Handbook for the Assessment of Soil Erosion and Sedimentation Using Environmental Radionuclides

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Handbook for the Assessment of Soil Erosion and Sedimentation Using Environmental Radionuclides

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Handbook for the Assessment of Soil Erosion and Sedimentation Using Environmental Radionuclides Edited by

F. Zapata Joint FAO/IAEA Division, International Atomic Energy Agency, Vienna, Austria

KLUWER ACADEMIC PUBLISHERS NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW

eBook ISBN: Print ISBN:

0-306-48054-9 1-4020-1041-9

©2003 Kluwer Academic Publishers New York, Boston, Dordrecht, London, Moscow Print ©2002 Kluwer Academic Publishers Dordrecht All rights reserved No part of this eBook may be reproduced or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, without written consent from the Publisher Created in the United States of America Visit Kluwer Online at: and Kluwer's eBookstore at:

http://kluweronline.com http://ebooks.kluweronline.com

CONTENTS Foreword W. Burkardt

vii

Facts Relating To The Co-ordinated Research Projects

ix

Summary

xi

1. Introduction F. Zapata, E. Garcia-Agudo, J.C. Ritchie and P.G. Appleby

1

2. Site Selection and Sampling Design D.J. Pennock and P.G. Appleby

15

3. Sampling Methods R.J. Loughran, P.J. Wallbrink, D.E. Walling and P.G. Appleby

41

4. Sample Processing D.J. Pennock and P.G. Appleby

59

5. Radionuclide Measurement Using Hpge Gamma Spectrometry P.J. Wallbrink, D.E. Walling and Q. He

67

6. Spatial Distribution of Caesium-137 R.J. Loughran, D.J. Pennock and D.E. Walling

97

7. Conversion Models For Use In Soil-Erosion, Soil-Redistribution and Sedimentation Investigations D.E. Walling, Q. He and P.G. Appleby 8. Special Considerations For Areas Affected By Chernobyl Fallout V.N. Golosov

111 165

9. Alternative Methods and Radionuclides For Use In Soil-Erosion and Sedimentation Investigations Q. He, D.E. Walling and P. J. Wallbrink

185

Contributing Authors

217

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FOREWORD This publication deals with soil erosion and sedimentation. Soil erosion and associated sediment deposition are natural landscape-forming processes that can be greatly accelerated by human intervention through deforestation, overgrazing, and non-sustainable farming practices. Soil erosion and sedimentation may not only cause on-site degradation of the natural resource base, but also off-site problems— downstream sediment deposition in fields, floodplains and water bodies, water pollution, eutrophication and reservoir siltation, etc.—with serious environmental and economic impairment. There is an urgent need for accurate information to quantify the problem and to underpin the selection of effective soil-conservation technologies and sedimentation-remediation strategies, including assessment of environmental and economic impacts. Existing classical techniques to document soil erosion are capable of meeting some of these needs, but they all possess important limitations. The quest for alternative techniques for assessing soil erosion, to complement existing methods, directed attention to the use of environmental radionuclides, in particular fallout as tracers to quantify rates and establish patterns of soil redistribution within the landscape. The concept of a project on the use of environmental radionuclides to quantify soil redistribution was first formulated at an Advisory Group Meeting convened in Vienna, April 1993, by the International Atomic Energy Agency (IAEA). Based on the recommendations of this meeting, two inter-disciplinary Co-ordinated Research Projects (CRPs) were formulated: a CRP on “Assessment of soil erosion through the use of the and related techniques as a basis for soil conservation, sustainable production and environmental protection” co-ordinated by the Joint FAO/IAEA Division, and another CRP on “Sedimentation assessment studies by environmental radionuclides and their application to soil conservation measures” organized by the Division of Physical and Chemical Sciences. The IAEA provided the core funding for the projects, which were implemented during the period 1995 to 2000. This handbook contains the developments made in the refinement and standardization of the technique for the assessment of soil erosion and sedimentation by both research networks. These networks comprised scientists from research institutions in Argentina, Australia (2), Brazil, Canada (2), Chile, China (2), France, Greece, Morocco (2), New Zealand, Poland, Romania (2), Russian Federation, Slovakia, Spain, Thailand, United Kingdom, United States of America, and Zimbabwe. The overall objective of the projects was to develop guidelines for estimating soil erosion and sedimentation for sustainable agricultural production and environmental protection. The specific research objectives were: i) to refine (including validation and standardization) relevant methodologies for documenting soil erosion and sedimentation using the technique across a range of environments, ii) to use the refined technique to test and calibrate existing models of soil erosion, and iii) to evaluate the effects of specific land-management approaches on soil erosion to provide data to underpin the selection of soil-conservation strategies. vii

The launching of these two closely linked IAEA research networks and the coordination meetings brought together twenty-five research groups and promoted exchange of ideas and sharing of experiences, thus making a major contribution to the further development of the technique. Much of the initial work focused on validating the approach worldwide in different environments, and on developing standardized protocols and refining procedures. As the efficacy and the value of the technique was increasingly recognized, the participants exploited the potential of the technique in a wide range of studies, including further applications. As the application of the technique required a multi-disciplinary team of trained technical staff and functional laboratory facilities for measuring activities, the IAEA supported exchanges of scientists among the various research groups and the training of young scientists at laboratories where there was experience in the application of the technique. The participants have published over one hundred papers and one special issue of Acta Geologica Hispanica; a special issue of Soil and Tillage Research is in preparation. These publications contain valuable information that should assist Member States to gather reliable information on erosion problems and to design appropriate control strategies. These projects promoted various follow-up activities such as the continuation of research on the use of environmental radionuclides by extending the approach to and to obtain erosion rates and soil-redistribution patterns on several spatial and time scales. The information contained in this book will provide scientists working in soil erosion and sedimentation newly developed research tools to collect soil-redistribution inventories, and pilot-test interventions to combat soil erosion and associated sedimentation, towards the ultimate goal of sustainable resource use and environmental protection. W. Burkart Deputy Director General Head of the Department of Nuclear Sciences and Applications

viii

FACTS RELATING TO THE CO-ORDINATED RESEARCH PROJECTS “ASSESSMENT OF SOIL EROSION THROUGH THE USE OF AND RELATED TECHNIQUES AS A BASIS FOR SOIL CONSERVATION, SUSTAINABLE PRODUCTION AND ENVIRONMENTAL PROTECTION” 1996–2001 “SEDIMENTATION ASSESSMENT STUDIES BY ENVIRONMENTAL RADIONUCLIDES AND THEIR APPLICATION TO SOIL CONSERVATION MEASURES” 1995–2000 FINANCIAL SUPPORT IAEA Regular Budget through the Research Contract Programme (1995–2000 / 1996–2001) CO-ORDINATION F. Zapata Co-ordinator, Soil Erosion Project Soil and Water Management & Crop Nutrition Section Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture E. Garcia Agudo Co-ordinator, Sedimentation Project Isotope Hydrology SectionDivision of Physical and Chemical Sciences PARTICIPANTS Soil-Erosion Project Contractors (Scientists from research institutes in developing countries) A. Bujan, CONEA, Buenos Aires, Ezeiza, Argentina O. Bacchi, CENA, USP, Piracicaba, SP, Brazil P. Schuller, UACH, Valdivia, Chile Huo Lua, Institute for Application of Atomic Energy, CAAS, Beijing, China Xinbao Zhang, Institute of Mountain Hazards and Environments, CAS, Chengdu, Sichuan, China S.P. Theocharopoulos, NARF, Soil Science Institute of Athens, Lykovrissi, Greece I. Ionita, Central Research Stn. for Soil Erosion Control, Perieni, Barlad, Romania B. Damnati, Université Abdelmalek Essaadi, Tangiers, Morocco

ix

E. Fulajtar, Soil Science & Conservation Research Institute, Bratislava, Slovak Republic V. Golosov, Moscow State University, Moscow, Russian Federation H. Nemasasi, SPRL, Chemistry and Soil Research Institute, Marondera, Zimabawe Agreement Holders (Scientists from advanced research institutes) P. Wallbrink, Division of Land and Water, CSIRO, Canberra, Australia D.J. Pennock, University of Saskatchewan, Saskatoon, Saskatchewan, Canada F. Penning de Vries, IBSRAM, Bangkok, Thailand D.E. Walling, University of Exeter, Exeter, Devon, United Kingdom J.C. Ritchie, USDA/ARS, Beltsville, United States of America Sedimentation Project Contractors Yong Li, Institute for Application of Atomic Energy, CAAS, Beijing, China S. Boulassa, Université Mohammed V, Rabat, Morocco W. Froehlich, Institute of Geography and Spatial Organization, PAS, Nawojowa, Poland R.M. Margineanu, National Institute for Physics and Nuclear Engineering, Bucharest, Romania Agreement Holders R.J. Loughran, University of Newcastle, NSW, Australia C. Bernard, Institut de Recherche et de Developpement en Agro-environnement, Quebec, Canada Ph. Bonte, CEA-CNRS, Gif-sur-Yvette, France L.R. Basher, Landcare Research, Lincoln, New Zealand I. Queralt, Institute of Earth Sciences “Jaume Almera,” CSIC, Barcelona, Spain

x

SUMMARY This handbook deals with the application of environmental radio-nuclides in studies of soil erosion and sedimentation and comprises nine chapters. Chapter 1 is an introduction to the handbook. It provides an overview of erosion and sedimentation problems, the use of environmental radionuclides, in particular to measure soil redistribution on the landscape and sediment deposition in lakes, reservoirs, and floodplains. Generalities, advantages and limitations, past and current applications of the technique, as well as prospects for future applications of environmental radionuclides are described. The need and purpose of the handbook are discussed. Chapter 2 is dedicated to the design of field-sampling programmes, a critical step in the successful application of the technique. Knowledge and experience from the applications of the technique are analysed, and guidelines for the design of fieldsampling programmes, according to the type of study, are developed. Chapter 3 describes sampling methods to determine levels of and other environmental radionuclides such as excess and It comprises four sections. The first three deal with sampling methods for measuring the depth distribution of the radionuclides, for determining their inventories and for sampling of sediments in depositional areas. The last section gives practical information on recording site and sample information. Chapter 4 deals with sample-processing procedures utilized in radionuclide analytical laboratories. Chapter 5 provides an overview, in a simplified and coherent manner, of methodologies that are commonly used to determine the activities of and other environmental radionuclides using gamma spectrometry. The components of typical gamma spectroscopy systems are described. The procedures for calibrating HPGe detectors and the use of computer software to convert radionuclide spectra to activities are outlined. Quality assurance and control procedures for radionuclide laboratories are described. Chapter 6 examines the approaches used in determining reference values, and how they are used to delineate spatial patterns of soil redistribution or zones of net erosion and net deposition. Guidelines are provided on data interpretation against topographic and soil variability, land use/management, and crucial non-dynamic factors influencing the magnitude of soil erosion and deposition. Chapter 7 discusses the need for calibration procedures called conversion models to derive quantitative estimates of rates of erosion or deposition. Conversion models to estimate rates of soil loss and deposition in cultivated and undisturbed soils are separated from those used with cores collected from river floodplains to estimate rates of sedimentation. The discussion focuses on the main approaches and on models that have been widely employed in recent studies. In addition, procedures for using environmental radionuclides to date sediment cores are also described. xi

Chapter 8 describes the distribution and behaviour of the additional inputs of from fallout resulting from the accident at Chernobyl. Difficulties in discriminating Chernobyl fallout from bomb fallout are discussed. Potentials and limitations of using Chernobyl fallout as a marker in sedimentation and sediment budget studies, and for monitoring soil redistribution, are examined. Chapter 9 is a complement to the rest of the manual. It covers alternative methods and radionuclides to overcome limitations of the technique. Two sections deal with alternative methods, such as the use of a portable gamma detector for in-situ measurement of inventories and the use of the inventory ratio excess of to to measure soil loss in regions of high reference-site variability in undisturbed soils. The potential use of as an alternative to to measure event-based or short-term rates and redistribution patterns is also described.

xii

CHAPTER 1 INTRODUCTION F. ZAPATA1, E. GARCIA-AGUDO2, J.C. RITCHIE3 and P.G. APPLEBY4 1

Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, A-1400 Vienna, Austria. 2R. Kaoru Oda 298, Jd. Das Vertentes, Sao Paulo, Brazil. 3 USDA Agriculture Research Service, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States of America. 4Environmental Radiometric Research Centre, Universitv of Liverpool, Liverpool, United Kingdom.

1.1. BACKGROUND Soil erosion and associated sedimentation are natural processes caused by water, wind, and ice. Several of man’s activities such as deforestation, overgrazing, changes in land use, and non-sustainable farming practices tend to accelerate soil erosion. Soil erosion and sedimentation cause not only on-site degradation of a non-renewable natural resource, but also off-site problems such as downstream sediment deposition in fields, floodplains and water streams. These problems and concern over the degradation of the landscape by erosion, and their impacts on soil fertility and crop productivity in agricultural land, water pollution, and sedimentation in lakes, reservoirs, and floodplains are well documented (Brown and Wolf, 1984; UNEP, 1992; Lal, 1994; Walling, 1989, 2000). Global estimates of economic damage from soil erosion and sedimentation have also been made (Clark, 1985; Colacicco et al., 1989; Pimentel et al., 1987, 1995; Bernard and livari, 2000). Recent focus on sustainability issues has resulted in increased attention on soil-degradation problems, in particular soil erosion and sedimentation. In view of increasing water scarcity and limited land resources to feed an ever-growing world population, there is a an urgent need to obtain reliable quantitative data on the extent and rates of soil erosion worldwide to provide a more comprehensive assessment of the problem and to underpin the selection of effective soil-conservation technologies and sedimentation remediation strategies, including assessment of their economic and environmental impacts (Lal, 2000; Walling, 2002). This chapter describes the use of fallout as a tracer for measuring soil erosion and sedimentation, and the potential use of other radionuclides such as and for these studies. It provides an overview of the technique describing key assumptions and requirements, and advantages and limitations of the technique. Also, applications, recent developments, and future trends of the technique are covered. The chapter is completed with an introduction to the handbook and a list of selected references. 1

F. Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 1–13. © 2002 IAEA. Printed in the Netherlands.

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F. ZAPATA, E. GARCIA-AGUDO, J.C. RITCHIE AND P.G. APPLEBY 1.2. MEASURING SOIL EROSION AND SEDIMENTATION

Measurements of spatially distributed soil erosion on the landscape or sediment deposition in lakes, reservoirs, and floodplains using classical techniques are difficult, time-consuming, and capital- and labour-intensive (Mutchler et al., 1994; Loughran, 1989).

1.2.1. Soil-Erosion Studies Many empirical and theoretical mathematical equations/models have been developed to estimate soil erosion. The most widely used is the Universal Soil Loss Equation (USLE), which is an empirical-based equation developed with data collected from soilerosion plots on “typical” soils of the United States, east of the Rocky Mountains (Wischmeier and Smith, 1965). While the USLE has been greatly misused (Wischmeier, 1976), it is still the most widely used, powerful and practical tool for estimating sheet and rill erosion on the landscape for management planning. A Revised Universal Soil Loss Equation (RUSLE) is available with applications to a wider range of conditions and locations than the original USLE (Renard et al., 1991, 1997). Many other efforts to model soil erosion and its off-site effects have had varying degrees of success and application in management and research (Foster, 1991). However, these models do not provide the information needed to understand the spatial patterns of erosion. Sedimentdeposition studies present similar problems of determining spatial patterns and rates of deposition. Models can provide estimates of deposition rates, but do not provide the spatial patterns needed for management decisions. Thus, existing classical techniques to document soil erosion are capable of meeting some of these needs, but possess important limitations. The quest for techniques as alternatives or complementary to existing methods has directed attention to the use of radionuclides.

1.2.2.Reservoir Studies Measurements of siltation rates in lakes and reservoirs are used in studies both of the integrated record of erosion in the catchment, and its impact on the status of the lake or reservoir. Eroded soils from the catchment accumulate on the bed of the lake together with autochthonous sediments formed by biological and geochemical processes in the water column and a range of other environmental indicators such as pollen grains, chemical pollutants, and fallout radionuclides. Where these sediments preserve the chronological order in which they were laid down, they form a natural archive containing a record of events in the environmental history of the lake and its catchment (Oldfield, 1975). Many studies have shown that, by dating the sediments, it is possible to reconstruct the record of these events on timescales ranging from a few decades to many centuries. Within the context of soil erosion, sediment studies may have a number of different purposes. These include: determination of the chronology of major episodes of soil erosion in the catchment;

INTRODUCTION

3

quantification of the net rate of soil loss from the catchment; identification of the main sources of eroded soil; assessment of the impact of soil erosion on the lake, including water quality and, in the case of a reservoir, its capacity. 1.3. RADIONUCLIDES AS TRACERS Over the past 50 years, the potential for using natural and man-made radioisotopes to study erosion and sedimentation has drawn much attention. Fallout natural and cosmogenic are radionuclides that have been used to provide independent measurements of soil-erosion and sediment-deposition rates and patterns (Ritchie and McHenry, 1990; Walling, 1998; Walling et al., 1999; Walling and He, 1999a, b; Zapata and García-Agudo, 2000). A bibliography of papers on and other radionuclide research related to the study of the erosion and sediment deposition has been compiled (Ritchie and Ritchie, 1998) and is now available on Internet (Ritchie and Ritchie, 2001) Caesium-137 from atmospheric nuclear-weapons tests in the 1950s and 1960s is a unique tracer for erosion and sedimentation, since there are no natural sources of in the environment. This is globally distributed (Playford et al., 1993; Cambray et al., 1989; Carter and Moghissi, 1977). High-yield thermonuclear weapons tests, beginning in November 1952 (Longmore, 1982), injected into the stratosphere where it mixed and circulated globally before being deposited on the landscape. Deposition was affected by precipitation rates and the number of surface nuclear weapon tests conducted each year (Davis, 1963). Global fallout of began in 1954, peaked in 1963 to 1964 and has decreased since this maximum; since the mid-1980s it has often being below detection levels (Cambray et al., 1989). Unique events, such as the Chernobyl accident in April 1986, can cause regional dispersal of measurable (Playford et al., 1993) that affect the total global deposition budget (Volchok and Chieco, 1986). This yearly pattern of fallout can be used to develop a chronology of deposition horizons in lakes, reservoirs, and floodplains. Caesium-137 is easily measured using gamma ray spectrometry (Ritchie and McHenry, 1973; Walling and Quine, 1993) Lead-210 is a naturally occurring radionuclide from the decay series. It is derived from the decay of gaseous Some in the soil diffuses into the atmosphere and decays to and subsequent fallout of to the landscape surface provides an input that is not in equilibrium (excess) with its parent (Robbins, 1978). By measuring and in the soil, excess can be calculated and used to measure soil movement and to date sediment profiles. Gamma-ray spectrometry can be used to measure and (Joshi, 1987). In contrast to the time-dependent fallout of atmospheric fallout of has been constant over the years (Crickmore et al., 1990; Nozaki et al., 1978). Limited data on atmospheric flux show great variability in deposition rates of ranging between 30 and 370 Bq (Appleby and Oldfield, 1992; Robbins, 1978).

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F. ZAPATA, E. GARCIA-AGUDO, J.C. RITCHIE AND P.G. APPLEBY

Beryllium-7 is also a naturally occurring radionuclide produced by the bombardment of the atmosphere by cosmic rays causing spallation of O and N atoms in the troposphere and stratosphere. Production of is relatively constant, producing a constant fallout deposition on the landscape (Wallbrink and Murray, 1994, 1996a; Krishnaswami et al., 1980). Daily surface fluxes of range between 140 and 740 Bq (Wallbrink and Murray, 1994). Gamma-ray spectrometry is used to measure (Murray et al., 1987). The chemistry of and is well understood (Schultz et al., 1960; Davis, 1963; Robbins, 1978; Wallbrink and Murray, 1994). When and reach the soil surface, they are quickly and strongly adsorbed by exchange sites and are essentially non-exchangeable in most environments (Tamura, 1964; Cremers et al., 1988; Robbins, 1978; Olsen et al., 1986). Biological and chemical processes move little of the adsorbed and physical processes of water and wind are the dominant factors moving and soil particles within and between landscape compartments. Accurately measuring and in environmental samples is relatively easy (Ritchie and McHenry, 1973; Walling and Quine, 1993; Joshi, 1987; Murray et al., 1987). Measured patterns of the distribution of (Wallbrink and Murray, 1996a; Walling et al., 1999), (Ritchie and McHenry 1990; Walling and He, 1999a), and (Wallbrink and Murray, 1996b; Walling and He, 1999b) tagged soil particles on the landscape provide information on short-term (<30 days), mediumterm (~40 years) and long-term (~100 years) average soil-redistribution rates and patterns, respectively. Furthermore, concentrations of and have been used to describe erosion processes in catchments, and in some cases the original depth in the soil profile from which the sediment was eroded (Wallbrink and Murray, 1993; Walling and Woodward, 1992; Wallbrink et al., 1999). Measurements of the vertical distribution (Krishnaswami et al., 1980; Fitzgerald et al., 2001), (Ritchie et al., 1972; Pennington et al. 1973), (Goldberg, 1963; Appleby and Oldfield, 1992), and (Libby, 1955) in depositional environments can provide information on the chronology of sediment deposition for time periods of weeks to thousands of years and have been widely applied (Ritchie and Ritchie, 1998, 2001). Of basic importance to sedimentation studies is a reliable means for dating lake sediments. The principal method for achieving this on time-scales spanning the past 100 to 150 years is by a naturally occurring radionuclide, supported by chronostratigraphic records of artificial radionuclides, such as due to fallout from the atmospheric testing of nuclear weapons, and accidental emissions e.g. from the 1986 Chernobyl reactor fire. 1.4. THE

TECHNIQUE

1.4.1. Initial Studies Menzel (1960) showed that loss was greatest from plots with the greatest soil loss. Other studies (Frere and Roberts, 1963; Graham, 1963) supported Menzel’s conclusion that erosion was a factor in the removal of and from catchments. Rogowski

INTRODUCTION

5

and Tamura ( 1965, 1970a, b) and Dahlman and Auerbach (1968) added as a tracer to erosion plots and followed its movement by measuring runoff, soil loss and loss at a flume at the end of the plot. Both studies showed significant exponential relationships between soil and loss, and it was concluded that movement on the landscape was related to soil movement and could be used to estimate soil redistribution patterns. Ritchie et al. (1974) also found an exponential relationship between soil and loss. Ritchie and McHenry (1975) combined their data with those from earlier studies (Rogowski and Tamura, 1965, 1970a, b; Menzel, 1960; Frere and Roberts, 1963; Graham, 1963) and confirmed that a significant exponential relationship existed between soil loss and radionuclide loss. McHenry and Ritchie (1977) showed that the spatial patterns in the distribution of within a field could be used to determine areas of net loss (erosion) and areas of net gain (deposition) within a landscape element. 1.4.2. Key Assumptions and Requirements of the Technique The key assumptions and requirements of the technique have been fully described (Walling and Quine, 1991, 1993; Ritchie and McHenry, 1990; de Jong et al., 1983; Loughran et al., 1988). Although the use of the technique to document rates and patterns of soil loss is attractive in its simplicity, it is founded on several key assumptions and a number of potential limitations and uncertainties must be recognized and addressed in any application (Ritchie and McHenry, 1990; Walling and Quine, 1991; Loughran et al., 1992; Walling and Quine, 1995; Walling, 1998). The assessment of redistribution is commonly based on a comparison of measured inventories (total activity per unit area) at individual sampling points with an equivalent estimate of the inventory representing the cumulative atmospheric fallout input at the site, taking due account of the different behaviour of cultivated and noncultivated soils. Because direct long-term measurements of atmospheric fallout are rarely available, the cumulative input or reference inventory is usually established by sampling adjacent, stable sites, where neither erosion nor deposition has occurred. Where sample inventories are lower than the local reference inventory, loss of Cslabelled soil and, therefore, erosion, may be inferred. Similarly, sample inventories in excess of the reference level are indicative of addition of Cs-labelled soil by deposition. The magnitude and direction of the measured deviations from the local reference level provide a qualitative assessment of soil redistribution (Walling and Quine, 1993; Walling and He, 1999a). To derive quantitative estimates of rates of soil erosion and deposition from measurements, it is necessary to establish a relationship between the magnitude of the deviation from the reference inventory and soil loss or gain (Ritchie et al., 1974). Many workers have favoured the use of calibration procedures or conversion models that relate the erosion or deposition rate to the magnitude of the reduction or increase in the inventory (Ritchie and McHenry, 1990; Walling and Quine, 1990, 1993; Walling and He, 1997, 1999a).

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F. ZAPATA, E. GARCIA- AGUDO, J.C. RITCHIE AND P.G. APPLEBY

1.4.3. Advantages and Limitations of the Technique Besides the objectives of the study and the availability of resources, the choice of a particular method for measuring soil erosion requires a thorough knowledge of the advantages and limitations of the technique to be used. The following section summarizes the main advantages and limitations of the technique to be considered in the context of soil erosion and sedimentation studies (Walling and Quine, 1995; IAEA, 1998; Walling, 2002). a) Advantages Estimates are based on contemporary sampling and provide a retrospective assessment of medium-term (30–40 years) rates of soil redistribution. Estimates can be obtained on the basis of a single site visit. Resulting estimates of soil-redistribution rates are integrated, medium-term, average data and are less influenced by extreme events. Estimates are of individual points within the landscape and information on rates and spatial patterns can be assembled. Sampling does not require significant disturbance of the landscape or study area. The results are compatible with recent developments in physically based distributed modelling and the application of GIS and geostatistics to soil-erosion and sedimentyield studies. Rates of soil redistribution represent integrated effects of all landscape processes resulting in movement of soil particles under defined land use/management. The technique provides information on both erosion and deposition in the same watershed and, therefore, net rates of sediment export. There are no major scale constraints, apart from the number of samples to be analysed. The technique permits quantification of processes, such as soil-tillage redistribution and soil loss and deposition associated to sheet erosion, from the interpretation of the data. Application in fingerprinting suspended sediment sources and estimating rates of overbank floodplain accretion. b) Limitations Need for a multi-disciplinary team for the successful application of the technique. This is a particular limitation in developing countries. Specialized laboratories with sample preparation and costly gamma-counting equipment are required. Requirements for quality assurance/control of low-level gamma-spectrometry measurements. The technique is effectively limited to documentation of sheet and general surface lowering, but it can be applied to study rill erosion in cultivated areas. It is an indirect approach that depends on the link between measured soil redistribution and observed redistribution.

INTRODUCTION

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There are uncertainties associated with the selection of the conversion models used to estimate erosion and deposition rates from the measurements. There is an inability to document short-term changes in erosion rates such as those related to changes in land use and management practices. The technique needs further standardization of the protocols for its worldwide application. While some the limitations are inherent to the technique, several others have been successfully addressed in the framework of the research networks reported below. The significance of these limitations, in particular the cost, must be evaluated in the context of the particular advantages of the technique and the limitations of other techniques. 1.4.4. Applications and Recent Developments Research in the United States (Ritchie and McHenry, 1973, 1990), Australia (Campbell et al., 1982; Elliott et al., 1990; Loughran et al., 1988, Wallbrink and Murray, 1993), Canada (de Jong et al., 1983; Kachanoski, 1993; Pennock et al., 1995) and England (Walling and Bradley, 1988; Walling and He, 1999a, b; Walling and Quine, 1991) has provided a solid data base on the use of to measure soil redistribution. The methodology for using radionuclides to determine the geochronology of sediment deposits is well developed. Using the same suite of radionuclides, with the addition of provides the basis for developing a geochronology of sediment deposits ranging from years to millennia in riparian zones, wetlands, lakes, reservoirs, or anywhere deposition occurs. The concept for a project on the use of environmental radionuclides to study soilredistribution rates and patterns was first formulated at an Advisory Group Meeting held in April 1993 in Vienna (IAEA, 1995). Based on recommendations from this meeting, project proposals for the creation of two research networks—Co-ordinated Research Projects (CRPs)—were formulated: the Erosion CRP co-ordinated by the Soil and Water Management & Crop Nutrition Section of the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, and the Sedimentation CRP organized by the Isotope Hydrology Section of the Division of Physical and Chemical Sciences of the IAEA (Zapata et al., 1995). The IAEA provided the core funding to implement these projects from 1995 to 2000. The overall objectives of these CRPs were consolidated at a consultants meeting held in Vienna in November 1995. Both meetings emphasized the need to promote the standardization of both field and laboratory protocols for the application of the technique (Pennock and Zapata, 1995; IAEA, 1998). The coordinated implementation of both CRPs was recommended because of the interrelationship between the processes of erosion and sedimentation at the catchment level, and the similarities in the application of the technique. The launching of these CRPs by the IAEA in 1996 has made a major contribution to co-ordinating and standardizing the procedures employed by researchers using the technique in soil erosion and sedimentation investigations in various areas of the world. Aspects of the methodology such as selection of reference sites, planning of sampling

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networks, laboratory analyses, including the preparation of a reference soil sample and an inter-comparison exercise, and the use of conversion models were refined and standardized. With regard to the conversion (calibration) models, standard computer software for the application of a range of models was developed and made available at the IAEA website to all participants in the CRPs and to other interested parties (Walling and He, 1997, 1999a). In addition, a model for providing an estimate of the reference inventory for a study site from information on latitude and longitude and mean annual precipitation for the site was developed and incorporated into the conversion model software (Walling and He, 2000). Research completed in 2001 demonstrated that reliable erosion and sedimentation rates integrated over the medium-term (ca. 40 years) could be obtained in a range of environments and spatial scales through use of the fallout radionuclide as a tracer. The development, refinement and calibration of the techniques has provided a universal tool to quantify soil-redistribution rates in a range of natural and agroecosystems, and has paved the way for a wider application of the technique (Zapata and Garcia-Agudo, 2000; Zapata, 2001a, b).

1.5. FUTURE TRENDS While methods for using to measure erosion are well developed, methods for using and are just beginning, but show promise and further research and development are needed (Walling and He, 1999a, b; Wallbrink and Murray, 1994, 1996a). With this suite of radionuclides as tracers there is the potential to measure short-term (single rain events), medium-term (~40 years) and longterm (~100 years) erosion rates, respectively. The use of these new and refined methods within an agricultural context will allow systems of land use and management, and the effectiveness of specific soil-conservation technologies, to be rapidly evaluated in a cost-effective manner. The new techniques will also provide an improved understanding of the relationships between rates of soil loss and soil quality, soil C and nutrient redistribution and the fate of agrochemicals and other environmental contaminants (Zapata and Garcia-Agudo, 2000, Zapata, 2001a). A new FAO/IAEA Co-ordinated Research Project will be launched in 2003 to further develop radionuclide methodologies and to pilot test soil-conservation strategies tailored to local conditions and resources (Zapata, 2001b). Similarly, another CRP has been initiated on the use of nuclear and allied techniques for sediment tracing (finger-printing) with emphasis on sustainable catchment management and dam sustainability (Turner, 2000). The newly developed research tools will be used to combat soil erosion and associated sedimentation towards the ultimate goal of sustainable resource use and environmental protection.

1.6. THE HANDBOOK This handbook contains the recent developments made in the refinement and standardization of the technique for the assessment of soil erosion and sedimentation by both research networks. The following chapters in this handbook will

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provide a review of the scientific basis, technical information, and methodology for using radionuclides, primarily and to measure soil redistribution and determine the geochronology of sediment deposits. In many cases, these methods are the only way to generate actual measurements of soil loss and deposition or sediment chronology. Of fundamental importance to these studies are sound strategies for sampling sediment records, and appropriate techniques for retrieving cores and processing sub-samples of them for radiometric assay. Although a single sediment core can yield reliable information on the history of events in the lake and its catchment, generally it is not sufficient for more detailed quantitative studies. Sediments are not uniformly distributed, and records in a single core may be influenced by various factors relating to its location in the lake such as proximity to inlet streams, water depth, biological activity, and the intensity of sediment focusing. Quantitative estimates of erosion losses from the catchment demand wholebasin studies based on a multi-core approach. Such studies are time-consuming and expensive, and it is essential that they have clear objectives and that they be planned and implemented in carefully so as to ensure that the objectives are met. This handbook also aims to give advice on matters relating to the selection of suitable coring sites, the sampling strategy, and on methods for retrieving cores and subsampling. Since errors and imperfections introduced at this stage of a project can at best only be partially corrected at later stages, often at the cost of much time and effort, it is vitally important to the success of the project that the important first steps are well planned and executed with careful attention to detail. 1.7. REFERENCES Appleby, P. G., & Oldfield, F. (1992). Application of lead-210 to sedimentation studies. In M. Ivanovich and R.S. Harman (Eds.), Uranium-series disequilibrium: Applications to earth, marine, and environmental sciences (pp.731–738). Oxford: Clarendon Press. Bernard, J. M., & Iivari T. A. (2000). Sediment damages and recent trends in the United Sates. International Journal of Sediment Research, 15, 35–48. Brown, L. R., & Wolf E. C. (1984). Soil erosion: quiet crisis in the world economy, Worldwatch paper 60. Washington: Worldwatch Institute. Cambray, R. S., Playford, K., Lewis, G. N. J., & Carpenter R. C. (1989). Radioactive fallout in air and rain: results to the end of 1988. AERE-R-13575. Harwell: UK Atomic Energy Authority. Campbell, B. L., Loughran, R. J., & Elliott, G. L. (1982). Caesium-137 as an indicator of geomorphic processes in a drainage basin system. Australian Geography Studies, 20, 49–64. Carter, M. W., & Moghissi, A. A. (1977). Three decades of nuclear testing. Health Physics. 33. 55–71. Clark, II, E. H (1985). The off-site cost of soil erosion. Journal of Soil and Water Conservation, 40, 19–22. Colacicco, D., Osborn, T., & Alt, K. (1989). Economic damage from soil erosion. Journal of Soil and Water Conservation, 44, 35–39. Cremers, A., Elsen, A., De Preter, P., & Maes, A. (1988). Quantitative analysis of radiocaesium retention in soils. Nature. 335, 247–249. Crickmore, M. J., Tazioli, G. S. Appleby, P. G., & Oldfield, F. (1990). The use of nuclear techniques in sediment transport and sedimentation problems, IHP-III Project 5.2 SC-90/WS-49. Paris: UNESCO. Dahlman, R. C., & Auerbach, S. I. (1968). Preliminary estimation of erosion and radiocesium redistribution in a fescue meadow, ORNL-TM-2343. Oak Ridge: Oak Ridge National Laboratory. Davis, J. J. (1963). Caesium and its relationship to potassium in ecology. In V. Schultz and A.W. Klement Jr. (Eds.), Radioecology (pp. 539-556). New York: Reinhold.

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de Jong, E., Begg, C. B. M., & Kachanoski, R. G. (1983). Estimates of soil erosion and deposition from some Saskatchewan soils. Canadian Journal of Soil Science 63, 607–617. Elliott, G. L., Campbell B. L., & Loughran R. J. (1990). Correlation of erosion measurement and soil caesium137 content. Journal of Applied Radiation and Isotopes, 41, 713–717. Fitzgerald, S. A., Klump, J. V., Swarzenski, P. W., Mackenzie, R. A., & Richards, K. D. (2001). Beryllium-7 as a tracer of short-term sediment deposition and resuspension in the Fox River, Wisconsin. Environmental Science and Technology, 35, 300–305. Foster, G. R. (1991). Advances in wind and water erosion prediction. Journal of Soil and Water Conservation, 46, 27– 29. Frere, M. H., & Roberts, H. J. Jr. (1963). The loss of from small cultivated watersheds. Soil Science Society of America Proceedings, 27, 82–83. Goldberg, E. D. (1963). Geochronology with lead-210 radioactive dating, ST1/PUB/68 (pp. 121–131). Vienna: IAEA. Graham, E. R. (1963). Factors affecting Sr-85 and I-131 removal by runoff water. Water and Sewage Works, 110,407–410. IAEA (1995). Use of nuclear techniques in studying soil erosion and siltation, IAEA-TECDOC-828. Vienna: IAEA. IAEA (1998). Use of in the study of soil erosion and sedimentation, 1AEA-TECDOC-1028. Vienna: IAEA. Joshi, S. R. (1987). Non-destructive determination of lead-210 and radium-226 in sediments by direct photon analysis. Journal of Radioanalysis and Nuclear Chemistry Articles, 116, 169–182. Kachanoski, R. G. (1993). Estimating soil loss from changes in soil Cesium-137. Canadian Journal of Soil Science, 73, 515–526. Krishnaswami, S., Benninger, L. K., Aller R. C., & Von Damm, K. L. (1980). Atmospherically-derived radionuclides as tracers of sediment mixing and accumulation in near-shore marine and lake sediments: evidence from and Earth and Planetary Science Letters, 47, 307-318. Lal, R. (2000). Soil management in developing countries. Soil Science 165, 7–72. Lal, R. (Ed.). (1994). Soil erosion. Ankeny, IA: Soil and Water Conservation Society. Libby, W. F. (1955). Radiocarbon dating. Chicago: University of Chicago Press. Longmore, M. E. (1982). The caesium-137 dating technique and associated applications in Australia – A review. In W. Ambrose and P. Duerden (Eds.), Archaeometry: an Australasian perspective (pp. 310-321). Canberra: Australian National University Press. Loughran, R. J. (1989). The measurement of soil erosion. Progress in Physical Geography, 13, 216–233. Loughran, R. J., Elliott G. L., Campbell B. L., Kiernan K., & Temple-Smith M. G. (1992). A reconnaissance survey of soil erosion in Australia. In Proceedings of the ISCO Conference Sydney, September 1992, Vol 2.1 (pp. 52–63). Sydney: International Soil Conservation Organization. Loughran, R. J., Elliott, G. L. Campbell B. L., & Shelly D. J. (1988). Estimation of soil erosion from caesium-137 measurements in a small cultivated catchment in Australia. Journal of Applied Radiation and Isotopes, 39, 1153-1157. McHenry, J. R., & Ritchie J. C. (1977). Estimating field erosion losses from fallout Cs-137 measurements. IAHS Publication 122 (pp. 26–33). Wallingford: IAHS Press. Menzel, R. G. (1960). Transport of strontium-90 in runoff. Science, 131. 499–500. Murray, A.S., Marten, R., Johnston A., & Martin P. (1987). Analysis of naturally occurring radionuclides at environmental levels with gamma spectrometry. Journal of Radiation and Nuclear Chemistrv, 115, 263– 288. Mutchler, C. K., Murphree, C. E., & McGregor K. C. (1994). Laboratory and field plots for erosion research. In R. Lal, (Ed.), Soil erosion (pp. 11–37). Ankeny, IA: Soil and Water Conservation Society. Nozaki, Y., DeMaster, D.J., Lewis, D.M., & Turekain, K.K. (1978). Atmospheric fluxes determined from soil profiles. Journal of Geophysical Research, 83 (C8), 4047–4051. Oldfield, F. (1975). Lakes and their drainage basins as units of sediment-based ecological study. Hydrobiology. 103. 71–74. Olsen, C. R., Larsen, I. L., Lowry, P. D., & Cutshall, N. H. (1986). Geochemistry and deposition of in river-estuarine and coastal water. Journal of Geophysical Research, 91, 896–908. Pennington, W., Cambray, R.S., & Fisher, E. M. (1973). Observations of lake sediment using fallout as a tracer. Nature, 242, 324–326.

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Pennock, D.J., Lemmon, D.S., & de Jong, E. (1995). Cesium-137 measured erosion rates tor five parentmaterial groups in southwestern Saskatchewan. Canadian Journal of Soil Science, 75, 205–210. Pennock, D.J., & Zapata, F. (1995). Report of the FAO/IAEA Consultants Meeting on “The use of isotopes in studies of soil erosion,” CT-2665, Vienna: IAEA. Pimentel, D., Allen, J., Beers, A., Guinand, L., Linder, R., McLaughlin, P., Meer, B., Musonda, D., Perdue, D., Poisson, S., Siebert, S., Stone, K., Salazar, R., & Hawkins A. (1987). World agriculture and soil erosion. Bioscience, 37, 277–283. Pimentel, D., Harvey, C., Resosudarmo, P., Sinclair, K., Kurz D., McNair, M., Crist, S., Shpritz, L., Fitton, L., Saffouri, R., & Blair, R. (1995). Environmental and economic cost of soil erosion and conservation benefit. Science, 267, 1117–1123. Playford, K., Toole, J., & Adsley, I. (1993). Radioactive fallout in air and rain: results to the end of 1991. AEA-EE-0498. Harwell: UK Atomic Energy Authority. Quine, T. A., & Walling, D. E. (1991). Rates of soil erosion on arable fields in Britain: quantitative data from caesium-137 measurements. Soil Use and Management 7, 169–176. Renard, K. G., Foster, G. R., Weesies,. G. A., McCool, D. K, & Yoder, D. C. (1997). Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). USDA Agricultural Handbook No. 537. Washington: United States Department of Agriculture. Renard, K. G., Foster, G. R., Weesies, G. A., & Porter, J. P. (1991). RUSLE Revised universal soil loss equation. Journal of Soil and Water Conservation, 46, 30–33. Ritchie, J. C., & McHenry, J. R. (1973). Determination of fallout Cs-137 and natural gamma-ray emitting radionuclides in sediments. International Journal of Applied Radiation and Isotopes, 24, 575-578. Ritchie, J. C., & McHenry, J. R. (1975). Fallout Cs-137: a tool in conservation research. Journal of Soil and Water Conservation, 30, 283-286. Ritchie, J. C., & McHenry, J. R. (1990). Application of radioactive fallout cesium-137 for measuring soil erosion and sediment accumulation rates and patterns: a review. Journal of Environmental Quality, 19, 215-233. Ritchie, C., McHenry J. R., Hill, A. C., & Hawks P. H. (1972). Fallout caesium-137 in reservoir sediments. Health Physics, 22, 97–98. Ritchie, J. C., & Ritchie C. A. (1998). Bibliography of publications of studies related to soil erosion and sediment deposition. In Use of in the study of soil erosion and sedimentation, IAEA-TECDOC-1028 (pp. 63-116), Vienna: IAEA. Ritchie, J. C., & Ritchie C. A. (2001). Bibliography of publications of studies related to soil erosion and sediment deposition, Ritchie, J. C., Spraberry, J. A., & McHenry, J. R. (1974). Estimating soil erosion from the redistribution of fallout Cs-137. Soil Science Society of America Proceedings, 38. 137-139. Robbins, J. A. (1978). Geochemistry and Geophysical application of radioactive lead. In J. O. Nriagu (Ed.), The biochemistry of lead in the environment (pp. 285-393). Amsterdam: Elsevier. Rogowski, A. S., & Tamura, T. (1965). Movement of by runoff, erosion and infiltration on the alluvial Captina silt loam. Health Physics, 11, 1333-1340. Rogowski, A. S., & Tamura T. (1970a). Environmental mobility of cesium-137. Radiation Botany, 10, 35–45. Rogowski, A. S., & Tamura T. (1970b). Erosional behavior of cesium-137. Health Physics, 18, 467–477. Schultz, R. K., Overstreet, R., & Barshad, I. (1960). On the soil chemistry of caesium-137. Soil Science. 89, 19–27. Tamura, T. (1964). Consequences of activity release: selective sorption reactions of cesium with soil minerals. Nuclear Safety, 5, 262–268. Turner, J. (2000). AGM on “Sediment tracing (finger-printing) by nuclear techniques and their application to the planning and design of erosion and sedimentation remediation strategies and the assessment of their effectiveness, with emphasis on dam sustainability,” IAEA Report AG-1090. Vienna: IAEA. UNEP (1992). Global assessment of soil degradation. Wageningen: ISRIC, and Nairobi: UNEP. Volchok, H. L., & Chieco, N. (1986). A compendium of the Environmental Measurement Laboratory’s research projects related to Chernobyl nuclear accident. USDOE Rep. EML-460. New York: Environmental Monitoring Laboratory. Wallbrink, P. J., & Murray A. S. (1993). The use of fallout radionuclide as indicators of erosion processes. Hydrological Processes, 7, 297–304.

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Wallbrink, P. J., & Murray A. S. (1994). Fallout of over south eastern Australia. Journal of Environmental Radioactivity, 25, 213-228. Wallbrink, P. J.,& Murray, A. S. (1996a) Distribution of in soils under different surface cover conditions and its potential for describing soil redistribution processes. Water Resources Research, 32. 467-476. Wallbrink, P. J.,& Murray, A. S. (1996b) Determining soil loss using the inventory ratio of excess lead-210 to cesium-137. Soil Science Society of America Journal, 60. 1201-1208. Wallbrink, P. J., Murray, A. S., & Olley, J. M. (1999). Relating suspended sediment to its original soil depth using fallout radionuclides. Soil Science Society of America Journal, 63, 369-378. Walling, D. E. (1989). The struggle against water erosion and a perspective on recent rcsearehin. In K. Ivanov and D. Pechinov (Eds.), Water erosion, UNESCO technical document in hydrology, SC-89/WS-57 (pp. 39– 60). Paris: UNESCO. Walling, D. E. (1998). Use of and other fallout radionuclides in soil erosion investigations: Progress, problems and prospects. In Use of in the study of soil erosion and sedimentation. IAEA-TECDOC1028 (pp. 39-62). Vienna: IAEA. Walling, D. E. (2000). Linking land use, erosion and sediment yields in river basins. Hydrobiology, 410, 223-240. Walling, D. E. (2002). Recent advances in the use of environmental radionuclides in soil erosion investigations. In Nuclear techniques in integrated plant nutrient, water and soil management. I A E A - C S P - 1 1 P ( pp. 279– 301). Vienna: IAEA. Walling, D. E., & Bradley, S. B. (1988). The use of caesium-137 measurements to investigate sediment delivery from cultivated areas in Devon, IAHS publication 174 (pp. 325-335): Wallingford: IAHS Press. Walling, D. E., & He, Q. (1997). Models for converting measurements to estimates of soil redistribution rates on cultivated and uncultivated soils. Report to the IAEA as a contribution to the IAEA Co-ordinated Projects on Soil Erosion and Sedimentation. Exeter: Department of Geography, University of Exeter. Walling, D. E., & He, Q. (1999a). Improved models for estimating soil erosion rales from Cesium-137 measurements. Journal of Environmental Quality, 28, 611–622. Walling, D. E., & He, Q. (1999b) Using fallout Lead-210 measurements to estimate soil erosion on cultivated land. Soil Science Society of America Journal, 63, 1404–1412. Walling, D. E., & He, Q. (2000). The global distribution of bomb-derived reference inventories. Report to the IAEA as a contribution to the IAEA Co-ordinated Projects on Soil Erosion and Sedimentation. Exeter: Department of Geography, University of Exeter. Walling, D. E., He, Q., & Blake, W. (1999). Use of B-7 and Cs-137 measurements to document short- and medium-term rates of water-induced soil erosion on agricultural land. Water Resources Research, 35, 3865-3874. Walling, D. E., & Quine, T. A. (1990). Calibration of measurements to provide quantitative erosion rate data. Land Degradation and Rehabilitation, 2, 161–175. Walling, D. E., & Quine, T. A. (1991). The use of measurements to investigate soil erosion on arable fields in the UK: potential applications and limitations. Journal of Soil Science, 42, 147–162. Walling, D. E., & Quine, T. A. (1993). Use of caesium-137 as a tracer of erosion and sedimentation: Handbook for the application of the caesium-137 technique. Exeter: UK Overseas Development Administration, Department of Geography. University of Exeter. Walling, D. E., & Quine, T. A. (1995). The use of fallout radionuclide measurements in soil erosion investigations in IAEA. In Nuclear techniques in soil-plant studies for sustainable agriculture and environmental preservation. .STI/PUB/947(pp. 597–619). Vienna: IAEA. Walling, D. E., & Woodward J. C. (1992). Use of radiometric fingerprints to derive information on suspended sediment sources. In J. E. Bogen, D. E. Walling and T. Day (Eds.), Erosion and sediment transport monitoring programmes in river basins. IAHS publication 210 (pp. 153–164). Wallingford: IAHS Press. Wischmeier, W. H. (1976). Use and misuse of the universal soil loss equation. Journal of Soil and Water Conservation, 31, 5–9. Wischmeier, W. H., Smith, D. D. (1965). Predicting rainfall-erosion losses for cropland east of the Rocky Mountains. Agriculture handbook no. 262. Washington: United States Department of Agriculture. Zapata, F. (2001 a). Final Report of the co-ordinated research project on “Assessment of soil erosion through the use of the Cs-137 and related techniques as a basis for soil conservation, sustainable agricultural production and environmental protection.” Vienna: IAEA.

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Zapata, F. (2001b). Report of the consultants meeting on “Assessment of soil conservation technologies for sustainable agricultural production.” Vienna: IAEA. Zapata, F., & García-Agudo, E. (2000). Future prospects for the technique for estimating soil erosion and sedimentation rates. Acta Geologica Hispanica, 35, 197–205. Zapata, F., García-Agudo, E., Hera, C., Rozanski, K., & Froehlich K. 1995. Use of nuclear techniques in soil erosion and siltation studies. In Nuclear techniques in soil-plant studies for sustainable agriculture and environmental preservation. IAEA proceedings series STI/PUB/947 (pp. 631 –642). Vienna: IAEA.

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CHAPTER 2 SITE SELECTION AND SAMPLING DESIGN D.J. PENNOCK1 and P.G. APPLEBY2 1

Department of Soil Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5A8, Canada. 2 Environmental Radiometric Research Centre, University of Liverpool, Liverpool, United Kingdom.

2.1. INTRODUCTION The design of the field-sampling programme is critical to the successful application of the and associated radionuclide techniques. Despite the importance of field sampling, few summaries exist to guide researchers. The purpose of this chapter is to summarize the existing literature on field sampling in radionuclide research and related earth science fields, and to develop guidelines for the design of fieldsampling programs. The literature cited is not comprehensive but is intended to guide the reader to specific applications of the techniques under discussion. 2.2. TYPES OF STUDIES AND SUITABILITY OF AND RELATED TECHNIQUES The initial question is whether the and related radionuclides techniques are suitable for the particular research problem under consideration. The range of environments in which the techniques have been deployed is great, as documented in the web-based bibliography (http://hydrolab.arsusda.gov/cesium137bib.htm) maintained by J. and C. Ritchie. The existing studies can be grouped into three main categories: soil redistribution (erosion), floodplain/reservoir sedimentation, and integrated catchment studies. Soil-redistribution studies focus on the measurement of soil loss (or erosion) and gain (or deposition) by physical processes that remove a fraction of the labelled surface soil and deposit it elsewhere. Processes that completely remove the layer, including many mass-wasting processes such as landslides or debris flows and erosion from subsurface piping, are not suitable for analysis using the technique. Soil redistribution occurs as a result of three main factors—tillage, water, and wind—and has been used to study the rates and patterns of all three. Results from studies were seminal in developing our understanding of the importance of tillage redistribution (Govers et al., 1999). 15

F. Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 15–40. © 2002 IAEA. Printed in the Netherlands.

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Tillage redistribution is caused by incremental soil displacement by tillage implements over time, and is especially well suited to study using the technique. The different agents of water erosion can generally be categorized on the basis of whether water flow is unconcentrated (sheet erosion) or concentrated (rill and gully erosion). The technique is well suited to measurement of unconcentrated erosion processes. The distinction between rills and gullies is somewhat qualitative; rills can be ploughed over by the farmer using typical tillage implements, whereas gullies cannot, but the distinction is important for studies. During rill incision, a fraction of the soil is removed by the concentrated flow. Caesiumlabelled soil is then redistributed from the adjacent soil surface during tillage operations into the rill incision. The surrounding soil surface will experience a net soil loss, but the unfilled rill will have labelled soil to the depth of the initial rill (and hence may appear to be a depositional site). In gully erosion, the entire labelled layer is typically removed, and the technique cannot be used to assess soil loss in the gullies themselves. It can, however, be used effectively in the areas of deposition of gully sediments to provide a chronological measure of gully development (Ionita and Margineanu, 2000). The use of in wind erosion studies is less common, but good literature examples exist (Sutherland et al., 1991; Harper and Gilkes, 1994). On level fields with no potential for significant run-on of surface flow, the only plausible erosion process that can be operating is wind erosion, hence the measured Cs changes can be assigned reliably to wind-erosion sources. Regions dominated by wind erosion may pose additional problems for the use of the technique due to aeolian deposition of Cs-labelled soil to the soil surface at reference sites (Chappell, 1999). Examples of the use of and related techniques in floodplain- and reservoirsedimentation studies are also well developed. The most common radionuclides used are and unsupported In the case of floodplains, there are two sources for direct fallout deposition from the atmosphere and the deposition of labelled sediment during episodes of sediment accretion (Walling et al., 1996). The depth distribution of from a depth-incremented core can be used to assign dates to different peaks of (Foster and Walling, 1994). The total inventory of a floodplain core can also be compared to the reference value for the local inventory of the surrounding area, to determine the excess inventory present at the sampled point (Walling et al., 1996). The technique has been used even in alluvial sediments with very low clay contents. For example, Ely et al (1992) used the technique in alluvial deposits with < 1 % clay. Also, abrasion of grains or disaggregation during fluvial transport has been shown not to have a significant effect on labelling (Dyer and Olley, 1999). And great potential exists for the use of radionuclides to integrate field studies with models of floodplain hydraulics (Siggers et al., 1999). Integrated catchment studies involve integration of the terrestrial and aquatic environments such that complete sediment accounting in the catchment can occur. As such, it may involve sampling of areas of active sedimentation or erosion that have a limited extent but which are critical for sediment transport within the catchment. For example, riparian strips have been documented to act as major

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sediment deposition points in a catchment. Also, catchments where mass-wasting processes occur or gully erosion is active will require the use of other measurement techniques used in conjunction with to achieve a complete sediment balance. Recent examples of integrated catchment studies are those of Hutchinson (1995), Zhang et al. (1997), Sogon et al. (1999), and Ionita and Margineanu (2000). 2.3. RECONNAISSANCE STAGE The objectives of the reconnaissance stage are three-fold. First, background environmental and socio-economic information should be compiled to allow the researcher to develop the field sampling program and other researchers to assess the similarity between the chosen research area and their own. Second, information on the environmental conditions and cultural practices that control the erosion/sedimentation processes operating in the area should be gathered. Finally, a field visit and preliminary sampling should be used to determine whether suitable reference sites exist and to provide preliminary estimates of Cs inventories and distribution in the area. 2.3.1. Compilation of Background Information The compilation of background information largely takes place using existing literature and government reports. Given the great diversity of global environments, no single list can be comprehensive; the factors listed in Table 2.1 represent a minimum data set. The key concept is that any factors likely to be of consequence in affecting erosion/sedimentation regimes in the study area should be documented. 2.3.2. Field Reconnaissance of Study Area A thorough reconnaissance of the study area is highly recommended for the development of a successful sampling program. The main goal of the field reconnaissance is to select specific sites that can be used in the main sampling program. An exploratory sampling of the sites should also be undertaken. The compilation of background information will provide general information for the study region, but the specific conditions present in the study area can only be assessed in the course of a field visit. The major objectives of the reconnaissance field visit are: 1) to determine whether suitable reference sites exist, 2) to assess the types and magnitude of erosion/redistribution in disturbed sites, and 3) to make an inventory of landforms, soils, and cultural practices present in the area. 2.3.2.1. Reconnaissance of Reference Sites The proper selection of reference sites is critical for successful implementation of the technique. The criteria for their selection are discussed in Section 2.4. During the field visit, the presence of possible reference sites must be assessed. If no reference sites exist, the technique can yield only relative measures of soil redistribution in the landscape, which may not justify its use. The technique can

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still be used as a chronological tool in floodplain/reservoir studies, although the “excess” inventory cannot be determined (Walling et al., 1996). If suitable reference sites are located, then a preliminary soil sampling for the depth distribution of should be completed following the procedures outlined in Chapter 3.

2.3.2.2. Land Use/Management Practices The specific land use/management practices used in the area can be assessed through discussions with landowners. Information on typical land-management practices and on changes in land use since 1950 should be documented. For the knowledge gained from the technique to be useful in conservation planning, the socio-economic context for the land-use practices used in the area must be understood (Forsyth, 1994). Information on local knowledge about soil conditions and the occurrence of erosion events should also be amassed and used in the development of the sampling program.

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2.3.2.3. Landforms and Soils The range of landforms present in the study region should be documented for use in planning the main field-sampling program. The great range of global landforms precludes an exhaustive inventory in this chapter, but the main factors of landform description in terms of the development of sampling plans can be summarized schematically (Figs. 2.1–2.4).

It has been amply established that the shape (morphology) of the landform is a major control on the redistribution of water and sediment, and that the position of a given point in a landscape is central to understanding the specific rates of soil and geomorphic processes operating on it (Wysocki et al., 2000; Pennock and Corre, 2001). Level surfaces have very low gradients and do not receive run-on surface flow from higher slope positions (Fig. 2.1). These level surfaces cannot experience high rates of tillage translocation; they can only sustain high water erosion losses if rainfall intensities are very high and/or rainfall duration is long. In an undisturbed state, these sites are very suitable for reference sites. Where the slope gradient is sufficiently high for water- and tillage-erosion processes to become active, three basic surface forms can occur (Figs. 2.2–2.4). The landforms can be described using three terrain or slope attributes (Table 2.2): slope gradient, plan (or across-slope curvature), and profile (or down-slope curvature). In sloping landforms that lack plan curvature (inclined surfaces), no across-slope concentration of flows occurs (Fig. 2.2). The magnitude of flow at any given point on inclined surfaces is determined solely by the flow received from positions immediately upslope of the point and the flow generated within the point itself. The

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terrain attributes of relevance for these surfaces are slope gradient, slope length, and the areal extent of slope units that show significant profile curvature (Table 2.2).

Slope forms that have significant plan curvature introduce across-slope convergence and divergence of flow (Fig. 2.3). These surfaces can be called undulating where the across-slope convexities and concavities are relatively smooth, or dissected where the concavities are more deeply incised. Simple, two-dimensional linear measures cannot be used to assess the area contributing flow to a given point. Instead three-dimensional positional measures such as catchment area are used (Table 2.2). In this case the overall landform should be described using slope gradient, plan and profile curvature, and total catchment area. The final example is a complex landform with no dominant slope and multiple small catchments (Fig. 2.4). No additional terrain attributes are required to describe the landform type, but the complexity of slope forms ensures that multiple flow routings occur. The landform types discussed here are not scale-dependent. In some cases the study field may occupy the entire slope form; in others, the study field may occupy only a fraction of the total slope complex. In the reconnaissance field visit, the nature of the landform at each potential study location should be assessed.

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The typical soil profiles in the landscape should also be assessed. The soil properties described and measured should allow the placement of the soil into the international and national soil classification systems. The key soil properties from an erosion perspective are the soil texture, the nature of horizons in the soil profile, and the presence of growth-impeding layers at depth. The former two are important controls on the erosion process; the latter is critical for assessing the possible implications of erosion for plant productivity. Soil properties in a level site will (in the absence of a strong textural contrast within the site) vary little, and can be assessed in the reconnaissance stage using a few randomly placed pits. In sloping landscapes, soils will differ depending on their position within the overall landform. This repeated soil-distribution pattern is termed

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a soil catena, and a soil pit in each major slope element should be dug and the soil profile described.

Soil sampling for depth distribution of (see Chapter 3) should be carried out at one reference site and one or more disturbed site(s). The purpose of this sampling is to assess the reference site inventory and to ensure that sufficient remain in the disturbed site to allow use of the technique. If possible, samples should be taken from depositional areas as well to determine the depth to which may be found in these positions. 2.4. SELECTION OF REFERENCE SITES The selection of reference sites is central for successful execution of a erosion study. The reference site is used to establish the inventory in the study region against which the changes in inventory, both in disturbed sites and in depositional environments, can be assessed. Sutherland (1996) summarized the most complete literature review on reference sites. Bunzl et al. (1997, 2000), Schuller et

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al. (1997), Lettner et al. (2000), and Golosov et al. (1999) provide more-recent information on selection of and variability within reference sites, while Pennock (2000) placed variability in reference sites in the context of variability in other soil properties.

The selection of reference sites should be guided by the following principles: The ideal reference site has experienced neither soil loss nor sediment deposition; the inventory reflects only the atmospheric inputs of the specific radionuclide and its decay through time. Level sites that do not receive flows from upslope positions are the preferred locations. The ideal reference site has been under continuous vegetation cover for the period since deposition of began in the early 1950s. Landowner contact is critical to establish the disturbance history of each site. Perennial grass or low herb cover is best. The spatial variation of Cs inputs is higher in forested sites because a) the mix of species in forests causes varied aerodynamic surface areas and hence various interception rates, b) the soil-toplant transfers are species-specific, c) stem flow concentrates activity around tree trunks, and d)surface soil disturbance by tree fall, bioturbation, and wind-throw increases complexity in forest soils (summarized from Sutherland, 1996). Protected areas such as parks, ceremonial areas, burial grounds are commonly used for reference sites although clearly some cultural sensitivity is required.

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The reference site should be located as close as possible to the disturbed sites that are to be sampled. For regional-scale studies, multiple reference sites should used to determine whether variation in the inventory occurred within the region. The inventory at any given site should be compared to any available national or global-level (Garcia-Agudo, 1998) radionuclide-deposition data. In some regions of the world, reference sites that meet these criteria are not available. In such cases, researchers should choose sites that best meet the guidelines presented above, and then clearly identify the conditions. For example, Nagle et al. (2000) worked in a steeply sloping landscape in the Dominican Republic and primarily used coffee groves for their reference sites. Adequate sampling and description allowed them to use the values from the coffee groves. Recently Walling and He (2000) prepared an updated version of the global map of bomb-derived fallout deposition. They have also developed a model that is capable of representing the global distribution of inventories and which can be used to estimate the inventory for a study area, taking into account the dominant factors influencing the deposition of from the atmosphere. 2.5. FIELD SAMPLING Sampling is required in field-based radionuclide studies because we cannot measure the desired attributes of the entire population. Instead, we can only sample a small proportion of the population, and then develop statistics based on our sample to characterize the population as a whole. The definition of the specific population to be sampled depends on the objectives of the research. Operationally, a population can be defined as a well defined set of objects for which inferences are sought. For example, in a study to assess the inventory at a reference site, the population is the total number of samples (e.g. 7-cm diameter cores) that could be taken from the site. In a study to compare erosion rates of fields under various land uses, each field with a specific land use is one object in the total population of fields in the study region. For a study that compares erosion rates on different slope elements, each spatially independent slope element at a site is one object in the population. In the latter two cases, the Cs concentration of the object as a whole is not measured; instead they are sampled by extracting a portion of the object, which is typically termed the evaluation unit (or support in geostatistical terminology). For example, we might take three 7-cm diameter cores as sub-samples from a given 10-m by 10-m landform element and then composite them to get one sample from that element. In sampling design, the number of objects to be sampled and the procedure to select the specific objects to be sampled are chosen by the researcher. Despite the great importance of sampling design in field studies, few sources are available to guide researchers in their choice of methods. The choice of the field-sampling design to be used and the numbers of samples required must be made in accordance with the objectives of the specific research project. In the following section the

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objectives of various types of projects are identified, and the implications of these objectives for sample numbers and sampling design are presented. 2.5.1. Definition of Project Objectives Eberhardt and Thomas (1991) identify eight categories of field studies. Three of their categories are relevant for studies: descriptive studies, analytical studies, and pattern-development studies. In descriptive studies, the objective of the sampling is to determine the value of measures of central tendency (such as the mean or median) and dispersion (such as the standard deviation or coefficient of variation) for the population. These measures can then be used to construct confidence intervals around the mean. Sample numbers are chosen to ensure that the confidence intervals around the mean are as small as possible. In analytical studies, the researcher typically starts with a definition of an a-priori hypothesis or series of hypotheses to be tested in the research. For example, comparisons among soil-redistribution rates associated with different slope positions (e.g. Pennock and de Jong, 1990; Basher, 2000; Montgomery et al., 1997; Sogon et al., 1999), different parent materials (Pennock et al., 1995), or different land-use practices or classes (e.g. Forsyth, 1994; Lu and Higgit, 2000) have been made. Sample numbers for each group are chosen to maximize the power of the comparison between the groups (Peterman, 1990). Pattern-development studies lead to the creation of maps or surfaces of the property under study. The principle underlying this approach is that the spatial pattern of a property, of reflects the action of underlying processes operating in the landscape. The spatial pattern of distribution documented by many researchers in the 1980s and 1990s was central to the acceptance of tillage translocation as a major erosional agent by earth and agricultural scientists (Govers et al., 1999) and represents one of the major contributions of the technique to date. Sampling for pattern has been used in agricultural fields (e.g. Longmore et al., 1983; Govers et al., 1996; Quine et al., 1999; Wallbrink et al., 1994) and floodplains (Walling et al., 1996; Siggers et al., 1999). 2.5.2. Sample Numbers and Sample Compositing The optimum number of samples to be gathered in a specific study depends in part on the objectives. Once these have been determined, the number of samples required to complete the project should then be compared to the resources available. If the resources are inadequate, then either the objectives of the study must be re-defined or the project should be abandoned. 2.5.2.1. Sample Numbers for Descriptive Sampling (Reference Sites) Descriptive sampling is of greatest relevance for establishing the at reference sites. Sutherland (1996) provided a comprehensive review of the literature available on reference sites. He used the coefficient of variation (CV) as his summary measure

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of dispersion, and reported that the median CV for the papers he reviewed was 19%, with a range from 1.5 to 86%. Sutherland (1996) recommended that not fewer than eleven independent samples from a probability-based sampling design should be taken at reference sites in order to have an allowable error of 10% at the 90% confidence limit. 2.5.2.2. Sample Numbers for Analytical Sampling In analytical sampling, the major objective is to compare levels in two or more groups based on structured hypothesis testing. The implications of hypothesis testing for sampling design have not been well explored in the or broader earthsciences literature. McGee et al. (1995) provided a useful discussion and application of the principles of hypothesis testing to and Peterman (1990) provided a broader viewpoint on hypothesis testing in conservation research. In the simplest type of hypothesis testing, two hypotheses are constructed: the null hypothesis of no difference between the two groups, and the alternative hypothesis of a significant difference occurring. The researcher chooses an “ level” to control the probability of rejecting the null hypothesis when it is actually true (i.e., of finding a difference between the two groups when none, in fact, exists in nature). An incorrect rejection of the null hypothesis is termed a Type I error. Peterman (1990) argued that in conservation research, the consequences of committing a Type II error (i.e., of failing to reject the null hypothesis when it is, in fact, false) can be graver than a Type I error. The probability of failing to reject the when it is, in fact, false is designated as and the Power of a test equals Low-power tests of the hypothesis are unlikely to detect a difference between two or more groups when a difference does, in fact, exist in nature. For example, a lowpower test may not detect a significant difference between a inventory at a reference site and an adjacent disturbed site even though significant erosion has occurred. Failure to detect the difference leads to a lack of recognition of the severity of erosion, and a failure to implement the appropriate conservation measures. Although the appropriate power level for a reliable test must reflect the gravity of the issue under examination, Peterman (1990) suggested that, in general, studies should be designed to achieve a minimum of 0.2 and hence a power of 0.80. The power of a test is a function of four factors: the chosen, the variance in the groups, sample numbers (N), and the effect size (the actual difference between the groups). First, the smaller the probability of committing a Type I error ( ), the lower the power (holding the other factors constant). Peterman (1990) questioned the uncritical acceptance of an “ level of 0.05 or 0.01” for conservation work, and argued that an of 0.10 or greater is more appropriate for some designs. Second, the higher the variance in the groups, the lower the power. The CV of reference sites is typically about 19% (see above), and the CV is normally higher for disturbed sites. This variability is largely inherent to the spatial distribution of and cannot be readily lowered (Bunzl et al., 1997; Lettner et al., 2000). Hence, sampling designs have to be made within the constraints posed by the inherent variability of

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The final two factors, effect size and sample numbers, are central to the planning of research designs. McGee et al. (1995) presented a graphical presentation of the relationship between effect size and sample numbers. The power of a given parameterization of the four factors controlling power can also be made using existing statistical software packages (Table 2.3). In this case, the power of a twosample, two-tailed t test with a CV held constant at 20% and the power set at 0.80 is shown. The effect size is shown as the real difference (expressed as a percentage) that exists between the means of the two groups—for example, between the mean inventory at a reference site and the mean inventory at an adjacent disturbed site.

Differences between two means of less than 5% require extraordinarily large sample numbers to achieve a power of 0.80 at any level, and differences of less than 10% require over thirty samples at even an of 0.20. Hence, it will be very difficult to detect low levels of soil loss or gain in a landscape using the technique. Ten samples in each group will be sufficient to achieve 0.80 power, if a 25% difference in true means exists between the two groups at an level of 0.10. Finally, adoption of an of 0.05 and particularly of 0.01 ensure that power will be low for the sample numbers typically used in sampling, unless the differences between the two groups are very large. 2.5.2.3. Sample Numbers for Pattern Development Studies In sampling for pattern development, the objective of the sampling is to ensure sufficient sample numbers for a reliable surface (map) to be interpolated. The

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optimum number of samples will depend greatly on the spatial variability of the radionuclides at the site, the topographical and pedological complexity of the site, and the specific interpolator chosen. Examples of high-resolution surfaces of for floodplains were created with 274 cores from a reach of the River Culm by Walling et al. (1996), and with as few as twenty to thirty samples for simple terrace surfaces by Quine et al. (1999). Burrough and MacDonnell (1998) provided guidelines on the choice of interpolator and the required number of samples. Kriging (sometimes termed geostatistical interpolation) requires very high sample numbers. Webster and Oliver (1992) argued that a minimum of 150 points is needed from each site. Montgomery et al. (1997) used two sample grids, one of 110 samples and one of forty-eight, to construct the variogram for their site. Lettner et al. (2000) used a total of 235 samples from an undisturbed site near Salzburg, Austria, to perform an in-depth geostatistical analysis of the 2.5.2.4. Sample Compositing In a composite sample, two or more individual samples are combined. Compositing is used to refer to two very distinct situations: 1) to combine sub-samples of a single point, and 2) to combine spatially independent (replicated) samples from different points. In the first case, samples that are not spatially independent of each other are composited. The discussion of sample numbers presented above assumes that the samples are spatially independent—in geostatistical terms, it assumes that the spacing between samples is greater than the range. If two or more samples are gathered within the range of spatial dependence, then they are not spatially independent and are sub-samples of the same point and should be composited. The confusion between sub-samples and true, replicated samples is a great concern in field sampling generally and was termed pseudo-replication by Hurlbert (1984). Sutherland (1994) presented an example of a non-parametric, low samplenumber test for spatial dependence. A full geostatistical evaluation of the range requires considerable resources, and sufficient studies have not been conducted to permit a reliable synthesis. As a guideline, each sample should be spaced at least 10 m away from adjacent samples. The compositing of spatially independent samples can also be used in certain types of studies. In designs where only a summary statistics is needed for the sampled area, rather than a measure of the variability within the site, a composite sample can be useful (Wolcott and Church, 1991). If the composite sample is large enough, the assumption is that it will be statistically similar to a pooled sample made from the same number of individual samples, and hence the variability from the composites will be low. Only a few composite samples would, therefore, be needed to give useful confidence limits (Wolcott and Church, 1991). It is critical for this that all samples combined in the composite be of equal size, and that proper aliquoting (splitting) procedures be used. While (with appropriate statistics) composite samples can be used in descriptive and analytical sampling, their use in sampling for pattern is clearly very limited.

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2.5.2.5. Guidelines for Sample Numbers All of the following guidelines assume the use of independent samples gathered using a probability-based sampling design. Descriptive sampling for determining the inventory at reference sites requires a minimum of eleven samples. Sampling for analytical designs (i.e., to compare between two or more groups) require a minimum of ten samples in each group to detect differences in of relevance for conservation planning. The number of samples required to detect differences of < 10% between mean Cs inventories is very high to achieve reasonable levels of power. Sampling for the creation of reliable surfaces (maps) of typically requires sample sizes of twenty to thirty for simple surfaces, thirty to fifty for more complex surfaces, and 100 to 150 for geostatistical evaluation. 2.6. SAMPLING DESIGN Sampling design refers to the way in which the specific points to be sampled in the field are chosen and their relationship to the other points to be sampled. Gilbert (1987) gave an overview of sampling designs, and initially split the designs into non-probability-based and probability-based designs. 2.6.1. Haphazard and Judgement Designs Haphazard and judgement sampling are the major types of non-probability-based sampling designs. As the name would imply, haphazard designs have no particular rationale underlying them and are based on the premise that any sample location will do (Gilbert, 1987); they are to be avoided. Sutherland (1996) criticized much of the sampling in the published literature on reference sites for utilizing haphazard designs. In judgement-based sampling, the researcher uses an understanding of the system under study to choose where to sample. For example, a researcher with a good understanding of the relationship between soil redistribution and slope elements in a region may choose to sample only particular slope elements to rank the erosion status of different landscapes. Webster and Yaalon (1994) argued that a few well chosen samples by an experienced researcher are of greater value than a poorly implemented probability-based design. Judgement-based sampling is certainly of relevance in the reconnaissance phase of the project. Samples chosen in this way cannot, however, be used to develop inventory statistics or to test hypotheses. Judgement-based designs are also of relevance when locating and describing a core for depth distribution of a radionuclide in floodplain studies. In this case, a core or exposure with the greatest possible depth of deposition is desired, in order to give the highest resolution radionuclide record. The selection and description of these cores is more akin to the selection of reference sections in geological mapping than to probability-based mapping.

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2.6.2. Probability-Based Designs Probability-based designs rely on a defined probability that any given point in the landscape could be chosen for sampling. This removes bias on the part of the researcher. Probability-based sampling is required in descriptive, analytical, and pattern development studies as discussed above. An initial distinction in probability-based sampling is between stratified and nonstratified designs. In non-stratified sampling, all points in the study area have an equal probability of being selected; in stratified sampling, points are assigned to predefined groups or strata, and the probability of being selected is weighted proportionally to the stratification scheme.

2.6.2.1. Sampling Designs for Descriptive and Pattern Development Studies Although many types of sampling designs exist (reviewed by Gilbert, 1987), only two main types (random and systematic) are commonly used in the earth sciences. Both simple and stratified random samplings have been used in radionuclide research. Implementation of random sampling programs was difficult in the past, but improvements in global positioning systems allow pre-programming of random sampling locations into the GPS prior to field sampling. Simple random sampling is, however, an inefficient way to assess the summary values for a whole field or strata within the field. Wolcott and Church (1991) found that for sampling of river gravels, up to 500 randomly chosen points were required in order to yield the same quality of statistical information as 100 systematic grid samples. The most commonly used sampling design for radionuclide studies is systematic, non-stratified sampling using either transects or grids (Figs. 2.5–2.10). These sampling plans are very useful for the development of summary statistics in descriptive studies. Grid designs are the most appropriate for the creation of surfaces or maps in sampling for pattern designs.

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Systematic sampling designs are often criticized by statisticians for reasons discussed by Eberhardt and Thomas (1991), but the ease with which they can be used and the efficiency with which they gather information make them very popular in the earth sciences (Wolcott and Church, 1991). For most designs, the spacing between the sampling points is constant for all points in a given transect or grid. The major caution in the use of systematic grids is that the objects to be sampled must not be arranged in an orderly manner that might correspond to the spacing along the transect or the grid. The choice of whether to select transects or grids should be made on the basis of landform morphology and complexity. For level landscapes, such as the ideal reference site, either a transect or grid can be used (Fig. 2.5). Sutherland (1996) recommended the use of a grid sampling design for reference-site sampling. In agronomic sampling, use of a series of transects placed in a zigzag fashion (Fig. 2.6) is typically recommended.

The appropriateness of transects in sloping terrain depends in part on the plan (across-slope) curvature. Where no significant across-slope curvature exists (Fig. 2.7) each point in the landscape receives flow from only those points immediately upslope. In this case, the variability in radionuclide inventories may be captured with a single transect (Fig. 2.7). This type of transect is often termed a toposequence. If significant plan curvature exists, a single transect will not, however, be sufficient. For the landscape shown in Figure 2.8, the single transect running upslope from A would sample only divergent slope elements, and a transect from C would sample only convergent elements. In this case a zigzag design or multiple, randomly oriented transects could be used, but more typically a grid design (i.e., a series of equally spaced, parallel transects) is used. It is important to ensure that all slope

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elements are represented in the grid design. A rule of thumb is that the grid should extend from the level summit of the slope to the toe slope along the long axis of the slope and along at least one complete convergent-divergent sequence across the slope (Fig. 2.8).

In complex landscapes such as the hummocky surface form (Fig. 2.9), the great range of catchment sizes and slope forms requires the use of a sampling grid. The spacing of the grids in this case depends more on the total area of the field to be sampled, but typically grid spacings of 10 to 25 m have been used. The development of the variogram in geostatistical studies ideally requires observations to be made at two or more scales such that the spatial dependence can be evaluated at different spacing (or lags). Lettner et al. (2000) used three grids with areas of and each of which contained eighty-one sampling points. The smaller area grids were nested within the larger grid, such that 235 samples were taken in all. Montgomery et al. (1997) used one major grid with 50-m spacing in one direction and 25-m spacing in another, and six clusters of eight samples with a spacing of 12.5 m between samples in each cluster.

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2.6.2.2. Sampling Designs for Analytical Studies For analytical sampling (i.e., designs concerned with testing for differences between groups), the use of non-stratified, systematic designs may be very inefficient. For example, in a landscape where 60% of the site is classified as one class of landform element and 5% is classified into a second class of element, a 100-point grid should yield approximately sixty points in the major element and five points in the second. If we use the guideline, which requires ten samples in each group for a test of acceptable power, the major element is greatly over-sampled and the minor element is under-sampled.

Appropriate sample numbers for analytical sampling can be efficiently gathered by an a-priori placement of points into the relevant groups or strata, and then a random selection of points within each stratum until the desired number is reached. In the example shown in Fig. 2.10, a grid was placed on the surface and then each point in the grid was classified into one of three slope-element groups. Grid points were then randomly selected until ten samples in each of the three groups were chosen. The summary statistics for the site as a whole can then be calculated by weighting each group by the proportion of the site it occupies, assuming equivalent CV in each of the strata (Eberhardt et al., 1976). The stratified, systematic grid will not, however, yield a regular grid of values that can be readily used to create a surface or map of the site, as is the goal in sampling for pattern.

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Integrated catchment studies also typically require an a-priori stratification of the study catchment into areas that are believed to have distinct ranges of soil erosion and deposition. For the catchment shown in Fig. 2.11, there are five no-till fields, five pastures, and eight conventional tillage fields. Each of these three agricultural land uses could be expected to be associated with a distinct range of soilredistribution rates, and two or more fields (replicates) of each land use should be sampled with a non-stratified grid design. Linear features such as field boundaries and the edges of the riparian areas are likely to act as significant sediment traps, and should be sampled using a transect-based design. The interiors of the riparian forest may be relatively undisturbed and (with appropriate sample numbers) may act as reference sites. Finally, the sediment cores from the reservoir can provide a record of deposition in the catchment. The mean redistribution values for each of the sampled strata can then be multiplied by the area of the strata to provide a complete sediment budget for the area. 2.6.2.3. Guidelines for Selection of Sampling Designs a) Level reference sites should be sampled using a systematic grid design; b) Simple slopes with no significant plan (across-slope) curvature may be sampled using a single transect. The transect should extend from the slope summit to the toe slope at the base of the slope; c) For slopes with significant plan curvature, a systematic, non-stratified grid should be used for sampling for pattern or descriptive sampling. The grid should

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extend from summit to toe slope along the long slope axis and across at least one convexity to concavity sequence across slope; d) For complex slopes with multiple small, local catchments, systematic grid designs should be used. Spacing between points of 10 m to 25 m is commonly used in these landscapes; e) Geostatistical analysis requires the use of grids with two or more scales in a nested design for reliable evaluation of the variogram; f) For analytical samplings (i.e., to test differences between groups) stratified grid sampling should be used. The site should be stratified prior to sampling, and at least ten samples from each group randomly selected for sampling. 2.7. RESERVOIR SAMPLING The main goal of reservoir sampling is to obtain cores in which there has been minimal disturbance to the in-situ physical, chemical and biological structure of the sediments at a series of locations appropriate to the objectives of the project. Careful planning and implementation is crucial to a successful outcome. Reliable sediment cores are the foundation on which the project is built, and mistakes made in sampling can seriously impair the quality of all subsequent work. Relevant site data should be gathered in advance, and should include: a large-scale map of the lake and its catchment, and its precise geographical location (latitude, longitude, altitude); mean annual rainfall; lake area, maximum depth, mean depth (or volume), and bathymetry; catchment area and relief. If the bathymetry of the lake is not known, a bathymetric survey of the lake should be carried out. This is usually achieved by taking depth transects across the lake using an echo sounder. A number of software packages are available for converting the results into a bathymetric map. For a more-detailed account, see e.g. Battarbee et al. (1983). Where relatively few cores are planned, the core sites need to be chosen with some care. Ideally they should be representative of typical depositional regimes in the lake. Sites near steep slopes in the bed of the lake should however be avoided to minimize the possibility of disturbances by episodic slumping. For high-quality records, deep-water cores are generally preferable to marginal sites in order to minimize the possibility of disturbances by wave action and wind stress. The ideal location is a flat central basin. Where there is more than one basin, at least one core should be chosen from each basin. Attempts have been made to model sedimentation patterns in lakes with simple bathymetries (Lehman, 1975; Chen et al. 1978). In such lakes, results from a relatively few cores can be used to make first-order estimates of net rates of erosion from the catchment. In shallow lakes, or lakes with complex basins, the distribution of sediments will be a function of many processes and factors, such as wind and wave action, turbidity currents, sediment slumps, etc. (cf. Håkanson and Jansson, 1983). Furthermore, changing bed configuration or changes in exposure may give

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rise to changes in the pattern of sedimentation through time (Dearing, 1983). In such cases, projects investigating the historical record of net losses of soil from the catchment will necessarily entail a much larger number of cores. In studies carried out by Foster et al. (1985, 1986) on the historical reconstruction of soil losses from two catchments in Warwickshire (UK), cores were retrieved from thirty-one points in the lake in one case, and eighty-one points in the other. Such studies are logistically much more difficult to carry out, and should only be undertaken at sites where there has been adequate preparation in advance. Since detailed analysis of even a single sediment core involves a substantial investment in time and resources, at sites that have not previously been investigated it is advisable to first carry out pilot studies involving a relatively small number of cores. These should be used to make an assessment of the quality of sediment records in the lake, sediment type, typical accumulation rates, and the reliability of chronological techniques. Sedimentation rates have been shown to vary from lake to lake by an order of magnitude or more, and some knowledge of typical values is very helpful in determining the most effective sampling strategy. There are two main approaches to site selection in multi-core studies. The first is to sample at all points on a rectangular grid covering the whole lake. The second is to sample at selected points chosen on the basis of the lake bathymetry, covering all the main depositional zones, which should include marginal sites, as well as all the main basins. The sampling frequency can be less in areas of the lake where the bathymetric pattern suggests that sediments are more uniformly distributed. Deltaic areas close to inlet streams thought to be major sources of eroded soil may require closer attention. In deciding on the sampling strategy, account must also be taken of the methods that will be used for processing the cores. Handling large numbers of cores will be feasible only if the planning includes rapid, cheap and simple methods for assessing, comparing, and correlating them. Detailed radiometric dating is time consuming and expensive and generally only appropriate to a selected subset of cores believed to contain good quality records. Radiometric dates from these primary cores are transferred to the undated secondary cores by establishing core correlations based on the identification of unequivocally synchronous stratigraphic horizons in each core, or group of related cores. In some cases there may be visual stratigraphic features such as a clay layer, or distinct change in sediment colour or texture. More usually the correlations will be based on one or more of measured parameters common to each core. These may include: mineralogical properties, such as water content, dry bulk density, loss on ignition, particle size; geochemical records; biological records (e.g. diatoms, pollen); mineral magnetic properties. Magnetic measurements in particular have been proven to provide a cheap and rapid method of core correlation, and have been used successfully in many studies (Thompson et al., 1975; Bloemendal et al., 1979; Dearing et al., 1981, 1987; Dearing, 1983, 1986; Foster et al., 1985, 1986). A recent survey of different methods

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for logging magnetic properties was published by Nowaczyk (2001). Magnetic features are not always unequivocal (Oldfield et al., 1999), and it is advisable to use at least one other independent method. Since all cores should be analysed for water content and loss on ignition, these two parameters are an obvious choice. Planning of the sampling program should also include details of the procedures for determining the spatial location of each core site within the lake, and the water depth. The spatial location can be determined by GPS, or by surveying. In the latter case readings of the bearing and distance must be taken between the core site and one or more fixed points on the shore of the lake (Battarbee et al., 1983). In small lakes, reference can be made to fixed lines set up across the lake. The water depth will usually be determined using an echo sounder. 2.8. REFERENCES Anderson, J. M., & Ingram, J. S. I. (1993). Tropical soil biology and fertility. A handbook of methods. Wallingford: CAB International. Basher, L. R. (2000). Surface erosion assessment using examples from New Zealand, Acta Geologica Hispanica, 35, 219–228. Battarbee, R. W., Titcombe, C., Donnelly, K., & Anderson, J. (1983). An automated technique for the accurate positioning of sediment core sites and the bathymetric mapping of lake basins. Hydrobiologia, 103, 71–74. Bloemendal, J., Oldfield, F., & Thompson R. (1979). Magnetic measurements used to assess sediment influx at Llyn Goddionduon, Nature, 200, 50–53. Bunzl, K., Schimmack, W., Belli, M., & Riccardi, M. (1997). Sequential extraction of fallout radiocesium from the soil: Small scale and large scale spatial variability. Journal of Radioanalysis and Nuclear Chemistry, 226, 47–53. Bunzl, K., Schimmack, W., Zelles, L., & Albers, B. P. (2000). Spatial variability of the vertical migration of fallout in the soil of a pasture, and consequences for long-term predictions, Radiation and Environmental Biophysics, 39, 197–205. Burrough, P. A., & McDonnell, R. A. (1998). Principles of geographical information systems. Oxford: Oxford University Press. Chappell, A. (1999). The limitations of using Cs-137 for estimating soil redistribution in semi-arid environments, Geomorphology, 29, 135–152. Chen Y. H., Lopes, J. L., & Richardson, E. V. (1978). Mathematical modelling of sediment deposition in reservoirs. Journal of the Hydraulic Division of the American Society of Civil Engineers, 104, 1605– 1612. Dearing J. A. (1983). Changing patterns of sediment accumulation in a small lake in Scania, southern Sweden. In J. Merilainen, P. Huttunen and R. W. Battarbee (Eds.), Palaeolimnology (pp. 59–64). The Hague: Dr. J. W. Junk. Dearing J. A. (1986). Core correlation and total sediment influx. In B. Berglund (Ed.), IGCP handbook (pp. 247–270). Chichester: Wiley. Dearing J. A. Elner, J. K., & Happey-Wood, C. M. (1981). Recent sediment flux and erosional processes in a Welsh upland lake-catchment based on magnetic susceptibility measurements. Quaternary Research, 16, 356–372. Dearing J. A., Håkansson, H., Liedberg-Jönsson, B., Persson, A., Skansjö, S., Widholm, D., & ElDaoushy, F. (1987). Lake sediments used to quantify the erosional response to land use change in southern Sweden. Oikos, 50, 60–78. Dyer, F. J., & Olley, J. M. (1999). The effects of grain abrasion and disaggregation on Cs-137 concentrations in different size fractions of soils developed on three different rock types, Catena, 36, 143–151. Eberhardt, L. L., & Thomas, J. M. (1991). Designing environmental field studies. Ecological Monographs, 61, 53–73.

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Eberhardt, L. L., Gilbert, R. O., Hollister, H. H., & Thomas, J. M. (1976). Sampling for contaminants in ecological systems. Environmental Science and Technology, 10. 917–925. Ely, L. L., Webb, R. H., & Enzel, Y. (1992). Accuracy of post-bomb and in dating fluvial deposits. Quaternary Research, 38, 196–204. Forsyth, T. J. (1994). The use of cesium-137 measurements of soil erosion and farmers’ perceptions to indicate land degradation amongst shifting cultivators in northern Thailand. Mountain Research and Development, 14, 229–244. Foster, I. D. L., Dearing, J. A., Simpson, A., Carter, A. D., & Appleby, P. G. (1985). Lake catchment based studies of erosion and denudation in the Merevale catchment, Warwickshire, UK. Earth Surface Processes and Landforms, 10, 45–68. Foster, D. L., Dearing, J. A., & Appleby, P. G. (1986). Historical trends in sediment yields: a case study in reconstruction from lake-sediment records in Warwickshire, UK. Hydrological Sciences, 31, 427– 443. Foster, I. D. L., & Walling, D. E. (1994). Using reservoir deposits to reconstruct changing sediment yields and sources in the catchment of the Old Mill Reservoir, South Devon, UK, over the past 50 years. Hydrological Science Journal, 39, 347–368. Garcia-Agudo, E. (1998). Global distribution of inputs for soil erosion and sedimentation studies. In Use of in the study of soil erosion and sedimentation, IAEA-TECDOC-1028 (pp. 117–121). Vienna: IAEA. Gilbert, R. O. (1987). Statistical methods for environmental pollution monitoring. New York: Van Nostrand Reinhold. Golosov, V. N., Walling, D. E., Panin, A. V., Stukin, E. D., Kvasnikova, E. V., & Ivanova, N. N. (1999). The spatial variability of Chernobyl-derived inventories in a small agricultural drainage basin in central Russia. Applied Radiation and Isotopes, 51, 341–452. Govers, G., Lobb, D. A., & Quine, T. A. (1999). Tillage erosion and translocation: emergence of a new paradigm in soil erosion research. Soil Tillage Research, 47, 167–174. Govers, G., Quine, T. A., Desmet, P. J. J., & Walling, D. E. (1996). The relative contribution of soil tillage and overland flow erosion to soil redistribution on agricultural land. Earth Surface Processes and Landforms. 21, 929–946. Håkanson L., & Jansson, M. (1983). Principles of lake sedimentology. Berlin: Springer Verlag. Harper, R. J., & Gilkes, R. J. (1994). Evaluation of the Cs-137 technique for estimating wind erosion losses for some sandy Western Australian soils. Australian Journal of Soil Research, 32, 1369–1387. Hurlbert, S. A. (1984). Pseudoreplication and the design of ecological field experiments, Ecological Monographs, 54, 187–211. Hutchinson, S. M. (1995). Use of magnetic and radiometric measurements to investigate erosion and sedimentation in a British upland catchment. Earth Surface Processes and Landforms, 20, 293–314. Ionita, I., & Margineanu, R. M. (2000). Application of for measuring soil erosion/deposition rates in Romania. Acta Geologica Hispanica, 35, 311–319. Lehman J. T. (1975). Reconstructing the rate of accumulation of lake sediment: the effect of sediment focusing, Quaternary Research, 5, 541–550. Lettner, H., Bossew, P., & Hubmer, A. K. (2000). Spatial variability of fallout Caesium-137 in Austrian alpine regions, Journal of Environmental Radioactivity, 47, 71–82. Longmore (McCallan), M. E., O’Leary, B. M., Rose, C. W., & Chandica, A. L. (1983). Mapping soil erosion and accumulation with the fallout isotope caesium-137. Australian Journal of Soil Research, 21, 373–385. Lu, X. X., & Higgit, D. L. (2000). Estimating erosion rates on sloping agricultural land in the Yangtze Three Gorges, China, from caesium-137 measurements. Catena, 39, 33–51. McGee, E. J., Keatinge, M. J., Synnott, H. J., & Colgan, P. A. (1995). The variability in fallout content of soils and plants and the design of optimum field sampling strategies. Health Physics, 68, 320-327. Montgomery, J. A., Busacca, A. J., Frazier, B. E., & McCool, D. K. (1997). Evaluating soil movement using caesium-137 and the Revised Universal Soil Loss Equation, Soil Science Society of America Journal, 61, 571–579. Nagle, G. N., Lassoie, J. P., Fahey, T. J., & McIntyre, S.C. (2000). The use of caesium-137 to estimate agricultural erosion on steep slopes in a tropical watershed. Hydrological Proceedings, 14, 957–969. Nowaczyk N. R. (2001). Logging of magnetic susceptibility. In W. M. Last and J. P. Smol (Eds.), Tracking environmental change using lake sediments, volume 1: Basin analysis, coring, and chronological techniques (pp. 155–170). Dordrecht: Kluwer Academic Publishers.

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Oldfield F, Appleby, P. G., & van der Post, K. D. (1999). Problems of core correlation, sediment source ascription and yield estimation in Ponsonby Tarn, West Cumbria, UK. Earth Surface Processes and Landforms, 24, 975–992. Pennock, D.J. (2000). Suitability of redistribution as an indicator of soil quality. Acta Geologica Hispanica, 35, 213–217. Pennock, D. J., & Corre, M. D. (2001). Development and application of landform segmentation procedures, Soil Tillage Research. 58, 151–162. Pennock, D.J., & de Jong, E. (1990). Spatial pattern of soil redistribution in Boroll landscapes, Southern Saskatchewan, Canada. Soil Science, 150, 867–873. Pennock, D. J., Lemmen, D. S., & de Jong, E. (1995). Cesium-137-measured erosion rates for soils of five parent-material groups in southwestern Saskatchewan. Can. Journal of Soil Science, 75, 205–210. Peterman, R. M. (1990). Statistical power analysis can improve fisheries research and management. Canadian Journal of Fish and Aquatic Science, 47, 2–15. Quine, T. A., Walling, D. E., Chakela, Q. K., Mandiringana, O. T., & Zhang, X. (1999). Rates and patterns of tillage and water erosion on terraces and contour strips: evidence from caesium-137 measurements. Catena, 36, 115–142. Schuller, P., Ellies, A., & Kirchner, G. (1997). Vertical migration of fallout in agricultural soils from Southern Chile. Science of the Total Environment, 193, 197–205. Siggers, G. B., Bates, P. D., Anderson, M. G., Walling, D. E., & He, Q. (1999). A preliminary investigation of the integration of modelled floodplain hydraulics with estimates of overbank floodplain sedimentation derived from Pb-210 and Cs-137 measurements. Earth Surface Processes and Landforms, 24, 211–231. Sogon, S., Penven, M-J., Bonte, P., & Muxart. T. (1999). Estimation of sediment yield and soil loss using suspended sediment load and measurements on agricultural land, Brie Plateau, France. Hydrobiologia. 410, 251–261. Sutherland, R. A. (1994). Spatial variability of and the influence of sampling on estimates of sediment redistribution, Catena, 21, 57–71. Sutherland, R. A. (1996). Caesium-137 soil sampling and inventory variability in reference locations: a literature review. Hydrological Proceedings, 10, 43–53. Sutherland, R.A., Kowalchuk, T.A., & de Jong, E. (1991). Cesium-137 estimates of sediment redistribution by wind. Soil Science, 151, 387–396. Thompson R., Battarbee, R. W., O’Sullivan, P. E., & Oldfield, F. (1975). Magnetic susceptibility of lake sediments. Limnology and Oceanography, 20, 687–698. Wallbrink, P. J., Olley, J. M., & Murray, A. S. (1994). Measuring soil movement using implications of reference site variability. In L. J. Olive, R. J. Loughran and J. A. Kesby (Eds.) Variability in stream erosion and sediment transport, IAHS publication 224 (pp. 95–102). Wallingford: IAHS Press. Walling, D. E., & He, Q. (2000). The global distribution of bomb-derived reference inventories. Report to the IAEA as a contribution to the co-ordinated research projects on soil erosion and sedimentation. Exeter: Department of Geography, University of Exeter. Walling, D. E., He, Q., & Nicholas, A.P. (1996). Floodplains as suspended sediment sinks. In M. G. Anderson, D. E. Walling, and P. D. Bates (Eds.) Floodplain processes (pp. 399–439). New York: John Wiley and Sons. Webster, R., & Oliver, M. A. (1992). Sample adequately to estimate variograms of soil properties. Journal of Soil Science, 43, 177–192. Webster, R., & Yallon, D. H.(1994). The research paper. Informal guide for authors. Catena, 21, 3–11. Wolcott, J., & Church, M. (1991). Strategies for sampling spatially heterogeneous phenomena: the example of river gravels. Journal of Sedimentary Petrology, 61, 534–543. Wysocki, D. A., Schoeneberger, P. J., & LaGarry, H. E. (2000). Geomorphology of soil landscapes. In M. E. Sumner (Ed.), Handbook of soil science (pp. E-5–E-39). Boca Raton: CRC Press. Zhang, X., Walling, D. E., Quine, T. A., & Wen, A. (1997). Use of reservoir deposits and caesium-137 measurements to investigate the erosional response of a small drainage basin in the rolling loess plateau region of China. Land Degradation and Development, 8, 1–16.

CHAPTER 3 SAMPLING METHODS R.J. LOUGHRAN1, P.J. WALLBRINK2, D.E. WALLING3, and P.G. APPLEBY4 1

School of Environmental and Life Sciences, University of Newcastle, Callaghan, NSW 2308, Australia. 2Environmental Hydrology, CSIRO, Division of Land and Water, PO Box 1666, Canberra, ACT 2601, Australia. 3Department of Geography, University of Exeter, Amory Building, Rennes Drive, Exeter EX4 4RJ, United Kingdom. 4 Environmental Radiometric Research Centre, Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom.

3.1. INTRODUCTION Methods for the collection of soil samples to determine levels of and other fallout radionuclides, such as excess and will depend on the purposes (aims) of the project, site and soil characteristics, analytical capacity, the total number of samples that can be analysed and the sample mass required. The latter two will depend partly on detector type and capabilities. A variety of field methods have been developed for different field conditions and circumstances over the past twenty years, many of them inherited or adapted from soil science and sedimentology. The use of in erosion studies has been widely developed, while the application of fallout and is still developing. Although it is possible to measure these nuclides simultaneously, it is still common for experiments to be designed around the use of alone. Caesium studies typically involve comparison of the inventories found at eroded or sedimentation sites with that of a “reference” site. An accurate characterization of the depth distribution of these fallout nuclides is often required in order to apply and/or calibrate the conversion models, described in Chapter 7. However, depending on the tracer involved, the depth distribution, and thus the sampling resolution required to define it, differs. For example, a depth resolution of 1 cm is often adequate when using However, fallout and commonly has very strong surface maxima that decrease exponentially with depth, and fine depth increments are required at or close to the soil surface. Consequently, different depth incremental sampling methods are required when using different fallout radionuclides. Geomorphic investigations also frequently require determination of the depth-distribution of fallout nuclides on slopes and depositional sites as well as their total inventories. 41 F. Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 41–57. © 2002 IAEA. Printed in the Netherlands.

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In the this chapter we describe sampling methods for measuring the depth distributions of and methods for determining nuclide inventories and for sampling radionuclides in depositional areas, and give practical aid on recording site and sample information.

3.2. QUANTIFYING THE DEPTH DISTRIBUTIONS OF FALLOUT RADIONUCLIDES 3.2.1. Depth-Incremental Sampling Using the Scraper-Plate Method The scraper plate—a device specifically developed [by Bryan Campbell, Australian Nuclear Science and Technology Organization (ANSTO)] for establishing the depth distribution of at reference and slope sites—has been widely adopted (Campbell et al., 1988; Loughran et al., 1992; Walling & Quine, 1993). The device has two components: a metal frame that is placed on the ground, and an adjustable metal plate that can scrape or remove fixed increments of soil-depth within the frame (Fig. 3.1). Advantages of the device are that it has been widely used, it provides a large volume of material from a large surface area, it has few moving parts and it is robust and of simple construction.

The frame can be made of angle section steel or aluminium welded at the corners, defining an internal (soil sampling) area of 50×20 cm, or of sufficient size to allow the collection of a large enough sample for detection when 1 cm of soil is

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removed. The frame should be sturdy enough to permit hammering into the soil so that its upper surface is flush with the ground, forming a datum (Fig. 3.1). A metal plate is used to cut or scrape soil within the frame. The plate has a bevelled cutting edge on one of its shorter sides and is designed to fit inside the frame (width approximately 18 cm). The longer side of the plate can be any size for convenient handling, but 40 cm is usually satisfactory. Corresponding holes along the longer sides of the plate at 1 cm intervals allow a bar to be fixed across it using wing-nuts. The bar (total length 42 cm and diameter 1.7 cm), protrudes across the plate and acts as a guide on the frame datum. The bar can be repositioned at 1 cm intervals, so that the exposed cutting edge of the plate can scrape soil at predetermined depths (Fig. 3.2). Where the soil contains a high density of roots and is particularly difficult to loosen using the bevelled scraper plate, it is possible to fix a narrow horizontal blade below the bottom of the plate to serve as the cutting edge.

The mass of soil collected within the frame will depend on its bulk density and, of course, the depth increment involved. Generally, the soil bulk density increases with depth. Surface layers (the upper 2 cm, for example) may contain a substantial amount of organic matter (e.g. leaf litter), therefore reducing the amount of mineral soil available for analysis. Because as little as 200 g (dry weight) can sometimes be yielded from the surface 1-cm layer (Table 3.1), increments of 2 cm are frequently used to ensure the collection of sufficient soil. A trowel, or similar implement, is used to transfer the scraped soil from the pit to a sample bag. The total depth of incremental sampling will depend on the length of the scraper plate and the possible presence of rock. To ensure that the total profile is sampled, a core may be taken from the soil at the base of the rectangular pit after the completion of sampling by the scraper-plate (see Section 3.3 below: bulk sampling). Further analyses can then be undertaken on this core. Even so, a decision on the minimum depth of sampling will be a matter of experience after the initial

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analyses have been completed in the laboratory. In undisturbed soils, is rarely displaced below 250 mm (Owens et al., 1996; Walling and Quine, 1995; Wallbrink et al., 1999) and so this represents a good depth at which to complete the initial depth sampling. If determining the full depth distribution is important, then it is generally better to collect “too many” samples than “too few”—they need not all be analysed if it appears that the maximum depth of penetration has been reached part way down the profile. One approach to determine rapidly the lower limit of is to count the middle sample first (to detect the presence of If is not present then a sample is analysed halfway between the top and the middle. Alternatively, if is present, then a sample is analysed halfway between the middle and the bottom. Thus, by a process of selective sample analysis depending on the presence or absence of decisions are made to select the next sample halfway, either up or down, between the last two “known” measurement points, and the tailing off region is therefore identified. This process also works particularly well for sediment cores, described below. It is advisable that preliminary depth-incremental sampling is carried out to determine the depth of penetration of before a full sampling programme involving both slope and reference sites is undertaken.

The following difficulties may be encountered during sampling by scraper plate: Dead and living vegetation, and/or stones may cover the ground surface. This material should be separately harvested, bagged and labelled. If a surface is too stony for sampling by scraper plate (Fig. 3.3), it may be possible to drive a core tube into it instead. See Chapter 4 (Sample Processing) for the treatment of samples prior to analysis. The natural ground surface intended for sampling may be uneven, perhaps protruding above the datum of the frame. This “above datum” material can be collected separately and, if light in weight, incorporated with material taken from the layer below.

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As sampling progresses, the freestanding walls of the pit may become unstable, allowing some soil to fall into the pit. Care should be taken so that soil is not dislodged; protruding stones can be excavated by knife. The application of water by spray may help stabilise the walls of the pit, but if soil has fallen onto the sampling surface, it should be carefully discarded. Roots should be cut and bagged with the mineral soil for that layer. See Chapter 4 for laboratory treatment of organic matter. Stones may be encountered during sampling. If they protrude through more than one layer, decide to which layer they (mostly) belong; carefully excavate them and include with soil from that layer. Refer to Chapter 4 (Sample Processing) for information on processing stone material in the laboratory. As indicated above, the excavation of a reference pit requires the precision of an archaeological dig. Tools that may assist in this process are brushes (for recovering soil), scalpels (for cutting roots), vacuum cleaners (cleaning off soil surfaces), metal scrapers (for working into square corners), and water spray cans (to stabilise the soil surfaces).

3.2.2. Sampling a Depth-Profile of Fallout

and

Using a Router and Frame

As described above, excess and have much shallower depth distributions than does and so require an alternative method of depth-incremental sampling. One such approach is to use a modified wood router as described by Wallbrink and Murray (1996). The wood router has a series of extension arms attached to the base plate, which allow it to rest on top of a 50x50 cm angle section frame (thickness 5 mm, width 30 mm, height 40 mm) that is pegged into the ground defining a suitable area within which to sample. The depth of the router bit is then set using the standard gauge mounted to the side of the router. This allows control over the vertical extension of the router bit over a distance of about 30 mm, in as little as 1-

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mm increments. The whole router is then moved around inside the locating frame, with the operator holding on to the extension arms (see Fig. 3.4). The spinning router blade dislodges or loosens the soil and sediment particles down to the set depth. The spinning blade is sufficient to cut through tree roots and (if a tungsten bit is used) can also shear through soil particles and larger grains. The loosened or dislodged material can then be vacuumed into a separate bag, and/or scraped up using a brush, ruler and scraper.

After the loosened or dislodged soil has been removed and bagged, the router bit is then lowered by a set amount using the depth gauge mounted on the unit, and the process is repeated. Because the router bit spins at high speed (10,000 rpm) the underlying surface is maintained flat and smooth and there is little contamination between layers. This method can provide a vertical resolution for depth sampling of as little as 1 mm over a ca. 30-mm depth range. The latter is defined by the make and model of wood router used. This depth range is sufficient to capture all of the and the majority of the It is also possible that some wood routers have bits that can extend well beyond 30 mm, thus increasing their potential for depth measuring in soils. It is often necessary to also measure the depth distribution of at the same time as those of and In this situation, the soil needs to be excavated beneath the profile exhumed by the wood router. To undertake this, a smaller scraper plate system can be used, similar to the Campbell (ANSTO) system (Campbell et al., 1988) described above. Here a locating frame is hammered into the base of the squared-off profile. On top of this locating frame sits a sliding frame, which supports a metal cutting blade about 30 cm high and about 20 cm in width. This metal blade

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is moved backwards and forwards across the soil surface, scraping off the exposed soil to dimensions of 20×20 cm. The metal cutting blade has holes 10 mm apart drilled vertically along either side. Pins can be placed through these allowing it to be progressively lowered within its support in the sliding frame. The positioning of the holes provides the vertical depth resolution, which, in this scraper system, is of 10mm increments. The benefits of this router and scraper approach are that very fine depth increments can be taken near the soil surface, allowing accurate characterization of the and profiles where concentrations decline rapidly with depth, as well as providing detailed information on the profile shape for Its disadvantages are that it is quite demanding in terms of labour and time and, because of the fine depth increments, a large number of samples are produced. This can place additional demands on analytical facilities. 3.2.3. An Alternative to the Scraper-Plate Method for Depth Sampling

There are some situations, such as very sandy soils, where collapse of the soil matrix is problematic, and an alternative to the classic scraper approach should be used. One such method described by Bacchi et al. (2000) involves the use of cylindrical PVC core liners. These perform the dual role of defining a known surface area for sampling, as well as supporting the excavated soil column and preventing it from falling into the sampling bay. The method involves placing a circular scraping tool inside a 30 cm diameter PVC cylinder. This tool is manually rotated to dislodge the exposed soil. The unit has been fabricated to take depth-increment layers of 5 cm, through to an overall depth of 40 cm. The sample volume is (Fig. 3.5). The benefit of this procedure is that the PVC cylinder is sequentially lowered into the soil after each increment is exhumed. This protects the sidewalls of the excavation, and prevents contamination of the samples by collapsed soil from upper sandy layers. Adaptation of this method could also involve using smaller depth increments (e.g. 1 cm). The benefits of this approach are that it is less labour intensive and the potential for cross contamination is small. Disadvantages are that the depth increments are large and so the information provided on the depth distribution of nuclides, such as and is limited. 3.2.4. Use of Sectioned Cores

In some circumstances, particularly in moist cohesive soils, it is possible to collect an intact soil core for sectioning, using coring equipment such as that described in Section 3.3. It is, however, important to ensure that this core can be recovered from the core tube without disturbance. Use of a cutting edge with a smaller diameter than the internal diameter of the core tube (cf. Section 3.3.1) will frequently ensure that the core can be removed intact by sliding it out of the top of the core tube. On removal from the core tube, the core should be gently placed in a piece of plastic guttering where it can be sectioned into the required depth increments. It is, however, important to recognize that the coring process may vertically compress the

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core within the core tube. The degree of compression can be ascertained by comparing the length of the core with the depth to which the core tube was driven into the soil. Where it can be assumed that compression has occurred uniformly along the length of the core, the thickness of the depth increments can be adjusted to take account of the compression. Where the degree of compression is likely to vary along the length of the core, it will be d i f f i c u l t to reconstruct the true depth profile and an alternative means of sampling must be sought. If, however, the depth profile is reported in terms of mass depth rather than linear depth, changes in bulk density caused by compression are of limited importance.

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3.3. SAMPLING METHODS FOR DETERMINING FALLOUT RADIONUCLIDE INVENTORIES 3.3.1. Bulk Sampling a Profile to Determine the

Inventory

Once information on the initial depth distribution of is obtained, it is usual for most of the sampling activity to focus on obtaining information on the total inventory at each sampling point. When only the total inventory of is needed, it is sufficient to collect a bulk sample by coring down through the soil. The procedure begins by first selecting a corer of suitable length to extend through the complete profile (this information is obtained by depth-incremental sampling). The simplest form of corer is a steel cylinder with a bevelled cutting edge. There is no standard internal diameter for the cylinder, but usually it is 7 to 10 cm. It is essential to calculate the surface area of the sample so that the total inventory of can be expressed per unit area. A cylinder with a wall thickness of 5 mm may be required if the soil is stony or resistant. In the case of cohesive clay soils, there may be a tendency for the core to become stuck in the core tube and difficult to remove. In such cases, it is advantageous to ensure that the diameter of the cutting edge is slightly smaller than the internal diameter of the core tube. This can be achieved by machining a separate cutting section, which is welded onto the bottom of the core tube (Walling and Quine, 1993). The cylinder is then hammered into the soil normal to the surface or perpendicularly. (If the core cylinder is inserted perpendicularly on a slope, then the sampled area will be greater than that for a sample taken normal to the surface. The sample surface area can be corrected by dividing the core area by the cosine of the slope angle). A protective steel plate or cover, with a welded ring on the undersurface that fits securely over the cylinder, is commonly used to form a strike surface for the hammer. The cover used at the University of Newcastle, Australia, is 20 mm in thickness and 155 mm square, and the core has an internal diameter of 92 mm and wall thickness of 5 mm. The cylinder is driven into the soil until the ground surface is level with its interior. Leaving the steel cover in place for protection, the core is excavated with hand tools (e.g. a mattock and trowel) until the base of the cylinder is exposed. A thin metal plate or trowel is slid under the cylinder so that soil does not escape when the cylinder is lifted. The contents can be directly transferred to a plastic sample bag, or bucket, by tapping the cylinder, or by prising material free with a knife-like tool if the soil is cohesive. The entire sample from within the corer is then mixed together and submitted for total analysis. Where a large number of cores need to be collected, or where sampling must be undertaken when the soil is dry, reliance on manual hammering to drive the core tube into the soil may limit progress. Researchers at the University of Exeter have adapted a motorized percussion hammer to drive the core tube into the soil (cf. Walling and Quine, 1993). In this case the percussion hammer fits directly onto the top of the corer, using a special adaptor and the core tube can be driven into the soil very rapidly. When sampling cohesive soils, or soils with cohesive lower horizons, it

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is not always necessary to excavate the core tube to seal the bottom of the core tube, since the core is unlikely to fall out of the tube when the core tube is extracted from the soil. In such situations, it is possible to make use of a portable winch to extract the core tube from the soil. This will again speed up the operation. Researchers at the University of Exeter have used a small ratchet lever hoist suspended from a “gallows” for this purpose. 3.3.2. Bulk Sampling a Profile to Determine the

or

Inventory

If total inventories of are required, then sampling of the entire soil profile with a single core is inappropriate. This is because the activity of in the upper 10 mm layer of the soil would be diluted beyond detection limits if it is mixed with unlabelled soil to 300 mm depth. A similar argument can apply to in uncultivated soils. A method to overcome this problem involves a process of sequential depth sampling. In this procedure (described in Wallbrink et al., 2002) soils are excavated in a series of steps to predetermined depths, documenting the main differences or activities of and within them. For example, a metal ring of height 30 mm and diameter 100 mm is first hammered into the ground. A cover plate is used such that when it is flush with the ground, exactly 20 mm of the ring penetrates the ground, the remainder sits above the soil surface. The ring prevents the hole from collapsing and defines a specific surface area and volume of soil, which is then excavated by an auger that fits over the metal ring. The auger is specially designed to excavate soil to 20 mm depth. This layer, bagged, labelled, and analysed separately, captures all the and the majority of the surface activity. The first ring is then extracted and a second ring of height 60 mm is placed in the soil, using the method described above, and the enclosed material from 20 to 50 mm depth is extracted using a different auger designed for this depth. This captures the tail of the and, often, the bulk of the Depth increments below this can be taken in 50-mm increments using a narrower gauge regular auger of diameter 90 mm. The metal ring is left in place to support the soil material at the top of the auger hole. The depth of the horizons can be determined either by aligning graduated markings on the auger shaft with the soil surface or by measuring to the base of the hole by ruler. Depth increments below 50 mm generally capture the remainder of the content. At the end of the process, a hole has been excavated in 0 to 20, 20 to 50, 50 to 100, 100 to 150 mm, etc., individual increments. Advantages of the method described above are that the inventories of and can all be determined from the same sample location. The sampling interval is also sufficiently fine that an approximate quantification of the distribution shapes of and can also be made. Disadvantages are that the process is more time consuming than taking a single bulk sample. Additional analyses are also required. Alternatives to the manual augering approach involve mechanical augers or compression augers. These are especially useful if vehicle access is afforded to the site.

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3.4. SAMPLING OF SEDIMENTS IN DEPOSITIONAL AREAS Where the depths of sediment in depositional areas are limited, the methods described in Sections 3.2 and 3.3 above can be used to collect samples for determining the depth distribution of or the total inventory. Where, however, greater depths of sediment are involved, these methods must be modified. Some possible approaches are listed below. 3.4.1. Using Soil Augers In cohesive soils and sediments, it may be possible to sample with a conventional bucket auger. The diameter of the hole can be measured and, hence, the surface area of the sample can be determined. Depth increments will be related to the capacity of the auger bucket, and they can be measured by placing a surveyor’s staff in the hole after the withdrawal of each sample. This method may be particularly useful when sampling deep floodplain and alluvial fan sediments (Loughran et al., 1992). Disadvantages of this method include: material may be dislodged from the walls during augering, there is less control over sampling depth than with the scraper-plate method, stones and large roots may prevent sampling, and dry sediment and soil may fall from the auger bucket when it is being withdrawn. Mechanical corers of the pneumatic or hydraulic type have also been used for sampling soft sediments in lakes and reservoirs (see Section 3.5). 3.4.2. Sampling Sediment Deposits Using the Scraper Method Sampling of dry-land (i.e. not submerged by water) deposits of considerable depth may be achieved using the scraper-plate method. For example, up to 1 m of sediment was sampled at 2-cm intervals within a dry reservoir near Broken Hill, semi-arid New South Wales, Australia (Jones et al., 2000). At an adjacent (dry) reservoir site, over 2.5 m of sediment were sampled in the same way. The procedure entailed digging a pit into the deposit and cleaning a vertical face. The frame was set on a portion of the original surface protected during the excavation. The worker stands in the pit and operates the scraper plate in the normal way. When the full extent of the scraper’s depth-capacity was reached (in this case 30 cm), the sampling surface inside the frame was covered with plastic for protection. Sediments above the margins of the frame were then excavated so that the scraper could continue to be operated, effectively from a new datum. 3.4.3. Sampling Sediment Deposits Using Box Monoliths An alternative method for measuring down-core variations in radionuclide contents is to encase a complete section of the soil profile within a metal box. This is known as a box-monolith core. In this situation, a vertical surface of the deposits is exposed, as described above. A box section of metal, (approximately 10×10×1,000 cm,

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width×depth×height) is then gently hammered into the surface of the exposure (with a rubber-handled mallet) until flush with the surrounding surface. The metal box is then “dug” away from the profile and the exposed face wrapped in heavy plastic. If handled carefully, a complete “intact” core of the deposit can be returned to the laboratory for investigation under more-controlled conditions. It is also desirable for soil and sediment stratigraphy to be described and photographed during any excavation procedure. 3.5. ACQUISITION OF RESERVOIR SEDIMENT CORES Anthropogenic disturbances of the environment have been most intense during the past 100 to 150 years. Sediment records spanning this period will usually be represented within the top 50 to 100 cm, though there are cases where very high accumulation rates may result in greater depths being required. A variety of relatively simple corers capable of collecting cores to these depths have been developed, including gravity corers, piston corers, Mackereth (pneumatic) corers, vibracorers and Russian corers. The choice will to some extent be determined by site characteristics such as water depth, sediment properties, and the depth of sediment that needs to be recovered, though availability and personal preference will also play a role. In making a choice there are, however, two important points that must be kept in mind: it is essential to recover the near-surface sediments and sediment/water interface intact, the depth of sediment recovered must extend to the base of the record (100–150 years). Failure to meet these criteria will seriously jeopardize the prospects for obtaining a good sediment chronology. The tube diameter will typically be between 5 and 10 cm. In near-surface sediments this will usually yield between 2 and 8 g of dried sediment for each 1 cm slice, though larger amounts will be obtained in deeper sections. The bottom edge of the tube should be bevelled to facilitate entry into the sediment. Tubes with a small diameter penetrate the sediments more easily, and are less likely to lose material during retrieval. Excess internal friction during the drive may however generate a pressure wave that deflects some sediment within the “footprint” of the core around the tube, resulting in an incomplete recovery. Large-diameter tubes have smaller losses during the drive, but are more difficult to force into the sediments, and more susceptible to loss during retrieval. The tube itself should be made of a transparent material so as to allow quick visual examination of the core when it is brought to the surface. A more detailed review of different types of corers, their characteristics and the main operating procedures was given by Glew et al. (2001). Here we summarize the essential details of the main types appropriate to studies of recent sediments.

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3.5.1. Gravity Corers

Gravity corers are probably the simplest device for obtaining good-quality sediment cores, and are the easiest to use. They generally consist of a Perspex tube open at both ends and fixed to the base of a heavy metal frame. The corer is allowed to descend freely through the water column. On reaching the bottom of the lake, the weight of the frame drives the tube into the sediments. A device in the frame then seals the top of the core tube so as to keep the sediments in place during retrieval by the attached line. The device for sealing the top of the tube can be tripped by a mechanism that operates automatically once the core tube has penetrated the sediments, or manually by sending down a “messenger.” The latter consists of a small circular ring attached to the recovery line and released from the surface after the corer has come to rest. It descends under its own weight guided by the line and trips the sealing mechanism when it reaches the corer. Kajak et al. (1965) and Glew (1995) show typical designs. The main advantages of gravity corers are that they are portable, simple to operate, and generally recover an intact sediment/water interface. The depth of sediments recovered depends on the weight of the corer (typically 5–10 kg) and the consistency of the sediments, but is usually between 20 and 70 cm. This will be sufficient for many studies, but may be insufficient at sites with high sedimentation rates, or in dense coherent sediments that are more difficult to penetrate. 3.5.2. Piston Corers

In piston corers, the core tube contains a close-fitting piston that is held in position in the bottom of the tube as the corer is lowered through the water column. Once the corer is in position, a restraining mechanism keeps the piston stationary whilst a driving mechanism slides the core tube downwards over the piston into the sediments. In a Livingstone-type corer (Livingstone, 1955), the core tube is physically pushed into the sediments using drive rods attached to a drive head at the top of the tube. They are also used to keep the piston at the bottom of the core tube as the corer is lowered through the water column. Once in position, the rods are retracted through the core tube and locked to the drive head, leaving the piston in place. During the drive, the piston is restrained by a cable passing up through the core tube to an attachment device at the surface. At the end of the drive this cable is fixed to the drive rods so as to keep the piston, now at the top of the core tube, in place during retrieval. In a cable-operated Kullenberg-type corer (Kullenberg, 1947), the core tube is driven into the sediment by a falling weight. As the corer is lowered into position, the driving weight is kept a fixed distance above the drive head by a separate cable and latch mechanism. On reaching the sediments, the tension on the cable is removed and the latch released, allowing the weight to free fall onto the drive head. One of the main advantages of a piston corer is that the frictional forces opposing the core tube as it is pushed into the sediments are to some extent offset by a partial

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vacuum created at the base of the stationary piston. A major disadvantage of roddriven piston cores is that they can only be used in relatively shallow water, whereas Kullenberg-type corers typically lose the uppermost sediment layers.

3.5.3. Mackereth Corers The Mackereth is a piston corer in which the core tube is pneumatically driven into the sediments. The core tube fits within a driving cylinder that is attached at its base to a cylindrical bell chamber that serves as an anchor, and keeps the corer upright on the bed of the lake. Once in place, compressed air injected into the driving cylinder forces the core tube down past the restrained piston into the sediments. The original Mackereth corer (Mackereth, 1958) was designed to recover long (6 m) sediment cores in a single drive. These generally lost the upper 20 cm or so and were not suitable for sampling recent sediments. The Mackereth mini-corer (Mackereth, 1969), designed to collect 1-m cores from the top of the sequence, has generally been very successful in recovering an intact sediment/water interface. It can be operated from a small boat or dinghy and has proved very popular in many studies. Its main disadvantage is the need for compressed air. This is usually provided by a steel cylinder, which, though portable, can be quite heavy. One danger of Mackereth corers is that they can become trapped in sediments with a high static shear strength, or rebound from thick sand or clay lenses.

3.5.4. Vibracorers In a vibracorer (e.g. Smith, 1992, 1998), high-frequency vibrations transmitted to the core tube by a device mounted at top of the tube reduce the shear strength in a thin (1–2 mm) layer of sediment at the base of the core tube, allowing it to penetrate the sediments with relative ease. Because vibracorers fluidize the sediments, they can be used to penetrate sand layers, and compact water saturated silts and clays that would be difficult to recover using a gravity or piston corer. They are less effective in non-saturated sediments, and sediments containing significant amounts of organic degree. In very soft sediments they may disturb the sediment structure.

3.5.5. Russian Corers These consist of a semi-cylindrical chamber attached to a plane face-plate, the width of which is a little greater than the diameter of the chamber. The chamber is pivoted along a vertical axis in the plane of, and attached to the face-plate at a distance of one radius from its edge, allowing the chamber to rotate freely about this axis. The corer is driven vertically into the sediments, and, once in place, the chamber is rotated fully through 180°, enclosing a half-cylinder of sediment. It is then locked in position while the corer is withdrawn from the sediments and pulled back up to the surface.

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Russian corers are not generally suitable for sampling the soft uppermost sediments due to difficulty in obtaining an adequate seal between the chamber and the plate, and the need to open the device in a horizontal position. Where the superficial sediments have been sampled using, e.g., a gravity corer, they may, however, be used to recover deeper more-compacted sediments, provided their depth relative to the superficial sediment can be determined, e.g. by core correlation in the overlapping sections. 3.5.6. Core Retrieval

The smaller types of corers are usually deployed from a small boat or rubber dinghy. Larger corers will need to be deployed from anchored floating platforms. Friction and buoyancy forces are usually sufficient to keep the sediment in place while the corer is brought to the surface. A rubber bung must, however, be inserted into the base of the core tube before lifting it from the water. Core-retaining devices designed to keep sediments in place during retrieval have been developed (Glew et al., 2001). They are, however, problematic, and in most cases unnecessary provided that core tubes of an appropriate diameter are used. The core must be kept upright at all times to preserve the sediment/water interface. This should be examined immediately on retrieval, and the core discarded if there is evidence of disturbance. If the core appears satisfactory, a second bung should be inserted carefully into the top of the tube in such a way as to exclude any air. Both bungs should then be properly secured with tape, and the core tube labelled with an appropriate core name. Where several cores are being collected at the same time, they should be placed in the boat in a vertical storage rack. Before moving off station, the water depth should be recorded, and the location of the core site determined by GPS or by taking bearings to fixed survey points. 3.6. RECORDING OF SITE AND SAMPLE INFORMATION

The accurate collection of soil samples and recording of sample information in logbooks is fundamental to the successful application of fallout-tracer methods. The importance of commitment to this component cannot be underestimated. Firstly, a label for each sample must be prepared, showing site name/code, date, and method of sampling, surface area of the sample, depth of sample increment and any other relevant information. It is best to use two bags for each sample, and to place the label between the bags to prevent soil moisture from destroying it. The innermost bag must have the sample code, date and a brief description written on it using an indelible marker. It is best to repeat this code on the base and the top of each bag. The bags should be securely tied or taped to ensure that no spillage occurs during transfer to the laboratory. It is essential to make detailed notes about the site, including listing the sampling-frame dimensions and depth increments for each sample. If possible, small laboratory scales should be used to measure the mass of each sample, and record this information. If possible, photographs should be taken of the site. It is also important to find out about site history from air photographs,

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maps, and local landholders. Such information may be helpful when interpreting results. Table 3.2 provides an example of a field data sheet used in a reconnaissance survey of soil erosion using in Australia. Most importantly, there is often a delay between submitting samples to the laboratory and their subsequent return. In this situation a detailed description of the broader experimental plan and sampling method(s) in the field notebook will also assist greatly when returning to the data.

3.7. CONCLUSIONS Careful and thorough soil sampling is the most important component of any study. This is an area in which large systematic (or random) errors can be introduced to the data. Unless meticulous notes and observations are made, these errors can be difficult to trace and their influence unknown. It is also one of the major reasons why discrepancies arise in data reported by different authors and studies in the literature. Consequently, it is crucial to note the type and dimensions of the sampling device(s) so that the surface area and depth of samples is known. Care should be taken to avoid contamination of samples by the inclusion of materials from outside

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the sampled area. All materials and samples should be carefully labelled and details noted in field notebooks. Attention to these details should avoid any possibility of jeopardizing the accuracy of subsequent laboratory analyses. 3.8. REFERENCES Bacchi, O. O. S., Reichardt, K., Sparovek, G., & Ranieri, S. B. L. (2000). Soil erosion evaluation in a small watershed in Brazil through fallout redistribution analysis and conventional models. Acta Geologica Hispanica, 35, 251–259. Campbell, B. L., Loughran, R. J., & Elliott, G. L. (1988). A method tor determining sediment budgets using caesium-137. In M. P. Bordas and D. E. Walling (Eds.), Sediment budgets. International Association of Hydrological Sciences Publication 174, 171–179. Glew, J. R., Smol, J. P., & Last, W. M., (2001). Sediment core collection and extrusion. In W. M. Last and J. Smol (Eds.), Tracking environmental change using lake sediments, volume 1: Basin analysis, coring, and chronological techniques (pp. 73–105). Dordrecht: Kluwer Academic Publishers. Glew, J. (1995). Conversion of shallow water gravity coring equipment for deep-water operation. Journal of Paleolimnology, 14, 83–88. Jones, P. A., Loughran, R. J., & Elliott, G. L. (2000). Sedimentation in a semi-arid zone reservoir in Australia determined by Ada Geologica Hispanica, 35, 329–338. Kajak, Z., Kacprzak, K., & Polkowski, R. (1965). Chwytacz rurowy do pobierania prób dna. Ekologia Polska Seria B, 1, 159–165. Kullenberg, B. (1947). The piston core sampler. Svenska hydroggrafisk-biologiska kommissionens skrifter. Tredge Seien Hydrografi, Bd. 1, 1–46. Livingstone, D. A. (1955). A lightweight piston sampler for lake deposits. Ecology, 36, 137–139. Loughran, R. J., Campbell, B. L., Shelly, D. J., & Elliott, G. L. (1992). Developing a sediment budget for a small drainage basin in Australia. Hydrological Processes, 6, 145–158. Mackereth, F. J. H. (1958). A portable core sampler for lake deposits. Limnology and Oceanography, 3, 181–191. Mackereth, F. J. H. (1969). A short core sampler for sub-aqueous deposits. Limnology and Oceanography, 14, 145–151. Owens, P. N., Walling, D. E., & He, Q. (1996). The behaviour of bomb-derived Caesium-137 fallout in catchment soils. Journal of Environmental Radioactivity, 32, 169–191. Smith D. G. (1992). Vibracoring: recent innovations. Journal of Paleolimnology, 7, 137–143. Smith D. G. (1998). Vibracoring: a new method for coring deep lakes. Palaeogeography, Palaeoclimatology, Palaeoecology, 140, 433–440. Wallbrink, P. J., & Murray, A. S. (1996). Distribution of in soils under different surface cover conditions and its potential for describing soil redistribution processes. Water Resources Research, 32, 467–476. Wallbrink, P. J., Murray, A. S., & Olley, J. M. (1999). Relating suspended sediment to its original soil depth using fallout radionuclides, Soil Science Society of America Journal, 63/2, 369–378. Wallbrink, P. J., Roddy, B. P. and Olley, J. M. (2002). A tracer budget quantifying soil redistribution on hill slopes after forest harvesting, Catena, 47, 179–201. Walling, D. E., & Quine, T. A. (1993). Use of caesium-137 as a tracer of erosion and sedimentation: handbook for the application of the caesium-137 technique. Exeter: University of Exeter. Walling, D. E., & Quine, T. A. (1995). Use of fallout radionuclide measurements in soil erosion investigations. In Nuclear techniques, in soil-plant studies for sustainable agriculture and environmental preservation (pp. 597–619). Vienna: Vienna.

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CHAPTER 4 SAMPLE PROCESSING D.J. PENNOCK1 and P.G. APPLEBY2 1

Department of Soil Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5A8, Canada. 2Environmental Radiometric Research Centre, Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom.

4.1. INTRODUCTION Proper sample processing is required in any field and laboratory program. This chapter compiles procedures for sample processing in radionuclide research so as to foster a higher degree of standardization than is currently practised. There are few, if any, special requirements. The stages in typical sample handling for radionuclide research are shown in Fig. 4.1. This chapter includes procedures for treatment of organic materials and additional material on handling samples with significant rock-fragment content because this material is lacking in several of the widely available sources. Additional information on most of the procedures presented below can be found in the methods books edited by Klute (1986) and Carter (1993). Information of relevance for tropical soils was presented by Anderson and Ingram (1993).

4.2. AIR-DRYING, GRINDING, AND SIEVING The initial stages of sample handling are common to most soil- and sedimentprocessing procedures. Air-drying and oven-drying are used at this stage. For large sample masses, air-drying may be more practical. Ensure that the volume of the sample corer (V) is recorded. In the next stage, the sample is disaggregated (either by hand or mechanically) and passed through a 2-mm mesh sieve to separate the soil (<2 mm solids) from the rock fragments (>2 mm). Bates (1993) commented that the soil should not be subjected to sufficient force or abrasion to break up individual sand, silt, and clay particles. Both components should be weighed and recorded as (rock fragments) and (soil) (Table 4.1). Anderson and Ingram (1993) suggested that if the rock fragment content is >5% of the total sample mass, it should be set aside for further analysis (see below).

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The treatment of organic material at this stage depends on the quantity. Finely divided organic material (i<2 mm diameter) will pass through the sieve and should be ground with the non-organic material. Material >2 mm is primarily roots and surface litter or residue. McGee et al. (1995) suggested that root material should be retained and re-incorporated for analysis prior to grinding. Surface inorganic residues should be treated in a similar manner. The specific manner of dealing with organic residues should be documented in the methods section of research reports.

4.3. SUB-SAMPLING AND BULK-DENSITY DETERMINATION An accurate measurement of the bulk density of the soil is required to convert the measured radionuclide concentration to the total inventory (reported in ). At this stage, either the whole sample or, more typically, a sub-sample must be ovendried to reach a constant rate. Specific information on procedures was provided by Blake and Hartge (1986) and Culley (1993). The general steps required are:

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1) Take a representative sub-sample using either a sample splitter or coning and quartering. In coning and quartering, the sample is poured onto a surface to form a cone. Two opposite quarters of the cone are removed, and the remainder is mixed together and re-coned. Continue to remove two opposite quarters until a sub-sample of the required size is obtained. 2) Weigh the sub-sample and place it into a tin container of known weight and then dry at 105°C until a constant weight is achieved. Topp (1993) suggested a constant weight is achieved when less than a 0.1% weight loss occurs in a 6-h period. This will typically occur in 2 to 3 days. Record the weight of the subsample plus container as 3) Dry and cool the container plus sample in a desiccator, and record the weight of the oven-dry sub-sample plus the container as 4) Calculate the gravimetric soil moisture as:

5) Use the gravimetric soil moisture to correct the total soil weight to an oven-dried basis as:

6) The bulk density

of the soil can now be calculated by:

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7) If the radionuclide measurement is to be made on the whole sample, the subsample should be returned to the whole sample at the end of this stage.

4.4. PROCEDURES FOR SOILS WITH A SIGNIFICANT ROCK-FRAGMENT CONTENT Three sources of error in radionuclide measurements due to rock fragments were identified by Auerswald and Schimmack (2000): The separation of fine earth and rock fragments may be incomplete; the fine fraction adhering to the rock fraction is assigned to the tracer concentration of the rock fragments, not the soil. The sample may not contain a representative proportion of the rock fragments. The fine particles adhering to the rock fragments may be dominated by the claysized fractions that have higher radionuclide contents than the soil as a whole. They found that up to 10% of the pool in the soil they analysed adhered to the rock fragments after sieving. Washing of the rock fragments removed a further 9%, but 1% still remained on the fragments. They concluded that errors of several 100 t in soil loss calculations may result if heterogeneity and concentration of the rock fragments are ignored. A second issue relating to rock fragments is their effect of the bulk density of the whole sample. For soils containing many rock fragments, results vary significantly with sample volume, and whole-soil density may differ appreciably from the bulk density of fine earth (soil with all fragments >2 mm removed). According to Vincent and Chadwick (1994), to accurately determine the bulk density of these types of soils, large sample volumes are required. Because large sample volumes have practical limitations, they presented an alternative approach that determines bulk density from modest-sized samples and corrects for the presence of rock fragment using mass-size distribution from large (>40 kg) representative disturbed samples, and rock fragment bulk densities. The correction for the bulk density of the gravel is of most relevance for soils with significant concretionary gravel content, such as many highly weathered tropical soils. For non-concretionary rock fragments, a standard bulk density of is used in the following equations. The following correction should be used after measuring the bulk density of the gravel fragments as shown in the following section (or using the value of for non-concretionary gravel), Bulk volume of concretion (Vbk>2) is determined from mass of gravel fragments and bulk density of gravel fragments

Bulk volume of fines (Vbk<2) is determined by the difference between the total volume of core-sample (V) and bulk volume of rock fragments (Vbk>2):

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Finally, bulk density of the soil (Db<2) is determined from mass of soil (M<2) and bulk volume of fines (Vbk<2) as follows:

The value Db<2 is the bulk density of the soil corrected for the influence of concretions. If gamma spectroscopy analysis is performed only on the soil fraction, this bulk density value should be used for subsequent calculations.

4.5. DETERMINATION OF BULK DENSITY AND POROSITY OF THE GRAVEL FRAGMENT As discussed above, this correction is of greatest relevance for soils with a significant concretion content. The bulk density of the concretions may be simply determined by a modification of the method described by Currie (1966). Concretions should be washed to remove all soil particles and then saturated with water by placement in a beaker of water that is then placed in an evacuating dessicator to which vacuum is applied for 30 min. After evacuation, the excess water is drained off and the concretions transferred to a 250-mL cylinder with a known volume of water. Volume of the concretions is determined by the amount of water displaced The saturated concretions are then poured onto a filter paper to drain excess water and weighed after which they are oven-dried and the oven-dry weight taken Since water evaporates very rapidly, the operations from the desiccator to the weighing of saturated samples must be done rapidly so as to avoid air re-entering the pores. The porosity and density can be calculated using the following equations:

4.6. SUB-SAMPLING SEDIMENT CORES Sediment cores retrieved from the bottom of the lake are normally sub-sampled by extrusion from the core tube. A typical procedure is to place the core tube vertically in a secure frame, and to insert a close-fitting piston into its base. A transparent collar of the same diameter as the core tube is then placed on the top of the core tube and held firmly in place while the core is advanced a pre-determined distance into the collar. Keeping the collar in place, the sub-sample is removed by inserting a thin slicing plate between the top of the core tube and the base of the collar. The slicing plate and collar should be removed carefully, using a sliding action, and a clean spatula used to transfer the wet sediment to a pre-weighed sample container that has been pre-labelled with the core name, sample depth, and container weight. Care should be taken to minimize losses of sediment or water by accidental spillage. Such

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losses will cause errors in the determination of the dry-mass sedimentation rate. The container should then be sealed, and weighed wet as soon as possible to minimize errors due to accidental leakage of water during transport back to the laboratory. An independent record of all measurements should be kept using a notebook or data logger. Notes should be made of any stratigraphic features and a record kept of the sediment type and colour. The sampling tools should all be washed carefully before taking the next slice. For a broader and more detailed description of sub-sampling techniques see Glew et al. (2001). In principle, the thickness of the core slices will depend on the sedimentation rate, and the intended resolution of the sediment record. If the slices are too thick, the temporal resolution will be poor. Slicing too thinly will require a large amount of unnecessary work with little benefit. For dating, since the core must span approximately 130 years in order to retrieve the full record, around twenty-five to thirty slices are required in order to achieve a 5-year resolution. Where the accumulation rate is such that the dating horizon is thought to be less than 20 cm, a common strategy is to sub-sample at 0.5 cm intervals for the top 5 cm, and 1 cm intervals thereafter. If the dating horizon is thought to be between 20 and 40 cm, it may be sufficient to sample at 1-cm intervals for the top 10 to 15 cm, and 2-cm intervals thereafter. Caution should be taken when slicing the cores. Generally speaking, higher accumulation rates should be expected in the deeper parts of the lake, and in deltaic deposits near inlet streams. Lower accumulation rates should be expected in marginal cores away from inlet streams. Ideally the core should be sliced at a field station close to the lake. Since this is often not possible, cores are commonly sliced in the field. This does, however, require greater care in the planning and preparation. If necessary, the cores can be transported back to the laboratory, though where they contain loose un-compacted sediments in the superficial layers they must be kept upright at all times, and shaking kept to a reasonable level. Back in the laboratory, the sub-samples from each core should be reweighed wet to check against water loss and any field errors, oven-dried in the original containers (typically at 50°C) and reweighed dry to determine the water content, and wet and dry bulk densities. 4.7. REFERENCES Anderson, J. M., & Ingram, J. S. I. (1993). Tropical soil biology and fertility. A handbook of methods. Wallingford: CAB International. Auerswald, K., & Schimmack, W. (2000). Element-pool balances in soils containing significant rock fragments. Catena, 40, 279–290. Bates, T.E. (1993). Soil handling and preparation. In M. R. Carter (Ed.), Soil sampling and methods of analysis (pp. 19–24). Boca Raton: Lewis Publishers. Blake, G. R., & Hartge, K. H. (1986). Bulk density. In A. Klute (Ed.), Methods of Soil Analysis. Part 1. Physical and Mineralogical Methods Second Edition (pp. 363–375). Madison: ASA-SSSA. Carter, M. R. (1993). Soil sampling and methods of analysis. Boca Raton: Lewis Pubishers. Culley, J. L. B. (1993). Density and compressibility. In M. R. Carter (Ed.), Soil sampling and methods of analysis (pp. 529–540). Boca Raton: Lewis Publishers. Currie, J. A. (1966). The volume and porosity of soil crumbs. Journal of Soil Science, 17, 4–35.

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Glew, J. R., Smol, J. P., & Last, W. M. (2001). Sediment core collection and extrusion. In W. M. Last and J. P. Smol (Eds.), Tracking environmental change using lake sediments. Volume 1: Basin analysis, coring, and chronological techniques. Dordrecht: Kluwer Academic Publishers. Klute, A. (1986). Methods of soil analysis. Part 1: Physical and mineralogical methods second edition. Madison: ASA-SSSA. McGee, E. J., Keatinge, M. J., Synnott, H. J., & Colga, P. A. (1995). The variability in fallout content of soils and plants and the design of optimum field sampling strategies. Health Physics, 68, 320–327. Topp, G. C. (1993). Soil water content. In M. R. Carter (Ed.), Soil sampling and methods of analysis (pp. 541–558). Boca Raton: Lewis Publishers. Vincent, K. R., & Chadwick, O. A. (1994). Synthesizing bulk density for soils with abundant rock fragments. Soil Science Society of America Journal, 58, 455–464.

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CHAPTER 5 RADIONUCLIDE MEASUREMENT USING HPGe GAMMA SPECTROMETRY P.J. WALLBRINK1, D.E. WALLING2 and Q. HE3 1

Environmental Hydrology, CSIRO, Division of Land and Water, PO Box 1666, Canberra, ACT 2601, Australia. 2Department of Geography, University of Exeter, Amory Building, Rennes Drive, Exeter EX4 4RJ, United Kingdom. 3CEM Centre, University of Durham, Stockton Road, Durham DH1 3UZ, United Kingdom.

5.1. INTRODUCTION This chapter provides an overview of methodology for determining the activity of and other environmental radionuclides in soil and sediment samples using gamma spectrometry. Section 5.2 describes the components of typical gamma spectroscopy systems. Section 5.3 outlines procedures for calibrating HPGe detectors and for converting gamma peaks to activities Section 5.4 summarizes the role of computer software in converting radionuclide spectrum to quantitative activities, and Section 5.5 provides some quality-assurance procedures. The contents of this chapter are not exhaustive nor are they meant for use as an operator manual. For such detailed information, the reader is encouraged to utilize references and further reading in Section 5.7. 5.2. LABORATORY MEASUREMENT OF SAMPLES USING BASIC GAMMA SPECTROMETRY There are several methods for determining the gamma-emitted radioactivity in samples of soil and sediment. However, the most cost-effective method is by highresolution, low-level gamma spectrometry techniques using high-purity germanium (HPGe) detectors. In simple terms, the radionuclides within the soil (or sediment) emit gamma photons at known energies. These interact with the germanium in the detector, which in turn emits signals corresponding to the energies of the incoming photons. The signals from the detector crystal are routed through an amplifier and directed to a Multi Channel Analyser (MCA) system. Here, the signals are displayed as a spectrum in which emission counts are plotted against radionuclide energies. Software packages then convert the peak-count information to specific activities using calibration procedures. These components and how they work together to form a gamma spectrometry system are described in detail below. 67

F.Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 67–96. © 2002 IAEA. Printed in the Netherlands.

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5.2.1. Principles of Gamma Spectrometry Most detectors are fabricated from high-purity germanium crystals, which are mechanically ground to a cylinder of varying dimensions. The germanium crystal generates free electrons in response to absorbing energy from ionizing radioactivity (such as gamma rays from in a soil sample). The magnitude of the charge in the crystal is directly related to the energy of the incident gamma ray. The crystal behaves as a semiconductor through which a high reverse-bias voltage is passed at cryogenic temperatures. Under these conditions, the charge (electron hole pairs) produced by absorption of the gamma ray is then swept to special contacts on opposite sides of the germanium crystal by an electric field. The resulting electrical pulse is integrated by an amplifier producing an output voltage, the pulse height of which is proportional to the incident photon energy (ORTEC, 1991). The shape, position and thickness of the contacts determine the detector ‘configuration’ and its suitability for use in measuring radionuclides of a particular energy range. There are many different configurations for the shape of the germanium crystal, the ways in which voltage is applied, and how the resulting charge from the gamma rays is collected. In Fig. 5.1, the different detector configuration types available from the Canberra Nuclear range, are illustrated. The diagram also indicates the corresponding energy ranges over which they are ideally suited. Similar information is given in Table 5.1 for a selection of detectors from the ORTEC range. In all cases, the detectors are suitable for measurement of which is a gamma emitter at 662 keV.

5.2.2. Difference Between an ‘N’-Type and a ‘P’-Type Detector When a detector is fabricated, thin layers of semiconductor materials are used to establish its electrical contacts. Detectors generally have a thick lithium donor contact and a thin boron receptor contact If the contact is on

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the outer detector layer, then it forms a layer of attenuating material through which gamma rays have to pass. The resulting transmission loss is small for high-energy photons, but can become significant at low energies (i.e. <100 keV). This is no problem for measuring at 662 keV, however it becomes problematic when attempting to resolve the peak at 46 keV.

In this situation, an alternative is to reverse the contacts such that the thin boron layer becomes the outer contact and the thick lithium layer becomes the inner contact. This configuration increases the detection efficiency significantly, especially below 100 keV, thus making it suitable for analysis of Those detectors with the thick contact in an interior figuration are known as ‘N’ types, and those with the thick window in an exterior configuration are known as ‘P’ types. In Fig. 5.1, the coaxial Ge would be classed as a ‘P’-type detector and the REGe is an ‘N’ type. 5.2.3. Alternative Detector Geometries, Well Detectors As can be seen from Fig. 5.1, there are several alternatives for detector configuration, and this determines the energy range over which they perform best. However, most of these assume that sample mass is not limiting, i.e. that there will always be enough sample material presented to the detector such that it can perform to its specified limits. Thus, alternative situations are also worth considering. For example, reservoir-core or suspended-sediment samples can be severely masslimited. In this situation, some detectors are constructed to offer maximum energy response for small sample masses. One such detector geometry involves a re-entrant volume (for the sample) created within the detector crystal itself. This geometry is known as a well detector and an isometric cutaway view of such a configuration is given in Fig. 5.2.

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These detectors have a high efficiency for small mass samples because the sample is effectively surrounded by active detector material. In most cases the reentrant hole is not cut all the way through the detector and some active germanium material is also left at the base of the well. This is commonly known as a geometry. In addition, the thin contact is on the inside of the well volume and the thick contact is on the outside. ,The loss of efficiency at low energies with the ‘P’-type well detector is compensated for by the greater resolution afforded by the re-entrant geometry. This gives them inherently good response to low-energy gamma rays in the range 20–100 keV. This is ideal for measuring in reservoirsediment samples.

5.2.4. Detector Construction and Cryostatic Cooling In addition to the electrons that are excited within the crystal as a function of gamma-ray interactions, further excitation can occur as a result of thermal energy. This additional excitation and electron activity produces background noise in the system. In order to reduce the effect of this phenomenon, detectors are usually operated at very low temperatures. For practical reasons, this is usually achieved by cooling detectors with liquid nitrogen. Fig. 5.3 shows a typical detector set-up with cryostatic cooling. The main components of the system are the cooling rod (usually made of copper), the Dewar container (for storage of liquid nitrogen), and the fill collar (for refilling the Dewar).

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The cryostatic cooling systems provide the following features: cooling of the detector to obtain stable operating temperatures; high quality vacuum in the cryostat to avoid adsorption of contaminants on the detector surface and for thermal insulation; suppression of heat transfer between cool inner parts and warm outer surface of the cryostat; mounting for the electrical contacts; and isolation from external vibration to avoid system noise (microphonic) interference.

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5.2.5. Electronic Components Associated With Gamma-Spectroscopy Systems Several electronic components are associated with gamma-spectrometry systems. The different components and their relationship to one another as illustrated by dotted lines, are shown diagrammatically in Fig. 5.4. Details of each item and its role are given below. High-purity Ge detectors are usually fitted with a charge-sensitive preamplifier, which acts as an interface between the detector crystal and the pulse-processing and analysis electronics further along the gamma-spectrometric system. The preamplifier is often assembled as an integral part of the detector housing itself. It takes the charge produced from the detector (by the gamma radiation from the sample) and integrates and amplifies this to produce a step-function pulse, the amplitude of which is proportional to the total charge. The first stage usually includes a FET circuit, which is located inside, or adjacent to, the cryostat and is also cooled to reduce background-noise interference.

The second component in the system is the amplifier. The amplifier primarily takes the pulse signal from the preamplifier and considerably magnifies it. It also filters and shapes the incoming pulse to enhance the signal-to-noise ratio. This improves the resolution and shortens the response time to prevent overlap between pulses. Count rates for radionuclides in environmental samples are generally less than 100 counts per second, thus the amplifier needs to perform best in this range.

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Charge collection within the germanium detector (created by interaction with gamma photons) occurs best when a bias voltage is applied across the detector volume. This is usually in the range ±1,000 to 5,000 V and is applied by a highvoltage supply unit. It is important for high voltage supplies to be stable, and in this respect most units have circuits to regulate against drift due to changes in temperature, or in mains power voltage. When using high voltage supplies in combination with preamplifiers equipped with a field effect transistor (FET), the voltage amount should be increased slowly to avoid damage to the FET. Similarly, the voltage should be decreased slowly when disconnecting the voltage supply. These electronic components require a mains power supply and a physical location within which they are housed. This can be provided by a NIM-bin (nuclear instrumentation module-) in which the amplifier, high-voltage supply, analogue to digital converter and test pulse generator can be simply plugged into locations in the rack. NIM-bins are of a modular design, the NIM standard also defines the pulse and logic specifications for the signals passing between the different modules inserted in the bin. There is high degree of compatibility and most components from the larger manufacturers (i.e. Canberra Industries and ORTEC International) will fit, and can be interchanged, within them. A single NIM-bin can provide housing for components for up to three detectors. The analogue signal produced by the detector and shaped by the amplifier needs to be converted to a digital signal prior to registering in the MCA. This is undertaken using an analogue to digital converter (ADC), which effectively converts the analogue signal from the amplifier to a digital value. Analogue to digital converters are reasonably expensive, and they can usually only process one incoming pulse at a time. One method for putting several pulses (i.e. from more than one detector) through to the ADC is by use of multiplexing. A multiplexer, or mixer-router, can take the separate counting chains from four, eight or sixteen individual inputs and route them through to a single ADC. However, this should be used only for low activity, or environmental-level gamma spectrometry, as high count rates can overload the mixer router leading to a phenomenon known as dead time, in which counts for channels are lost. The pulses that emerge from the ADC are then registered in one of the channels of the multi-channel analyzer (MCA). The MCA is often hardwired into the computer system (via an electronic circuit inserted into the motherboard). The MCA provides the means by which the counts from the detector are stored according to the energy that produced them. It performs a number of tasks including collecting and sorting the input pulses, storing those data in a spectrum, providing a format to display the data on the computer screen, and performing some analysis of the data. The operator can also use it as a diagnostic tool to check the operational performance of the system (i.e. determining full width at half maximum FWHM resolutions). The maximum number of channels into which a spectrum can be divided is usually 8,192, which, for a typical gamma spectrum, results in a resolution of about 0.225 keV per channel.

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5.2.6. Factors Affecting the Precision of Gamma-Spectrometry Analyses

A typical erosion study involves analysis of soils and sediments, although it can also include biological material such as plant and animal tissue or organic matter. The main objective is to achieve an analysis of the activity of the sample, generally within an error of +5–10%. Several factors contribute to the overall level of accuracy obtained, including: the efficiency of the detector, the activity of the sample, the mass of sample, the geometry used in presenting the sample to the detector, internal and external background interference, and the quality and thickness of lead shielding. Each of these factors is described in more detail below: The term efficiency is often used to describe detector performance. However, efficiency can be measured in various ways. For example, detector efficiency was often referred to as relative efficiency. This is a measure of the performance of a detector crystal, relative to a 3×3 inch (75×75 mm) NaI (sodium iodide) crystal in which the source is placed at 25 cm from the detector crystal. However, this term is mostly historical and relates to a time when NaI (Ti) detectors were commonly used to measure gamma rays. A more commonly used terminology is absolute efficiency. This is defined as the number of impulses recorded by the detector with respect to the number of gamma photons actually emitted by the radiation source. This value depends on various detector properties (i.e. ‘P’or ‘N’ type) and the counting geometry used, specifically, the sample shape, volume, and distance to the detector. Calculated absolute efficiencies for ‘P’-type and ‘N’-type detectors using material in a disc geometry (which contains approx 40 g dry mineral material) are shown in Fig. 5.5. As expected, the absolute efficiencies of these two detector types show a similar slope above 100 keV for this geometry. However, below 100 keV, the curves spread significantly with values of between 2 and 9% at 46 keV (i.e. The differences are due to the different way in which the detectors are constructed. The lowest absolute efficiencies are associated with the ‘P’-type detector, which is less sensitive to incoming photons at low energy ranges because it has the thicker n contact on the outside. Conversely the ‘N’-type detector has a higher absolute efficiency below 100 keV. The activity of the sample can also be important. For example, the counts that accumulate at a given energy range are due to genuine photon emissions from the sample plus those from background interference. However, if the background is constant, then a sample with high activity will accumulate relatively more counts in the peak compared to the background. Thus, as the total area of the peak increases, the relative size of the background input decreases, as does the proportional background error. Figure 5.6 displays a series of curves giving the estimated standard error (%) for a suite of radionuclides as a function of the

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specific activity. The data were collated using the methodology outlined by Murray et al. (1987) in order to assess minimum detection limits. They emphasize the fact that as a sample activity increases, the estimated standard error decreases, and that conversely as the activity decreases, then the relative errors will increase.

The sample mass and geometry in which this is presented to the detector can also have a major bearing on the precision of the final analysis. Clearly it is best to present as much sample material to the detector as possible, in order to increase the total number of photons emitted by the sample, and thus potentially captured by the detector crystal. However, there are trade offs due to sample selfattenuation. This is where low-energy photons (such as those for at 46 keV) emitted from the sample are absorbed within the sample matrix itself, and are thus not able to interact with the detector crystal. Nonetheless, for most detector set-ups, the measurement of sample activity and calculation of minimum detection limits are improved by using large mass samples. Table 5.2 gives data outlining experimentally derived minimum detection limits for a suite of radionuclides for two different detector configurations and geometries containing two different sample masses. It can be seen that the minimum detection limits for all the nuclides listed were lower in the mineral cup geometry (250 g of material) than those for the disc geometry (40 g of material). In addition. the ‘N’-type detectors had lower minimum detection limits than the ‘P’ types.

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The geometry and form in which the sample is presented to the detector are also important. For example, CSIRO Land and Water laboratories use three different geometries. The dimensions of these are given in Fig. 5.7, and are known as stick, disc, and cup respectively, in order of increasing size. Other laboratories use inverted Marinelli beakers, or varying diameters and thicknesses of the disc form. The selection of which geometry to use is often a function of available sample size. Where material is abundant (such as from soil cores), then the largest available geometry is usually preferred (according to the benefits outlined in Table 5.1). On the other hand, the sample size for cores from depositional areas in lagoons and swamps, or even suspended sediment material from rivers, is often mass-limited. These are best prepared in smaller disc-shape, or stickshape geometries. Samples prepared in the inverted-Marinelli shape (Figure 5.7) are fitted over the end of the detector and effectively surround the germanium crystal assembly. Samples in the planar-disk form are placed directly on top of the detector can and held in place by a locating ring. The rod samples are used only in the re-entrant of the well detector, the latter having the advantages outlined in Section 5.1.3. Background interference is a major factor in achieving acceptable minimum detection limits and precision in analyses. The major sources of background interference can be divided into two main types; (i) internal and (ii) external (Murray et al., 1987). The origin of the former can be in the materials used to build the detector itself, which emit interfering gamma rays at the same energies as those in environmental samples. These contribute mainly to the peak itself. For example, Murray and Aitken (1980) reported on the contribution of natural U and Th series nuclides to detector backgrounds. It is now possible to commission the construction of detectors directly from manufactures in which certain materials are avoided. Examples of background spectra from detectors in which attention has, and has not, been paid to material used in detector construction were given by Murray et al. (1987). Large differences were found between the spectra. Materials commonly used in low internal background detectors are magnesium and copper, while aluminium is avoided. Beryllium windows are often used to permit better passage of low-energy photons. The second component of background noise (ii) is that external to the system. This is generally due to the inherent radiation environment to which the detector is exposed, and usually affects the whole spectral background. Some researchers go to great lengths to ensure that they are located in a low-background environment. For example, high-precision laboratories are often placed far underground (to avoid cosmic radiation) while whole counting rooms have been lined with copper. Simpler and more cost-effective methods, however, involve close attention to the quality and thickness of lead shielding around the detector itself. For analyses of radionuclides at environmental levels, in particular and the provision of a lead shield (of thickness 100 mm) is usually considered adequate. The purpose of this shielding is to attenuate high-energy photons from all sources external to the detector. Within this, it is also advisable to install a liner of either copper or steel (thickness 10 mm), the purpose of which

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is to attenuate lead photons emanating from the lead shielding. If possible, these materials should be selected and/or tested for low inherent activity at the energy ranges of interest.

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Figure 5.8a shows a typical shield configuration from Canberra™. It involves an outer jacket of 10 mm carbon steel, an inner shield of 100-mm-thick lowbackground lead and a graded liner of tin and copper. It is manufactured for use with a detector in a vertical configuration. The same shielding effects can also be custom built. For example, bricks constructed of aged lead can be purchased via merchants. The bricks are then used to build a “castle” of lead surrounding the detector itself. If there is access to a workshop then sliding lid assemblies, floor mounts and internal steel and copper liners can all also be manufactured costeffectively. Custom-built lead shielding and sliding lid assemblies in the CSIRO laboratory are shown in Fig. 5.8b. 5.3. DETECTOR CALIBRATION, METHODS FOR ANALYSIS AND CALCULATION OF SAMPLE ACTIVITY Several methods are used for calibrating detectors for analysis of radioactivity in samples at environmental levels. A common procedure involves direct calibration using standard sources of known activity. This method is employed at the CSIRO Land and Water laboratories and by the University of Exeter laboratory and is described in detail below.

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5.3.1. Direct Calibration The laboratory at CSIRO contains eight working gamma spectrometers. These are two ORTEC HPGe closed ended ‘N’-type coaxials, one Canberra HPGe closed ended ‘N’-type coaxial, one ORTEC HpGe well detector ‘P’ type, one Canberra HpGe well detector and three Canberra BeGe ‘N’ types. These are directly calibrated using standard sources of known activity. The method works by establishing a normalized count rate per standardized mass, activity, and count time for each radionuclide energy line, geometry and detector. There are several advantages to using a direct calibration, over an efficiency-curve approach. For example, it overcomes problems arising from the different attenuation characteristics of the different gamma emitters within the range of 46 to 662 keV and it is not subject to problems with cascades (true coincidence summing) and any errors associated with determining the efficiency curve. The overall method is based on that outlined in Murray et al. (1987). The different procedures for and as well as for (and other U-series elements) are outlined separately below. 5.3.1.1. Calibration standards for and The and standards used for calibration are based on standardized solutions purchased from Amersham International. A quantity of these solutions is evaporated to dryness on an appropriate ground matrix (such as a low-activity sand) and then

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homogenized by ring-mill grinding before casting. Replicate standards of each nuclide for each sample geometry are prepared. These replicates provided an estimate of the errors associated with the mechanical preparation of the standards. Each standard is counted on each of the detectors for a period of ~84 ksecs. The total peak area, less the background, is converted to a normalized count rate (counts ksecto which the count rate of “unknown” soil/sediment samples is then be compared to calculate their activity The ‘N’-type detectors used in this work are able to resolve the 662-keV line of from that of an interfering line at 665 keV. Consequently, no corrections for the presence of this nuclide were necessary. There is no significant interference near the peak at 478 keV. Standards for are prepared using potassium sulphate and potassium chloride cast with an inert material in the same manner as for and above. 5.3.1.2. Calibration Standards for and Uranium Series Nuclides Excess is usually determined by subtracting the concentration of from that of its parent, However, analysing for and requires calibrating the detectors for the series, of which both are daughters. The process begins by creating U-series standards from uranium ore of known activity (BL-5) provided by CANMET in which the is in equilibrium with The ore is diluted by weight into the same inactive matrix as the and standards, and then ground in the ring-mill again. Three replicates of each geometry are then made and set aside for at least five half-lives of (23 days, to allow build up of the radon daughters, and to equilibrium with the parent These standards are then counted in the same way as described for generating normalized count rates for (186 keV), (63 keV), (63 kev), (186 keV), (295 keV), (352 keV), (609 keV) and (46 keV). The concentration is then determined assuming secular equilibrium with its radon daughters. 5.3.1.3. Materials and Methods Used In Preparation Of Standards and Samples The approach at CSIRO LW laboratories is to utilize a combination of aluminium moulds and polyester resin to create the different geometric shapes required (Fig. 5.7). The moulds themselves are constructed from a series of components, which if assembled in the correct order leaves the appropriate geometric shape exposed as a void inside them. The soil/sediment powder (following ashing and grinding in the ring-mill) is then mixed with polyester resin and a small amount of hardener is added, ~1% by volume of resin. This mixture is then poured into the moulds while still viscous. The weight of the soil/sediment sample, the polyester resin and the hardener are all carefully noted during this process, in order to calculate the net amount of soil/sediment retained within each sample. Typical sample retentions by using this process are ~ 8, 40, 170, 250 g in the stick, disk, puck, and cup geometries respectively. After 24 h of curing, the moulds are then dismantled to reveal the sample in solid geometric form. There are advantages and disadvantages to producing soil/sediment samples within a polyester resin matrix. Some of them are listed below:

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i) The determination of excess

(i.e. unsupported or requires analysis of both and via decay from its gaseous daughter The polyester resin remains gas tight, ensuring equilibrium between and its daughters in the lower part of the uranium decay chain. ii) The standards used to calibrate detectors are prepared in the same three geometries using the same polyester resin as the “unknown” samples. This ensures constancy of sample matrix and density between them, reducing the potential for any systematic errors. iii) The polyester resin matrix is very robust, which reduces the chances of breakage and physical damage; in addition they can be stored for long periods for future access. iv) Disadvantages of this approach include the effort and cost of preparing samples with polyester resin. The sample also remains inaccessible. It can be retrieved only by ashing in a muffle furnace.

5.3.1.4. Alternative Approaches For Sample Preparation Several methods are available for presenting samples and standards to the gamma detector, including plastic containers (Marinelli beakers), reusable polyurethane moulds, and pressing samples into gas-tight tin or plastic containers with a hydraulic ram. The advantage of these latter approaches is that they are non-destructive, and the user is able to retrieve the samples. This makes it easier to physically examine the material after processing or further analyses on the same sample material are possible. However, all approaches must meet several criteria: they must have a reproducible geometry, be able to contain the uranium gas radon where is being analysed, be easy to prepare and provide minimal risk for the handler.

5.3.2. Computational Procedures For Detector Calibration and Calculation of Sample Activity The preceding sections have described the components necessary to install and set up a gamma system, as well as some general methodology on how to calibrate a system to determine the activity of unknown samples. In the following section, specific examples of some of the key steps in the calibration and activity determination process are described. As above, calibration of a detector system involves deriving an energy calibration (the relationship between the channel-numbers on the MCA system and the gamma energies of specific radionuclides) and an efficiency calibration (the efficiency of the detector for capturing gamma rays of specified energies).

5.3.2.1. Detector Energy Calibration The channel locations of specified gamma rays (with known energy) on the MCA of the gamma spectrometer can be determined by counting a standard, or standard

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sources, containing the radionuclides and matching them to the corresponding full energy peaks (FEPs) of the gamma rays. 5.3.2.2.Detector Efficiency Calibration Once a detector has been energy-calibrated, its efficiency for a specific gamma ray (with single energy emitted from a specific radionuclide) must be calculated in order to determine the overall activity of the radionuclide in the sample. The detector efficiency for a specific gamma ray is defined as the ratio of the net FEP count rate of that gamma ray from a standard, compared to its known emission rate where the emission rate is defined as the total number of gamma rays emitted per unit time:

As outlined in Section 5.2.6, the detector efficiency is dependent on a number of factors, including the composition of the standard, the geometry of the sample, and its position in relation to the detector (both influence the solid angles of the sample in relation to the detector crystal). In practice, the efficiency calibration for a specific gamma ray involves simply obtaining the net counts in the FEP of the gamma ray from a radionuclide standard being counted by the detector. This occurs after the FEP position of the gamma ray on the MCA is established and the region of interest (ROI) set. The net counts in the FEP of the gamma ray are calculated by subtracting the counts produced by the interference of other gamma rays and the background noise from the total counts. This can be done manually or using the data-processing system of the spectrometer. At Exeter University, the ROIs for the various radionuclides are set at 42.0 to 47.5 keV for 346.0 to 354.5 keV for and 656.0 to 664.5 keV for In the following discussion, counts refer to counts recorded in the ROI. If the activity of a radionuclide standard was at time (yr) when it was made, and it was counted on a detector at time t (yr), the activity efficiency f of the detector, which is defined as the efficiency multiplied by the emission probability r of this gamma ray:

can be calculated for the particular container used to pack the standard viz.:

where: = count time (s), = total counts,

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= mass of standard (kg), = background counts of an un-spiked sample (same container and mass) (0 for both and = corresponding background count time (s), decay constant of the radionuclide is the half-life (yr),

The efficiency f is clearly also a function of the standard/sample geometry (such as the shape of the container and density and volume of the material used to make the standard). It is emphasized that the unit of given above is in If the number of gamma rays per kilogram per second was given as for the radionuclide standard, then the following conversion is needed to calculate

where: the emission probability of the radionuclide for the specific

5.3.2.3. The Effect of Sample Geometry on Detector Efficiency As discussed in Section 5.2.6, it may be important to take into account the effect of sample geometry when calculating sample activity for a specific radionuclide. To demonstrate how efficiency varies with sample geometry, Fig. 5.9 illustrates the relationship between efficiency and sample mass for standards packed using plastic pots (inner diameter 8.0 cm, outer diameter 9.5 cm, inner height 6.0 cm and outer height 6.5 cm) measured for a gamma detector being used at Exeter University. In this case, the detector activity efficiency can be expressed as an linear function of mass m (kg) of the standards:

It is, therefore, suggested that when using plastic pots to pack samples, a constant efficiency for pots containing different mass should not be used. Rather, a varying efficiency, such as that represented by equation 5.5, should be deployed to calculate sample activity. In situations where density varies among samples, the activity efficiency may be represented as a function of sample height in the pots. When using Marinelli beakers to pack samples, the sample geometry should be the same as that of the standard used for efficiency calibration.

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5.3.2.4. Activity Calculations The specific activity of a radionuclide in a sample, A at the time of analysis can be calculated from the detector efficiency and values of relevant parameters, viz.:

where: T = count time (s), C = total counts, = background counts without sample (0 for = corresponding background count time (s), M = mass of sample (kg), f(M) = activity efficiency.

and

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5.3.2.5. Calculation of Areal Activity Some times, areal activities or inventories for sectioned cores or bulk cores are needed. For a sectioned core, the areal activity can be calculated from:

where: = total mass of the ith section (kg), = activity of the sub-sample of the ith section (Bq S = corer area For bulk cores, the areal activity can be calculated as:

where: = total mass of the bulk core (kg), A = activity of the sub-sample of the bulk core analysed (Bq S = corer area

5.4. SOFTWARE PACKAGES FOR GAMMA SPECTROMETRY ANALYSIS A large amount of data is produced by HPGe gamma-spectrometric systems, and this can be rapidly and accurately processed by computer software. The tasks required for such software range from simple handling of the MCA spectrum data, through to processing and analyzing the spectrum data to convert it to radionuclide activities, or some combination of both. Software falls into three main types. The first is hard-wired into the computer (i.e. via a circuit board inserted into the PC motherboard) and is usually a program such as an MCA system. It undertakes operations such as capturing and presenting count information from the ADC, determining position of peaks in a spectrum, and performing energy calibrations. A second set of programs operates outside the MCA environment and is used for post processing of the spectrum. They can undertake full calibration of the data and conversion to nuclide concentrations. The third type attempts to fulfill all the functions above in which spectra can be analysed immediately after acquisition (Gilmore and Hemingway, 1995). Section 5.4.1 describes some of the tasks required of such software and Section 5.4.2 gives details of the software that is commercially available.

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5.4.1. Tasks Required of Gamma-Spectrometry Software A thorough description of the requirements of software programs for collecting and processing gamma spectrum was given by Gilmore and Hemingway (1995), and a brief outline of the main functions is given below. The first part of any analysis procedure is defining or locating the peaks in the spectrum. This can be achieved in various ways, of which the simplest is directly defining the regions of interest by specific channel number. This is an extremely powerful and accurate method where only one or two nuclides are of interest, or where the same gamma peaks are routinely measured. Alternatively, if multi-nuclide analysis is required then peak-search programs may be appropriate. Variations on these include statistical routines, which identify channels successively higher than those preceding it, then mapping the corresponding fall in channel counts on the other side, thus defining the peak. This procedure works well for peaks with high count rates, yet is problematic for peaks defined by low count rates. A commonly used alternative involves the calculation of the first and second derivatives of the Gaussian peak, where the first derivative changes sign as it cross the peak centroid, and the second derivative reaches a minimum at the centroid (Mariscotti, 1967). As discussed in Section 5.3.2, an energy calibration is often required to assess the radionuclide data. This involves first creating a spectrum from a known standard source, then defining each peak and physically providing its exact energy. On the basis of this information, the system then defines and provides centroid positions and energy data for other peaks in the spectrum. The peak centroid rarely falls on an exact channel number, and the software must be able to define the gamma-ray energy represented by the peak to within a fraction of a channel. An estimation of the peak width is also necessary for calculation of the peak area, and subsequent conversion to total nuclide activity. This is not necessarily straight forward as not all detectors produce gamma peaks that are perfectly Gaussian. They may have an underlying step function (where the mean left-hand background count rates are higher than the mean right-hand background count rates), or have high and low energy tails (i.e. the peak does not rise sharply from the background continuum, but rather is elevated on tails). Various software packages make different allowances for these effects, and some have the potential for using different methods of calculating the same information. It is best to consult the user manuals of the respective suppliers with respect to performance in this regard. The next step after defining the peak position, centroid and width, is to define the peak area. A critical issue is the selection of the number of channels to define the appropriate background. Again, various software packages have different options and levels of sophistication for determining this. An advantage of the direct calibration method described in Section 5.2.3 is that the backgrounds for the unknown samples are measured independently for each nuclide for each detector. The regions of interest for the left- and right-hand background are also individually set. Another important parameter used in some laboratories is the derivation of a full energy peak-efficiency calibration. In practice, the peak efficiency is the ratio of

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the number of counts detected in a peak to the number emitted by the source. The computations needed to undertake this procedure for a single nuclide at a particular energy are outlined in Section 5.3.2.2. The efficiency calibration curve is usually obtained by measuring many gamma rays from known standard sources and by plotting efficiency against energy. The relationship is generally linear over energy ranges of ~130 to 2,000 keV, and below 130 keV, although it can drop off below 100 keV (see Fig. 5.5). The efficiency calibration curve is another method by which peak areas can be converted to activity. It is important, however, that the spectra used for calibration should be generated under a set of ideal conditions, and that these conditions are the same as when the “unknown samples are presented to the detector for real analysis. Some factors that have to be taken into account include the source-to-detector distance, the shape of the source (and samples), self-absorption within the source (and samples), i.e. the density of the source, random and true coincidence summing, and decay of the source during counting. A complete and informative description of the factors involved in the calculation of peak-efficiency curves was reported by Gilmore and Hemingway (1995).

5.4.2. Commercially Available Software Several software packages and programs are available for analysis of gamma spectra. As above, these relate to different aspects of the total analysis procedure. A brief inventory of the major packages and their suppliers is given below based on information provided by Gilmour and Hemingway (1995), including the computeroperating system under which they can operate. Software systems primarily relating to MCA alone: Canberra Industries System 100 (a subsidiary of Cogema) EGG Maestro 32 (DOS) (now ORTEC Products) For spectrum analysis alone: EG&G Omnigam Canberra Industries Sampo-90 JF computing Fitzpeaks (DOS) GCS Services Compact (DOS) For combined MCA and post-spectrum analysis: EG&G Gammavision EGG Maestro-II (DOS) (now ORTEC Products) Canberra Nuclear Genie-2000 Oxford instruments Gamma Trac (DOS) The selection of software is best undertaken in conjunction with representatives of the supplier, who can tailor a software system or package to meet the specific requirements of the user. It is also advised that, once the software is installed, the user should undertake an independent procedure to ensure that the analysis programs are performing correctly. Such a procedure is available from the American National Standard “Calibration and use of Germanium spectrometers for the measurement of gamma-ray emission rates of radionuclides.” This is available as document N42.141999, through Canberra Meriden™.

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5.5. QUALITY CONTROL, QUALITY ASSURANCE Although HPGe systems provide analyses with a high level of precision, their longer-term accuracy can be compromised by several factors. These include shifts in the spectrum due to electronic drift, presence of radon gas around the detector volume, increasing background from in-growth of uranium and thorium impurities in detector materials, deteriorating detector vacuum, contamination of the detector cap, and changes in electronic component performance as a result of temperature changes (Marten, 1992). Thus, it cannot be assumed that, once installed, a gamma spectrometric system will behave in a stable and consistent manner through time. It is necessary to undertake an active and thorough ongoing quality-control program. The following quality-assurance schedules are based on those employed by CSIRO Land and Water, Australia. 5.5.1. Stability Of Detector Backgrounds The stability of detector backgrounds should be checked every month. In practice, this can be achieved by placing a blank resin disk on the detector, which is the same shape as the regular disk geometry. At the same time, a layer of thin plastic film is replaced on the detector can itself. This protects the detector from direct contamination from the samples. The blank resin sample is then usually counted for a period of ~240 ksecs (one weekend). The resulting spectrum is analysed according to the normal procedure as an “unknown” sample. Several standard blank resin disks are used and these are rotated through the detectors to avoid the possibility of systematic error due to contamination. The results are then calculated as counts ksec1 for all the energy lines of interest [i.e. (662 keV) (487 keV) (186 keV), (63 keV), (63 kev), (186 keV), (295 keV), (352 keV), (609 keV), and (46 keV)]. These data are then placed into a spreadsheet and each energy line is then plotted for each detector, over time. If the procedure is adopted every month, then it is unlikely that an error due to an anomalous background will go undetected for a period of greater than 3 months. An example of a continuous background record covering the period 1993 to 2001 is given in Fig. 5.10. This is for (CSIRO detector G) an ORTEC HpGe well detector ‘P’ type. Observation of the data showed erratic behaviour in background count rates at various energy lines (e.g. 186, 352 and 46 keV) during the period 1995 to 1996. The problem physically manifested itself in persistent condensation, corrosion of the detector can and subsequent loss of vacuum, until ultimate detector failure in mid 1996. On the basis of the background count rates prior to failure, a decision had already been made to decommission the detector and return it to the manufacturer for repair, which was done during 1997. The data show that, upon its return, the detector achieved the same background performance as originally specified, in addition to a noticeable improvement at 46 keV. Background records also allow the operator to compare performance to that claimed by the manufacturers, and to ascertain how well the detector is operating

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compared to its potential limits. Measurement of backgrounds can also help in setting maintenance schedules, and as a diagnostic tool for assessing changes to the physical environment of the laboratory. These include changes to the quality and thickness of the lead shielding, moving the detector around in the laboratory, recalibration, or any change to the physical construction of the detector assembly itself.

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5.5.2. Stability of Detector Efficiency and Calibration As indicated above, the detectors at CSIRO Land and Water are directly calibrated. However, this procedure relies on the following: a) a constant relationship between the calibration standards and the “unknown” samples, b) properly characterizing the backgrounds, and c) a stable electronic operating environment (outlined in Section 5.4 above). Because some of these factors can be difficult to monitor directly, it is important to instigate a procedure to independently verify that the detector is providing accurate analyses of important radionuclides. This needs to be undertaken at intervals that are short enough to allow timely rectification if problems occur.

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5.5.2.1. High Activity Standard The performance of the detector can be effectively monitored by the creation of an independent standard, made from known calibrated materials provided by a reputable supplier. The standard can contain known mass (g), total amount (in Bq) and concentrations of uranium, thorium series nuclides in addition to caesium-137 if desired. This is then prepared in reasonably high activities as an unknown sample according to the regular procedure, and then counted once a month on each detector. The high activities ensure that each peak is well resolved. The resulting determinations of nuclide activities are then plotted up for each detector. A comparison of the results from each month compared to the trend from the samples previously analysed, enables the operator to ascertain when problems arise. An example of the data collected for uranium series nuclides is given in Fig. 5.11 for CSIRO detector ‘C’ (ORTEC HPGe closed ended ‘N’-type co-axial). The data cover the period 1990 to 2000 and two distinct patterns of behaviour can be seen. This is most evidenced in the and lines in which an abrupt change in performance can be seen at around the end of 1994. The period 1990 to the end of 1993 is characterized by a persistent downward trend in activities of and In contrast, the determinations remained stable, and, as this was a major nuclide of interest, the detector was kept operational. Following three continuous records of erratic behaviour in the and lines, ultimately it was decided to pump and recalibrate the detector in late 1993. Following this, the detector operated relatively stably and the precision of the determinations appeared to have been improved. A gap in the record around 1996 marks a period when no high-activity standard was run. Following five years of relatively uniform behaviour, a steady rise in calculated activities of and was then observed during 1999. Following the third successive rise in observed concentrations, a fault was diagnosed as a failed component in the preamplifier. On this basis, the detector was decommissioned and returned to the manufacturer for repair. 5.5.2.2. Low Activity Standard A similar procedure can be undertaken for low (environmental) levels of and In the CSIRO situation, samples of surface soil were prepared in each of the three geometries. These samples are also run on each detector each month. This gives the operator data on the performance of each detector for levels of radioactivity that are close to those expected in day to day operational situations. Fig. 5.12 shows the data for the same detector “C” as above, obtained for the period 1996 to 1999. On close inspection, the analyses of appeared to rise in the last few months of 1999, consistent with the high-activity trends observed over the same period in Fig. 5.11. The same is clearly true for although not for which, at these low activity levels, remained relatively constant. As these latter data were within acceptable limits, it allowed the detector to remain in commission for longer than would otherwise be the case, given the broader evidence of detector malfunction from Fig. 5.11.

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5.5.2.3. Participation in Intercomparisons In addition to the internal laboratory checks and quality-control procedures, it is highly recommended that researchers also participate in intercomparison exercises. For example, the AQCS (Analytical Quality Control Services) of the IAEA’s

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Laboratories at Seibersdorf run laboratory intercomparison exercises on an annual basis (http://www.iaea.org/programmes/aqcs/). The user selects from the AQCS catalogue a series of nuclides that (s)he wishes to analyse for. A request is sent to the IAEA and material is returned to the participating laboratory, where it is processed “blind” in the normal sample-preparation procedure. The materials used for these intercomparisons are often analysed in advance by the IAEA, and their major properties are well known. Results from the participating laboratories are then returned to the IAEA, which then publishes the overall results anonymously. Each laboratory has a code and researchers can identify their own data and compare them with the mean values. Where differences arise the laboratory manager can investigate the issue further, and take appropriate measures as needed. Conversely, researchers in regional laboratories with a particular interest in a suite of radionuclides can co-operatively run their own intercomparisons. An example of this can be found in Twining (1996) for the South Pacific Environmental Radioactivity Association. Under the auspices of the IAEA co-operative research projects on soil erosion and sedimentation and internal intercomparison exercise was conducted for and The information was invaluable, especially where data were to be directly compared across laboratories (Zapata and Garcia Agudo, 1998).

5.6. CONCLUSIONS In this chapter we have outlined the basic methodology, equipment, and software necessary to determine activities of and other gamma-emitting radionuclides using HPGe gamma-spectrometry methods. The analysis of radioactivity in samples at environmental levels is a complex task. The equipment can be expensive, and the level of skills required to achieve accurate analyses with good precision is very high. There is ongoing need for a comprehensive quality-assurance programmes as well as participation in inter-laboratory comparisons. As mentioned in the introduction, this chapter is not meant to be exhaustive, nor to be used as an operator’s manual. The practitioner is advised to become familiar with the texts and articles listed below.

5.7. ACKNOWLEDGMENTS The authors would like to acknowledge Associate Professor Robert Loughran and Mr. Haralds Alksnis for reviewing the article. Mr. Alksnis also gave assistance with the collation of data and presentation of some of the diagrams.

5.8. REFERENCES AND FURTHER READING Alksnis, H. A., Hunt, D., & Wallbrink, P. J. (1999). Radionuclides in the environment. Training manual, CSIRO Land and Water, technical report 30/99. Canberra: CSIRO. Canberra Nuclear, current equipment catalogue. Currie, L .A. (1968). Limits for qualitative detection and quantitative determination. Analytical Chemistry, 40, 586–593.

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Decker, K. M, & Sanderson, C. G. (1992). A re-evaluation of commercial IBM PC software for the analysis of low-level environmental gamma-ray spectra. International Journal of Radiation and Applied Instrumentation, 43, 232–337. Debertin, K. J., & Helmer, G. (1988). Gamma and X-ray spectrometry with semiconductor detectors. Amsterdam: North Holland. EG&G ORTEC, current equipment catalogue. Ehmann, W. D., & Vance, D. E. (1991). Radiochemical and nuclear methods of analysis. New York: Wiley. Gilmore, G., & Hemingway, J. D. (1995). Practical gamma-ray spectrometry. Chichester and New York: John Wiley & Sons. IAEA (2001). Analytical quality control services (AQCS). Current catalogue of intercomparison runs and reference materials. IAEA, P.O. Box 100, Wagramer Strasse 5, A-1400 Vienna, Austria. (http://www.iaea.org/programmes/aqcs/). Ivanovich, M., & Harmon, R. S. (Eds.). (1992). Uranium-series disequilibrium: applications to earth, marine and environmental sciences, edition. Oxford: Clarendon Press. Knoll, G. F. (1989). Radiation detection and measurement, second edition. New York: John Wiley. Mariscotti, M. A. (1967). A method for automatic identification of peaks in the presence of background and its application to spectrum analysis. Nuclear Instruments and Methods, 50, 309–320. Marten, R. (1992). Procedures for routine analysis of naturally occurring radionuclides in environmental samples by gamma ray spectrometry with HPGe detectors. Internal Report IR 76. Jabiru: Supervising scientist for the Alligators Rivers Region, JH/03/019. Moens, L., De Donder, J., Lin, X., De Corte, F., De Wispelaere, A., & Simontis, A. (1981). Calculation of the absolute peak efficiency of gamma-ray detectors for different counting geometries. Nuclear Instruments and Methods, 187, 451–472. McFarland, R. C. (1991). Behaviour of several germanium detector full-energy-peak efficiency curvefitting functions. Radioactivity and Radiochemistry, 2, 4–10. Murray, A. S., & Aitken, M. J. (1980). The measurement and importance of radioactive disequilibria in TL samples. In A specialist seminar on thermoluminescence dating, PACT, 6, 155–162. Murray, A. S., Marten, R., Johnston, A., Martin, P. (1987). Analysis for naturally occurring radionuclides at environmental concentrations by gamma spectrometry. Journal of Radiology and Nuclear Chemistry Articles, 115, 263–288. ORTEC (1991). Equipment information manual. Robbins, J. A. (1978). Geochemical and geophysical applications of radioactive lead. In J. O. Nriagu (Ed.), Biogeochemistry of lead in the environment (pp 285-393). Amsterdam: Elsevier Scientific. Tsoulfanidis, N. (1983). Measurement and detection of radiation. New York: McGraw-Hill. Twining, J. (1996). An intercomparison of gamma spectrometry on two samples of biological origin by 8 laboratories in 4 countries. Applied Radiation and Isotopes, 47, 801–810. Walling, D. E. and Quine, T. A. (1993). Use of caesium-137 as a tracer of erosion and sedimentation: Handbook for the application of the caesium-137 technique. Exeter: Department of Geography, University of Exeter. Zapata, F., & Garcia-Agudo, E. (1998). Report on the Second Research Co-ordination Meeting of the Coordinated Research Projects on “The assessment of soil erosion through the use of Cs-137 and related techniques as a basis for soil conservation, sustainable agricultural production and environmental protection” and “Sediment assessment studies by environmental radionuclides and their application to soil conservation measures”, Bucharest, May 1998. Vienna: IAEA.

5.9. GLOSSARY OF TERMS Becquerel (Bq) The activity unit or rate of nuclear transformation of radionuclides is the number of nuclear disintegrations per second. Bomb fallout Fission by-product from above-ground detonation of nuclear bombs. This nuclide was released into the stratosphere, distributed globally and moved back to the troposphere. From there it was largely washed out by rainfall onto the earth’s surface. Its regional distribution is, thus, related to rainfall.

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Detector calibration The process by which a gamma detector is set up to quantify the radioactivity of various nuclides in “unknown” samples. Gamma radioactivity High-energy electromagnetic radiation emitted from a gamma-producing radionuclide (or radioisotope) as a result of its transition in energy states in the nuclei. Gamma spectrometry The science of measuring the activity (Bq) of gammaproducing radionuclides in natural and man-made samples. The technique is based on the fact that different radionuclide species emit gammas at different energies when they decay. keV The energy unit of gamma rays is commonly expressed in thousands of electron volts. Quality control A series of established procedures to assess the ongoing accuracy and precision of analyses from a detector and laboratory. Often achieved by analysing samples of known radioactivity (i.e. sources) as independent unknowns, and plotting the results over time. Standards and sources Radioactive materials prepared with known radioactivity, mass, sample size, and geometry and presented to the detector as part of the calibration exercise. They are used also for system diagnostics, and for qualitycontrol and quality-assurance programs.

CHAPTER 6 SPATIAL DISTRIBUTION OF CAESIUM-137 R.J. LOUGHRAN1, D.J. PENNOCK2 and D.E. WALLING3 1

School of Environmental and Life Sciences (Geography), The University of Newcastle, Callaghan, New South Wales 2308, Australia. 2Department of Soil Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5A8, Canada. 3Department of Geography, University of Exeter, Amory Building, Rennes Drive, Exeter EX4 4RJ, United Kingdom.

6.1. INTRODUCTION The interpretation of distribution across the landscape requires knowledge of the original input of the isotope from the atmosphere, and the subsequent loss to radioactive decay. By sampling soils at stable sites it should be possible to determine the residual level of associated with the original input, which is commonly termed the reference inventory. Determining the reference value or reference inventory, against which other values are compared, is one of the most important steps in using to understand the variation of erosion and sedimentation in relation to topography, land use, soil properties, conservation works, hydrology and vegetation cover (Chapter 1). The reference value is used to identify sampling points that have less than the reference inventory (net soil loss), and those that have more than the reference value (net soil deposition). Detailed soil sampling (for example, on a grid basis: Chapter 2) may then allow the two-dimensional mapping of the isotope inventories to show zones of net erosion and deposition. With the addition of depth-incremental sampling at each point, a three-dimensional image of the isotope’s distribution may be built up. Available resources (for example, detector time in the laboratory) will partly determine the scale and type of study. Most commonly, one-dimensional (soil sampling along a transect) or twodimensional (by grid-sampling) approaches have been used in studies. “Losses” and “gains” of the isotope may then be translated into net soil losses and gains (Chapter 7) and interpreted against measures of topography, soil properties, land use and other factors. Alternatively, the values themselves may be correlated with variations in topography, soils, land use, conservation structures and vegetation cover.

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This chapter examines approaches used in determining reference values, and how these are used to delineate zones of net erosion and net deposition. It concludes with an examination of how the erosion/deposition data can be interpreted against topographic and soil variability, and land use/management, the most important nondynamic factors affecting the magnitude of soil erosion and deposition. 6.2. CALCULATION OF AREAL ACTIVITY Laboratory analyses (Chapter 5) provide the specific activity of Specific activity is translated into areal activity for the sample using Eq. 6.1:

6.3. DETERMINATION OF THE REFERENCE INVENTORY The selection of reference sites and sampling networks is discussed in Chapter 2. Sutherland (1991; 1996) noted that strategies for determining reference inventories often lacked statistical rigour, and many studies did not report the sampling design. Generally, only a few samples were collected at reference sites, and the coefficients of variation (CV%) were high: forested sites (19–47%), although lower at pasture/grassland sites (5.1–41%). Sutherland (1996) concluded that approximately eleven soil samples “would be generally adequate for many reference locations assuming that independent random samples are selected.” Of forty studies reviewed by Sutherland (1996), only thirteen were adequately sampled for the determination of the reference inventory. Owens and Walling (1996) stated that the observed variability in reference values could, in the absence of soil erosion and deposition, be due to: random spatial variability, systematic spatial variability, sampling variability, and measurement precision. Random spatial variability could be due to variations in soil bulk density, infiltration capacity, the presence of macropores, cracks, and stones, the effects of vegetation cover and roots, micro-topography, and human and animal disturbance. Systematic spatial variability is apparent at a larger (regional) scale, where variations in rainfall and wind flows may have affected fallout patterns. Sampling variability “is a function of the surface area over which the samples are collected” (Owens and Walling, 1996). This factor is illustrated in Table 6.1, in which data collected with a sampling frame (Chapter 3) are compared with twelve samples collected by core on a grid layout (Ormerod, 1999). While the CV of the twelve core samples was 20%, and the standard deviation was 15 mBq the mean of the core values was very close to the inventory for the scraper/frame sample Measurement precision will be affected

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by the activity of the sample, counting time and detector efficiency. This source of variability will be greater where soil levels are low (Chapter 5).

If reference samples are collected over an area of approximately 1 ha, it may be assumed that the systematic spatial variability of is zero. Sampling variability may be reduced by increasing the sampled area, although this advantage may be offset by the necessity to obtain a representative sub-sample in the laboratory (Owens and Walling, 1996). “For example, a sample collected over to a depth of 40 cm yields ca. 500 kg of soil” (Owens and Walling, 1996). Usually, no more than 1 kg of soil is required for analysis, so thorough mixing to produce a representative sub-sample will be required, otherwise additional errors will be introduced. Measurement precision can be improved by counting large samples for long periods (Owens and Walling, 1996). In their study of reference sites in two contrasting environments (United Kingdom and Zimbabwe), Owens and Walling (1996) concluded that random spatial variability was the most important factor in explaining variability. They recommended the use of a grid network of sampling points across the reference site, and the collection of three replicate cores within at each point. The cores may be bulked and the counting time adjusted according to content and detector efficiency.

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It is advisable to carry out one depth-incremental sampling within a frame so that the depth-distribution of is known before coring is commenced. A coring cylinder can then be inserted to the appropriate depth to ensure that the total profile of is intercepted without incorporating a large amount of unlabelled soil that will dilute the concentration and reduce the measurement precision. 6.3.1. Setting a Reference Value Many studies have utilized the average content of samples at the reference site as the reference inventory, regardless of how many samples were collected. In cases where cores, and a scraper plate and frame are used, averages can be weighted to take account of differences in the sampled area (e.g. Morris and Loughran, 1994). These approaches take no account of the uncertainties described above. Walling (1990), however, adopted a 20% range above and below the reference value when determining depositional and erosional sampling points, respectively, “to take account of the precision of the measurements and the natural sampling variability evidenced by the soil cores” (Walling, 1990). The use of a single figure for the reference inventory may imply “a greater precision than actually exists” (Owens and Walling, 1996). Therefore, they advocated a range for the reference value rather than a single figure, given by the expression:

where: SEM = the standard error of the mean. Sampling points in the landscape that have values within the range fall within the total variability associated with the reference site. The above approaches assume that suitable reference-sampling sites are available in the study area, which is not necessarily the case at all locations (Section 2.4). For example, Nagle et al. (2000) observed that “one of the most vexing problems involved in the use of the technique in the study area (a tropical, mountain area of the Dominican Republic) was finding un-cleared and uncultivated sites to use as reference sites.” In Western Australia, also, virtually all of the landscape has been cleared for grain production and soils in remnant woodland/forest are waterrepellent, thus making the adsorption of patchy (McFarlane et al., 2000). In such instances, other approaches to achieving reliable reference values need to be investigated. One approach is to assess all possible reference sites in the field, as done by Nagle et al. (2000). They considered forests to be the most suitable, “despite the potential for higher within-site variability in forests owing to canopy processing of rain and fallout and soil disturbance from root throws.” Additionally, researchers in various parts of the world have noted a strong relationship between rainfall and reference values, creating the possibility that reference values can be obtained or confirmed from rainfall data alone. This approach is discussed below.

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6.3.2. Reference Values in Relation to Precipitation

Within a latitudinal zone, fallout has been shown to be a function of rainfall in many regions (Basher, 2000). Over a range of annual rainfall from 350 to 2,800 mm in New Zealand, for example, there is a strong linear relationship between mean annual precipitation and values at undisturbed sites (Basher, 2000):

where: Soil-Cs = the areal activity at the site R = the mean annual precipitation (mm). Use of this, or other established regional equations, provides a means of “independently estimating reference values and verifying local measurements of the reference value” (Basher, 2000). This approach was used in Australia during a reconnaissance survey of soil erosion using Reference values were difficult to establish at some locations in Tasmania and Western Australia due to a lack of suitable sites close to sampled slope transects because of rock outcrops, disturbance, and water repellent soils (Richley et al., 1997; McFarlane et al., 2000). The reference inventory at any given site should be compared to any available national or global-level (Garcia-Agudo, 1998) radionuclide deposition data. Recently, Walling and He (2000) have developed a model for providing an estimate of the reference inventory for a study site from information on latitude and longitude and mean annual precipitation for the site. This model has been incorporated into the conversion model software package to estimate erosion rates from measurements. 6.4. ESTABLISHING PATTERNS OF

ACROSS THE LANDSCAPE

Detailed studies of soil quality at sites in Saskatchewan, Canada, and Ghana, show that the spatial variability of is comparable with that of soil organic carbon and soil total nitrogen (Pennock, 2000). Using the coefficient of variation (CV) (standard deviation/sample mean × 100%) as an indicator of variation, it is judged that 137Cs is “moderately” variable (CV between 15 and 35%). It is suggested that from ten to twenty-five samples must be taken within the “moderately” variable class to obtain an estimate of the mean to within ±10% at the 95% level of confidence (Wilding and Drees, 1983; Pennock, 2000). Bachhuber et al. (1987), studying the spatial variability of concentrations in a single field in Germany, concluded that at least fourteen samples were required to obtain the mean activity within a tolerable error of 10% with 95% confidence limits. It may, therefore, be concluded that approximately twenty soil samples will be required to determine levels within a land-use category/landscape unit for meaningful conclusions to be drawn about soil-erosion status. The number of samples to be taken can, however, also be partly determined by the availability of detector time.

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Several approaches to sampling design have been adopted to study the spatial variation of the most common of which recognise the transfer of soil and adsorbed by erosion by water and tillage in a down-slope direction. Transects with a down-slope orientation and sampling on a grid basis have both been used to examine distribution in relation to topography, soil properties, and land use. Grid sampling is preferable because it provides a two-dimensional picture of distribution (or three-dimensional if depth-incremental sampling is carried out at each sampling point) that can be matched with the topography more satisfactorily than if a single transect is used. Variability of topography, the area of the land-use unit (e.g. field) and the total number of samples allocated to a project usually determine the spacing of the sampling interval (Chapter 2). Tables 6.2 and 6.3 provide an indication of the range of sampling intervals that have been used in soil studies.

Sample number and spacing will influence the pattern of inventories (and soil loss and gain) obtained from a survey. Higgitt (1995) assessed the influence of sample number on maps of soil loss/gain based on measurements within a 3.2ha cultivated field in Shropshire, England. A total of eighty-three samples was taken on a 20 × 20 m grid, and a random-numbers generator was used to successively withdraw samples from the grid to achieve sample sizes of seventy, sixty, fifty, and twenty-five. “The interpolated maps maintain a broadly similar pattern until the sample size is reduced to twenty-five, where a large portion of the left side is assumed to be depositional. However, the summary statistics (shown in Table 6.4) for the field remain quite similar at all sample sizes” (Higgitt, 1995). Soil mixing by cultivation will undoubtedly reduce the spatial variability of compared with uncultivated sites. For example, the sampling of a slope covered by tussock grasses and trees showed that values were higher on the upslope side of tussocks (deposition) compared with the down-slope side (Loughran et al., 1993), suggesting that the sampling interval should match micro-topography.

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6.4.1. Caesium-137 in Relation to Soils, Topography, Land Use, and Management

Comparisons between the spatial distribution of in soils and influencing factors, such as soil properties, topography, and land use and management have been the focus of many studies over the past three decades. Other studies have utilized measurements of these factors, along with rainfall erosivity, to estimate soil loss using the Universal Soil Loss Equation (USLE), or derivatives, for comparison with estimates of net soil loss derived from measurements. The outcome of these comparisons will clearly depend on the type of model used to convert measurements into soil loss (Chapter 7).

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It is advisable to measure at least some soil properties so that variations in can be interpreted with more certainty. For example, in pioneering studies carried out in the United States, Ritchie and McHenry examined relationships between and soil texture (sand, silt, and clay percentages), N, C, P, CEC, and organic content (McHenry and Ritchie, 1977; Ritchie and McHenry, 1978). More recently, Chappell et al. (1998), added soil bulk density, soil strength, soil colour, and pH, while others have included A-horizon thickness and depletion (Sutherland, 1991; de Jong et al., 1986). Research on the relationship between soil redistribution and topography has been a major theme since the earliest studies using (e.g. Loughran et al., 1989). The assessment of this relationship has been greatly aided by the ease with which terrain attributes can be derived from any digital elevation model (DEM). The creation of a DEM involves interpolation of an elevation surface from point elevations or from existing topographical databases. The DEM is then used to calculate terrain attributes using widely available computer software. The most commonly used terrain attributes can be divided into three groups: morphological, positional, and compound (Table 2.2). The relevance of any particular terrain attribute for soil redistribution studies depends on both the overall landform shape and the specific redistribution processes operating in the landscape. The dominant hydrological controls on the rates of water-erosion processes are discharge (typically simplified to the depth of flow) and slope gradient (e.g. Govers, 1985). Slope gradient is of relevance across all landform types, but the particular attribute used as a surrogate for depth of flow differs depending on overall landform shape. In an inclined landscape (i.e., those that lack significant plan curvature) only two morphological attributes are necessary (gradient and profile curvature) and the primary positional attribute of relevance is slope length. Under conditions of spatially unvarying production of saturation overland flow, flow depth will increase down slope, and hence the potential for flow detachment and transport w i l l increase down slope (Moore and Burch, 1986). These rectilinear back slopes were the sole experimental unit used for the development of the USLE, and only slope gradient and slope length (i.e., the compound slope length and steepness (LS) factor) were used to calculate the effect of topography on erosion rates in the USLE and revised USLE (Renard et al., 1997). The applicability of a two-dimensional terrain attribute such as the LS factor decreases in landscapes that have convergence of flow paths resulting from significant plan curvature. In these landscapes, slope length alone is of limited relevance because of convergence or divergence of flow (Moore and Burch, 1986). The terrain attributes typically used as surrogate measures for flow depth in landscapes with significant plan curvature are catchment area and dispersal area. Several approaches exist to calculate these attributes (Moore and Grayson, 1991; Costa-Cabral and Burges, 1994). The fundamental understanding of the topographical controls on the occurrence of tillage redistribution is largely in place (Govers et al., 1999). Whether a point loses or gains soil by tillage translocation depends on the change in slope gradient between the boundaries of the segment (i.e., the profile curvature) (Govers

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et al., 1999). Soil loss due to tillage occurs on convexities, and soil gain in concavities. Rectilinear back slopes are dominated by transport of soil, and no net change in the mass of soil occurs. Therefore the spatial pattern of soil redistribution due to tillage translocation will closely map to the pattern of profile curvature in the landscape. Two broad approaches to using terrain attributes in soil-erosion research exist. The first develops quantitative relationships between specific terrain attributes or combinations of attributes and either soil redistribution directly or the hydrological processes controlling erosion rates. Quine (1999) has emphasized the need to simultaneously model the effect of topography on water erosion and on tillage translocation for realistic simulations of combined erosion impact on landscapes. The second use of terrain attributes examines the association between soil redistribution and quantitatively defined landform segments. Pennock and Corre (2001) have most recently summarized the development of landform segmentation procedures. The purpose of these procedures is to develop three-dimensional slope segments based on two or more terrain attributes and then to use these segments as the fundamental sampling units in field studies and for grouping data for subsequent data analysis. The slope segments must be shown to be functionally distinct with regards to the specific process being examined—in other words, a distinct range of the values for the process must be associated with the different landform segments. In the earliest studies on soil redistribution, landform segments were typically qualitatively defined (e.g. Brown et al., 1981; Campbell et al., 1982; de Jong et al., 1983). This limits their reproducibility in subsequent research designs. Martz and de Jong (1987, 1991) and Pennock and de Jong (1987, 1990) developed quantitatively defined landform segments for Saskatchewan landscapes, and similar approaches have been developed and applied elsewhere, for instance in Australia (Morris and Loughran, 1994), England (Walling and Quine, 1991; Quine and Walling, 1993), New Zealand (Basher, 2000), France (Sogon et al., 1999), Mexico (Garcia-Oliva et al., 1995), and Niger (Chappell, 1996). Soil erosion in relation to land use, especially comparisons between natural forest and cultivated and grazing land, has been a major feature of erosion research. Statistical tests of differences in levels in soils undergoing different management practices (often using the non-parametric Mann-Whitney U test), have revealed the severity of erosion of cultivated soils, often on steep slopes, in comparison with uneroded reference sites in forest, woodland and grasslands. Some examples are listed below: wind erosion in relation to land clearing by bulldozer in Saskatchewan, Canada (Sutherland, 1992); woodland, pasture and cultivated land in Devon, United Kingdom (Loughran et al., 1987); forest, slash-and-burn agriculture and pasture in Mexico (Garcia-Oliva et al., 1995); various land-management systems, tillage redistribution, cultivated terraces and grassland in Guansu Province, China (Zhang et al., 1994);

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contour strips, terraces and tillage effects in China, Lesotho, and Zimbabwe (Quine et al., 1999); pasture versus cropping/cultivation [Foster et al. (1994) in England, Basher et al. (1995) in New Zealand, Elliott and Cole-Clark (1993) in Australia]; forest/woodland, grazing land and vineyards in Australia (Loughran et al., 2000); urbanization in eastern Australia (Whitelock and Loughran, 1994). In the recently published volume of Acta Geologica Hispanica (Queralt et al., 2000), which deals with the use of for soil erosion and sedimentation studies, nine of the thirteen studies concerned with soil erosion focussed on the effects of land use and management in the United States, New Zealand, China (twice), Morocco, Brazil, Argentina, Chile, and Slovakia.

6.5. CONCLUSION It has been shown that inventories have a coefficient of variation of approximately 20% at reference sites (Pennock, 2000), and that this variability is probably because of random spatial variability (Owens and Walling, 1996). At reference sites it is recommended that a grid-sampling network is employed, with the collection of three replicate cores within 1 m of each sampling point. The cores may be bulked for analysis (Owens and Walling, 1996). While the number of samples needed to estimate the reference value within the required statistical limits will depend on the variability found during analysis, between fifteen and thirty samples will usually be necessary for an accurate estimate of central tendency (Pennock, 2000). Owens and Walling (1996), suggest that Eq. 6.2 is used to determine a “reference range” rather than a single value, which might imply a greater accuracy than is really the case. This range can then be used to determine points of net soil loss and gain within the landscape. Sampling for spatial variability of may take the form of transects or, preferably, a grid (Chapter 2). There has been no standardization of sampling frequency, as Tables 6.2 and 6.3 reveal. Rather, each study’s methodology has been established according to the study aims, the perceived field-variability of the isotope (e.g. has cultivation mixed the soil, or is micro-topography a factor in the redistribution of and the number of samples that can be analysed in the laboratory. It is, however, recommended that at least twenty samples be taken along transects or in a grid pattern. Samples can be taken by core to a depth that will incorporate the total profile, previously determined by depth sampling, although the deposition of sediment particularly at the slope-base may over-thicken the profile in areas affected by water erosion. Excavation, soil auger or other suitable means should be used to sample such sites to greater depths (Chapter 3). It is recommended that at least some basic soil properties be measured (e.g. texture, organic matter, bulk density and horizon/plough layer depth) to aid interpretation (Chapter 2). Topographic characteristics can be used to group landform elements, and land-use types can be grouped for comparisons. The

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selection of appropriate models to transform data into estimates of soil losses and gains that can be related to controlling factors such as soil erodibility, slope characteristics, and land use and management are discussed in Chapter 7. 6.6. REFERENCES Bachhuber, H., Bunzl, K., & Schimmack, W. (1987). Spatial variability of in the soil of a cultivated field. Environmental Monitoring and Assessment, 8, 93–101. Basher, L. R. (2000). Surface erosion assessment using examples from New Zealand. Acta Geologica Hispanica, 35, 219–228. Basher, L.R., Matthews, K. M., & Zhi, L. (1995). Surface erosion assessment in the south Canterbury downlands, New Zealand, using distribution. Australian Journal of Soil Research, 33, 787–803. Bernard, C., & Laverdière, M. R. (2000). Using as a tool for the assessment and management of erosion/sedimentation risks in view of the restoration of the Rainbow Smelt (Osmerus mordax) fish population in the Boyer River basin (Québec, Canada). Acta Geologica Hispanica, 35, 321–327. Bouhlassa, S., Moukhchane, M., & Aiachi, A. (2000). Estimates of soil erosion and deposition of cultivated soils of Nakhla watershed, Morocco, using technique and calibration models. Acta Geologica Hispanica, 35, 239–249. Brown, R. B., Cutshall, N. H., & Kling, G. F. (1981). Agricultural erosion indicated by redistribution. I. Levels and distribution of activity in soils. Soil Science Society of America Journal, 45, 1184–1190. Buján, A., Santanatoglia, O. J., Chagas, C., Massobrio, M., Castiglioni, M., M. S., Ciallella, H., & Fernandez, J. (2000). Preliminary study on the use of the method for soil erosion investigation in the pampean region of Argentina. Acta Geologica Hispanica, 35, 271–277. Campbell, B. L., Loughran, R. J., & Elliott, G. L. (1982). Caesium-137 as an indicator of geomorphic processes in a drainage basin system. Australian Geographical Studies, 20, 49–64. Campbell, B. L., Loughran, R. J., Elliott, G. L., & Shelly, D. J. (1986). Mapping drainage basin sediment sources using caesium-137. In Drainage basin sediment delivery. International Association of Hydrological Sciences Publication, 159, 437–446. Chappell, A. (1996). Modelling the spatial variation of processes in the redistribution of soil: digital terrain models and in southwest Niger. Geomorphology, 17, 249–261. Chappell, A., Warren, A., Oliver, M. A., & Charlton, M. (1998). The utility of for measuring soil redistribution rates in southwest Niger. Geoderma, 81, 313–337. Costa-Cabral, M. C., & Burges, S. J. (1994). Digital elevation model networks (DEMON): A model of flow over hillslopes for computation of contributing area and dispersal areas. Water Resources Research, 30, 1681–1692. de Jong, E., Begg, C. B. M., & Kachanoski, R. G. (1983). Estimates of soil erosion and deposition for some Saskatchewan soils. Canadian Journal of Soil Science, 63, 607–617. de Jong, E., Wang, C., & Rees, H. W. (1986). Soil redistribution on three cultivated New Brunswick hillslopes calculated from measurements, solum data and the USLE. Canadian Journal of Soil Research, 66, 721–730. Elliott, G. L., & Cole-Clark, B. E. (1993). Estimates of erosion on potato lands on krasnozem soils at Dorrigo, NSW, using the caesium-137 technique. Australian Journal of Soil Research, 31, 209–223. Foster, I. D. L., Dalgleish, H., Dearing, J. A., & Jones, E. D. (1994). Quantifying soil erosion and sediment transport in drainage basins; some observations on the use of In Variability in stream erosion and sediment transport. International Association of Hydrological Sciences Publication, 224, 55–64. Fulajtar, E. (2000). Assessment of soil erosion through the use of at Laslovke Bohunice, Western Slovakia. Acta Geologica Hispanica, 35, 291–300. Garcia-Agudo, E. (1998). Global distribution of inputs for soil erosion and sedimentation studies. In Use of in the study of soil erosion ami sedimentation, IAEA-TECDOC-1028 (pp. 117–121). Vienna: IAEA. Garcia-Oliva, F., Martinez Lugo, R., & Maass, J. M. (1995). Long-term net soil erosion as determined by redistribution in an undisturbed and perturbed tropical deciduous forest ecosystem. Geoderma, 68, 135–147.

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Govers, G. (1985). Selectivity and transport capacity of thin Hows in relation to rill erosion. Catena, 12, 35–49. Govers, G., Lobb, D. A., & Quine, T. A. (1999). Tillage erosion and translocation: emergence of a new paradigm in soil erosion research. Sail Tillage Research, 51, 167–174. Higgitt, D. L. (1995). The development and application of caesium-137 measurements in erosion investigations. In I. D. L. Foster, A. M. Gurnell and B. W. Webb (Eds.), Sediment and water quality in river catchments (pp. 287-305). Chichester: John Wiley & Sons. Ionita, I., & Margineanu, R. M. (2000). Application of for measuring soil erosion/deposition rates in Romania. Acta Geologica Hispanica, 35, 311–319. Li, Y., Lindstrom, M. J., Zhang, J., & Yang, J. (2000). Spatial variability of soil erosion and soil quality on hillslopes in the Chinese Loess Plateau. Acta Geologica Hispanica, 35, 261–270. Longmore, M. E., O’Leary, B. M., Rose, C. W., & Chandica, A. L. (1983). Mapping soil erosion and accumulation with the fallout isotope caesium-137. Australian Journal of Soil Research, 21, 373– 385. Loughran, R. J., Campbell, B. L., & Walling, D. E. (1987). Soil erosion and sedimentation indicated by caesium-137: Jackmoor Brook catchment, Devon, England. Catena, 14, 201–212. Loughran, R. J., Campbell, B. L., Elliott, G. L., Cummings, D., & Shelly, D. J. (1989). A caesium-137sediment hillslope model with tests from south-eastern Australia. Zeitschri ft Geomorphologie, 33, 235–250. Loughran, R. J., Elliott, G. L., Campbell, B. L., Curtis, S. J., Cummings, D., & Shelly, D.J. (1993). Estimation of erosion using the radionuclide caesium-137 in three diverse areas in eastern Australia. Applied Geography, 13, 169–188. Loughran, R. J., Elliott, G. L., Maliszewski, L. T., & Campbell, B. L. (2000). Soil loss and viticulture at Pokolbin, New South Wales, Australia. In The hydrology-geomorphology interface: rainfall, floods, sedimentation, land use. International Association of Hydrological Sciences Publication, 261, 141– 152. Martz, L. W., & de Jong, E. (1987). Using cesium-137 to assess the variability of net soil erosion and its association with topography in a Canadian prairie landscape. Catena, 14, 439–451. Martz, L. W., & de Jong, E. (1991). Using cesium-137 and landform classification to develop a net soil erosion budget for a small Canadian prairie watershed. Catena, 18, 289–308. McFarlane, D. J., George, R. J., Loughran, R. J., Elliott, G. L., Ryder, A. T., Bennett, D., & Tille, P. J. (2000). A national reconnaissance survey of soil erosion in Australia: Western Australia. Newcastle: Australian National Landcare Program and The University of Newcastle. McHenry, J. R., & Ritchie, J. C. (1977). Physical and chemical parameters affecting transport of in arid watersheds. Water Resources Research 13, 923–927. Moore, I. D., & Burch, G. J. (1986). Physical basis of the length-slope factor in the Universal Soil Loss Equation. Soil Science Society of America Journal, 50, 1294–1298. Moore, I. D., & Grayson, R. B. (1991). Terrain-based catchment partitioning and runoff prediction using vector elevation data. Water Resources Research, 27, 1177–1191. Morris, C. D., & Loughran, R. J. (1994). Distribution of caesium-137 in soils across a hillslope hollow. Hydrological Processes, 8, 531–541. Nagle, G. N., Lassoie, J. P., Fahey, T. J., & McIntyre, S. C. (2000). The use of caesium-137 to estimate agricultural erosion on steep slops in a tropical watershed. Hydrological Processes, 14, 957–969. Ormerod, L. M. (1999). Sedimentation rates and sediment provenance within a predominantly urbanised catchment: Ironbark Creek, New South Wales. PhD thesis. Callaghan: University of New Castle. Owens, P. N., & Walling, D. E. (1996). Spatial variability of caesium-137 inventories at reference sites: an example from two contrasting sites in England and Zimbabwe. Applied Radiation and Isotopes, 47, 699-707. Pennock, D. J. (2000). Suitability of redistribution as an indicator of soil quality. Acta Geologica Hispanica, 35, 213–217. Pennock, D. J., & Corre, M. D. (2001). Development and application of landform segmentation procedures. Soil Tillage Research, 58, 151–162. Pennock, D. J., & de Jong, E. (1987). The influence of slope curvature on soil erosion and deposition in hummock terrain. Soil Science, 144, 209–217. Pennock, D. J., & de Jong, E. (1990). Spatial pattern of soil redistribution in Boroll landscapes, southern Saskatchewan, Canada. Soil Science, 150, 867–873.

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Queralt, I., Zapata, F., & Garcia-Agudo, E. (Eds.). (2000). Assessment of soil erosion and sedimentation through the use of the and related techniques. Acta Geologica Hispanica, 35, 195–367. Quine, T. A. (1999). Use of caesium-137 data for validation of spatially distribuled erosion models: the implications of tillage erosion. Catena, 37, 415–430. Quine, T. A., & Walling, D. E. (1993). Use of caesium-137 measurements to investigate relationships between erosion rates and topography. In D. S. G. Thomas and R. J. Allison (Eds.), Landscape sensitivity (pp. 31–48). Chichester: John Wiley & Sons Ltd. Quine, T. A., Walling, D. E., Chakela, Q. K., Mandiringana, O. T., & Zhang, X. (1999). Rates and patterns of tillage and water erosion on terraces and contour strips: evidence from caesium-137 measurements. Catena, 36, 115–142. Renard, K. G., Foster, G. A., Weesies, G. A., McCool, D. K., & Yoder, D. C. (1997). Predicting soil erosion by water: A guide to conservation planning with the revised Universal Soil Loss Equation (RUSLE), USDA Agricultural Handbook No. 703. Washington: USDA. Richley, L., Loughran, R. J., Elliott, G. L., & Saynor, M. J. (1997). A national reconnaissance survey of soil erosion in Australia: Tasmania. Newcastle: Australian National Landcare Program and The University of Newcastle. Ritchie, J. C., & McHenry, J. R. (1978). Fallout cesium-137 in cultivated and noncultivated north central United States watersheds. Journal of Environmental Quality, 7, 40–44. Soileau, J. M., Hajek, B. F., & Touchton, J.T. (1990). Soil erosion and deposition evidence in a small watershed using fallout cesium-137. Soil Science Society of America Journal, 54, 1712–1719. Sogon, S., Pcnven, M.-J., Bonte, P., & Muxart, T. (1999). Estimation of sediment yield and soil loss using suspended sediment load and measurements on agricultural land, Brie Plateau, France. Hydrobiologia, 410. 251–261. Sutherland, R. A. (1991). Examination of caesium-137 areal activities in control (uneroded) locations. Sail Technology, 4, 33–50. Sutherland, R. A. (1992). Caesium-137 estimates of erosion in agricultural areas. Hydrological Processes, 6, 215–225. Sutherland, R. A. (1996). Caesium-137 soil sampling and inventory variability in reference locations: a literature survey. Hydrological Processes, 10, 43–53. Theocharopoulos, S. P., Florou, H., Kritidis, P., Belis, D., Tsouloucha, F., Christou, M., Kouloumbis, P., & Nikolaou, T. (2000). Use of isotope technique in soil erosion studies in central Greece. Acta Geologica Hispanica, 35, 301–310. Walling, D.E. (1990) Linking the field to the river: sediment delivery from agricultural land. In J. Boardman, I. D. L. Foster and J. A. Dearing (Eds.), Soil Erosion on Agricultural Land (pp. 129–152). Chichester: John Wiley & Sons Ltd. Walling, D. E., & He, Q. (2000). The global distribution of bomb-derived reference inventories. Report to the IAEA as a contribution to the co-ordinated research projects on soil erosion and sedimentation. Exeter: Department of Geography, University of Exeter. Walling, D. E., & Quine, T. A. (1991). Use of measurements to investigate soil erosion on arable fields in the UK: potential applications and limitations. Journal of Soil Science, 42, 147–165. Whitelock, B., & Loughran, R. J. (1994). Sediment production and storage in a urbanizing basin, Lake Macquarie, New South Wales, Australia. In Variability in stream erosion and sediment transport, International Association of Hydrological Sciences Publication, 224, 103–110 Wilding, L. P., & Drees, L. R. (1983). Spatial variability and pedology. In L. P. Wilding, N. E. Smeck, & G. F. Hall (Eds.), Pedogenesis and soil taxonomy: I. Concepts and interactions (pp. 83–116). New York: Elsevier Science. Zhang, X., Quine, T. A., Walling, D. E., & Zhou Li (1994). Application of the caesium-137 technique in a study of soil erosion on gully slopes in a yuan area of the Loess Plateau near Xinfeng, Gansu province, China. Geografiska Annaler, 76A, 103–120. Zhang, X. B., Quine, T. A., Walling, D. E., & Wen, A. B. (2000). A study of soil erosion on a steep cultivated slope in the Mt. Gongga Region near Luding, Sichuan, China, using the technique. Acta Geologica Hispanica, 35, 229–238.

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CHAPTER 7 CONVERSION MODELS FOR USE IN SOIL-EROSION, SOIL-REDISTRIBUTION AND SEDIMENTATION INVESTIGATIONS 1

2

3

D.E. WALLING , Q. HE and P.G. APPLEBY 1

Department of Geography, University of Exeter, Amory Building, Rennes Drive, Exeter EX4 4RJ, United Kingdom. 2CEM Centre, University of Durham, Stockton Road, Durham DH1 3UZ, United Kingdom. 3Environmental Radiometric Research Centre, Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom.

7.1. THE NEED FOR CONVERSION MODELS Information on the magnitude and spatial pattern of the inventories associated with soil or sediment cores collected from a landscape or individual field or from a river floodplain can frequently be used to provide a general indication of the relative rates of erosion or deposition involved and the associated patterns, but the results can only be essentially qualitative. Thus, for example, a map of the pattern of inventories in a field, such as that presented in Fig. 7.1 A, could be used in conjunction with information on the local reference inventory to establish the basic pattern of erosion and deposition within the field and to assess the variation of the relative magnitude of the erosion and deposition rates involved. In this example, the reference inventory was estimated to be ca. at the time of sampling, and areas of the field, with inventories less than this value could be seen as evidencing net erosion, whereas areas with inventories in excess of the reference value could be seen as representing areas of net deposition. The greater the difference between the measured inventory and the reference value, the greater the erosion or deposition rate can be assumed to be. Thus, maximum erosion rates can be seen to occur on the middle sections of the slopes and the greatest amounts of deposition are found along the axis of the depression or small valley running up the centre of the field. Similarly, the spatial distribution of inventories associated with sediment cores collected from an area of river floodplain could provide qualitative information on the pattern of sedimentation across the floodplain and on the relative magnitude of deposition rates associated with specific morphological features. Again, this would involve comparison of the measured inventories with a reference value representative of areas with no deposition. 111

F. Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 111–164. © 2002 IAEA. Printed in the Netherlands.

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In most investigations, however, such qualitative data will be of only limited value and there will be a need to derive quantitative estimates of the rates of erosion or deposition involved. For this reason, calibration procedures, also called conversion models, are required. In the case of a soil-erosion study, for example, such a model can be used to convert the measured inventories obtained from a field to estimates of the actual rate of erosion or deposition associated with the sampling points. The erosion rates estimated from the measured inventories in the field depicted in Fig. 7.1A, using a mass balance conversion model that takes into

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account the effects of soil redistribution by tillage (see Section 7.3.3.6), are shown in Fig. 7.1B. The values shown represent mean annual rates over the past ca. 40 years. The ability to establish actual erosion and deposition rates clearly represents an important advance over the qualitative information on rates and patterns of erosion and deposition that can be inferred from Fig. 7.1A. Such data can also provide a basis for establishing the overall sediment budget for the field, and, thus, the balance between the erosion, deposition, and sediment output (Table 7.1). The sediment delivery ratio of 40% estimated for this field indicates that only 40% of the sediment mobilized by erosion is transported beyond the field and that 60% of the mobilized sediment is, therefore, redeposited further down the slopes and in the bottom of the depression or small valley running up the centre of the field. Similar calibration procedures can be used to convert the values of inventory obtained for individual floodplain cores to estimates of the sedimentation rate at the points from which the cores were collected. In some cases, these calibration routines or conversion models are little more than simple empirical relationships, whereas in others they are considerably more complex and are developed from a physically based representation of the various processes influencing the relationship between the inventory and the erosion or deposition rate. Further discussion of conversion models can usefully distinguish those employed in soil-erosion investigations to estimate rates of soil loss and deposition, and those used with cores collected from river floodplains, to estimate sedimentation rates. In addition, procedures for using environmental radionuclides to date sediment cores will also be discussed.

7.2. CONVERSION MODELS FOR SOIL-EROSION INVESTIGATIONS In most soil-erosion investigations, the approach used to estimate erosion and deposition rates is founded on a comparison of measured inventories with a reference value that represents the inventory to be expected at a site experiencing neither erosion nor deposition. In this context, the reference value provides an assessment of the total fallout input to the site, corrected for

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radioactive decay to the time of sampling. The resulting estimates of the erosion or deposition rate represent an average rate for the period extending back from the time of sampling to either the beginning of fallout in the mid 1950s, or the time of peak fallout in the early to mid 1960s, depending on the assumptions of the calibration model used. Although it has not been widely attempted, it is also, in principle, possible to estimate erosion and deposition rates for a specific period, by collecting cores from the same points during surveys separated by a number of years and establishing the reduction or increase in inventory over that period, whilst taking account of radioactive decay. In using this approach, however, it would be important to ensure that the period elapsed between the two surveys was sufficient to ensure that a significant difference in inventory would be detected, by taking account of the rates of erosion or deposition involved and the precision of laboratory measurements of activity. Thus, if the laboratory precision was of the order of ±10% at the 95% level of confidence, the increase or decrease in inventory caused by erosion or deposition would need to be significantly greater than 10%. As a result, a substantial time gap between the two surveys (e.g. 10 years) is likely to be required and this removes one of the key advantages of the technique, namely the potential to obtain retrospective information on erosion and deposition rates, essentially immediately, on the basis of a single site visit. For this reason, the resurvey approach is unlikely to represent a viable option in most investigations, and discussion of calibration procedures and conversion models will here focus on the more standard approach of comparing measured inventories with a reference inventory. In reviewing the various procedures and models that could be used to convert measurements to estimates of erosion or deposition rates, an important distinction can be made between cultivated soils and soils under permanent pasture or rangeland, which are uncultivated and essentially undisturbed. The need for this distinction relates to the vertical distribution of the inventory in the soil profile. In the case of a cultivated soil, the is likely to be well mixed within the plough depth, and thus, uniformly distributed through this layer. In contrast, in undisturbed soils, the is likely to be concentrated near the surface in response to its origin as atmospheric fallout. In many such soils, most of the will be contained within the upper 10 cm. Loss of a given proportion of the inventory is, therefore, likely to reflect a much higher erosion rate for a cultivated soil than for an undisturbed soil, since, in the latter case, most of the will be concentrated near the surface. Equally, the content of eroded soil is likely to be much more variable in the case of undisturbed soils, being dependent on the cumulative depth of erosion, and this needs to be taken into account when estimating deposition rates from the increase in the inventory, relative to the reference inventory. The following discussion of conversion models and calibration procedures will, therefore, consider cultivated and undisturbed soils separately. Furthermore, rather than reviewing all of the calibration procedures and conversion models that have been reported in the literature, emphasis will be placed on describing the main approaches

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and introducing a number of models that have been more widely employed in recent studies (cf. Walling and He, 1999). 7.3. CULTIVATED SOILS In their critical review of calibration models used in soil-erosion investigations, Walling and Quine (1990) distinguished between empirical and theoretical procedures or models. In the former case, a relationship between the erosion or deposition rate and the percentage loss or gain in the inventory, relative to the reference value, is derived empirically using the results from long-term erosion-plot, or similar, data. In the latter case, the calibration relationship is derived theoretically, by considering the main factors, including the erosion and deposition rates, that will influence the magnitude of the inventory, and incorporating these into an algorithm for estimating the inventory to be expected for a given erosion or deposition rate. The resulting data can then be used to establish the required calibration relationship. This simple division can be usefully applied here. 7.3.1. Empirical Calibration Relationships These calibration procedures involve simple empirical functions relating mean annual soil loss to the percentage reduction in the inventory, relative to the reference X (%) of the form:

where: X = percentage reduction in total inventory (defined as local reference inventory A= measured total inventory at the sampling point and to be determined. However, in many, if not most, studies, it will not be possible to use such empirically derived relationships. The data from long-term erosion-plot studies needed to derive the relationship may not be available for the study area and, as with any empirical approach, the available relationships will be location-specific, reflecting a number of local factors, for example, the soil properties, the method of cultivation, the implements used, and the crops grown. Use of a relationship in an environment different from that in which it was developed is, therefore, unlikely to be acceptable. The likely validity of any empirical relationship must also be considered, since measurements of erosion rates obtained from erosion plots may not be representative of the natural landscape or directly equivalent to the estimates obtained from measurements. For example, because of their small size, erosion plots may not be representative of the processes operating on natural slopes with greater slope lengths. Rills may be less likely to occur on plots than on natural slopes. Equally, the erosion

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rate obtained from plot measurements commonly represents the net soil loss averaged over the area of the plot, and is, therefore, not directly comparable with the point estimates of erosion rate provided by measurements. There are also several other potential problems and inconsistencies associated with the use of empirical equations (cf. Walling and Quine, 1990). It is important to ensure that the data used to derive an empirical calibration relationship should all have a similar time base and, ideally, the erosion plots should have been in operation throughout the period since the beginning of fallout. Where the installation of an erosion plot post-dates the main period of fallout, uncertainties regarding the former land use and erosion rates and the influence of plot installation on the inventories within the plot area may render the data of little value. It is also very important to recognize that any calibration relationship derived using this approach will relate to the period of plot measurement and will be time-specific. For example, Ritchie and McHenry (1975) used data available from erosion plots and small watersheds to produce a relationship of the form:

Since this equation was developed using data collected during the 1960s and early 1970s, it is time-specific and should not be applied to more recent conditions, as attempted by Menzel et al. (1987). The percentage reduction in the inventory for a given erosion rate would clearly be very much greater at present than in the early 1970s and the equation would seriously underestimate erosion rates if applied to present-day conditions. Since erosion plots are designed to measure the net soil loss from the area defined by the plot, they are unable to provide information on deposition rates. The use of empirical calibration relationships is thus, effectively restricted to estimating erosion rates and the empirical approach has not been used to estimate deposition rates for sampling points where the measured inventory exceeds the reference inventory. One useful example of the successful derivation of empirical calibration equations is provided by the work of Elliott et al. (1990) and Loughran and Campbell (1995). These authors used data from long-term erosion plots in New South Wales, Australia, to derive calibration relationships for cultivated areas of the form:

where: X = the percentage reduction in the inventory relative to the reference inventory This equation is, however, site- and time-specific and would need updating for use with measurements undertaken at the present time. In addition, Loughran and Campbell (1995) drew attention to the uncertainties associated with the values of soil loss reported for the plots used in this study, suggesting that the soil losses may have

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been underestimated by a factor of two for losses between 1% and 50% due to measurement errors. The failure of erosion plots to be fully representative of erosion on natural slopes might also be expected to cause the above equations to underestimate actual erosion rates, and it is noteworthy that the erosion rates estimated for a small catchment in the Hunter Valley, New South Wales, Australia, by Loughran et al. (1990), using a similar equation based on data from cultivated erosion plots, were an order of magnitude less than those estimated using the proportional model, a simple theoretical calibration model, which is discussed below.

7.3.2. Theoretical Calibration Models Theoretical calibration models attempt to avoid both the need for empirical data on which to base the calibration relationship and the many uncertainties associated with such data, by adopting a theoretical approach to establishing the relationship or model. In this case, the relationship between the erosion or deposition rate is derived theoretically by taking account of the various factors influencing the relationship between the rate of soil loss and the reduction in the inventory. In addition, the theoretical approach can provide the basis for deriving relationships for estimating deposition rates at sites where the measured inventory exceeds the reference value. The resulting theoretical calibration models vary greatly in their complexity, ranging from the simple proportional model that assumes that the proportion of the plough layer removed by erosion is directly proportional to the reduction in the inventory relative to the reference inventory, to more complex mass-balance models, which attempt to model the change in the content of the soil profile through time in response to the time-variant fallout inputs, losses of from the profile due to erosion, and the incorporation of soil containing no from below the original plough depth. Thus, for example, whereas the proportional model assumes that the is uniformly distributed or mixed within the plough layer, a mass-balance model could take account of the fact that the fallout occurring in a particular period during the years of significant fallout would initially accumulate at the surface and would only be mixed into the plough layer when the soil was cultivated. If most of the erosion occurred immediately prior to cultivation, that erosion could be expected to remove a much greater proportion of the cumulative inventory than if the erosion occurred after cultivation, when the input of fresh would be mixed within the soil. Similarly, mass-balance models are able to take account of the particle size selectivity of the erosion process. If, as is frequently the case, there is preferential mobilization of fine grained sediment by erosion, the mobilized sediment is likely to be enriched in and a given reduction in the inventory would, therefore, reflect a lower erosion rate than in the case of the bulk removal of soil by erosion. A number of these theoretical calibration models are described below.

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7.3.2.1. The Proportional Model The proportional model is probably the most commonly used theoretical model for estimating soil-erosion rates from measurements on cultivated soils (cf. Mitchell et al., 1980; de Jong et al. 1983; Fredericks and Perrens, 1988; Martz and de Jong, 1987; Vanden Berghe and Gulinck, 1987; Walling and Quine, 1990). The model is based on the simple premise that fallout inputs are completely mixed within the plough or cultivation layer and that the depth of soil lost as a result of erosion during the period since the beginning of accumulation is directly proportional to the reduction in the content of the soil profile relative to the reference inventory. Thus, if half of the input has been removed, the total soil loss over the period is assumed to be 50% of the plough depth. The erosion rate can be readily calculated by dividing the depth or mass of soil lost by the number of years involved. The basic equation of the proportional model can, therefore, be represented as:

where: d = depth of the plough or cultivation layer (m), B = bulk density of soil T= time elapsed since initiation of accumulation (yr). Slight variations on the basic form of the proportional model represented in Eq. 7.4 have been documented in the literature (e.g. de Jong et al., 1983; Vanden Berghe and Gulinck, 1987; Fredericks and Perrens, 1988; Kachanoski, 1987; Martz and de Jong, 1991), but the overall principle remains the same. In most cases where this model has been applied, no account has been taken of the effects of selective removal of fines on the validity of the results obtained. If selective removal of fines occurs, erosion rates will be overestimated, since in most environments is preferentially associated with the fine fraction. A particle size correction factor P should, therefore, be incorporated into Eq. 7.4 to take account of this problem, viz.:

where: P = the ratio of the concentration of mobilized sediment to that of the original soil (cf. He and Walling, 1996). Because the grain-size composition of mobilized sediment is usually enriched in fines compared with the original soil, P is generally greater than 1.0, due to the strong affinity of for fine soil particles. The value of P is, therefore, a function of the grain-size composition, both of mobilized sediment and the original soil (see Section 7.5.1.1 for its estimation).

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Although the proportional model was originally employed to estimate erosion rates for sampling points where the measured inventory is less than the reference inventory, its basic assumptions can be extended to permit estimation of deposition rates. Since the proportional model assumes (wrongly) that the concentration of the eroded sediment remains constant through time, the concentration of sediment deposited at a depositional site may, therefore, also be assumed to be constant. In cases where the inventory A for a sampling point is greater than the local reference inventory deposition of sediment may be assumed to have occurred and the annual deposition rate may be estimated using the equation:

where: percentage increase in the total inventory particle size correction factor. in Eq. 7.6 is another particle-size correction factor, representing the ratio of the concentration of deposited sediment to that of the mobilized sediment. Because the grain size composition of deposited sediment is usually depleted in the finer fractions compared to mobilized sediment, is generally less than 1.0 (see Section 7.5.1.1 for its estimation). Since, in its basic form, the proportional model only requires information on the plough depth and soil bulk density, in addition to values of the percentage reduction of the inventory for individual sampling points, it is very easy to apply. However, the key assumptions of this model, whilst apparently logical, are a considerable oversimplification of the actual processes related to the behaviour and accumulation of in the soil. The accumulation of takes place over many years and some of the fallout input will remain at the soil surface prior to incorporation into the soil profile by cultivation. If some of the fresh accumulated on the surface is removed by erosion prior to its incorporation into the soil profile, soil-loss rates provided by the model will be overestimated, since it assumes that the is uniformly mixed throughout the plough layer. Equally, however, since this model does not take into account the maintenance of the depth of the plough layer, through the balancing of surface lowering by the progressive incorporation of soil from below the original plough depth, and the mixing of the remaining into this soil, the results obtained are likely to significantly underestimate the actual rates of soil loss. The erosion of a depth of soil equivalent to the plough depth would not result in the total removal of the original inventory, as assumed by the model, since a plough layer will still exist and some of the original inventory will be mixed within this layer. To demonstrate this, Fig. 7.2 compares the relationship between the erosion rate and the percentage reduction in the inventory relative to a reference inventory, generated using the

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proportional model, with that derived using a simple mass-balance approach, which takes into account the effect of progressive incorporation of the subsoil from below the plough depth into the plough layer. The deviation of erosion rates estimated using the proportional model from those estimated using the simple mass balance approach increases with increasing percentage reduction in the inventory. When the reduction in the inventory relative to the local reference inventory exceeds 50%, the proportional model could underestimate the erosion rate by more than 40%.

7.3.2.2. The Gravimetric Approach Another simple calibration procedure is that employed by Brown et al. (1981b) and Lowrance et al. (1988), which was termed the gravimetric approach by those authors. Unlike the proportional model, this approach was applied to the entire study area to obtain a single estimate of the erosion rate, rather than to the measurements of inventory obtained for individual sites, although it could in fact be applied to individual sites. The mean inventory for an eroded area (A) is compared with the reference value for the area and the deficit is calculated and converted to an estimate of the average soil loss from the area, using an estimate of the mean concentration of surface soil within the eroded area and the time (T, yr) elapsed since initiation of the 137Cs accumulation, viz.:

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In the original study of a small watershed in Oregon (Brown et al., 198la), the estimate of was obtained by algebraic manipulation of the budget of the watershed, assuming that the total removed from the eroded area must balance the amount deposited within the watershed, plus that transported out of the basin and represented by the sediment delivery ratio. Using the same approach, subsequent workers, such as Lowrance et al. (1988), have, however, estimated directly from measurements undertaken in an undisturbed area such as a forest. The use of the current concentration in the soils to represent is likely to overestimate the erosion rates, because concentrations in the soil will decline with time due to progressive surface lowering and the incorporation of soil containing no from below the plough depth. 7.3.3.3. Mass-Balance Models Mass-balance models, which have been widely used, attempt to overcome some of the limitations of the simple proportional model by modelling the changes in the content of the soil profile through time in response to fallout inputs, losses of from the profile due to erosion, and the incorporation of soil containing no from below the original plough depth, over the period since the onset of fallout (Kachanoski and de Jong, 1984; Fredericks and Perrens, 1988; Quine, 1989, 1995; Walling and Quine, 1990, 1993; He and Walling, 1997; Yang et al., 1998; Yang et al., 2000). The basic form of a mass-balance model for an eroding site can be expressed as follows:

where: A(t) = cumulative activity per unit area t = time since the onset of fallout (yr), R = erosion rate = the average plough depth represented as a cumulative mass depth = decay constant for l(t) = annual deposition flux at time For many locations, detailed information on the annual deposition flux is unlikely to be available. In this situation the fallout record from a representative station in the same hemisphere can be scaled to match the measured reference inventory at the study site and used to provide values of I(t) (see Section 7.5.1.2). Solution of Eq. 7.8 provides the basis for establishing a relationship between mean annual soil loss during the period since the beginning of fallout and the percentage reduction in the measured inventory, relative to the local reference inventory, required for calibration purposes. Equation 7.8 provides a general framework for establishing a conversion model. Many workers have refined the basic equation in order to take account of other

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processes and factors that can be expected to influence the relationship between the erosion rate and the percentage reduction in the inventory, relative to the reference inventory. Thus, for example, Kachanoski and de Jong (1984) included an enrichment coefficient in the model, in order to take account of the selective erosion of fine material and the preferential association of with fine soil particles. Similarly, Fredericks and Perrens (1988) modified the model to take account of inter-annual variation in erosion rates, in order to make it more applicable to Australian conditions. Quine (1989, 1995), Walling and Quine (1993) and He and Walling (1997) further extended the mass-balance model to take account of the fate of the freshly deposited fallout before its incorporation into the plough layer by cultivation. Zhang et al. (1990) and Kachanoski (1993) have also formulated a simplified mass-balance model, by assuming that the total input was received at a particular time (1963), and deriving an exponential relationship between annual soil loss and total reduction. In addition, a number of recent investigations have highlighted the role of tillage displacement in causing soil redistribution and, thus, redistribution on cultivated land (e.g. Walling and Quine, 1993; Quine, 1995; Quine et al., 1996). Such tillage-induced redistribution can occur even in the absence of soil erosion and this component of redistribution needs to be taken into account when using measurements to derive estimates of water-induced soil erosion per se. If the effects of tillage redistribution on the magnitude and spatial pattern of measured inventories can be quantified and taken into account, the remaining component of redistribution will reflect the impact of water erosion. Walling and Quine (1993), Quine (1995) and Quine et al. (1996) have attempted to incorporate the influence of tillage in redistributing into a mass-balance model, and Walling and He (1999) reported a further refinement of that approach. Further consideration of the range of mass-balance models that could be used to provide calibration relationships for estimating soil-erosion rates from measurements can usefully focus on three examples. The first is the simplified mass-balance model proposed by Zhang et al. (1990), the second is a more comprehensive mass-balance model documented by Walling and He (1999), and the third is the mass-balance model incorporating the influence of tillage displacement presented by Walling and He (1999).

7.3.3.4. A Simplified Mass-Balance Model Zhang et al. (1990) have proposed a simplified mass-balance model that assumes that the total fallout occurred in 1963, instead of from the mid 1950s to the mid 1970s. A site with a total inventory A less than the local reference inventory is assumed to be an eroding site, while sites with inventories higher than the reference inventory are assumed to be depositional sites. In its original form, this simplified mass-balance model did not take account of particlesize effects. But a correction factor P can be included. For an eroding site assuming a constant rate of surface lowering the total inventory at year t (yr) can be expressed as:

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where: P = particle size correction factor defined as in Eq. 7.5, d = average plough depth expressed as cumulative mass depth The above equation can be rearranged to derive the mean annual rate of soil loss as:

For a depositional site assuming a constant deposition rate at the site, the sediment deposition rate can be estimated from the concentration of the deposited sediment according to:

where: excess inventory of the sampling point over the reference inventory in year t (defined as measured inventory less local reference inventory) concentration of deposited sediment in year particle size correction factor (calculated as in Eq. 7.6). The concentration of deposited sediment can be assumed to be represented by the weighted mean concentration of sediment mobilized from the upslope contributing area. can, therefore, be calculated using the following equation:

where: S = the upslope contributing area R = the erosion rate concentration of mobilized sediment from an eroding point which can be calculated from Eq. 7.9 as

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where: i.e. the local reference value at the time of sampling. This simplified mass-balance model takes into account the progressive reduction in the concentration of the soil within the plough layer, due to removal of surface soil by erosion and the incorporation of soil containing negligible from below the original plough depth and, thus, represents an important improvement over the proportional model. The model is also easy to use and requires only information on plough depth and the local reference inventory. However, it does not take into account the potential for removal of freshly deposited fallout before its incorporation into the plough layer by cultivation, which may occur during rainfall events that produce surface runoff and, therefore, erosion. The assumption that the total fallout input occurred in 1963 is also an oversimplification. 7.3.3.5. An Improved Mass-Balance Model Following Walling and He (1999), the basic mass-balance model represented by Eq. 7.8 can be further improved to take account of the fate of the freshly deposited fallout before its incorporation into the plough layer by cultivation and the effects of particle-size selectivity in sediment mobilization, transport, and deposition on redistribution. For an eroding point the change in the total inventory A(t) with time can be represented as:

where: the proportion of the freshly deposited fallout removed by erosion before being mixed into the plough layer by cultivation. If sheet erosion (rate R) and an exponential depth distribution for the initial distribution of fallout at the surface of the soil profile are assumed, following He and Walling (1997), can be determined as:

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where: the proportion of the annual input susceptible to removal by erosion, H = the relaxation mass depth of the initial distribution of fallout in the soil profile The value of is dependent on the timing of cultivation and the local annual rainfall regime. For example, consider a situation where there is only one period per year with high-intensity rainfall events, which can generate surface runoff and, thus, erosion, and this occurs shortly before the period of cultivation. In this case, all the already accumulated at the soil surface as well as the input directly associated with this rainfall will be susceptible to removal by erosion, and the value of can be assumed to be 1.0, if there is only one cultivation operation. In cases where the period of high-intensity rainfall occurs immediately after cultivation, the accumulated at the soil surface before the occurrence of this event will be incorporated into the plough layer by the tillage operation, and only the component of input directly associated with this period of high-intensity rainfall will be susceptible to removal by erosion. Under these circumstances, the value of may be estimated using the ratio of the total depth of rainfall associated with the period of high intensity rainfall to the total annual rainfall If there is more than one cultivation operation and more than one period of heavy rainfall that can produce surface runoff, each year, the estimation of will need to consider the timing and magnitude of precipitation inputs in relation to the cultivation operations. If represents the year when cultivation started, building on Eqq. 7.14 and 7.15, the total inventory A(t) in year t can be expressed as:

where: the 137Cs inventory

Assuming it is constant, the erosion rate R can be estimated by solving Eq. 7.16 numerically, when the deposition flux and values of the relevant parameters are known. In the absence of local information on the annual deposition flux, this may be estimated by assuming that the temporal distribution of annual fallout totals was similar to that recorded at a representative monitoring station in the region (see Section 7.5.1.2) and adjusting the magnitude of these values to take account of reference inventory of the study site (i.e. by multiplying by the ratio of the local reference inventory to that of the monitoring station in the region). The concentration of mobilized sediment can be expressed as:

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The first term on the right-hand side of Eq. 7.18 represents the removal of the freshly deposited and the second term the erosion of the accumulated stored in the plough layer. Because the deposition flux I(t) is determined by the history of atmospheric nuclear weapons tests and associated fallout, the relationship between inventory and erosion rate predicted by the model (Eq. 7.16) will be controlled by the parameters H, and P. Figure 7.3 demonstrates the sensitivity of the model predictions to the values of the various parameters, assuming a reference inventory and a temporal pattern of deposition flux similar to that documented at Milford Haven, United Kingdom (Cambray et al., 1989).

The model-predicted erosion rates are positively related both to the plough depth and to relaxation depth H, but are inversely related both to and to the particlesize correction factor P. The model is more sensitive to than to H. For a location by with 20% loss relative to the local reference inventory, an increase in 50% would result in an increase of the erosion rate by ca. 36%, whereas an increase in H by 100% would result in an increase in the erosion rate by only ca. 12%. The model is very sensitive to both and P, but is more sensitive to the latter. When is doubled, the erosion rate would be reduced by ca. 19%, whereas when P is increased by 33%, the erosion rate would be reduced by ca. 25%. Accurate

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estimation of these parameters, and more particularly d and P, is therefore important, in order to obtain reliable estimates of erosion rates. If A(t) is greater than the local reference inventory at a sampling point, deposition may be assumed. The excess inventory (defined as the measured total inventory A(t) less the local direct fallout input can be attributed to the accumulation of associated with deposited sediment derived from the upslope areas and can be expressed as:

where: the deposition rate the concentration of deposited sediment reflects the combination of sediment and its associated mobilized from the entire eroding area that converges on the aggrading point. Generally, can be assumed to be represented by the weighted mean of the concentrations of the sediment mobilized from the upslope contributing area and can, therefore, be calculated as:

Since deposited sediment is commonly depleted in the finer fractions, relative to the mobilized sediment, will generally be <1.0. From Eqq. 7.19 and 7.20, the mean annual deposition rate can be calculated using the following equation:

7.3.3.6. A Mass-Balance Model Incorporating the Effects of Soil Redistribution by Tillage The mass-balance models described above do not take account of soil redistribution caused by tillage. As tillage is likely to result in the redistribution of soil and within a field, even in the absence of water-induced erosion, it should be taken into account when using measurements to derive estimates of erosion rates. Walling

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and Quine (1993) were probably the first to attempt to incorporate the effects of tillage redistribution into a mass-balance model. The model presented here, which is based on that reported by Walling and He (1999), represents a refinement of that approach. It is important to note that, whereas the calibration procedures and models described above can be applied to measurements obtained for individual sampling points, this particular mass-balance model can only be applied to a complete slope transect parallel to the flow direction, because it is necessary to take account of the down-slope transfer of soil by tillage. The effect of tillage on soil redistribution can be represented by a down-slope sediment flux. Following Govers et al. (1996), the down-slope sediment flux from a unit contour length may be expressed as:

where: the steepest slope angle (°), a constant related to the tillage practice employed If, for a uniform slope (i.e. where there is no divergence or convergence of surface flow), a flow line down the slope is divided into several sections and each section can be approximated as a straight line, then for the ith section (from the hilltop), the net soil redistribution induced by tillage can be expressed as:

where: the slope angles of the ith and (i-1)th segments, of the ith segment, and and are defined as:

is the slope length

Values of the parameter ø in Eq. 7.22 may be determined experimentally (cf. Govers et al., 1994; Quine et al., 1996), but if no experimentally derived data are available, can be estimated from the erosion rate the net soil-erosion rate) for an eroding point from the first slope segment at the top of the slope (with length and slope angle assuming that water erosion is negligible due to the limited slope length and that there is no tillage input to this point):

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can be calculated from the measured total point using Eq. 7.16:

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inventory

For a point experiencing water erosion at a rate inventory with time t can be expressed as:

for that

variation of the total

where: and the concentrations of the sediment associated with tillage input, tillage output, and water output respectively The net erosion rate is:

For a point at which water-induced deposition is occurring (at a rate variation of the total inventory with time can be expressed as:

where: the

concentration of the sediment input from water-induced deposition

The net erosion rate R is:

The concentration o f the soil within the plough layer expressed as:

can be

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where: the net deposition rate. The relationships between and

and

are as follows:

while the concentration of water-derived deposited sediment can be expressed as:

For a given point along the flow line, the tillage-induced erosion or deposition rate can be calculated from Eqq. 7.23 and 7.25, and the net soil-erosion rate (R>0) or deposition rate (R<0), attributable to water erosion, can be estimated by solving Eqq. 7.27, 7.28, 7.32, and 7.33 numerically. The mass-balance model described above is based on measurements undertaken along slope transects parallel to the down-slope direction of flow. This treats the movement of soil particles and the associated by tillage as a onedimensional process and assumes no convergence or divergence of tillage fluxes on the slope. In many landscapes, this assumption will be unrealistic, due to the occurrence of converging and diverging tillage-induced down-slope fluxes and it is necessary to take account of the three-dimensional pattern of tillage-induced and water-induced soil redistribution within the landscape. Walling et al. (1999) have shown how this can be achieved using a grid with regular cells. The net tillageinduced soil-redistribution rate for a grid cell can be expressed as:

with the values of

and

being calculated as:

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where: the width of the cell (m), the cell area The net rate of tillage-induced sediment input, to a cell will reflect the sediment input contributed from all its neighbouring cells. Other calculations are essentially the same as used for the transect approach (i.e. Eqq. 7.25–7.33). This grid-cell approach is particularly suited to the use of a GIS package such as ARC/INFO.

7.4. UNDISTURBED SOILS For undisturbed soils, the processes involved in redistributing in the profile differ greatly from those for cultivated soils. The depth distribution of in the undisturbed soil profile will be significantly different from that in cultivated soils, where it is mixed within the plough layer (Walling et al., 1995; He and Walling, 1997). In most environments, the inventories associated with undisturbed soils will be concentrated near the surface and concentrations will decline exponentially with depth. In many cases, a large proportion of the total inventory will be contained within the top 15 cm of the soil. Loss of a given percentage of the reference inventory is, therefore, likely to reflect a much lower erosion rate than for a cultivated soil. Alternative approaches are, therefore, required for deriving estimates of soil-erosion rates from measurements for undisturbed soils. As in the case of cultivated soils, empirical relationships and theoretical models have been employed. Thus, it is appropriate to consider here both approaches in turn.

7.4.1. Empirical Relationships As with cultivated soils, empirical calibration relationships similar to Eq. 7.1 could be derived for undisturbed soils using data from erosion plots. The number of studies where such relationships have been successfully established have been relatively few, but Elliott et al. (1990) and Loughran et al. (1995) reported the development of a calibration relationship for grazing areas in New South Wales, Australia, equivalent to that provided by Eq. 7.3 for cultivated areas in the same region, viz.:

where: X = the percentage reduction in the inventory relative to the reference inventory.

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The same limitations as indicated for empirical relationships developed for cultivated areas will also apply to those developed for undisturbed soils.

7.4.2. Theoretical Models As in the case of cultivated soils, the lack of data necessary to establish empirical relationships means that most attempts to develop calibration procedures for undisturbed soils have employed theoretical models. These again vary considerably in their degree of complexity and two main approaches can be identified. In the first, attention focuses on the characteristic exponential depth distribution of in undisturbed soils. If the depth distribution can be characterized by a simple numerical function, it is possible to estimate the depth of soil eroded from the proportion of the reference inventory remaining in the soil profile. Such calibration models are commonly referred to as profile distribution models. The second approach is analogous to the mass-balance models used to develop calibration relationships for cultivated soils. In this case, an attempt is made to model the accumulation and vertical distribution of in the soil profile through time and, thus, the relationship between erosion rate and the degree of reduction of the reference inventory. These models are frequently termed diffusion and migration models, since they are the two main processes influencing the downward transfer of into the soil and, thus, the vertical distribution of in the soil. Both of these approaches will be considered in turn.

7.4.2.1. Profile-Distribution Models In most situations, the depth distribution of in an undisturbed stable soil will exhibit an exponential decline with depth. This may be described by the following function (cf. Walling and Quine, 1990; Zhang et al., 1990):

where: x = mass depth from soil surface amount of above depth coefficient describing profile shape The greater the value of the shape factor the deeper the penetration of into the soil. If it is assumed that the total fallout occurred in 1963 and that the depth distribution of the in the soil profile is independent of time, the erosion rate for an eroding point (with total inventory less than the local reference inventory can be estimated using the following relationship (cf. Walling and Quine, 1990; Zhang et al., 1990):

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where: t = the year of sample collection (yr), X = the percentage reduction in the reference inventory Although the profile-distribution model is simple and easy to use, it involves a number of important simplifying assumptions. These include failure to take account of the time-dependent behaviour of both the fallout input and the postdepositional redistribution of within the soil profile after deposition from the atmosphere. It is clear that, in reality, the deposited at the surface will gradually move down into the soil and, thus, the coefficient is likely to increase with time. As such, this model could overestimate rates of soil loss. The model as described above also assumes that the depth distribution of in the soil can be adequately characterized by an exponential function. Although the literature provides a considerable body of evidence to confirm this assumption (cf. Walling and Quine, 1992, 1995; Walling, 1998), it should be recognized that other functions may be appropriate in some instances, and in such cases alternative computation procedures will be required (cf. Yang et al., 1998). The general validity of the profiledistribution model, and in particular the assumption of an exponential depth distribution, has, nevertheless, been documented by Porto et al. (2001), who demonstrated close correspondence between the estimates of net soil loss from a small catchment in southern Italy obtained using this approach and measured values of sediment yield available for the same catchment. 7.4.2.2. Diffusion and Migration Models Although the simple profile-distribution model (Eq. 7.38) described above can be used to obtain estimates of soil-erosion rates for undisturbed soils, a more realistic approach would need to take account of the temporal variation of the depth profile resulting from the time-dependent fallout input and the postdepositional redistribution of in the soil profile (cf. Pegoyev and Fridman, 1978; Bachhuber et al., 1982; Reynolds et al., 1982; Walling and He, 1992, 1993; Knatko et al., 1996; He and Walling, 1997). Redistribution of within the soil profile represents the result of a complex set of mechanisms including physical, physico-chemical and biological processes. In order to avoid the need to model each of these processes, He and Walling (1997) represented their net effect using a onedimensional transport model characterized by an effective diffusion coefficient D and a migration rate for the soil profile (cf. Pegoyev and Fridman, 1978; Walling and He, 1993). The two lumped parameters D and V reflect all redistribution processes, including physico-chemical processes involving the adsorption and desorption of by soil particles, which are frequently represented

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by the distribution coefficient or the retardation factor (cf. Reynolds et al., 1982). Variation of the concentration in surface soil with time t (yr) may be approximated as:

where: D = the diffusion coefficient V = the downward migration rate of in the soil profile The diffusion coefficient D and the migration rate V describe the evolution of the shape of the profile with time. High values of D and V will imply a deeper penetration of into the soil profile. For an eroding point, i.e. the measured total inventory is less than the local reference inventory and where sheet erosion can be assumed, the erosion rate R may be estimated from the reduction in the inventory (defined as the reference inventory less the measured total inventory and the concentration in the surface soil from Eq. 7.40 using the relationship:

For a depositional location, the deposition rate can be estimated from the concentration of deposited sediment and the excess inventory (defined as the total measured inventory less the local reference inventory using the following relationship:

where

can be calculated from:

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Assuming a reference inventory of and a temporal pattern of deposition flux similar to that documented at Milford Haven, United Kingdom (Cambray et al., 1989), Fig. 7.4 illustrates the relationships between erosion rate and the percentage reduction in the inventory relative to the local reference inventory predicted by the model, for a range of values for the parameters D, V, H and P. Figure 7.4 indicates that the model is very sensitive to these parameters, and the predicted erosion rates are positively related to D, V and H, but inversely related to P. For a location with 20% loss relative to the local reference inventory, an increase in P by 33% would result in a reduction of the erosion rate by ca. 25%. The model is more sensitive to D than to V and H. If the value of V or H is doubled, the erosion rate would be increased by ca. 7%, whereas if D is increased by 66%, the erosion rate would be increased by as much as 23%. Since the model is sensitive to these parameters, particular care is required in their estimation.

7.5. SELECTING AND USING A CALIBRATION MODEL FOR A SOIL EROSION INVESTIGATION The various models presented in Sections 7.3 and 7.4 provide the investigator with a considerable, and perhaps bewildering, degree of choice in selecting a conversion model for use in a particular investigation. It is particularly important to distinguish cultivated and undisturbed soils in making the selection, but, beyond this, the choice is likely to reflect a trade-off between simplicity and complexity, the limitations of the individual models and their ease of application. Thus, for example, whereas the proportional model is relatively easy to apply using Eqq. 7.4, 7.5, and 7.6, the improved mass-balance model and the mass-balance model incorporating soil redistribution by tillage are considerably more complex and demanding in terms of

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their implementation. In some cases, the available data and the nature of the sampling programme may also introduce constraints. Some of the models require the input of values for a number of parameters that need to be known and others, such as the mass-balance model incorporating tillage translocation, can only be applied where samples are collected from slope transects running parallel to the flow direction or from the intersections of an appropriate grid. In most cases the simpler models possess important limitations that are overcome by the more complex models, but at the price of increased complexity and demand for computational skills. For many models, it will be necessary to produce a computer program to undertake the various calculations. Thus, as indicated above, the proportional model, whilst simple to apply, is likely to underestimate the erosion rates and the assumptions involved in using the model to estimate deposition are also highly questionable. Equally, the profile distribution model, which is again relatively simple to apply, takes no account of the time-dependence of both the fallout input and the redistribution of the fallout input within the soil profile and could, therefore, overestimate rates of soil loss. The more complex models, such as the mass-balance models and the diffusion and migration model, attempt to take account of more of the factors known to influence the relationship between the erosion or deposition rate and the reduction or increase in the inventory and it is, therefore, commonly assumed that their results will be more reliable. However, in the absence of independent validation, this increased reliability cannot be guaranteed. In many studies it may be advisable to use more than one model, in order to provide a measure of the potential uncertainties involved. Furthermore, in view of the large number of different calibration procedures and models documented in the literature, it would be advantageous to use standardized calibration procedures, so that the results obtained from different studies are comparable, even if their absolute accuracy remains uncertain. Recent work at the University of Exeter, United Kingdom, within the framework of the IAEA Coordinated Research Projects on the use of environmental radionuclides in soil erosion and sedimentation studies (cf. Walling and He, 2001) addresses some of the problems and uncertainties surrounding the use of calibration models by producing simple computer software for applying a range of the available models in a standardized manner. The resulting software that is freely available helps to overcome many of the difficulties involved in applying the more numerically complex models. In addition, by focusing on a limited selection of models, use of the model software affords a means of ensuring that the models are applied in a standardized manner in different investigations. The software covers the following six models, which correspond to those described in Sections 7.3 and 7.4: 1) The proportional model (cf. Section 7.3.2.1). 2) A simplified mass-balance model based on that proposed by Zhang et al. (1990) (cf. Section 7.3.3.4) (Mass-Balance Model 1). fallout input 3) An improved mass-balance model incorporating time-variant and consideration of the fate of freshly deposited fallout before its incorporation into the plough layer by cultivation (cf. Section 7.3.3.5) (Mass-Balance Model 2).

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4) A mass-balance model incorporating soil redistribution by tillage (cf. Section

7.3.3.6) (Mass-Balance Model 3). 5) A profile distribution model for uncultivated soils (cf. Section 7.4.2.1). 6) A diffusion and migration model for uncultivated soils (cf. Section 7.4.2.2). All six models can be used with data from single transects, and, with the exception of Mass-balance model 3, all the models can be used with random point data obtained from a field or study area. Instructions for running the models and estimating parameters are provided with the software. A listing of the key parameters in models 2 to 6 and an indication of their likely values is provided in Table 7.2, and further information on the derivation of some of the more complex parameters is provided below.

7.5.1. Estimation of Key Parameters Used in Calibration Models 7.5.1.1. The Particle Size Correction Factors P and The particle-size correction factors P and provide a means of taking account of the particle-size selectivity of erosion and deposition processes and thus the enrichment or depletion of eroded and deposited sediment in relative to the original soil. The correction factor P, which is applied when estimating erosion rates (e.g. Eqq. 7.5, 7.10, and 7.16), is defined as the ratio of the concentration in mobilized sediment to that of the original soil, whereas which is used when estimating deposition rates (e.g. Eqq. 7.6, 7.20, and 7.33), is defined as the ratio of the content of deposited sediment to that of the mobilized sediment. Both factors could be estimated directly by measuring the concentration of the relevant soil or sediment, but, since such data are unlikely to be available, they are more commonly estimated indirectly, by comparing the particle-size distributions of the two components of the ratio. It is well known that particle size exerts a strong influence on the content. One useful approach to estimating P and from particle size data is that reported by He and Walling (1996), which makes use of measurements of the specific surface area of the soil or sediment involved. An estimate of the specific surface area of a sediment sample can be readily derived from its particle-size distribution, by assuming spherical particles. If the specific surface area of mobilized sediment is and that of the original soil is He and Walling (1996) showed that P can be calculated as:

where: v = a constant with a value of ca. 0.65.

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If the specific surface area of deposited sediment is as:

The value of v in Eq. 7.45 is the same as that in Eq. 7.44.

can be calculated

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7.5.1.2. Estimating Annual Fallout Deposition Fluxes Several of the models (i.e. the improved mass-balance model, the mass-balance model incorporating soil redistribution by tillage, and the diffusion and migration model) require information on the annual atmospheric deposition flux. In the absence of direct measurements, the record of annual fallout inputs to a study site can be synthesized from those recorded at other monitoring stations. For example, for study sites in the northern hemisphere, the temporal distribution of annual fallout inputs can be assumed to be similar to that reported for total fallout inputs to the northern hemisphere by Cambray et al. (1989), based on data recorded at a number of stations located in that hemisphere. The local deposition flux I(t) for a study site can, therefore, be calculated as:

where: an hypothetical record of annual deposition flux for a site in the northern hemisphere based on the annual totals of total deposition to the northern hemisphere a scaling factor defined as:

where: the current inventory for the hypothetical fallout record. A hypothetical record of annual deposition flux for the northern hemisphere, starting in 1954 and continuing to 1999, and providing a total inventory of in 1996, is listed in Table 7.3. Chernobyl-derived inputs are not included in this record, but in areas where Chernobyl-derived fallout was received and its deposition flux is known, this could be added to the data set in Table 7.3. The same approach can be adopted for sites in the southern hemisphere and a hypothetical record of annual fallout for a representative site in the southern hemisphere is also provided in Table 7.3. For this site, the total inventory measured in 1996 would be

7.5.1.3 Estimating the Proportion Factor When running mass-balance models 2 and 3, values for the proportion factor must be supplied. The value of represents the proportion of the annual fallout input susceptible to removal by erosion prior to incorporation into the soil by cultivation and, therefore, depends on the local rainfall regime and the timing of cultivation.

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In situations where the soil is cultivated once per year and high-intensity rainfall events, which can generate surface runoff and thus erosion, occur shortly before the period of cultivation, the already accumulated at the soil surface as well as the input directly associated with these high-intensity rainfall events will be susceptible to removal by erosion, and the value of can be assumed to be In cases where the main period of high-intensity rainfall capable of causing erosion occurs immediately after cultivation has been completed, the accumulated in the soil surface before the occurrence of these events will have been

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incorporated into the plough layer, and only the directly associated with these rainfall events will be susceptible to removal by erosion. Under these circumstances, the value of may be estimated as the ratio of the depth of rainfall associated with the period of high-intensity rainfall, which produces surface runoff, to the total annual rainfall In general, values of will lie between If there is more than one cultivation each year, the estimation of needs to consider the timing of precipitation in relation to tillage operations.

7.5.1.4 Estimating the Relaxation Depth H Values of the relaxation depth H for the initial distribution of fallout in surface soils must be supplied for both mass-balance models 2 and 3 and the diffusion and migration model. An exponential depth distribution is commonly assumed and this parameter reflects the depth to which the fresh fallout input penetrates the soil. It is defined as the mass depth at which the concentration reduces to 1/e of the surface concentration. The value can be determined experimentally by observing the behaviour of applied to a soil surface using a rainfall simulator and could be expected to vary according to soil properties. He and Walling (1997) reported values of for soils in Devon, United Kingdom. 7.5.1.5 Estimating the Parameter in the Profile Shape Model The parameter used in the profile shape model can be estimated by fitting an exponential function to the depth distribution in an undisturbed soil, using a least squares curve fitting routine. Figure 7.5A illustrates a typical exponential distribution of concentration with depth in an uncultivated soil. In some situations, although the depth distribution of concentration is not exponential, the depth distribution of the cumulative inventory can generally be approximated as an exponential function (e.g. Fig. 7.5B). In either case, in order to estimate an exponential function of the form can be fitted to the depth distribution using least-squares with f(0) and as the two parameters to be determined. 7.5.1.6 Estimating D and V in the Diffusion and Migration Model Values of D are typically in the range and values of are commonly in the range 0.2 to Both parameters can be estimated empirically from the depth distribution of in an undisturbed soil. Figure 7.6 presents a typical profile for an uncultivated soil, which can be used to derive estimates of D and V. The profile is characterized by a relatively broad peak, with the maximum concentration located a few centimetres below the soil surface. Although accurate values of D and V can be obtained through solving the one-dimensional transport equation (cf. He and Walling, 1997), they may be approximated using the following equations:

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where: t = the year when the soil core was collected (yr), mass depth of the maximum concentration the mass depth where the concentration reduces to 1/e of the maximum concentration

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7.6. ESTIMATING THE RATE OF DEPOSITION OF FINE OVER-BANK SEDIMENT ON RIVER FLOODPLAINS The basis for using measurements to estimate rates of accretion of over-bank floodplain sediments reflects the accumulation of in these sediments as a result of inputs from two primary sources. These sources are, firstly, direct atmospheric fallout to the floodplain surface and, secondly, the deposition of sediment-associated during the process of sediment accretion. In the latter case, the sedimentassociated represents radiocaesium originating as fallout over the surface of the upstream catchment, which has been adsorbed by soil and sediment particles and subsequently mobilized by erosion and transported downstream as part of the suspended sediment load of the river. Some of this suspended sediment load and its associated will be deposited on the floodplain during over-bank flooding. Both the vertical distribution and the total inventory of in floodplain sediments will, therefore, commonly differ from those in the soils of adjacent undisturbed areas above the level of floodplain inundation, since the latter will have

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received only from direct fallout. Figure 7.7 compares the profile recorded for a sediment core collected from the floodplain of the River Stour in Dorset, United Kingdom, with that for a soil core collected from an adjacent area of undisturbed permanent pasture above the level of flood inundation.

The substantially greater inventory of the floodplain core reflects the accumulation of additional associated with the deposition of fine sediment during over-bank flood events. The progressive accumulation of fine sediment on the floodplain is reflected by the occurrence of to much greater depths in the floodplain core and the similarity between the depth distribution and the temporal pattern of fallout over the period from the 1950s to the time of sampling. The peak level of activity found at ca. 21 cm can be equated with the surface of the floodplain in 1963, since this was the year of peak fallout and maximum activity in the sediment eroded from the upstream catchment (cf. Walling and He 1992). Existing procedures for using measurements to estimate the age/depth relationship, and, thus, the sedimentation rate associated with a floodplain sediment core have used two approaches (cf. Walling and He 1997). In the first, the shape of the depth profile (e.g. Fig. 7.7B) is used in conjunction with information on the temporal pattern of fallout input, whilst in the second the sedimentation rate is estimated from a single measurement of the total inventory of the core. It is important to note that, in both cases, it is only possible to derive an estimate of the mean sedimentation rate for the period extending from the time of the main bomb

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fallout input to the time of collection of the sediment core, and this assumes that sedimentation is an essentially continuous, rather than more intermittent, process. Both approaches can be considered in turn. In analysing the shape of the depth profile in relation to the record of fallout input, the absolute magnitude of the annual fallout inputs may not be known. However, it can generally be assumed that the relative magnitude of these values will follow the pattern shown by monitoring stations in the same region of the world. The record for Milford Haven, United Kingdom (cf. Cambray et al., 1989) is thus widely used in Europe, whilst those for New York and Adelaide/Brisbane have been frequently used in North America and Australia, respectively. Equally, the generalized temporal fallout patterns for the northern and southern hemispheres presented in Table 7.3 afford an effective basis for estimating the fallout pattern for any site in the two hemispheres. In the simplest application of this approach, either the depth of the level with peak activity is equated with the floodplain surface in the year of peak fallout input, which is commonly 1963 in the northern hemisphere (cf. Ritchie et al., 1975; McHenry et al., 1976; Walling and He, 1992), or the depth at which significant concentrations first appear is assumed to indicate the position of the surface in the mid 1950s (cf. Popp et al., 1988; Ely et al., 1992). In both cases, it is necessary to take account of possible post-depositional redistribution of in the sediment profile. For this reason, the age/depth relationship is commonly established using the depth of the peak activity, since the position of the peak is less likely to be influenced by post-depositional redistribution than the depth at which first appears. An estimate of the downward migration rate associated with a profile can be obtained by examining the shape of the profile for an adjacent undisturbed soil above the level of floodplain inundation (e.g. Fig. 7.7A). In the case of an undisturbed soil not subject to sediment accumulation, the peak activity should remain at the surface in the absence of downward migration. In most cases, however, the peak will be displaced slightly below the surface and the magnitude of the displacement affords a means of estimating the downward migration rate for the period between the year of peak fallout and the time of collection of the sample. In order to avoid complications in estimating sedimentation rates associated with down-core changes in bulk density, the depth profile is commonly plotted with depth expressed as a cumulative mass depth below the surface. Thus, if both the cumulative mass depth at which the peak activity occurs and the downward migration rate of the peak are known, the mean sedimentation rate can be estimated as:

where: the time elapsed between the year of peak fallout and the time the core was collected (yr).

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In a more complex procedure described by Walling and He (1997), a model describing the key processes responsible for the development of the depth profile (e.g. fallout inputs, sediment deposition, and downward migration) was fitted to the measured depth distribution, to establish the sedimentation rate, which was treated as an unknown. In the above discussion of the use of the depth profile to establish the age/depth relationship for a floodplain sediment core, it is implicitly assumed that the floodplain sediments are undisturbed and that the depth profile reflects the interaction of the progressive accumulation of sediment with the fallout input. In some situations, however, the floodplain will be cultivated and the sediments will be disturbed and in many cases mixed within the plough depth. Although it will no longer be possible to use the down-core profile, Allison et al. (1998) and Walling et al. (1998, 1999) have shown that it is still possible to estimate the sedimentation rate, if the floodplain has been regularly cultivated since the inception of fallout. If no sedimentation has occurred, will only be found to a depth equivalent to the plough depth. If, however, sedimentation has occurred, its depth will be represented by the depth to which is found below the plough depth, due to the progressive accretion of the surface. The comparison of the plough depth with the depth to the base of the profile will therefore, afford a means of estimating the sedimentation rate, viz.:

where: time elapsed (yr) since the beginning of significant fallout and the collection of the sediment core. The second approach to estimating the mean sedimentation rate for a sediment core is based on a single measurement of the total inventory for the core. This value is in turn used to estimate the excess inventory defined as the total inventory less the estimated local direct atmospheric fallout inventory The latter can be established using cores collected from adjacent areas of stable, undisturbed grassland above the level of inundating floodwater. The excess inventory represents the input associated with deposited sediment and its magnitude will, therefore, reflect the rate of sediment deposition and the concentration in the deposited sediment. The latter will have varied through time in response to the temporal pattern of fallout, its accumulation within catchment soils and its subsequent remobilization by erosion. Walling and He (1997) reported the use of a model to represent this value and, thereby, estimate the mean sedimentation rate. A simpler approach involves the assumption that, in relative terms, temporal variation of the concentration in deposited sediment will have been similar across the floodplain surface and that the main factor giving rise to spatial variation in the content of deposited sediment will be its grain-size

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composition. If the sedimentation rate and excess inventory are known for a specific reference point on the floodplain (for example, from a well defined profile obtained from a sectioned sediment core) the sedimentation rate at other points on the floodplain can be estimated from a comparison of the values of excess inventory and the grain-size composition of the sediment at those points with that of sediment from the reference point, i.e.

where: and the specific surface area of surface sediment from the reference point and the measurement point, respectively v = a constant reflecting the relationship between concentration and specific surface area, which has been shown by He and Walling (1996) to have a value of ca. 0.65 to 0.7. It is important to include the second term in Eq. 7.52 and, therefore, the comparison of the specific surface area of surface sediment from the two sampling points, since, in addition to the deposition rate, the magnitude of the inventory will also be influenced by the grain-size composition of the sediment. It is well known that the content of sediment from a common source will usually increase as its grain size decreases (cf. He and Walling, 1996). Use of the specific surface area of surface sediment assumes that this is representative of sediment from the entire depth of the core and this is likely to be valid for most over-bank deposits. This second approach is also applicable to cultivated floodplain surfaces, where cultivation should not greatly influence the magnitude of the inventory, although tillage will itself serve to redistribute the floodplain sediment horizontally and may, therefore, smooth any spatial variation in sedimentation rate. However, the potential for winnowing of fines from cultivated areas by wind erosion must also be recognized. For cultivated floodplains, the value of for the reference point will be based on Eq. 7.51 rather than Eq. 7.50. A key factor in assessing the relative merits of the two approaches for estimating floodplain-sedimentation rates from measurements outlined above is the number of laboratory measurements required. In order to define the profile, it is necessary to section the core into depth increments and to analyse each increment for its content. In view of the lengthy count times involved, it may, therefore, only be possible to analyse a small number of cores and this will necessarily limit the potential for studying spatial patterns of floodplain sedimentation. In contrast, the use of total inventory values involves only a single analysis of the bulk core and it is, therefore, possible to assemble information for a greater number of points on a floodplain and to document the spatial variability of sedimentation rates across a floodplain. In practice, a combination of the two approaches will frequently be used, since the deposition rate derived from a sectioned core can be used as a reference

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value to estimate the deposition rates for a large number of bulk cores collected from the adjacent area using Eq. 7.52. The above discussion of the use of measurements to estimate rates of overbank deposition on river floodplains relates to situations where the presence of radiocaesium in floodplain sediments reflects the input of bomb-derived from the mid 1950s to the 1970s. In some areas of Europe and adjacent regions, the Chernobyl accident in 1986 will have provided additional inputs of fallout (see De Cort et al., 1998). In most areas, the additional inventory associated with the Chernobyl input will be significantly less than the pre-existing bomb-derived inventory, but, in some locations, the Chernobyl input is two orders of magnitude or more greater than the bomb-fallout input (cf. Walling et al., 2000). Although the presence of Chernobyl-derived will complicate the interpretation of depth profiles and inventories, it can also afford increased potential for establishing the chronology of floodplain deposits. In the case of the depth profile, the existence of a second well defined fallout input in 1986 will frequently be clearly apparent in the profile, and this can afford a basis for establishing the depth of both the 1963 and the 1986 surfaces and, thus, deposition rates over the period 1963 to 1986 and 1986 to the present. Comparison of the two deposition rates would afford valuable information on changes in sedimentation rates over the recent past. The values of total inventory obtained for individual cores containing bomb- and Chernobyl-derived radiocaesium will reflect both sources of radiocaesium, but, since the basic positive relationship between the magnitude of the excess inventory and the deposition rate will apply to bomb-derived and Chernobyl fallout, and if it can be assumed that the spatial pattern of deposition across the floodplain has not changed significantly since 1963, it should again be possible to estimate deposition rates by relating the excess inventories for individual cores to that for a core where the total depth of sedimentation since 1963 has been established from the depth profile, using Eq. 7.52.

7.7. DATING SEDIMENT RECORDS Critical to studies of sediment records of erosion and siltation in lakes and reservoirs is a reliable means for dating the sediments. The principal method for achieving this on time-scales spanning the past 100 to 150 years is by a naturally occurring radionuclide of lead, formed by the radioactive decay of Both radionuclides are members of the decay series, the relevant sections of which are shown in Fig. 7.8.

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Disequilibrium between and arises through displacement of the intermediate gaseous radionuclide A fraction of the atoms produced by the decay of in soils diffuses through the soil into the atmosphere where it decays through a series of short-lived radionuclides to This is removed from the atmosphere by precipitation or dry deposition, falling onto the land surface or into lakes and oceans. falling directly into lakes is scavenged from the water column and deposited on the bed of the lake with the sediments. The total activity in sediments has two components: supported which derives from in situ decay of the parent radionuclide and unsupported which derives from this atmospheric flux. Supported activity is determined from measurements of the in situ Since sediments are highly saturated, only a very small fraction of the produced by decay in sediments escapes to the overlying water column (Appleby and Oldfield, 1992). In consequence, the and supported can usually be regarded as being in radioactive equilibrium. Unsupported is determined by subtracting supported activity from the measured total activity

Sediments on the bed of the lake containing atmospherically delivered unsupported Pb from a given year are isolated from further inputs by the overlying deposits laid down in succeeding years. The initial unsupported activity in the sample declines exponentially with time in accordance with the radioactive decay law 210

where: the radioactive decay constant t = the number of years since burial. By measuring the present-day activity of the sample this equation can be used to calculate the sediment age t provided there is a means for estimating its initial activity. Procedures for making this estimate are unequivocal at sites where sedimentation rates have been constant. Sites where sedimentation rates have varied present greater problems. Procedures for both situations are presented here, starting from the simpler case.

7.7.1. Lakes With Constant Sediment Accumulation Rates In lakes where the erosive processes in the catchment and production rates in the water column are steady, giving rise to constant rates of accumulation of sediment (measured as dry mass), it may be supposed that each layer of sediment has the same initial unsupported activity. If denotes the cumulative dry mass of

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sediment above a sample of depth x cm beneath the sediment-water interface, the age of the sample at this depth will be

where: r = the dry mass sedimentation rate The parameter m, calculated from the dry bulk density data (see Appendix A at the end of the chapter), is an alternative measure of depth in the core, and has the advantage of being independent of the degree of sediment compaction. Combining Eqq. 7.54 and 7.55, the unsupported activity will, in this case, decline exponentially with depth in accordance with the formula

where: C(m) and C(0) = the unsupported of the core.

concentrations at depth m, and at the surface

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When plotted against m on a logarithmic scale, the resulting activity versus depth profile will appear linear. The mean sedimentation rate r can be determined from the slope of the graph using a least-squares fit procedure. This method is illustrated in the results from Loch Maree, United Kingdom (Bennion et al., 2001), shown in Fig. 7.9. The unsupported activity versus depth relation is closely approximated by an exponential relation, indicating uniform accumulation over a period of more than a century. The slope of the regression line was giving a mean sedimentation rate of

7.7.2. Lakes With Variable Sediment Accumulation Rates In view of the extensive anthropogenically driven environmental changes that have taken place over the past 150 years, rates of erosion and sediment accumulation are likely to have varied significantly at many sites during this period. Where this has occurred, unsupported activity will vary with depth in a more complicated way and profiles (plotted logarithmically) will be non-linear. Figure 7.10 shows examples from two sites, Tunnel End Reservoir (United Kingdom), and Lake Sidi Ali (Morocco). Two relatively simple models, commonly referred to as the CRS and CIC models (Appleby and Oldfield, 1978; Robbins, 1978), have been proposed for calculating dates with variable sedimentation rates.

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7.7.2.1. CRS 210Pb Dating Model The CRS (constant rate of supply) model is perhaps the most widely used. The basic assumption of this model is that the rate of supply of fallout to the core site is constant, reflecting the constant flux of from the atmosphere. The initial concentration in any sediment layer will thus vary in inverse proportion to the sedimentation rate. This is exemplified by results from three Finnish lakes with annually laminated sediments (Appleby et al., 1979). Cores from each of these lakes contained sediment layers recording dilution of fallout by increased sedimentation. dates for these cores calculated using the CRS model were in good agreement with those determined by laminae counting. If P denotes the supply of to the core site, the initial concentration in each sediment layer will be

where: r = the (dry mass) sedimentation rate. Assuming P constant, it is readily shown that if

denotes the inventory of unsupported

in the whole core, and

denotes the inventory beneath sediments of depth m and age t, then

A and A (0) are calculated by numerical integration of the concentration versus depth profile. The procedures are detailed in Appleby (2001). Note that if the activity C is measured in and the cumulative dry mass m is measured in the inventories will be measured in To convert them to they must be multiplied by 10. The dry mass sedimentation rate at time t in the past can be calculated directly using the formula:

It can alternatively be calculated as the mass increment per unit time between adjacent samples. The mean rate of supply of to the core site is given by

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The methodology developed in the original paper on dating of lake sediments (Krishnaswamy et al., 1971) assumed that in fresh waters is quickly removed from solution onto particulate matter, and that unsupported activity in sediments is essentially that due to the constant overhead fallout from the atmosphere. In practice, it is found that there are a number of other factors affecting the supply of to the lake, and its distribution within the lake. In addition to direct fallout, there may be substantial inputs of eroded soils from the catchment. Losses via the outflow may result in only a proportion of total input to the lake being transmitted through the water column to the bottom sediments. Deposits reaching the bed of the lake may be redistributed spatially by hydrological processes and sediment focussing. Nonetheless, in spite of these complexities, the CRS model has consistently given good results in a large number of cases (Binford et al., 1993; Blais et al., 1995). 7.7.2.2. CIC210Pb Dating Model The CIC (constant initial concentration) model assumes that sediments in the core all had the same initial unsupported concentration at the time they were laid down on the bed of the lake, regardless of differences in the sedimentation rate. In this case, the initial concentration in the sediments of depth m and age t is given by the present concentration C (0) of sediments at the sediment/water interface. By measuring the present-day concentration C of the sediments at depth m, the age t of sediments at this depth can be calculated using the formula

An implicit assumption of this model is that the supply rate at the core site is proportional to the sedimentation rate. Although the weight of evidence suggests that this is not generally the case, it is sometimes realized at sites where primary sedimentation rates have been constant and the core site has been impacted, e.g. by episodic slump events or changes in the pattern of sediment focussing. 7.7.2.3. Model Validation The CRS and CIC models give the same results at sites with constant sedimentation rates. At sites where sedimentation rates have increased, CRS model dates will generally be older than those give by the CIC model. At sites where they have decreased, the CRS model dates will be younger. In deciding which model to use, consideration must also be given to the possibility that non-linearities in the record may be due to a number of other processes such as mixing of the superficial

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sediments by physical, biological, or chemical processes, or interruptions to the normal process of sediment accumulation caused by in-wash or slump events. For reliable dating, each case must be assessed for the dominant mechanism and dates calculated according to a suitable model. There are a number of ways of assessing the consistency of the data with a particular model (Appleby and Oldfield, 1983; Oldfied and Appleby, 1984). Centra-indications to the use of the CRS model are supply rates (Eq. 7.59) that are excessively high or excessively low compared to the atmospheric flux. Contra-indications to the use of the CIC model are non-monotonic variations in the concentration versus depth profile. Such features necessarily indicate changes in the initial concentration. Well resolved features in the profile preclude sediment mixing. In-wash or slump events may be indicated by abrupt changes of concentration.

Where there are substantial disagreements in dates given by the CRS and CIC models, records of artificial radionuclides such as and caused by fallout from the atmospheric testing of nuclear weapons can provide an invaluable independent means for resolving any differences. Global fallout of debris from the

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weapons tests began in 1954, and reached a peak in 1963. Where sediments have preserved accurate records of these events, the corresponding depths may be readily identified and dated accordingly. In many parts of Europe, the 1986 depth can also be identified from sediment records of fallout from the Chernobyl reactor accident. By using or stratigraphic evidence in combination with it is often possible to date the recent sediment record with a high degree of accuracy, especially for sediments spanning the past 50 years. In many cases it is found that the dominant processes controlling the supply of fallout to the core site are consistent with one or other of the simple models. Where this is not the case, composite models such as those described in Appleby (1998, 2001) may be used. Figure 7.1 la shows the and records in a sediment core from Carlingwark Loch in Galloway, south-west Scotland (Bennion et al., 2001). Well resolved peaks at 16 cm and 50 cm identify the depths corresponding to 1986 and 1963. Identification of the deeper peak with the weapons fallout maximum is confirmed by its coincidence with a small peak (Appleby et al., 1991). Figure 7.11b compares the CRS model dates with those determined from the record. Also shown is the chronology calculated using a composite model to resolve discrepancies between these two independent methods.

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7.7.2.4. Dating Multi-Cores In those studies where several cores from a lake have been assayed for the reliability of dating can be enhanced by combining data from the suite of cores and regarding them as a single composite core representing a much larger area of the lake. Since sediment focussing does redistribute sediments spatially, the basic CRS model assumption of a constant rate of supply of although not valid for a single site, may be valid on this larger scale. To implement this, it is first necessary to establish a reliable correlation between the cores, based on physical, geochemical, radiometric, or magnetic stratigraphic features. Then if is a depth parameter, which identifies synchronous levels in different cores, and . is the unsupported inventory beneath the entire sediment layer identified by this parameter, the age t of this layer is given by the equation

The values of and are calculated by summing the corresponding inventories of the individual cores, weighted by the areas they represent. The use of this method is exemplified in Oldfield et al. (1980). 7.7.3. Case Studies 7.7.3.1. Sediment Records of the Impact of Afforestation on Soil Erosion in Galloway, United Kingdom One-metre-long sediment cores from the deepest points in seven lochs in Galloway, Scotland (Batterbee et al., 1985) were used in a qualitative study of the historical impact of afforestation programs on soil erosion. The cores were collected using a Mackereth mini-corer (Mackereth, 1969), extruded vertically and sliced at 0.5 cm or 1 cm intervals. Dried sub-samples were analysed for and and dates calculated using the CIC and CRS models. At three sites with undisturbed catchments (Lochs Enoch, Valley, and Glenhead), equilibrium between and the supporting equilibrium, corresponding to ca. 150 years accumulation, was reached at depths of between 20 to 35 cm. The decline in unsupported activity with depth closely followed an exponential relation, and both dating models indicated little net change in sedimentation rates during this period. In contrast, records in cores from the four sites with recently afforested catchments (Skerrow, Grannoch, Dee, and Fleet) all showed evidence of substantial disturbances dating from the time of planting. Non-monotonic features in the sediment records were attributed to substantial inputs of catchment soils caused by ploughing. At these sites, equilibrium was not reached until depths of between 40 and 100 cm.

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7.7.3.2. Historical reconstruction of catchment erosion rates from sediment records in two sites in Warwickshire, United Kingdom Foster et al. (1985, 1986) used multi-core studies of sediment records to make quantitative historical reconstructions of net soil losses by erosion in the catchments of Merevale Lake and Seeswood Pool in Warwickshire, United Kingdom. In the Merevale study, a total of eighty-one sediment cores were retrieved at points on a 25 × 25 m grid over a period of 5 days using a modified Mackereth corer operated from a dinghy. At Seeswood Pool, cores were retrieved from thirty-one locations, mainly on a 50 × 50 m grid. The depths of sediment recovered varied from less than 10 cm at many marginal sites to as much as 100 cm in some of the deeper parts of the lakes.

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Coring positions were identified from fixed ground stations by intersecting compass bearings. The cores were extruded vertically at 1-cm intervals and ovendried at 50°C. Sub-samples from each slice were transferred to 10-mL pots for magnetic measurements. Sediments from two cores in each lake were analysed for and dates for these cores calculated using the CRS and CIC models were transferred to the undated cores using core correlations determined from the magnetic measurements. From the results the spatial distributions of sedimentation in each lake were calculated for each of a number of different time periods. Figure 7.12 compares the patterns of sediment accumulation in Seeswood Pool during the periods 1926 to 1933 and 1978 to 1983 (Foster et al., 1986). Planimetric methods were used to calculate the total annual dry mass of sediment accumulating in each lake for each time period. Yields in terms of soil loss from each catchment (following corrections for autochthonous sedimentation) are shown in Fig. 7.13. 7.8. REFERENCES Allison, M. A., Kuehl S. A., Martin T. C., & Hassan A. (1998). Importance of flood-plain sedimentation for river sediment budgets and terrigenous input to the oceans: Insights from the BrahmaputraJamuna river. Geology, 26, 175–178. Appleby, P. G. (1998). Dating recent sediments by210 Pb: Problems and solutions. In Proceedings of the 2nd NKS/EKO-1 Seminar, Helsinki, 2–4 April 1997 (pp. 7–24). Helsinki: Finnish Radiation and Nuclear Safety Authority (STUK).

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Appleby, P. G. (2001). Chronostratigraphic techniques in recent sediments. In W. M. Last and J. P. Smol (Eds.), Tracking enivironmental change using lake sediments,volume 1: Basin analysis, coring, and chronological techniques (pp. 171–203). Dordrecht: Kluwer Academic Publishers. Appleby, P. G., & Oldfield, F. (1978). The calculation of dates assuming a constant rate of supply of unsupported to the sediment. Catena, 5, 1–8. Appleby, P. G., & Oldfield, F. (1983). The assessment of data from sites with varying sediment accumulation rates. Hydrobiologia, 103, 29–35. Appleby, P. G., & Oldfield, F. (1992). Application of to sedimentation studies. In M. Ivanovich and R. S. Harmon (Eds.), Uranium series disequilibrium (pp. 731–778). Oxford: Oxford University Press. Appleby, P. G., Oldfield, F., Thompson, R., Huttenen, P., & Tolonen, K. (1979). 210 Pb dating of annually laminated lake sediments from Finland. Nature, 280, 53–55. Appleby, P. G., Richardson, N., & Nolan, P. J. (1991). dating of lake sediments. Hydrobiologia, 214, 35–42. Bachhuber, H., Bunzl, K., & Schimmack, W. (1982). The migration of and in multilayered soils: results from batch, column, and fallout investigations. Nuclear Technology, 59, 291–301. Batterbee, R. W., Appleby, P.G., Odell, K., & Flower, R. J. (1985). dating of Scottish lake sediments, afforestation and accelerated soil erosion. Earth Surface Processes and Landforms, 10, 137–142. Bennion, H., Fluin, J., Appleby, P. G., & Ferrier, B. (2001). Palaeolimnological investigation of Scottish freshwater lochs. Scotland and Northern Ireland forum for environmental research, ENSIS report No. SR(00)02 F. London: University College. Binford, M. W., Kahl, J. S., & Norton, S. A. (1993). Interpretation of profiles and verification of the CRS dating model in the PIRLA project lake sediment cores. Journal of Paleolimnology, 9, 275– 296. Blais, J. M., Kalff, J., Cornett, R. J., & Evans, R. D. (1995). Evaluation of dating in lake sediments using slable Pb, Ambrosia pollen, and Journal of Paleolimnology, 13, 169–178. Brown, R. B., Cutshall, N.H., & Kling, G.F. (1981a). Agricultural erosion indicated by redistribution: I. Levels and distribution of activity in soils. Soil Science Society of America Journal, 45, 1184–1190 Brown, R. B., Kling, G. F., & Cutshall, N. H. (1981b). Agricultural erosion indicated by redislribution.: II. Estimates of erosion rates. Soil Science Society of America Journal, 45, 1191– 1197. Cambray, R. S., Playford, K., & Carpenter, R.C. (1989). Radioactive fallout in air and rain: results to the end of 1988. UK Atomic Energy Authority report AERE–R 10155. London: HMSO. De Cort, M., Dubois, G., Fridman, S. D., Germenchuk, M. G., Israel, Y. A., Janssens, A., Jones, A. R., Kelly, G. N., Kvasnikova, E. V., Matveenko, I. I., Nazarov, I. M., Pokumeiko, Y.M., Sitak, V. A., Stukin, E. D., Tabachny, L. Y., Tasturov, S. Y., & Avdyushin, S. I. (1998). Atlas of caesium deposition on Europe after the Chernobyl accident, EUR 16733. Brussels-Luxembourg: ECSC-EECEAEC. de Jong, E., Begg, C. M., & Kachanoski, R. G. (1983). Estimates of soil erosion and deposition from Saskatchewan soils. Canadian Journal of Soil Science, 63, 607–617. Elliott, G. L., Campbell, B. L., & Loughran. R. J. (1990). Correlalion of erosion measurements and soil caesium-137 content. International Journal of Radiation and Applied Instrumentation (A) Applied Radiation and Isotopes, 41, 713–717. Ely, L. L, Webb, R. H., & Enzel, Y. (1992). Accuracy of post-bomb and C-14 in dating fluvial deposits. Quaternary Research, 38, 196–204. Foster, D. L, Dearing, J. A., & Appleby, P. G. (1986). Historical trends in sediment yields: a case study in reconstruction from lake-sediment records in Warwickshire, U.K. Hydrological Sciences, 31, 327– 443. Foster, I. D. L., Dearing, J. A., Simpson, A., Carter, A.D., & Appleby, P. G. (1985). Lake catchment based studies of erosion and dunudation in the Merevale catchment, Warwickshire, U.K. Earth Surface Processes and Landforms, 10, 45–68. Fredericks, D. J., & Perrens, S. J. (1988). Estimating erosion using caesium-137: II Estimating rates of soil loss. IAHS publication 174 (pp. 225–231). Wallingford: IAHS Press.

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Govers, G., Quine, T.A., Desmet, P..J., & Walling, D. E. (1996). The relative contribution of soil tillage and overland flow erosion to soil redistribution on agricultural land. Earth Surface Processes mill Landforms, 21, 929–946. Govers, G., Vandaele, K., Desmet, P. J., Poesen, J., & Bunte K. (1994). The role of tillage in soil 210 on hill slopes. European Journal of Soil Science, 45, 469–478. redistribution He, Q., & Walling, D. E. (1996). Interpreting the particle size effect in the adsorption of and unsupported pb by mineral soils and sediments. Journal of Environmental Radiactivily, 30, 117– 137. He, Q., & Walling, D. E. (1997). The distribution of fallout 137 Cs and 210 Pb in undisturbed and cultivated soils. Applied Radiation and Isotopes, 48, 677–690. Kachanoski, R. G. (1987). Comparison of measured soil 137-cesium losses and erosion rates. Canadian Journal of Soil Science, 67, 199–203. Kachanoski, R. G. (1993). Estimating soil loss from changes in soil cesium-137. Canadian Journal of Soil Science, 73, 515–526. Kachanoski, R. G., & de Jong, E. (1984). Predicting the temporal relationship between soil cesium-137 and erosion rate. Journal of Environmental Quality, 13, 301–304. Knatko, V. A., Skomorokhov, A. G., Asimova, V. D., Strakh, L. I., Bogdanov, A. P., & Mironov, V. P. (1996). Characteristics of 90Sr, 137Cs, and 239,240Pu migration in undisturbed soils of Southern Belarus after the Chernobyl accident. Journal of Environmental Radiactivity, 30, 185–196. Krishnaswamy, S., Lal, D., Martin, J. M., & Meybeck, M. ( 1 9 7 1 ) . Geochronology of lake sediments. Earth Planetary Science letters, 11, 407–414. Loughran, R. C, & Campbell, B. L. (1995). The identification of catchment sediment sources. In I. D. L. Foster, A. M. Gurnell and B.W. Webb (Eds.), Sediment and water quality in river catchments (pp. 189–205). Chichester: Wiley. Loughran, R. C., Campbell, B. L., & Elliott, G. L. (1990). The calculation of net soil loss using caesium137. In J. Boardman, I. D. L. Foster and J. A. Dearing (Eds.), Soil erosion on agricultural land (pp. 119–126). Chichester: Wiley. Lowrance, R., McIntyre, S., & Lance, C. (1988). Erosion and deposition in a field/forest system estimated using cesium-137 activity. Journal of Soil and Water Conservation, 43, 195–199. Mackereth, F. J. H. (1969). A short core sampler for sub-aqueous deposits. Limnology and Oceanography, 14, 145–151. Martz, L. W., & de Jong, H. (1987). Using cesium-137 to assess the variability of net soil erosion and its association with topography in a Canadian Prairie landscape. Catena, 14, 439–451. Martz., L. W., & de Jong, E. (1991). Using cesium-137 and landform classification to develop a net soil erosion budget for a small Canadian prairie watershed. Catena 18, 289–308. McHenry, J. R., & Ritchie, J. C. (1977). Physical and chemical parameters affecting transport of Cs–137 in arid watersheds. Water Resources Resources, 13, 923–927. McHenry, J. R., Ritchie, J.C., & Verdon, J. (1976). Sedimentation rates in the upper Mississippi river. In Rivers ’76 vol II. (pp. 1339–1349). New York: ASCE. Menzel, R. G., Jung, P.-K., Ryu, K.-S., & Urn, K.-T. (1987). Estimating soil erosion losses in Korea with fallout cesium-137. Applied Radiation and Isotopes, 38, 451–454. Mitchell, J. K., Bubenzer, G. D., McHenry, J. R., & Ritchie, J. C. (1980). Soil loss estimation from fallout cesium-137 measurements. In M. DeBoodt and D. Gabriels (Eds.) Assessment of erosion (pp. 393–401). Chichester: Wiley. Oldfield, F., & Appleby, P. G. (1984). Empirical testing of dating models. In E. Y. Haworth and J. G.Lund (Eds.), Lake sediments and environmental history (pp. 93–124. Leicester: Leicester University Press. Oldfield, F., Appleby, P.G., & Thompson, R. (1980). Palaeoecological studies of lakes in the Highlands of Papua New Guinea. I. The chronology of sedimentation. Journal of Ecology, 68, 457–477. Pegoyev, A. N., & Fridman, S. D. (1978). Vertical profiles of cesium-137 in soils (English translation). Pochvovetleniye 8, 77–81. Popp, C. L., Hawley, J.W., Love, D. W., & Dehn, M. (1988). Use of radiomclric (Cs-137, Pb-210), geomorphic and stratigraphic techniques to date recent oxbow sediments in the Rio Puerco drainage. Grants Uranium region, New Mexico. Environmental Geology and Water Science, 11, 253–269.

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Porto, P., Walling, D. E., & Ferro, V. (2001). Validating the use of caesium-137 measurements to estimate soil erosion rates in a small drainage basin in Calabria, Southern Italy. Journal of Hydrology, 248, 93–108. Quine, T. A. (1989). Use of a simple model to estimate rates of soil erosion from caesium-137 data. Journal of Water Resources, 8, 54–81. Quine, T. A. (1995). Estimation of erosion rates from the caesium-137 data: the calibration question. In I. D. L. Foster, A. M. Gurnell and B. W. Webb (Eds.), Sediment and water quality in river catchments (pp. 307–330). Chichester: Wiley. Quine, T. A., Walling, D.E., & Govers, G. (1996). Simulation of radiocaesium redistribution on cultivated hillslopes using a mass-balance model: an aid to process interpretation and erosion rates estimation. In M. G. Anderson and S. M. Brooks (Eds.), Advances in hillslope processes (pp. 561– 588). Chichester: Wiley. Reynolds, W. D., Gillham, R. W., & Cherry, J. A. (1982). Evaluation of distribution coefficients for the prediction of strontium and cesium migration in a uniform sand. Canadian Geotechnology Journal, 19, 92–103. Ritchie, J. C., Hawks, P. H., & McHenry, J. R. (1975). Deposition rates in valleys determined using fallout cesium-137. Geological Society of America Bulletin, 86, 1128–1130. Ritchie, J. C., & McHenry, J. R. (1975). Fallout Cs-137: a tool in conservation research. Journal of Soil and Water Conservation, 30, 283–286. Robbins, J. A. (1978). Geoehemical and geophysical applications of radioactive lead. In J. O. Nriagu (Ed.), Biogeochemistry of lead in the environment (pp. 285–393). Amsterdam: Elsevier Scientific. Vanden Berghe, I., & Gulinck, H. (1987). Fallout 137Cs as tracers for soil mobility in the landscape framework of the Belgian loamy region. Pedologie, 37, 5–20. Walling, D. E. (1998). Use of and other fallout radionuclides in soil erosion investigations: progress, problems and prospects. In Use of 137Cs in the study of soil erosion and sedimentation, IAEA-TECDOC-1028 (pp. 39–62). Vienna: IAEA. Walling, D. E., Golosov, V. N., Panin, A. V., & He, Q. (2000). Use of radiocaesium to investigate erosion and sedimentation in areas high levels of Chernobyl fallout. In I. D. L. Foster (Ed.), Tracers in geomorphology (pp. 291–308). Chichester: Wiley. Walling, D. E., & He, Q. (1992). Interpretation of caesium-137 profiles in lacustrine and other sediments: the role of catchment-derived inputs. Hydrobiologia, 235/236, 219–230. Walling, D. E., & He, Q. (1993). Towards improved interpretation of caesium-137 profile in lake sediments. In J. McManus and R. Duck (Eds.), Geomorphology and sedimentology of lakes and reservoirs (pp. 31–53). Chichester: Wiley. Walling, D. E. & He, Q. (1997). Use of fallout in investigations of overbank deposition on river floodplains. Catena, 29, 263–282. Walling, D, E., & He, Q. (1999). Improved models for estimating soil erosion rates from cesium-137 measurements. Journal of Environmental Quality, 28, 611–622. Walling, D. E., & He, Q. (2001). Models for converting 137Cs measurements to estimates of soil redistribution rates on cultivated and undisturbed soils (including software for model implementation). Report to IAEA. Exeter: University of Exeter. Walling, D. E., He, Q., & Blake, W. (1999). Use of and measurements to document short- and medium-term rates of water-induced soil erosion on agricultural land. Water Resources Research, 35, 3865–3874. Walling, D. E., He, Q., & Quine, T. A. (1995). Use of caesium-137 and lead-210 as tracers in soil erosion investigations. IAHS publication 229 (pp. 163–172). Wallingford: IAHS Press. Walling, D. E., Owens, P. N., & Locks, G. J. L. (1998). The role of channel and floodplain storage in the suspended sediment budget of the River Ouse, Yorkshire, UK. Geomorphology, 22, 225–242. Walling, D. E., Owens, P. N., & and Leeks, G. J. L. (1999). Rates of contemporary overbank sedimentation and sediment storage on the floodplains of the main channel systems of the Yorkshire Ouse and River Tweed, UK. Hydrological Processes, 13, 993–1009. Walling, D. E., & Quine, T. A. (1990). Calibration of caesium-137 measurements to provide quantitative erosion rate data. Land Degradation and Rehabilitation, 2, 161–175. Walling, D. E., & Quine, T. A. (1992). The use of caesium-137 measurement in soil erosion surveys, IAHS publication 210 (pp. 143–152). Wallingford: IAHS Press.

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Walling, D. E., & Quine, T. A. (1993). Use of caesium-137 as a tracer of erosion and sedimentation: Handbook for the application of the caesium-137 technique. Exeter: University of Exeter. Walling, D. E., & Quine, T. A. (1995). The use of fallout radionuclides in soil erosion investigations. In Nuclear techniques in soil-plant studies for sustainable agriculture and environmental preservation, IAEA Publication ST1/PUB/947 (pp. 598–619). Vienna: IAEA. Yang, H., Du, M. Chang, Q. Minami, K., & Hatta, T. (1998.) Quantitative model for estimating soil erosion rates using Pedosphere, 8, 211–220. Yang, H., Du, M., Zhao, Q., Minami, K., & Hatta, T. (2000). A quantitative model for estimating mean annual soil loss in cultivated land using measurements. Soil Science and Plant Nutrition, 46, 69–79. Zhang, X. B., Higgitt, D.L., & Walling, D. E. (1990). A preliminary assessment of the potential for using caesium-137 to estimate rates of soil erosion in the Loess Plateau of China. Hydrological Science Journal, 35, 267–276.

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7.1.A. APPENDIX 7.1.1.A. Calculation of dry bulk density and cumulative dry mass in sediment cores Accurate determination of the dry bulk density of each sediment layer is essential both to reliable dating and to calculations of sediment accumulation rates. Sediment density is characterized by a number of parameters: wet bulk density

dry bulk density

dry-weight fraction

water content

solids density Only two of these parameters are independent. Any two are sufficient to calculate the remaining three. The simplest to determine, and usually the most reliable, is the dryweight fraction F, or, equivalently, the water content W. The wet bulk density is determined by weighing a known volume of wet sediment. This is done in two ways: by transferring a sub-sample of wet sediment to a small pre-weighed cuboid sample holder of accurately known volume; by weighing the whole section in the original sample holder. The latter method requires that losses during sectioning be kept to a minimum. Given the dry-weight fraction and wet bulk density, the dry bulk density is calculated using the formula

The density of the dry solids in the sediment is

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where: the density of water. In most sediments, the value of is typically though it may be a little lower in organic sediments. The water density can be taken to be Where the calculated value of is significantly different from 2.5, it may be more accurate to calculate the dry bulk density using the formula

with a nominal value for of In most cases, the dry bulk density will be significantly higher in deeper sediments than in the superficial layers, largely due to compression by the weight of later deposits. In consequence, volumetric sedimentation rates (measured in do not give a true measure of sediment yield. For mass-balance calculations, it is more appropriate to measure depths and sedimentation rates in terms of dry mass of sediment. The depth of a sediment sample of depth x cm beneath the sediment/water interface, measured in terms of cumulative dry mass, is given by

If the dry bulk density is measured in the cumulative dry mass m will be expressed in The value of m for each sample depth is calculated by numerical integration of with respect to the linear depth x. For details, see Appleby (2001). If m(t) denotes the depth (in these terms) of sediments of age t, the (dry mass) sedimentation rate is

CHAPTER 8 SPECIAL CONSIDERATIONS FOR AREAS AFFECTED BY CHERNOBYL FALLOUT V.N. GOLOSOV Laboratory for Soil Erosion and Fluvial Processes, Faculty of Geography, Moscow State University, Moscow 119899, Russian Federation

8.1 INTRODUCTION In this chapter, the implications, advantages and limitations associated with additional input of Chernobyl-derived are discussed. It is shown that its vertical migration is similar to that of bomb-derived fallout. However, the Chernobyl-derived is characterized by high spatial variation. Additional requirements for the selection of an ideal study site and the collection of samples for the establishment of reference inventories are described. Possible approaches for the application of the technique for estimating soil redistribution (loss/gain) and for sedimentation and sediment-budget studies in areas affected with various levels of Chernobyl contamination are examined. 8.2. CHERNOBYL-DERIVED CAESIUM-137: ITS DISTRIBUTION AND BEHAVIOUR 8.2.1. Specificity of Chernobyl-Derived

Deposition

An RMBK 1000 reactor at the Chernobyl Nuclear Power Plant in the former USSR (now the Ukraine) exploded on 26 April 1986. As a result of this accident, about 85 PBq of were released into the atmosphere (Devell et al., 1995). Of this, the largest fraction, i.e. about 64 PBq of Chernobyl was deposited over continental Europe (de Cort et al., 1998) and the rest fell mainly on European water bodies. Some fallout was transported beyond the air masses above Europe and deposited on other continents and oceans. Chernobyl- and bomb-derived fallout differed mainly in terms of the altitude of transport. Contaminated clouds were transported from Chernobyl within the lower layers of the atmosphere. The radionuclides released on 26 and 27 April 1986 were transported at 700 to 1,500 m. At later stages (up to 11 May 1986), the radioactive material was released at even lower altitudes (De Cort et al., 1998). Thus, spatial distribution of Chernobyl was strongly influenced by rainfall intensity and local topography (Fridman et al., 1997). 165 F. Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 165–183. © 2002 IAEA. Printed in the Netherlands.

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Maps showing the spatial distributions of deposited on Europe from atmospheric nuclear weapons tests and/or bomb-derived fallout and from Chernobyl-derived fallout have been published by De Cort et al. (1998). Taking into consideration the levels reported in these maps, ratios of pre-Chernobyl (bomb-derived) to post-Chernobyl fallout inputs can be determined and should be taken into account for the application of the technique. According to the contamination level and the ratio of the fallouts, the following areas can be distinguished in Europe: 1) extremely high levels of Chernobyl-fallout input 2) high levels of Chernobyl-fallout input 3) relatively high levels of Chernobyl-fallout input 4) moderate levels of Chernobyl-fallout input and 5) low Chernobyl-fallout input The most-contaminated areas, i.e. with deposition levels exceeding have been studied in greater detail using various methods (airborne and ground mobile and static gamma spectrometry), thus enabling the compilation of medium-scale maps and better estimates of contamination levels (Table 8.1). For areas with deposition levels of less than the precision of the maps is much lower with the exceptions of Russia, Belarus and northwest of the Ukraine, where detailed airborne gamma spectrometry surveys were made. They show the general patterns of deposition, which, in fact may, be different from actual levels of contamination in the studied catchment area.

AREAS AFFECTED BY CHERNOBYL FALLOUT 8.2.2. Depth Distribution of Chernobyl-Derived Cultivated Sites

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Within Undisturbed and

The vertical migration of Chernobyl fallout in typical soil profiles from undisturbed reference locations was usually very limited (Fig. 8.1).

In most cases, most of the inventory was found in the top 3 cm of the profile, with relatively little below 10 cm (Bakunov and Arkhipov, 1995). However, some downward displacement of the maximum peak was observed in peat and silty soils (Haak and Rydberg, 1998). This may reflect weak sorption of radiocaesium in

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the acid peat soil and a more intensive vertical redistribution of soil particles by geochemical processes in the silty soil (Askbrant et al., 1996). The depth-incremental profiles of for depositional and adjacent reference sites in areas of high Chernobyl fallout are shown in Fig. 8.2. They are similar to those reported for bomb-derived fallout and show clearly the subsurface activity peak, which represents the soil-surface level at the time of the accident (He et al., 1996; Margineanu et al., 2000).

Usually the concentrations for these peaks are similar to those found at the surface of the undisturbed reference profiles (Fig. 8.3). The reduction in concentrations towards the soil surface is likely to reflect the mixing of the plough layer and progressive reductions in inventory through erosion. In cases where the activity of the subsurface peak exceeded the activity of the undisturbed reference profile, it suggests mobility of fallout by runoff prior to adsorption by the soil, or erosion transport of radiocaesium with soil particles before the first tillage operation after the deposition. The depth distribution patterns in cultivated areas indicate that had been mixed within the plough layer by cultivation. In eroded areas, the concentrations declined to near zero immediately below the plough depth and in the deposition sites significant concentrations may be found under the plough depth, thus showing progressive accumulation. In some areas with high levels of Chernobyl contamination, where cultivation was deep (up to 40 cm) for remediation purposes during the years immediately after 1986, substantial concentrations can be found under the plough depth within eroded areas.

AREAS AFFECTED BY CHERNOBYL FALLOUT 8.2.3. Spatial Variability of Chernobyl-Derived

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Deposition

In most places, with the exception of the area around the nuclear-power plant, the Chernobyl-derived fallout was associated with a single rainfall event, or to the prevailing winds in case of dry fallout deposition. Local topography and vegetation cover can influence the microclimate and precipitation distribution over small areas, which explains high mesoscale systematic variability of Chernobyl-derived across the various regions (De Cort et al, 1998; Izrael and Soudakova, 1998; Borzilov et al., 1993). However, for correct application of the technique in studies of soil erosion and sedimentation, it is necessary to define random and systematic spatial variations in inventory within the relatively small (up to few areas that are usually selected for detailed study (Branca and Voltaggio, 1993; Golosov et al., 1999a). The highest random spatial variability was found within the zone around the Chernobyl plant with deposition levels of more than The activities of five samples taken from an area of showed variations of as much as 3- to 10-fold due to the presence of highly contaminated ash particles (Izrael, 1990, 1996). The random spatial variability within the plain, with contamination levels of 40 to is usually similar to that reported for bomb-derived because the Chernobyl fallout was associated with relatively intensive rains (Silant’ev and Silant’ev, 1997). In areas with such high levels of Chernobyl radionuclide contamination, pre-existing bomb-derived inventories can be disregarded (Kvasnikova et al., 1999; Golosov et al., 2000a). The magnitude of random spatial variability of the inventories of various geomorphologic units can be observed in Table 8.2 (Golosov et al., 1999a, 1999b). Although this magnitude also depends on the measurement area, the sizeable area of the in-situ measurements with a field-portable gamma detector) reduces problems caused by microscale variability (Owens and Walling, 1996; Sutherland, 1998; Golosov et al., 2000b).

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A more complex situation is found within the areas with Chernobyl contamination levels of due to the heterogeneous distribution of the precipitation (Table 8.3). In mountainous areas with such contamination level, the coefficients of variation of the inventories can reach up to 51 to 72%, probably due to surface runoff that could have occurred immediately after Chernobyl fallout (Alberts et al., 1998; Velasco et al., 1997).

The areas with Chernobyl-contamination levels of 1 to are characterized by overlapping of the Chernobyl-derived fallout and the bombderived redistribution already transformed by various processes. A wide range of random spatial variability may be found depending on the specific local position in the landscape. Table 8.4 shows that Chernobyl-derived fallout may cover the previously formed bomb-derived redistribution, partly masking it within different geomorphologic units of cultivated slopes. In these areas, the recently Chernobyl-derived and bomb-derived fallout cannot be distinguished, except in uncultivated deposition units.

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Additional fallout inputs of Chernobyl-derived of less than did not significantly change the random spatial variability bomb-derived (Sogon et al., 1999). In such areas the coefficients of variation were similar (Bernard et al., 1998) to those for bomb-derived (Sutherland, 1996). However, the pattern of sediment redistribution estimated from the spatial distribution of bomb-derived activity can be modified because of the irregularity of additional Chernobyl fallout inputs. It is, therefore, advisable to calculate soil redistribution based on the loss/gain data for each of the different geomorphologic units, rather than independently on the loss/gain data for each sampling point. The systematic spatial variability of Chernobyl-derived fallout inputs usually reflects variations in rainfall amount, vegetation cover, and soil type, as well as spatial variability in the physical and chemical properties of the contaminated soil particles (Bunzl et al., 1989). Medium-scale maps of radionuclide contamination, which were produced for some areas with high levels of Chernobyl contamination, can provide a basis for identifying mesoscale systematic variability across the local region (De Cort et al., 1998). It is, therefore, necessary to identify the systematic spatial variability of the area to be selected for detailed study. Areas with Chernobyl contamination levels exceeding usually showed very high systematic spatial variability over the whole region (De Cort et al., 1998; Bonnett et al., 1989) and also in individual catchments (Table 8.5). This may be explained by the interaction of air masses (wind direction and velocity, intensity and structure of rain, altitude above ground) and topographic characteristics of relief, including forest and soil conditions.

Some additional inputs to the spatial variability of Chernobyl-derived redistribution may be related to overland flow and soil erosion, which may have occurred simultaneously with the fallout or before the next tillage cycle (Fig. 8.3). In some cases, however, it is possible to define a relationship for the Chernobylfallout inputs in the study area, with the altitude for instance, as shown in Fig. 8.4 (Golosov et al., 1999a). Such systematic variation in the initial should be taken into account in any attempt to estimate rates of soil redistribution within a studied slope or catchment (Panin et al., 2001).

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In areas with Chernobyl contamination levels of 1 to local systematic spatial variability depends mainly on the type of Chernobyl fallout (wet or dry deposition). Areas affected by dry deposition will have a relatively more uniform pattern. Local systematic variability cannot be assessed in areas with Chernobyl contamination levels of less than

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8.3. SELECTION OF THE STUDY AREA Special care should be taken in the selection of the study area, due to the high spatial variability of Chernobyl-derived fallout mentioned above. In addition to the considerations described for site selection in areas with bomb-derived fallout (see Chapter 2), the following should be taken into account for the selection of an ideal site: 1) location close to a meteorological station(s); 2) information is available on land use and management (crop rotation and tillage system) and field configuration, from spring 1986; 3) sites are present around the area that are suitable for establishing a reference inventory (see selection of reference sites in Chapter 2); 4) eroded and undisturbed depositional units are present, preferably with small reservoirs along pathways from the studied cultivated slope to the river channel. Meteorological data for precipitation (intensity and quantity) and wind (speed and direction) from 26 April to 15 May 1986 should be used to make a preliminary assessment of prevailing meteorological conditions for deposition of Chernobylderived fallout within the local landscape. The spatial variability of Chernobyl fallout along the slope may be low if the rains were of relatively uniform intensity and the wind velocity was close to zero. However, a final decision about the local spatial variability can be made only after measuring the inventories in samples taken from several potential reference sites located around the study area. The variability of the reference inventories should meet the requirements established in Chapter 2 for bomb-derived fallout or show a systematic trend of increased fallout inputs as presented in Fig. 8.5. This should be taken into consideration for calculating the soil redistribution, as described later.

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If the variability of the reference inventories is too high and irregular, it will not be possible to calculate soil redistribution using the conversion (calibration) models. However, other approaches are available for estimating soil redistribution (see Sections 8.4 and 8.5). The information on land use and management of the study area during deposition of Chernobyl fallout and up to the time of first tillage operation, combined with the meteorological data on rainfall intensity, should be utilized for assessing the potential of redistribution by erosion. The intensity of a possible erosion event within the studied site can be preliminarily estimated by means of a simple erosion model (USLE, RUSLE, etc.). Independently, the occurrence of an erosion event in this period can be checked by comparing the peak values in the vertical distribution of in soil profiles from an uncultivated depositional site and a reference site adjacent to it (Golosov et al., 1998; Golosov, 2000). If the subsurface peak concentration of the depositional site exceeds the surface peak concentration of the reference site, this would indicate loss of Chernobyl-derived with water-eroded sediment before tillage. In this case, the spatial variability of Chernobyl-derived would increase in cultivated parts of the study area and, thus, it is not possible to use conversion models for calculating soil redistribution within such a site. Some other approaches can be applied to study soil redistribution through the use of technique (see Sections 8.4 and 8.5). 8.4. SOME PECULIARITIES OF USING CONVERSION MODELS FOR THE ASSESSMENT OF SOIL REDISTRIBUTION WITHIN AREAS WITH CHERNOBYL CONTAMINATION. If the selected study area meets the requirements described above, it is possible to use conversion models for the assessment of soil redistribution in territories with Chernobyl inventory levels of or Nevertheless, some limitations still exist. Thus, in areas with Chernobyl contamination in the range of 1 to the Chernobyl-derived and the bomb-derived fallouts cannot be distinguished due to their overlapping, except in reference sites and the measurements cannot provide intricate patterns of soil loss (De Roo, 1991; Higgitt et al., 1992, 1993; Kachanoski, 1987). The areas with high levels of Chernobyl fallout, i.e. levels exceeding should be grouped according to the magnitude of the ratio between Chernobyl- and bomb-derived fallout inputs. In areas with a ratio of less than 4:1 conversion models are not recommended for the assessment of soil redistribution because the bomb-derived redistribution may confer additional uncertainties. For areas greatly contaminated with Chernobyl fallout (ratio over 4:1) it is possible to set the time of fallout to May 1986. The uncertainties associated with the fate of freshly deposited prior to its incorporation into the plough layer by cultivation are substantially reduced, if it is confirmed that cultivation occurred shortly after the fallout or that erosion events did not occur during the fallout or up to first tillage operation. However, only areas (within cultivated sites) with erosion and deposition rates exceeding can be

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identified using Chernobyl fallout, because only 15 years had elapsed (Litvin et al., 1996; Walling et al., 2000a). This limitation, however, should be overcome as the elapsed time increases (Walling et al., 2000b). On another hand, several parameters required by the mass-balance model incorporating soil movement by tillage may be more easily defined for the period since 1986. If the input of tillage erosion to soil redistribution is insignificant for relatively gentle cultivated slopes, the simple mass balance or the proportional models can be used to estimate soil redistribution. If some linear trend of reference inventories along the transect has been determined for the study area, as shown in the upper part of Fig. 8.5, this should be included in the input block of the selected conversion model. As the random spatial variability may be relatively low within each geomorphological unit, it is recommended that specific reference inventories be used for the calculation of soil redistribution within the different geomorphologic units along the established trend (see lower part of Fig. 8.5) In areas with Chernobyl-derived fallout input of some conversion models can be applied without any modification for calculating soil redistribution using the technique, if the selected area meets the requirements described in Section 8.3. Chernobyl-derived input of was similar to the bomb-derived fallout input in Europe in 1964 and was even less than that in 1963 (Walling, 1998). Thus, the inclusion of this additional deposition flux I (t) in the input file of the massbalance model incorporating tillage is recommended to obtain the correct pattern of soil redistribution within the study area. However, the proportional model may be used as well for estimating sediment budgets from measurements on cultivated soils (Wicherek and Bernard, 1995; Bernard et al., 1998; Sogon et al., 1999). 8.5. USE OF CHERNOBYL-DERIVED IN SEDIMENTATION AND SEDIMENT-BUDGET STUDIES 8.5.1. Use of Chernobyl-Derived

in Sedimentation Studies

Chernobyl-derived fallout is an extremely accurate chronological marker for various undisturbed deposition sites along pathways from cultivated slopes to river channels or across the river valleys (terraces and floodplains) because the behaviour of the in the soil profile is similar to bomb-derived fallout, but its peak concentration is significantly greater (Vanden Berghe and Gulinck, 1987; Walling et al., 1992a, 1992b; Walling and Quine, 1993; Callaway et al., 1996; Rowan et al., 1993; Golosov, 1998; Golosov and Kvasnikova, 2000; Golosov and Ivanova, In press). In areas with contamination levels exceeding it is possible to make in-situ measurements of inventory at accumulation sites using a portable gamma detector when most of the inventory is contained within the upper 40 cm of the soil profile (Govorun et al., 1996; Chesnokov et al., 1997). In such cases, it is necessary first to establish the vertical distribution of at the different geomorphologic units (several levels of floodplain, different places of sediment storage along pathways from cultivated slope to the river valley, etc.).

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Because limitations exist in the study of sedimentation rates using both bomband Chernobyl-derived fallout in areas with contamination levels in the range of 1 to two possible approaches are described here to overcome them. In the first approach, the position of the peak-activity levels can be used to estimate the depth of the 1963 and 1986 surfaces (Fig. 8.6B). An overlapping of the vertical distribution curve of Chernobyl-derived with that of bomb-derived fallout may be observed in areas with Chernobyl contamination levels exceeding if the sedimentation rates before the Chernobyl accident were not sufficiently high (Fig. 8.6A). In the second approach, when the total inventory of a core from a deposition site is compared to a value representing the local inventory obtained from soil cores collected from undisturbed reference sites, the problem of systematic spatial variability of Chernobyl fallout should be taken into consideration. In this case, it is necessary to determine if there is a relationship in the initial fallout across the study site, as shown in Fig. 8.4.

8.5.2. Sediment-Budget Approach In areas with Chernobyl fallout predominates (bomb-derived contribution <25% from total inventory), a detailed study of Chernobyl-derived redistribution in the geomorphological units within cultivated fields and along pathways to the river valley can be made to establish sediment budgets and estimate mean soil erosion rates (Bogen et al., 1994; Golosov et al., 1998; Panin et al., 2001). This alternative approach can be used in areas with relatively low erosion intensity within some of the eroded units, thus the current differentiation of eroded sites in

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terms of reduced Chernobyl inventory is insufficient for using calibration models for the assessment of soil redistribution. The following three key stages can be defined for the application of this approach: i) Large-scale geomorphologic mapping of the study site, ii) Fieldsampling program and iii) Assessment of redistribution in the study site and calculation of the sediment budget. 8.5.2.1. Large-Scale Geomorphologic Mapping of the Study Site The main objective of this mapping is to divide the study area into main component morphological (topographic) units, with well defined intensity of erosion and deposition processes (Fig. 8.7). The area of each geomorphologic unit should be carefully measured.

The following main morphological elements can be typically distinguished within an agricultural catchment in terms of their roles in sediment transport, i.e.: 1) Essentially stable (reference) areas, which may be represented by flat uncultivated and cultivated interfluves (slope <1°), grassy valley slopes and valley terraces. 2) Eroded areas, which may be represented by cultivated slopes divided as units according to slope, gradient, and morphology (concave, ephemeral gully, etc.), banks, and bottom gullies. 3) Deposition areas, which may be represented by the field margins, uncultivated hollows dissected by valley sides, gully cones, ponds and dry valley bottoms.

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The latter may be also subdivided into morphological units according to deposition rates. 8.5.2.2. Sampling Strategy The field-sampling program for stable units is similar to that described for the reference sites (see Chapter 2). A minimum of ten to thirteen bulk samples should be taken within each eroded unit. Depending on the relief of the unit, a grid or individual transect systems can be used for the collection of samples (Fig. 8.7). Only one point for incremental depth sampling can be chosen in areas within each deposition unit. In addition, five to ten bulk samples should be taken in each deposition unit. Insitu measurements of inventory can be made instead of collecting bulk samples within different geomorphologic units, if the level of Chernobyl contamination is sufficiently high (see 8.5.1 above). 8.5.2.3. Assessment of Soil Redistribution at the Study Site and Calculation of Sediment Budget The total losses of soil from the eroded units per year can be estimated using the following equation:

where: total losses of soil from the eroded units per year areas of the eroded geomorphologic units mean contents for the eroded units at the time of I(t) = the initial (reference) input fallout corrected for the time of sampling (may be different for different eroded units, if some trend of initial Chernobyl fallout input was established for the study site) T= the period elapsed between the time of sampling and 1986 (yr), dimensionless particle size and organic matter correction coefficient (He and Walling, 1996), the concentration in surface soil from eroded units In areas with predominant Chernobyl fallout, the total storage of sediment within the deposition units per year can be calculated:

where: storage of sediment from the catchment per year

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areas of the deposition geomorphologic units mean contents at sampling for the deposition units the content of deposited sediment from upstream If the study catchment is a closed system (for example, a pond located in the catchment outlet), the soil losses should be equal to the sediment storage:

In this case, it is possible to check the calculation of the soil losses and even to define the inputs of the eroded units, if differences in concentration between them (for example, ephemeral gully and simple cultivated slopes) are observed (Walling and He, 1997). As a result, a detailed sediment budget for the study catchment can be established. Furthermore, these data may be used for the validation of erosion models, because the information on land use and management, meteorological and other input data are available for the site since 1986. If the study catchment is an open system, the soil losses can be more than or equal to the sediment storage:

In this case, it is possible to calculate the sediment delivery ratio coefficient for the catchment (Golosov et al., 1998). In addition, an assessment of soil losses from the catchment area is recommended using independent methods such as erosion models, soil-morphological method etc. (Golosov et al., 2000a; Panin et al., 2001). 8.5.3. Assessment of Mean Erosion Rates Using Deposition Data If the study catchment is a closed system, a more simple approach can be used for the assessment of mean erosion rates for areas affected with the Chernobyl fallout. A detailed geomorphological mapping is made within deposition units and the area of each deposition unit is measured. A detailed depth incremental sampling should be done at several points (minimum of three) along a representative cross-section within each deposition unit to document lateral variations in the sedimentation rates for the post-Chernobyl fallout period. The depth of the post-Chernobyl sediment storage is defined directly from the profile and the total volume of sediment is calculated:

where: total storage of sediment within the catchment from 1986 depth of post-Chernobyl deposition within each geomorphologic unit (m), areas of the deposition units

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Thereafter, the erosion rate is defined from the equation:

where: Y = mean annual soil loss from eroded units; density of the soil; T (yr) = time elapsed since May 1986; eroded units.

B = bulk = total area of

8.6. PERSPECTIVES OF USE OF CHERNOBYL-DERIVED FOR MONITORING STUDIES OF SOIL EROSION AND SEDIMENTATION Although the intensity of soil erosion in temperate Europe is relatively low compared to rates in other parts of the world, increasing attention is being paid to the off-site effects of soil erosion such as siltation of reservoirs and navigation channels, agrochemical pollution, euthrophication, water quality, etc., because of their significant effects economically and environmentally. Thus, clearly, there is scope to utilize the Chernobyl fallout for monitoring studies of soil redistribution, in particular sedimentation and sediment budgets and soil-associated pollutants within agricultural catchments. Such studies can be implemented using standardized protocols across regions of Europe that have received high levels of Chernobylfallout input and selected as representative of predominant agro-ecosystems. Standard data sets can be collected for monitoring purposes, model application, and development of decision-support systems. Such information would be of great value for the development of guidelines on soil- and water-conservation measures and the provision of national, regional, and international policies for sustainable land and water management and environmental protection programmes.

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Borzilov, V. A., Konoplev, A. V., & Bulgakov, A. A. (1993). Application of the Chernobyl experience in developing methodology for assessing and predicting the consequences of radioactive contamination of the hydrosphere. Hydrological considerations in relation to nuclear power plants. Proceedings of an International Workshop (pp. 246–263). Paris: UNESCO,. Branca, M., & Voltaggio, M. (1993) Erosion rates in badlands of central Italy – estimated by radiocaesium isotope ratio from Chernobyl nuclear accident. Applied Geochemistry, 8, 437–445. Bunzl, K., Schimmack, W., Kreutzer, K., & Schierl, R. (1989). Interception and retention of Chernobylderived and in a spruce stand. Science of the Total Environment, 78, 77–87. Callaway, J. C., De Laune, R. D., & Patrick, W. H. (1996). Chernobyl used to determine sediment accretion rates at selected northern European coastal wetlands. Limnology and Oceanography, 41, 444–450. Chesnokov, A. V., Fedin, V. I., Govorun, A. P., Ivanov, O. P., Liksonov, V. I., Potapov, V. N., Smirnov, S. V., Shcherbak, S. B., & Urutskoev, L. I. (1997). Collimated Detector Technique for Measuring a Deposit in Soil under a Clean Protected Layer. Applied Radiation and Isotopes, 9, 1265–1272. De Cort, M., Dubois, G., Fridman, S. D., Germenchuk, M. G., Izrael, Y. A., Jones, A.R., Kelly, Kvasnikova, E. V., Matveenko, I. I., Nazarov, I. M., Sitak, V. A., Stukin, E. D., Tabachny, L. Y., Tsaturov, Y. S., & Avdyushin, S. I. (1998). Atlas of caesium deposition on Europe after the Chernobyl accident, European Commission Report EUR 16733. Luxembourg: European Commission. De Roo, A. P. J. (1991). The use of as a tracer in an erosion study in South Limburg (the Netherlands) and the influence of Chernobyl fallout. Hydrological Process 5, 215–217. Devell, L., Guntay, S., & Powers, D. A. (1995). The Chernobyl reactor accident source term: development of a consensus view, CSNI report of NEA/OECD. Paris: OECD. Fridman, S. D., Kvasnikova, E. V., Glushko, O. V., Golosov, V. N., & Ivanova, N. N. (1997). Cesium137 migration in the geographical complexes of the central Russian hills. Meteorology and Hydrology, 5, 45–55. (in Russian) Golosov‚ V. N., Panin, A. V., & Markelov, M. V. (1999a). Chernobyl Redistribution in the Small Basin of the Lokna River, Central Russia. Physican Chemistry of the Earth (A), 10, 881–885. Golosov, V. N. (1998). Accumulation in balkas of Russian plain. In R. S. Chalov (Ed.), Eroziya poch i ruslovye processy 11 (pp. 97–112). Moscow: Moscow State University. ( i n Russian) Golosov, V. N. (2000). Radiometric dating in studies of erosion and accumulation. Geomorphologiya, 2, 26–33. (in Russian) Golosov, V. N., & Ivanova, N.N. (In press). Sediment-associated Chernobyl 137Cs redistribution in small basins in central Russia. In R. J. Allison (Ed.), Applied geomorphology: theory and practice. London: John Wiley & Sons. Golosov, V. N., & Kvasnikova, E. V. (2000). Erosion and deposition processes and migration of the artificial radionuclides in landscape. In Y. A. Izrael (Ed.), Radioactivity after nuclear explosions and accidents, vol. 1 (pp. 733–741). Saint Petersburg: Hydrometeoizdat. Golosov, V. N., Markelov, M. V., Panin, A. V., & Walling, D. E. (1998). Cs-137 contamination of river systems in Central Russia as a result of the Chernobyl incident. In H. Wheather and C. Kirby (Eds.), Hydrology in a changing environment, vol. 1 (pp. 535–546). London: WileyEurope. Golosov, V. N., Walling, D. E., & Panin, A. V. (2000a). Post-fallout redistribution of Chernobyl-derived Cs-137 in small catchments within the Lokna river basin. In M. Stone (Ed.), The role of erosion and sediment transport in nutrient and contaminant transfer, IAHS publication 263 (pp. 49–58). Wallingford: IAHS Press. Golosov, V. N., Walling, D. E., Panin, A. V., Stukin, E. D., Kvasnikova, E. V., & Ivanova, N. N. (1999b). The spatial variability of Chernobyl-derived Cs-137 inventories in small agricultural drainage basin in Central Russia 11 years after the Chernobyl incident. Applied Radiations and Isotopes, 51, 341– 352. Golosov, V. N., Walling, D. E., Stukin, E. D., Nikolaev, A. N., Kvasnikova, E. V., & Panin, A. V. (2000b). Application of a field-portable scintillation detector for studying the distribution of Cs-137 inventories in a small basin in Central Russia. Journal Environmental Radioactivity, 4, 79–94. Govorun, A. P., Liksonov, V. I., Romasko, V. P., Fedin, V. I., Urutskoev, L. I., & Chesnokov, A. V. (1994). Spectrum sensitive portable collimated gamma-radiometer CORAD. Pribory i Tekhnika Experimenta, 5, 207–208. (in Russian)

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Haak, E., & Rydberg, T. (1998). Deposition, transfer and migration of and in Swedish agricultural environments, and use of for erosion studies. In Use of in the study of soil erosion and sedimentation, IAEA-TECDOC-1028 (pp. 27–38). Vienna: IAEA. He, Q., & Walling, D. E. (1996). Interpreting the particle size effect in the adsorption of and unsupported by mineral soils and sediments. Journal of Environmental Radioactivity, 30, 117– 137. He, Q., Walling, D. E., & Owens, P. N. (1996). Interpreting the 137Cs profiles observed in several small lakes and reservoirs in southern England. Chemical Geology, 129, 115–131. Higgitt, D.L., Froehlich, W., & Walling, D. E. (1992). Application and limitations of Chernobyl radiocaesium measurements in a Carpathian erosion investigation, Poland. Land Degradation and Rehabilitation, 3, 15–26. Higgitt, D. L., Rowan, J. S., & Walling, D. E. (1993). Catchment scale deposition and redistribution of Chernobyl radiocaesium in upland Britain. Environment International, 19, 155–166. Izrael, Y. A. (Ed.) (1990). Chernobyl: radionuclide contamination of the environment 295. St. Petersburg: Gidrometeoizdat. (in Russian) Izrael, Y. A. (1996). Radioactive fallout after nuclear explosions and accidents 356, Saint Petersburg: Progress-Pogoda. (in Russian). Izrael, Y. A., & Soudakova, E. A. (Eds.) (1998) Atlas of radioactive contamination of European Russia, Belarus and Ukraine. Moscow: Federal Service of Geodesy and Cartography. Kachanoski, R. G. (1987). Comparison of measured soil cesium-137 losses and erosion rates. Canadian Journal of Soil Science, 67, 199–203. Kvasnikova, E. V., Stukin, E. D., & Golosov, V. N. (1999). Variability of Chernobyl contamination of Cs-137 in relation to distance from the Chernobyl nuclear power station. Meteorology and Hydrology, 2, 5–12 (in Russian). Litvin, L. F., Golosov, V. N., Dobrovol’skaya, N. G., Ivanova, N. N., Krasnov, S. F., & Kiryuhma, Z. P. (1996). Redistribution by water erosion processes. Journal of Water Resources 3, 286–291. Margineanu, R., Ionita, I., Breban, D., & Gheorghiu, D. (2000). Inventory of 137Cs from Chernobyl accident in the Moldavian Tableland of Romania. In Izrael, Y. A. (Ed.), Radioactivity after nuclear explosions and accidents, vol. 1 (pp. 742–748), Saint Petersburg: Hydrometeoizdat. Owens, P. N., & Walling, D. E. (1996). Spatial variability of caesium-137 inventories at reference sites: an example from two contrasting sites in England and Zimbabwe. Applied Radiation and Isotopes, 47, 699–707. Panin, A. V., Walling, D. E., & Golosov, V. N. (2001). The role of soil erosion and fluvial processes in the post-fallout redistribution of Chernobyl-derived caesium-137: a case study of the Lapki catchment, Central Russia. Geomorphology. 40, 185–204. Rowan, J. S., Higgitt, D. L., & Walling, D. E. (1993). Incorporation of Chernobyl-derived radiocaesium in reservoir sedimentary profiles. In McManus J. and Duck R. (Eds.), Geomorphology and sedimentology of lakes and reservoirs (pp. 55–71). London: Wiley. Silant’ev, K. A., & Silant’ev, A. N. (1997). Analysis of radionuclide contamination of territory using spatial distribution in the soil. Atomnaya Energiya, 4, 323–325. (in Russian) Sogon, S., Penven, M-J., Bonte, P., & Muxart, T. (1999). Estimation of sediment yield and soil loss using suspended sediment load and measurements on agricultural land, Brie Plateau, France. In Garnier J. and Mouchel J.-M. (Eds.), Man and river systems (pp.251–261). Dordrecht: Kluwer. Sutherland, R. A. (1996). Caesium-137 soil sampling and inventory variability in reference locations: a literature survey. Hydrological Processes, 10, 43–53. Sutherland, R. A. (1998). Potential for reference site resampling in estimating sediment redistribution and assessing landscape stability by the caesium-137 method. Hydrological Processes 7, 995–1007. Vanden Berghe, I., & Gulinck, H. (1987). Fallout as a tracer for soil mobility in the landscape framework of the Belgian loamy region. Pedologie, 37, 5–20. Velasco, R. H., Toso J. P., & Belli, M. (1997). Radiocesium in the Northeastern part of Italy after the Chernobyl accident: vertical soil transport and soil-to-plant transfer. Journal of Environmental Radioactivity, 1, 73–83. Walling, D. E., Golosov, V.N., Kvasnikova, E.V., & Vandecasteele, C. (2000a). Radioecological aspects of soil pollution in small catchments. Pochvovedenie, 7, 888–897. Walling, D. E. (1998). Use of and other fallout radionuclides in soil erosion investigations: progress, problems and prospects. In Use of 137Cs in the study of soil erosion and sedimentation, IAEATECDOC-1028 (pp.39–62).Vienna:IAEA.

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Walling, D. E., Golosov, V. N., Panin, A. V., & He, Q. (2000b). Use of radiocaesium to investigate erosion and sedimentation in areas with high levels of Chernobyl fallout. In I. D. L. Foster (Ed.), Tracers in geomorphology (pp. 183–200), Chichester: Wiley. Walling, D. E., & Quine, T. A. (1993). Using Chernobyl-derived fallout radionuclides to investigate the role of downstream conveyance losses in the suspended sediment budget of the river Severn, UK. Physical Geography, 14, 239–253. Walling, D. E., Quine, T. A., & Rowan, J. S. (1992a). Fluvial transport and redistribution of Chernobyl fallout radionuclides. Hydrobiologia, 235/236, 231–246. Walling, D. E., & He, Q. (1997). Use of fallout in investigations of overbank sediment deposition on river flood plains. Catena, 29, 263–282. Walling, D. E., Quine, T. A., & He, Q. (1992b). Investigating contemporary rates of floodplain sedimentation. In Carling, P. A. and Petts, G. E. (Eds.), Lowland floodplain rivers: Geomorphological perspectives (pp. 166-184). Chichester: Wiley. Wicherek, S. P., & Bernard, C.( 1995). Assessment of soil movements in a watershed from Cs-137 data and conventional measurements (example: the Parisian Basin). Catena, 25, 141–151.

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CHAPTER 9 ALTERNATIVE METHODS AND RADIONUCLIDES FOR USE IN SOIL-EROSION AND SEDIMENTATION INVESTIGATIONS Q. HE1, D.E. WALLING2 and P.J WALLBRINK3 1

CEM Centre, University of Durham, Stockton Road, Durham DH1 3UZ, United Kingdom. 2 Department of Geography, University of Exeter, Amory Building, Exeter EX4 4RJ, United Kingdom. 3Environmental Hydrology, CSIRO, Division of Land and Water, PO Box 1666, Canberra, ACT 2601, Australia

9.1. INTRODUCTION The use of for documenting rates and patterns of soil redistribution and sediment deposition represents an important advance that overcomes many of the limitations of existing techniques (e.g. Ritchie and McHenry, 1990; IAEA, 1998; Walling and Quine, 1992, 1995; Walling and He, 1997; Walling, 1998). Thus, the approach presents several key advantages (cf. Chapter 1), but a number of potential limitations must also be recognized and addressed in any application (Walling and Quine, 1995; Walling, 1998; Chapter 1). For example, traditional procedures for applying measurements in soil-erosion and sedimentation investigations involve the collection of soil or sediment cores from a study site and their subsequent transfer to the laboratory for preparation and analysis of activity by gamma spectrometry. The resulting measurements of activity are used to calculate the inventories for the individual cores and, thus, the sampling points (see previous chapters). In cases where a large number of cores are collected and require analysis, their processing and laboratory measurement will involve substantial effort. Furthermore, an extended period of time will generally be required for the measurements, because long count times are required for environmental samples containing relatively low levels of activity. Appreciable delays in obtaining results may, therefore, arise and it is not generally possible to obtain immediate data for use in planning and developing an ongoing sampling programme for detailed investigations.

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F. Zapata (ed.), Handbook for the assessment of soil erosion and sedimentation using environmental radionuclides, 185–215. © 2002 IAEA. Primed in the Netherlands.

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Similarly, although the time-integrated nature of the estimates of soilredistribution and sediment-deposition rates obtained using the traditional technique provides an average value for a period of ca. 45 years, which may be viewed as an advantage in that it overcomes the problems of representativeness frequently associated with short periods of monitoring, it may equally represent a limitation where information relating to shorter periods is required. For example, where land use or other environmental conditions have changed during the past 40 to 45 years or where it is known that erosion occurs only during extreme events, a mean erosion rate for the period of ca. 45 years may be of limited value. In the case of soil erosion, it is not possible to establish the range of values of annual soil0redistribution rate encompassed by the mean value provided by the technique, or the magnitude and timing of any changes involved. Equally, there are likely to be many situations where there is need to assess erosion rates associated with particular storm events or short periods or with specific short-lived land-use conditions. Furthermore, the estimates of medium-term rates of soil redistribution provided by the approach will reflect the integrated effects both of water and of wind erosion and soil redistribution by tillage activity (see Govers et al., 1994, 1996; Quine et al., 1997; Chapter 7). It is necessary to separate the erosion and tillage components if, as will frequently be the case, information on water and wind erosion alone is required. This should ideally be achieved by measuring erosion rates during periods between tillage operations when tillage redistribution will be absent, but this would require measurement of short-term erosion rates, rather than the longer-term average rates provided by measurements. In the case of sediment deposition on floodplains, information on rates of sedimentation associated with individual over-bank flood events, rather than the average rate for a longer period, would again frequently be of value. Another limitation is that, in some environments where inventories are small, the variability of reference inventories can be large (Wallbrink et al., 1994). The net effect of this is to limit the precision of subsequent manipulations between any “reference: and “field” measurements, since the precision of any estimated soil losses or gains is defined by the uncertainty surrounding the initial input “reference” term. It is probable that the distribution of fallout is similarly affected by the same processes, and so the relationship between the two tracers may yield a more stable means by which to define a reference input, than either nuclide in isolation. In view of these limitations, there is clearly a need to explore the potential for enhancing and extending the technique by using other methods to obtain the measurements within a shorter period of time and by using other fallout radionuclides with behaviour similar to that of but with a continuous input or a half-life extending to days rather than years, that could be used to document either the short-term contemporary rates of soil redistribution and sediment deposition or address issues of variability. This chapter discusses the procedures involved in employing field-portable gamma detectors to obtain in-situ measurements of inventories, and also the methodology for using measurements in soil erosion

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and floodplain sedimentation studies (cf. Tyler et al, 1996; He and Walling, 2000; Walling et al., 2000). It includes a short section on utilizing the inventory ratios of and for measuring soil loss in uncultivated forested environments where reference inventories are low and highly variable. 9.2. IN-SITU MEASUREMENT OF INVENTORIES USING FIELD-PORTABLE GAMMA DETECTORS The potential for using field-portable in situ gamma spectrometers to obtain on-site measurements of inventories for soils and sediments is attracting increasing attention (cf. Zombori et al., 1992; Tyler et al., 1996; He and Walling, 2000). In-situ measurements would appear to offer a number of significant advantages. These include, firstly, the potential for relatively rapid field measurements, which could either replace the collection of cores for subsequent laboratory counting or be used in a reconnaissance mode as an input to the planning of a detailed sampling strategy; secondly, limited disturbance of the site under investigation; and, thirdly, more representative results by virtue of the greater surface area or mass of soil or sediment involved in the measurement. Problems of representativeness are frequently encountered with soil cores, in view of the relatively small surface areas involved and micro-scale variability in soil properties and surface conditions. Because of the much larger sample mass associated with direct field measurement, the count times required by in-situ measurements will commonly be significantly shorter than those required by laboratory detectors. Figure 9.1 portrays a field-portable gamma detector being used for in-situ measurement of inventories in a cultivated field in Devon, United Kingdom. 9.2.1. Basic Principles Since the pioneering work of Beck et al. (1972), the use of in-situ gammaspectrometry measurements for documenting levels of environmental radioactivity in soils has become well established (cf. Miller and Helfer, 1985; Helfer and Miller, 1988; Zombori et al., 1992; Lettner et al., 1996; Tyler, 1996; He and Walling, 2000). In essence, this technique involves the collection of gamma spectra using a fieldportable detector mounted on a tripod above the ground and subsequent analysis of the spectra to determine the activity of specific radionuclides contained within the soil. Within the field of view of the detector, the ground surface should be relatively flat and free of large obstacles; the radionuclide activities are assumed to be uniform spatially within this zone. Knowledge of the vertical distribution of the radionuclide of interest within the soil is required in order to take account of attenuation of gamma rays by the soil matrix and thus derive an estimate of the total radionuclide inventory of the soil from the measured spectrum.

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Information on characteristic radionuclide depth distributions required for such calibration can be obtained through laboratory analysis of sectioned soil cores. Zombori et al. (1992) and Tyler et al. (1996) have also developed a technique for using the forward scattering ratio derived from the shape of the full-energy peak in the in-situ spectra, to infer directly the vertical distribution of in the soil or sediment at the measurement point. This approach is based on the fact that a proportion of the gamma radiation from the in the soil profile that reaches the detector will have its energy reduced as a result of scattering by the soil particles. The count rate on the left-hand side of the full-energy peak will, therefore, be higher than that on the right-hand side of the peak. The vertical distribution of in soils and sediments will, therefore, be reflected by the shape of the full energy peak at 661.6 keV and the count rates in the region between 609.3 keV and 727.2 keV Zombori et al. (1992) and Tyler et al. (1996) have shown that the parameter Q, defined as the ratio of the net count rate at the 661.6 keV peak to the difference between the average count rate between the peak at 661.6 keV and the peak at 609.3 keV and the average count rate

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between the peak at 661.6 keV and the peak at 727.2 keV, is closely related to the depth distribution of the activity, the magnitude of activity and the physical and chemical properties of the soil or sediment profile. In general, the region of interest used for calculating the net peak count rate C from the in situ measurements is set to 657.03–663.52 keV, and the energy regions used for calculating the forward scattering parameters and are set to 612.12 to 656.53 keV and 665.51 to 721.40 keV respectively. The parameter B is calculated as

Figure 9.2 illustrates the counts per channel (0.499 keV) for a portion of the insitu gamma spectrum collected from a location in a cultivated field in Devon, United Kingdom, using a field-portable detector with the count time set to 3,600 s. Each channel represents an energy of 0.499 keV. The channels shown are from 1230 (or 616.12 keV) to 1449 (or 721.40 keV). For this particular spectrum, the net count rate C at its full energy peak can be calculated as the ratio of the total net counts from channel 1321 (657.03 keV) to channel 1333 (663.52 keV) to the count time. The parameter can be calculated as the ratio of the average counts per channel from channel 1230 (612.12 keV) to channel 1319 (656.53 keV) to the count time, and the parameter can be calculated as the ratio of the average counts per channel from channel 1337 (665.51 keV) to channel 1449 (721.40 keV) to the count time.

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9.2.2. Field And Laboratory Procedures It should be emphasized that the field and laboratory procedures presented here are those that have been successfully employed by researchers at Exeter University. Other researchers may use slightly different approaches. The field-portable gamma spectrometer used consists of an EG&G ORTEC HPGe high resolution N-type coaxial detector (relative efficiency 40%) equipped with a 5-L liquid dewar and coupled to a NOMAD Plus power supply and multichannel analyser system and a portable computer. Energy calibration of the spectrometer is undertaken using the gamma rays of known energies from and point sources supplied by Amersham International. A linear relationship between the channel number and energy can be established. For in-situ measurements, the detector is mounted on a tripod 1 m above the ground surface to collect the gamma spectrum. At this height, the field of view of the detector is a circle of ca. 20 m diameter, although the sensitivity of the detector within this zone decreases rapidly towards the outer boundary. The detector is set perpendicular to the ground surface, in order to ensure that the field of view is symmetrical and that gamma rays are collected from the whole area. Count times should be set according to the level of in the soil or sediment to provide reliable measurements. He and Walling (2000) have used count times of ca. 5,000 s at most of their study sites. In order to calibrate the detector, soil or sediment cores must be collected from several locations within a study site where the field-portable detector is deployed, for subsequent sectioning and laboratory analysis, in order to provide information on the depth distribution of at these locations. To ensure the representativeness of the depth distribution established for a particular measuring location, several cores must be collected for subsequent laboratory analysis. Thus, for example, at a particular measuring location, five cores may be taken from the four corners and the centre of a 4 × 4 m square centred immediately beneath the detector. The core tube used for collecting the sectioned soil and sediment cores should be inserted vertically (i.e. perpendicular to the horizontal) in order to provide areal activities or inventories defined in the conventional manner. 9.2.3. Calibration of Field-Portable Gamma Detectors for

Measurement

The purpose of calibrating a field-portable detector is to establish a relationship between the distribution of (or inventory) in the soil or sediment profile within the field of view of the detector and the characteristics of the collected spectrum for individual measuring points. This can be achieved by analysing the spectrum produced by the in-situ gamma measurements and using laboratory measurements to obtain information on the depth distribution of for sectioned soil or sediment cores collected from those measuring points. The resulting relationship can then be used to estimate inventories for other measuring points where only in-situ measurements are undertaken. Since the depth distribution of

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137

Cs in cultivated soils is generally different from that in undisturbed soils or sediments, such as floodplain deposits, detector calibration for cultivated soils will differ from that for undisturbed soils or sediments. 9.2.3.1. Cultivated Soils The vertical distribution of in cultivated soils is primarily controlled by tillage practices that mix the soil and the associated within the plough layer. Where erosion takes place, the will be uniformly distributed within the plough layer. Where deposition occurs, the depth to which is found will increase, because the original plough layer will be buried beneath the accumulating soil. Because of tillage mixing, will be uniformly distributed within the plough layer in most cultivated soils. This feature is demonstrated in Fig. 9.3, which illustrates the depth profiles for two soil cores collected from a cultivated field in Devon, United Kingdom, and sectioned into 2-cm increments, obtained using laboratory measurements. These profiles are typical of those commonly encountered in cultivated soils.

In general, therefore, the concentration within a ploughed soil profile can be viewed as uniform vertically, within the penetration depth D i.e. the depth to which is found), which can in turn be used to characterize its depth distribution in the soil profile and can be established by analysis of sectioned cores in the laboratory. Values of the parameter Q associated with the in-situ spectrum can be calculated from the collected in-situ spectra, and should reflect both D and the soil properties. To establish the relationship between Q and the corresponding values of penetration depth obtained for sectioned cores, the values of D need to be corrected by the term (where is the slope angle in degrees), if the field detector is set up perpendicular to the slope surface and the core tube for collecting soil cores is inserted vertically. If it is assumed that the value of D obtained from the sectioned

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cores at each measuring location is representative of the entire area within the field of view of the detector, the relationship between Q and D may in general be expressed as:

where: parameter characterizing the attenuation of gamma rays by soil particles, which is related to soil properties. The form of the function must be determined empirically. As an example, Fig. 9.4A depicts the relationship between Q and D obtained for six measuring points within a cultivated field in Devon, United Kingdom, where both insitu gamma measurements had been undertaken and sectioned cores had been collected for laboratory analysis. The relationship shown in Fig. 9.4A can be expressed as:

In Eq. 9.2, the two constants and which are related to and reflect the effect of the interaction between the gamma rays from and soil particles, were estimated to be 144 and respectively. If it is assumed that these values of and are applicable to the entire field, Eq. 9.2 can be used to estimate the penetration depth D for locations where only in-situ measurements were undertaken, from the values of Q derived from the collected gamma spectrum. The next stage of the detector-calibration process involves establishing a relationship between the values of net peak count rate C measured using the field detector at the measuring locations where sectioned soil cores are collected and the corresponding values of inventory obtained from the cores analysed in the laboratory. It seems reasonable to assume that the inventory for a measuring location will be proportional to the product of the count rate C and the penetration depth D:

The function form of Eq. 9.3 can also be established using the dataset collected for calibration purposes. Figure 9.4B presents the relationship between and CD for the six measuring points within the cultivated field described above. Again, an exponential relationship can be fitted to the results, viz.:

The two constants respectively.

and

were estimated to be

and

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Finally, solving Eq. 9.1 for D and substituting D in to Equation 9.3, a relationship between and and can be established. In general, such a relationship can be expressed as:

In Eq. 9.5, is a function of empirically determined parameters such as and Once has been determined, Eq. 9.5 can be used to calculate inventories for locations where only in-situ measurements are undertaken. Again for the above example, Eq. 9.5 can be explicitly expressed as:

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Equation 9.6 may be used to calculate the inventories for other measuring locations within the field where in-situ measurements are made, if it is assumed that the values of and derived from the data available for the locations where sectioned cores were collected are applicable to other locations in the field.

9.2.3.2. Floodplain Sediments In many areas of the world, floodplain areas are not cultivated due to the risk of inundation and waterlogging, although they may be used as permanent pasture for livestock grazing. The depth distribution of in the sediment profile will, therefore, commonly differ significantly from that found in cultivated soils. This contrast is clearly evident in Fig. 9.5, which presents the profiles associated with two sediment cores sectioned at 2-cm increments collected from the floodplain on the River Culm in Devon, and analysed in the laboratory. The profiles found in floodplain sediments will generally be characterized by a concentration peak located a significant distance below the surface and by a gradual, and approximately exponential, decline in concentration below this peak. This characteristic form reflects the interaction of the temporal pattern of fallout and the progressive accretion of sediment on the floodplain surface. Because floodplain sedimentation rates will generally be characterized by substantial spatial variability (cf. Walling et al., 1996; Walling and He, 1997), the depth of the peak in the sediment profile will also vary spatially. In the case of cultivated soils discussed in Section 9.2.3, the activity is relatively uniform within the plough depth and a well defined relationship between the in-situ count rate C and the penetration depth can be expected.

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However, such a relationship will not exist for floodplain sediments, because the activities within the sediment profile will vary with depth and the selfadsorption of the gamma rays from contained within the sediment at specific depths will be closely related to the thickness of the overlying layer through which they have to pass. A simple measure of penetration depth will, therefore, not be sufficient to represent the depth distribution of in floodplain sediments. Following Tyler et al. (1996), the effective penetration depth for a sectioned sediment core analysed in the laboratory, which is defined as the concentration weighted mass depth

can be used to characterize the vertical distribution of in floodplain sediments. In Eq. 9.7, is the mass depth from the sediment surface, and is the laboratory-measured activity. Using a similar approach to that adopted for cultivated soils, if it is assumed that the value of obtained from the sectioned sediment core at each measuring location is representative of the entire area within the field of view of the detector, the relationship between and may be expressed as:

where: = a parameter characterizing the attenuation of gamma rays by sediment particles. The relationship between the inventory and the net count rate C and the effective penetration depth may be expressed as:

The form of both Eqq. 9.8 and 9.9 must again be determined empirically by analysing the spectra obtained from the in-situ measurements and the depth distribution of in sediment established by laboratory analysis of sectioned sediment cores. The relationship between and and may then be established:

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In Eq. 9.10, is again a function of empirically determined parameters. Equation 9.10 can be used to calculate inventories for locations on the floodplain where only in-situ measurements are undertaken. As an example, Fig. 9.6 shows the relationships between the parameter Q and the effective penetration depth and between the laboratory measured inventory and the in-situ measured for five measuring points on the River Culm floodplain, where both in-situ measurements were made and sediment cores were collected for laboratory assay. Comparing Fig. 9.4 with Fig. 9.6, it can be seen that the values of the parameter Q are substantially higher for the floodplain sediments than those for the cultivated soils. This is because the mass depths of penetration associated with the floodplain sediments are significantly lower than those for the cultivated soil, although the linear depths are similar, due to the lower density of the floodplain sediments.

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Again, exponential functions similar to Eqq. 9.2 and 9.4 can be used to establish equivalent relationships for the floodplain sediments, and values for the parameters and were estimated to be 1,254, and respectively. An equation similar to Eq. 9.6 can also be established and may be used to derive inventories from the measured spectra for locations when only in-situ measurements are undertaken. 9.2.4. Application of In-Situ

Measurements

The ability to obtain relatively rapid on-site estimates of inventories for a number of measuring points using field-portable gamma detectors undoubtedly offers considerable potential both for reconnaissance measurements over extended areas and as input to the planning of an ongoing sampling programme. The ability to obtain estimates of inventories without the need for the destructive sampling associated with the collection of soil or sediment cores may also offer an important advantage in some studies. This method is also particularly useful for areas where there are high levels of such as those regions of Europe where substantial inputs of Chernobyl-derived were received, since count times will be considerably reduced. The models for converting measurements into estimates of rates of soil redistribution or sediment deposition presented in Chapter 7 are equally applicable to the data for soils or sediments obtained using in-situ measurements. In-situ measurements are, however, not without limitations. These include the need to take account of the “field of view: of the detector and of the variability of detector response across this field. More importantly, in-situ measurements of activity obtained using field-portable detectors will be influenced by attenuation of the gamma rays by the soil or sediment matrix. Information on the depth distribution of in the soil or sediment profile is, therefore, an essential requirement, in order to derive a reliable estimate of the total inventory at the measurement point (cf. Beck et al., 1972; Miller and Helfer, 1985). This latter problem is particularly significant in the case of bomb-derived Because of its relatively long half-life and an extended period of atmospheric deposition, it will generally have penetrated relatively deeply into the soil profile, due to mixing of the soil by tillage practices, natural downward translocation mechanisms, or burial of the surface horizons by accreting soil or sediment at depositional sites. These factors are likely to be particularly significant at locations where soil erosion or floodplain sedimentation is under investigation. 9.3. USE OF MEASUREMENTS TO STUDY SHORT-TERM OR EVENT-BASED EROSION AND SEDIMENTATION In situations where information on event-based or short-term rates and patterns of soil redistribution or sediment deposition is required, use of measurements may offer considerable potential as an alternative to

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Beryllium-7 is an environmental or fallout radionuclide with a half-life of 53 days, which is produced primarily by the bombardment of the earth’s atmosphere by cosmic rays. It is subsequently deposited onto the earth’s surface as fallout in association with wet precipitation. Therefore, differs from in three important respects. Firstly, it is of natural origin, whereas is, in most instances, a product of the atmospheric testing of nuclear weapons. Secondly, its input can be viewed as effectively continuous, whereas significant inputs were primarily restricted to the period associated with the testing of nuclear weapons, from the late 1950s to early 1970s. Thirdly, because of its short half-life (53 days) rapidly decays and the inventory of a soil or sediment core will reflect the magnitude of recent fallout receipts and recent soil or sediment redistribution, rather than the longer-term build up of fallout inputs and long-term soil or sediment redistribution. However, like is rapidly and strongly adsorbed by soil and sediment particles in most environments (Hawley et al., 1986; Wallbrink and Murray, 1996a) and it has been successfully used as a sediment tracer for studying sediment mixing in lakes and for fingerprinting sediment sources (Wan et al., 1987; Burch et al., 1988; Walling and Woodward, 1992; Wallbrink and Murray, 1993, 1996a). In these applications, the presence of in sediment provided evidence for recent contact with the fallout input. More recently, Walling et al. (2000) and Blake et al. (1999) have used measurements for documenting short-term rates of soil redistribution on cultivated land. Like fallout is rapidly adsorbed by soil or sediment particles on reaching the ground with precipitation. Results from experiments indicate that, as with the adsorbed is primarily associated with fine soil and sediment particles (see Blake, 2000), and this needs to be taken into account when using for erosion and sedimentation studies, due to the grain size selectivity involved in erosion and sediment-transport processes. 9.3.1. Use of Assumptions

in Erosion and Sedimentation Investigations: Principles and

As with the key principle underlying the use of measurements in shortterm or event-based soil erosion and floodplain sedimentation investigations is the fact that the radionuclide is firmly adsorbed by soil and sediment particles and that its post-fallout redistribution will, therefore, reflect the redistribution of soil or sediment particles in the landscape. To use measurements to study erosion on cultivated soils or sediment deposition on floodplains associated with individual events, information on the preevent spatial distribution of across the study area, as well as its concentration in eroded or deposited sediment, is needed. By comparing the pre- and post-event distributions, it is possible to estimate erosion and deposition rates. The need for preevent and post-event surveys necessarily introduces a degree of complexity into both the field-measurement programme and the subsequent data analysis and

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interpretation. However, there are situations where measurements can be used for studying short-term or event-induced erosion and deposition, based on some simplifying assumptions. For example, in the case of cultivated soils, if surface runoff has not occurred for a relatively long period (e.g. 5 months, or three half-lives of it may be assumed that deposition of has been spatially uniform at the field or small catchment scale. If, subsequently, a rainfall event that can generate overland flow and therefore soil erosion occurs, the pre-existing will be redistributed across the soil surface. If it is also assumed that the deposited with this rainfall is primarily associated with the initial stages of the rainfall when overland flow has not been initiated and is spatially uniform, redistribution of this component of across the soil surface may be assumed to be similar to that for the pre-existing Therefore, any spatial variation of inventories observed after an erosional event will reflect the redistribution of soil particles induced by the event. In situations where the above assumptions are met, measurement can be used to study soil erosion in a way similar to measurement. For example, a local reference inventory may also be established after the event by analysing soil cores collected from adjacent undisturbed sites, and this reference value can be compared with the inventory values associated with soil cores collected from the cultivated field. Any depletion of the content of soil cores relative to the reference inventory will indicate soil erosion at the sampling location, while any increase will indicate soil deposition. As with models may also be developed to obtain quantitative information on soil redistribution, once the behaviour of in soils is understood (see Section 9.3.2). In the case of floodplain sedimentation, any point on the floodplain surface will receive inputs from two potential sources. The first is the direct input from atmospheric fallout and the second is via accumulation of enriched fine sediment deposited during an over-bank flood event. Again, if a sufficiently long period has elapsed since the last over-bank event, the contribution from deposited sediment, which is likely to be spatially variable, can be assumed to be negligible and the fallout component can be assumed to be spatially uniform. Any increase in the inventory on the floodplain after an over-bank event, relative to the inventory determined for a reference site above the level of flood inundation, can therefore be attributed to over-bank sedimentation. 9.3.2. The Vertical Distribution of 7Be in Soils and Sediments To use for studying soil erosion or sediment deposition over short periods, an understanding of the behaviour of in soils and sediment is needed. Figure 9.7 shows the vertical distribution of in four sectioned shallow soil cores collected from an undisturbed site (Core A) and a cultivated field (Cores B, C and D) in a small catchment in Devon, after an extended period of rainfall.

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These profiles are similar to those reported by other researchers (Bei et al., 1996; Wallbrink and Murray, 1996a,b), which suggest that significant concentrations of will only be found in the immediate surface layer. In the case of the three cultivated soil cores, Core B was from a location on the flat area at the top of the field, and Core C was from a location on the valley side. Core D was from a depression at the bottom of the field. The majority of was found in the top several mm of the soil cores, except in the case of Core D where extends to a mass depth of (or c. 2.4 cm). Concentrations in both Cores A and B declined with increasing depth, although penetrated to a slightly greater depth in Core B than in Core A. The reduced depth of penetration associated with Core A resulted in higher concentrations in the surface layer (0–0.3 cm), and probably reflects minor contrasts in soil texture and other soil properties, such as bulk density, between the cultivated and undisturbed soil. However, the total inventories for

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both Cores A and B were very similar at and respectively. The local reference inventory at the time of sampling was estimated to be based on the analysis of six cores collected from nearby undisturbed soils. The total inventory associated with Core B was close to this value, suggesting that negligible erosion or deposition, and therefore negligible loss or gain of had occurred at this sampling point, which was located on a flat area at the top of the field and is therefore unlikely to be subject to erosion or deposition. Although the activity in Core C was also limited to the surface layer, the total inventory was significantly lower than that of Core A or Core B. Assuming a uniform input across the field, this indicates that soil and associated have been lost from this sampling point. The vertical distribution of in Core D wass different from that in the other three cores. In this core, there was a subsurface concentration peak located at a mass depth of and was found to a mass depth of (2.4 cm), significantly deeper than the other three cores. The total inventory of for this core was also substantially higher than the estimated local reference inventory at the time of sampling. These characteristics are indicative of a depositional location. The existence of a concentration peak below the soil surface within the soil profile of Core D reflects the deposition of sediment containing lower concentrations mobilized from the upslope eroded areas. 9.3.3. Field and Laboratory Procedures The field and laboratory procedures involved in measurements are similar to those involved in measurements. Because of its short half-life, samples should be collected immediately after the event under investigation and analysed as soon as possible to provide significant levels of for gamma analysis. Because is restricted to shallow depths, only shallow cores (less than 5 cm deep) are required. However, when collecting bulk cores for analysis, the core tubes should in general be of a larger diameter than those used when sampling for analysis, in order to produces a sample of sufficient mass for gamma assay. To obtain information on the detailed depth distribution of in soils or sediments, large diameter cores can be collected and sectioned into thin layers (with depth increments of a few millimetres, e.g. <5 mm) for subsequent analysis. In studies where samples of suspended sediment are needed, traditional sampling methods can be adopted. Beryllium-7 is measured by gamma spectrometry at an energy of 478 keV and the count times for laboratory analysis are similar to those employed for analysis. 9.3.4. Models for Converting Measurements Into Short-Term or Event-Based Rates and Patterns of Soil Redistribution and Sediment Deposition The various calibration procedures that are available for use with measurements have been discussed in Chapter 7, and it is possible to develop analogous procedures for measurements for estimating rates of soil erosion or

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sediment deposition. The models discussed below apply to situations where preevent is either absent or spatially uniform at a study site. 9.3.4.1. A Model for Converting Measurements Into Soil Redistribution Rates As indicated in Fig. 9.7, it may be assumed that the initial distribution of fallout inuts within the surface soil will be exponential, i.e.,

where: = the mass depth from the soil surface (positive downwards) = the initial concentration of at depth = the initial concentration of in the surface soil = the relaxation mass depth describing the shape of the initial depth distribution For an exponential depth profile, 63% of the total loading will be retained in the depth The greater the value of the deeper the penetration of into the soil profile. The reference inventory for a study area is the measured total inventory at an uneroded stable site:

From Eq. 9.12, the inventory distribution can be expressed as:

below depth

for the initial

Assuming that erosion removes a thin layer from the soil surface, the inventory remaining at an eroded point will be lower than the reference inventory If is the depth of soil eroded (or the erosion amount the remaining inventory can be calculated from Eq. 9.13 by setting By including the measured inventory and taking into consideration the grain-size selectivity associated with the erosion process, Eq. 9.13 can be inverted to give the erosion amount

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where: = the ratio of the concentration of mobilized sediment to that of the original soil and takes values similar to that for (see Chapter 7). Because the grain-size composition of mobilized sediment is usually enriched in fines compared with the original soil, is generally greater than 1.0, due to the strong affinity of fine soil particles for The value of is, therefore, a function of the grain-size composition of both mobilized sediment and the original soil. Equation 9.14 indicates that the shape factor is an important parameter for deriving the soilerosion amount from the measured total inventory and that there is a linear relationship between the erosion amount and the natural logarithm of the ratio of the reference inventory to the measured inventory. As the erosion amount is proportional to the relaxation depth of the initial distribution an accurate estimate of the value of is important. Assuming that the profile associated with Core B depicted in Fig. 9.7 is representative of its initial distribution in the soil, a value of is estimated for This value is similar to those for the initial distribution of in surface soils observed in the experiments reported by He and Walling (1997). When the measured inventory for a sampling point is higher than the reference inventory net soil deposition may be assumed. The deposition amount will be related to the extent to which the inventory exceeds the reference value and the concentration of the deposited sediment Since only short-term or event-based soil redistribution is involved and longerterm temporal variation in the content of deposited sediment due to the decay effect can be neglected, the deposition amount may be calculated as:

The concentration of deposited sediment can be assumed to represent the weighted mean concentration of sediment mobilised from the upslope contributing area

where: = another particle size correction factor, representing the ratio of the concentration of deposited sediment to that of the mobilized sediment, which has values similar to those for (see Chapter 7). Because the grain-size composition of deposited sediment is usually depleted in the finer fractions compared to mobilized sediment, is generally less than 1.0.

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As an example of using the procedures described above, Fig. 9.8 depicts the spatial distribution of inventories and the soil-redistribution amounts estimated using the technique described above, within a ploughed field at Higher Walton Farm in Devon, after an extended period of rain in January 1998, which caused significant soil erosion in the field. It should, however, be recognized that the procedures used to estimate soilredistribution rates from measurements outlined above will only apply to situations where significant erosion events are separated by relatively long periods of time (e.g. ca. 5 months or three half-lives of They assume that the documented spatial pattern of inventories reflects soil redistribution occurring during the erosion event and that any pre-existing inventories and the input associated with the event can be treated as spatially uniform. If the last significant erosion event occurred ca. 5 months previously, inputs associated with that event can be assumed to have decayed to very low levels. Equally, if subsequent precipitation did not produce significant erosion, the inventories associated with those inputs can be assumed to be spatially uniform. Because cultivation will mix existing activity into the plough layer and greatly reduce the inventory in the surface layer, this will also serve to cancel the effects of preceding erosion events. In many instances, however, several erosion events may occur without being separated by a sufficient period. In such cases it should still prove possible to use measurements to estimate soil redistribution amounts, but additional information on the temporal distribution of fluxes will be required and there will be a need to take account of the decay of fallout inputs in both soil and mobilized sediment and the sequence of erosion events. Potential applications of the information on soil redistribution amounts provided by measurements could clearly include the validation and calibration of distributed event-based soil erosion and sediment-delivery models, since it is possible to obtain estimates of water-induced soil redistribution relating to short periods and in some situations to individual events. 9.3.4.2. A Model for Converting Measurements into Sedimentation Amounts The procedures involved in using measurements to document short-term or event-induced amounts of sediment deposition on floodplains follow the principles and assumptions of existing techniques for using to estimate floodplain sedimentation rates (Walling and He, 1997; Chapter 7). In brief, any point on the floodplain surface will receive inputs from two potential sources. The first is direct input from atmospheric fallout and the second is via accumulation of fine sediment deposited during over-bank flood events. Any excess on the floodplain, relative to the inventory determined for a reference site above the level of flood inundation, can therefore be attributed to over-bank sedimentation. In order to document deposition associated with individual events, it is clearly important that the distribution of the inventory across the site immediately prior to the event should be uniform and essentially equal to the local fallout inventory. This will not be the case if other over-bank events have occurred in the immediate past.

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As with the excess difference between the measured

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inventory value (defined as the inventory and the estimated local reference

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value) associated with each specific point on a floodplain can be used to estimate the amounts of sediment accumulated at that point

where: concentration of the newly deposited sediment It is difficult to collect recently deposited sediment from each sampling point, therefore it is difficult to obtain the value for If, however, samples of suspended sediment transported by the river can be collected during the same event and a relationship between activity and grain-size composition can be established for this sediment, the activity of recently deposited sediment at each sampling location can be estimated from the grain-size distribution of the surface sediment and the activity associated with the suspended sediment. This is similar to the approach used for (Walling and He, 1997). Blake (2000) expressed the relationship between activity of a progressively fining sub-sample of a suspended sediment sample and that of the original suspended sediment as:

where: concentration of the sub-samples concentration of the original suspended sediment sample = the specific surface of the sub-sample = the specific surface area of the original sample = a parameter representing the particle size selectivity of the sorption processes and takes a value of ca. 0.64. For each sampling location, the concentration of recently deposited sediment may be estimated using the following equation:

where: = the average concentration of the suspended sediment samples collected from the same storm event = the mean specific surface area of the suspended sediment sample = the specific surface of the surface sediment sample from the sampling location

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As an example, Fig. 9.9 illustrates the spatial pattern of sedimentation over a small area of the floodplain of the River Culm near Silverton Mill, Devon, associated with a sizeable over-bank flood event that occurred in October 1998 and was estimated from measurements using the procedures outlined above.

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This area was systematically cored with a 15-cm diameter corer to a depth of 5 cm (ninety-eight cores from a ca. 10-m grid) after the floodwater receded. In addition, suspended sediment samples associated with this event were collected and several reference cores were taken from undisturbed higher ground close to the site. The reference inventory for the site after this event was estimated to be based on four reference cores. The mean inventory for this area following the flood event was estimated to be demonstrating an excess of attributable to the deposition of fine sediment. Figure 9.9 demonstrates the potential for using to quantify floodplain sedimentation at the event scale. In addition to providing information on sedimentation depths associated with individual events, based on a single site visit, the technique also affords scope for collecting information at a higher spatial resolution than that achievable using conventional techniques. Furthermore, it must be recognized that sedimentation depths of the magnitudes documented for individual events could not be easily or accurately measured using conventional techniques. As such, the technique provides a valuable means of studying the effects of non-permanent floodplain features (e.g. vegetation, increased surface roughness due to cattle poaching, etc.) on floodplain sedimentation, in addition to the influence of floodplain topography. Collection of data for a series of over-bank events of varying magnitude or duration could also provide a basis for investigating the relationship between event magnitude or duration and sedimentation depth. The results provided by measurements could also be used as a means of validating numerical models of floodplain deposition, which are frequently event-based (e.g. Nicholas and Walling, 1998, 1997). To date, the validation of such models has had to rely on matching the patterns and general magnitude of medium-term estimates of sedimentation rate provided by measurements, or direct measurements of sedimentation during individual events using techniques such as astroturf mats (cf. Lambert and Walling, 1988), The latter are generally unable to document small amounts of deposition or to provide a very high spatial resolution, and may also be of questionable accuracy, due to interference with the natural floodplain surface. Although Fig. 9.9 clearly demonstrates that measurements can provide a powerful tool for investigating depths and patterns of over-bank sedimentation associated with individual events, it is important to recognize that the approach requires that any excess inventory inherited from previous events should be minimal. On most rivers, significant over-bank flood events are likely to be relatively infrequent, and similar opportunities should therefore arise. Where over-bank events are more frequent, the approach could still be used if a survey is undertaken immediately prior to the event to document any excess inventory inherited from previous events and thus the spatial variability associated with pre-existing inventory levels on the floodplain. However, this would involve a pre-flood sampling programme that essentially replicated the post-flood survey, thereby removing two key advantages of the technique, namely the requirement for only a single site visit and avoidance of the need to forecast the occurrence of a flood in order to undertake a pre-flood survey.

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9.4. USING THE INVENTORY RATIO OF EXCESS TO TO MEASURE SOIL LOSS IN REGIONS OF HIGH REFERENCE VARIABILITY 9.4.1. Basic Principles Caesium-137 is widely used to measure soil redistribution. However there are environments in which the initial distribution is not uniform. There can be considerable variability in initial fallout due to rain shadowing and small-scale runon-runoff processes at the time of deposition (e.g. Sutherland, 1991, 1994; Wallbrink et al., 1994). In these situations an ideal reference value can be difficult to determine, and the changes observed in inventories between reference and eroded areas may not result from soil redistribution alone. Fallout is also affected by these processes and, thus, areal concentrations of the two should be correlated. Furthermore, these two nuclides penetrate to different depths in uncultivated soils, thereby producing a varying activity ratio with depth, and this gives rise to an alternative method (Wallbrink and Murray, 1996b) for determining soil loss in uncultivated areas in regions where initial variability of fallout is high. 9.4.2. Experiment at St. Helens Forest, Tasmania: Design and Sampling Methodology The coefficient of variation of reference inventories is notoriously high in forests. The Tasmanian Forestry Commission logged parts of the St. Helens forest differently as part of an experiment to examine erosion under different harvesting conditions. After logging operations ceased, four plots were cordoned off. Unlogged plots 1 and 4 were adjacent to each of the harvested areas and left as control sites. Plot 2 (normal impact) represented standard logging practice while plot 3 (minimal impact) was harvested less intensively. It was anticipated that soil loss from plot 2 would exceed that of plot 3. The radionuclide concentrations of and in the soils from the logged and unlogged sites were determined by taking nine or ten representative soil cores from within each plot. Detailed depth sampling was undertaken at the two “control” sites (plots 1 and 4) to determine the initial distribution of the two nuclides. These profiles were of known surface area and acquired using the method described in Wallbrink and Murray (1996a). 9.4.3. Results The concentrations of and measured in the detailed profiles from plots 1 and 4 are shown as a function of depth in Figs. 9.10a, b and 9.11a, b, respectively. The cumulative inventories of each nuclide have been calculated with depth, by summing the areal concentrations within each increment towards the surface (Figs. 9.10c and 9.11c; for clarity only the top 150 mm are shown). The deeper penetration of is clearly visible.

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The radionuclide inventories from the cores within the plots were highly variable. The two unlogged plots (1 and 4) were statistically indistinguishable (at P <0.05, one-tailed test) and the reference value was taken from their average, (n=18, Relative Standard Deviation, RSD, 47%). This can be compared to the average areal concentrations of 710±90 (n=10; RSD=38%) and

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(n=10; RSD=49%) at sites 2 and 3 respectively, giving relative depletions of 12±16 and 15±18%. However, due to the high initial variability there was no statistical difference in areal concentrations, (P <0.05, one-tailed test) between the unlogged control sites and either of the two logged sites. There was also no statistical difference between the two logged sites (P <0.05, one-tailed test).

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A similar analysis was undertaken using excess inventories. The control plots were again indistinguishable (P <0.05, one-tailed test) and the combined average areal concentration of from these was 1,820±240 (n=18; RSD=57%). This can be compared to the average inventory values of 520±110 (n=10; RSD=66%) and 1,010±110 (n=10; RSD=35%) from plots 2 and 3. The logged plots 2 and 3 were statistically distinguishable both from one another and from the combined control plot value (P <0.05, one-tailed test) and their inventory values represent reductions of 71±15 and 45±15% respectively. Clearly, plot 2 lost a larger fraction of the initial inventory than plot 3. Comparing these data with their respective reference depth profiles at control plots 1 and 4, (Figs. 9.10c and 9.11c) gives depth losses of about 20±4 mm for site 2 and 11±4 mm for site 3. Nevertheless, it is important to note that the inventory values from the two detailed profiles at plots 1 and 4 (each taken over approximately differed by a factor of about 2. This emphasizes the possible error in assuming that the control inventories apply to the logged sites. 9.4.4. Using the Inventory Ratio It was suggested above that areal concentrations of and may be related, and a clear correlation was observed between them in the total core inventories from the control plots 1 and 4 (Fig. 9.12).

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Thus, an alternative approach for measuring soil loss is proposed based on the observation that in undisturbed soils and have different penetrations into the surface layers of soil. The bulk of activity is retained closer to the surface than (see Figs. 9.10a and 9.1la). Thus, the ratio of the inventory of (below a particular depth in the soil profile) to the inventory of below the same depth is unique. This ratio has finite values, and thus acts as a useful indicator, over the range of penetration of i.e. over a few centimetres. The ratio of the inventories from the two profiles at plots 1 and 4 decreased monotonically with depth and provided unique values down to about 80 mm (Fig. 9.13).

9.4.5. Comparison of Reference Inventory Ratio Profiles With Disturbed Sites The inventory ratios were calculated for each of the ten 300-mm cores taken from the logged sites, 2 and 3; the averages were 0.74±0.09 (n=10) and 1.73±0.29 (n=l0) respectively. These values are statistically different from one another, (P <0.05, onetailed test). The locations at which these ratios intersect the activity ratio curves from the respective “control” plots (shown in Fig. 9.13) correspond to the depth of soil removal required to leave behind these inventory ratio values. Average soil loss from these was then calculated to be about 40±5 mm from the heavily logged plot 2, and 17±5 mm from the more carefully managed plot 3. The average measured bulk density of these soils was through the top 100 mm, and so these depths

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from plots 2 and 3 correspond to net soil losses of 440±55 and 190±55 t respectively. Note that the uncertainties given are relative to the measurement errors on the initial ratio values only. 9.4.6. Conclusions From the Inventory-Ratio Method There are environments in which the distribution of is highly heterogeneous. It may be difficult to discern a reference level within acceptable confidence limits. In these situations, it is possible that the distribution of fallout will be affected by the same processes, and so taking the ratio of one to another may reduce the heterogeneity associated with either in isolation. Furthermore, the difference in depth dependence between the two nuclides dictates that the activity ratio between them decreases monotonically with depth, and can be used to quantify depth losses from disturbed sites at which the reference activity ratio is assumed to hold. 9.5. REFERENCES Beck H. L., deCampo, J., & Gogolak, C. (1972). In situ Ge (Li) and NaI (Tl) gamma-ray spectrometry. USDOE Report HASL-258. Washington: US Department of Energy. Blake, W. H., Walling, D. E., & He, Q. (1999). Using as a tracer in soil erosion investigations. Applied Radiation and Isotopes, 51, 599–605. Blake, W. H. (2000). The use of as a tracer in sediment budget investigations, unpublished PhD thesis. Exeter: University of Exeter. Bei, Z,, Wan, G., Wang, C., Wan, X., & Huang, R. (1996). distribution in surface soil of central Guizhou karst region and its erosion trace. Progress in Natural Science, 6, 700–710 Burch, G. J., Barnes, C. J., Moore, I. D., Barling, R. D., Mackenzie, D. J., & Olley, J. M. (1998). Detection and prediction of sediment sources in catchments: Use of and In Proceedings, Hydrology and Water Resources Symposium (pp. 146–151). Canberra: Australian National University. Govers, G., Vandaele, K., Desmet, P. J. J., Poesen, J., & Bunte K. (1994). The role of tillage in soil redistribution on hill slopes. European Journal of Soil Science, 45, 469–478. Govers, G., Quine, T. A. Desmet, P. J. J., & Walling, D. E. (1996). The relative contribution of soil tillage and overland flow erosion to soil redistribution on agricultural land. Earth Surface Processes and Landforms, 21, 929–946. Hawley, N., Robbins, J. A., & Eadie B. E. (1986). The partitioning of in fresh water. Geochemica et Cosmochimica Acta, 50, 1127–1131. He, Q., & Walling, D.E. (1997). The distribution of fallout and in undisturbed and cultivated soils. Applied Radiation and Isotopes, 48, 677–690. He, Q., & Walling, D. E. (2000). Calibration of a field-portable gamma detector to obtain in situ measurements of the inventories of cultivated soils and floodplain sediments. Applied Radiation and Isotopes, 52, 865–872. Helfer I. K., & Miller K. M. (1988). Calibration factors for Ge detectors used for field spectrometry. Health Physics, 55, 15–29. IAEA (1998). Use of in the study of soil erosion and sedimentation, IAEA-TFCDOC-1028. Vienna: IAEA. Lambert, C. P., & Walling D. E. (1988). Measurement of channel storage of suspended sediment in a gravel bed river. Catena, 15, 65–80 Lettner, H., Andrási, A., Hubmer, A. K., Lovranich, E., Steger, F., & Zombori, P. (1996). In situ gammaspectrometry intercomparison exercise in Salzburg, Austria. Nuclear Instruments and Methods in Physics Research A, 369, 547–551.

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Miller, K. M., & Heifer, I. K. (1985). In situ measurements of inventory in natural terrain. In Symposium of the Health Physics Society (pp. 243–251). Nicholas, A. P., & Walling, D. E. (1997). Modelling flood hydraulics and overbank deposition on river floodplains. Earth Surface Processes and Landforms, 22, 59–77. Nicholas, A. P., & Walling, D. E. (1998). Numerical modelling of floodplain hydraulics and suspended sediment transport and deposition. Hydrological Processes, 12, 1339–1355. Quine, T. A., Govers, G., Walling, D. E., Zhang, X., Desmet, P. J., Zhang, Y., & Vandaele K. (1997). Erosion processes and landform evolution on agricultural land-new perspectives from caesium-137 measurements and topographic-based erosion modelling. Earth Surface Processes and Landforms, 22, 799–816. Ritchie J. C., & McHenry, J. R. (1990). Application of radioactive fallout cesium-137 for measuring soil erosion and sediment accumulation rates and patterns: a review. Journal of Environmental Quality, 19, 215–233. Sutherland, R. A. (1991). Examination of Caesium-137 areal activities in control (uneroded) locations. Soil Technology, 4, 33–50. Sutherland, R. A. (1994). Spatial variability of and the influence of sampling on estimates of sediment redistribution. Catena, 21, 57–71. Tyler, A. N., Sanderson, D. C. W., & Scott E. M. (1996). Estimating and accounting for source burial through in-situ gamma spectrometry in salt marsh environments. Journal of Environmental Radioactivity, 33, 195–212. Wallbrink P. J., & A. S. Murray (1993). The use of fallout nuclides as indicators of erosion processes. Hydrological Processes, 7, 297–304. Wallbrink P. J., & A. S. Murray (1996a). Distribution and variability of in soils under different surface cover conditions and its potential for describing soil redistribution processes. Water Resource Research, 32, 467–476. Wallbrink P. J., & A. S. Murray (I996b). Determining soil loss using the inventory ratio of excess lead210 to Cesium-137. Soil Science Society America Journal, 60, 1201–1208. Wallbrink, P. J., Olley, J. M., & Murray. A. S. (1994). Measuring soil loss using implications of reference site variability. In L. J. Olive, R. J. Loughran and J. Kesby (Eds.), Variability in stream erosion and sediment transport, IAHS publication 224 (pp. 95–103). Wallingford: IAHS Press. Walling D. E. (1998). Use of and other fallout radionuclides in soil erosion investigations: Progress, problems and prospects. In Use of in the study of soil erosion and sedimentation, IAEA-TECDOC-1028 (pp. 39–62). Vienna: IAEA. Walling, D. E., & He, Q. (1997). Use of fallout in investigations of overbank sediment deposition on river floodplains. Catena, 29, 263–282. Walling, D. E., He, Q., & Blake, W. H. (2000). Use of and measurements to document shortand medium-term rates of water-induced soil erosion on agricultural land. Water Resources Research, 35, 3865–3874. Walling, D. E., He, Q., & Nicholas, A. P. (1996). Floodplains as sediment sinks. In M. G. Anderson, D. E. Walling and P. D. Bates (Eds.), Floodplain processes (pp. 399–440). Chichester: Wiley. Walling, D. E., & Quine, T. A. (1992). The use of caesium-137 measurements in soil erosion surveys. In IAHS publication 210 (pp. 143–152). Wallingford: IAHS Press. Walling, D. E., & Quine T. A. (1995). The use of fallout radionuclides in soil erosion investigations. In Nuclear techniques in soil-plant studies for sustainable agriculture and environmental preservation, IAEA ST1/PUB/947. Vienna: IAEA. Walling, D. E., & Woodward, J. C. (1992). Use of radiometric fingerprints to derive information on suspended sediment sources. In IAHS publication 210 (pp. 153–164). Wallingford, IAHS Press. Wan, G. J., Santschi., P. H., Sturm, M., Farrenkothen, K., Lucek, A., Werth, E., & Schuler C. (1987). Natural and fallout radionuclides as geochemical tracers of sedimentation in Greifensee, Switzerland. Chemical Geology, 63, 181–196. Zombori, P., Nèmeth, I., Andrási, A., & Lettner, H. (1992). In-situ gamma-spectrometric measurement of the contamination in some selected settlements of Byelorussia (BSSR), Ukraine (UkrSSR) and the Russian Federation (RSFSR). Journal of Environmental Radioactivity, 17, 97–106.

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CONTRIBUTING AUTHORS Peter G. Appleby Environmental Radiometric Research Centre Department of Mathematical Sciences University of Liverpool Liverpool United Kingdom Tel: +44 (0)151 794 4020 Fax: +44 (0)151 794 4061 [email protected] Edmundo Garcia-Agudo R. Kaoru Oda, 298 05541-060 Sao Paulo Brazil Tel: 005511 3744-2523 Mobile: 005511 9887 5383 Fax: 005511 3507-0335 [email protected] [email protected] Valentin Golosov Laboratory for Soil Erosion and Fluvial Processes Faculty of Geography Moscow State University Moscow 119899 Russian Federation Tel/Fax: 007095 9395044 [email protected] [email protected] Qingping He CEM9, CEM Centre Block 4, Mountjoy Research Centre University of Durham Stockton Road Durham DH1 3UZ United Kingdom Tel: +44 (191)374 1930 Fax: +44 (191) 374 1900 [email protected]

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Robert Loughran School of Environmental and Life Sciences (Geography) The University of New Castle Callaghan New South Wales 2308 Australia Tel: +61 2 49215084 Fax: +61 2 492215877 [email protected] Daniel Pennock Department of Soil Science University of Saskatchewan Saskatoon Saskatchewan S7N 5A8 Canada Tel: 001 306 966 6852 Fax: 001 306 966 6881 [email protected] Jerry C. Ritchie USDA Agriculture Research Service Hydrology and Remote Sensing Laboratory BARC-West Bldg. 007 Beltsville, MD 20705 United States of America Tel: 001 301 504 8717 Fax: 001 301 504 8931 [email protected] Desmond E. Walling Department of Geography University of Exeter Amory Building Rennes Drive Exeter EX4 4RJ United Kingdom Tel: 0044 1392 263345 Fax: 0044 1392 263342 [email protected] [email protected]

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Peter Wallbrink Environmental Hydrology CSIRO, Division of Land and Water PO Box 1666 Canberra ACT 2601 Australia Tel: 0061 2 62465823 Fax: 0061 2 62465800 [email protected] Felipe Zapata International Atomic Energy Agency (IAEA). Department of Nuclear Sciences and Applications Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture PO Box 100 Wagramer Strasse 5 A-1400 Vienna Austria Tel: 0043 1 2600 21693 Fax: 0043 1 26007 [email protected]