologie, Suppl., 12, 28–32.

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Bolton, B. R., Pile, J. P., & Kundapen, H. (2009). Texture, geochemistry, and mineralogy of sediments of the Fly River system. In: B. Bolton (Ed.), The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System. Elsevier, Amsterdam, Vol. 9, 51–112. Chappell, J. (1992). Effects of increased sediment flux in the Fly River delta: Sediment core results. Australian National University, School of Biogeography & Geomorphology. Report to Ok Tedi Mining Limited dated 1992. 64 pp. Coleman, J. M., & Wright, L. D. (1975). Modern river deltas: Variability of processes and sand bodies. In: M. L. Broussard (Ed.). Deltas, Models for Exploration. Houston Geological Society, Houston, pp. 99–149. Crockett, J., Nittrouer, C., Ogston, A., Sternberg, R., Driscoll, N., Babcock, J., Milliman, J., Slingerland, R., Naar, D., Donahue, B., Walsh, J., Dietrich, W., Parker, G., Bera, M., Davies, H., Harris, P., Goni, M., Aller, R., & Aller, J. (2005). Where rivers and oceans collide: Geological complexities of this interface revealed by the NSF MARGINS program. EOS, Transactions, 83(6), 1–32. Crockett, J., Nittrouer, C. A., Ogston, A. S., & Goni, M. A. (2009). Variable styles of sediment accumulation impacting strata formation on a clinoform: Gulf of Papua, Papua New Guinea. In: B. Bolton (Ed.), The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System. Elsevier, Amsterdam, Vol. 9, 177–204. Dalrymple, R. W., Baker, E. K., Harris, P. T., & Hughes, M. G. (2003). Sedimentology and stratigraphy of a tide-dominated, foreland basin delta (Fly River, Papua New Guinea). In: H. Sidi, D. Nummedal, P. Imbert, H. Darman, & H. W. Posamentier (Eds). Tropical Deltas of Southeast Asia-Sedimentology, Stratigraphy and Petroleum Geology. SEPM Special Publication No. 76, pp. 147–173. D’Addario, G. W., Dow, D. B., & Swoboda, R. (1976). Geology of Papua New Guinea 1:2,500,000. Bureau of Mineral Resources, Canberra, Australia. Dietrich, W. E., Day, G., & Parker, G. (1999). The Fly River, Papua New Guinea: Inferences about river dynamics, floodplain sedimentation and fate of sediment. In: A. J. Miller, & A. Gupta (Eds). Varieties of Fluvial Form. Wiley, New York, pp. 345–376. Galloway, W. E. (1975). Process framework for describing the morphologic and stratigraphic evolution of deltaic depositional systems. In: M. L. Broussard (Ed.). Deltas, Models for Exploration. Houston Geological Society, Houston, pp. 87–98. Harris, P. T. (1994). Incised valleys and backstepping deltaic deposits in a forelandbasin setting, Torres Strait and Gulf of Papua, Australia. In: R. W. Dalrymple, R. Boyd, & B. A. Zaitlin (Eds). Incised-Valley Systems: Origin and Sedimentary Sequences. SEPM Special Publication No. 51, pp. 98–108. Harris, P. T., Baker, E. K., Cole, A. R., & Short, S. A. (1993). A preliminary study of sedimentation in the tidally dominated Fly River Delta, Gulf of Papua. Continental Shelf Research, 13, 441–472. Harris, P. T., Pattiaratchi, C. B., Keene, J. B., Dalrymple, R. W., Gardner, J. V., Baker, E. K., Cole, A. R., Mitchell, D., Gibbs, P., & Schroeder, W. W. (1996). Late Quaternary deltaic and carbonate sedimentation in the Gulf of Papua

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foreland basin: Response to sea level change. Journal of Sedimentary Research, 66, 801–819. Harris, P. T., Hughes, M. G., Baker, E. K., Dalrymple, R. W., & Keene, J. B. (2004). Sediment transport in distributory channels and its export to the prodeltaic environment in a tidally dominated delta: Fly River, Papua New Guinea. Continental Shelf Research, 24(10), 2431–2454. Hughes, M. G., & Baker, E. K. (1996). Using satellite remote sensing data to identify coastal changes in the Fly River Delta, PNG – pilot study. Ocean Science Institute Report No. 68. Jaeger, J. M., & Nittrouer, C. A. (1995). Tidal controls on the formation of fine-scale sedimentary strata near the Amazon River mouth. Marine Geology, 125, 259–281. Jukes, J. B. (1847). Narrative of the Surveying Voyage of H.M.S. Fly, Commanded by Captain F.P. Blackwood, R.N., in Torres Strait, New Guinea and Other Islands of the Eastern Archipeligo During the Years 1842–1846, Vols I and II. T&W. Boone, London. Kineke, G. C., & Sternberg, R. W. (2000). Sediment dispersal from the Sepik River, Papua New Guinea, via surface and subsurface plumes. EOS, Transactions, 80, 49, OS218. Larcombe, P., Carter, R. M., Dye, J., Gagan, M. K., & Johnson, D. P. (1995). New evidence for episodic post-glacial sea-level rise, central Great Barrier Reef, Australia. Marine Geology, 127, 1–44. Lo¨ffler, E. (1977). Geomorphology of Papua New Guinea. Australian National University Press, Canberra, 258 pp. Milliman, J. D., Farnsworth, K. L., & Albertin, C. S. (1999). Flux and fate of fluvial sediments leaving large islands in the East Indies. Netherlands Journal of Sea Research, 41, 97–107. Ok Tedi Mining Limited (1988). Sixth supplement agreement environmental study 1986–1988. Final Draft Report OTML, PNG. Palinkas, C. M., Nittrouer, C. A., & Walsh, J. P. (2006). Inner-shelf sedimentation in the Gulf of Papua, New Guinea: A mud-rich shallow shelf setting. Journal of Coastal Research, 22, 760–772. Pickup, G. (1984). Geomorphology of tropical rivers: I. Landforms, hydrology and sedimentation in the Fly and lower Purari, Papua New Guinea. In: A. P. Schick (Ed.). Channel Processes – Water, Sediment, Catchment Controls. Braunschweig, Catena Supplement 5, Catena-Verlag, Reiskirchen, Germany, pp. 1–17. Pigram, C. J., Davies, P. J., Feary, D. A., & Symonds, P. A. (1989). Tectonic controls on carbonate platform evolution in southern PNG: Passive margin to foreland basin. Geology, 17, 199–202. Pritchard, D. W. (1967). What is an estuary, physical viewpoint. In: G. H. Lauf (Ed.). Estuaries. American Association for the Advancement of Science, Washington D.C., publ. no. 83. Provis, D. G., & Lennon, G. W. (1983). Eddy viscosity and tidal cycles in a shallow sea. Estuarine and Coastal Shelf Science, 16, 351–361.

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Robertson, A. I., Daniel, P. A., & Dixon, P. (1991). Mangrove forest structure and productivity in the Fly River estuary, Papua New Guinea. Marine Biology, 111, 147–155. Salomons, W., & Eagle, A. M. (1990). Hydrology, sedimentology and the fate and distribution of copper in mine-derived discharges in the Fly River system, Papua New Guinea. The Science of the Total Environment, 97/98, 315–334. Spencer, L. K. (1974). Sedimentation and geological history of the Fly River region, Papua. M.Sc. Preliminary Report. University of Sydney, 58 pp. Spencer, L. K. (1978). The Fly estuarine delta, Gulf of Papua, Papua New Guinea. Unpublished M.Sc. Thesis, University of Sydney, 278 pp. Thom, B. G., & Wright, L. D. (1983). Geomorphology of the Purari Delta. In: T. Petr (Ed.). The Purari: Tropical Environment of a High Rainfall River Basin. Dr. W. Junk Publishers, The Hague, 624 pp. Torgersen, T., Jones, M. R., Stephes, A. W., Searle, D. E., & Ullman, W. J. (1985). Late Quaternary hydrologic changes in the Gulf of Carpentaria. Nature, 13, 785–787. Veevers, J. J. (1984). Phanerozoic Earth History of Australia. Clarendon Press, Oxford, 418 pp. Walsh, J. P., & Nittrouer, C. A. (2004). Mangrove-bank sedimentation in a mesotidal environment with large sediment supply, Gulf of Papua. Marine Geology, 208, 225–248. Walsh, J. P., Driscoll, N. W., & Nittrouer, C. A. (2003). Controls on subaqueousdelta clinoform development. EOS, Transactions, 84(46), OS12A-0188. Walsh, J. P., Nittrouer, C. A., Palinkas, C., Ogston, A. S., Sternberg, R. W., & Brunskill, G. J. (2004). Clinoform mechanics in the Gulf of Papua, New Guinea. Continental Shelf Research, 24, 2487–2510. Wolanski, E. (1994). Physical Oceanographic Processes of the Great Barrier Reef. CRC Press, Boca Raton, USA, 185 pp. Wolanski, E., & Eagle, M. (1991). Oceanography and sediment transport in the Fly River estuary and Gulf of Papua. In: Proceedings 10th Australasian Conference on Coastal and Ocean Engineering, Auckland, pp. 453–457. Wolanski, E., & Gibbs, R. J. (1995). Flocculation of suspended sediment in the Fly River estuary, Papua New Guinea. Journal of Coastal Research, 11(3), 754–762. Wolanski, E., King, B., & Galloway, D. (1995). Dynamics of the turbidity maximum in the Fly River estuary, Papua New Guinea. Estuarine, Coastal and Shelf Science, 40, 321–337. Wolanski, E., King, B., & Galloway, D. (1997). Salinity intrusion in the Fly River estuary, Papua New Guinea. Journal of Coastal Research, 13, 983–994. Wright, L. D. (1985). River deltas. In: R. A. Davis (Ed.). Coastal Sedimentary Environments. 2nd Edn., Springer-Verlag, New York, pp. 1–75.


Chapter 5

Variable Styles of Sediment Accumulation Impacting Strata Formation on a Clinoform: Gulf of Papua, Papua New Guinea John S. Crockett1, Charles A. Nittrouer1,, Andrea S. Ogston1 and Miguel A. Goni2 1

School of Oceanography, University of Washington, Seattle, WA 98195, USA College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA 2

5.1. Introduction Clinoforms are sigmoidal-shaped deposits on the continental shelf, and have been recognized as the basic building blocks of continental margin morphology (Mitchum et al., 1977). Clinoforms are well represented in the ancient geological record (e.g., Asquith, 1970; Leithold, 1993) and are common on modern shelves adjacent to large rivers (e.g., Ganges–Brahmaputra, Kuehl et al., 1989; Huang He, Alexander et al., 1991; Liu et al., 2004; and Amazon, Nittrouer et al., 1986a). While a general understanding of the factors that affect the evolution of clinoform strata exists, we are still improving our ability to quantify processes responsible for the sedimentary deposits that are the building blocks of these stratigraphic environments. The across-shelf anatomy of a clinoform includes a landward topset, where sediment accumulation is slow due to enhanced shear stresses created by waves and currents; a foreset in deeper water, where shear stresses decrease and accumulation is rapid; and a seaward bottomset, where accumulation is Corresponding author. Tel.: 206-543-5099; Fax: 206-543-6073;

E-mail: [email protected] (C.A. Nittrouer).

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wave- and current-induced shear stress inhibits sediment deposition in shallow water

rollover point

topset

deeper water creates a “stress refuge” and allows accumulation on the foreset

reduced sediment supply causes slow accumulation on the bottomset

foreset

bottomset

Figure 5.1: Schematic illustration of two-dimensional clinoform growth. Significant processes for each region are indicated. The distribution of accumulation rates allows the clinoform to prograde into deeper water while maintaining a self-similar shape. slow due to reduced sediment supply (Fig. 5.1). The dimensions, shape, and sedimentary fabric of clinoforms contain information about the depositional conditions. Interpretation of this record in the context of sea-level change, basin subsidence, and sediment supply is a fundamental element in the stratigraphic approach to investigating sedimentary sequences (Vail et al., 1977; Vail, 1987; Posamentier et al., 1988; Van Wagoner et al., 1990). Previous studies quantifying the factors that influence clinoform shape have focused predominantly on the rate and mechanisms of clinoform progradation into deeper water (e.g., Wright et al., 1988; Kuehl et al., 1989; Alexander et al., 1991; Nittrouer et al., 1996). Clinoforms have been modeled primarily as two-dimensional (2-D) features with variation only in the across-shelf dimension (as a function of distance from shore and water depth). The 2-D approach has been reasonable and has led to important discoveries concerning the processes that govern clinoform growth. However, most clinoforms extend for hundreds of kilometers along shelf, which suggests that different processes likely operate to cause diversity of sedimentation over this distance. It is the aggregate of processes that creates the gross morphology. However, the three-dimensional (3-D) complexity of clinoform development is poorly known. Depending on the characteristics of the river discharge (e.g., amount, grain size, and variability of discharge) and ocean conditions (e.g., waves and currents), sediment can accumulate in either a steady-state fashion, an episodic fashion, or both. On the continental shelf adjacent to the Fly River in Papua New Guinea, clinoform accumulation was examined by earlier

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studies (e.g., Harris et al., 1993; Walsh et al., 2004). However, these studies of sedimentation included limited sediment cores near the mouth of the Fly River. Through the present study, data addressing the along-shelf heterogeneity of clinoform progradation have been obtained and can be used to appraise the 3-D character of clinoform processes. The objectives of this paper are to (1) identify the styles of sediment accumulation and their distribution on the Fly River shelf, (2) relate the styles of accumulation to oceanographic processes, and (3) present a more complete picture of the complex processes that are responsible for creating the clinoform deposit found on the Fly River shelf.

5.2. Background 5.2.1. Physical Setting The Gulf of Papua (GOP) is located off the southeastern coast of New Guinea (Fig. 5.2). The Fly River discharges into the western side of the GOP and supplies 1.15 108 t/y of sediment (Milliman, 1995), which makes it one of the world’s top 20 rivers in terms of sediment supply to the ocean (Milliman and Meade, 1983). New Guinea has a rugged mountain range running down the center of the island, with peaks W4,000 m in elevation that receive W10 m/y of precipitation (Harris et al., 1993). Rainfall decreases to B2 m/y at the coast. The steep slopes and high rainfall produce large denudation rates of 3–4 mm/y (Pickup, 1984). The great relief of the highlands gives way to an extensive alluvial plain across which the Fly River system meanders for the final 800 km, with only a 20-m change in elevation. Under typical Pacific Ocean conditions, warm water resides as a pool north of New Guinea, causing high rates of precipitation and creating wet tropical conditions for New Guinea. The extensive floodplains and relatively constant rainfall combine to produce a hydrograph for the Fly River that typically varies by less than a factor of 2–3 over the seasonal cycle (Nittrouer et al., 1995). However, the GOP can be subject to some large-scale climatic effects. During El Ninõ conditions, the warm pool is displaced to the eastern Pacific, precipitation is reduced in the highlands of New Guinea, and rivers dramatically decrease their discharge into the GOP. The Fly River mouth has the classic morphology of a tide-dominated delta (Fisher et al., 1969; Galloway, 1975; Wright, 1977, 1985; Miall, 1984). It is generally mesotidal (2–4 m range, reaching a maximum of B5 m at the delta apex during spring tides; Wolanski and Alongi, 1995) and produces tidal

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0 °N

New Guinea 8°0′S

10°S

5m

15m

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T13-20 T13-30 T9-18 T9-30

8°30′S T8-16

T13-48 T13-65 T12-35

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8°45′S

150°E

140°E

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T8-50 T7-30 T6-30

T8-60 Depth in Meters

T5-40 T4-30 T4-50 T2-17

9°0′S T1-17 T1-23

20 40

T2-30

60

9°15′S

80

0 143°30′E

10

100

20 Kilometers 143°45′E

144°0′E

144°15′E

144°30′E

Figure 5.2: The Fly River margin was divided into 13 shore-perpendicular transects, which were resampled on a seasonal basis. Transect T1 is located at the southwest end of the study area, and transect T13 is in the northeast. Each transect is separated from the next by B10 km. T8 corresponds to Umuda shelf valley, and T4 is Kiwai Valley. Station locations are superimposed on a multibeam bathymetric survey (colored isobaths) undertaken for portions of the Gulf of Papua (see Crockett et al., 2008). currents W100 cm/s in the distributary channels of the delta (Ogston et al., 2008). The climate of the GOP is dominated by seasonal fluctuations between monsoon and trade-wind seasons. During the monsoon season (December–March), winds blow from the northwest and waves are


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fetch-limited, creating wave heights that are typically o0.3 m. Waves generated by the trade winds (May–October) enter the GOP from the southeast with a very long fetch and typically are W1.3 m in height (Thom and Wright, 1983). Large frontal storms rarely travel within 101 of the equator (Pielke, 1990) and have little direct impact on the GOP. 5.2.2. Sedimentary Setting The large sediment supply and a broad (W150 km) continental shelf in the GOP together provide an environment conducive to the creation of a clinoform (Walsh et al., 2004). The modern clinoform of the Fly River is building over the continental shelf and extends to B65-m water depth (Slingerland et al., 2008). The shelf gently slopes from the base of the modern clinoform to the shelf break at B150-m water depth. By using mean wave heights (Thom and Wright, 1983) and tidal currents from one location, Walsh et al. (2004) demonstrated that the depth to the ‘‘rollover point’’ separating topset from foreset (Fig. 5.1; B25–40 m, deepening toward the northeast) is likely influenced by the bed shear stress resulting from combined waves and currents. Due to seasonal variability, shear stresses are sufficient to transport sediment from the topset to the foreset during the trade-wind season and insufficient to transport sediment during the monsoon season. Several subaqueous valleys incise the Fly River shelf (Crockett et al., 2008). Kiwai Valley is narrow, steep-sided and extends seaward from the Fly River delta (Fig. 5.2). Umuda Valley is a broad valley and extends seaward from the northernmost distributary of the Fly River delta (Fig. 5.2). These shelf valleys presently accumulate a small fraction of the overall sediment supplied from the Fly River (o1%, Crockett et al., 2008) because of their small areal extent. Sediment from the prograding clinoform accumulates in the valleys, and they also serve as conduits for moving sediment across shelf via gravity-driven flows. 5.2.3. 210

210

Pb Geochronology

Pb is a member of the 238U natural radioactive series and is found in seawater as a result of runoff, atmospheric precipitation, and the decay of its 226 Ra precursor in the water column (Bruland, 1974). 210Pb has a half-life of 22.3 y and therefore is appropriate to use in the examination of sediment accumulation over the past century (Nittrouer et al., 1979). In seawater, 210 Pb is permanently adsorbed onto the surfaces of sediment particles and

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the relatively rapid removal of 210Pb from seawater causes it to occur in sediment at activities above those supported by the decay of 226Ra there. This process creates activities of two types in the seabed: ‘‘excess’’ activity, which indicates the presence of 210Pb scavenged from seawater to the surfaces of particles; and ‘‘supported’’ activity, which is generated by the decay of 226Ra contained within particles. Because of analytical limitations associated with relatively low initial activities supplied to the surface of the seabed in coastal environments, excess activity can be detected only until four to five half-lives of the radioisotope have elapsed. If excess 210Pb activity is present, the sediment was deposited in the past century. 210 Pb geochronology has been utilized in most aqueous environments. In the marine environment, it has been used effectively to measure steady-state sediment accumulation rates on the continental shelf. When sediment is deposited on the seabed, it is effectively removed from the presence of excess 210Pb in the water column, and the acquired activity decays toward the supported level. At a location where sediment is steadily accumulating, a profile of 210Pb activity shows a logarithmic decrease. The slope of a line fit to the activities can be used to calculate the rate of sediment accumulation at that site. In some cases, physical and biological reworking of the seabed can create a surface mixed layer (SML) of uniform 210Pb activity, below which sediment accumulates in a steady-state fashion. 210 Pb profiles do not always follow this simple pattern. Initial 210Pb activity reaching the seabed can be influenced by particle size (210Pb preferentially adsorbs to clay particles, which have relatively large surface areas). Other factors affecting excess 210Pb activities are the amount of dissolved 210Pb in the water column, suspended-sediment concentration during deposition, and resuspension that exposes particles to dissolved 210Pb. All of these factors either separately or together can conspire to produce activity profiles that vary with depth in core and do not decrease logarithmically. This is an indication that sediment accumulation is a non-steady-state process and is impacted by variability in the factors described above. Non-steady-state sedimentation often results from episodic events that have an easily identified signature. On the Eel River shelf, California, floodrelated deposition creates beds with low, uniform 210Pb activity because of competitive scavenging by particles during high-concentration deposition events (Sommerfield and Nittrouer, 1999). Similar profiles have been observed on the Fly River shelf and termed ‘‘event horizons’’ (Walsh et al., 2004). The adsorption of 210Pb onto sediment particles is limited for high sediment concentrations due to (1) the presence of a lutocline that inhibits mixing of sediment and water in the bottom boundary layer (BBL) (Ross and Mehta, 1989), and (2) competitive scavenging by which many sediment particles share the available dissolved 210Pb. Both of these processes cause low


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activity for individual particles when transport and deposition rates are high (Sommerfield and Nittrouer, 1999).

5.3. Methods To provide comprehensive coverage of the study area, the shelf at the mouth of the Fly River was divided into 13 shore-perpendicular transects. Transect T1 is located at the southwestern boundary of the delta and transect T13 is located beyond the northeastern boundary of the Fly River mouth, in the central GOP (Fig. 5.2). Each transect is separated from the next by B10 km. Stations are denoted by their transect number followed by the nominal water depth (e.g., site T13-20 is on transect T13 in B20 m of water). Two to seven stations were reoccupied seasonally on each transect. At each site occupied, a box core (B50 cm in length) and a kasten core (B300 cm in length) were collected. Box cores were used to capture the sediment–water interface for evaluation of seasonal changes in the seabed and collected at least once each season. Kasten cores were used to evaluate the longer-term sedimentary history of the site. 5.3.1. Sedimentary Analysis From each box and kasten core, 2.5-cm-thick slabs (covering the entire core length) were removed and X-rayed to reveal internal sedimentary structures. A 15-cm PVC tube was inserted into box cores and was subsampled every 1 cm down to 10-cm depth, then every 2 cm to the bottom of the core. To measure grain size, the samples were wet sieved at 63 mm to separate the sand fraction from the mud (i.e., silt and clay). The sand was subsequently dried and weighed. The grain size of the mud fraction was analyzed by a Sedigraph 5100. Clay and silt mass percentages were corrected for the total mass of the sample. Grain-size variations were used to corroborate the changes observed in Xradiographs. Kasten cores were subsampled directly from the core barrels. One sample was collected every 2 cm down to 50-cm depth, then every other 2 cm to the bottom of the core. Grain size was also measured on kasten-core samples. 5.3.2.

210

Pb Analysis

To document decadal-scale sediment accumulation rates, 210Pb was used. 210 Pb activities were determined using a method modified from Nittrouer et al. (1979). Sediment samples were dried and ground to expose surface areas.

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Approximately 5 g of sample was spiked with a known amount of 209Po to quantify the efficiency of the laboratory procedures. 210Po, the effective daughter of 210Pb, was chemically released from the sediment by leaching in 16N HNO3 and 6N HCl. Both 209Po and 210Po were removed from the leachate onto silver planchets by spontaneous electrodeposition. Alpha decay detected from the planchets was measured over B24 h. From the measured activity of 210Po, the activity of 210Pb was calculated. Activities were normalized to the salt-corrected dry mass and expressed as decay per minute per gram (dpm/g). All activities were decay-corrected to the time of collection.

5.3.3. Bottom-Boundary-Layer Tripods To measure sediment-transport conditions near the seabed, a series of BBL tripods were deployed, and more details of the data can be found in Ogston et al. (2008) and Martin et al. (2008). A tripod at T13-20 is used in this paper to represent conditions on the outer topset. The tripod was configured to measure nearbed currents (acoustic Doppler velocimeter, electromagnetic current meter), tides and waves (pressure sensor), suspended-sediment concentration (optical backscatterance sensor, OBS), and water-column currents (upward-looking acoustic Doppler current profiler). The tripod was deployed during trade-wind conditions for 4 weeks in August and September 2003. Subsequent deployments were during monsoon conditions for 4 weeks in January and February 2004, and during transition conditions for 4 weeks in April and May 2004.

5.3.4. Bottom-Boundary-Layer Data Processing 5.3.4.1. Currents Current observations were averaged over an 8-min burst collected each hour. The wave-orbital velocity was calculated using the root-mean-square of the velocity fluctuations around the mean velocity in each hourly burst. The wave height and period were evaluated from the spectrum of pressure within the individual bursts. The dominant period was identified in the spectrum, and the significant wave height was determined from the spectral energy. Current and wave velocities were used to estimate bottom shear stress (tb) according to the Grant–Madsen model (Grant and Madsen, 1979). A bed roughness of 0.2 cm was used, based on field observations of the seabed recovered in box cores. Bottom stresses are reported as shear


velocities (u): rffiffiffiffiffi tb un ¼ r

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(1)

where r is the density of sea water (1.027 g/cm3).

5.3.4.2. Suspended-sediment concentration Suspended-sediment concentration was determined from OBS measurements, which were calibrated with surficial seabed sediment before and after each deployment. Calibrations were performed by mixing specific concentrations of suspended sediment and documenting the relationship between the concentration and the sensor response. No evidence was seen at the T13-20 site of the very-high-concentration turnaround in OBS response that has been documented by other studies (e.g., Kineke et al., 1996; Ogston et al., 2000).

5.4. Results 5.4.1. Sediment Accumulation Seven distinct styles of sediment accumulation have been identified on the Fly River shelf (Fig. 5.3). An eighth sedimentary condition is typified by uniform, supported 210Pb activities, indicating that negligible modern accumulation occurs – a condition common in the southwestern portion of the study area (transects T1, T2, and T3). Steady-state accumulation profiles that exhibit logarithmic decay with no SML are confined to Umuda Valley (T8) and southwest of that feature. Steady-state profiles are further subdivided by accumulation rates with those W1.0 cm/y designated ‘‘rapid’’ or Type I, and those o1.0 cm/y designated ‘‘slow’’ or Type II (Fig. 5.3). Neither style of steady-state accumulation (rapid and slow) is present northeast of Umuda Valley and they occur primarily on transects T4, T6, T7, and T8. Site T8-60 has a profile that indicates a clear change in accumulation rate because of the slope change in the decay profile, and this is designated Type III. Event layers (Walsh et al., 2004) are present near the surface of cores T5-40 and T10-40 and this style is Type IV. A thick, uniform SML can unconformably overlie sediment with supported activity (T8-16, T8-18, and T10-17), which is Type V. Type VI is defined as a uniform SML overlying a

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T8-50 20

10

40 20 60 30

80

SAR = 1.2 cm/y

100 0.1

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SAR = 0.2 cm/y 10

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Type I: Steady-state accumulation rate with rapid accumulation 0

0

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1 Type II: Steady-state accumulation rate with slow accumulation 20

40

60

80

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100 T5-40

event layer

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SAR = 0.5 cm/y

100

60 80 0.1

0 20 40 60 80 100 120 140 160 180 0.1

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1 Type III: Steady-state accumulation at different rates

10

T10-17

200 0.1

SAR = 2.0 cm/y

1 Type IV: Event layer in surface sediment with steady-state accumulation below

10

0 T9-18 50 100 SAR = 3.0 cm/y

150

1 Type V: Uniform surface activity with background activity below

10

200 0.1

1 Type VI: Uniform surface layer with steady-state accumulation below

0 T12-35 50 Type VII: Quasi-steady-state accumulation with varying activity

100 150 SAR = 5.5 cm/y 200 0.1

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Pb Activity (dpm/g)

10

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region of logarithmic decrease (T7-30, T8-20, T9-18, T9-30, and T10-60). A final sedimentary style is characterized by variable activity with a general trend of decreasing activity with depth in core (T11-36, T12-35, T13-30, T13-48, and T13-65) and is labeled Type VII. Non-steady-state accumulation is common northeast of T5, and is particularly prevalent in shallow depths of Umuda Valley (T8) and on transects farther northeastward. X-radiography of non-steady-state cores reveals sedimentary structure that is dominated by physical stratification.

5.4.2. Bottom-Boundary-Layer Sediment Transport 5.4.2.1. Trade-wind conditions Waves during trade-wind conditions had a significant height of 1.2 m with a period of B8 s. They generated a significant wave-orbital velocity of 13.8 cm/s in 20 m of water on the open clinoform (site T13-20). The significant tidal-current velocity was 41.6 cm/s at 1 mab (meter above bed) for the same site. Shear velocities and suspended-sediment concentrations were analyzed to compare seasonal variability in sediment resuspension. During trade-wind conditions, maximum current shear velocities (u) reached 3.4 cm/s on the open clinoform. Currents are predominantly generated by tides in this region, and periods of slack water occur with Figure 5.3: Seven styles of sediment accumulation have been identified within the seabed (vertical axis is depth in core, cm; closed circles are total 210 Pb activity; open circles are excess 210Pb activity). Type I: Steady-state sedimentation with high sediment accumulation rate (SAR) indicates relatively rapid and constant input of sediment to the seabed. Type II: Slow accumulation results from less sediment supply to a site. Type III: Changing slopes in the activity profiles indicate that the rate of sediment accumulation has changed at these sites. Type IV: Event layers are identified by layers with a decrease in 210Pb activity correlated with an increase in clay content (% clay shown by triangles and scale across top). Type V: Excess activity lies unconformably on sediment with only background activity, which is found predominantly in shallow (o20 m) water. Type VI: A thick uniform surface layer is a common feature in the northeastern portion of the study area. Type VII: Variable activity with a decreasing trend down core results from variations in the initial activity of accumulating sediment on timescales that are short compared to the timescale of accumulation.

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negligible velocity. Combined wave–current shear velocities reach a maximum of 4.6 cm/s and a minimum of near zero for some slack tidal periods (Fig. 5.4). Suspended-sediment concentration varies with shear velocity (r2 ¼ 0.44), and reaches a maximum of 0.58 g/l and a minimum of 0.02 g/l at 13 cmab (centimeter above bed) (Fig. 5.5). Along-shelf profiling indicates that high suspended-sediment concentrations are present both to the southwest (in Umuda Valley maximum, W10 g/l) and farther northeast of transect T13 (Martin et al., 2008). T13-20 is a representative site for this region of the shelf. Comparing the shear velocity and suspended-sediment concentration shows that a critical value of wave–current shear velocity for resuspension is in the range 1.5–2.0 cm/s (Fig. 5.5). During the 28-day record of the trade-wind season, wave-current shear velocities exceeded 1.5 cm/s during 81% of the study period and 2.0 cm/s during 59% of the period.

Trade-wind conditions, T13-20 5.0 Combined wave/current shear velocity Current shear velocity (cm/s)

4.5

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4.0 3.5 3.0 2.5 2.0

~Threshold of motion

1.5 1.0 0.5 0 235

240

245

250

255

260

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Day of Year, 2003

Figure 5.4: Shear velocity during trade-wind conditions at tripod site T13-20. Shear velocities are driven predominantly by tidal flow, and the fortnightly cyclicity is clearly visible. Wave–current combined shear velocities were calculated according to Grant and Madsen (1979). Maximum combined shear velocity (u) exceeds 4.0 cm/s.


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0.6 ~Threshold of Motion

Suspended-sediment concentration (g/l)

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Figure 5.5: Relationships between suspended-sediment concentrations and combined wave–current shear velocity. Suspended-sediment concentrations increase with increasing shear velocity and indicate that sediment motion begins at shear velocities between 1.5 and 2.0 cm/s.

5.4.2.2. Monsoon conditions Monsoon conditions had a significant wave height of 0.45 m with a period similar to that of trade-wind conditions, and significant wave-current orbital velocity of 5.5 cm/s at 20-m water depth. Significant tidal currents were similar to those during the trade-wind season (B40 cm/s). This resulted in combined shear velocities that generally varied from 0.5 to 3.5 cm/s. Suspended-sediment concentrations were also lower during this period than in the trade-wind season, reaching a maximum of 0.3 g/l at 13 cmab, but having an average concentration an order of magnitude less. During monsoon conditions, suspended-sediment concentration also increased with shear velocity (r2 ¼ 0.52), and initiation of motion occurs at shear stresses similar to those of the trade-wind period. Combined wave–current shear velocities over the 28-day period exceeded 1.5 cm/s during 51% of the time and exceeded 2.0 cm/s during 31% of the time (28 days).

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5.5. Discussion Sediment accumulation on the Fly River shelf should be viewed in the larger context of clinoform development, which has occurred in several episodes. Recent seismic and multibeam studies of the GOP bathymetry document the modern clinoform foreset, which extends from B20 to B65 m and downlaps onto an erosional surface. Variability of sediment accumulation is expected because the history of clinoform evolution in the GOP has revealed an irregular basal surface (i.e., stream-eroded; Slingerland et al., 2008) over which the modern clinoform is prograding. Many mechanisms for clinoform progradation have been proposed and documented around the world. These include wave-supported turbidity currents (Kostic et al., 2002), fluid-mud flows (Kineke et al., 1996; Kuehl et al., 1996), and advection/diffusion of suspended sediment (Pirmez et al, 1998). Recently, gravity-driven processes have gained popularity as a necessary mechanism of clinoform progradation. Turbidity currents, fluid muds, and hyperpycnal plumes are able to deliver large masses of sediment necessary to account for the high accumulation rates found on the foreset of clinoforms, and they have all been implicated in the creation of the largest modern clinoforms (Amazon, Kineke et al., 1996; Kuehl et al., 1996; Ganges–Brahmaputra, Kuehl et al., 1997; Michels et al., 1998). These gravity-driven processes leave non-steady-state signatures in the seabed, similar to those found in the study area (Fig. 5.3, Type IV). The Fly River shelf exhibits eight recognizable styles of sedimentation that can be grouped into three general categories: negligible accumulation, steady-state accumulation, and non-steady-state accumulation. The spatial variability in distribution of accumulation signatures (Fig. 5.6) indicates that multiple mechanisms are in operation on this shelf.

5.5.1. Negligible Accumulation At several stations, there is no excess 210Pb and this indicates that negligible accumulation is occurring at these sites. These sites occur on the outer topset (15–25 m), where waves and tidal currents regularly rework the seabed and prevent accumulation of new sediment. These areas were observed to be capable of resuspension at least 59% of the time during trade-wind conditions and 31% of the time during monsoon conditions. Consequently, physical stratification is observed in X-radiographs (Fig. 5.7). Transects T1 and T3 have no excess 210Pb in cores collected from W25-m water depth, which likely reflects limited sediment supply in this region of the study area.


8°15′

191

NA NA NSS VH,V

NA 8°30′S

NSS VH,V NA NSS H.V NSS VH,V NSS VH,V

UL BKD UL BKD UL SS SSL

8°45′S

SSL UL SS

NA SSL

9°S

NA NA

NA SSL

UL BKD NA NA UL GDSSh UL SSH UL SSH UL SSH SSH UL SS,CR

NA UL GDSSH NA SS L NA Title (surface layer profile) SSH NA NA - no apparent accumulation

9°15′S

143°45′E

SS - Steady-state accumulation NSS - Non-steady-state accumulation UL - Surface uniform layer Subscript (sub-layer profile) L - Steady-state accumulation (< 1.0 cm/y) H - Steady-state accumulation (> 1.0 cm/y) GD - Gravity-driven layer SS - Steady-state accumulation BKD - Background activity only CR - Changing accumulation rates VH - Very high accumulation rate (> 2.0 cm/y) V - Variable activity, steady-state accumulation

144°E

144°15′E

Figure 5.6: The distribution of sedimentary styles on the Fly River shelf. The first designation indicates the character of the surface sediment. The subscripts describe the character of the subsurface sediment. Sites with negligible accumulation are dominant in the southwestern portion of the study area. The northeastern portion is dominated by sites with very high accumulation rates and variable 210Pb activities. The central region has transitional sedimentary styles.

192


T3-20

T4-17

T5-20

T6-20

0 cm

5 cm

30 cm

Figure 5.7: X-radiographs (negatives) of cores from the topset are generally dominated by physical stratification generated by the strong waves and tidal currents, even in the southwestern area of relatively slow sediment accumulation (transects T3 to T6). A variation on negligible accumulation at B20-m water depth occurs on transects T8 and T10. Sites T8-16, T8-18, and T10-17 all have a deposit with uniform excess activity at the surface and supported activities beneath (Type V). These stations are in or near Umuda Valley, which maintains some of the highest suspended-sediment concentrations on the entire shelf (Martin et al., 2008). Today, Umuda Valley is a major focus of sediment supply from the Fly River. When large amounts of sediment are delivered to local areas, stresses due to tidal currents are insufficient to keep it all in suspension and temporary deposition results, but not long-term accumulation.

5.5.2. Steady-State Accumulation Steady-state accumulation occurs at many sites throughout the study area, and many of these profiles also have an SML. Two sites without a mixed layer are located on the foreset of the clinoform entering Kiwai Valley (T4-30 and T4-50), two other sites are between Kiwai Valley and Umuda Valley (T6-30 and T7-20), and one site is within Umuda Valley (T8-50). Northeast


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of Umuda Valley, there are no examples of steady-state accumulation without uniform surface layers. The absence of an SML implies that physical and biological processes are not active in mixing the seabed. At the sites that additionally exhibit steady-state accumulation, the generation of the observed profile is driven by accumulation, the initial activity of the accumulating sediment, and the decay constant of 210Pb. Two of the sites with slow steady-state sediment accumulation are located on the foreset of the clinoform west of Kiwai Valley (e.g., T4-30 and T4-50). Similar profiles are observed for the Holocene clinoform of the Huang He (Yellow River) (Alexander et al., 1991). Because of river avulsion and sea-level rise, today the river mouth is displaced by several hundred kilometers from the clinoform built B11 kya (thousand years ago). Modern accumulation rates on the clinoform are steady state (topset 0.6–1.2 cm/y, foreset 0.3 cm/y, bottomset negligible; Liu et al., 2004), but maximum rates occur on the topset, which is incompatible with models of clinoform progradation. Most of the Huang He sediment is deposited via hyperpycnal plumes at the river mouth (Bornhold et al., 1986; Wright et al., 1986, 1988), indicating that the clinoform is not a likely sink for much sediment today. Slow rates of steady-state accumulation also are observed in the Adriatic Sea (Palinkas and Nittrouer, 2006), where a clinoform is generated by sediment from the Apennine mountain range. The Apennine rivers were collectively dammed at the end of World War II (Capelli et al., 1997; Coltorti, 1997; Farroni et al., 2002; Syvitski and Kettner, 2007), which dramatically decreased their sediment supply to the Adriatic Sea. Prior to that change, the collective line source of rivers was actively building a clinoform on the western side of the Adriatic Sea. Modern accumulation rates are slow, and do not always show the highest accumulation rates on the foreset, again a condition that is not conducive to the active progradation of a self-similar deposit. Considering the documented conditions in the Yellow Sea and the Adriatic Sea, the low rates of sediment accumulation in the southwestern portion of the Fly River clinoform likely reflect a stage of negligible progradation.

5.5.3. Non-Steady-State Accumulation 5.5.3.1. Deposits of uniform

210

Pb activity

Surface layers with uniform 210Pb activities are created by biological mixing (e.g., Washington shelf; Nittrouer et al., 1979) or physical mixing

194


(e.g., Amazon shelf; Kuehl et al., 1996) that homogenize the 210Pb activity to the depth of mixing. Under steady-state accumulation with an SML, sediment is deposited on the seabed, an equal amount is displaced below the region of active mixing, and the SML migrates upward with the sediment surface. The 210Pb in the displaced sediment continues to decay with its characteristic half-life and an accumulation profile develops below the SML. At most locations with uniform 210Pb profiles on the Fly River shelf, the SML is B1 m thick. Some examples of bioturbation are found along the shelf, although burrows and trace evidence of biological mixing are generally not common. Organisms found in the GOP mix only the upper few centimeters of the seabed (Aller and Aller, 2004). Typically, biological mixing on continental shelves does not extend much below 10 cm into the sediment (Rhoads et al., 1985), so benthic organisms are unlikely to account for the thickness of many mixed layers on this shelf. Physical mixing can resuspend sediment deep into the seabed. On the Amazon shelf, resuspension has been observed in the form of a seasonal surface layer that extends more than a meter into the seabed (Kuehl et al., 1996). The magnitude of resuspension is driven by the energetic oceanographic conditions present on the Amazon shelf. Tides, which are a dominant physical forcing mechanism there, have a maximum range of B6 m and generate currents as great as 200 cm/s (Gibbs, 1982; Nittrouer et al., 1986b; Kineke et al., 1996). Tidal currents play a significant role in reworking the seabed up to 10-cm depth over a diurnal tidal cycle (Jaeger and Nittrouer, 1995). In addition, significant wave heights average 1–2 m (Meserve, 1974) and maximum significant wave heights W3.0 m (13 s period) (Sternberg et al., 1996) contribute to seabed mixing. In contrast, maximum tidal currents on the Fly River shelf are o100 cm/s (Martin et al., 2008). The maximum significant wave height measured during the study period was 3.0 m. The mean significant wave height during trade-wind conditions was 1.2 m, but decreased to 0.5 m during the monsoon. Resuspension depths due to wave-orbital velocities have been calculated for a variety of wave conditions on the Eel River shelf (Wiberg, 2000), which is a silt-dominated environment (Borgeld, 1985; Borgeld et al., 1996; Sommerfield and Nittrouer, 1999; Crockett and Nittrouer, 2004) similar to the Fly River shelf. Under wave-orbital velocities that vary from 50 to 200 cm/s, resuspension on the Eel River shelf was always o10 cm into the seabed (Wiberg, 2000). On the Fly River shelf, significant wave-orbital velocities at 20-m water depth during the trade-wind period averaged only 13.8 cm/s, and wave resuspension is not expected to extend into the seabed more than a few centimeters.


195

5.5.3.2. Mechanisms for deposition of uniform layer Tidal currents generate a significant portion of the shear stress on the Fly River shelf, with waves imprinting a variable increase in calculated shear velocities (Fig. 5.4). The combined stresses are sufficient to transport sediment (at least in shallow water) a majority of the time, and this transport likely plays a role in the development of the thick mixed layers. In shallow water where thick deposits with uniform 210Pb are observed, physical sedimentary structures indicate that sediment resuspension and deposition is important in creating the stratigraphy. The unconformable contact between the surface deposit with excess 210Pb and the underlying deposit with supported activities (Fig. 5.8) indicates an erosive boundary between the two strata. The regular occurrence of tidal currents combined with variations in sediment supply may control sedimentation in this region. When sediment is in short supply, the currents and waves progressively erode the seabed. The depth of erosion is not the result of any one period of exceptional shear stress; rather it is the result of regular incidence of shear stresses sufficient to transport sediment. This process continues until new sediment is supplied. In cores that have excess 210Pb activity lying Water Content (%) 0

10

20

30

40

50

60

0 T8-18 50

Depth (cm)

100

150

Total 210Pb Activity

200

Water Content 250 0.1

1

10

Total 210Pb Activity (dpm/g)

Figure 5.8: Water content correlates with 210Pb activity. More-consolidated subsurface sediment is resistant to erosion during transport events.

196


unconformably on supported sediment, a discontinuity in water content (and porosity) also exists (Fig. 5.8). More-consolidated subsurface sediment is resistant to erosion, creating conditions for the surface layer to be periodically removed and redeposited with little impact on the subsurface layer. When large amounts of sediment are available, the transport capacity of tidal currents may be overwhelmed and sediment deposited. Sediment deposition occurs on a timescale that is short compared to the resolution of 210 Pb. With initial (surface) excess activities of o2 dpm/g and analytical errors of about 70.3 dpm/g, sedimentation can be resolved for a timescale of B6 y (Kuehl et al., 1995). This allows rapid deposition on a tidal scale (fortnightly or monthly) to create thick surface layers with uniform 210Pb activities. In deeper water, wave and tidal shear stresses are weaker and not able to facilitate this process, confining thick uniform layers to shallow water where wave and tidal shear stresses are strongest.

5.5.3.3. Event deposition Low-activity sediment associated with elevated clay content has been observed previously by Walsh et al. (2004) on the foreset northeast of transect T13. In the present study, sites T5-40 and T10-40 exhibit 210Pb and grain-size profiles that are consistent with an interpretation of event sedimentation (Fig. 5.9). The event recorded near the surface of these cores overlies a region of logarithmic decay, indicating that under usual conditions, the site was undergoing steady-state accumulation of sediment. Most known processes would not be able to transport fine-grained sediment to the observed accumulation depth (B40 m) while preserving the low-activity signature. BBL transport in the absence of a lutocline would generate mixing with ambient water, thereby increasing the surface activity of the suspended sediment. Settling through the water column would similarly expose the accumulating sediment to higher concentrations of dissolved 210Pb. Furthermore, the sedimentary characteristics of the deposits (e.g., physical structure and thickness; Fig. 5.10) imply that they were emplaced during a single depositional event (possibly with multiple pulses), and involved a large amount of sediment in transport. Water-column studies have identified nearbottom suspended-sediment concentrations greatly exceeding the 10 g/l threshold needed for gravity flows (Ogston et al., 2008; Martin et al., 2008). This demonstrates that fluid-mud conditions exist at discrete locations. Shortperiod waves (3–8 s), like those found in the GOP, have been demonstrated to create thin (o2 cm) layers of fluid mud in experiments (Lamb and Parsons, 2005), and these thin layers are difficult to observe under field conditions.


197

T5-40 % Clay Composition 0

20

40

60

80

100

0

event layer

Depth (cm)

50

Total 210Pb activity Excess 210Pb activity

100

150 SAR = 2.0 cm/y 200 0.1

1 210Pb

10

Activity (dpm/g)

Figure 5.9: Details of core T5-40 showing an event layer with decreased 210 Pb activity correlated with increased clay content. The event layers are physically stratified in X-radiographs (see Fig. 5.10). The suite of evidence strongly suggests that high-concentration gravity-driven flows are responsible for the event deposits in the GOP.

5.5.3.4. Fast accumulation rates with variable

210

Pb activity

Variable initial activity of accumulating sediment precludes development of a steady-state 210Pb profile. However, in other systems (e.g., Amazon, Ganges– Brahmaputra) that exhibit variable 210Pb profiles with a general decay trend, using the steady-state accumulation model with best-fit lines has generated accumulation rates in good agreement with independent geochronometers (e.g., 228Ra/226Ra; Dukat and Kuehl, 1995; Michels et al., 1998). The best-fit approach seems to be a reliable estimate where a general decay trend is observed in the 210Pb activity profile. Such a trend indicates that accumulation and radioactive decay dominate the activity profile even in the presence of variations in initial activity. Typically, steady-state profiles exhibit minimal scatter around a regression line, but some variability is unavoidable

198


Core T5-40 0 cm

10 cm

Event Layer

40 cm

Figure 5.10: X-radiograph (negative) of core T5-40. The event layer contains interlaminated sand (light colored) and mud (dark colored). Overlying sediment shows evidence of biological activity through the presence of biogenic sedimentary structures. because of factors mentioned previously. In the case of profiles from the northeast part of the study area, the scatter is large and the profiles are interpreted to be non-steady-state because the variations in activity are great compared to the mean activity in the sediment. In these conditions, it is valuable to examine the profiles to gain insight regarding sediment dynamics in the context of longer-term accumulation. Low-activity sediment is found on the topset because of limited interaction with the oceanic source of dissolved 210Pb. In addition, high concentrations of suspended sediment that compete for the small amount of excess 210Pb in the water column (see Section 5.2) are common in shallow water and can be transported to accumulate in deeper water. Low concentrations of sediment that have ample interaction with ocean water can conversely be expected to exhibit higher activity. An example of this effect is shown by a study performed near the mouth of the Yangtze River. Where the suspended-sediment


199

concentration exceeds 100 mg/l, McKee et al. (1984) found that 95% of the 234 Th inventory (another particle-reactive radioisotope produced from 238U in seawater) is associated with particles. In regions where the suspended-sediment concentration is lower by more than an order of magnitude (10 mg/l), particle association of 234Th is decreased to only B60%. This indicates that under lower-concentration conditions, individual particles are able to scavenge a much higher proportion of the available particle-reactive isotopes in the water column. Therefore, low-concentration conditions can produce a higher specific activity in the seabed, and temporally variable suspended-sediment concentrations may contribute to the generation of non-steady-state profiles. Non-steady-state profiles also have been observed on the Amazon continental shelf, where they result from thick seasonally mixed surface layers on the clinoform topset that are mobilized as fluid muds and flow to the foreset region (Kuehl et al., 1995). 210Pb profiles in foreset cores demonstrate variable activity reflecting pulses of sediment input from the topset region (Kuehl et al., 1986). These are subsequently buried by sediment with high concentrations of dissolved 210Pb, which is adsorbed by particles settling through isotope-rich open-ocean water (Moore et al., 1996). The periodic input of low-activity sediment from near-bottom fluid-mud flows interspersed with high-activity sediment deposited under conditions of lower suspended-sediment concentration results in the observed quasi-cyclic profiles (Kuehl et al., 1996). Foreset cores from the GOP have 210Pb profiles with similarities to cores from the Amazon shelf, and we interpret low-activity strata to form through deposition of high-concentration nearbottom suspensions that originate on the topset.

5.6. Conclusions A high level of heterogeneity characterizes the sedimentary record along and across the Fly River shelf. Seven distinct styles of accumulation are recognized, resulting in sediment accumulation rates that range from 0.2 to 5.0 cm/y, with an eighth pattern described by the lack of any detectable modern (100 y) accumulation. Preservation of sedimentary strata is also variable on this shelf and is largely controlled by the intensity of physical processes and the local rates of sediment accumulation. Cores collected from the continental shelf directly off the Fly River mouth reveal accumulation rates that are slow (o1 cm/y) or negligible. These observations indicate that progradation of the clinoform is presently limited in the southwestern portion of the study area.

200


Cores collected northeast of the Fly River mouth contain sediment layers with low 210Pb activity and high clay content. Low-activity sediment is generally deposited under conditions of large suspended-sediment concentrations. To emplace the thick deposits observed at the water depths where they are found, sediment gravity flows are a likely mechanism. Strong tidal currents occur at regular intervals on this shelf and shear stresses are sufficient to transport sediment on the outer topset a majority of the time during all seasons (up to 80% during trade-wind conditions and 50% during monsoon conditions); thick, uniform 210Pb layers are observed at many sites in the central and northeastern portion of the study area. Some uniform layers are likely mixed by biology, but those layers rarely extend deeper than 10 cm into the seabed and biological mixing cannot account for the thickness of all the observed uniform layers. Shear stresses are also insufficient to resuspend sediment in a single event and homogenize the thicknesses observed. Generation of the uniform layers is likely related to recurring tidal currents. When supply is limited, tidal currents and waves erode the surface layer. When supply is ample, rapid deposition (in relation to the timescales measured by 210 Pb) occurs and creates a deposit that exhibits uniform activities.

ACKNOWLEDGMENTS We thank all US, PNG, and Australian scientists who helped with fieldwork, including the crew of the R/V Melville. This paper is based on work supported by the National Science Foundation under Grant Nos. OCE0203351 and OCE0504616 (to Nittrouer and Ogston) and OCE0220600 (to Goni).

REFERENCES Alexander, C. R., DeMaster, D. J., & Nittrouer, C. A. (1991). Sediment accumulation in a modern epicontinental-shelf setting: The Yellow Sea. Marine Geology, 98, 51–72. Aller, J. Y., & Aller, R. C. (2004). Physical disturbance creates bacterial dominance of benthic biological communities in tropical deltaic environments of the Gulf of Papua. Continental Shelf Research, 24, 2395–2416. Asquith, D. O. (1970). Depositional topography and major marine environments, Late Cretaceous, Wyoming. American Association of Petroleum Geologists Bulletin, 54, 1184–1224. Borgeld, J. C. (1985). Holocene stratigraphy and sedimentation on the northern California continental shelf. Ph.D. Dissertation, University of Washington, Seattle, 177 pp.


201

Borgeld, J. C., Clarke, J. E. H., Goff, J. A., Mayer, L. A., & Curtis, J. A. (1996). Acoustic backscatter of the 1995 flood deposit on the Eel Shelf. Marine Geology, 154, 197–210. Bornhold, B. D., Yang, Z.-S., Keller, G. H., Prior, D. B., Wiseman, W. J., Jr., Wang, Q., Wright, L. D., Xu, W. D., & Zhuang, Z. Y. (1986). Sedimentary framework of the modern Huanghe (Yellow River) delta. Geo-Marine Letters, 6, 77–83. Bruland, K. W. (1974). Geochronology in the coastal marine environment. Ph.D. Dissertation, University of California, San Diego, 106 pp. Capelli, G., Miccadei, E., & Raffi, R. (1997). Fluvial dynamics in the Castel di Sangro plain: Morphological changes and human impact from 1875 to 1992. Catena, 30, 295–309. Coltorti, M. (1997). Human impact in the Holocene fluvial and coastal evolution of the Marche region, Central Italy. Catena, 30, 311–335. Crockett, J. S., & Nittrouer, C. A. (2004). The sandy inner shelf as a repository for muddy sediment: An example from northern California. Continental Shelf Research, 24, 55–73. Crockett, J. S., Nittrouer, C. A., Ogston, A. S., Naar, D. F., & Donohue, B. T. (2008). The origin, evolution and filling of exposed submarine valleys on the Fly River shelf. Journal of Geophysical Research, 113, F01S12, doi: 10.1029/2006JF000674. Dukat, D. A., & Kuehl, S. A. (1995). Non-steady-state Pb-210 flux and the use of Ra-228/Ra-226 as a geochonometer on the Amazon continental shelf. Marine Geology, 125, 329–350. Farroni, A. M. V., Magaldi, D., & Tallini, M. (2002). Total sediment transport by the rivers of Abruzzi (central Italy): Prediction with the RAIZAL model. Bulletin of Engineering Geology and the Environment, 61, 121–127. Fisher, W. L., Brown, A. J. S., & McGowan, J. H. (1969). Delta Systems in the Exploration for Oil and Gas. Texas Bureau of Economic Geology, Austin, 97 pp. Galloway, W. E. (1975). Process framework for describing the morphologic and stratigraphic evolution of deltaic depositional systems. In: M. L. Brousard (Ed.). Deltas Models for Exploration. Houston Geological Society, Houston. Gibbs, R. J. (1982). Currents of the shelf of north-eastern South America. Estuarine Coastal and Shelf Science, 14, 238–299. Grant, W. D., & Madsen, O. S. (1979). Combined wave and current interaction with a rough bottom. Journal of Geophysical Research, 84, 1797–1808. Harris, P. T., Baker, E. K., Cole, A. R., & Short, S. A. (1993). A preliminary study of sedimentation in the tidally dominated Fly River delta, Gulf of Papua. Continental Shelf Research, 13, 441–472. Jaeger, J. M., & Nittrouer, C. A. (1995). Tidal controls on the formation of finescale sedimentary strata near the Amazon river mouth. Marine Geology, 125, 259–281. Kineke, G. C., Sternberg, R. W., Trowbridge, J. H., & Geyer, W. R. (1996). Fluidmud processes on the Amazon continental shelf. Continental Shelf Research, 16, 667–696.

202


Kostic, S., Parker, G., & Marr, J. G. (2002). Role of turbidity currents in setting the foreset slope of clinoforms prograding into standing fresh water. Journal of Sedimentary Research, 72, 353–362. Kuehl, S. A., DeMaster, D. J., & Nittrouer, C. A. (1986). Nature of sediment accumulation on the Amazon continental shelf. Continental Shelf Research, 6, 209–225. Kuehl, S. A., Hariu, T. M., & Moore, W. S. (1989). Shelf sedimentation off the Ganges-Brahmaputra river system: Evidence for sediment bypassing to the Bengal fan. Geology, 17, 1132–1135. Kuehl, S. A., Pacioni, T. D., & Rine, J. M. (1995). Seabed dynamics of the inner Amazon continental shelf: Temporal and spatial variability of surficial strata. Marine Geology, 125, 283–302. Kuehl, S. A., Nitttouer, C. A., Allison, M. A., Faria, L. E. C., Dukat, D. A., Jaeger, J. M., Pacioni, T. D., Figueiredo, A. G., & Underkoffler, E. C. (1996). Sediment deposition, accumulation, and seabed dynamics in an energetic fine-grained coastal environment. Continental Shelf Research, 16, 787–816. Kuehl, S. A., Levy, B. M., Moore, W. S., & Allison, M. A. (1997). Subaqueous delta of the Ganges-Brahmaputra river system. Marine Geology, 144, 81–96. Lamb, M. P., & Parsons, J. D. (2005). High-density suspensions formed under waves. Journal of Sedimentary Research, 75, 386–397. Leithold, E. L. (1993). Preservation of laminated shale in ancient clinoforms: Comparison to modern subaqueous deltas. Geology, 21, 359–362. Liu, J. P., Milliman, J. D., Gao, S., & Cheng, P. (2004). Holocene development of the Yellow River’s subaqueous delta, North Yellow Sea. Marine Geology, 209, 45–67. Martin, D. P., Nittrouer, C. A., Ogston, A. S., & Crockett, J. S. (2008). Tidal and seasonal dynamics of a muddy inner-shelf environment, Gulf of Papua. Journal of Geophysical Research, 113, F01S07, doi: 10.1029/2006JF000681. McKee, B. A., DeMaster, D. J., & Nittrouer, C. A. (1984). The use of Th-234/U-238 disequilibrium to examine the fate of particle-reactive species on the Yangtze continental shelf. Earth Planetary Science Letters, 68, 431–442. Meserve, J. M. (1974). US Navy marine climatic atlas of the world, Vol. 1, North Atlantic Ocean. United States Government Printing Office, Washington, DC, 371 pp. Miall, A. D. (1984). Deltas. In: R. G. Walker (Ed.). Facies Models. Geological Association of Canada, St. John’s, NL, pp. 106–118. Michels, K. H., Kudrass, H. R., Huebscher, C., Suckow, A., & Wiedicke, M. (1998). The submarine delta of the Ganges-Brahmaputra; cyclone-dominated sedimentation patterns. Marine Geology, 149, 133–154. Milliman, J. D. (1995). Sediment discharge to the ocean from small mountainous rivers: The New Guinea example. Geo-Marine Letters, 15, 127–133. Milliman, J. D., & Meade, R. H. (1983). World-wide delivery of river sediments to the oceans. Journal of Geology, 91, 1–21. Mitchum, R. M., Jr., Vail, P. R., & Sangree, J. B. (1977). Seismic stratigraphy and global changes of sea level, part 6: Stratigraphic interpretation of seismic


203

reflection patterns in depositional sequences. In: C. E. Payton (Ed.). Seismic Stratigraphy – Applications to Hydrocarbon Exploration. American Association of Petroleum Geologists, Tulsa, pp. 117–133. Moore, W. S., DeMaster, D. J., Smoak, J. M., McKee, B. A., & Swarzenski, P. W. (1996). Radionuclide tracers of sediment-water interactions on the Amazon shelf. Continental Shelf Research, 16, 645–665. Nittrouer, C. A., Sternberg, R. W., Carpenter, R., & Bennett, J. T. (1979). The use of Pb-210 geochronology as a sedimentological tool: Application to the Washington continental shelf. Marine Geology, 31, 297–316. Nittrouer, C. A., DeMaster, D. J., Kuehl, S. A., & Kowsmann, R. O. (1986a). The deltaic nature of Amazon shelf sedimentation. Geological Society of America Bulletin, 97, 444–458. Nittrouer, C. A., Curtin, T. B., & DeMaster, D. J. (1986b). Concentration and flux of suspended sediment on the Amazon continental shelf. Continental Shelf Research, 6, 151–174. Nittrouer, C. A., Brunskill, G. J., & Figueiredo, A. G. (1995). The importance of tropical coastal environments. Geo-Marine Letters, 15, 121–126. Nittrouer, C. A., Kuehl, S. A., Figueiredo, A. G., Allison, M. A., Sommerfield, C. K., Rine, J. M., Faria, E. C., & Silveira, O. M. (1996). The geological record preserved by Amazon shelf sedimentation. Continental Shelf Research, 16, 817–841. Ogston, A. S., Cacchione, D. A., Sternberg, R. W., & Kineke, G. C. (2000). Observations of storm and river flood-driven sediment transport on the northern California continental shelf. Continental Shelf Research, 20, 2141–2162. Ogston, A. S., Sternberg, R. W., Nittrouer, C. A., Martin, D. P., Goni, M. A., & Crockett, J. S. (2008). Sediment delivery from the Fly River tidally dominated delta to the nearshore marine environment and the impact of El Nino. Journal of Geophysical Research, 113, F01S11, doi: 10.1029/2006JF000669. Palinkas, C. M., & Nittrouer, C. A. (2006). Clinoform sedimentation along the Apennine shelf, Adriatic Sea. Marine Geology, 234, 245–260. Pickup, G. (1984). Geomorphology of tropical rivers: I. Landforms, hydrology and sedimentation in the Fly and lower Purari, Papua New Guinea. In: A. P. Schick (Ed.). Channel Processes – Water, Sediment, Catchment Controls. Catena Supplement, 5, 1–17. Pielke, R. A. (1990). The Hurricane. Routledge, New York. Pirmez, C., Pratson, L. F., & Steckler, M. S. (1998). Clinoform development by advection-diffusion of suspended sediment: Modelling and comparison to natural systems. Journal of Geophysical Research, 103(B10), 24141–24157. Posamentier, H. W., Jervey, M. T., & Vail, P. R. (1988). Eustatic controls on clastic deposition I. Conceptual framework. In: C. K. Wilgus, C. G. Hastings, S. C. Kendall, H. W. Posamentier, C. A. Ross, & J. C. Van Wagoner (Eds). Sea-Level Changes: An Integrated Approach. Society for Sedimentary Geology, Tulsa, pp. 125–154. Rhoads, D. C., Boesch, D. F., Zhican, T., Fengshan, X., Liqiang, H., & Nilsen, K. L. (1985). Macrobenthos and sedimentary facies on the Changjiang delta platform and adjacent continental shelf, East China Sea. Continental Shelf Research, 4, 189–213.

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Ross, M. A., & Mehta, A. (1989). On the mechanics of lutoclines and fluid mud. Journal of Coastal Research, 5, 51–61. Slingerland, R., Driscoll, N. J., Milliman, J. D., Miller, S. R., & Johnstone, E. A. (2008). Anatomy and growth of a Holocene clinothem in the Gulf of Papua. Journal of Geophysical Research, 113, F01S13, doi: 10.1029/2006JF000628. Sommerfield, C. K., & Nittrouer, C. A. (1999). Modern accumulation rates and a sediment budget for the Eel shelf: A flood-dominated depositional environment. Marine Geology, 154, 227–241. Sternberg, R. W., Cacchione, D. A., Paulson, B., Kineke, G. C., & Drake, D. E. (1996). Observations of sediment transport on the Amazon subaqueous delta. Continental Shelf Research, 16, 697–715. Syvitski, J. P. M., & Kettner, A. J. (2007). On the flux of water and sediment into the northern Adriatic. Continental Shelf Research, 27, 296–308. Thom, B. G., & Wright, L. D. (1983). Geomorphology of the Purari Delta. In: T. Petr (Ed.). The Purari: Tropical Environment of a High Rainfall River Basin. Dr. W. Junk Publishers, The Hague, 624 pp. Vail, P. R. (1987). Seismic stratigraphy interpretation using sequence stratigraphy. Part 1. Seismic stratigraphy interpretation procedure. AAPG Studies in Geology, 27, 1–10. Vail, P. R., Mitchum, J., Todd, R. G., Widmier, J. M., Thompson, S., III, Sangree, J. B., Bubb, J. N., & Hatlelid, W. G. (1977). Seismic stratigraphy and global changes of sea level. In: C. E. Clayton (Ed.). Seismic Stratigraphy: Applications to Hydrocarbon Exploration. American Association of Petroleum Geologists, Tulsa, pp. 49–212. Van Wagoner, J. C., Mitchum, R. M., Campion, K. M., & Rahmanian, V. D. (1990). Siliciclastic sequence stratigraphy in well logs, cores and outcrops: Concepts for high resolution correlation of time and facies. American Association of Petroleum Geologists, Tulsa. Walsh, J. P., Nittrouer, C. A., Palinkas, C. M., Ogston, A. S., Sternberg, R. W., & Brunskill, G. (2004). Clinoform mechanics in the Gulf of Papua, New Guinea. Continental Shelf Research, 24, 2487–2510. Wiberg, P. (2000). A perfect storm: Formation and potential for preservation of storm beds on the continental shelf. Oceanography, 13, 93–99. Wolanski, E., & Alongi, D. M. (1995). A hypothesis for the formation of a mud bank in the Gulf of Papua. Geo-Marine Letters, 15, 166–171. Wright, L. D. (1977). Sediment transport and deposition at river mouths: A synthesis. Geological Society of America Bulletin, 88, 857–868. Wright, L. D. (1985). River deltas. In: R. A. Davis (Ed.). Coastal Sedimentary Environments. Springer-Verlag, New York, pp. 1–76. Wright, L. D., Yang, Z.-S., Bornhold, B. D., Keller, G. H., Prior, D. B., & Wiseman, W. J., Jr. (1986). Hyperpycnal plumes and plume fronts over the Huanghe (Yellow River) delta front. Geo-Marine Letters, 6, 97–105. Wright, L. D., Wiseman, W. J., Bornhold, B. D., Prior, D. B., Suhayda, J. N., Keller, G. H., Yang, Z.-S., & Fan, Y. B. (1988). Marine dispersal and deposition of Yellow River silts by gravity-driven underflows. Nature, 332, 629–632.


Chapter 6

A Mass Balance for Sediment and Copper in the Rivers, Estuaries, Shelf and Slope of the Gulf of Papua, Papua New Guinea Gregg J. Brunskill1,, Irena Zagorskis2 and John Pfitzner2 1

84 Alligator Creek Road, Alligator Creek, Queensland 4816, Australia Australian Institute of Marine Science PMB 3, Townsville MC, Queensland 4810, Australia 2

6.1. Introduction A steady-state ocean is a useful paradigm in chemical oceanography. All that is added to the ocean must be removed on decadal to millennial scales, so that major and minor element concentrations and ratios in seawater remain similar over geologically long periods of time (Rubey, 1951; Mackenzie and Garrels, 1966; Garrels and Mackenzie, 1971; Lowenstein et al., 2005). Continental movements from polar zones to the tropics, tectonic uplift of mountain ranges, rifting ocean basins and submarine vents, climatic change, glacial/ interglacial sea level changes, biological evolution, and anthropogenic alterations of the land and rivers have changed the rate of addition of different elements (and their isotopic ratios) to the sea (Edmond, 1992; Richter and Turekian, 1993; Edmond and Huh, 1997; Schlesinger, 1997; Hooke, 2000; Peizhen et al., 2001; Vorosmarty et al., 2003; Meybeck and Vorosmarty, 2005; Syvitski et al., 2005). For elements that do not have a gas phase (that can escape to the atmosphere), changes in the rate of supply of the elements to the ocean can often be seen in the sedimentation history book. For river inputs, most dissolved and particulate elements are removed by sedimentation in estuaries and on the continental shelf. Of the trace elements, 50–95% of river inputs are probably trapped in organic and inorganic phases close to the estuaries of the major rivers of the world (Martin and Windom, 1991). Corresponding author. Tel.: 07 4778 8142; Fax: 07 4772 5852;

E-mail: [email protected] (G.J. Brunskill).

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Dissolved and particulate copper (pCu) is supplied to the world ocean from rivers, atmospheric dust, and submarine vents. Global river supply of Cu to the ocean is estimated to be 30 109 mol yr1 (76% in the particulate form, according to Martin and Meybeck, 1979; Carey et al., 2002), and input from atmospheric precipitation and dust might be 3–6 109 mol yr1 (Mackenzie and Wollast, 1977). The global influx of Cu from submarine vents to the world ocean is poorly known (James et al., 1995), but Lackschewitz et al. (2004) indicate that black smoker vents in the Manus Basin (NE Papua New Guinea) produce mineral deposits greatly enriched in Cu and other trace elements. Various authors (e.g., Gibbs, 1973) have shown that most (75%) Cu supply from rivers is in the crystalline mineral particulate form, and that riverine dissolved Cu (dCu) (or Cu–ligand, Cu–colloid) is usually removed to suspended particles or sediments along the salinity gradient in estuaries on the inner shelf (Sholkovitz and Copland, 1981; Boyle et al., 1982; Windom et al., 1988; Cobelo-Garca and Prego, 2003; Chadwick et al., 2004; Cobelo-Garcia et al., 2004; Monbet, 2004; Jiann et al., 2005). In estuarine water and seawater, most Cu is in the particulate form as organic matter or aluminosilicate phases. Dissolved copper is thought to be almost completely associated with dissolved organic matter (proteins and polysaccharides), the colloidal phases, or in ionic ligand form with carbonate, hydroxide, and chloride (Massey, 1973; Gordon, 1992; Gordon et al., 1996; Moffett and Brand, 1996; Li, 2000; Shafer et al., 2004; Heidmann et al., 2005). Variations in the distribution coefficient of Cu between particulate and dissolved phases (Kd ¼ [mmol Cu g1 particulate matter]/[mmol Cu g1 filtered water]) are thought to be 105 to 106 in seawater, if the colloid phase is considered (Shafer et al., 2004). The oceanic residence time (t ¼ annual removal rate/mass in ocean water, or annual addition rate/ mass in ocean water) for copper is about 2–5 104 years, but the residence time for the surface layer and euphotic zone of the open ocean is probably shorter, perhaps on the order of 30 years (Goldberg, 1963; Brewer and Spenser, 1975; Broecker and Peng, 1982; Li, 2000). In ocean margin sediments, most river-supplied Cu is probably buried in the aluminosilicate phases (Gibbs, 1973; Mantoura et al., 1991). According to water column speciation and sediment trap studies, most delivery of Cu to marine sediments from the pelagic water column may be with organic matter (Kumar et al., 1996). As most organic matter is decomposed in deep water and the surface sediments, the liberated pore water copper may be sequestered by sulfide in anaerobic sediments (Di Toro et al., 1990), or with clay minerals and the Fe and Mn oxide phases in oxidized surficial sediments (Strawn et al., 2004; Heidmann et al., 2005). The mobility of Cu during sedimentary diagenesis and transport from sediments to the water column is

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greatly facilitated by natural organic ligands, which are present in huge excess over Cu concentrations (Seritti et al., 1986; Moffett and Brand, 1996; Moffett et al., 1997; Skrabal et al., 1997; Kozelka and Bruland, 1998). In some coastal seas, the annual diffusive flux of ligand–Cu from margin sediments is greater than the annual supply from rivers and the atmosphere (Williams et al., 1998; Audry et al., 2004). Copper is an essential element for biological growth, and is an important component of enzyme systems for nitrogen fixation, denitrification, metabolic oxygen reduction, methane oxidation, and blood oxygen transport in many organisms (Herskovits and Hamilton, 1991; Kim et al., 2004; Prigge et al., 2004; Tocheva et al., 2004; Lieberman and Rosenzweig, 2005). Copper, and other essential trace elements (Fe, Mo, Zn, Mn, etc.) probably limit plankton growth in some parts of the ocean, away from sources of river and dust inputs (Springer-Young et al., 1992). As in seawater, the concentrations of free ionic Cu in living cells are probably o1018 M, and all normal Cu metabolism is facilitated by metallothionein proteins, carbohydrate ligands, and enzymes (Lippard, 1999; Rae et al., 1999). In the ocean, Cu concentrations in offshore surface water are probably regulated by phytoplankton uptake and release, with an expected Cu/OC ¼ 3–5 mmol Cu/mol OC (Sunda and Huntsman, 1995; Luoma et al., 1998). When copper supply to estuaries is enhanced from technological activities, biological toxicity is sometimes reduced by physiological reactions in cells that sequester Cu in excretory organs or vesicles (Sarasquete et al., 1992; Canli et al., 1997; Meyer et al., 1999), or by trapping of Cu in microbial mucilaginous exudations (Seritti et al., 1986; Moffett et al., 1997; Dryden et al., 2004; Rivera-Duarte et al., 2005). In spite of these cellular protection mechanisms, CuSO4 (bluestone) is an excellent biocide for microbes, crustacea, and mollusks when applied in high concentrations to small bodies of water (van Hullebusch et al., 2003; Garcia-Villada et al., 2004). High concentrations of copper in sewage (0.2–0.5 mg L1, Islam and Tanaka, 2004), mine wastes, and metal industries have been shown to be deleterious to many estuarine and marine, benthic, and planktonic invertebrates and fishes (Jonas, 1989; Sharp and Stearns, 1997; Negri and Heyward, 2000; Agell et al., 2004; Chelazzi et al., 2004; Geracitano et al., 2004; Kim and Kang, 2004; Lehman et al., 2004; Rivera-Duarte et al., 2005; Virkutyte et al., 2005). Over the last century in North America, approximately 1.6 1014 g of Cu has been extracted from the lithosphere for human technological use, and over half of this mined Cu was disposed to waste in landfills, tailings, and slag reservoirs (Spatari et al., 2005). These authors show that since 1940, there has been an order of magnitude increase in the proportion of industrial copper that is lost to postconsumer waste.

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The geography of New Guinea (Fig. 6.1) and its coastal oceanography have been reviewed by Brunskill (2004). The catchment area of rivers draining into the Gulf of Papua is 142 109 m2, and these combined rivers deliver about 330–400 109 m3 of freshwater to the Gulf, containing 150–200 1012 g yr1 of suspended sediments. The catchments of these rivers are largely undisturbed, except for two large mines, Ok Tedi Mining Ltd (OTML) in the headwaters of the Fly River, and Porgera (Placer Dome Asia Pacific) in the headwaters of the Strickland River. Davies (2004), Harris et al. (2004), and Hemer et al. (2004) describe the distribution of nutrient elements, sediment, and sediment deposition climate for the Fly River delta. Aller and Aller (2004) and Aller et al. (2004) describe some of the biogeochemical aspects of the inner-shelf mud deposits, and Walsh et al. (2004) describe the large clinoform delta front that forms from the combined inputs of the rivers of the Gulf of Papua. Baker et al. (1990), Baker and Harris (1991), and Alongi et al. (1991) give data on the Cu concentration in biota and surface sediments of the Fly River delta. Apte and Day (1998) show the distribution of dCu (and other trace elements) in the water of the Gulf of Papua and Torres Strait. Wolanski and Gibbs (1995), Wolanski et al. (1995a, b, 1997, 1998) describe estuarine dynamics, sediment fluxes, and the circulation of the inner-shelf water, and Pickard et al. (1977) and Burrage (1993) describe the larger-scale Hiri Current Gyre in the northern Coral Sea (Fig. 6.1). Our objectives in this paper are to present the annual rate of supply of Cu to the Gulf of Papua from rivers, and the removal rate of Cu by burial in sediments. The excess of river Cu input over observed Cu burial rates will be delivered to the Hiri Gyre of the Coral Sea. We speculate that this system is not in steady state, as there has been an increase in dissolved and particulate Cu supply rate from the Fly River, because of mining operations in the headwaters.

6.2. Methods Field and laboratory methods for this work are given in detail in Brunskill et al. (2003), and are briefly summarized here with emphasis on methods of measurement of copper. 6.2.1. Field Sampling End member fresh river water and estuarine salinity gradient samples were collected from the ship in acid-cleaned plastic buckets or Niskin bottles. To collect suspended sediment, immediately after sampling, the water sample

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was pulled by vacuum through preweighed filters in the ship laboratory. Suspended sediment samples for ICP-AES analyses were collected on cellulose acetate 0.45 mm pore diameter filters stored in glass scintillation vials, and samples for organic carbon (OC) were collected on precombusted glass fiber GF/F filters and stored in aluminum foil envelopes. All suspended sediment samples on filters were kept frozen until they were oven dried and weighed for analyses. Water for dissolved element analyses was also subsampled from the above water samples. Water samples for dissolved element analyses were filtered through 0.45 mm Minisart disposable filters, and for dissolved organic carbon (DOC) analyses were filtered through polycarbonate membrane filters. These samples were acidified with concentrated HCl after sampling. Larger river suspended sediment samples were extracted from 60 to 1,000 L plastic barrels filled with zero salinity river water. The barrels were allowed to settle for several days to weeks, and the supernatant water was siphoned to allow recovery of the settled sediment slurry. Sediment trap cylinders were constructed of stainless steel 2 m high and 25 cm in diameter (height/diameter ¼ 8) with no top aperture baffles. There were six replicate cylinders in each aluminum trap frame. The trap frame was fitted with a 2 3 m tailfin of plywood, and the frame was suspended on a gimballed galvanized steel shaft that was attached to the plastic coated mooring wire above and below the trap frame. Current meters (Aanderaa RCM5) were positioned 10 m below each sediment trap frame on the mooring wire. Sediment traps were positioned at water depths of 300 m below the surface and 100 m above the bottom at locations identified by the ship’s Global Positioning System (GPS) (Fig. 6.2). The trap mooring was anchored to a 2 tonne concrete weight by means of chain and an acoustic release device. The teflon bottles attached to the bottom of each cylinder cone were filled with salinity 60 water with added HgCl2 for preservative. The bottles were immediately removed from the cylinders upon recovery, and the water was vacuum filtered through GF/A filters, 1.6 mm nominal pore size, to obtain the particulate matter. Grab samples and sediment cores were collected from sites located by GPS estimations (Figs. 6.2, 6.5, and 6.6). We used a modified van Veen grab in shallow locations, or a weighted Smith–MacIntyre grab at deeper locations, both having a top opening port for sampling surface (1–3 cm) sediment, on transects from the intertidal zone to the continental slope. Sediment cores from intertidal mangrove mud banks were taken with a custom built 150 mm i.d. plastic barrel push corer attached to a block and tackle tripod hook. A small gravity corer (steel 150 mm i.d. tubes, 0.5–2 m long) with 300 kg


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Figure 6.2: A bathymetric map of Gulf of Papua, showing the locations of sediment cores and sediment traps. The cores displayed in Figs. 6.8–6.11 are numbered on this map. Data for all other cores are given in Table 6.4. driving weight, a top closing lid upon retrieval, and an orange-peel type core catcher was used from the R/V Harry Messel. Sediment slices from both the mangrove corer and the small gravity corer were obtained by piston extrusion from the core bottom upward. Open water and deep water Kasten cores (Kuehl et al., 1985) were taken from the R/V Lady Basten and the R/V Franklin, using over 500 kg driving weight. The core tubes were 150 mm diameter square steel (2–4 m long, opening on one side for subsampling) with core top closure upon retrieval and a bottom core catcher. Sediment was subsampled for chemical analyses from grab samples and core slices, using cleaned plastic or stainless steel tools, and stored in plastic vials frozen on board the ship. Porites sp. coral bommies near Bramble Cay were cored in triplicate in 1994–1996, using a hand-held drill corer powered by a hydraulic motor. Cores

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were split sawed at AIMS, X-rayed, and studied under ultraviolet light to see the annual growth bands. Subsamples of coral aragonite from individual annual growth bands were obtained using a dremel tool with a steel bit. 6.2.2. Chemical and Radiochemical Analyses Measurements of concentrations of Cu, Al, and S were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES, Varian Liberty 220). For sediments they were analyzed after nitric and perchloric acid digestion of the dried and ground sediment sample (Loring and Rantala, 1992; Thompson and Walsh, 1993). Digestion was carried out in Pyrex tubes in a programmable Block Digester at 1201C for 3 h followed by 1801C for 3 h. Cu was measured from the emission at 324.754 nm. These ICP measurements represent strong acid extracts of the bulk sediment, and do not include elements contained in acid-resistant minerals such as quartz and the heavy minerals. Filters with suspended sediment from river water, estuarine salinity gradient water samples, and sediment trap samples were weighed dry, digested, and analyzed for metals in the same manner. Filtered water samples were analyzed directly by ICP-AES to measure dissolved elements. Aragonite powder from coral growth bands was dissolved in nitric acid and analyzed by ICP-AES for Ca, Fe, Sr, Ba, Pb, and Cu. Cu analytical precision was 5% or better for all element measurements on water and sediment. Digestion and recovery of Cu in certified reference materials 1646 Estuarine Sediment (NIST), Standard Reference Sediment MESS 2 from the National Research Council of Canada, and BCJS-1 Marine Sediment (NRCC) were within certified limits or within 95% confidence limits of several years of past data for that digest. No samples were below our detection limit for Cu in particulate material, and determinations on our reference samples suggest that we are measuring total Cu by this procedure. Measurements of organic carbon (OC) in sediments analyzed prior to 1995 were performed using a Beckman Carbon Analyzer with an infrared carbon dioxide detector, after acidification of the sediment slurry to digest inorganic carbon. Later OC analyses used a Shimadzu TOC Analyzer with solid sampler, after HCl extraction. Particulate OC, collected from water samples, was also analyzed using the Shimadzu TOC Analyzer after acidification of the suspended sediment on the glass fiber (GF/F) filters. DOC was determined by high-temperature catalytic oxidation on a Shimadzu TOC5000 Analyzer (Hedges et al., 1993). Gamma spectrometric measurements of 210Pb, 226Ra, 137Cs, and other isotopes were made on 50–150 g of dried and ground bulk sediment core


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slices packed (with a 10 tonne hydraulic press) into a custom designed gas-tight Perspex container. The energy spectra of the gamma spectrometers were calibrated with Amersham and CANMET standards, of known low-activity spikes of suitable nuclides, in cleaned silica and carbonate sand of geometry and mass similar to the sediment samples. IAEA marine sediment reference material IAEA-315 was used to check the calibrations. Counting errors of the sample measurements were less than 10%, except for some very low-activity 137Cs samples which had errors of 30%. Interpretations of radiochemical tracer sedimentation history were done with several submodels described by Robbins (1978, 1986). These utilize a sediment mixed layer thickness, a decadal-century scale average input of excess 210Pb, Brisbane measurements of thermonuclear bomb fallout 90Sr (for 137Cs) over 1950–1990 (McCallan et al., 1980; Torgersen et al., 1983; B400 Bq 137Cs m2), and diffusion coefficients for 210Pb and 137Cs in marine sediments (Li and Gregory, 1974). Estimates of the annual atmospheric flux of 210Pb and the 137Cs inventory have been obtained from soil profiles in north Queensland (approximately 50 Bq 210Pb m2 yr1, 300 Bq 137 Cs m2; Pfitzner et al., 2004). Mass accumulation rate (MAR) for each core profile is derived from the dry mass (g cm2) accumulated over several half-lives (22.26 years) of 210Pb in excess of its grandparent 226Ra, when there is a good log-linear relationship between accumulated sediment mass and excess 210Pb, in units of kg m2 yr1. In some intertidal and o20 m water depth cores, excess 210Pb and bomb fallout 137Cs are uniformly or irregularly distributed down the core, and sometimes we do not capture the entire inventory of these radiotracers of sedimentation. This may be the result of sediment mixing in situ, resuspension and mixing in the nepheloid layer, and subsequent redeposition or massive short-term (weekly, monthly, yearly) transient accumulation of uniformly labeled recent sediment (RS). For these later cores, we estimate ‘‘transient mass accumulation’’ (TMA) in units of the mass accumulated in four half lives of excess 210Pb (g cm2). This measure is intended to describe sediments of varying grain size and composition that are being resuspended, deposited, and moved as fluid mud toward sites of more permanent (century to millennial scale) sediment accumulation. Areas of the Gulf of Papua river catchment and the bathymetric contours for the adjacent continental shelf were determined from digitized map reading software. Annual and mean river discharge of water were provided by Ok Tedi Mining Ltd. (personal communication), and the Bureau of Water Resources of the PNG Department of Environment and Conservation (Mr. Narua T. Lovai, Boroko, NCD, PNG).

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6.3. Results We will present our results in the order useful for our mass balance of Cu: annual river supply rate, removal rate to sediments, removal rate to sediment traps, and the remainder being available to the Hiri Current of the Coral Sea. 6.3.1. River Supply Rate Freshwater data from 1993 to 2003 samples of the Fly, Kikori, and Purari Rivers (Fig. 6.2) for salinity, suspended sediment, dissolved and pCu, dissolved and particulate organic matter, and pAl and sulfur are presented in Table 6.1. The dCu measurements are from Simon Apte’s work (ref, this book), and dCu concentrations in the upper Fly River (above the confluence of the Strickland and Fly Rivers) are in the range 50–150 nM. The Strickland River contributes a large amount of water to the lower Fly River (catchment area ¼ 36.7 109 m2), with dCu in the range 7–16 nM (Apte, personal communication 2004). pCu in these river water samples is one to two orders of magnitude higher (1–4 mmol g1 of suspended sediment, or 0.6– 1 mmol L1) in concentration, compared to dCu. DOC varies little in the Fly River samples (0.15–0.28 mmol L1), but DOC in the Kikori and Purari Rivers appears to be somewhat lower in concentration (0.06–0.20 mmol L1). Particulate OC varies in concentration from 0.5 to 1.5 mmol g1 (or 0.08 to 0.25 mmol L1) amongst the three river freshwaters. Large particulate organic matter, such as living and dead terrestrial and mangrove trees, and rafts of floodplain and mangrove vegetation are commonly seen in the river, but are difficult to sample quantitatively (see Robertson et al., 1993). pAl varies little (2.3–4.4 mmol g1) in the suspended sediment of these rivers, whereas particulate sulfur (pS) varies by a factor of 7 (10–71 mmol g1) in suspended sediment samples. The wet tropical catchment areas of the Gulf of Papua rivers have average erosion rates of 1.0–1.2 kg m2 yr1, a factor of 5–10 higher than the other rivers listed in Table 6.2. High erosion rates are expected in catchments that have high relief (4.5 km) and high rainfall (4–10 m yr1). The rate of release of dCu from the Strickland, Kikori, and Purari River catchment soils and bedrock exposures is 21–36 mmol dCu m2 yr1, whereas the upper Fly River gives up much more dCu to the sea (243 mmol m2 yr1). Particulate Cu fluxes from the catchments of the Kikori and Purari Rivers were 920–1,940 mmol m2 yr1, whereas the upper Fly River annual transport of pCu was 2,460 mmol m2 yr1. Higher river catchment yields of dCu and pCu for the upper Fly River are due to mine tailings disposal into the headwater

Table 6.1: River zero salinity chemistry for the Gulf of Papua. River Fly

SS Sample Type Barrel SS Filter GFC

Barrel SS Filter c.a. Filter c.a. Barrel SS Filter c.a. Filter c.a. Barrel SS Filter c.a. Mean

Sep ‘97 Sep ‘97 Jan ‘99

0.1 0.1

dCu (nM)

271 62a 48a

0.1 0.7 0 0 0.8

217 243 250 141 164a

0.13 0.13 0.9 0 0 0.1 0 0 0.1 0.1 0.1

353 170 296 165 286 239 44 46 45

91

pCu (mmol g1)

DOC (mM)

1.07 1.52

0.276

2.8a 2.96 1.07 1.78 2.47 1.77 4.0 1.87 2.19 1.56 2.30 2.64 2.33 2.41 3.10 2.2 0.93 2.65 1.62 1.7

POC (mmol g1)

pAl pS (mmol g1) (mmol g1)

0.60

2.45

15

0.52

2.93 2.83 2.33 3.17 3.48

25 10 17 20 13

0.67

2.81

0.94

2.38 2.81 3.00 2.30 2.85 2.8

18 18 14 31 32 19 49 37 23

2.64 2.80 4.41 3.3

39 44 27 37

0.281 0.243 0.257 0.256

0.155 0.152 0.220b 0.215 0.216 0.23

0.69 0.87 0.72 1.76

0.059b 0.100 0.08

1.8

215

Kikori Barrel SS Filter c.a. Filter c.a. Mean

Jan ‘93 Jan ‘93 Feb ‘93 Jul ‘93 Feb ‘94 Feb ‘94 Feb ‘94 Feb ‘94 Feb ‘94 Mar ‘94 Mar ‘95 Mar ‘95 Mar ‘95 Aug ‘97 Aug ‘97 Jan ‘99 Feb ‘03 Feb ‘03

SS (mg L1)


Filter c.a. Filter c.a. Barrel SS Filter c.a. Filter c.a.

Date Salinity

216

Table 6.1: (Continued ). SS Sample Type

Date Salinity

Purari Filter c.a.

Feb ‘95

0.1

Wame Barrel SS Filter c.a. Filter c.a. Barrel SS Filter c.a. Mean

Sep ‘97 Sep ‘97 Jan ‘99 Feb ‘03 Feb ‘03

0.4 0.4 0.1 0.1 0.1

SS (mg L1) 191 30 40 187 112

dCu (nM)

pCu (mmol g1)

DOC (mM)

0.80

0.103

0.80 0.71 0.83 0.94 1.04 0.85

POC (mmol g1)

44 1.47

0.095b 0.111 0.200 0.13

pAl pS (mmol g1) (mmol g1)

0.75 0.94 1.1

2.40 2.75 3.59 2.84 3.71 3.1

71 64 30 28 15 42

Note: The Fly River samples were collected upstream of Sumogi Island, well below the confluence of the upper Fly River and the Strickland River. SS, surface water suspended sediment; dCu, copper that passes through a filter; pCu, particulate copper retained on a filter; DOC, dissolved organic carbon; POC, particulate organic carbon; pAl, particulate aluminum; and pS, particulate sulfur; GFC, Whatman glass fiber coarse filter; c.a., cellulose acetate 0.45 mm pore diameter filter. a Data from Simon Apte, Centre for Advanced Analytical Chemistry, Sydney, NSW, Australia ([email protected]) Chapter 9 (319–371) of this book. b Peter Davies data, See Davies (2004).


River


217

Ok Tedi River. The mountainous and tropical Amazon River transports a similar amount of dCu from its catchment (per unit area, and compared to the Strickland, Kikori, and Purari Rivers), but temperate zone (and technologically developed) European river catchments yield much lower dCu and pCu transport to the sea (Table 6.2). We estimate the average annual river input of suspended sediment, dCu and pCu to the Gulf of Papua in Table 6.3. Approximately 275 106 mol of dissolved and pCu are added to the Gulf of Papua annually, and about 70% of this is from the Fly River. This computation is based on the freshwater concentrations of Cu multiplied by estimates of average annual river flow. The estimate for dCu (10 106 mol yr1) is probably too high, as half of this dCu appears to be removed from solution and adsorbed to particulate phases in the lower salinity gradient. We have no dCu data for the Kikori and Purari Rivers, so we have used Apte’s data for the Strickand River (B12 nM) as an estimate of this input.

6.3.2. The Salinity Gradient Simon Apte’s data for dCu along the salinity gradient show that over half of the dCu is removed from the solution phase to the particulate phase at salinities of 0–3 (Apte, 2009). After this initial removal of dCu, there appears to be conservative mixing of high concentrations of dCu (50–150 nM) in the Fly River with low concentrations of dCu from the Strickland River (12 nM) and in the Gulf of Papua (1 nM). DOC concentrations decline in an irregular manner along the salinity gradient (Fig. 6.3), from 0.2 to 0.3 mmol L1 in low-salinity water, to o0.1 mmol L1 in outer shelf waters. Our DOC salinity gradient profile for August 1997, and Robertson et al. (1993) profile for 1991, show an increase in DOC at salinity 15–20. We have no dissolved Al data, but sulfate mixes conservatively from low concentrations in the rivers (B1 mM) to high concentrations (28 mM) at salinity 35 in Coral Sea water. Solution pH varies from 7 to 8.2 along the salinity gradient. Our pCu data for the salinity gradient (Fig. 6.3) contain data for suspended sediment from the Fly, Kikori, and Purari rivers, their deltas, and offshore waters. River water varied from 1 to 3 mmol pCu g1, and most samples from the salinity gradient were close to 1 mmol pCu g1. A few samples of suspended sediment from February 1994 (near Bramble Cay), February 2003, and November 2003 (from offshore of the Kikori River Delta) had higher pCu concentrations of 3–6 mmol g1 at salinity 20–35. We have no reason to believe that these samples were contaminated by us, as the

Upper Fly Strickland Fly and Strickland Purari Kikori Amazon Zaire (Congo)

Chanjiang (Yangtze) Huanghe (Yellow) Zhujiang (Pearl) Mekong GangesBrahmaputra Netravati and Gurpur Mississippi Loire Morlaix Scheldt Danube

SS (g m2 yr1)

pAl (mol m2 yr1)

1,118 1,200

dCu pCu (mmol m2 yr1) (mmol m2 yr1) 243 28

1,100 1,143 192

3.1 3.4 21 0.84

11

0.03

36 21 30

2,460 920 1,940 806

1.6

18

256

205

1,460 249 200 941

614 192 340 442

0.83 2.7

331 105 15 23 102

250 0.40

0.5

80 17 4 8 8.4

Note: The average annual load of river sediment, Al, and Cu was divided by the river catchment area.

12 78 184

Source This study, Apte (2009). Apte (2009) This study This study This study Boyle et al. (1982); Martin and Meybeck (1979) Eisma and van Bennekom (1978); Martin et al. (1978); Meybeck (1979); Sholkovitz et al. (1979) Zhang et al. (1992); Zhang (1999) As above As above Martin and Meybeck (1979) As above Shankar and Manjunatha (1994) Martin and Meybeck (1979) Waeles et al. (2004a, b) Monbet (2004) Zwolsman and van Eck (1999) Guieu et al. (1998)


River

218

Table 6.2: The annual rate of river transport of suspended sediment, particulate Al, dissolved and particulate Cu from river catchment areas.

Table 6.3: The annual river supply rate of water, surface suspended sediment, and copper to the Gulf of Papua. River

Qa SSa (109 m3 yr1) (1012 g yr1)

dCu (nM)

39.3

81723

34

91(1)

36.7 76.0

112721 193

51 85

12(1)

33.7

97

37

17.5 15 142

30 12 332

20 14 156

pCu S dCu S pCu S Cu (mmol g1) (106 mol yr1) (106 mol yr1) (106 mol yr1) 7.4

2.2

1.3 8.7

187

196

[12]

0.85

1.2

31

33

[12] [12]

1.7 [0.85]

0.36 0.14 10.4

34 12 264

34 12 275

Note: Dissolved Cu input was calculated as average dCu concentration times mean annual river flow rate (Qa). Particulate copper was calculated as measured average pCu times mean annual suspended sediment discharge rate (SSa). Fly and Strickland River water flow data are from OTML. Dissolved Cu data(1) is from Simon Apte. Numbers in square brackets are estimates based on Apte’s Strickland River data. SdCu=Qa dCu for an average year. SpCu ¼ SSa pCu for an average year. SCu=SdCuþSpCu for an average year. Ad is the land drainage area for each river.


Fly River at Obo, upstream of Strickland River Strickland River Total Fly River input to delta Purari (Wame Channel) River Kikori Other Total for Gulf of Papua

Ad (109 m2)

219

220


Figure 6.3: The variation of dissolved and particulate organic carbon (OC), particulate Cu and Al, and suspended sediment concentration along the salinity gradient from fresh river water to offshore Gulf of Papua seawater, over 1993 to 2003. same sampling and analytical methods were used on samples from lower salinity waters. Figure 6.3 also gives a view of the variation of suspended sediment, pAl, and POC along the salinity gradient. A maximum in suspended sediment concentration is usually seen between salinity 5 and 15 in the Fly River delta. The composition of the suspended sediment does not change much along the salinity gradient, with most values between 2.5 and 3.5 mmol Al g1, 1–2 mmol POC g1, and 10–30 mmol S g1. A few samples from the mid shelf


221

Figure 6.4: The variation of the ratios of particulate Cu/Al, Cu/OC, Cu/S along the salinity gradient from fresh river water to offshore Gulf of Papua seawater. south of the Kikori Delta, and near Bramble Cay, are greatly depleted in pAl and enriched in pS and POC, and these samples usually had high pCu concentrations (Fig. 6.4). Per unit volume, pAl, and POC were found in high concentrations, and declined in an irregular manner to low concentrations offshore at salinity 30–35. The ratios pCu/pAl, pCu/POC, and pCu/pS along the salinity gradient are shown in Fig. 6.4. The ratio of Cu/Al in suspended sediment along the salinity gradient changes little (3–8 104) from salinity 0 to 25, but Cu is enhanced relative to aluminum in the low suspended sediment concentrations of the outer Gulf of Papua at salinities greater than 30. Particulate Cu declines in proportion to POC and pS along the salinity gradient (Fig. 6.4).

6.3.3. The Distribution of Cu in Surface Sediments Copper concentrations in surface sediment grab samples (0–3 cm) are higher (600–1,000 nmol g1) in the aluminosilicate clay-rich deltas and inner

222


shelf, and much lower in the hard bottom carbonate sediments of the outer shelf (Fig. 6.5). Some of the deep water pelagic carbonate sediments of the continental slope and northern Coral Sea have higher Cu concentrations (150–700 nmol g1), especially in the eastern Gulf offshore from Port Moresby. This distribution of Cu appears to be related to the relative abundance of the aluminosilicate clay and coarse carbonate fractions, with fine-grained sediments that have high Al concentrations usually having high Cu concentrations (Figs. 6.6 and 6.7). The sediment molar ratio Cu/Al varies 1–5 104, with enhanced Cu concentrations being found on the Fly River delta front and seaward near the 100 m depth contour, and along the central and eastern inner shelf on the top and foreset beds of the clinoform (Fig. 6.6). Sediments with low Cu/Al were usually black sand-rich (SE of the Bamu and Turama Inlets) or hard-bottom carbonate-rich sediments of the outer shelf from 80 to 150 m water depth (Fig. 6.6). The relationship between Cu and Al in Fig. 6.7 indicates a family of outliers which probably represent ‘‘hotspots’’ of undiluted recent Fly River sediment in zones of transient sediment deposition, which have much higher concentrations of Cu (1,000–4,000 nmol g1, Table 6.1). Large variation in concentrations of sedimentary organic matter, sulfur (Fig. 6.7), manganese, and iron (not shown) do not give useful predictions of Cu concentrations.

Figure 6.5: The variation of Cu concentration in surface sediment grab samples from the Gulf of Papua. The cross (þ) symbols indicate locations of surface sediment grab samples that were analyzed for Cu in this study.

Figure 6.6: The variation of the ratio Cu/Al in surface sediment grab samples from the Gulf of Papua. The cross (þ) symbols indicate locations of surface sediment grab samples that were analyzed for Cu in this study.

Figure 6.7: The relationships between copper, aluminum, OC, and sulfur in surface sediment grab samples from the Gulf of Papua. The locations of these grab samples are shown by the (þ) symbols in Figs. 6.5 and 6.6, and we have sorted the data points in these graphs by the depth zones 0–20 m, 20–100 m, and W100 m.

224


6.3.4. Sediment Core Chemistry and Accumulation Rates of Copper in Sediments Table 6.4 and Figs. 6.8–6.11 show the variation in Cu and likely host elements with sediment core depth, and core profiles of radiochemical tracers that we use to estimate sediment accumulation rate. We present these data according to the depth zones indicated in Table 6.4: the intertidal cores, subtidal cores to 10 m depth, cores from 10–100 m depth of the major sedimentary clinoform, and cores from the continental slope and northern Coral Sea at water depths of 200–2,000 m. The depth zone from 100 to 200 m is largely hard-ground carbonate sediment, from which we have not recovered any cores, and which we consider to have zero or very low sediment and copper accumulation rates on our recent century time scale.

6.3.5. Intertidal Zone, 0–3 m Tidal range in the Gulf of Papua is 3–4 m, and tidal energy moves sediment seaward, landward, and along-shore. Most medium to large tidal channels are nondepositional zones with hard sandy bottoms, and there are many sandbars and islands that appear to be composed of sand and gravel. Fine-grained sediments accumulate on the low-current mangrove aprons opposite the channel cut bank, and sometimes at the junctions of smaller channels with larger channels. We have observed the transient nature of some of the mangrove mud banks, some of them accumulating and then vanishing over several years of observation. With very few exceptions in the intertidal zone, excess 210Pb and bomb fallout 137Cs profiles in cores of mud and sandy mud suggest that sequential packages of sediment are deposited episodically and are sometimes mixed and homogenized during frequent resuspension and redeposition events. As an example for the intertidal zone, cores 205 (in the Fly River delta, see Fig. 6.2) and 3618 (in the Kikori River delta, Ai Ai River) do not show the expected exponential decline in excess 210 Pb or the known history of 137Cs deposition (Fig. 6.8), and thus cannot easily be used to estimate sediment accumulation rate. They do indicate that a large thickness (1–1.5 m) of sediment is labeled with our short-lived radiotracers, and this is roughly quantified by our RS parameter in Table 6.4. We consider RS (in g cm2) to be equivalent to an inventory of sediment that is transient on a time scale less than four half-lives of 210Pb (89 years). In both of these intertidal cores, the RS inventory is incomplete,

Table 6.4: Gulf of Papua sedimentation rates, sediment Cu concentrations, and Cu burial rate. Depth interval Area Core m (109 m2) Number 0–10

20–30

2.93

2.18

MAR Ex210PbI 2 1 (kg m yr ) (Bq m2) 5,208 704 4,325 5,972 400 1,595 W26,580 W21,410 8,504 12,382 4,684 12,879

137

RS (g cm2)

CsI Cu (nmol (Bq m2) g1)

75 33 W66 99 5.1 24 W85 W100 50 50 40 105

500 134 244 406 53 195 W1,032 W960 384 536 177 446

787 787 820 800 700 658 800 700 720 630 1,100 1,420

Cu Cu (mmol m2 (profile) yr1)

IT IT IT IT 8 8 IT 10 6 9 5 8

EoM EoM EoM EoM EoM EoM EoM EoM 6.6 EoM EoM EoM 6.9 Transient

223 224 1,206 2,067 3,163 3,615 3,639 Mean

15 15 16 13 20 15 14

3.6 M, 1.4 M, 3 M, 0.6 M, 2.5 M, 0.7 EoM 1.7

5,322 2,288 5,706 3,566 8,789 2,667 5,247

35 16 50 14 48 10 24

384 250 667 159 441 60 125

580 500 628 680 700 650 600

O O O

2,048 3,161 3,154 3,616 Mean

24 27 27 24

28.5 M, 0.3 26.7 6.5 18.5

15,618 1,039 10,710 5,048

W120 7 110 60

943 44 828 133

600 300 400 410

O O O

I O I S O O O I O

O O

6.63 11.7 W6.1 8.9 0.40 1.8 W7.6 W7.9 4.8 3.5 4.9 16 (6.8) Transient 2.0 0.70 1.9 0.41 1.8 0.46 0.81 1.1 17.1 0.090 10.7 2.7 7.6

225

203 204 205 206 217 218 3,618 3,634 3,638 3,636 3,666 3,668 Mean


10–20

12.57

Z (m)

226

Table 6.4: (Continued ).

30–50

50–100

3.97

14.3

Z (m)

MAR Ex210PbI 2 1 (kg m yr ) (Bq m2)

RS (g cm2)

137

CsI Cu (nmol (Bq m2) g1)

Cu Cu (mmol m2 (profile) yr1)

208 210 215 216 230 231 2,046 3,123 3,128 3,139 3,150 3,617 3,619 3,623 Mean

48 48 42 42 45 45 40 42 46 42 48 52 37 49

8.0 9.6 10 13.5 3.5 4.8 2.6 2.3 3.5 EoM 22 9.8 9.5 25.6 9.6

14,093 15,762 12,500 13,713 11,803 16,677 3,717 13,160 9,336 45,526 41,025 20,214 16,280 50,767

70 65 82 86 38 46 22 40 32 W220 W150 65 85 W180

338 408 844 904 19 99 30 190 329 1,494 1,777 573 620 1,764

400 425 600 600 400 400 176 520 610 600 600 580 470 600

S S O S S I S S I O I S I

220 221 234 235 3,134 3,144 3,148 3,158 3,620 3,622 Mean

55 55 66 66 68 58 76 83 76 70

4.3 5.5 2.0 1.4 14.7 2.4 4.1 2.0 3.8 1.9 4.2

9,106 11,648 15,392 11,776 49,340 9,140 20,792 18,384 20,312 15,473

30 35 W20 18 180 55 35 30 40 28

198 233 61 38 1,501 171 137 69 134 23

381 390 420 480 600 400 400 425 390 200

O O S O O O, I O S I

3.2 4.1 6.0 8.1 1.4 1.9 0.46 1.2 2.1 0.59 13.2 5.7 4.5 15.0 4.8 1.6 2.1 0.84 0.67 8.8 0.92 1.6 0.85 1.5 0.38 1.9


Depth interval Area Core m (109 m2) Number

100–200 200–1,000

4.7 5.7

1,000–2,000

9.75

923 923 473 473

232 233 240 241 1,611 1,616 1,632 1,630 Mean

1,618 1,618 1,117 1,117 1,509 1,245 1,472 2,045

0.25 0.25 0.40 0.50 0.35

13,676 19,398 3,132 6,464

W8 6 7 13

ND ND ND ND

550 450 150 180

O S S S

0.14 0.11 0.060 0.090 0.10

0.85 0.40 o0.1 0.5 o0.2 o0.3 o0.01 0.55 0.36

11,604 19,357 4,677 5,110 2,496 658 750 5,300

20 W22 8 W5 4 4 1.3 10

ND ND ND ND ND ND ND ND

700 625 440 420 600 400 500 700

S S I O I S D S

0.60 0.25 o0.044 0.21 o0.12 o0.12 o0.005 0.39 0.22

Note: Locations of sediment core sites are given in Fig. 6.2. Z, water depth at core site; MAR, sediment mass accumulation rate; Ex 210PbI, inventory of excess 210Pb down core in Bq m2; RS, Recent sediment labeled with excess 210Pb in g cm2; 137CsI, Inventory of 137Cs down the core in Bq m2; IT, intertidal zone; EoM, Episodic sedimentation or mixed core; M, thick 210Pb mixed layer; ND, not detected; Cu core profile code: I, Cu increasing at core top; D, Cu decreasing toward top; S, no variation in Cu; O, Oscillating Cu concentrations down core. RS was converted to Transient Mass Accumulation (TMA) ¼ g m2 yr1 accumulated over 4 210Pb half lives (89 years). This TMA was multiplied by the Cu concentration of the sediment to obtain a transient Cu accumulation rate in sediments.


236 237 238 239 Mean

227

228


Figure 6.8: Intertidal and deltaic (0–3 m water depth) sediment core profiles of Cu, Cu/Al, Cu/OC, Cu/S, excess 210Pb, and 137Cs for representative cores 205 and 3618 from the Gulf of Papua. See Table 6.4 for an interpretation of the depositional history of these cores. There is no exponential decline in excess 210Pb in most of the cores from this depth zone, and we interpret these locations to have massive episodic sediment deposition or deep mixing of sediment supplied in the last century. as our maximum depth of core samples had easily measurable excess 210Pb and 137Cs. We designate this type of sedimentation as ‘‘episodic or mixed’’ (EoM) in Table 6.4. For purposes of the Cu mass balance, we have divided the sediment mass inventory RS in Table 6.4 by 89 years, to obtain a semiquantitative transient mass accumulation (TMA) rate, but we do not give this TMA equal status to estimates of MAR obtained from cores that display exponential declines in excess 210Pb and a reasonable profile of 137 Cs. In the intertidal cores in Table 6.4, RS varies from 33 to 99 g cm2, and the calculated TMA ranges from 3 to W11 kg m2 yr1. The inventories


229

Figure 6.9: Subtidal (3–10 m water depth) sediment core profiles of Cu, Cu/ Al, Cu/OC, Cu/S, excess 210Pb, and 137Cs for representative cores 3638 and 3668. See Table 6.4 for an interpretation of the depositional history of these cores. There is no exponential decline in excess 210Pb in most of the cores from this depth zone, and we interpret these locations to have massive episodic sediment deposition or deep mixing of sediment supplied in the last century. of excess 210Pb and 137Cs in the cores in Table 6.4 are related to RS and the thickness of the transient sediment mass. Concentrations of Cu in core 205 increase smoothly from 490 nmol g1 at the core bottom to 800 nmol g1 at the sediment surface, which suggests that the sediment is not wholly homogenized by mixing (Fig. 6.8). The ratios Cu/Al and Cu/OC also increase smoothly toward the sediment surface, indicating a 50% enrichment in Cu with respect to the aluminosilicate phase of the sediment in recent time. Core 205 was taken in mangrove sediments in

230


Figure 6.10: Inner shelf (10–100 m) sediment core profiles of Cu, Cu/Al, Cu/ OC, Cu/S, excess 210Pb, and 137Cs for representative cores 3134, 3154, and 3639. See Table 6.4 for an interpretation of the depositional history of these cores. The arrow indicates the approximate core horizon of deposition of sediment in 1900.


231

Figure 6.11: Continental slope and northern Coral Sea sediment core profiles of Cu, Cu/Al, Cu/OC, Cu/S, excess 210Pb, and 137Cs for representative cores 241 and 1630. The arrow indicates the approximate core horizon of deposition of sediment in 1900. See Table 6.4 for an interpretation of the depositional history of these cores. the channel between Purutu and Aibinio Island, in the middle of the estuarine salinity gradient of the Fly River delta. Concentrations of Cu in core 3618 show no trend with time, and vary between 700 and 830 nmol g1 (Fig. 6.8). These variations in Cu concentration appear to be due to variations in the abundance of the aluminosilicate phase, as Cu/Al ratios are fairly constant down core at 2.5–3 104. This core was taken in a mangrove apron mud bank at the juncture of a tidal creek and a major tidal channel in the Kikori River delta. The other intertidal cores listed in Table 6.4 show similar profiles of Cu, Cu/Al, Cu/OC, and Cu/S.

232


6.3.6. Subtidal Zone, 3–10 m Table 6.4 gives sedimentation rate and Cu data for seven cores from the subtidal zone of the Gulf of Papua. This region is generally difficult to core with our equipment, as much of the area is black sand or wave-packed stiff muddy sand. Only one core (3638 in Table 6.4 and Fig. 6.9) from a small patch of mud south of Turama Inlet (see Fig. 6.2) gave us an accumulation rate from our radiotracers. Excess 210Pb MAR was 6.6 kg m2 yr1, and 137 Cs was distributed down to 50 cm in this core. The other cores for this zone listed in Table 6.4 are similar to core 3668 (Fig. 6.9) from south of Bamu Inlet (Fig. 6.2), where excess 210Pb and 137Cs are distributed down the core in an irregular way to 106 cm core depth. Core 3668 appears to consist of two packages of sediment labeled with excess 210Pb homogeneous sediment, the top 10 cm package of higher activity, and then a homogeneous package from 10 to 106 cm. Other cores from this zone often show 2–5 separate packages of radiotracer labeled sediment, and some have occasional laminations of coarse black sand and finer muddy sand. As defined in the previous section, we estimate RS for these cores to be 5 to W100 g cm2, with a TMA of 0.5 to W11 kg m2 yr1 (Table 6.4, Fig. 6.9). We think that our estimate of fine-grained sediment and sedimentary Cu accumulation in this 3–10 m depth zone is likely to be over-estimated, because: (1) most of our coring attempts were successful in small patches of mud within a larger area that is hard packed sand and copper-poor, (2) we do not have coring equipment that works well in sand, (3) we have few cores from this largest area of the Gulf, the topset of the clinoform, and (4) the observed nonchronological deposition is difficult to quantify. Our methods clearly do not quantify the rate of accumulation of sandy sediments. Concentrations of Cu, and the ratios Cu/Al and Cu/OC, show a small increase from the core bottom to the surface 40 cm in core 3638 (Fig. 6.9), with a dramatic increase in the Cu/S ratio. Core 3668 displays a somewhat oscillatory down core variation in Cu, Cu/Al, Cu/OC, and Cu/S, with a general enhancement in Cu concentration in the surface 40 cm, relative to its likely host phases Al, organic matter, and sulfur (Fig. 6.9). We estimate an average TMA for the 3–10 m water depth zone of 6.7 kg m2 yr1, where RS varies from 5 to W100 g cm2. Average pCu accumulation rate in this zone is a transient 6.7 mmol m2 yr1 (Table 6.4). Obviously, the uncertainty in extrapolation of these parameters in this depth zone is large.


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6.3.7. Inner Shelf, 10–100 m In general, the quality of our sediment cores, and the application of our radiotracer methods to estimate MAR, were much better offshore, where mud accumulation occurs in a more chronological fashion well below wave base and the effects of tidal scouring. The surface of the cores usually showed a 1–3 cm rusty red oxidized iron layer, sometimes with surface sediment polychaete worm tubes intact. MAR varied from 0.3 to 28.5 kg m2 yr1 (Table 6.4, Fig. 6.10), and most of the cores had 210Pb surficial mixed layers of 10–50 cm depth. We present three cores as examples of this depositional zone in Fig. 6.10. Core 3639 from 14 m water depth (Fig. 6.2) has a 25 cm thick mixed layer of excess 210Pb and 137Cs labeled sediment (RS ¼ 12 g cm2), below which is an older sediment with undetectable activities of our radiotracers. This may represent a fluid mud layer resting temporarily on much older sediments. Concentrations of Cu, and ratios of Cu/Al and Cu/OC, vary little from the core bottom to the surface, but there is a large increase in Cu/S within the surface 25 cm layer. Core 3154 from 30 m water depth (Fig. 6.2) has a good exponential decline in excess 210Pb with core depth (or accumulated mass per unit area), which suggests a MAR of 26.7 kg m2 yr1 with little indication of surface sediment mixing in the core. 137Cs was detected to 130 cm core depth, and this core probably represents o30 years of deposition history. RS ¼ 110 g cm2, which also suggests a large thickness of RS that contains our radiotracer labels. Cu concentrations, and the ratios Cu/Al, Cu/OC, and Cu/S are nearly constant from the bottom of the core (at 260 cm) to 50 cm, but all these parameters increase and then decline slightly in the top 50 cm of the core (Fig. 6.10). Core 3134 from 67 m water depth at the bottomset toe of the clinoform, south of the Kikori Delta (Fig. 6.2), has a thin 210Pb mixed layer of 11 cm, and displays an exponential decline in excess 210Pb activities over four halflives and 150 cm of core depth (Fig. 6.10 and Table 6.4). This chronology and MAR of 14.7 kg m2 yr1 is confirmed by the 137Cs profile, which was found to be undetectable below 50 cm core depth. RS ¼ 180 g cm2, which indicates a very large inventory of RS of deposition age o100 years. The inventory of excess 210Pb and 137Cs is also very large, approximately 50 and 5 times greater than atmospheric supply rates respectively. These data suggest that this site receives fine-grained sediment with our attached radiotracers from a much larger area, probably the 0–20 m water depth zone. Cu concentrations, Cu/Al and Cu/S vary little from the core bottom to about 50 cm, where these

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parameters increase slightly. Cu/OC varies little in this core, but declines in the top 50 cm. All of the other 33 cores listed in Table 6.4 show similar trends to our example cores. MAR varied from 0.3 to 28 kg m2 yr1, RS varied from 7 to W220 g cm2, and sedimentary Cu accumulation rate varied from 0.09 to 17 mmol m2 yr1. 6.3.8. Continental Slope and Northern Coral Sea, 200–2,000 m The average accumulation rate of sediment and Cu is one to two orders of magnitude smaller on the seafloor of the slope and northern Coral Sea (Table 6.4). No 137Cs was detected in these deeper water cores, and we rely on the profile of excess 210Pb alone to estimate MAR. In most cores, excess 210Pb was detected only in the top 6–10 cm, but an exponential decline was observed, suggesting MAR in the range o0.1 to 0.85 kg m2 yr1 (Table 6.4, Fig. 6.11). These sediments are a golden tan pelagic foraminifera and pteropod ooze with a variable and small aluminosilicate fraction. We give profile data for two example cores in Fig. 6.11. Core 241 was taken at the base of the slope offshore directly south of the mouth of the Purari River at 1,117 m water depth (Fig. 6.2). The excess 210 Pb profile is based upon the top 6 cm, where excess 210Pb activities are very high (100–300 Bq kg1), and the profile suggests a MAR ¼ 0.5 kg m2 yr1. If this chronology is correct, then the changes in Cu concentration in this core shown in Fig. 6.11 occurred well before 1900. Cu concentration is relatively constant at 400 nmol g1 from the core bottom at 160 cm up to 20 cm core depth, where there is a rapid decline in Cu concentration to 300 nmol g1, followed by an increase back to 400 nmol g1. This near surface variation in Cu concentration was not caused by variations in the supply of aluminosilicate minerals, as the Cu/Al ratio changes over this near surface interval. The abundance of Cu relative to organic matter and sulfur increases from about 100 cm core depth to the surface (Fig. 6.11). Core 1630 was taken from 2,045 m water depth in the northern Coral Sea, SE of Eastern Fields (Fig. 6.2). A good exponential decline in excess 210Pb was observed, again with very high activities in the top core slices, suggesting a MAR of 0.55 kg m2 yr1 (Fig. 6.11). Cu concentrations vary from 220 to 800 nmol g1 over the 160 cm core length, with the top 10 cm having Cu concentrations of about 700 nmol g1. The ratios Cu/Al, Cu/OC, and Cu/S all show an oscillatory behavior, with Cu/S declining greatly in the top 6 cm slices of the core.


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The other 10 cores listed in Table 6.4 have similar characteristics, with an average MAR of 0.3 kg m2 yr1 and a sedimentary Cu accumulation rate of 0.06 to 0.6 mmol m2 yr1. The inventory of sediment mass labeled with our radiotracer (RS) ranged from 1 to 22 g cm2, and the inventory of excess 210 Pb was usually greater than expected from atmospheric fallout for this region (B50 Bq m2 yr1).

6.3.9. Removal Rate of Copper to Sediment Traps The rate of removal of Cu from the pelagic water column at the base of the continental slope and northern Coral Sea was determined during TROPICS cruises in May–July 1997 (Fig. 6.2 and Table 6.5). This time period is during the SE Trade Winds season, when maximum wave energy is directed into the crescent of the Gulf of Papua (Fig. 6.1). We tried to estimate the Cu removal rate from the warm surface layer of the northern Coral Sea with traps set at 300 m, below the thermocline at 80–130 m. Deeper traps set on the mooring wire at 900–1,360 m (100 m above the seafloor) probably collected the sediment rain from the euphotic zone as well as horizontal fluxes of sediment from the continental shelf and slope. Total sediment flux to the traps was 0.1 to 0.2 g m2 d1 (Table 6.5), but much higher trap fluxes were observed from the deep Kerema Canyon trap site (0.6 g m2 d1) where shelf sediment is probably discharged into the Coral Sea. The sediment trap material is greatly enhanced in Cu concentration, relative to sources in the Gulf of Papua rivers and continental shelf (Table 6.5) and the sediment composition beneath the sediment trap mooring sites (cores 236, 237, 240, 241, 1630) in Table 6.4. In proportion to Al, OC, and S, Cu concentration in the sediment trap material is enhanced 5 to over 10 fold, compared to river, shelf, and slope sediments. If we extrapolate these sediment trap results to a full year, and multiply the composition by the annual mass flux to the traps, we obtain the annual Cu removal rates shown in Table 6.6. These removal rates of Cu (0.1–0.5 mmol m2 yr1) for trap sites south of the Fly River and in the northern Coral Sea are about one tenth of Cu accumulation rates on the inner shelf, but are very similar to sedimentary Cu burial rates on the slope and northern Coral Sea (Table 6.4). In contrast, the sediment trap mooring in the Kerema Canyon collected material that was enriched in Cu (higher Cu concentration than found in rivers), had higher sediment accumulation rates, and relatively high sedimentary Cu accumulation rates (0.7–4.3 mmol Cu m2 yr1).

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Trap site

Water depth (m)

Trap depth (m)

Mooring duration days

SSE Fly River Slope Kerema Canyon Eastern fields Northern Coral Sea

Cu Al OC S Mass flux (g m2 d1) (mmol g1) (mmol g1) (mmol g1) (mmol g1)

dates

1,040

300 940

50 50

Jun–Jul ‘97 Jun–Jul ‘97

0.115 0.232

970

300 870

44 44

Jun–Jul ‘97 Jun–Jul ‘97

0.181 0.574

1,460

300

29

May ‘97

0.118

1,360

29

May ‘97

0.106

Note: Locations of sediment trap moorings are given in Fig. 6.2.

3.55 5.80 11.6 20.4 2.71 10.0

2.34 7.23

12 3.23

0.73 0.45

2.96 31.5

1.10 2.6

0.23 0.83

0.25 0.98

15.9 5.33

0.16 0.14


Table 6.5: Mooring details, bulk sediment mass flux, and chemical composition of Gulf of Papua sediment trap material (copper, aluminum, organic carbon, and sulfur).

Trap site

Trap depth (m)

Mass (g m2 yr1)

Cu (mmol m2 yr1)

S (mmol m2 yr1)

Al (mmol m2 yr1)

OC (mmol m2 yr1)

SSE Fly River slope

300 940

42 85

149 491

31 38

98 612

504 274

Kerema Canyon

300 870

66 210

766 4,270

15 174

196 6,600

72 545

Eastern Fields

300

43

117

6.9

11

685

1,360

38

387

5.4

38

206

Northern Coral Sea

Note: Annual fluxes were calculated by multiplying the average trap sediment composition by the sediment mass flux per unit area per day, and then by 365 days yr1. These data were derived from Table 6.5.


Table 6.6: Sediment trap annual fluxes for total sediment dry weight, copper, sulfur, aluminum, and organic carbon in the Gulf of Papua in 1997.

237

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6.3.10. Copper in Annual Growth Bands of Corals One of three replicate Porites sp. coral cores from near Bramble Cay in Torres Strait was scanned by gamma densitometry to determine the chronology of the growth bands. Corals in this region have extension rates of 12–18 mm yr1 and calcification rates of 1.7–2 g cm2 yr1, and some cores show annual records back to 1776 (Lough et al., 1999). Samples were taken of growth bands from the years 1906 and 1911 to determine the average Fe and Cu concentration of river-supplied elements before mine tailings disposal began in the Fly River catchment. Samples from growth bands representing 1984–1990 and 1990–1992 were taken to determine the average Fe and Cu concentration in corals after mine tailings had been added to the upper Fly River for a decade. The results are presented in Table 6.7 as the ratio Fe/Ca and Cu/Ca, which indicates that recent coral growth bands have Cu/Ca ratios 40–60% greater than this ratio in the early 1900s, whereas Fe/Ca ratios have changed little over this time period. Fe and Cu were approximately equal in concentration in the growth band aragonite (0.2–0.3 mmol g1) in 1906–1911, but Cu concentrations doubled in coral growth bands of 1984–1992 (0.40–0.46 mmol g1).

6.4. Discussion 6.4.1. Rate of Addition of Copper to the Gulf of Papua The mass balance for Cu in the Gulf of Papua is given in Table 6.8. The dominant input is pCu from rivers (264 106 mol yr1), whereas dCu input was estimated from Simon Apte’s data as 10 106 mol yr1. Over 70% of this dCu and pCu came from the Fly River (Table 6.3). The rate of transport of Cu from these wet tropical river catchment areas is relatively high (1–2 mmol Cu m2 yr1) compared to temperate zone river catchments in industrialized countries (Table 6.2). This is partly due to the high relief of the headwater catchments, high rainfall (5–10 m yr1), relatively young bedrock, and the tectonic uplift rate (3–6 cm yr1) of these mountain ranges. The weathering rate of Cu in the headwater mountains of the Fly and Purari Rivers is probably higher than that shown in Table 6.2, as the high relief fraction of the river catchment areas will provide most of the riverine sediment and copper. The Ok Tedi and Porgera mine tailings disposal will provide an additional sediment and trace element load to the river, and the Ok Tedi mine has probably doubled the pCu supply rate of


239

Table 6.7: The ratio Fe/Ca and Cu/Ca from annual growth bands of a massive Porites sp. coral bommie near Bramble Cay, directly south of the mouth of the Fly River. Sample (no.)

Growth band (year)

Luminescence

110F 49F 845F 890F

1984–1990 1990–1992 1911 1906

Yes No Yes No

Fe/Ca ( 106)

Cu/Ca ( 106)

23 23 20 50

39 47 23 29

Note: This coral core was collected in 1995, and the annual growth bands were tracked using gamma densitometry and measurement of luminescence according to Isdale et al. (1998), Lough et al., (1999). Coral growth bands that are strongly luminescent are thought to be more affected by river runoff, while growth bands with little or no luminescence have had little river influence.

Table 6.8: The copper mass balance for the Gulf of Papua. Parameter River input Loss to sediment burial Loss to sediment traps, 300 m Loss to sediment traps, 1,000 m Export to Coral Sea

dCu (106 mol yr1) 10.4

0.000119

pCu (106 mol yr1)

S Cu (106 mol yr1)

264

275 156 2.0 6.8

119

119

Note: The annual river input includes the sum of the Fly, Strickland, Purari, and Kikori Rivers, as well as an estimate for ungauged catchment areas (using the unit area annual catchment yield for pCu from the Purari and Kikori Rivers). Loss to sediment burial was calculated from the average Cu burial rate for each depth zone multiplied by the area of that depth zone in Table 6.4. The unit area fluxes to the sediment traps were multiplied by the seafloor area of the slope and northern Coral Sea (200–2,000 m) listed in Table 6.4, to obtain the average annual removal rate from the water column. The dCu exported to the Coral Sea is estimated based upon Kd ¼ 106.

the upper Fly River, and increased dCu by a factor of B10 (Table 6.2, and Simpson et al., 2005). Simpson et al. (2005) show that chemolithotrophic microbes oxidize the fresh sulfidic mine tailings (containing chalcopyrite, digenite, and chalcocite) within a few days of discharge to the river, and that downstream pCu is largely nonsulfidic. The extensive floodplains on the catchment lowlands of these rivers are likely to be a sink for sediments and Cu. If this annual river supply rate of 275 106 mol of Cu to the Gulf of Papua was deposited in the sediments of the 0–100 m depth zone

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of area 36 109 m2, this would provide an average Cu burial rate of 7.6 mmol m2 yr1. Input of Cu to the Gulf of Papua from dust to this region is likely to be very low (Duce et al. 1991; Hesse and McTainsh, 2003; Jickells et al. 2005), contained in 0.2–0.5 g dust m2 yr1. If the dust contained 5 mmol Al g1, and if Cu/AlB104 in this dust, then the input might be o0.25 mmol Cu m2 yr1, or o15 103 mol yr1 over the Gulf of Papua. Inputs of Cu from upwelling of deep Coral Sea water are not known, but likely to be large, because of the large volume of Coral Sea water advected onto the shelf, compared to river inputs (Coral Sea water/river water ratio B300). 6.4.2. Rate of Removal of Copper From the Gulf of Papua The measured removal of Cu from the water column of the Gulf of Papua to sediment burial at the seafloor from 0–2,000 m water depth was 156 106 mol yr1, or about 56% of the river input rate (Table 6.8). Most of this Cu removal was in the depth zone from 0 to 100 m on the inner shelf, where sedimentation rates were high and Cu burial rates were 0.4 to 15 mmol m2 yr1 (see Table 6.4). The largest area of fine-grained and Al–Cu rich sediment accumulation was in the region between Turama Inlet, the Kikori and Purari River deltas, whereas the delta front clinoform directly southeast of the Fly River contains relatively small amounts of fine sediment and lower accumulation rates (Fig. 6.6). Removal rates of Cu from the slope and pelagic water column of the Northern Coral Sea were much smaller. About 2 106 mol Cu yr1 were scavenged from the clear blue euphotic zone south of the slope (to the 300 m sediment traps), and additional 6.8 106 mol Cu yr1 was delivered to the deep sediments (the 900–1,300 m sediment traps) of the northern Coral Sea by lateral injection (turbidity currents, nepheloid layers) from the shelf (Tables 6.6 and 6.8). We propose that much of this off-shelf transport occurs south of Kerema and eastward toward Port Moresby, where the width and area of the shelf is greatly reduced. Evidence to support this suggestion comes from the 870 m deep Kerema sediment trap (Tables 6.5 and 6.6), which collected five times more sediment with much higher Cu concentration (20.4 mmol Cu g1), compared to the other two trap sites (Fig. 6.2). Deep water oceanic removal rates of Cu from the water column to sediments are in the range 7–14 mmol Cu m2 yr1, and much of this Cu appears to be associated with organic matter (Fischer et al., 1986; Heggie et al., 1987; Noriki et al., 1998). Surface sediment diagenesis of organic


241

matter probably releases some of this Cu back to the deep water (Kumar et al., 1996). These sediment accumulation rates of Cu are several orders of magnitude smaller than those found in the inner shelf of the Gulf of Papua, but are within a factor of 10 of some of the data from the 1–2 km water depth zones of the northern Coral Sea (Tables 6.4 and 6.6).

6.4.3. Annual Export from the Shelf and Slope to the Coral Sea This removal of Cu by sedimentation leaves 43% of the river annual input to escape the Gulf into the northern Coral Sea, the Hiri Gyre, and the New Guinea Coastal Current. If a Kd of 106 is appropriate (Shafer et al., 2004) for the salinity 34–35 water of the Hiri Gyre, then most of this Cu must be in the particulate or colloid phase. This annual input of 119 106 mol of Cu per year must be the largest riverine input of Cu to the Coral Sea, as water and sediment inputs from north Queensland are small. Due to its very large volume (B20 Sv, Burrage, 1993), the Hiri Gyre (and the South Equatorial Current) would carry a very large input of Cu. Some perspectives upon how this loss of Cu from the shelf happens can be seen in Table 6.9, where we present the mole ratios Cu/Al, Cu/OC, and Cu/S for the river suspended sediment input, the fraction being buried on the shelf, the Kerema Canyon trap particles, and the largely pelagic particles caught by Table 6.9: Changes in the abundance of copper relative to likely host mineral phases (aluminosilicate clays, organic matter, sulfide minerals) for components of the Gulf of Papua Cu mass balance. Mass balance parameter River freshwater suspended sediment Shelf and slope sediments Pelagic and shelf particles in Kerema Canyon traps Pelagic particles in Eastern Fields traps

Cu/ Al 104

Cu/ OC 104

Cu/ S 103

Comments

3–8

8–30

20–96

1–4

3–15

2–20

6–39

78–105

25–50

Loss of Cu, compared to river input Gain of Cu

102–108

2–19

17–71

Gain of Cu

Note: These ratios are taken from Figs. 6.5, 6.7, 6.9 and 6.10 and Tables 6.3, 6.5, and 6.6.

242


sediment traps SE of Eastern Fields Reef in the northern Coral Sea. We use these ratios to imply the dominant host particle types (aluminosilicate clay minerals, organic matter, and iron/manganese oxide/sulfide minerals) that carry pCu from the river inputs to the Coral Sea (Gibbs, 1973) as shown in Figs. 6.4 and 6.7. River suspended sediments have Cu/Al ¼ 3–8 104, whereas most sediments carrying pCu to burial sites on the shelf and slope have reduced Cu concentrations and Cu/Al ¼ 1–4 104 (Figs. 6.8–6.11). This reduction in Cu/Al suggests a release of Cu from the aluminosilicate phase along the reaction pathway. This ratio increases greatly in particles caught by the offshore sediment traps (Tables 6.5, 6.6 and 6.9) where Cu/Al ¼ 40–100 104, and where the aluminosilicate mineral fraction in hemipelagic carbonate sediment is relatively small. However, seafloor sediments below the sediment traps at the base of the slope and northern Coral Sea do not have such high Cu/Al ratios (Figs. 6.8–6.11), indicating that these Cu-rich particles must be carried further seaward, or that diagenesis releases sedimentary Cu into deep Coral Sea water. This same sequence is observed for Cu/OC and Cu/S (high in river suspended sediment, decrease in shelf sediments, much higher Cu enrichment in the Kerema Canyon sediment trap particles), except that the northern Coral Sea (Eastern Fields) trap sediments had similar or lower Cu/OC (2–19 104) compared to the river input sediments (Table 6.9). These variations in Cu/Al and Cu/OC suggest that some transformation of the riverine sediment happens along the salinity gradient and on the innershelf sediment accumulation sites. This transformation of particle surfaces must release Cu from the riverine sediments, sorb Cu to a more mobile (colloidal?) aluminosilicate and/or organic matter phase that can be transported off the shelf to the northern Coral Sea. Perhaps much of the repeated mixing, resuspension, oxidation, redeposition, and diagenetic reduction of transient sediments in the intertidal and subtidal zone (Table 6.4) is the location of this transformation process (Simpson et al., 1998; Aller, 2004; Aller et al., 2004; Aller and Blair, 2004; Robert et al., 2004). Fresh river water Kd ¼ [moles Cu/g SS]/[moles Cu/g filtered water] B2–6 104, whereas at the other end of the salinity gradient in seawater we find Kd ¼ 5–10 105 (derived from Simon Apte’s dCu and pCu data, and our data in Fig. 6.4). This suggests that riverine pCu is more labile and reactive, and that marine particles have more sorption sites that attract dCu. Whatever the process might be, Cu accumulation rates in our sediment cores have been relatively constant for several millennia over most of the shelf, slope, and northern Coral Sea (Figs. 6.9–6.11). If Cu uptake into living Porites sp. aragonite comes from the dCu pool at Bramble Cay, then our coral cores suggest that there has been at least a


243

doubling of the availability of dCu to these corals in the last century (Table 6.7). Inoue et al. (2005) have shown that Cu/Ca varies in coral growth bands according to increase and decrease of anthropogenic Cu supply to the coral habitat. The isopleths of Cu concentration over the Gulf of Papua (Fig. 6.5) give the impression that Cu is equally abundant in the river deltas and inner shelf, and in the northern Coral Sea deep sediments. Table 6.4 shows that the sediment accumulation rate of Cu to deltaic and inner-shelf sediments is 10–100 times greater than that of the deep water Coral Sea sediments, and that the factor controlling this difference is bulk sediment accumulation rate. Pelagic and shelf-derived particles with relatively high Cu concentrations (Tables 6.5 and 6.6) rain to the seafloor at 1–2 km water depths, but most of this Al or OC-bound Cu must be diagenetically released back to the water column and transported elsewhere. The variation in Cu concentration in suspended and bottom sediments is best predicted by Al (Figs. 6.3–6.7), whereas organic matter, sulfur, iron, and manganese do not appear to vary in proportion to Cu concentration in sediment. The equation for this relationship (Fig. 6.7) is Cu ¼ 0:2187ðAlÞ þ 5:7421; R2 ¼ 0:48 In the outer shelf relict carbonate sediments, where both Al and Cu are found in very low concentrations, the sedimentary ratio of Cu/Al may give some spurious results (Fig. 6.6). The Cu/Al relationship (Figs. 6.6 and 6.7) also reveals a few Cu enriched sediment locations to the SE of the North Channel of the Fly River Delta, which are probably undiluted recent Fly River suspended sediments influenced by Ok Tedi Mine tailings additions to a Fly River headwater tributary (Ok Tedi) over the last 25 years. Notice that our sediment cores have been taken over the period 1993–2003, and that many of the cores with Cu enrichment at the surface are more recent cores. We might expect increasing delivery of Cu-rich sediment to the Gulf of Papua in the next several decades, when the upper delta turbidity maximum becomes saturated with Cu-rich sediments from the Fly River. The addition of 29 1012 g yr1 of Cu-rich mine tailings over the past 25 years of the OTML operations (Simpson et al., 2005) can be seen in a few core sites in the Fly Delta mangrove channels and the intertidal zone eastward in the Gulf of Papua (Figs. 6.8 and 6.9), but natural variations in Cu concentrations over the last millennium are of similar magnitude. Most of these longer term pre-1900 natural variations in Cu concentration (Figs. 6.9–6.11) are the result of variations in supply rates of aluminosilicate (Cu-rich) and carbonate (Cu-poor) minerals to the seafloor.

244


Mine tailings rich in copper are added to the headwaters of the Ajkwa River in Irian Jaya (West Papua), and the downstream Cu signal is very strong (enhancement by factors of 20–40 above pre 1950 sediment Cu accumulation rates) in the intertidal zone mangrove mud (Brunskill et al., 2004). There must be some large difference in hydrological and sediment transport mechanisms for the Ajkwa River, compared to the Fly River, as the Fly River somehow sequesters much of the mine tailings in the floodplains and upper delta. It may be that the volume of fluid mud (Wolanski et al., 1995b, Wolanski and Gibbs, 1995) moving in and out of the Fly River delta is so large, that 20 years of mine tailings input is greatly diluted and slowly dispersed over the shelf. If this is the case, then we would expect the titration of the Fly River delta fluid mud with Cu-rich mine tailings to proceed over the next few decades, increasing the pCu concentration in the surface mixed layer of inner-shelf sediments of the entire Gulf of Papua.

6.5. Conclusions About 57% of the river-supplied particulate and dCu can be found in the sediments of the continental shelf and slope of the Gulf of Papua. The remainder (119 106 mol of Cu per year) must be delivered in ligand, colloid, or particulate form to the Hiri Gyre of the Coral Sea. This system is not in steady state, as there has been a large increase in the river supply rate of Cu from mining operations in the headwaters of the Fly River. There are a few sites in the inner shelf where this excess Cu can be observed, but most of the shelf and slope sediment cores do not show large increases in Cu in recent sediments. This is probably due to estuarine dilution by the natural fluid mud reservoir, and century scale bottom sediment mixing on the inner shelf.

ACKNOWLEDGMENTS This work is the result of over a decade of research in the Gulf of Papua as part of Project TROPICS, involving many ships and ship crews, scientific collaborators, and logistic and diplomatic support from Australia, Papua New Guinea, and USA. We particularly wish to thank the Masters and crew of the R/V Lady Basten and R/V The Harry Messel from the Australian Institute of Marine Science, the R/V Franklin from the Australian National Facility and CSIRO Marine ship managers and technicians, Field Operations Managers John Hardman and Tony McKenna of AIMS, and


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David Vaudrey and Ron Plaschke of CSIRO Marine. Ok Tedi Mining LTD (Murray Eagle, Ian Wood, Jim Veness, Barrie Bolton) provided their measurements of river flow for the Fly and Strickland Rivers, and access to the R/V Western Venturer for research in the Fly Delta. We thank Simon Apte for access to his measurements of dCu and pCu in the Fly River salinity gradient. We thank Ruth Blunden and Greg French of the Australian Department of Foreign Affairs and Trade in Canberra, and Sarah Story of the Australian Embassy in Port Moresby, for their assistance in arranging research ship clearances in foreign waters. Don Niles, Michael Laki, and Jim Robbins (PNG National Research Institute), Patricia Pepina (Marine Research Subcommittee, Government of Papua New Guinea), and Dr. Hugh Davies (Earth Sciences, University of Papua New Guinea) assisted with our research visa applications and helped in other ways. Coral cores were collected by Glen Shen, Roberta Hamme, and Irena Zagorskis, and Bruce Parker (deceased) provided expertise in coral growth band history and sampling for chemical analyses. In the AIMS analytical laboratory, Steve Boyle and Cassie Payn did the ICP-AES and DOC analyses presented here. The AIMS Engineering Workshop built all of our coring equipment, and the AIMS library kept us up to date with the biogeochemical literature. We thank Sheila M. Brunskill for help with mangrove coring, careful proof reading of this manuscript, and a lot of other things.

REFERENCES Agell, G., Turon, X., De Caralt, S., Lopez-Legentil, S., & Uriz, M. J. (2004). Molecular and organism biomarkers of copper pollution in the ascidian Pseudodistoma crucigaster. Marine Pollution Bulletin, 48, 759–767. Aller, R. C. (2004). Conceptual models of early diagenetic processes: The muddy seafloor as an unsteady, batch reactor. Journal of Marine Research, 62(6), 815–835. Aller, J. Y., & Aller, R. C. (2004). Physical disturbance creates bacterial dominance of benthic biological communities in tropical deltaic environments of the Gulf of Papua. Continental Shelf Research, 24(19), 2395–2416. Aller, R. C., & Blair, N. E. (2004). Early diagenetic remineralization of sedimentary organic C in the Gulf of Papua deltaic complex (Papua New Guinea): Net loss of terrestrial C and diagenetic fractionation of C isotopes. Geochimica et Cosmochimica Acta, 68(8), 1815–1825. Aller, R. C., Hannides, A., Heilbrun, C., & Panzeca, C. (2004). Coupling of early diagenetic processes and sedimentary dynamics in tropical shelf environments: The Gulf of Papua deltaic complex. Continental Shelf Research, 24(19), 2455–2486. Alongi, D. M., Tirendi, F., & Robertson, A. I. (1991). Vertical profiles of copper in sediments from the Fly Delta and Gulf of Papua, Papua New Guinea. Marine Pollution Bulletin, 22, 253–255.

246


Apte, S. C., & Day, G. M. (1998). Dissolved metal concentrations in the Torres Strait and Gulf of Papua. Marine Pollution Bulletin, 36, 298–304. Apte, S. C. (2009). Biogeochemistry of copper in the Fly River. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 321–373. Audry, S., Schafer, J., Blanc, G., Bossy, C., & Lavaux, G. (2004). Anthropogenic components of heavy metal (Cd, Zn, Cu, Pb) budgets in the Lot-Garonne fluvial system (France). Applied Geochemistry, 19(5), 769–786. Baker, E. K., Harris, P. T., & Beck, R. W. (1990). Cu and Cd associated with suspended particulate matter in Torres Strait. Marine Pollution Bulletin, 21, 484–486. Baker, E. K., & Harris, P. T. (1991). Copper, lead, zinc distribution in the sediments of the Fly River Delta and Torres Strait. Marine Pollution Bulletin, 21, 484–486. Boyle, E. A., Huested, S. S., & Grant, B. (1982). The chemical mass balance of the Amazon Plume. II. Copper, nickel, and cadmium. Deep Sea Research, 29, 1355–1364. Brewer, P. G., & Spenser, D. W. (1975). Minor element models in coastal waters. In: T. M. Church (Ed.). Marine Chemistry of Coastal Environments. American Chemical Society, Washington, D.C., pp. 80–96. Broecker, W. S., & Peng, T.-H. (1982). Tracers in the Sea. Published by LamontDoherty Geological Observatory, Columbia University, Palisades, New York, 690 pp. Brunskill, G. J., Zagorskis, I., & Pfitzner, J. (2003). Geochemical mass balance for lithium, boron, and strontium in the Gulf of Papua, Papua New Guinea (Project TROPICS). Geochimica et Cosmochimica Acta, 67(18), 3365–3383. Brunskill, G. J. (2004). New Guinea and its coastal seas, a testable model of wet tropical processes: An introduction to Project TROPICS. Continental Shelf Research, 24, 2273–2295. Brunskill, G. J., Zagorskis, I., Pfitzner, J., & Ellison, J. (2004). Sediment accumulation rates and geochemical history in sediment cores from the Ajkwa River estuary mangroves in Irian Jaya (West Papua, Indonesia). Continental Shelf Research, 24, 2535–2551. Burrage, D. M. (1993). Coral sea currents. Corella, 17, 135–145. Canli, M., Stagg, R. M., & Rodger, G. (1997). The induction of metallothionein in tissues of the Norway lobster Nephrops vorvegicus following exposure to cadmium, copper and zinc: The relationships between metallothionein and the metals. Environmental Pollution, 96, 343–350. Carey, A. E., Nezat, C. A., Lyons, W. B., Kao, S.-J., Hicks, D. M., & Owen, J. S. (2002). Trace metal fluxes to the ocean: The importance of high-standing oceanic islands. Geophysical Research Letters, 29(23), 2099, doi:10.1029/2002GL015690. Chadwick, D. B., Zirino, A., Rivera-Duarte, I., Katz, C. N., & Blake, A. C. (2004). Modeling the mass balance and fate of copper in San Diego Bay. Limnology and Oceanography, 49(2), 355–366.


247

Chelazzi, G. M., De Pirro, M., & Williams, G. A. (2004). Different cardiac response to copper in limpets from metal polluted and clean shores of Hong Kong. Marine Environmental Research, 58, 83–93. Cobelo-Garca, A., & Prego, R. (2003). Land inputs, behaviour and contamination levels of copper in a ria estuary (NW Spain). Marine Environmental Research, 56(3), 403–422. Cobelo-Garcia, A., Prego, R., & Labandeira, A. (2004). Land inputs of trace metals, major elements, particulate organic carbon and suspended solids to an industrial coastal bay of the NE Atlantic. Water Research, 38(7), 1753–1764. Davies, P. (2004). Nutrient processes and chlorophyll in the estuaries and plume of the Gulf of Papua. Continental Shelf Research, 24(19), 2317–2341. Di Toro, D. M., Mahony, J. D., Hansen, D. J., Scott, K. J., Hinks, M. B., Mayr, S. M., & Redmond, S. M. (1990). Toxicity of cadmium in sediments: The role of acid volatile sulfide. Environmental Science and Technology, 9, 1487–1502. Dryden, C. L., Gordon, A. S., & Donat, J. R. (2004). Interactive regulation of dissolved copper toxicity by an estuarine microbial community. Limnology and Oceanography, 49(4), 1115–1122. Duce, R. A., Liss, P. S., Merill, J., Atlas, E. L., Buat-Menard, P., Hicks, B. B., Miller, J. M., Prospero, J. M., Arimoto, R., Church, T. M., Ellis, W., Galloway, J. N., Hansen, L., Jickells, T. D., Knap, A. H., Reinhardt, A. H., Schneider, B., Soudine, A., Tokos, J. J., Tsunogai, J. J., Wollast, R., & Zhou, M. (1991). The atmospheric input of trace species to the world ocean. Global Biogeochemical Cycle, 5, 193–259. Edmond, J. M. (1992). Himalayan tectonics, weathering processes, and the strontium isotope record in marine limestones. Science, 258, 1594–1597. Edmond, J. M., & Huh, Y. (1997). Chemical weathering yields from basement and orogenic terrains in hot and cold climates. In: W. F. Ruddiman (Ed.). Tectonic Uplift and Climate Change. Plenium, NY, pp. 329–351. Eisma, D., & van Bennekom, A. J. (1978). The Zaire River and estuary and the Zaire outflow in the Atlantic Ocean. Netherlands Journal of Sea Research, 12(3/4), 255–272. Fischer, K., Dymond, J., Lyle, M., Soutar, A., & Rau, S. (1986). The benthic cycle of copper: Evidence from sediment trap experiments in the eastern tropical North Pacific Ocean. Geochimica et Cosmochimica Acta, 50, 1535–1543. Garcia-Villada, L., Rico, M., Altamirano, M., Sanchez-Martin, L., Lopez-Rodas, V., & Costas, E. (2004). Occurrence of copper resistant mutants in the toxic cyanobacteria Microcystis aeruginosa: Characterisation and future implications in the use of copper sulphate as algaecide. Water Research, 38(8), 2207–2213. Garrels, R. M., & Mackenzie, F. T. (1971). Evolution of Sedimentary Rocks. Norton Publishers, New York. Geracitano, L. A., Bocchetti, R., Monserrat, J. M., Regoli, F., & Bianchini, A. (2004). Oxidative stress responses in two populations of Laeonereis acuta (Polychaeta, Nereididae) after acute and chronic exposure to copper. Marine Environmental Research, 58, 1–17.

248


Gibbs, R. J. (1973). Mechanisms of trace metal transport in rivers. Science, 180, 71–73. Goldberg, E. D. (1963). The oceans as a chemical system. In: The Sea, Volume 2. Wiley, New York, pp. 3–25. Gordon, A. S. (1992). Isolation of compounds with affinity for copper from seawater using immobilized copper ion affinity chromatography. Marine Chemistry, 38, 1–12. Gordon, A. S., Dyer, B. J., Kango, R. A., & Donat, J. R. (1996). Copper ligands isolated from estuarine water by immobilized metal affinity chromatography: Temporal variability and partial characterization. Marine Chemistry, 53, 163–172. Guieu, C., Martin, J.-M., Tankere, S. P. C., Mousty, F., Trincherini, P., Bazor, M., & Dai, M. H. (1998). On trace metal geochemistry in the Danube River and Western Black Sea. Estuarine, Coastal and Shelf Science, 47, 471–485. Harris, P. T., Hughes, M. G., Baker, E. K., Dalrymple, R. W., & Keene, J. B. (2004). Sediment transport in distributary channels and its export to the prodeltaic environment in a tidally dominated delta: Fly River, Papua New Guinea. Continental Shelf Research, 24(19), 2431–2454. Hedges, J. I., Bergamaschi, B. A., & Benner, R. (1993). Comparative analyses of DOC and DON in natural waters. Marine Chemistry, 41, 121–134. Herskovits, T. T., & Hamilton, M. G. (1991). Higher order assemblies of molluscan hemocyanins. Comparative Biochemistry and Physiology, 99B, 19–34. Heggie, D., Klinkhammer, G., & Cullen, D. (1987). Manganese and copper fluxes from continental margin sediments. Geochimica et Cosmochimica Acta, 51(5), 1059–1070. Heidmann, I., Christl, I., & Kretzschmar, R. (2005). Sorption of Cu and Pb to kaolinite–fulvic acid colloids: Assessment of sorbent interactions. Geochimica et Cosmochimica Acta, 69(7), 1675–1686. Hemer, M. A., Harris, P. T., Coleman, R., & Hunter, J. (2004). Sediment mobility due to currents and waves in the Torres Strait-Gulf of Papua region. Continental Shelf Research, 24(19), 2297–2316. Hesse, P. P., & McTainsh, G. H. (2003). Australian dust deposits: Modern processes and the Quaternary record. Quaternary Science Review, 22(18/19), 2007–2035. Hooke, R. LeB. (2000). On the history of humans as geomorphic agents. Geology, 28, 843–846. Inoue, M., Suzuki, A., Nohara, M., Kan, H., Edward, A., & Kawahata, H. (2005). Coral skeletal tin and copper concentrations at Pohnpei, Micronesia: Possible index for marine pollution by toxic anti-biofouling paints. Environmental Pollution, 129(3), 399–407. Isdale, P. J., Stewart, B. J., Tickle, K. S., & Lough, J. M. (1998). Palaeohydrological variation in a tropical river catchment: A reconstruction using fluorescent bands in corals of the Great Barrier Reef, Australia. The Holocene, 8, 1–8.


249

Islam, M. S., & Tanaka, M. (2004). Impacts of pollution on coastal and marine ecosystems including coastal and marine fisheries and approach for management: A review and synthesis. Marine Pollution Bulletin, 48, 624–649. James, R. H., Elderfield, H., & Palmer, M. R. (1995). The chemistry of hydrothermal fluids from the Broken Spur site, 291N mid-Atlantic Ridge. Geochimica et Cosmochimica Acta, 59(4), 651–659. Jiann, K.-T., Wen, L.-S., & Santschi, P. H. (2005). Trace metal (Cd, Cu, Ni and Pb) partitioning, affinities and removal in the Danshuei River estuary, a macro-tidal, temporally anoxic estuary in Taiwan. Marine Chemistry, 96, 293–313. Jickells, T. D., An, Z. S., Anderson, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata, H., Kubilay, N., La Roche, J., Liss, P. S., Mahowald, N., Prospero, J. M., Ridgwell, A. J., Tegen, I., & Torres, R. (2005). Global iron connections between desert dust, ocean biogeochemistry and climate. Science, 308, 67–71. Jonas, R. B. (1989). Acute copper and cupric ion toxicity in an estuarine microbial community. Applied and Environmental Microbiology, 55, 43–49. Kim, S.-G., & Kang, J.-C. (2004). Effect of dietary copper exposure on accumulation, growth and haematological parameters of the juvenile rockfish, Sebastes schlegeli. Marine Environmental Research, 58, 65–82. Kim, H. J., Graham, D. W., DiSpirito, A. A., Alterman, M. A., Galeva, N., Larive, C. K., Asunskis, D., & Sherwood, P. M. A. (2004). Methanobactin, a copperacquisition compound from methane-oxidizing bacteria. Science, 305(5690), 1612–1615. Kozelka, P. B., & Bruland, K. W. (1998). Chemical speciation of dissolved Cu, Zn, Cd, Pb in Narragansett bay, Rhode Island. Marine Chemistry, 60, 267–282. Kuehl, S. A., Nittrouer, C. A., DeMaster, D. J., & Curtin, T. B. (1985). A long square-barrel gravity corer for sedimentological and geochemical investigation of fine-grained sediments. Marine Geology, 62, 365–370. Kumar, N., Anderson, R. F., & Biscaye, P. E. (1996). Remineralization of particulate authigenic trace metals in the Middle Atlantic Bight: Implications for proxies of export productivity. Geochimica et Cosmochimica Acta, 60, 3383–3397. Lackschewitz, K. S., Devey, C. W., Stoffers, P., Botz, R., Eisenhauer, A., Kummetz, M., Schmidt, M., & Singer, A. (2004). Mineralogical, geochemical and isotopic characteristics of hydrothermal alteration processes in the active, submarine, felsic-hosted PACMANUS field, Manus Basin, Papua New Guinea. Geochimica et Cosmochimica Acta, 68(21), 4405–4427. Lehman, J. T., Bazzi, A., Nosher, T., & Nriagu, J. O. (2004). Copper inhibition of phytoplankton in Saginaw Bay, Lake Huron. Canadian Journal of Fisheries and Aquatic Sciences, 61(10), 1871–1880. Li, Y.-H., & Gregory, S. (1974). Diffusion of ions in seawater and in deep-sea sediments. Geochimica et Cosmochimica Acta, 38, 703–714. Li, Y.-H. (2000). A compendium of geochemistry, from solar nebula to the human brain. Princeton University Press, Princeton, NJ, 475 pp.

250


Lieberman, R. L., & Rosenzweig, A. C. (2005). Crystal structure of a membranebound metalloenzyme that catalyses the biological oxidation of methane. Nature, 434(7030), 177–182. Lippard, S. J. (1999). Free copper ions in the cell?. Science, 284, 748–749. Loring, D. H., & Rantala, R. T. T. (1992). Manual for the geochemical analyses of marine sediments and suspended matter. Earth-Science Reviews, 32, 235–283. Lough, J. M., Barnes, D. J., Devereux, B. J., & Tobin, S. (1999). Variability in Growth Characteristics of Massive Porites on the Great Barrier Reef. CRC Reef Research Centre Technical Report No. 28, Townsville, Queensland, 95 pp. Lowenstein, T. K., Timofeeff, M. N., Kovalevych, V. M., & Horita, J. (2005). The major ion composition of Permian seawater. Geochimica et Cosmochimica Acta, 69, 1701–1719. Luoma, S. N., van Geen, A., Lee, B.-G., & Cloern, J. E. (1998). Metal uptake by phytoplankton during a bloom in south San Francisco Bay: Implications for metal cycling in estuaries. Limnology and Oceanography, 43(5), 1007–1016. Mackenzie, F. T., & Garrels, R. M. (1966). Chemical mass balance between rivers and oceans. American Journal of Science, 264, 507–525. Mackenzie, F. T. & Wollast, R. (1977). Sedimentary cycling of global processes. In: E. D. Goldberg, I. N. McCave, J. J. O’Brien & J. H. Steele (Eds). The Sea-Ideas and Observations on Progress in the Study of the Seas, Vol. 6: Marine Modeling. Wiley, New York, pp. 739–788. Mantoura, R. F. C., Martin, J.-M., & Wollast, R. (Eds). (1991). Ocean Margin Processes in Global Change. Wiley, New York, p. 469. Martin, J.-M., Thomas, A. J., & van Grieken, R. (1978). Trace element composition of Zaire suspended sediments. Netherlands Journal of Sea Research, 12(3/4), 414–420. Martin, J.-M., & Meybeck, M. (1979). Elemental mass balance of material carried by major world rivers. Marine Chemistry, 7, 173–206. Martin, J.-M., & Windom, H. L. (1991). Present and future roles of ocean margins in regulating marine biogeochemical cycles of trace elements. In: R. F. C. Mantoura, J.-M. Martin, & R. Wollast (Eds). Ocean Margin Processes in Global Change. Wiley, New York, pp. 45–67. Massey, A. G. (1973). The chemistry of copper. In: The Comprehensive Inorganic Chemistry Series, Chapter 27. Pergamon Press, Paris, pp. 1–78. McCallan, M. E., O’Leary, B. M., & Rose, C. W. (1980). Redistribution of Caesium137 by erosion and deposition on an Australian soil. Australian Journal of Soil Research, 18, 119–128. Meybeck, M. (1979). Note on dissolved elemental contents of the Zaire River. Netherlands Journal of Sea Research, 12(3/4), 293–295. Meybeck, M., & Vorosmarty, C. (2005). Fluvial filtering of land-to-ocean fluxes: From natural holocene variations to anthropocene. Comptes Rendus Geoscience, 337, 107–123. Meyer, J. S., Santore, R. C., Bobbitt, J. P., Debrey, LD., Boese, C. J., Paquin, P. R., Allen, H. E., Bergman, H. L., & DiToro, D. M. (1999). Binding of nickel and


251

copper to fish gills predicts toxicity but free ion activity does not. Environmental Science and Technology, 33(6), 913–916. Moffett, J. W., & Brand, L. E. (1996). Production of strong, extracellular Cu chelators by marine cyanobacteria in response to Cu stress. Limnology and Oceanography, 41, 388–395. Moffett, J. W., Brand, L. E., Croot, P. L., & Barbeau, K. A. (1997). Cu speciation and cyanobacterial distribution in harbours subject to anthropogenic Cu inputs. Limnology and Oceanography, 42, 789–799. Monbet, P. (2004). Dissolved and particulate fluxes of copper through the Morlaix River estuary (Brittany, France): Mass balance in a small estuary with strong agricultural catchment. Marine Pollution Bulletin, 48, 78–86. Negri, A. P., & Heyward, A. J. (2000). Inhibition of coral fertilisation and larval metamorphosis by tributyltin and copper. Marine Environmental Research, 51, 17–27. Noriki, S., Arasahitani, Y., Minakawa, M., Harada, K., & Tsunogai, S. (1998). Vertical cycling of Cu and Ni in the western North and Equatorial Pacific. Marine Chemistry, 59, 211–218. Peizhen, Z., Molnar, P., & Downs, W. R. (2001). Increased sedimentation rates and grain sizes 2–4 Myr ago due to the influence of climate change on erosion rates. Nature, 410, 891–897. Pfitzner, J., Brunskill, G. J., & Zagorskis, I. (2004). 137Cs and excess 210Pb deposition patterns in estuarine and marine sediment in the central region of the Great Barrier Reef Lagoon, north-eastern Australia. Journal of Environmental Radioactivity, 76(1-2), 81–102. Pickard, G. L., Donguy, J. R., Henin, C., & Rougerie, F. (1977). A Review of the Physical Oceanography of the Great Barrier Reef and Western Coral Sea. Australian Institute of Marine Science Monograph Series, volume 2, 135 pp. Prigge, S. T., Eipper, B. A., Mains, R. E., & Amzel, L. M. (2004). Dioxygen binds end-on to mononuclear copper in a precatalytic enzyme complex. Science, 304(5672), 864–867. Rae, T. D., Schmidt, P. J., Pufahl, R. A., Culotta, V. C., & O’Halloran, T. V. (1999). Undetectable intracellular free copper: The requirement of a copper chaperone for superoxide dismutase. Science, 284, 805–808. Richter, F. M., & Turekian, K. (1993). Simple models for the geochemical response of the ocean to climatic and tectonic forcing. Earth and Planetary Science Letters, 119, 121–131. Rivera-Duarte, I., Rosen, G., Lapota, D., Chadwick, D. B., Kear-Padilla, L., & Zirino, A. (2005). Copper toxicity to larval stages of three marine invertebrates and copper complexation capacity in San Diego bay, California. Environmental Science and Technology, 39(6), 1542–1546. Robbins, J. A. (1978). Geochemical and geophysical applications of radioactive lead. In: J. O. Nriagu (Ed.). Biogeochemistry of Lead in the Environment, Vol. 1A. Elsevier Scientific Publishers, pp. 285–393.

252


Robbins, J. A. (1986). A model for particle-selective transport of tracers in sediments with conveyor belt deposit feeders. Journal of Geophysical Research, 96, 17081–17104. Robert, S., Blanc, G., Schafer, J., Lavaux, G., & Abril, G. (2004). Metal mobilization in the Gironde Estuary (France): The role of the soft mud layer in the maximum turbidity zone. Marine Chemistry, 87(1–2), 1–13. Robertson, A. I., Daniel, P. A., Dixon, P., & Alongi, D. M. (1993). Pelagic biological processes along a salinity gradient in the Fly Delta and adjacent river plume (Papua New Guinea). Continental Shelf Research, 13(2–3), 205–224. Rubey, W. W. (1951). Geologic history of sea water. Bulletin of the Geological Society of America, 62, 1111–1147. Sarasquete, M. C., Gonzales de Canales, M. L., & Gimeno, S. (1992). Comparative histopathological alterations in the digestive gland of marine bivalves exposed to Cu and Cd. European Journal of Histochemistry, 36, 223–232. Schlesinger, W. H. (1997). Biogeochemistry, An Analysis of Global Change. Academic Press, Sydney, Australia, 588 pp. Seritti, A., Pellegrini, D., Morelli, E., Barghigiani, C., & Ferrara, R. (1986). Copper complexing capacity of phytoplankton exudates. Marine Chemistry, 18, 351–358. Shafer, M. M., Hoffmann, S. R., Overdier, J. T., & Armstrong, D. E. (2004). Physical and kinetic speciation of copper and zinc in three geochemically contrasting marine estuaries. Environmental Science and Technology, 38(14), 3810–3819. Shankar, R., & Manjunatha, B. R. (1994). Elemental composition and particulate mental fluxes from Netravati and Gurpur Rivers to the coastal Arabian Sea. Journal of the Geological Society of India, 43, 255–265. Sharp, A. A., & Stearns, D. E. (1997). Sublethal effects of cupric ion activity on the grazing behaviour of three calanoid copepods. Marine Pollution Bulletin, 34, 1041–1048. Sholkovitz, E. R., van Grieken, R., & Eisma, E. (1979). The major element composition of the suspended matter in the Zaire river and estuary. Netherlands Journal of Sea Research, 12(3/4), 407–413. Sholkovitz, E. R., & Copland, D. (1981). The coagulation, solubility and adsorption properties of Fe, Mn, Cu, Ni, Cd, Co, and humic acids in river water. Geochimica et Cosmochimica Acta, 45, 181–189. Simpson, S. L., Apte, S. C., & Batley, G. E. (1998). Effect of short-term resuspension events on trace metal speciation in polluted anoxic sediments. Environmental Science and Technology, 32, 620–625. Simpson, S. L., Apte, S. C., & Davies, C. M. (2005). Bacterially assisted oxidation of copper sulfide minerals in tropical river waters. Environmental Chemistry, 2(1), 49–55. Skrabal, S. A., Donat, J. R., & Burdige, D. J. (1997). Fluxes of copper-complexing ligands from estuarine sediments. Limnology and Oceanography, 42, 992–996. Spatari, S., Bertram, M., Gordon, R. B., Henderson, K., & Graedel, T. E. (2005). Twentieth century copper stocks and flows in North America: A dynamic analysis. Ecological Economics, 54, 37–51.


253

Springer-Young, M., Piotrowicz, S. R., & Harvey, G. R. (1992). Impact of an episodic event on copper and zinc concentrations and speciation in surface waters of the Gulf of Mexico. Deep Sea Research, 39, 953–964. Strawn, D. G., Palmer, N. E., Furnare, L. J., Goodell, C., Amonette, J. E., & Kukkadapu, R. K. (2004). Copper sorption mechanisms on smectites. Clays and Clay Minerals, 52(3), 321–333. Sunda, W. G., & Huntsman, S. A. (1995). Regulation of Cu concentration in the oceanic nutricline by phytoplankton uptake and regeneration rates. Limnology and Oceanography, 40, 132–137. Syvitski, J. P. M., Vorosmarty, C. J., Kettner, A. J., & Green, P. (2005). Impact of humans on the flux of terrestrial sediment to the global coastal ocean. Science, 308(5720), 376–380. Thompson, M., & Walsh, J. N. (1993). Handbook of Inductively Coupled Plasma Spectrometry (2nd ed.). Chapman and Hall Publishers, pp. 155–156. Tocheva, E. I., Rosell, R. I., Mauk, A. G., & Murphy, M. E. P. (2004). Side-on copper-nitrosyl coordination by nitrite reductase. Science, 304(5672), 867–870. Torgersen, T., Chivas, A. R., & Chapman, A. (1983). Chemical and isotopic characterisation and sedimentation rates in Princess Charlotte Bay, Queensland. Bureau of Mineral Resources Journal of Australian Geology and Geophysics, 8, 191–200. van Hullebusch, E., Chatenet, P., Deluchat, V., Chazal, P. M., Froissard, D., Botineau, M., Ghestem, A., & Baudu, M. (2003). Copper accumulation in a reservoir ecosystem following copper sulfate treatment (St. Germain Les Belles, France). Water, Air and Soil Pollution, 150, 3–22. Virkutyte, J., Velizarova, E., Ribeiro, A. B., & Sillanpaa, M. (2005). Copper and chromium electrodialytic migration in CCA-treated timber waste. Water, Air, Soil Pollution, 160(1–4), 27–40. Vorosmarty, C. J., Meybeck, M., Fekete, B., Sharma, K., Green, P., & Syvitski, J. P. M. (2003). Anthropogenic sediment retention: major global impact from registered river impoundments. Global and Planetary Change, 39, 169–190. Waeles, M., Riso, R. D., Maguer, J.-F., & Le Corre, P. (2004a). Distribution and chemical speciation of dissolved cadmium and copper in the Loire estuary and North Biscay continental shelf, France. Estuarine, Coastal and Shelf Science, 59(1), 49–57. Waeles, M., Riso, R. D., & Le Corre, P. (2004b). Seasonal variations of dissolved and particulate copper species in estuarine waters. Estuarine Coastal and Shelf Science, 62(1–2), 313–323. Walsh, J. P., Nittrouer, C. A., Palinkas, C. M., Ogston, A. S., Sternberg, R. W., & Brunskill, G. J. (2004). Clinoform mechanics in the Gulf of Papua, New Guinea. Continental Shelf Research, 24(19), 2487–2510. Williams, M. R., Millward, G. E., Nimmo, M., & Fones, G. (1998). Fluxes of Cu, Pb, and Mn to the NE Irish Sea: The importance of sedimental and atmospheric inputs. Marine Pollution Bulletin, 36, 366–375. Windom, H., Smith, R., Rawlinson, C., Hungspreugs, M., Dharmvanij, S., & Wattayakorn, G. (1988). Trace metal transport in a tropical estuary. Marine Chemistry, 24, 293–305.

254


Wolanski, E., & Gibbs, R. J. (1995). Flocculation of suspended sediment in the Fly River estuary, Papua New Guinea. Journal of Coastal Research, 11, 754–762. Wolanski, E., Norro, A., & King, B. (1995a). Water circulation in the Gulf of Papua. Continental Shelf Research, 15, 185–212. Wolanski, E., King, B., & Galloway, D. (1995b). Dynamics of the turbidity maximum in the Fly River Estuary, PNG. Estuarine, Coastal and Shelf Science, 40, 321–337. Wolanski, E., King, B., & Galloway, D. (1997). Salinity intrusion in the Fly River estuary, PNG. Journal of Coastal Research, 13, 983–994. Wolanski, E., Gibbs, R. J., Spagnol, S., King, B., & Brunskill, G. J. (1998). Inorganic sediment budget in the mangrove-fringed Fly River Delta, Papua New Guinea. Mangroves and Salt Marshes, 2, 85–98. Zhang, J., Huang, W. W., Liu, S. M., Liu, M. G., Yu, Q., & Wang, J. H. (1992). Transport of particulate heavy metals towards the China Sea: A preliminary study and comparison. Marine Chemistry, 40, 161–178. Zhang, J. (1999). Heavy metal compositions of suspended sediments in the Changjiang (Yangtze) River) estuary: Significance of riverine transport to the ocean. Continental Shelf Research, 19, 1521–1543. Zwolsman, J. J. G., & van Eck, G. T. M. (1999). Geochemistry of major elements and trace metals in suspended matter of the Scheldt estuary, southwest Netherlands. Marine Chemistry, 66, 91–111.


Chapter 7

Modeling the Impact of Tailings and Waste Rock Disposal on the Fly River System Geoff Pickup1, and Yantao Cui2 1

Consulting Geomorphologist, 1538 Sutton Road, Sutton, New South Wales 2620, Australia 2 Consulting Geomorphologist, Stillwater Sciences, 2855 Telegraph Avenue, Berkeley, CA 94705, USA

7.1. Historical Background Sediment transport modeling has a long history at the Ok Tedi. It began in 1979, after reconnaissance investigations predicted significant deposition in both the Ok Tedi and the Fly (e.g., Pickup, 1978). Disposal of tailings and loss of material from the waste rock dumps into the Kawerong and Jaba Rivers from the Bougainville copper mine during the early 1970s had already caused significant environmental and social problems. The Ok Tedi mine was expected to have similar effects, but the likely extent and severity were unknown. More information was therefore sought by both the Papua New Guinea government and the Mining Consortium prior to negotiation of the mining agreement. Sediment transport models had previously been developed for the Bougainville mine (Higgins, 1979; Pickup and Higgins, 1979) and for the Purari River in the Gulf of Papua (Pickup, 1980). It therefore seemed feasible to apply them to the Ok Tedi. Before mine construction began, it was expected that tailings would be held behind a dam on the Ok Ma and it would be possible to build conventional, relatively stable waste rock dumps at the mine site. Only soft and highly weathered overburden was to be disposed of via the river system, although Corresponding author. Tel.: þ61 26238 3427;


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Pickup et al. (1979) anticipated up to 30% loss from the conventional waste rock dumps. The first modeling studies therefore concentrated on the Mine Area Creeks (Ok Mani and Sulphide Creek) and the Ok Tedi. These are steep and highly active systems with braided channels and, in the case of the Ok Tedi, a number of gorge reaches. The early models focused on gravel transport and deposition, as only limited amounts of sand and finer sediment were expected and would pass through the Ok Tedi to reach the Middle Fly. Construction difficulties caused the tailings dam proposal to be abandoned in 1984, and this radically changed the impact of the mine. Tailings were now disposed of into the river system. Large volumes of fine sediment began to accumulate in the floodplain reaches of the Lower Ok Tedi and the upper Middle Fly. Rising water levels and rain forest dieback in these areas had become apparent in the mid-1990s, and the focus of modeling shifted to the sand-bed floodplain channels. Work also began on floodplain and levee deposition and increased potential for flooding. The most recent sediment modeling studies have combined upper and lower river system deposition models with studies of floodplain hydraulics (Cui and Parker, 1999; Pickup and Cui, 2003; Pickup, 2003, 2005) and predict deposition, water level rise, and the lateral extent of flooding. However, attempting to model the full implications of mine waste deposition throughout the river system remains a daunting task, and there are still many gaps in knowledge. Since the first study by Pickup et al. (1979), many different types of sediment transport model have been used at the Ok Tedi. The techniques have varied from empirical estimates based on riverbed sediment particle sizes (Vanoni and Henderson, 1979) to sophisticated scale models (Foster et al., 1984) and two-dimensional hydrodynamic approaches (Hranisavljevic et al., 1996). Some modeling exercises have been successful, while others are less so, often because data on sediment inputs or system characteristics are inaccurate or lacking (Higgins et al., 1987). Indeed, matching model sophistication to data accuracy and availability has always been a problem, and every modeling study has faced significant unknowns. Overall, however, both data and model accuracy have improved over time. In this chapter, rather than looking at each modeling study, we review the range of approaches taken and some of the problems faced. We also present results from a recent sediment modeling study and preview some future activities. The review is not exhaustive and provides a somewhat personalized view of a 25-year-long modeling effort at the Ok Tedi.

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7.2. Challenges in Modeling the Impact of the Ok Tedi Project Predicting the impact of the Ok Tedi mine is one of the world’s most difficult sediment modeling challenges, with almost every kind of fluvial environment and transport process represented in the system. No single model has proved capable of representing all these environments, and many of the processes involved go beyond the limitations of the sediment transport theory. We examine these issues in detail below, but some common problems include: Lack of knowledge about natural sediment loads in the system. While some baseline information was collected for the Ok Tedi before mining started, initial estimates of load varied widely (Higgins et al., 1987). For example, between 1978 and 1985, figures of 1.5–21.4 Mt/year were used for the natural load of the Upper Ok Tedi and 3–30 Mt/year for the Lower Ok Tedi. More recently, natural sediment loading has been treated as a model calibration parameter and varied so that a model receiving only natural load shows limited or zero deposition. Lack of understanding of the long-term, large-scale tectonic and geomorphic processes, such as possible basin subsidence and continued basin response to the Holocene sea level rise. It is possible that the river is still recovering from the Holocene sea level rise (e.g., Dietrich et al., 1999) and continues to aggrade as a natural background condition to mine-related deposition. Basin subsidence, if it exists, provides an additional sediment sink. The response of the river to sea level rise and basin subsidence could be a significant element of the overall sediment budget, given the 500-km-long river reach that has to be modeled. Problems with the sediment transport theory. Existing transport equations do not perform well in the river system. In the mine area and the Upper Ok Tedi, gravel transport equations are pushed to their limit by the very high sediment concentrations. In the backwater zone of the Middle Fly, there are extensive silt deposits on the channel bed, and silt may even travel as bedload. No sediment transport equation handles this situation. Modeling studies that have attempted to validate their results by comparison with observed behavior have usually had to resort to a model calibration to get the models to work. Lack of information on channel changes. Most modeling has been one dimensional and used very simple models of change in channel cross section. Deposition in the upper river system has involved transitions from a single channel to extreme forms of braiding. Erosion in the post-mining period will create terraces and a reversion to a single channel in many reaches. We lack

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even the basic knowledge to replicate these processes in sediment transport models. Flow varies downstream in the Middle Fly as water goes overbank and is added to off-channel water bodies, or as these bodies drain back into the main channel. We know little about these processes. Also, the floodplain usually has too much cloud cover for monitoring using visible/near-infrared monitoring from remote-sensing satellites. We lack a floodplain deposition model apart from an early attempt at modeling reported by Dietrich (2000). Existing theory about floodplain processes is limited, and construction of an empirical model is a daunting logistical task, given the size and variability of the floodplain. Many of these challenges have remained unchanged since the beginning of the Ok Tedi project. Other areas have advanced, including recent developments in transport of fine sediment (e.g., Wright and Parker, 2005a, b). We describe progress and results in the following sections.

7.2.1. Approaches to Upper River System Geomorphology 7.2.1.1. System behavior Coarse sediment is delivered from the waste rock dumps to Harvey Creek and headwaters of Sulphide Creek by mechanical failures, landslides, and debris flows (see Fig. 1.1 of Pickup and Marshall, 2009). In the northern dumps, material is fed into Sulphide Creek down steep slopes and over a waterfall. Below the southern dumps, the upper part of Harvey Creek also has debris flows and landslides, but further downstream, a large alluvial fan that extends into the valley of the Ok Mani has developed. The fan behaves as a debris flow runout zone, but its toe is continuously eroded by the Ok Mani. Although the bed of Harvey Creek has built up by more than 50 m in places since dumping started, it has also experienced major sidewall erosion as water flow has moved to fan edges and undercut adjacent hillsides. This process added an estimated 180 Mt of sediment to the river system between 1990 and 2003. Sidewall undercutting may also have played a role in the Vancouver landslide in the upper reaches of Sulphide Creek, which released about 120 Mt between 1989 and 1992. Sidewall erosion occurs throughout the Mine Area Creeks as laterally migrating braided channels undermine adjacent hillsides. The Ok Mani and lower Sulphide Creek are both highly active braided systems, and it is quite common to see 10 or more individual channels in reaches experiencing rapid deposition. Suspended sediment concentrations


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below the tailings discharge point in the Ok Mani can exceed 100,000 mg/l, and the water–sediment mixture in many channels may flow as a supercritical slurry. The Ok Tedi provides a range of geomorphic environments (Fig. 7.1). Narrow gorge sections alternate with wider reaches, with several channels in upstream reaches. However, there has been only limited long-term deposition because of steep slopes and high discharges. Further downstream, the river has a braided gravel channel, a mixed-load braided and single channel reach, and finally a single sand-bed channel. Deposition has raised the bed of each of the channel systems to the extent that both flow and deposition now regularly encroach onto the floodplain.

7.2.1.2. Representing sediment transport in the Mine Area Creeks Early attempts to represent dump behavior involved application of a simple dump loss rate that did not vary through time. Initially, there was much controversy about what these rates might be, and initial designs involved stable dumps on the northern side of the mine and failing dumps feeding into the Ok Mani. Pickup et al. (1979) used measured dump loss rates from the Bougainville mine but ran a range of optimistic and pessimistic scenarios. Others used more conservative loss rates (e.g., Vanoni and Henderson, 1979). Later studies have used observed dump loss rates and tried to represent the interaction between the debris flow zones below the dumps and the braided systems downstream. In the OkGrav model, progressively developed by Gary Parker since the late 1980s (e.g., Parker and Dietrich, 1993), the river system has debris flow runout zones below the northern and southern dumps. These feed into braided channel reaches covering lower Sulphide Creek, the Ok Mani, and the Upper Ok Tedi above the Ok Mani junction. These feed into the Middle Ok Tedi, which is treated as a gravel reach capable of transporting sand and finer material as wash load. Rock waste is fed into the model at the northern and southern dumps at rates based on observed or projected annual dumping rates. The rock waste is initially partitioned into gravel, sand, and silt fractions based on expected breakdown from the dump site to the base of the debris flow runout zones. Much of the gravel, and some of the sand and silt, is captured in the debris flow runout zones as they aggrade with constant slope (Klohn Leonoff, 1993). The rest of the gravel is delivered to the fluvial sub-reaches immediately downstream. Sediment is also produced indirectly in the form of landslide material as a consequence of the dumping of rock waste. This material includes the

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Figure 7.1: Geomorphic zones of the Mine Area Creeks and Middle Ok Tedi. Upper left: alluvial fan and debris flow runout zone, Harvey Creek, and Ok Mani. Upper right: debris flow runout zone, upper Sulphide Creek. Centre left: a hyperbraided reach on the lower Ok Mani. Centre right: gravel bars in a confined reach of the Middle Ok Tedi. Lower left: a formerly armored and stable braided reach on the Middle Ok Tedi now experiencing major deposition. Lower right: the dredging operation at the downstream end of the Middle Ok Tedi in what was formerly the gravel–sand transition zone. Photos: Barrie Bolton, Stuart Miller, and Geoff Pickup.


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Vancouver slide on the upper reach of Sulphide Creek, which added about 120 Mt of material between 1989 and 1992. It also includes sidewall erosion in upper Harvey Creek arising from undercutting by streams at the edge of the Harvey Creek fan. Observed and predicted schedules for this delivery are occasionally updated based on new information from consultants working for the mine. The initial breakdown into gravel, sand, and silt fractions is assumed to be identical to that for rock waste. The debris flow runout zones are assumed to aggrade at a constant slope of 8%, based on field measurements. The fractions of gravel, sand, and silt captured in this zone are also based on field measurements. The area of deposition expands as the bed aggrades and the river valleys widen. The downstream ends of the debris flow runout zones are constrained by waterfalls or a shift to fluvial sediment transport as slope decreases downvalley and water discharge increases. In the OkGrav model, it was assumed that the debris zones aggrade and degrade at the same vertical rate as the uppermost node of the fluvial zone. After the mine ceases operation, degradation processes will be driven from downstream by the fluvial system. Degradation of the debris zones is then adjusted to keep pace with incision in the fluvial zones downstream.

7.2.1.3. Modeling braided gravel channel systems in the Ok Mani, Sulphide Creek, and the Ok Tedi The first attempts to model sediment transport in the Mine Area Creeks and the Ok Tedi used models that had been developed and calibrated for transport of mine waste on the Kawerong and Jaba Rivers in Bougainville (Higgins, 1979; Pickup and Higgins, 1979). The Bougainville experience showed that it was not feasible to use standard sediment transport equations, and some form of direct or indirect model calibration was necessary. Problems were also experienced in obtaining sufficient topographic data to adequately represent system geometry, and eventually, two approaches evolved (Pickup et al., 1979; Maunsell and Partners, 1982). Where detailed topography was available, notably the Mine Area Creeks and the Upper Ok Tedi, the system was divided into short reaches, and sediment routing was applied. This involved calculation of a reach-by-reach sediment mass balance that is progressively updated after each time step. Deposited sediment is allowed to build up the bed in each reach and change river slope. This process feeds back to and affects the transport rate, continuously changing system geomorphology. Where topographic data were sparse, a ‘‘representative reach’’ approach was taken in which short reaches in different sections

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of the river were surveyed in detail. A sediment transport equation is then used to define sediment outflow for these reaches and any excess deposited upstream. Slope and channel geometry remain unchanged in the representative reaches throughout this process. Since the late 1980s, most work on the upper river system has used the OkGrav model, which applies a sediment routing approach, although some reaches are very long for this procedure. OkGrav has gone through many iterations, and the current version operates as follows. The river is assumed to be steep enough to allow quasi-normal flow, so backwater equations are not used to predict flow velocities and slope. Also, rather than using daily discharges as input, the flows are computed for a number of points on a flow duration curve. This curve is specified for each node along the system but assumed to be invariant in time. The model thus cannot distinguish between wet and dry years. The model focuses on gravel transport. It assumes three sources of gravel: natural gravel, gravel derived from rock waste from the mine, and gravel derived from landslide material. The model also tracks mine-derived sand and silt. Sand and silt derive from rock waste, slide material, and tailings. An additional source of sand and silt is abrasion (see below). Gravel transport is calculated using the Parker (1990) surface-based transport relation. It treats sediment mixtures ranging from 2 to 512 mm on a fractional basis. Three layers are assumed in the model: a bedload layer, a bed surface (active) layer, and a substrate layer. The average transport rate and transport grain size distribution for a year is based on calculations from the flow duration curve. The gravel-sized rock waste is relatively easily abraded. The products of abrasion are computed to be silt and sand but mostly the former. The coefficient of abrasion is assumed to be relatively large near the mine and relatively smaller farther downstream to reflect the gradual dominance of resistant gravel as the friable material is ground out. Although the model allows for different abrasion rates for several lithologies, only two lithologies have been used: harder natural gravel and softer mine-derived gravel. The basis for the abrasion calculations is given in Parker (1991a, b). Within the Mine Area Creek fluvial zones (Ok Gilor–Ok Mabiong–Ok Tedi and Ok Mani), the bed is allowed to aggrade or degrade between any pair of nodes, according to whether or not the gravel supply exceeds the sediment delivery. The width of deposition is divided into a channel width that is used to compute sediment transport and a wider valley width over which aggraded sediment is allowed to deposit uniformly. This configuration approximates the reworking of the valley flat by a braided or wandering gravel-bed stream. The channel widths were determined from aerial


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photography and adjusted in the ‘‘zeroing’’ procedure discussed below. Valley geometry was assumed to be V-shaped, so that valley width increases with bed aggradation. This was particularly important for the Ok Mani, which is now an order of magnitude wider than the pre-mine state. Valley shape was obtained from topographic maps. The Mine Area Creek deposition is assumed to consist gravel particles, but sand and some silt fill the pore spaces as the bed aggrades. This material is released as the bed later incises into its own deposits. Exactly the same algorithm is used for the Middle Ok Tedi between the Ok Mani junction and Konkonda, with the exception that valley width is not allowed to change according to bed height. Because the river later degrades into its own deposits upon mine closure, it is necessary to store in memory both the thickness of the deposit and the grain size distribution. The stored grain size distributions consist averages of the deposit over a specified thickness. Sand and silt deriving directly from rock waste, slide material, and tailings are allowed to deposit in or be eroded from the Mine Area Creeks and the Upper Ok Tedi. They are neither deposited in nor eroded from the Middle Ok Tedi. The sand and silt load at the Ok Tedi–Ok Mani junction is delivered directly to Konkonda (gravel–sand transition) with no intervening storage. The sand and silt produced by abrasion in the Middle Ok Tedi is also delivered directly to Konkonda with no storage. This assumption was reasonable in the early days of mining, but there is now about 15–30 Mt of stored sand between Ningerum and Konkonda. It therefore proved necessary to extend the sediment transport model for the sand-bed reach of the Middle Fly upstream to account for this material. Models of bed evolution are prone to large errors if used without prudent adjustment. The model was adjusted in the following way. Assuming that no mine was ever built, gravel infeed and channel width were adjusted so as to predict a river system that changes a negligible amount over the planned lifetime of the mine. The natural gravel load was determined in this way. This load is very small compared with sediment delivery from the mine. 7.2.1.4. OkGrav model calibration/validation Most of the field data for model validation came from Marshall (2001). They include:

Sediment deposition history in the Ok Mani and Harvey Creek. Erosion in Sulphide Creek between 1996 and 2000. Erosion in the Upper Ok Tedi between 1996 and 2000. The depositional history at selected cross sections.

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The sediment deposition history in the Ok Mani and Harvey Creek is presented in Fig. 7.2. The model closely predicts the observed sediment deposition. The amounts of erosion in Sulphide Creek and on the Upper Ok Tedi between 1996 and 2000 are also closely predicted (Figs. 7.3 and 7.4). The depositional histories in cross sections TED44, TED50, TED54, and TED56 are presented in Fig. 7.5. Comparison between the model results and field data indicates that the model correctly predicts the general trend and the magnitude of sediment deposition in three of the four cross sections, that is, TED44, TED50, and TED56. The model did not reproduce the general trend of bed degradation between 1999 and 2001 for cross section TED54. This discrepancy may be caused by the fact that field data are for thalweg elevation while the model results represent the average bed elevation. A closer inspection of the survey data for TED54 revealed that only a few surveys covered the entire cross section, so the attempt to validate the model against average bed elevation failed. Also, the cross section is close to a valley constriction that may have resulted in localized scour at times. Field data at TED50 and TED56, which are located approximately 9.8 km upstream and 4.8 km downstream of TED54, respectively, all show

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Figure 7.3: Predicted and estimated sediment erosion in Sulphide Creek between 1996 and 2000. Data were estimated from digital elevation models and differ slightly from the values in Marshall (2001).

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Figure 7.5: Predicted and measured change in bed elevation of the Ok Tedi at cross sections TED44, TED50, TED54, and TED56. The predicted values are for average bed elevation; the field data are for thalweg elevation.


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continued aggradation between 1999 and 2001. With this in mind, we suggest that the discrepancy for cross section TED54 may be discounted.

7.2.2. Model Approaches to the Lower River System 7.2.2.1. System behavior The Lower Ok Tedi and much of the Middle Fly have a sand-bed channel that is partly confined by terrace remnants in upper reaches but is free to meander over much of its length. The lower Middle Fly is affected by backwater from the Strickland and by tides, especially at low flow. The backwater reach has silt on the bed for much of the time but still transports sand under some conditions. There is frequent flooding when flow goes overbank, but the floodplain does not always act as a conveyance system. Instead, standing water on the floodplain confines sediment-transporting flow to the channel for much of the time. Sediment load in the Lower Ok Tedi and beyond has been reduced by dredging since 1998. The dredging operation extracts more than 15 Mt/year on average, most of which is sand.

7.2.2.2. Characteristic approaches: Lower Ok Tedi and Middle Fly In the early stages of the Ok Tedi project, little was known about the geomorphology of the Fly River system beyond the results of the CSIRO land systems survey (Blake and Ollier, 1971; Paijmans et al., 1971). Given this lack of information, two basic approaches were used to model the lower river system: in the Lower Ok Tedi and the Upper Middle Fly, a representative reach approach was taken, with reach nodes surveyed at Ningerum, Konkonda, and Kuambit. Transport rates were calculated using an early version of HEC-6 (Hydrologic Engineering Centre, 1992). Further downstream, it was assumed that mine waste would behave in the same way as natural load. Existing bed material sizes were then used to predict deposition, assuming that mine-derived sediment finer than the material on the bed would pass downstream (Pickup et al., 1979; Vanoni and Henderson, 1979). Mine-derived sediment that was of the same size as the bed material would either be transported or deposited depending on whether the river had sufficient capacity to transport the additional load. This approach is likely to underestimate deposition, especially where large increases in sediment load are involved. However, at this stage of the project, tailings were to be stored behind a dam, so only a limited increase in load was expected.

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Later attempts to model the river were based on more extensive data. While many attempts have been made, two are of particular note since they illustrate widely differing approaches to lower river system modeling and influenced later approaches. Both, however, were still limited by the lack of data on river system geomorphology. Klohn-Crippen (1996) applied an early version of the MIKE11 model (Danish Hydraulic Institute, 1996) to the Lower Ok Tedi and the Middle Fly. MIKE11 is a one-dimensional hydraulic and sediment model capable of calculating water surface profiles as well as sediment transport and deposition. Channel slope and geometry were constructed on the basis of eight measured cross sections, and a number of scenarios were run, including various dredging rates and several major landslide scenarios. Sediment inputs from the upper river system were calculated using OkGrav. Little information was available to validate the model. The basic approach used by Klohn-Crippen (1996) has been followed by most of the modeling studies carried out since then. MIKE11 predicted extensive bed level rise throughout the system but with significant recovery within the Middle Fly sand zone within 20–40 years of mine closure. Further downstream, the bed level increase was greater than that predicted in more recent modeling studies but with a shorter recovery time. However, backwater effects on the lower Middle Fly from the Strickland were not allowed for. Floodplain inundation, based on river water surface profiles and estimated floodplain height, was also calculated and found to increase downstream over time. However, once again, there was significant recovery in the upper part of the system within several decades after mine closure. A second study in 1996 applied a hydrodynamic approach to river system modeling using the two-dimensional RMA hydraulic and sediment model (King, 1996). Hranisavljevic et al. (1996) constructed a two-dimensional finite element grid and attempted to model flow and sediment transport both in the channel and on the floodplain. The grid consisted of a fine mesh covering the channel and the meander belt and a coarser mesh covering the outer floodplain area. A trapezoidal channel was assumed, and topographic data for the floodplain came from 35 east–west laser profiles flown between Kuambit and a point just downstream of Everill Junction. While reasonable estimates of in-channel deposition were obtained for the Ok Tedi, results were less satisfactory for the Middle Fly. Estimates of floodplain deposition were also made, and while the broad spatial pattern may look reasonable, it is clear that the lack of topographic data limited what could be achieved. While the two-dimensional model was an interesting experiment, its value was limited by the lack of data for calibration and validation at the time.


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Also, the model did not adequately reproduce flow patterns on the floodplain. Much of the floodplain is occupied by large bodies of standing water during flood times and by inflow and outflow to and from off-channel water storages. The two-dimensional model shows floodplain flows parallel to the channel or across meander loops. These patterns occur on the Fly but are not the dominant form. Floodplain flow patterns are also made complex by the presence of pre-Holocene terrace remnants, which may divert water flow and isolate some areas from the adjacent channel. The topographic data used to describe the floodplain did not capture many of these features. Data availability has improved greatly since the 1996 study, but even now, there are insufficient data to justify going beyond a one-dimensional model of the river channel. There is also still a shortage of information on floodplain topography, flow patterns, and hydraulic roughness, which makes it difficult to justify the two-dimensional modeling needed to represent floodplain behavior. Subsequent modeling efforts have used a onedimensional approach. Parker et al. (1996) developed the customized OkPlain model to simulate the sand-bed reach of the Ok Tedi between Konkonda and D’Albertis Junction. Again, the upstream sediment supply was produced with the OkGrav model, and OkPlain simulates only the transport of fine sediment downstream of the gravel-bed reaches. OkPlain employed a standard backwater formulation for flow calculation and the Brownlie (1981) bed material load equation for sediment transport capacity calculation. One of the distinctive features of OkPlain is that it has an ad hoc floodplain deposition module to simulate the amount of overbank sediment deposition parameters that can be calibrated based on field observations. In addition, the model tracks different types of sediment by size fraction. Experience with the OkPlain model indicated that setting the downstream boundary condition at D’Albertis Junction is inadequate because in-channel sediment deposition continues to progress downstream. With that, the model became OkFly and was expanded further downstream, and the lower boundary was set at Obo just upstream of Everill Junction. The model also included the Upper Fly River between D’Albertis Junction and Kiunga to account for water and sediment supply (Cui and Parker, 1999). OkFly results show river-wide aggradation, extending into the Upper Fly. The main depositional wedge forms in the Ok Tedi and progrades downstream during mine life and for many years after mine closure. The general conclusion from this modeling is that aggradation and floodplain inundation will continue to increase in the Fly River even after the mine closure as the sediment wedge progresses downstream, and that recovery of the system will be slow.

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OkFly was used to evaluate various management scenarios before the completion of the most recent modeling efforts. Examination of dredging with OkFly indicates that the operation will result in some recovery in the sand-bed reach of the Lower Ok Tedi and that the effect will gradually shift downstream into the Middle Fly.

7.2.2.3. Lower Ok Tedi and Middle Fly modeling with HEC-6: The 2003 study HEC-6 (Hydrologic Engineering Centre, 1992) is a one-dimensional openchannel flow numerical model designed to predict changes in river profiles resulting from scour and deposition over periods of years. The model was developed by the US Army Corps of Engineers and has been in use for more than 20 years. HEC-6 divides the river into a series of reaches whose geometries are described by measured cross sections. A continuous flow record is partitioned into a series of steady flows of variable discharge and duration. A water surface profile is calculated for each flow providing information on water surface elevation, flow velocity, energy slope, width, and depth at each cross section. Potential sediment transport rates are calculated at each cross section from these flow parameters and a sediment mass balance obtained for each reach, based on sediment inflow and outflow. Each cross section is then changed depending on the amount of scour or deposition. The flow computations proceed to the next flow in the sequence and are repeated with the updated channel geometry. Sediment calculations are performed for each particle size fraction in the load and allow for both sorting and bed armoring. HEC-6 represents a river system by a main stem plus a set of tributaries. Water and sediment flow in at the upper end of the model with outflow at the lower end. Any difference between sediment inflow and outflow is accounted for by erosion or deposition. Inflow and outflow may also occur at tributary junctions. The layout used in this study is shown in Fig. 7.6. Inflow of mine waste at the upper end of the system was calculated using sediment-rating curves derived in OkGrav. However, OkGrav does not allow for the sand deposition that has occurred in the Konkonda–Ningerum reach, which may include 15–30 Mt of material. This was accounted for by extending HEC-6 upstream to overlap part of the lowest reach modeled in OkGrav. HEC-6 then produces about 25 Mt of sand deposition upstream of Konkonda. Inflows of natural load must also be provided for the main stem and the various tributaries. While various estimates have been made of the natural


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Figure 7.6: HEC-6 model layout showing main inflows and outflows. rate of sediment delivery to the Lower Ok Tedi and from the Upper Fly (Higgins et al., 1987), amounts vary substantially. In the absence of anything better, sediment inputs from the Ok Mart and the Upper Fly were taken from GHD (1999). However, a 4-km reach of the Upper Fly was used as a buffer zone between Kuambit and the Upper Fly sediment input point in HEC-6 to allow for backwater. The natural load of the Ok Tedi was estimated during model ‘‘zeroing’’ runs (see below) in which natural sediment input was gradually increased to the point where there was little or no net scour in the 1984 reconstructed profile over a 13-year period. Sediment load particle size data came from riverbed samples collected before mine construction began (Pickup et al., 1979). Channel cross sections for the Lower Ok Tedi and the Middle Fly came from survey data provided by A. R. Marshall. The December 1997/March 1998 survey was used as a baseline while the March 2002 survey provided an endpoint for the model calibration/validation runs. The 1997 survey was also used to reconstruct the pre-mining river geometry. Roughness coefficients for flow profile calculations were derived by comparing model results with observed water surface profiles (Pickup, 2001).

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Flow data for modeling may be in the form of a flow duration curve or a sequence of discharges. All model runs described in this chapter used a sequence of observed daily discharges for 1985–2002. Discharges for future periods were generated by repeating this record.

7.2.2.4. HEC-6 model calibration/validation HEC-6 offers a choice of sediment transport equations for clay, silt, sand, and gravel. There are also different methods for dealing with erosion and deposition of material in the silt and clay fractions. Most other parameters can be directly measured or calculated from stream, gauging data, and bed material samples. Once transport equations and other parameters have been selected, the model should be validated from observed data where possible. On the Ok Tedi and the Middle Fly, there are enough data to allow the following tests of model accuracy: Model ‘‘zeroing’’ using a crude reconstruction of riverbed levels in late 1984 from a small number of long-term cross sections, including Konkonda, Kuambit, Wygerin, and Obo. The aim of model zeroing is to show that the river does not experience significant erosion or deposition over time with estimated natural sediment loads. It may also be used to estimate natural sediment loads where they are uncertain. A test of whether the model can reproduce 1985–1997 deposition on the Lower Ok Tedi and the Middle Fly, using the reconstruction of 1984 riverbed levels. A test of whether HEC-6 can reproduce the complex pattern of erosion and deposition that developed after the introduction of dredging at Bige on the Ok Tedi in 1998. Since then, more than 120 cross sections have been surveyed to a very high standard, up to twice a year, along the Lower Ok Tedi and the Middle Fly. 1997–2002 included a drought and a very wet period, both of which affected river behavior and created a challenging test of the model. The first and second tests of model accuracy are not particularly rigorous because only eight cross sections can be used to estimate changes over more than 400 km of river. The third test provides a good indication of what level of accuracy the model can achieve but covers only a short time period. Model calibration runs showed that none of the sand transport equations in HEC-6 produced transport rates great enough to move sand down into the


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Middle Fly in sufficient quantity to reproduce observed deposition rates. Instead, deposited material built up in the Lower Ok Tedi. The greatest concentration of deposition was at the upper end of the reach between Iogi and Konkonda and produced increases in riverbed and water levels far higher than those observed in the reach. Underestimation of transport rates is common when using sediment transport equations in heavily laden rivers, and models frequently require calibration. It is possible to calibrate HEC-6 by adding user-derived sediment discharge-rating curves for each particle size range used in the model. However, insufficient data are available to develop suitable empirical curves for the Fly. An alternative approach to calibrating HEC-6 is to rescale the time interval used in the model, which, in effect, increases the transport rates and moves sediment down the system more quickly. This approach proved effective, and the model was run using the Yang transport equation speeded up by a factor of 8. Model zeroing and calibration runs produce close agreement between modeled and observed river behavior. Model calculations in the zeroing run (Fig. 7.7) show slight erosion immediately below Iogi and slight deposition in the Lower Ok Tedi. The upper Middle Fly above Wygerin is close to being stable, but downstream, deposition gradually increases with both distance and time, with about 60 Mt accumulating in the Manda–Obo reach. This is the Strickland backwater zone and, in both pre-mining and current riverbed sediment surveys (see Bolton et al., 2009), showed a marked reduction in the amount of medium sand present. This is consistent with a river experiencing deposition. The deposition in the first 50 km at the downstream end of the lower Middle Fly is affected by the model boundary condition and may be inaccurate. The overall pattern of deposition in the Middle Fly resembles a deposition sequence suggested by Pickup (1984). In this scheme, the downstream edge of the Middle Fly sand zone, which extends from D’Albertis Junction to Manda, slowly moves downstream as a front, into the backwater zone. Behind this front, the bed slowly rises to maintain slope, but this effect dissipates upstream. The vertical striping shows the effect of local variability in the river channel characteristics. This variability takes the form of channel openings, where sediment accumulates, and constrictions, which hold back material in upstream reaches but have limited local deposition. The vertical line marked ‘‘A’’ shows an extreme example of this behavior. The openings and constrictions are often associated with outcrops of resistant ‘‘red beds,’’ where the pre-Holocene floodplain survives in elevated terrace remnants. The vertical striping may be broken up into repeating cells of higher and lower deposition (e.g., the middle part of the vertical line marked ‘‘B’’).

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An apparent rise in the level of the Strickland, backing up the lower Middle Fly and virtually halting meander migration in the lower Middle Fly because of lower bank shear stress values associated with reduced slope. Possible subsidence associated with a fault that crosses the Middle Fly floodplain. This may explain why terrace remnant elevations decrease down the Middle Fly but rise again in the Lower Fly (Pickup, 2001). The Middle Fly channel levee system may be up to 7 m higher than the surrounding floodplain.

Estimates of the aggradation rate vary, but Dietrich et al. (1999) suggest a rate of 0.1–1 mm/year for the zone away from the channel, 1–10 mm/year for filling of meander cutoff oxbows, and perhaps 5 mm/year for the channel system. However, the channel system aggradation rate may be lower because some sand is transported out of the channel by overbank flow and through tie channels. These rates may be conservative. For example, a detailed stratigraphic study of Magela Creek in the uranium province of Australia’s Northern Territory shows that the whole floodplain has risen at an average rate of about 4 mm/year since the post-glacial rise in sea level ended 5,000–7,000 years ago (Clarke et al., 1992). Magela Creek is much smaller than the Fly but would have a similar history of post-glacial sea level rise. It is also backed up by the much larger East Alligator River, so the situation is analogous to the Middle Fly and the Strickland. However, the Magela Creek catchment is much flatter and more geologically stable than that of the Fly, so delivered sediment load would be less. It therefore seems reasonable to expect a higher natural rate in the Middle Fly. In fact, the 70-year modeling run suggests a natural accumulation of about 10 mm/year if all deposited sediment stays in the channel. If 30% is lost to the floodplain, the rate comes down to 7 mm/year, which is close to the Dietrich et al. (1999) estimate of 5 mm/year. This suggests that, though our estimates of deposition under natural sediment load are high, they are not unreasonable. The reconstructed 1985 river channel therefore produces a reasonable pattern of modeled river behavior. After model zeroing, a number of calibration runs were carried out using model runs with natural load, tailings, and waste rock input for 1985–1997. There are two major sources of uncertainty in these model runs. First, the 1984 bed reconstruction may contain substantial errors. Second, output of sand and silt from OkGrav may not always be accurate since there are not enough data to calibrate sand storage and transport at the downstream end of the model. In spite of these uncertainties, HEC-6 should still reproduce

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the general pattern of deposition in the river. The water surface profile should also change to reflect rising bed levels. The results are good by river modeling standards. Rising bed levels upstream of the 450-km point are closely reproduced. The model is slightly less successful on the Lower Ok Tedi, and the 1997 bed levels close to D’Albertis Junction (429 km) are underestimated by about 1 m. There is also a tendency to underestimate 1997 bed levels on the upper part of the Middle Fly between 300 and 410 km, but the average is less than 0.5 m. Given uncertainties in the input data and less-than-optimal cross section spacing, this is an acceptable degree of discrepancy. Bed level change in the 0- to 300-km reach (lower Middle Fly) largely consists profile smoothing as holes are filled in and some constrictions are reduced by local scour. There is also a buildup of material close to the downstream end of the model where the backwater effect from the Strickland is greatest. While these results seem reasonable, available data are not good enough for a convincing test of model performance. Little is known about tributary inflows and outflows in this reach, and data from only three cross sections were available for the 1984 river reconstruction. Overall, however, results seem reasonable. The pattern of observed and modeled changes in the water surface profile is broadly similar (Fig. 7.8). However, there are some differences in particular reaches. The modeled water surface profile above 450 km is very close to the profile calculated from 1997 cross sections (labeled as 1997 Observed in Fig. 7.8). In the 300- to 450-km reach, it is about 1 m too low. A difference of this magnitude over 150 km is not great, given that bed levels have risen by about 4 m. Below 300 km, the profiles are very similar. Comparison of observed and modeled deposition in the 1985–1997 and 1985–2002 calibration periods shows reasonably good results, given that the reconstructed 1985 profile could contain errors. However, changes to the upper 300 km of the river system upstream of Mabaduam are modeled more closely than the lower river. Also, there seems to be a tendency to underestimate deposition in the Fly based on the 2002 profile. A more detailed test is to compare modeled changes between 1997/1998 and 2002 with observed changes from cross section surveys (Fig. 7.9). This is quite a severe test of model performance because the cross section surveys cover a period with both wet and dry phases as well as more average years. Also, sediment inputs from OkGrav would not represent the wet and dry periods very well because it uses discharges derived from long-term average flow duration curves. The 1997/1998–2002 comparisons show that the impact of dredging upstream of the 400-km point is reproduced very closely. However, the


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Figure 7.9: Observed and modeled results for 1997/1998–2002. The upper graphs show changes in bed level. The lower graphs show water surface profiles. flows since 1984 and possibly 1972, according to Fly River gauge height graphs contained in SMEC (1978). Water surface elevation results are closer to observed river behavior than the bed level simulations. The pattern of change between 1998 and 2002 is almost identical, and by 2002, the profiles are almost identical over the whole of the river. This is a very good result, given that we are attempting to predict changes in elevation of only a few meters over almost 500 km of river.

7.3. Predictions of Future Deposition, Water Level Change, and Inundation Assuming mine closure in 2010 and dredging at the current rate, patterns of deposition and water level change are shown in Figs. 7.10 and 7.11.


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Figure 7.10: Predicted deposition of natural and mine-related sediment in the Lower Ok Tedi and the Middle Fly between 1985 and 2064, assuming mine closure in 2010 and dredging at the current rate. At its simplest, the pattern of deposition may be seen as a flow of material with a wave front that gradually moves down the system over time. This behavior shows as a prominent diagonal break between the green (little or no deposition) feature in the lower left of the image and the red and yellow (greater deposition) zone. The flow attenuates with distance and with time once mining ceases. It also breaks up into separate cells in the lower part of the Middle Fly but leaves behind long-term deposits in many reaches. Initially, heavy sediment accumulation occurs in the upper part of the Ok Tedi between Iogi and D’Albertis Junction. This deposition is reduced by

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Figure 7.11: Predicted water level change between 1985 and 2064 in the Lower Ok Tedi and the Middle Fly, assuming mine closure in 2010 and dredging at the current rate. dredging and natural erosion after mine closure. By about 2060, much of this deposition has cleared, and some of the irregularities in the bed that were filled during the lead-in period to stabilize the model begin to reappear. The Lower Ok Tedi holds material longer, and deposition persists in some reaches to at least 2060. The bulk of deposition initially occurs on the Middle Fly in the 240- to 420-km reach. Some, but not all, of this material shifts downstream after mine closure. There is some clearing of deposited material from the upper


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70–100 km after about 2040, but deposition increases further downstream and shows little sign of clearing by 2060. There are local buildups of sediment in the lower part of the Middle Fly after about 2020. These show as short, vertical red stripes in the top left-hand part of the figure. There is also a prominent scour zone marked ‘‘C,’’ where a scour hole buried during the pre-mining lead-in period reappears after 2020. While modeled behavior in the lower reaches of the Middle Fly appears logical, little is known about water inflows and outflows in this reach, so questions of accuracy remain. The downstream end of the system is also affected by the assumption of a stable-rating curve at Obo as a boundary condition. There is no evidence of rating shift between 1987 and 2001 (Pickup, 2001), but data quality is poor. Water level changes tend to be more regular than raw deposition data because rises in water level affect upstream reaches and smooth out local increases in bed level. Water level increase is greatest at the upstream end of the system but decreases rapidly after dredging and mine closure. Further downstream, water levels continue to rise until about 2060 when the system stabilizes. Water level changes decrease with distance downstream. However, by 2060, they are still significantly higher than the pre-mining situation over most of the Middle Fly and all of the Lower Ok Tedi. 7.3.1. Deposition on Channel Levees and the Floodplain Predicting deposition rates on the floodplain remains a problem for sediment modeling. Deposition occurs on the floodplain surface, in the tie channels that connect the main river to flooded meander cutoffs, in the cutoffs themselves, and on main channel and tie channel levees. Using early data on copper distribution in sediments, Dietrich (2000); Dietrich and Day (2004) has shown that the bulk of deposition occurs on main channel and tie channel levees and decreases exponentially with distance from the channel across the floodplain surface. There is also the potential to increase deposition in the off-river water bodies. However, as Day and Associates (1996) notes, most are not under threat of infilling. Indeed, Day estimated that the larger off-river water bodies might lose 1–2% of capacity while smaller ones might lose up to 10% over the life of the mine. These calculations apply to oxbow lakes in meander cutoffs rather than the much larger blocked valley lakes. Rowland et al. (2005) looked at deposition rates in off-river water bodies through extension of tie channels and their levees into cutoffs. They conclude that tie channel extension is the dominant process of off-river water body

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infilling and that rates have increased 6–17 times since 1980. They also concur with Day and Associates (1996) that most off-river water bodies are not in danger of infilling. The pattern of floodplain deposition can be inferred from airborne gamma ray data acquired during drought [see Pickup and Marks (2000, 2001) for a description of how gamma ray emissions can be linked to deposition]. Figure 7.12 shows a typical pattern from a meander on the lower Middle Fly with the gamma ray data in the left-hand image and panchromatic LANDSAT coverage of the same area on the right. The concentration of

Figure 7.12: Total gamma emissions from an airborne gamma ray survey of meanders on the lower Middle Fly during drought conditions when the floodplain was virtually dry. Emissions are highest in the red areas and decrease through yellow, green, light blue, dark blue, and purple. The LANDAT ETM image on the right shows ground features in more detail. High emissions are thought to indicate freshly deposited mine sediment. The low-emission areas behind the levees indicate sediments with a high organic content, but some gamma ray emission may be blocked by the presence of soil–water in these areas.


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7.4. Future Paths The modeling techniques currently in use are close to their limits of accuracy, given available input data, sediment transport technology, and capacity for model calibration. Future advances are most likely to come from new datasets that remove bottlenecks and open up new opportunities for

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prediction. There will also be changes in emphasis as the need for prediction of system behavior after mine closure increases. In the upper river system, further progress is limited by the lack of detailed topographic data showing deposition rates over time for the Upper and Middle Ok Tedi. OkGrav is reasonably well calibrated for deposition but largely untested for river behavior after mine closure when the system will begin to scour. This process may leave sections of the current riverbed as terraces, which will be exposed to more rapid weathering than at present. Future modeling activities in the upper river system are therefore increasingly likely to concentrate on post-mining river behavior. In the lower river, any improvement to sediment transport calculations is likely to be incremental. Information about water losses to the floodplain and backflow to the channel was a significant data gap in the 2003 modeling exercise. What lower boundary condition to use in modeling is also a problem, given the complex interaction between the Fly and the Strickland and tidal effects. Some of these issues have been addressed in a recent study of floodplain hydraulic behavior (see Pickup, 2009). However, the improvements have yet to be incorporated in a sediment transport model. On the floodplain, there is still no satisfactory approach to predicting the amount and location of deposition. While we know what the spatial pattern is and the general form it takes, a predictive model will need extensive calibration from observed data. Airborne gamma ray surveys provide the easiest method of acquiring these data but can only be usefully undertaken on rare occasions when the floodplain is dry.

REFERENCES Blake, D. H., & Ollier, C. D. (1971). Alluvial plains of the Fly River, Papua. Zeitschrift fur Geomorphologie Supplementband, 12, 1–17. Bolton, B. R., Pile, J. L., & Kundapen, H. (2009). Texture, geochemistry and mineralogy of sediments of the Fly River System. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 51–112. Brownlie, W. R. (1981). Prediction of flow depth and sediment discharge in open channels. Report No. KH-R-43A, W. M. Keck Laboratory of Hydraulics and Water Resources, California Institute of Technology, Pasadena, California, USA, 232 pp. Clarke, R. L., Guppy, J., Mahon, D., McBride, P., & Wasson, R. J. (1992). Late quaternary evolution of the Magela plain. In: Wasson, R. J. (Ed.). Modern Sedimentation and Late Quaternary Evolution of the Magela Creek Plain.


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Australian Government Publishing Service, Canberra, pp. 81–157. Supervising Scientist for the Alligator Rivers Region Research Report 4. Cui, Y., & Parker, G. (1999). Sediment transport and deposition in the Ok Tedi-Fly River system, Papua New Guinea: The modeling of 1998–1999. St. Anthony Falls Laboratory, University of Minnesota, 27 pp. Danish Hydraulic Institute (1996). MIKE 11. A microcomputer based modeling system for rivers and channels. Danish Hydraulic Institute. Day, G., & Associates (1996). Particle size and shape characteristics of deposited sediments in the Middle Fly River and sediment deposition rates in the tie channels and off-river water bodies. Volume 1. Ok Tedi Mining Ltd., Environment Department. Dietrich, W. E. (2000). Quarterly and fourth monthly report – Middle Fly sedimentation project. Department of Earth and Planetary Science, University of California, Berkeley, 51 pp. Dietrich, W. E., & Day, G. (2004). Rates and patterns of floodplain sedimentation, middle fly floodplain (1985–1994). Presentation at the Sediment Transport Model Workshop, Cairns, Australia. January, 2004. Environment Department, OK Tedi Mining Ltd. Dietrich, W. E., Day, G., & Parker, G. (1999). The Fly River, Papua New Guinea: Inferences about river dynamics, floodplain sedimentation and fate of sediment. In: A. Miller, & A. Gupta (Eds). Varieties of Fluvial Form. Wiley, New York, pp. 345–376. Foster, D. N., Cox, R. J., Miller, C. A., & Wallace, B. C. (1984). Ok Mani diversion scheme – weir, intake channel and tunnel. University of New South Wales Water Research Laboratory Technical Report 84/07, 42 pp. GHD (1999). Hec6 model for Ok Tedi and Fly River. Ok Tedi Mining Ltd. Hranisavljevic, D., King, I. P., Chadwick, M. J., Nittim, R., & Cox, R. J. (1996). Ok Tedi and Fly Rivers. Hydrodynamic and sediment transport modeling. University of New South Wales Water Research Laboratory Technical Report 96/15, 59 pp. Higgins, R. J. (1979). Sediment transport in a river with high induced load. Civil Engineering Transactions, Institution of Engineers Australia, CE21, pp. 111–117. Higgins, R. J., Pickup, G., & Cloke, P. S. (1987). Estimating the transport and deposition of mining waste at Ok Tedi. In: C. R. Thorne, J. C. Bathurst, & R. D. Hey (Eds). Sediment Transport in Gravel Bed Rivers. Wiley, Chichester, UK, pp. 949–976. Hydrologic Engineering Centre (1992). HEC-6 scour and deposition in rivers and reservoirs. Users manual, US Army Corps of Engineers. King, I. (1996). Program Documentation RMA-2: Finite Element Model for Flow Estimation in Rivers and Streams. Resource Management Associates, Suisin, CA. Klohn-Crippen (1996). Waste management study. Ok Tedi and Fly River model report. Ok Tedi Mining Ltd., 2 vols. Klohn Leonoff (1993). Ok Mani diversion and waste storage. Ok Tedi Mining Ltd., Appendix IV. Marshall, A. R. (2001). Upper Ok Tedi sediment storage analysis – November 2000. Environment Department, Ok Tedi Mining Ltd., 25 pp.

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Maunsell and Partners Pty. Ltd. (1982). Ok Tedi environmental study. Report to Ok Tedi Mining Ltd., Tabubil, 7 vols. Paijmans, K., Blake, D. H., Bleeker, P., & McAlpine, J. R. (1971). Land Resources of the Morehead-Kiunga Area, Territory of Papua and New Guinea. CSIRO, Melbourne, Australia, Land Research Series 29. 124 pp. Parker, G. (1990). Surface-based bedload transport relation for gravel rivers. Journal of Hydraulic Research, 28(4), 417–436. Parker, G. (1991a). Selective sorting and abrasion of river gravel: Theory. Journal of Hydraulic Engineering, 117(2), 131–149. Parker, G. (1991b). Selective sorting and abrasion of river gravel: Applications. Journal of Hydraulic Engineering, 117(2), 150–171. Parker, G., & Dietrich, W. A. (1993). Numerical modeling of the Klohn Leonoff waste control scheme for the Ok Mani, Papua New Guinea. In: Klohn Leonoff. Ok Mani Diversion and Waste Storage. Ok Tedi Mining Ltd., Appendix IV. Parker, G., Cui, Y., & Imran, J. (1996). Flooding in the lower Ok Tedi, Papua New Guinea due to the disposal of mine tailings and its amelioration. International Seminar on Recent Trends of Floods and their Preventive Measures, Hokkaido River Disaster Prevention Research Center, June 20–21. Pickup, G. (1978). Report on environmental aspects of Ok Tedi project waste disposal. Australian National University North Australia Research Unit, Darwin, 15 pp. Pickup, G. (1980). Hydrologic and sediment modeling studies in the environmental impact assessment of a major tropical dam project. Earth Surface Processes, 5, 61–75. Pickup, G. (1984). Geomorphology of tropical rivers. I. Landforms, hydrology and sedimentation in the Fly and lower Purari, Papua New Guinea. Catena Supplement, 5, 1–18. Pickup, G. (2001). Geomorphic processes in the Ok Tedi and Fly River system: Current status, future trends and rehabilitation. Report to Ok Tedi Mining Ltd., 62 pp. Pickup, G. (2003). Effects of mine life extensions and rates of dredging on the Ok Tedi and Fly River. Uncertainty analysis for the null scenario. Report to Environment Section, Ok Tedi Mining Ltd., 38 pp. Pickup, G. (2005). Floodplain inundation modeling and forecasting for the Middle Fly. Report to Environment Section, Ok Tedi Mining Ltd., 88 pp. Pickup, G. (2009). Floodplain inundation modeling and forecasting for the Middle Fly. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System, Vol. 9. Elsevier, Amsterdam, pp. 291–318. Pickup, G., & Higgins, R. J. (1979). Estimating sediment transport in a braided gravel channel – the Kawerong River, Bougainville, Papua New Guinea. Journal of Hydrology, 40, 283–297. Pickup, G., & Marks, A. (2000). Identifying large-scale erosion and deposition processes from airborne gamma ray remote sensing and digital elevation


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models in a weathered landscape. Earth Surface Processes and Landforms, 25, 535–557. Pickup, G., & Marks, A. (2001). Regional-scale sedimentation process models from airborne gamma ray remote sensing and digital elevation data. Earth Surface Processes and Landforms, 26, 273–279. Pickup, G., & Cui, Y. (2003). Effects of mine life extensions and rates of dredging on the Ok Tedi and Fly River – A sediment transport model study using Okgrav6 and HEC-6. Report to Environment Department, Ok Tedi Mining Ltd., 113 pp. Pickup, G., & Marshall, A. R. (2009). Geomorphology, hydrology and climate of the Fly River System. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River system, Vol. 9. Elsevier, Amsterdam, pp. 3–49. Pickup, G., Higgins, R. J., & Warner, R. F. (1979). Impact of waste rock disposal from the proposed Ok Tedi mine on the Fly River and its tributaries. Department of Minerals and Energy and Office of Environment and Conservation, Papua New Guinea, 139 pp. Rowland, J. C., Lepper, K., Dietrich, W. E., & Wilson, C. (2005). Tie channel sedimentation rates, oxbow formation age, and channel migration rate from Optically Stimulated Luminescence (OSL) analysis of floodplain deposits. Earth Surface Processes and Landforms, 30(9), 1161–1179. SMEC (1978). Hydrologic investigations for the Ok Tedi project. Report prepared for Dampier Mining Co. Ltd., Snowy Mountains Engineering Corporation, 115 pp. Vanoni, V. A., & Henderson, F. M. (1979). The effect of mine sediments on the Ok Tedi-Fly River system. Ok Tedi feasibility study. Volume 2 – Environment. The Ok Tedi Consortium, pp. 74–121. Wright, S., & Parker, G. (2005a). Modeling downstream fining in sand-bed rivers, I: Formulation. Journal of Hydraulic Research, 43(6), 612–619. Wright, S., & Parker, G. (2005b). Modeling downstream fining in sand-bed rivers, II: Application. Journal of Hydraulic Research, 43(6), 620–630.


Chapter 8

Floodplain Inundation Modeling and Forecasting for the Middle Fly Geoff Pickup Consulting Geomorphologist, 1538 Sutton Road, Sutton, New South Wales 2620, Australia

8.1. Introduction Modeling of deposition in the Ok Tedi and Fly River systems (Cui and Parker, 1999; Pickup and Cui, 2009) has shown that dredging will slow or halt bed level rise in the lower Ok Tedi and upper Middle Fly. However, there is still a large body of sediment that was downstream of the dredge site at Bige by the time dredging operations began in 1998. Channel cross-section surveys show that this material continues to move downstream (Marshall, 2002) and modeling indicates that it will produce a significant rise in water levels in future years. Given the low gradient of the Middle Fly and the large area of floodplain, higher water levels will increase the extent and frequency of floodplain inundation. The Pickup and Cui sediment model results presented elsewhere in this volume have limitations because they do not allow for processes such as downstream flood-wave attenuation, flows in and out of off-river water bodies, local rainfall, tidal variations, and backwater effects from the Strickland and major tributaries such as the Binge and the Agu (Pickup, 2003). Some of these processes may reduce the amount by which water levels will rise. Capacity to predict changes to the amount and frequency of floodplain inundation has been limited by lack of topographic data. Apart from widely separated laser profiler transects flown in 1995, little was known about floodplain topography at the resolution needed for inundation mapping and Corresponding author. Tel.: +61 26238 3427


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modeling. It was therefore not feasible to calculate the volume of floodplain storages such as the many large off-river water bodies or to identify floodplain flow paths that link these storages to the main river. It was also not possible to model the lateral extent of floodplain inundation. In late 2003, NASA released a digital elevation model (DEM) from the Shuttle Radar Topography Mission (SRTM) covering Papua New Guinea. This DEM puts modeling of floodplain inundation a step closer. However, with a stated accuracy of only 5–7 m in elevation and limited rainforest canopy penetration by the radar, the SRTM DEM is not good enough for inundation modeling in its raw form. Several other developments have made it possible to correct the SRTM DEM data to a point where flood inundation modeling becomes feasible. First, a body of remotely sensed data from the LANDSAT Thematic Mapper has accumulated since 1997. These data may be used to map the extent of floodplain inundation over a range of river heights on the few occasions where cloud cover is limited. Second, the European Space Agency ENVISAT satellite carries a high resolution, synthetic aperture radar that allows imaging of flooded areas through cloud. These datasets have been used together with water surface profiles derived from river gauge heights to adjust SRTM DEM elevations so that they reproduce observed flooding behavior more closely. This chapter describes the development of a floodplain inundation model based on corrected SRTM data. The model incorporates unsteady flow down the main river channel, inflows and outflows to off-river water bodies, and backwater effects from the Strickland. Tests of model accuracy show that it is capable of producing water surface profiles that vary with time as floods pass down the Middle Fly and off-river water bodies fill and empty. They also show that the model can reproduce observed extents of floodplain inundation. The model has been used with predicted channel deposition rates from Pickup and Cui (2009) and shows how floodplain inundation increases with time as mining waste passes downriver.

8.2. Digital Elevation Data for the Floodplain – the Shuttle Radar Topography Mission (SRTM) 8.2.1. Background SRTM was the primary payload on the STS-99 Mission of the Space Shuttle Endeavour which launched on February 11, 2000 and flew for 11 days

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covering most of the Earth’s land area (Farr and Kobrick, 2000). SRTM data spacing is either 1 arc-second or 3 arc-seconds, referred to as SRTM-1 and SRTM-3, respectively. Since 1 arc-second at the equator corresponds to roughly 30 m in horizontal extent, the sets are sometimes referred to as ‘‘30 m’’ or ‘‘90 m’’ data. Only the 90 m data are currently available for areas outside the United States. There are five potential sources of error in the SRTM DEM when used for inundation modeling on the Fly floodplain: These are: Differences between the SRTM reference geoid and AHD as used in OTML elevation data. These may be up to 1.8 m (Marshall, personal communication). There is also a long-wavelength roll-induced error of about 2 m in SRTM data (Farr, personal communication). Errors associated with radar speckle and the use of interferometry to derive elevations. Data voids due to radar shadowing by locally higher terrain and over water bodies. Inability to capture small features (Teng, 2002) such as tie channels when using a 3 arc-second grid. Some tie channels may only be a few meters wide yet they may be the main path for flooding of some off-river water bodies from the main channel of the Fly. The SRTM DEM is a DEM rather than a ground surface elevation dataset. As such, elevation data describe what the sensor detects rather than true ground levels. This may well be the vegetation canopy, especially in forests. There has been considerable discussion of SRTM DEM accuracy on Internet message boards. Error levels seem to vary with terrain and surface characteristics, with claims of accuracy to within 1–2 m in flat areas and 5–7 m on steeper slopes (see also Smith and Sandwell, 2003; Sun et al., 2003). Water bodies present specific problems. If the water is too smooth, no radar signal returns and there will be a void in the SRTM data. Rugged terrain may also have data voids because some areas may be in the radar shadow of adjacent hills. Vegetation effects on SRTM elevations are greatest over closed canopy rainforest. Comparisons between forested and adjacent cleared areas show that forest adds 4–25 m to SRTM elevations. Elevation errors in grassland and open forest are less than in rainforest but can also be significant. Some are associated with isolated stands of trees and shrubs. Others seem to be the result of radar speckle. Profiles taken across the SRTM DEM in flat areas with grass cover or bare sediment suggest that most errors are 72 m or less.

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8.2.2. Correction Procedures for SRTM Data SRTM elevation data were corrected by involved identifying inundated areas on airborne and remotely sensed satellite imagery and linking them with observed water surface profiles in the Middle Fly. The DEM was then adjusted iteratively so that observed floodplain inundation patterns are generated by the GRADFLOW model (Pickup et al., 2002) for each known water surface profile. The water surface profiles along the main river are calculated by linear interpolation between the gauging stations at Obo (FLY16), Manda (FLY15), and Kuambit (FLY10)1. The DEM correction procedure assumes that floodplain water surface elevations adjust to main channel water surface elevations quickly. If so, inundated areas on the floodplain detected on satellite imagery will have similar water surface elevations to the main channel where the two are connected. Channel water surface elevations can then be used to set a maximum elevation for inundated areas of the floodplain with only limited loss of accuracy. This assumption was tested using water-level data for tie channels and offriver water bodies collected in the mid-1990s. Overall, it seems that floodplain water levels adjust rapidly and closely approach those of the Fly in times of flood. Also, because the Fly rises and falls relatively slowly, floodplain water levels can be close to water levels in the river. Some errors will occur when water levels are mismatched but they are likely to be less than 1 m in most cases. This is small compared with other sources of error in the SRTM DEM. There were many steps in correcting the DEM. They included testing and use of synthetic aperture radar data from the ENVISAT satellite (Fig. 8.1). The ENVISAT instrument can be set to acquire many combinations of radar incidence angle and polarization. These had to be tested to determine the best way of identifying inundated areas. LANDSAT data were also used but many scenes were obscured by cloud. Tests of ENVISAT data over the Fly floodplain show that the largest incidence angles (ENVISAT swath IS7, 42.5–45.2 degrees) give the best water body discrimination. However, swath width is too narrow to cover the floodplain in a single satellite pass. Inundation monitoring would, therefore, require multiple passes on different days. This would make it difficult to establish a pattern of inundation across the whole floodplain that was matched to a single set of flow conditions. Low incidence angle data (ENVISAT swath IS1, 15.0–22.9 degrees) cover the whole floodplain but detect what appear to be wind-generated waves on the water surface, which are indistinguishable from forest backscatter (Fig. 8.1). ENVISAT swath IS4

Figure 8.1: ENVISAT IS1 (upper) and IS4 (lower) HH polarization images of the Middle Fly floodplain. There is more water in the channel and on the floodplain in the lower image. Water bodies are clearly shown in black on the lower image. In the upper image some channel reaches (marked by red arrows) cannot be distinguished from the surrounding floodplain. This may be the effect of wind-driven surface waves on radar returns.

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data (31.0–36.3 degrees) gives the best compromise between water body detection and areal coverage and was used here. Reducing the effect of vegetation on SRTM elevations requires data on vegetation canopy heights. However, canopy heights vary from one vegetation type to another, and also within vegetation types This is a common problem in the open forest, mixed forest/grassland systems, and areas of rainforest dieback that are common on the Fly floodplain. There is limited information in the literature on correcting SRTM elevations for vegetation effects. Kellndorfer et al. (2004) were able to calculate vegetation canopy height by comparing SRTM elevations with a national reference elevation dataset in the United States but this approach is not feasible on the Fly. De Ruyver (2004) attempted to correct SRTM elevations in the Pantanal Wetlands of Brazil. This area has some similarities to the Middle Fly. His approach was first to classify vegetation using LANDSAT TM data, creating a basic stratification of cover types. He then calculated normalized difference vegetation index2 (NDVI) values and assumed a correlation with vegetation height but with a different range in each vegetation type. The range was based on observation but the approach was not field tested or verified. This approach does not work in the Fly because NDVI values seem unrelated to canopy height in most vegetation types. An alternative method was therefore sought. As a first step in reducing the effect of vegetation on elevation, the floodplain has been classified into land cover types using LANDSAT TM data. A simplified version of the classes is listed in Table 8.1. Once the DEM has been corrected, the change in SRTM elevations can be mapped and overlaid on satellite imagery classified into different land cover types. Adding all the changes together for each cover type and averaging gives a mean change in elevation for each type. This may give a first-order elevation correction where vegetation has a uniform height. However, it fails because vegetation height varies within and across cover types, so another approach is needed. Many attempts were made to detect a pattern in the SRTM elevation changes generated by the correction procedure. While there were clear differences associated with each land cover type locally, other factors were at work and a general relationship could not be found across the floodplain. The best result was obtained by comparing SRTM elevation changes with height above local river base level for each cover type. This required three steps: Identification of flow paths, calculation of local base level and calculation of the height of each grid cell above that base level. This was done using the


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Table 8.1: Aggregated land cover types on floodplains and adjacent areas classified from transformed LANDSAT data. Name Forested areas Terrace forest 1 Terrace forest 2

Open forest

Wet forest

Class description Closed canopy forest on terraces bordering the floodplain, forest on lower terrace surfaces Forest on terraces bordering the floodplain in drier areas on the west side of the lower Middle Fly. May include areas with openings in the canopy. Some areas may have been logged or burnt by bushfire. Open forest with bare soil or sediment exposed in some areas. Occupies lower terrace slopes and tributary valley floors. May include occasionally inundated rainforest areas on the main floodplain Wet and sometimes sparsely forested areas on low-lying ground on and bordering the floodplain. Bare sediment may be visible through the canopy. Many areas are affected by forest dieback.

Grassed floodplain and frequently flooded areas Open Grass or bare surfaces with sparse tree or shrub cover. floodplain 1 Frequently wet and may include forest dieback areas with scattered trees Open Grassed floodplain surfaces, some localized tree and shrub floodplain 2 cover Wet grassed As open floodplain 2 but lower and more frequently floodplain inundated Swamp 1 Frequently inundated areas with exposed mud at low water levels. May also have sparse grass, shrub, or tree cover Swamp 2 Low lying and occasionally waterlogged grassed floodplain Flooded areas at low-medium water surface elevations Flooded River water and flooded areas Unclassified Unclassified

Small unclassified areas that are often a mix of existing classes

DEM processing routines in the SAGA GIS (http://www.saga-gis. uni-goettingen.de/html/index.php). Use of Gradient Analysis3 to extract a simple relationship between the SRTM elevation corrections and elevation above local base level. Fitting a predictive relationship to the Gradient Analysis results to allow correction of SRTM elevations. This could then be applied to locations that

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were too high to be reached by the flows observed on the satellite image database and so could not be corrected by the procedures described at the beginning of this section. Examples of the correction factors for three different land cover types are shown in Fig. 8.2. The correction factors were only applied to SRTM DEM elevations less than 15 m above local base level. Beyond that, there are insufficient points in the Gradient Analysis to fit a predictive relationship. An approximate test of the accuracy of the corrected SRTM DEM can be made by comparing the elevation of channel bank grid cells with banktop elevations from channel cross-section surveys. However, some differences between these two datasets can be expected for the following reasons: Surveyed cross sections do not tend to be in locations where one or both channel banks end in low lying, flooded zones, Corrected SRTM data are 30 m grid cell averages whereas the crosssection survey data are for point locations, and There is only limited satellite coverage at high water levels so the SRTM DEM elevations tend to cluster around a few water surface profile elevations. 5 Open Forest Terrace Forest 1

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Figure 8.2: Examples of correction factors for SRTM DEM elevations for different land cover types.


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Where there are two sets of parallel profiles, this indicates that some data have been corrected using satellite data on flood extent while others have only had vegetation effects stripped off. These locations lie above the highest water level on the satellite data. More flood information would produce more variability. In spite of these issues, the two datasets compare reasonably well (Fig. 8.3). The main clusters of SRTM data, represented by lines of points on Fig. 8.3, are within 1–1.5 m of the surveyed cross-section banktops. The scatter of points above these lines comes from locations where the channel bank intersects the Pleistocene terrace that borders the floodplain. Cross-section surveys that extend onto the terrace show similar elevations above the general banktop level. There is also a group of SRTM DEM points 3–4 m below the cross-section survey banktop levels. These low points compare reasonably well with the lower elevations in the 1995 laser profiler data.

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8.3. Floodplain Hydraulic Model – Development and Testing 8.3.1. The Unsteady Flow Model The unsteady flow calculations are based on the HEC-RAS model developed by the US Army Corps of Engineers (2003). The floodplain system is represented in HEC-RAS as: A channel described by a series of surveyed cross sections. A set of off-channel storages with known storage volume–height relationships. A set of connections between the channel and the off-channel storages. These are included in the model as a series of lateral weirs. Flows pass down the channel and are attenuated during transmission and by transfer of water to and from floodplain storages at rates, which vary with differences in water surface elevation between the main channel and the storages. This has the effect of reducing flood height on the rising stage as water flows from the channel into off-channel storages. Flow is then augmented on the falling stage of the flood as the off-channel storages empty back into the main channel of the Fly. Model boundary conditions are set by a time series of discharges at the upstream end of the model and a time series of water levels at the downstream end. The water-level record for the gauging station at Obo (FLY15) is used as the lower boundary condition since it incorporates both backwater effects from the Strickland and tidal effects. The storage-volume curves were derived from the SRTM DEM and runs with the GRADFLOW model. A base water surface profile was interpolated from gauging data for January 11, 1998 when the river was very low and LANDSAT imagery showed that the floodplain storages were largely dry. The water surface profile was progressively raised above the base profile, 1 m at a time, and the volume of the inundated area was calculated. These calculations were initially carried out at a spacing of one LANDSAT TM pixel (B30 m) but were then aggregated into a single storage on each side of the channel between each surveyed cross section. Various attempts were made to deal with inputs from floodplain tributaries. These contribute about 9% of total flow to reach upstream of Manda. However, no information is available on the amount and timing of inflows so it was not feasible to build them into the model directly. An alternative approach is to assume that tributary inflows partly fill floodplain storages and reduce capacity for inflows from the main river.


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The resultant changes to available floodplain storage volumes are fairly low when water levels are high. Numerical trials with changes of up to 5% in floodplain storage volumes have virtually no effect on the main river water surface profile so it seems fairly safe to ignore tributary inflows.

8.3.2. Unsteady Flow Model Testing Results of model testing are shown in Fig. 8.4. The modeled water levels at Manda (FLY16) show acceptably close correspondence with observed values. The water levels at Kuambit (FLY10) are reasonably accurate and many of the features of the backwater dominated water-level record at FLY16 are reproduced. The main errors are overestimation of the water level of some high flows and underestimation of low-flow elevations. A comparison between model predictions for Manda (FLY16) both with (brown line) and without storage effects (dark green line) is also shown in Fig. 8.4. It is clear that floodplain storage plays a major role in damping flood Observed 20 FLY10

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Figure 8.4: Observed and modeled water levels for Manda (Station FLY16) compared with water levels for Kuambit (FLY10) and Obo (FLY15). Note the effects of floodplain storage on water-level variability at FLY16.

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waves and reducing water levels downriver. It also seems that a large volume of river water passes through the floodplain storages at various stages.

8.3.3. Floodplain Inundation Model The GRADFLOW model uses the water surface profiles produced by the hydraulic model to inundate the floodplain. The channel and the floodplain DEM are divided into 30 30 m grid cells. The algorithm begins by flooding the main channel and any tie channels directly connected to it. After that, floods are extended laterally from each channel grid cell one step at a time by searching all immediate neighbors. As each neighboring grid cell is encountered, it is tested to see whether (a) it is already flooded and, (b) it lies above the water level in the main river channel. If either condition is met, the cell is not flooded on this pass. If the cell lies below the main river water level and is not already flooded, it is inundated. In the next iteration, all neighbors of the newly flooded cell are tested and the search gradually proceeds outwards from the flooded area until stopped by higher ground or blocked by cells that are already flooded. This procedure works well in areas where water moves onto the floodplain during flooding and returns to a similar location on the main channel as the flood recedes. It is less successful where water leaves the channel through a levee breach, flows down the backplains and reenters the main channel further downstream. The GRADFLOW algorithm contains a range of procedures to allow for this effect (Pickup and Marks, 2000, 2001). Tests of the inundation model are presented in Figs. 8.5–8.7. These compare areas flooded by the model with observed areas of water on LANDSAT TM images. Water surface profiles used in this test come from HEC-RAS model runs with channel cross section data generated by the HEC-6 sediment model (Pickup and Cui, 2009) rather than observed cross sections. We are, therefore, testing both the inundation model and the channel geometry used to generate the water surface profiles into the future. The LANDSAT TM image shown in Fig. 8.5 was used in DEM correction so the modeled pattern of flooding should match with what is observed. The images shown in Figs. 8.6 and 8.7 were not used in DEM correction and provide an independent test. While there are local anomalies, the results are generally good. The observed and modeled floods in Fig. 8.5 show a close match. Where there are differences, they often occur in areas with, or adjacent to cloud shadow. These were not corrected in the DEM because flooding was obscured.

Figure 8.5: Comparison of modeled inundation area (blue area on upper image) with observed flooding on a LANDSAT TM image on February 27, 2001 on the upper Middle Fly near D’Albertis Junction. Flooded areas on the TM image are blue and black. Flow duration is about 20%.

Figure 8.6: Comparison of modeled inundation area (blue area on upper image) with observed flooding on a LANDSAT TM image on October 22, 2000 on the lower Middle Fly at Aiambak just north of Everill Junction. Flooded areas on the TM image are blue, black, and the darker purple tones. Some bright green areas close to the river may be inundated vegetation or floating grass mats. Flow duration is about 30%.

Figure 8.7: Comparison of modeled inundation area (blue area on upper image) at 10% flow duration with observed flooding on a LANDSAT TM image (February 11, 2001) at Everill Junction. Flooded areas on the TM image are blue, black, and most of the purple tones. The whole of the Middle Fly floodplain is inundated. Some bright green areas close to the river may be inundated vegetation or floating grass mats. Inundation on the Strickland floodplain (lower right) was not modeled. Flow duration is about 20%.

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Other results from missing tie channels that leave small off-river water bodies unconnected to the main river channel. The area shown in Fig. 8.6 also indicates a close match although the extent of flooding appears to be slightly exaggerated in some areas. This may occur because waterlogged grass and floating grass mats on the TM image do not show as flooded areas. This area is also very flat and changes in the water surface profile as small as 0.2 m can change the flooded area quite substantially. The flood in Fig. 8.7 provides a severe test of model performance. There is minimal relief so small differences in the water surface profile mean large changes in flooded area. Large areas of floating grass mat and flooded vegetation obscure the flooded area on the TM image while cloud and shadow also make it difficult to recognize surface water. Overall however, the match between observed and modeled inundation is fairly close although model results may slightly overestimate the flooded area. The model should not only be able to predict water-level elevations and inundation extents, but it should also preserve the flow frequency characteristics of the water-level record. A test of this capacity is shown in Fig. 8.8. 12

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Figure 8.8: Observed and modeled water-level duration curves for Manda (FLY16). Model data were generated from river profile and cross-section data for 2000 from the HEC-6 sediment model.


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The two curves in this figure show how well the model predicts flow durations at Manda (FLY16). The model water-level data were generated using cross sections from the 2003 sediment model so we are testing both the HEC-RAS model and the HEC-6 simulations. The results are, again, extremely close, indicating that model results reproduce the natural flow frequencies very well. The two curves deviate at low water surface elevations but this may be a result of inaccuracies in the input data rather than the performance of the model. This is not really an issue in model performance since we are mainly interested in forecasting inundation at higher flows.

8.4. Forecasting the Extent and Frequency of Floodplain Inundation 8.4.1. Methods Once calibration and testing were completed, the hydraulic model was run on the scenario described in Chapter 7 (Pickup and Cui, 2009). This involves dredging at 15.1 Mt/year and mine closure in 2010. A synthetic flow record was used in each model run based on observed data for Kuambit and Obo. This record has similar flow frequency characteristics to the long synthetic flow record used in the sediment model. Water surface profiles from the hydraulic model were used to derive a set of water surface elevation frequencies down the length of the Middle Fly. These were used to inundate the floodplain using GRADFLOW. The resultant inundation maps and water surface profile changes with time are presented in Figs. 8.9–8.16. The hydraulic model and the GRADFLOW routines can also be used to estimate flows between the river and the floodplain. These values were used to estimate sediment delivery to the floodplain surface. This value does not include levee deposition and further development of the levee model described in Chapter 7 is planned. The HEC-RAS model cannot generate the continuously changing bed levels produced by the HEC-6 sediment transport model used in the 2003 sedimentation study. However, it is possible to represent the effects of deposition on floodplain inundation by taking the river channel characteristics produced in HEC-6 model runs at 10 year intervals and using them in HEC-RAS. Changes in the pattern of floodplain inundation over time can then be generated.

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Figure 8.10: Model estimates of inflow from the main channel of the Middle Fly to the floodplain as a percentage of total river flow.


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Figure 8.11: Pre-mining situation 1985, modeled floodplain inundation patterns for the upper Middle Fly.

8.5. Results Figure 8.9 shows the modeled changes in water surface elevation through time. Behavior is typical of a river experiencing an increase in sediment load. Deposition gradually progresses downstream raising water levels until the

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Figure 8.12: Pre-mining situation 1985, modeled floodplain inundation patterns for the lower Middle Fly.

river establishes a new long profile with a steeper gradient. This allows it to convey delivered load further downstream. As water levels rise, more water will circulate through off-channel storages but this effect is not strong enough to interfere with the basic pattern of water-level rise that is progressing downstream.


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Figure 8.13: Modeled floodplain inundation patterns for the upper Middle Fly in 2010. When there is a reduction in sediment load, the profile will begin to flatten from the upper reaches downstream. However, the effect of increased load may continue to raise water levels in downstream reaches even once profile flattening begins at the upper end of the system. The effects of increased load take many years to pass down the river and water levels continue to rise long after mine closure.

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Figure 8.14: Modeled floodplain inundation patterns for the lower Middle Fly in 2010. There are some irregularities in water surface profile changes. This results from not having enough surveyed cross sections for detailed hydraulic modeling and the use of a one-dimensional sediment model. In reality, the profiles would be smoother.


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Figure 8.15: Modeled floodplain inundation patterns for the upper Middle Fly in 2050. The proportion of total main channel discharge entering the floodplain varies from about 9% at the start of mining to about 14% in 2050 (Fig. 8.10). This is less than Dietrich and Day’s (2004) estimate of 20–40%. Most of the increase is due to the body of sediment already

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Figure 8.16: Modeled floodplain inundation patterns for the lower Middle Fly in 2050. on the bed of the lower Ok Tedi and Middle Fly prior to the start of dredging. The floodplain inflow data may be used together with sediment transport data to obtain a crude estimate of sediment delivery to the floodplain.


315

Suspended sediment data for Station FLY11 at Niukamba obtained by depth integrated sampling show a mean sediment concentration of 570 mg/l. However, these data were not obtained using a large enough sampler and have very similar values to surface gulp samples. A correction factor of 1.2 gives a mean concentration of 684 mg/l and a total inflow to the floodplain of about 5 Mt/year. This does not include sediment deposited on the levees, which could involve 1–2 times as much material. The SRTM DEM and the GRADFLOW model have been used to calculate the duration and extent of floodplain inundation. Maps are presented here for the pre-mining channel based on the 1985 river reconstruction used in the 2003 sediment modeling study, for 2010 and for 2050 when the river is close to adjusting to the increased sediment load. The floodplain maps show that there is a major increase in flooding in the upper part of the Middle Fly during mine life. The lower Middle Fly experiences major changes after mine closure, no matter what the scenario. Recovery in the upper river is very limited as inundation remains more frequent than in the pre-mine situation. Once the initial rise in water occurs, the changes pass downstream and flooding occurs more frequently. Lateral extension is limited because the floodplain is confined by terraces. Flooding does extend up tributaries as water levels rise but the main effect is in the downstream direction. The precise impact varies with location but some areas go from experiencing flooding for 10% or less of the time to 70% or more. This is likely to produce substantial changes in the whole floodplain ecosystem. Many of these changes will occur long after mine closure. While continued dredging does improve the situation, the bulk of the impact comes from the sediment that had already passed Bige before dredging started. There are few options available to deal with this.

8.6. Conclusions The floodplain inundation model and maps show how the passage of mine waste down the Middle Fly may affect the floodplain. Over time, inundation depth and frequency will increase in many areas. This will affect a whole range of geochemical, biological, and social processes. It will also change the amount, type, and accessibility of both terrestrial and aquatic resources used by floodplain communities. The inundation maps may be used in association with other knowledge to derive estimates of the timing and extent of some of these changes.

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Frequency and extent of inundation is one of the variables affecting the rate of weathering through the process of wetting and drying. Floodplain inundation also delivers sediment containing sulfides to the floodplain with the amount of deposition declining exponentially with distance from the channel (Dietrich, 2000). There will also be greater deposition in low-lying areas close to the channel, all other things being equal. Inundation depth and frequency maps have some potential for predicting floodplain areas where ARD problems may arise. The distribution of many floodplain plant communities reflects frequency and duration of flooding. While there may be some tolerance to variations in flooding allowing plant communities to persist, other areas are likely to experience changes in plant cover. These may occur rapidly and allow invasive species to colonize large areas. Aquatic environments will also change. Many areas will be flooded for longer periods and terrestrial environments may become increasingly aquatic. Major changes to the whole floodplain ecosystem can be expected. The floodplain model is close to the limits of what can be done with available data. It is not a full hydraulic model so there will be some imprecision in the predictions. Also, the SRTM DEM can be improved as more satellite imagery becomes available. These will produce differences of degree rather than major changes in the inundation predictions. Ultimately, the accuracy of the floodplain inundation rests on the accuracy of predictions from the sediment transport model. While there are questions about this model in some areas (Pickup and Cui, 2009; Booth, 2004), the overall pattern of predicted deposition is thought to be reasonable.

Notes 1. Gauging station locations are shown in Figs. 4 and 5 of the ‘‘Geomorphology’’ chapter. 2. NDVI is a widely used vegetation greenness index based on the difference between red and near-infrared values in satellite imagery. 3. Gradient Analysis (Pickup and Marks, 2000) is a technique for identifying complex relationships between variables in satellite images and Geographic Information System layers with very large amounts of data and significant noise. When the values in every grid cell are plotted, relationships between variables may be obscured by the noise, especially where thousands-to-hundreds of thousands of observations are involved. In the Gradient Analysis carried out here, elevation above base level is split into classes and the average value of the SRTM elevation correction is then calculated for each elevation above base level class on a grid cell by grid cell basis. The result may then be plotted and a normal or weighted regression equation fitted to give a predictive relationship.


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REFERENCES Booth, S. (2004). Sediment Transport Model Workshop. Cairns, Australia, 21st–23rd January 2004. Final Report. Environment Department, Ok Tedi Mining Ltd. and Total Catchment Management Services. Cui, Y., & Parker, G. (1999). Sediment transport and deposition in the Ok Tedi-Fly River System, Papua New Guinea: the modeling of 1998–1999. St. Anthony Falls Laboratory, University of Minnesota, Minnesota. De Ruyver, R. (2004). DEM Optimization for Hydrological Modelling using SRTM for the ‘Pantanal Region’, Brazil. M.Sc. Thesis. International Institute for Geo-Information Science and Earth Observation, Enschede, the Netherlands. Dietrich, W. E. (2000). Quarterly and Fourth Monthly Report, Middle Fly Sedimentation Project. Department of Earth and Planetary Science, University of California, Berkeley. Dietrich, W. E., & Day, G. (2004). Rates and Patterns of Floodplain Sedimentation, Middle Fly Floodplain (1985–1994). Presentation at the Sediment Transport Model Workshop, Cairns, Australia. January, 2004. Environment Department, Ok Tedi Mining Ltd. Farr, T. G., & Kobrick, M. (2000). Shuttle Radar Topography Mission produces a wealth of data. American Geophysical Union Eos, 81, 583–585. Kellndorfer, J., Walker, W., Pierce, L., Dobson, C., Fites, J. A., Hunsaker, C., Vona, D., & Clutter, M. (2004). Vegetation height estimation from Shuttle Radar Topography Mission and National Elevation Datasets. Remote Sensing of Environment, 93, 339–358. Marshall, A. R. (2002). Ok Tedi – Middle Fly Bed Aggradation Survey. Epoch 6 – March 2002 (and associated spreadsheets). Environment Department, Ok Tedi Mining Ltd. Pickup, G. (2003). Effects of Mine Life Extensions and Rates of Dredging on the Ok Tedi and Fly River. Uncertainty Analysis for the Null Scenario. Report to Environment Section Ok Tedi Mining Ltd. Pickup, G., & Marks, A. (2000). Identifying large-scale erosion and deposition processes from airborne gamma ray remote sensing and digital elevation models in a weathered landscape. Earth Surface Processes and Landforms, 25, 535–557. Pickup, G., & Marks, A. (2001). Regional-scale sedimentation process models from airborne gamma ray remote sensing and digital elevation data. Earth Surface Processes and Landforms, 26, 273–279. Pickup, G., & Cui, Y. (2009). Modeling the impact of tailings and waste rock disposal on the Fly River system. In: B. Bolton (Ed.). The Fly River, Papua New Guinea: Environmental Studies in an Impacted Tropical River System. Elsevier, Amsterdam, Vol. 9, pp. 257–289. Pickup, G., Marks, A., & Bourke, M. (2002). Palaeoflood reconstruction on floodplains using geophysical survey data and hydraulic modeling. In: P. Kyle

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House, R. H. Webb, V. R. Baker, & D. R. Levish (Eds). Ancient Floods, Modern Hazards: Principles and Applications of Palaeoflood Hydrology. Water Science and Application. American Geophysical Union, Washington D.C., Vol. 5, pp. 47–60. Smith, B., & Sandwell, D. (2003). Accuracy and resolution of Shuttle Radar Topography Mission data. Geophysical Research Letters, 30, 1467–1470. Sun, G., Ranson, K. J., Kharuk, V. I., & Kovacs, K. (2003). Validation of surface height from Shuttle Radar Topography Mission using shuttle laser altimeter. Remote Sensing of Environment, 88, 401–411. Teng, L. W. (2002). Drainage analysis using DEMs from different sources. http:// www.crwr.utexas.edu/gis/gishydro03/Classroom/trmproj/Teng/Summary.htm US Army Corps of Engineers, Hydrologic Engineering Centre (2003). HEC-RAS Hydraulic Reference Manual.


Chapter 9

Biogeochemistry of Copper in the Fly River Simon C. Apte Centre for Environmental Contaminants Research, CSIRO Land and Water, PMB 7, Bangor Sydney, New South Wales 2234, Australia

9.1. Introduction Since mining of the Mount Fubilan porphyry copper–gold ore body by Ok Tedi Mining Limited (OTML) began in 1984, the Ok Tedi/Fly River system (Fig. 9.1) has received high loads of mine-derived sediments enriched in particulate copper. The potential release of copper from these sediments and its toxicity to aquatic organisms in the river system was an obvious concern to mine management. In order to understand this issue, it was necessary to understand the fate, mobility, and transport of mine-derived copper. The factors governing the dissolution of particulate copper from mine-derived sediments and the chemical speciation of dissolved copper were of particular concern. This chapter gives an overview of the geochemical studies undertaken over the first 15 years of mine life, before acid rock drainage (ARD) was detected in the system. A number of very detailed studies were carried out to gain an understanding of copper geochemistry in river, offriver water body (ORWB), estuarine, and coastal shelf environments. The studies were made challenging because of the remoteness of the study environments and the logistical demands imposed. As a result of these efforts, a quite extraordinary depth of knowledge on the copper geochemistry of the Fly River system was obtained, much of this information being of relevance to other aquatic systems. The factors influencing dissolved copper concentrations in the aquatic environments of the Fly River system are covered in this chapter. Corresponding author. Tel.: þ61-2-9710-6838; Fax: þ61-2-9710-6837;

E-mail: [email protected] (S.C. Apte).

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Figure 9.1: Location of sampling sites on the Ok Tedi and Fly rivers.

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9.2. Copper and Mine-Derived Suspended Sediment Distributions in the River System Details of the basic geochemistry and hydrology of the Fly River system may be found in the review by Salomons and Eagle (1990). The Ok Tedi, Fly, and Strickland rivers have quite similar bulk chemical compositions (Salomons and Eagle, 1990) and are dominated by calcium and bicarbonate ions which reflect the limestone geology of the upland areas. The pH of water in the Ok Tedi and Fly River are generally in the range 7.0–8.5; however, the waters draining from the Middle Fly floodplain that fill the ORWB of this region are characterized by low hardness, low pH, and high dissolved organic carbon (DOC). These waters are also introduced into the main river system following rainfall events. Since 1989, when the copper extraction circuits at the OTML mill were fully commissioned, the mine, with approval from the State, has discharged typically 70,000 tonnes/day of fine-grained tailings and 140,000 tonnes/day of waste rock overburden directly into the river system. An additional 20,000 tonnes/day of natural sediment enters the river system as a result of valley wall erosion directly related to the mine’s activities. Once introduced into the river system, the majority of the silt and clay load travels down the river in suspension. In-river grinding (particle abrasion) of coarse waste rock, particularly in the upper reaches of the river system, also generates fine particles. Aside from the Strickland River, the inputs of naturally suspended sediments are relatively small and mine-derived sediments dominate the sediment load. Over the last 20 years, OTML has extensively monitored a wide range of parameters at sites in the river, estuary, and ORWB of the Fly River system. Thousands of samples have been collected and analyzed at the mine environment laboratory in Tabubil and at off-site laboratories. A detailed analysis of this data and the inherent trends are outside the scope of this chapter; however, the general concentration versus distance trends of some important geochemical parameters are worthy of note (Fig. 9.2). Total suspended solids (TSS) are highest closest to the mine and then decrease sharply with distance down the Fly River. TSS concentrations then increase slightly below the junction with the Strickland River owing to the sediment input by this river. Particulate copper concentrations in suspended sediments (Fig. 9.2) are highest closest to the mine and gradually decrease through the Middle Fly owing to mixing with natural sediments low in copper. There is a step-change decrease in particulate copper concentration at the junction with the Strickland River owing to dilution with natural sediments from the

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Strickland which are relatively low in copper. Depending on the type of ores being processed, suspended particulate copper concentrations in the Ok Tedi, just below the mine site, range from typically 1,000 to 1,800 mg/g. This represents an increase in particulate copper concentrations of over 20 times the pre-mining concentrations of suspended sediments (typically 50 mg/g) in many parts of the system. Dissolved copper concentration profiles with distance along the Ok Tedi and Fly River show a trend that is somewhat counter-intuitive (Fig. 9.2). Copper concentrations in the water column actually increase with distance from the mine and are highest in the Middle Fly region of the river between Bosset and Obo, some 400–600 km from the mine site. At the junction of the Fly and Strickland Rivers, there is a sharp decrease in dissolved copper concentration. Laboratory modeling experiments showed that this phenomenon is not just a consequence of dilution, but partly caused by the rapid adsorption of copper onto the large load of natural sediments introduced by the Strickland River which are low in particulate copper (Apte et al., 1995a). This process adsorption results in typically a 30% reduction in dissolved copper concentration (Fig. 9.3). It should be noted that in the work discussed in this chapter, the term ‘dissolved copper’ is operationally defined and includes any copper species that passes through a 0.45 mm diameter pore size filter. This may include colloidal species.

9.3. Factors Affecting Copper Concentrations in the Fly River Most mining-related studies concerning trace metal mobility have either been directed to the effects of ARD, where metals are released in soluble forms and following pH neutralization can then precipitate (Chapman et al., 1983; Johnson, 1986), or the leaching of metals from deposited sediments (Nimick and Moore, 1991; Pedersen et al., 1993). The Fly River system is unusual as, at the point of discharge, most copper is in particulate form and dissolved copper comprises only a minor proportion (o1%) of the metal’s total load. Understanding the factors affecting copper release from mine-derived Figure 9.2: Summary of routine OTML monitoring data. (a) mean discharge (1993–1996), total suspended solids (TSS), (b) particulate copper, and (c) dissolved copper concentrations downstream of the mine. The data are annual average values. The years 1993, 1994, and 1996 were classified by OTML as being climatically dry, normal, and wet years, respectively.

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8

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Figure 9.3: Adsorption of dissolved copper as a function of equilibration time. Mixing of Fly River (Obo) and Strickland River waters at 1:1 dilution. Initial copper concentration 7.4 mg/L, TSS 535 mg/L. particles was therefore critical in unraveling the geochemical copper cycle and understanding copper toxicity to aquatic organisms. During the 1990s, the ores being processed at the Ok Tedi mine were dominated by copper sulfide minerals such as chalcopyrite with lesser quantities of chalcocite, digenite, covellite, and bornite. In addition, there was some oxide mineralization containing copper oxide minerals such as malachite, cuprite, and azurite. Thermodynamic equilibrium calculations clearly show that the solubility of copper sulfide mineral phases such as amorphous copper sulfide and chalcopyrite at circumneutral pH are in the submicrogram per liter range and cannot account for the observed riverinedissolved copper concentrations in the system (typically range of 0.5–20 mg/ L). This indicates the importance of copper oxide/carbonate minerals and copper sulfide oxidation in determining dissolved concentrations in the river system. In the absence of oxygen, the aqueous solubilities of the principal copper sulfide mineral phases, chalcocite and chalcopyrite, were negligible (o0.5 mg/ L) (Apte et al., 1999). However, suspension of these minerals in Fly River water in equilibrium with the atmosphere results in rapid surface oxidation reactions and large increases in solubility. Chalcopyrite was significantly less susceptible to oxidation than chalcocite. This may be attributed to the role of iron in controlling the solubility of CuFeS2.


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Copper solubility tests using filtered waters from the Fly River were conducted in order to better understand copper dissolution from minederived solids (Apte et al., 1999). The measured and calculated solubilities of Cu(OH)2, malachite, azurite, and tenorite over the pH range 6.8–8.0 in Fly River water are shown in Fig. 9.4. Solubility calculations were carried out using the program MinteqA2 (Allison et al., 1991). The predicted solubility of copper varies widely depending on which solid is assumed to control dissolved copper concentrations. Experiments indicated that despite the differences in minerals added to the waters, dissolved copper concentrations after 16 h equilibration of the copper mineral with the river water at 251C were remarkably similar and within an order of magnitude of each other. The experimental results suggest that the minerals undergo transformation during resuspension in oxygenated water to form the same solid phase which controls copper solubility, regardless of the composition of the parent mineral. Based on experimental measurements described above, the maximum attainable dissolved copper concentration (o0.45 mm) in Fly River water at pH 7.8 was found to be ca. 250 mg/L. The experimentally observed solubility is at least eight times higher than dissolved copper concentrations typically 1000


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observed in the river system. The fact that dissolved copper concentrations of this magnitude have never been observed in the field, indicates the importance of adsorption reactions in attenuating dissolved copper concentrations. In the ORWB of the Fly River, where water pH can be much lower than the river system, the maximum attainable dissolved copper concentrations are much higher. For instance, at pH 7.0 the maximum solubility is 550 mg/L, and at pH 6.6 the maximum value is 850 mg/L. Tailings leaching studies were conducted in order to understand the factors affecting the initial release of copper from mine-derived sediments as would occur when the mine sediments are introduced into the river system. The experiments were conducted by immersing known concentrations of tailings solids into freshwaters and measuring the subsequent release of copper over a time period of typically 24 h. Three freshwaters were used in the leaching studies: Ok Mani (an upper tributary of the Ok Tedi), the Fly at Kiunga (above the junction with the Ok Tedi), and Bosset Lagoon (a slightly acidic ORWB in the Middle Fly). The water quality parameters for these samples are summarized in Table 9.1. In order to characterize temporal variations in copper release as would occur as ore composition changes, a series of 24 h composite flotation plant tailings (November 1994 to January 1995) were used in the study. The particulate copper concentrations of the 25 tailings samples varied over the range of 730–2,130 mg Cu/g. Typically, 4075% of the tailings particles were o63 mm with coarse particles (W180 mm) comprising 1377% of total mass. When immersed in river water, the initial release of copper from tailings material was characterized by a rapid initial release of copper in the first hour followed by a slower release over the ensuing 17 h (Fig. 9.5). The copper released in the first hour comprised 58–79% of the dissolved copper concentrations observed at the end of the experiment (48 h). Copper release was essentially independent of particle concentration over the range 0.5–4 g/ L (Fig. 9.6). As expected, pH played a significant role in determining copper solubility. The amount of copper released into solution increased with decreasing pH (Fig. 9.7). In waters having a pH of less than 7.0, there was a Table 9.1: Chemical properties of the waters used in the leach tests. Water

pH Dissolved Dissolved Complexing DOC (mg/L) Cu (mg/L) Ca (mg/L) Capacity (mg/L)

Ok Mani 7.8 Fly River at Kiunga 7.8 Bosset Lagoon 6.6

0.8 1.0 4.1

33 24 6

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Figure 9.7: Effect of pH on dissolved copper release from mine-derived sediments. Unfiltered river water sample from Konkonda (total suspended solids 1,150 mg/L) titrated with acid and base. significant increase in the amount of copper leached from tailings particles. This has a bearing on processes occurring in ORWB where pH values below 7.0 can occur. Mine-derived particles transported into ORWB would therefore be expected to release more copper into solution. Water type had a significant effect on copper release with leachable copper concentrations increased in the order: Bosset Lagoon W Fly River W Ok Mani (Fig. 9.8). The highest copper concentrations were attained in the samples containing the highest DOC concentrations and copper complexation capacities (CuCCs). It was therefore postulated that dissolved organic matter (DOM) played a role in the release of copper from mine-tailings particles. This important mechanism was proven experimentally by employing UV irradiation to destroy dissolved organic matter of the test waters prior to leach testing. A dramatic reduction in the amount of copper released into solution was observed in the leach tests using UV-irradiated waters (Fig. 9.9). Further experiments conducted on other tailings samples yielded similar results. The mechanism of copper release may involve the initial complexation of surface-bound copper by DOM followed by release of the Cu-DOM complex into solution. The composition of DOM and specifically, the nature of functional groups which are able to complex metals are potentially important factors in determining the extent of copper mobilization. It was hypothesized that stronger complex formation is observed with DOM derived from lowland floodplain sources (i.e., Fly River and Bosset Lagoon). Increasing the calcium concentration of the leach test waters


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Figure 9.10: Effect of dissolved calcium concentration on copper release from sample tailings sample T12. (Fly River water, tailings concentration 1 g/L, leaching time 18 h). (Fig. 9.10) did not enhance the release of copper from mine tailings. Ionexchange processes involving the displacement of copper ions from surface binding sites by other divalent cations are therefore unlikely to contribute significantly to copper release. Significant between-sample variability was observed in the amount of copper leached from the tailings (Fig. 9.8) showing that tailings composition played an important role in determining the amount of copper released into solution. The amount of copper released into solution was typically between 1 and 8% of the total copper present in the tailings particles. Statistical analysis of the data sets showed there were no significant correlations between the final concentration of copper measured in the leach tests and major element concentrations (including Cu, Mn and Fe, S) and particle size. Highly significant correlations (Po0.05) were however found between the fraction of copper that dissolved in cold, dilute nitric acid (acid-soluble copper, ASM-Cu) and the three sets of leach test data (Fly River: r ¼ 0.850, Ok Mani: r ¼ 0.755, Bosset Lagoon: r ¼ 0.800). Under the conditions adopted for the analysis of ASM-Cu (pH 2, 10 min extraction time), sulfide copper phases are insoluble (Svehla, 1987) and only oxidized forms of copper are measured (e.g., copper hydroxides and carbonates). The relationship between ASM-Cu and the Fly River leach test data is shown in Fig. 9.11. ASM-Cu concentrations ranged from 208


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Figure 9.11: Relationship between cold acid-soluble copper concentrations of the tailings samples (ASM-Cu) and the amount of copper released in the batch leach tests conducted with Fly River water. Dissolved Cu ¼ 0.020 [ASM-Cu]þ6.65. (r ¼ 0.850, po0.05). to 974 mg/g and were typically 35% of total particulate copper concentrations. Oxidation of copper sulfide minerals may occur either in the mine pit (on exposure to air) or during the processes of crushing and grinding of the ores. Over the pH range typically encountered in the river system, complexation by DOM was the most important single process determining the release of copper from mine-derived particulates observed in this study. The amount of copper released into solution depended on the concentration and composition of DOM and the amount of copper soluble in dilute acid in the tailings particles. Copper release from waste rock also occurs via the same mechanisms identified for mine tailings. While some waste rock types contain particulate copper concentrations comparable to mine tailings, the proportion of copper present in an oxidized form is generally much lower than in mine tailings (e.g., typically 10% ASM-Cu in waste rock samples compared to 30% ASMCu in tailings samples). This is because ore particles are subject to additional oxidation during mineral processing (e.g., during crushing and grinding) which increases ASM-Cu concentrations of the tailings particles. Nevertheless, waste rock particles may undergo oxidation during riverine transport, which will increase copper mobility.

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9.4. Riverine Processes This section considers the in-river geochemical transformations that affect copper geochemistry. Dissolved copper concentrations in the river are determined by a combination of geochemical processes during the 10–15 day transit time of suspended particulates through the river system. These processes include: copper release from mine-derived sediments, copper complexation by natural organic matter, sorption reactions involving natural and mine-derived sediments and copper sulfide oxidation. A conceptual model of copper transport and reactivity in the Fly River is presented in Fig. 9.12.

9.4.1. Copper Complexation by Dissolved Organic Matter To a large extent, dissolved copper concentrations in the river system reflect changes in the concentration and composition of DOM. CuCC comprises the concentration of organic ligands that are present in the sample and available to strongly complex copper. It is determined by titration of the sample with copper and, after an appropriate equilibration period, measurement of the Key dCu Dissolved Copper pCu Particulate Copper L Organic Ligand

L inputs from rivers and floodplain

dCu

dCu

dCu Cu

Cu Cu

Cu Cu

dCu,pCu

Cu Cu

Cu

Cu O2

desorption Cu + L

Cu

L

Cu Cu

organic complexation

oxidation

adsorption

dCu,pCu

CuL

Estuary

solution complexation

from upper river

dCu

Cu

Cu

M

dissolution

dCuL Cu

dCu Sedimentation and resuspension River Bed

diffusion pCu

dissolution

dCu in porewater

Figure 9.12: Conceptual model of copper cycling in the river system.


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uncomplexed copper (Apte et al., 2001). CuCC is an operationally defined parameter which is influenced by the measurement technique used to estimate uncomplexed copper. In the work described in this chapter, anodic stripping voltammetry (ASV) was used to measure CuCC. CuCC is lowest in the Ok Tedi and increases progressively downstream to a maximum in the Middle and Lower Fly (Fig. 9.13). The highest complexing capacities (30–50 mg/L) are found in the ORWB of the Middle Fly. These gradients in complexing capacity concentrations largely reflect changes in vegetation type, i.e., the transition from upland forest to lowland swamp, and the associated differences in dissolved organic matter production rates and inputs. OTML has routinely monitored CuCC at several sites in the river on a quarterly basis since 2002. Analysis of the data set to date (Rogers et al., 2005) indicates temporal variability, but no identifiable changes with time. The data analysis indicated little evidence of a relationship between flow and CuCC (Apte et al., 1999). The size distribution of copper complexing ligands present in filtered (o0.45 mm) water samples collected from the river system were characterized using a combination of equilibrium dialysis and differential pulse ASV (Apte et al., 2001). The proportion of CuCC associated with small molecular weight (o1,000 Da) ligands increased progressively from 40% in the upper catchment to 79% at lowland floodplain/wetland locations (Fig. 9.14). This

Complexing Capacity (µg/L)

40

30

20

10

n io ct un iJ

re Bu

ric kl St

Le w ad a

O gw a

er an

d

R

iv

O bo

Bo ss Bo et ss et La go on

ba Fl

y

uk N

at

um

ga un Ki

da on nk Ko

ge in N

O

k

M

ru

an

m

i

0

Figure 9.13: Typical copper complexation capacities of waters from the Fly River system. Locations are shown in Fig. 9.1.

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Copper Complexation Capacity (µg/L)

20 14,000 MWCO 15

10

5

0 Ok Mani

Kiunga

Oxbow 6

Lake Pangua

Sample

Figure 9.14: Variation of copper complexing capacity with molecular size fraction as determined by dialysis. The molecular weight cutoffs (MWCO) for the dialysis membranes used in the study are given in Daltons.

increase illustrated the role of the floodplain as a source of low molecular weight ligands to the river system. A significant proportion of copper complexation was also associated with ligands in the W14,000 Da fraction. As the majority of filterable iron was also found in this fraction, it is likely that this complexing pool contains organic ligands adsorbed to the surface of inorganic colloids as well as large molecular weight ligands. Destruction of dissolved organic matter by sample pretreatment with UV radiation resulted in a complete loss in CuCC detectable by ASV confirming that the observed complexation of copper was associated with organic ligands and not inorganic components of the samples.

9.4.2. In-River Oxidation of Copper-Containing Minerals On entry to the river system, typically 30% of the copper in the mine-derived sediments is present in an oxidized form as a result of oxidation processes that have occurred at the mine (e.g., during ore crushing and grinding). As noted earlier, oxidation of mine-derived copper sulfides to mineral forms that are more amenable to solubilization (e.g., malachite and amorphous copper


337

Table 9.2: Copper concentrations measured on river samples (January 1995). Site Ningerum Konkonda Nukumba Fly at Bosset Obo Ogwa Burei Junction

TSS (mg/L)

Dissolved Cu (mg/L)

2380 1150 170 118 7 124 58

12.7 8.5 12.4 13.8 8.6 2.3 3.4

Particulate Acid leachable Cu (mg/g) Cu (mg/g) 1190 1240 1400 1230 1580 159 158

328 534 809 970 1110 79 105

Acid leachable % of total Cu 28 43 58 79 71 50 67

hydroxide) is an important process which determines metal release into solution. Typical copper concentrations in dissolved and particulate phases in the Fly River are shown in Table 9.2. As can be seen, the proportion of ASM-Cu increases with distance from the mine. When river water samples from close to the mine were incubated under controlled conditions (temperature 301C, pH: 8.0–8.3), significant dissolved copper release was observed which was accompanied by an increase in ASM-Cu, indicating further oxidation of copper sulfides (Figs. 9.15 and 9.16). This experiment clearly indicated the role of in-river oxidation in the mobilization of copper from mine-derived particulates. Dissolved copper release and copper sulfide oxidation were markedly lower in sterile control samples demonstrating biological mediation (Figs. 9.15 and 9.16). Attempts to isolate the bacteria responsible for copper mineral oxidation were unsuccessful; however, laboratory investigations provided strong evidence that the copper sulfide oxidizing bacteria were chemolithotrophs (Simpson et al., 2005). The results suggest that such bacteria are naturally present in mineralized areas and are actively involved in the cycling of particulate copper between sulfide and hydroxy-carbonate forms, thus influencing the solubility and bioavailability of copper. It is well known that certain chemolithotrophic bacteria (e.g., Thiobacillus and Leptospirillum species) obtain energy from the oxidation of copper sulfide minerals at low pH (Nordstrom and Southam, 1997). However, these bacteria do not oxidize metal sulfides at pH values of greater than 6 (Kuenen et al., 1992; Blowes et al., 1995, 1998). The results point to a hitherto unidentified process affecting copper sulfide mineral stability in tropical river systems. The experiments demonstrated extensive biologically mediated copper

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35 Tabubil

30



35 25 20 15 10 5

Ningerum

30 25 20 15 10 5 0

0 0

4

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20

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24

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13



12 Time (days)

Time (days)

10 8 5 3 0 0

4

8

12 16 Time (days)

20

24

13 10 8 5 ARM 380

3 0

0

4

8

12 16 Time (days)

20

24

Figure 9.15: River water incubation experiments showing the variation of dissolved copper concentrations with time. The symbols represent the mean of duplicate treatments for the unmodified waters (K), and waters amended with formalin (3) and a single filtered water treatment ( ). The error bars encompass the range of duplicate measurements.

oxidation at pH 8.0–8.3 and provided a clear link between ASM-Cu concentrations and increasing dissolved copper concentrations. It is likely that these bacteria are particularly active in the Fly River system owing to the practice of in-river tailings disposal. The discharge of fine particles high in copper sulfide provides an ideal environment for these bacteria to flourish. The oxidation of sulfide minerals increases the reactivity of the solid copper phase, thereby making it easier for other processes (e.g., complexation by dissolved organic matter) to solubilize copper. The oxidation rates followed zero-order kinetics for the first 150 h, after which the oxidation processes appeared to be strongly inhibited presumably following the consumption of easily oxidizable solid copper sulfide phases or armoring of particles with insoluble oxidation products such as Fe- and Cu- hydroxy/ carbonate phases, sulfur or sulfates, which are slow to dissolve at circumneutral pH. Particle-size fractionation studies indicate that the bulk of the oxidation occurs in the o20 mm fraction. Copper release rates calculated from experimental data obtained during an extensive study in 1995 (Apte et al., 1995b) are summarized in Table 9.3.


339

700

700 Tabubil ASM-Cu (µg/g)

ASM-Cu (µg/g)

600 500 400 300

600 500 400 300

Ningerum

200

200 0

4

8

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16

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24

0

4

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700 600

ASM-Cu (µg/g)

ASM-Cu (µg/g)

Nukumba

500 400 300 200

0

4

8

12 16 Time (days)

20

24

600 500 400 300 200

ARM 380 0

4

8

12 16 Time (days)

20

24

Figure 9.16: River water incubation experiments showing the variation of acid-soluble copper concentrations with time. The symbols represent the means of duplicate treatments for the unmodified waters (K), and waters amended with formalin to eliminate bacteria (3). The error bars encompass the range of duplicate measurements.

Table 9.3: Dissolved copper release rates measured in sample incubation studies (5-day period). Site Ningerum Konkonda Nukumba Fly at Bosset

Release rate, mg Cu/g sediment/day 0.6270.06 0.2770.07 3.1371.01 Not detectable

9.4.3. Adsorption and Desorption Reactions Involving Copper As noted earlier, copper release from mine-derived particles occurs on initial contact of mine sediments with river water, slow release as a response to mineral oxidation, and changes in CuCC. An important step change in dissolved copper concentrations also occurs at the junction of the Fly River and Ok Tedi. Laboratory mixing tests (Apte et al., 1995b) demonstrated

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significant release of dissolved copper from mine-derived particulates when the Ok Tedi and Fly rivers join at D’Albertis Junction. The release of copper is rapid (less than 10 min to attain equilibrium). Instead of a dilution effect (40% Ok Tedi to 60% Fly River), dissolved copper concentrations increased from the expected value of 4 to 16 mg/L. This is the result of copper desorption from mine-derived particulates which is mediated by copper complexation by dissolved organic matter introduced by the upper Fly River. Copper adsorption from solution onto suspended sediments is also important in the river system. The results of adsorption experiments conducted on unfiltered water samples from the Fly River are shown in graphical form in Fig. 9.17 as a plot of the final dissolved copper concentration (after 18 h equilibration) versus the initial dissolved copper concentration (concentration measured in the filtered controls). The straight lines in the plots indicate the anticipated dissolved copper concentrations if no adsorption had taken place. In all experiments, extensive adsorption of inorganic copper was observed. A striking feature of the plots was the similar final copper concentration, irrespective of the initial amount of copper added. This illustrates the role of the sediments to ‘buffer’ dissolved copper concentrations and is a consequence of the large excess of particulate copper present in an exchangeable form. 9.4.4. Short-Term Variations in Dissolved Copper Concentrations OTML’s routine monitoring data for sites in the Ok Tedi and Fly River downstream of mine inputs are characterized by large fluctuations in dissolved copper concentrations with time (spiky data). For a long time, there was much speculation as to whether these trends were real, or simply reflected contamination during sampling and analysis. In order to resolve this problem, a 12-month intensive monitoring study was conducted in 1999 at Nukumba on the Fly River, followed by a further period of 4 months of intensive monitoring at Bige (located in the Ok Tedi). Samples were collected on an hourly basis for most of the study. The resulting dissolved copper data set is one of the most intensive ever produced by OTML. The study confirmed that the large variability inherent in OTML’s monthly monitoring data is indeed real (Fig. 9.18, Table 9.4). On some occasions, dissolved copper concentrations doubled within a period of several hours (Fig. 9.18). The study greatly altered the appreciation of the timescales of the processes affecting dissolved copper concentrations in the river system. The inherent variability of the dissolved copper concentration data indicates the pitfalls


341

90

Final dissolved Cu (µg/L)

Konkonda TSS: 1150 mg/L

60

30

0 0

30

60

90

Initial dissolved Cu (µg/L) 90

Final dissolved Cu (µg/L)

Fly, Bosset TSS: 118 mg/L

60

30

0 0

30

60

90

Initial dissolved Cu (µg/L)

Figure 9.17: Adsorption of dissolved copper added to unfiltered water samples from the river system. Samples were spiked with inorganic copper and equilibrated for 18 h prior to the measurement of dissolved copper. The straight lines indicate the expected dissolved copper concentrations if no adsorption had taken place.

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(a) 25

dCu (µg/L)

20

15

10

5 02/11/1999 02/01/2000 02/03/2000 02/05/2000 02/07/2000 02/09/2000 Date

30

(b)

dCu (µg/L)

25

20

15

10

5 21/11/2000

19/12/2000

16/01/2001

13/02/2001

Date

Figure 9.18: (a). Time series plot of hourly dissolved copper concentrations at Nukumba (352 days of data with a range of 6–22 readings taken per day). (b). Time series plot of hourly dissolved copper concentrations at Bige. Ninety-five days of data with approximately 18 readings taken per day are depicted.


343

Table 9.4: Intensive monitoring study: summary statistics of dissolved copper concentrations (mg/L) of each of the months of sampling at Nukumba. Month January February March April May June July August September October November December All data

Minimum

Median

Maximum

Mean

Variance

5.0 7.9 6.4 8.7 9.0 9.3 8.5 6.4 6.9 11.7 6.1 6.8 5.0

13.0 13.0 14.0 13.2 14.2 13.5 15.4 15.9 12.0 11.5 13.2 17.3 13.6

20.0 21.1 25.8 22.9 26.2 22.1 19.6 23.4 22.5 27.4 25.4 21.0 27.4

13.6 13.4 14.4 13.9 15.1 16.0 12.2 11.8 13.5 17.8 13.5 12.9 13.9

8.3 4.6 15.4 8.7 8.1 5.0 3.6 4.7 11.4 12.8 7.7 5.4 9.9

associated with the interpretation of trends in dissolved copper concentrations based on low-frequency sampling (e.g., monthly monitoring data). Failure to take into account the variability that occurs at timescales of hours and days may result in erroneous or biased interpretation. The application of time series analysis techniques (Shao et al., 2002) failed to detect any noteworthy cyclic or noncyclic trends in the data at hourly, daily, weekly, and monthly timescales. No strong correlations between dissolved copper concentrations and river level or mine production data such as waste rock output and waste rock type could be found. However, some correlations between dissolved copper concentrations and rainfall were observed at Bige when time lags were incorporated into predictive regression models. This could involve the rainfall-related release of dissolved copper from stored dredge material as well as from deposited sediments located on the river banks and adjacent floodplain. The climatic conditions encountered during the studies described earlier were characteristic of a ‘wet’ phase. As a result, the data set does not provide information on dissolved copper concentrations that may develop in the system under ‘dry’ climatic conditions. OTML’s monitoring data following the El Ninõ period of 1996–1997 provides a very good indication of climatic effects, and shows elevated dissolved copper concentration in the Ok Tedi and Middle Fly following the cessation of the dry period. For instance, concentrations as high as 48 mg/L were recorded at Obo on the Middle Fly

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during early 1998. These elevated copper concentrations may result from aerial oxidation of exposed riverine sediments and release of copper on rewetting. Indeed, recent fieldwork by OTML has confirmed this with dissolved copper concentrations up to 44,000 mg/L in porewaters collected from an area subject to acid generation (B. Bolton, personal communication, May 2006). This illustrates the importance of catchment processes and the role of stored sediments as a potential source of dissolved copper. The impacts of dry weather events (including El Ninõ) on dissolved copper concentrations still remains a concern for OTML. The possible causes of copper spikes may also include reactive minerals discharged infrequently from the mine (e.g., skarn ores) and ARD-related groundwater inputs. The speciation of copper during spike events has not been determined, but copper spikes are likely to be highly bioavailable especially when CuCC concentrations are exceeded.

9.5. Copper Cycling in Floodplain and Off-river Water Body Environments The 2,400 km2 floodplain of the Middle Fly River is relatively narrow, widening from ca. 4 km near Kiunga to over 14 km near Everill Junction. The inner floodplain contains numerous oxbow lakes whereas the outer floodplain is composed of backswamps and blocked valley lakes. Before extensive forest die-back occurred, the floodplain was covered with dense vegetation with little exposed sediment. The high annual rainfall in the headwaters of the Fly River and Ok Tedi result in periodic flooding of the Middle Fly floodplain, as well as inundation of over some 118 ORWB. Typically, floodplain areas can be covered to a depth of 2–3 m for periods of up to 8 months before the waters recede. In the early 1990s, an investigation conducted by OTML confirmed significant deposition of mine-derived sediments as a network across the floodplain during flooding events (Day et al., 1993). ORWB are also recipients of mine-derived sediments during these periods of floodplain inundation, particularly when there is high river flow and low standing water on the floodplain. Subsequent studies were conducted to assess the stability of mine-derived copper deposited on the floodplain and in ORWB. A key concern was the stability of the deposited particulate copper and the potential for copper release into solution. This problem was addressed by use of sediment porewater dialysis peepers (Teasdale et al., 1995) which were deployed to measure in situ depth profiles of dissolved copper across the


345

sediment/water interface (Apte et al., 1993, 1995b). This approach allowed a field-based assessment of copper mobilization. Field deployments of porewater peepers were carried out during June 1994 and January 1995 at established ORWB and flooded floodplain sites. Details of porewater peeper sampling procedures may be found in the review by Teasdale et al. (1995). Briefly, each peeper comprised a narrow rectangular acrylic block with 96 water-filled slots located 1 cm apart down the length of the peeper. Both sides of the peeper were covered by a porous polysulfone membrane (0.45 mm pore size). At each site, a number of peepers were positioned in the sediments with about 75% of the peeper chambers below the sediment–water interface. The peepers were then allowed to equilibrate for a period of at least 14 days, during which time dissolved species diffused across the semipermeable membranes, after which they were recovered and sampled immediately. Sediment cores were also collected at each site. The particulate copper profiles of sediment cores at each site (Fig. 9.19) confirmed elevated particulate copper concentrations in the surficial sediments at all sites. Mine-derived copper signatures were detectable to depths of over 30 cm at many sites (Fig. 9.19). Dissolved metal concentrations of the overlying waters are shown in Table 9.5. During the time of the study, the floodplain was covered with river water (as indicated by the dissolved calcium concentrations) with copper concentrations typical of the Middle Fly. Peeper profiles of dissolved copper, iron, and manganese are shown in Figs. 9.20 and 9.21. Porewater copper concentrations were generally lower than dissolved copper concentrations found in the overlying water column. The peeper profiles indicated a net downward flux of copper from the water column to the sediments. These profiles clearly indicate that there was little detectable mobilization of particulate copper in porewaters, rather, the key process was removal of dissolved copper from the water column. Dissolved iron and manganese concentrations were consistently higher in the deeper sediment porewaters and decreased toward the sediment–water interface. This is consistent with the bacterially mediated reductive dissolution of iron and manganese oxyhydroxides in the anoxic sediment layers (Davison, 1993; Hamilton-Taylor et al., 1996). At some sites, it is evident that the maximum production of these dissolved species occurs close to the sediment–water interface. This probably reflects the natural abundance of bacteria capable of reducing particulate iron and manganese to their soluble lower oxidation sites. Dissolved iron and manganese concentrations decreased dramatically above the sediment–water interface but were detectable in measurable quantities indicating significant diffusion of these species from the porewaters to the overlying waters (Table 9.5).

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Floodplain 15

Depth (cm)

0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50

0

200

400 600 800 1000 Particulate Copper (µg/g)

1200

Lake Pangua: tie-channel

Depth (cm)

0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50

0

200 400 600 800 Particulate Copper (µg/g)

1000

Lake Pangua: floodplain 0-5

Depth (cm)

5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45

0

100

200

300

400

500

600

Particulate Copper (µg/g)

Figure 9.19: Particulate copper profiles in floodplain and ORWB sediment cores (January 1995). Refer to Fig. 9.1 for site locations. At some sites, very localized high-concentration spikes of dissolved copper were observed at depth. These cannot be attributed to contamination as they were observed in replicate peeper measurements. The precise reason for this localized copper mobilization at depth is currently unknown. These events are very localized and do not give rise to significant fluxes of dissolved copper to the overlying waters.


347

Table 9.5: Dissolved metals and suspended solids in overlying waters during the 1995 peeper deployment. Site

Sample location

Ca (mg/L)

Cu (mg/L)

Fe (mg/L)

Mn (mg/L)

Floodplain 15 (Water depth 1.8 m)

Surface Middle Bottom

26.4 26.5 26.5

19.8 18.7 17.9

79 69 106

o2 o2 3

L. Pangua: Tie-channel (Water depth 1.6 m)


24.3 23.9 24.6

15.6 15.7 16.5

58 63 59

14 o2 o2

L. Pangua: Floodplain (Water depth 1.6 m)


23.0 22.5 22.4

12.2 11.2 10.6

63 60 65

o2 o2 o2

The flooded floodplain and ORWB which have received mine-derived inputs appear to act as a sink for copper rather than a source to the overlying water column. The absence of any net fluxes of copper from the sediments to the water column, despite very high particulate copper concentrations, suggests that sediment-bound copper is stabilized in an unreactive form (possibly as sulfides) in the deeper anoxic sediments. A proposed model of copper cycling on the floodplain and ORWB is shown in Fig. 9.22. It is hypothesized that the natural iron cycle (and possibly the manganese cycle) plays a major part in controlling dissolved copper concentrations under wet conditions. The removal of dissolved copper from the water column is considered to take place by adsorption onto iron(III) oxyhydroxides generated close to the sediment–water interface. Based on the peeper profiles, quantitative estimates of the times for a major reduction in copper concentration in the ORWB were calculated (Apte et al., 1995b). It was estimated that it would take between 7 and 28 years for dissolved copper concentrations to return to pre-mining levels. It should be noted however, that the studies described in this section were conducted under flooded floodplain conditions. The stability of copper in floodplain sediments during prolonged periods of drought and release of copper during postdrought flooding has not been studied. Hot, dry climatic conditions may lead to the aerial oxidation of reduced particulate copper phases (e.g., copper sulfides), which in turn increases the potential for subsequent release into solution on contact with flood waters. Such release may be episodic and may well be greatest during the first flood event after a

Copper -25

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Figure 9.20: Porewater depth profiles obtained using dialysis peepers of dissolved copper, iron, and manganese at the Floodplain 15 site (January 1995).

Copper -25

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Peeper 2

25 50 75

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349

Figure 9.21: Porewater depth profiles obtained using dialysis peepers of dissolved copper, iron, and manganese at the Lake Pangua tie-channel site (January 1995).


Depth (cm)

-25

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Figure 9.22: Conceptual model of copper cycling in ORWBs and areas of the floodplain subject to frequent inundation. prolonged dry period. Clearly, extensive copper release during the first floods that follow a prolonged El Ninõ event is a potential cause for concern. Riverine-dissolved copper concentrations in the middle Fly are likely to be at their highest under this climatic scenario.

9.6. Copper Cycling in the Fly River Estuary 9.6.1. Background to the Estuary The Fly River Estuary and delta region (Fig. 9.23) cover an area of approximately 7,100 km2 (Salomons and Eagle, 1990). The estuary is split into southern, northern, and far northern channels and is partially stratified with an average water depth of less than 8 m. Between 60 and 80% of the freshwater flows through the southern channel (Wolanski et al., 1995), and saline water usually intrudes no further than the junction of the three channels. The estuary is subject to large tides and is very turbid (Wolanski and Eagle, 1991). The sediment inflow to the estuary before mining commenced was estimated to be 85 106 tonnes/yr and has increased with mining to 120 106 tonnes/yr, about 90% of which moves as suspended load (Wolanski et al., 1992). As a result of mine-derived sediment inputs, riverine end-member concentrations of dissolved and particulate copper in the Fly River Estuary have increased since pre-mining times from approximately 0.5 to 5 mg/L and


351

Bamu Estuary Site TM

Feb 93 July 93 March 94

0

40 km

Figure 9.23: Map of the Fly River estuary showing sampling locations.

40 to 300 mg/g, respectively (Apte et al., 1995b). From the start of mining, the estuary was noted as a potential sink for mine-derived sediments and an important transition zone in terms of the physical and chemical processes that may affect copper mobilization. The processes affecting the behavior and speciation of copper in the Fly River Estuary were subsequently investigated through a combination of field studies and laboratory modeling experiments carried out during the first half of the 1990s. Four extensive field surveys were conducted over the period February 1993 to March 1994. The first two surveys focused on determining surface-waterdissolved copper concentrations throughout the estuary, and the chosen sampling sites represented a compromise between a good spatial coverage of the estuary (e.g., all three channels) and the sampling waters over the full salinity range (Fig. 9.23). The March 1994 survey focused on determining

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depth profiles of dissolved and particulate copper at key locations. In March 1995, additional field studies were conducted to elucidate the mechanism of copper removal in the low-salinity zone of the estuary. In order to avoid sample contamination and erroneously high results, ultratrace sampling and analysis protocols were used throughout the study. To avoid metal contamination, surface water samples were collected using a small dinghy positioned approximately 100 m upstream of the main ship. Surface water samples were collected from a depth of approximately 0.5 m below the surface. Suspended sediment profiles obtained during the surveys (Fig. 9.24) illustrate the turbid nature of the Fly River Estuary with concentrations ranging from 2 to 2,100 mg/L. The pH of estuarine waters varied in a consistent manner between surveys with a marked increase of 0.1–0.4 pH units in the 0–1 salinity range followed by a more gradual increase over the remaining salinity range (Fig. 9.25). Suspended particulate copper concentrations dropped sharply from greater than 200 to 100 mg/g in the 0–1 salinity region and then dropped to a concentration of 57714 mg/g at salinities W12 (Fig. 9.26). This sharp decrease in particulate copper concentration in the low-salinity zone of the estuary was attributed to a rapid and efficient mixing of mine-derived particulates with natural suspended particulate material low in copper. In July 1993, the decrease in particulate copper concentration was coincident with the presence of a turbidity maximum in the low-salinity region of the estuary; however, in the March 1994 survey, a turbidity maximum was not visible and yet the same sharp decrease in particulate copper concentrations was observed. This indicated that there were sufficient estuarine particulates in solution to dilute mine-derived particulates at all tidal states. The suspended particulate copper concentrations in midestuary are comparable with particulate copper concentrations of 12–71 mg/g in benthic sediments from the Fly River Estuary (Alongi et al., 1991; Baker and Harris 1991). It should be noted that particulate metal concentrations vary with changes in particle size. Generally, metal concentrations are inversely related to particle size. Dissolved copper displayed a remarkably consistent relationship with salinity throughout the surveys (Fig. 9.27). A rapid decrease in dissolved copper concentration was observed in the very low-salinity region of the estuary (0–3), which accounted for the removal from solution of typically 50% of the river-borne dissolved copper. Over the rest of the estuarine salinity gradient, dissolved copper could be explained by dilution alone (conservative behavior), decreasing in a linear fashion with increasing salinity. Despite variations in riverine copper concentrations, the proportion of dissolved copper removal observed over the three main surveys was quite


353

2500

(a)

TSS (mg/L)

2000 1500 1000 500 0 0

5

10

15 Salinity

20

25

30

1000

(b)

TSS (mg/L)

800 600 400 200 0 0

5

10

15

20

25

30

Salinity 250

(c)

TSS (mg/L)

200 150 100 50 0 0

5

10

15

20

25

30

Salinity

Figure 9.24: Total suspended solids versus salinity: (a) February 1993, (b) July 1993, (c) March 1994 (all depths).

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8.2 Feb-93

Jul-93

Mar-94

8

pH

7.8 7.6 7.4 7.2 7 0

5

10

15 Salinity

20

25

30

Figure 9.25: Surface water pH versus salinity: (’) February 1993, (7) July 1993, (K) March 1994.

300

Particulate Cu (µg/g)

Jul-93

Mar-94

200

100

0 0

5

10

15

20

25

30

Salinity

Figure 9.26: Particulate copper versus salinity. similar. No marked difference in dissolved copper behavior was observed between the three main channels and little variation of dissolved copper concentration with depth was noted that could not be accounted for by differences in salinity. Depth profile samples (March 1994) collected at nine estuarine sites (Fig. 9.23) (data not shown) also failed to indicate any systematic increase or decrease in dissolved copper with depth that could be attributed to remobilization from sediments or scavenging onto suspended sediments (Apte et al., 1995b). In spite of the size of the estuary and the


355

5 (a) Dissolved Cu (µg/L)

4

3

2

1

0 0

5

10

15

20

25

30

35

Salinity 5 Dissolved Cu (µg/L)

(b) 4

3

2

1

0 0

5

10

15

20

25

30

35

Salinity 12 Dissolved Cu (µg/L)

(c) 10 8 6 4 2 0 0

5

10

15

20

25

30

35

Salinity

Figure 9.27: Dissolved copper versus salinity: (a) February 1993, (b) July 1993, (c) March 1994 (all depths).

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complexity of its physical structure, dissolved copper concentrations were largely determined by salinity and were not appreciably influenced by changes in suspended sediment concentration. Substantial removal of CuCC from solution was observed at low salinity (probably through precipitation of humic materials) (Fig. 9.28). The DOC versus salinity profiles (Fig. 9.29) also showed nonconservative behavior with removal occurring over the 0–15 salinity range. The differences in behavior between DOC and CuCC are consistent with the organic ligands comprising 20

CuCC (µg/L)

15

10

5

0 0

5

10

15

20

25

30

35

Salinity

Figure 9.28: Copper complexing capacity versus salinity (July 1993 survey). 4 Feb-93

Jul-93

DOC (mg/L)

3

2

1

0 0

5

10

15

20

25

30

35

Salinity

Figure 9.29: Dissolved organic carbon versus salinity: (’) February 1993, (7) July 1993.


357

the CuCC being only a small subset of DOC. Mantoura and Woodward (1983) noticed similar relationships in the Severn Estuary, UK. Humic materials precipitate in the low-salinity zone, but DOC remained conservative (Mantoura and Woodward, 1983). Despite the elevated copper inputs, complexing capacity was still in excess of dissolved copper and copper organic complexes are the major solution species. The change in CuCC concentrations with salinity were similar to the changes observed in dissolved copper concentrations. This may involve precipitation of complexing ligands and removal from solution. 9.6.2. Mechanisms of Dissolved Copper Removal Laboratory simulations of estuarine processes were carried out in order to understand the relative importance of flocculation and adsorption as controls of dissolved copper concentrations. The flocculation of dissolved organic matter and iron which often occurs in the low-salinity regions of estuaries (Sholkovitz, 1976, 1978) may reduce dissolved copper concentrations through coprecipitation of copper (and possibly the coagulation of copper–organic complexes). Dissolved copper may also be adsorbed onto estuarine particulates, particularly in the turbidity maximum region. Metal adsorption processes may also be enhanced by the slight but consistent increase in pH in this region. Conversely, the increase in the concentration of calcium and magnesium with salinity may increase the competition for binding sites and lead to the desorption of copper from particulate material. In order to reduce sampling artefacts, all experiments were conducted onboard ship within hours of sample collection. Flocculation experiments were performed with both filtered and unfiltered river water. The experiments involved mixing known quantities of river water and seawater together to give a final salinity of 6, followed by measurement of dissolved metal concentrations. The chemical characteristics of the samples used are summarized in Table 9.6. The tests indicated extensive precipitation of iron and appreciable coremoval of copper at low salinities (Table 9.7). The amount of iron removed from solution varied from 90% in the unfiltered experimental treatment to 76% in the filtered treatment. This suggests that the presence of natural particulate material enhances the coagulation of iron colloids. The precipitation of copper was less affected by the presence of particulate material with 23% removal occurring in the filtered water experiment compared to 30% removal with unfiltered solutions. The 30% removal in laboratory experiments compares to typically 50% removal as observed in the three field surveys.

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Table 9.6: Typical composition of low-salinity region samples (collected during March 1995). Parameter

Site Lewada

TM

176 o0.01 7.50 6.8 26.3 133 100 75

164 0.27 7.72 4.2 25.9 121 86.0 71

TSS (mg/L) Salinity PH Dissolved Cu (mg/L) Copper complexing capacity (mg/L) Particulate Cu (mg/g) Acid-soluble copper (mg/g) % ASM/pCu

Table 9.7: Results of the estuarine mixing experiments (24 h equilibration). Sample

Treatment

Dissolved Fe (mg/L)

Dissolved Cu (mg/L)

Filtered water

Control Final (n ¼ 5)

29.872.0 7.170.4

4.070.2 3.170.3

Unfiltered water

Control Final (n ¼ 5)

56.671.4 5.570.3

4.770.2 3.370.1

Note: 100 mL aliquots of river water (Lewada) were mixed with 20 mL of seawater to give solutions with a final salinity of approximately 6. The solutions were mixed on a bottle roller for 24 h, filtered through 0.45 mm membrane filters, and subsequently analyzed for dissolved metals.

The adsorption of copper onto estuarine suspended material was also evaluated in laboratory experiments. These tests used samples taken from a brackish water location (Site TM, Fig. 9.23, 0.27 salinity) and at Lewada. The mean particle-size diameters, measured by laser particle sizing were 9.2 and 7.2 mm for Lewada and TM, respectively. The adsorption experiment (Fig. 9.30) showed that estuarine sediments have a strong affinity for dissolved copper. A release of copper relative to the filtered controls was observed in the zero copper addition experimental treatment which may be explained by disaggregation of particles during agitation and generation of colloidal particles small enough to pass through the 0.45 mm membrane filters. The proportion of dissolved copper removed from solution actually increased with the concentration of dissolved copper added, from 20% at the lowest added copper concentration to 52% at the highest spiked concentration. The observed increase in adsorptive affinity with added copper concentration


359

Final Dissolved Cu (µg/L)

25

20

15

10

5

0 0

5

10 15 Initial Dissolved Cu (µg/L)

20

25

Figure 9.30: Adsorption of copper onto estuarine particulates in the lowsalinity zone of the estuary. Note that the straight line indicates the expected dissolved copper concentration if no adsorption had taken place. Adsorption of copper onto estuarine suspended material was tested onboard the ship. 20 mL aliquots of filtered river water (Lewada) were spiked with copper and equilibrated for 2 h. A 180 mL portion of sample TM (salinity 0.27, suspended sediment concentration 164 mg/L) was added to each container to give a final concentration of 200 mL. The samples bottles were placed on a bottle roller for 24 h, after which the solutions were filtered and analyzed for dissolved copper. All samples and filtered controls were prepared in triplicate. could be explained by changes in copper speciation in solution, in particular the increase in concentration of inorganic copper species. Partition coefficients, Kd ([particulate copper (mg/g)]/[dissolved copper (mg/L)] were calculated for the samples collected during the March 1994 survey. Above salinity W5, there was a significant increase in Kd with salinity (Fig. 9.31) which implies that the adsorptive affinity of particulate material increased with increasing salinity. This cannot be explained by any of the processes identified during the field and laboratory modeling studies. Despite being used widely in estuarine studies, the partition coefficient approach has several criticisms. The speciation of copper is ignored, and this form of analysis assumes that the particulate copper is fully exchangeable with the dissolved fraction which is not necessarily the case. For example, the ASM-Cu concentrations measured on the estuarine particulates (Table 9.6) indicate that about 70% of the particulate copper is present in an oxidized (exchangeable) form. Not all of this fraction will be exchangeable with the solution phase.

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S. C. Apte

100000 Jul-93

Mar-94

5

10

Kd (L/kg)

80000

60000

40000

20000

0 0

15

20

25

30

Salinity (‰)

Figure 9.31: Kd versus salinity (July 1993 and March 1994 data). Overall, the modeling experiments indicated that the removal of copper in the low-salinity zone of the estuary can be attributed to a combination of flocculation and adsorption onto estuarine particulates. A combination of efficient particle mixing and the substantial removal of dissolved copper at low salinity significantly attenuates the impacts of mine-derived sediments on the Fly River Estuary and surrounding coastal waters. The ability of the estuary to attenuate mine-derived impacts will depend on the size of the pool of natural suspended sediments available to dilute the mine-derived sediments. Sediment transport studies (Wolanski et al., 1996) suggest that there is significant input of silt-sized particulates from the Gulf of Papua via the Northern Channel which replenishes the estuarine particulate pool. The magnitude of this flux is much greater than the input of sediments from the Fly River (about sevenfold greater). These observations suggest that the capacity of the estuarine sediments to dilute the mine-derived sediments will not change significantly over mine life.

9.7. Modeling of Copper Geochemistry Geochemical modeling involves the use of mathematical models based on fundamental thermodynamic and in some cases kinetic concepts to calculate


361

the concentration and chemical forms of an element under specified conditions. In the context of aquatic systems, this includes the distribution between dissolved and particulate phases and the chemical forms (speciation) of the element that exist in solution. The prediction of the behavior of metals in river systems requires detailed knowledge of both the chemical processes, the hydrology of the system, and the movement of sediments. Attempts to model the chemistry of the Fly River date back to the late 1980s. The Fly River model (Kersten and Kerdijk, 1991) was an interactive computer model specifically developed as a management tool to assess the effects of mine tailings and overburden from the Ok Tedi mine. The model was based on the general purpose model CHARON (Chemistry Applied to the Research of Natural systems) developed by Delft Hydraulics (de Rooij and Kroot, 1991) which combined chemical equilibrium, slow reaction kinetics, and water–sediment transport submodels. The critical geochemical parameters determining the distribution of copper between dissolved and particulate phases were assumed to be: the adsorbing capacity of the suspended matter, the amount of exchangeable copper on the particles, and the chemical composition of the water (e.g., dissolved organic matter and pH). Calculations were performed in 1988 (OTML, 1988) and predicted the potential effects of tailings and waste rock disposal on the river system from 1987 to 2008. Dissolved copper predictions were satisfactory during the cyanide phase of mine operation because all available copper was complexed by cyanide and remained in solution. Dissolved copper concentrations in this period were therefore driven by river flows. In 1991, following the transition from the ‘cyanide’ to ‘copper’ phase of mine life, deficiencies in the predictive capabilities of the Fly model were recognized. In particular, the model significantly underpredicted dissolved copper concentrations at key monitoring sites. A major assumption of predictions was the concept of fixed reactivity of mine-derived particulate copper. A ‘site specific’ version of the Fly model was used in 1992 (OTML, 1992) to predict annual average dissolved copper concentrations at Kuambit, Obo, and Ogwa during 1992–1996. The model was calibrated with mean monitoring data from the 1991 calendar year. It was recognized however that modeling could not be successful if the system was treated as a ‘black box.’ From August 1998 to May 1999, a 10-month intensive study was carried out to develop a predictive mechanistic model for the assessment of various mine-waste retention schemes. The investigations described earlier in this chapter provided a platform for a more sophisticated, mechanistic approach to modeling copper geochemistry. The resulting OkCSIRO geochemical model incorporated the key chemical processes of complexation,

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S. C. Apte

partitioning, and sulfide mineral oxidation. The geochemical model was used to predict annual average concentrations of dissolved copper, dissolved inorganic copper (bioavailable copper), and particulate copper at sites in the river system for the period 1990–2052. The model considered eight sites along the Ok Tedi and Fly Rivers: Ningerum, Konkonda, Nukumba, Bosset, Obo, Ogwa, Burei Junction, and Lewada. The model utilized a single pH-dependent, site-specific partition coefficient which described the partitioning of inorganic copper between solid and solution phases coupled with a single ligand complexation model describing copper binding by natural organic matter in solution. The model input data were: (i) Predicted suspended sediment concentrations at each site (split into tailings, waste rock, valley wall erosion, and natural riverine sediments at each site): These were obtained from the Parker sediment transport model (developed for OTML by Professor Gary Parker, University of Minnesota, St. Anthony Falls Laboratory). (ii) Information from the OTML mine plan on the future copper concentrations of mine tailings and waste rock: This information was derived from the mine production schedule data supplied by OTML which provided the tonnages and annual average copper content of waste rock and tailings. The o63 mm suspended sediment fraction predicted by the sediment transport model was assigned as the TSS concentration at each site. As noted in previous studies (Apte et al., 1999), particulate copper concentrations increase with decreasing particle size. The mine plan information on copper concentrations in bulk mine tailings and waste rock was therefore likely to underestimate the copper concentration of suspended sediments in the river system because of the presence of coarse particulates. In order to overcome this problem, a conversion factor was developed to predict the pCu o63 mm concentration in both the waste rock and tailings solids fractions. This was derived from the observed relationship between total copper and particulate copper in the o63 mm fraction of waste rock and tailings samples. A very consistent linear relationship was observed between total particulate copper and the copper present in the o63 mm fraction (Fig. 9.32). Both tailings and waste rock obeyed the same relationship. (iii) River flow data (real and synthetic) for the period 1992–2052: The same flow data was used in both the Parker sediment model and OkCSIRO. The synthetic flow data was constructed from OTML hydrological monitoring data and comprised a predetermined sequence of annual hydrological data for 1996 (wet), 1992 (dry), 1994 (normal), and 1997 (El Ninõ).


363

(iv) Annual average values of water pH at each site: These were derived from OTML monitoring data (Table 9.8). (v) ASM-Cu: This is the concentration of particulate copper that is oxidized and most likely exchangeable with the solution phase. It is calculated from the total copper concentration using a site-specific reactivity parameter (i.e., the %ASM-Cu), which increases with distance from the mine. A fixed value of %ASM-Cu was assigned for each site. The values were derived from previous CSIRO monitoring data where ASM-Cu and pCu 6000

pCu

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