Handbook of Erosion Modelling E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 1076

Veröffentlichungsjahr: 2011

Beschreibung

The movement of sediment and associated pollutants over the landscape and into water bodies is of increasing concern with respect to pollution control, prevention of muddy floods and environmental protection. In addition, the loss of soil on site has implications for declining agricultural productivity, loss of biodiversity and decreased amenity and landscape value. The fate of sediment and the conservation of soil are important issues for land managers and decision-makers. In developing appropriate policies and solutions, managers and researchers are making greater use of erosion models to characterise the processes of erosion and their interaction with the landscape. A study of erosion requires one to think in terms of microseconds to understand the mechanics of impact of a single raindrop on a soil surface, while landscapes form over periods of thousands of years. These processes operate on scales of millimetres for single raindrops to mega-metres for continents. Erosion modelling thus covers quite a lot of ground. This book introduces the conceptual and mathematical frameworks used to formulate models of soil erosion and uses case studies to show how models are applied to a variety of purposes at a range of spatial and temporal scales. The aim is to provide land managers and others with the tools required to select a model appropriate to the type and scale of erosion problem, to show what users can expect in terms of accuracy of model predictions and to provide an appreciation of both the advantages and limitations of models. Problems covered include those arising from agriculture, the construction industry, pollution and climatic change and range in scale from farms to small and large catchments. The book will also be useful to students and research scientists as an up-to-date review of the state-of-art of erosion modelling and, through a knowledge of how models are used in practice, in highlighting the gaps in knowledge that need to be filled in order to develop even better models.

Leseprobe

Contents

Contributors

1 Introduction

References

Part 1 Model Development

2 Model Development: A User’s Perspective

2.1 Introduction

2.2 Some Fundamentals

2.3 Conceptual Framework

2.4 Operating Equations

2.5 Spatial Considerations

2.6 Temporal Considerations

2.7 Temporal and Spatial Scale Interactions

2.8 Testing, Calibration and Validation

2.9 Some Practicalities

Acronyms

References

3 Calibration of Erosion Models

3.1 Introduction

3.2 Calibration at Different Scales

3.3 Sensitivity of Process Models

3.4 Calibration Examples Based on Automatic Parameter Estimation

3.5 Spatial Calibration of Erosion Patterns

3.6 Conclusions

References

4 Dealing with Uncertainty in Erosion Model Predictions

4.1 Why Worry About Uncertainty in Erosion Models?

4.2 Uncertainty About Uncertainty Estimation

4.3 Model Evaluation as Hypothesis Testing in the Face of Uncertainty

4.4 The Information Content of Observations in Constraining Uncertainty

4.5 Review of Uncertainty Analysis of Soil Erosion Models

4.6 Case Study: Using WEPP to Predict UK and US Erosion Data

4.7 The Future

References

5 A Case Study of Uncertainty: Applying GLUE to EUROSEM

5.1 Introduction

5.2 Description of the European Soil Erosion Model (EUROSEM) Structure and Operation

5.3 Methodology

5.4 Results

5.5 Discussion

5.6 Conclusion

Acknowledgements

References

6 Scaling Soil Erosion Models in Space and Time

6.1 Introduction

6.2 Process-Based Scaling in Simple Conditions

6.3 Statistical Scaling in Simple Conditions

6.4 Combined Scaling Approaches and More Complex Conditions

6.5 A Travel-distance Approach to Scaling Erosion Predictions

6.6 Erosion and Landscape Evolution

6.7 Discussion – the Research Frontier in Scaling Erosion Models

6.8 Conclusion

References

7 Misapplications and Misconceptions of Erosion Models

7.1 Introduction

7.2 Misapplications of Soil Erosion Models

7.3 Misconceptions About Erosion Models

7.4 Conclusions

References

Part 2 Model Applications

8 Universal Soil Loss Equation and Revised Universal Soil Loss Equation

8.1 Introduction

8.2 RUSLE

8.3 RUSLE2

8.4 Summary

References

9 Application of WEPP to Sustainable Management of a Small Catchment in Southwest Missouri, US, Under Present Land Use and with Climatic Change

9.1 Description of Problem Area

9.2 Model Criteria

9.3 Models that Might be Applicable

9.4 WEPP Setup and Implementation

9.5 Model Results

9.6 Summary

References

10 Predicting Soil Loss and Runoff from Forest Roads and Seasonal Cropping Systems in Brazil using WEPP

10.1 Introduction

10.2 Case Study 1: Estimation of Erosion Rates on Forest Roads in Brazil

10.3 Case Study 2: Prediction of Water Erosion for Soil and Climatic Conditions in Viçosa Municipality, Minas Gerais State

10.4 Conclusions

Acknowledgements

References

11 Use of GUEST Technology to Parameterize a Physically-Based Model for Assessing Soil Erodibility and Evaluating Conservation Practices in Tropical Steeplands

11.1 Introduction

11.2 Short History of the Development of GUEST

11.3 Theory Outline for GUEST (Type B)

11.4 Subsequent Development of GUEST

11.5 Experimental Methods Commonly Used in GUEST-Based Projects

11.6 Results of Some Field Projects Using GUEST Technology

11.7 Soil Erosion Research at IBSRAM-ASIALAND Sites

11.8 Concluding Comments

References

12 Evaluating Effects of Soil and Water Management and Land Use Change on the Loess Plateau of China using LISEM

12.1 Introduction

12.2 Study Area

12.3 LISEM Model

12.4 LISEM in relation to the Loess Plateau

12.5 Method

12.6 Results

12.7 Discussion

12.8 Conclusions

Acknowledgements

References

13 Modelling the Role of Vegetated Buffer Strips in Reducing Transfer of Sediment from Land to Watercourses

13.1 Introduction

13.2 The Study Area

13.3 Model Selection

13.4 Model Application

13.5 Conclusions

Acknowledgements

References

14 Predicting Impacts of Land Use and Climate Change on Erosion and Sediment Yield in River Basins using SHETRAN

14.1 Introduction

14.2 Model Requirements

14.3 SHETRAN

14.4 Model Calibration and Uncertainty

14.5 Model Fitness for Purpose

14.6 SHETRAN in the Context of Physically-based, Basin-scale Sediment Yield Models

14.7 Experience of Model Application

14.8 Future Research Needs

14.9 Conclusion

Acknowledgements

References

15 Modelling Impacts of Climatic Change: Case Studies using the New Generation of Erosion Models

15.1 Introduction

15.2 Potential Impacts of Climatic Change on Erosion Processes

15.3 Erosion Modelling Approaches and Climatic Change

15.4 Case Studies

15.5 Conclusions, Limitations and Research Needs

References

16 Risk-Based Erosion Assessment: Application to Forest Watershed Management and Planning

16.1 Background

16.3 WEPP Windows

16.4 Online Interfaces

16.5 GIS Interface

16.6 Discussion

16.7 Applicability to Climate Change

16.8 Summary

Acknowledgement

References

17 The Future Role of Information Technology in Erosion Modelling

17.1 Introduction

17.2 Characterization of an Internet Application

17.3 Advantages of Internet-based Applications

17.4 Issues Related to Internet-based Applications

17.5 Examples of Internet Applications

17.6 Example of an Internet-Based Application

17.7 Conclusion

Acknowledgements

References

18 Applications of Long-Term Erosion and Landscape Evolution Models

18.1 A Short History of Landform Evolution Modelling

18.2 Using LEMs as Erosion Models

18.3 Application Case Studies

18.4 Calibration of Landform Evolution Models

18.5 Landform Evolution Model Limitations

18.6 Future Trends in Landform Evolution Modelling

18.7 Conclusions

Acknowledgements

References

19 Gully Erosion: Procedures to Adopt When Modelling Soil Erosion in Landscapes Affected by Gullying

19.1 Why Model Gully Erosion?

19.2 Gully Erosion and Gully Types

19.3 Prediction of Gully Erosion

19.4 Interaction Between Gully Erosion, Hydrological and Other Erosion Processes

Acknowledgements

References

Part 3 Future Developments

20 The Future of Soil Erosion Modelling

References

Index

Colour plates

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Library of Congress Cataloguing-in-Publication Data

Handbook of erosion modelling/edited by R.P.C. Morgan and M.A. Nearing.

p. cm.

Includes bibliographical references and index. ISBN 978-1-4051-9010-7 (cloth)

1. Soil erosion-Simulation methods. I. Morgan, R.P.C. (Royston Philip Charles), 1942II. Nearing, M.A. (Mark A.)

S627.M36H36 2011

631.4′50113-dc22 2010026596

A catalogue record for this book is available from the British Library.

This book is published in the following electronic formats: eBook 9781405190107; Wiley Online Library 9781444328455

Contributors

J.C. BATHURST School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom

K.J. BEVEN Lancaster Environment Centre, University of Lancaster, Lancaster LA1 4YW, United Kingdom; GeoCentrum, Uppsala University, Uppsala, Sweden; ECHO/ISTE, EPFL, Lausanne, Switzerland

G.S. BILOTTA School of Environment and Technology, University of Brighton, Cockcroft Building, Brighton BN2 4GJ, United Kingdom

R.E. BRAZIER School of Geography, University of Exeter, Amory Building, Exeter EX4 4RJ, United Kingdom

K. COUGHLAN P O Box 596, Annerley, Queensland, Australia 4103

S.M. DABNEY USDA-ARS, National Sedimentation Laboratory, 598 McElroy Drive, Oxford, MS 38655, USA

L.K. DEEKS National Soil Resources Institute, Cranfield University, Cranfield, Bedfordshire MK43 0AL, United Kingdom

J.H. DUZANT National Soil Resources Institute, Cranfield University, Cranfield, Bedfordshire MK43 0AL, United Kingdom

W.J. ELLIOT USDA Forest Service, Rocky Mountain Research Station, 1221 South Main Street, Moscow, ID 83843, USA

B. FENTIE Queensland Department of Environment and Resource Management, 80 Meiers Road, Indooroopilly, Queensland, Australia 4068

J. FREER School of Geographical Sciences, University of Bristol, University Road, Bristol BS8 1SS, United Kingdom

D.C. GOODRICH USDA-ARS, Southwest Watershed Research Center, 2000 East Allen Road, Tucson, AZ 85719, USA

G. GOVERS Physical and Regional Geography Research Group, Department of Earth and Environmental Sciences, Katholieke Universiteit Leuven, GEO-Institute, Celestijnenlaan 200E, 3001 Heverlee, Belgium

A.J.T. GUERRA Department of Geography, Institute of Geosciences, Federal University of Rio de Janeiro, Avenida Jose Luiz Ferraz 250, Apto 1706, CEP.22.790-587, Rio de Janeiro, Brazil

D.P. GUERTIN Landscape Studies Program, School of Natural Resources, University of Arizona, Tucson, AZ 85721, USA

P.B. HAIRSINE CSIRO Land and Water Division, G.P.O. Box 1666, Canberra 2601 Australian Capital Territory, Australia

G.R. HANCOCK School of Environment and Life Sciences, Faculty of Science, The University of Newcastle, Callaghan, New South Wales 2308, Australia

R. HESSEL Soil Science Centre, Alterra, Wage ningen University and Research Centre, P O Box 47, 6700 AA Wageningen, The Netherlands

C.J. HUTTON School of Geography, University of Exeter, Amory Building, Exeter EX4 4RJ, United Kingdom

V.G. JETTEN Department of Earth Systems Analysis, International Institute of Geoinformation Science and Earth Observation, Hengelosestraat 99, P O Box 6, 7500 AA, Enschede, The Netherlands

T. KRUEGER School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom

J.M. LAFLEN USDA-ARS (retired), 5784 Highway 9, Buffalo Center, IA 5042, USA

D.T. LIGHTLE USDA-NRCS, National Soil Survey Center, 100 Centennial Mall North, Lincoln, NE 68508-3866, USA

B. LIU School of Geography, Beijing Normal University, 19 Xinwai Street, Beijing 100875, China

M.P. MANETA Geosciences Department, University of Montana, 32 Campus Drive #1296, Missoula, MT 59812, USA

R.K. MISRA Faculty of Engineering and Surveying, University of Southern Queensland, Too woomba, Queensland, Australia 4350

R.P.C. MORGAN National Soil Resources Institute, Cranfield University, Cranfield, Bedfordshire MK43 0AL, United Kingdom

M.A. NEARING USDA-ARS, Southwest Water shed Research Center, 2000 East Allen Road, Tucson, AZ 85719, USA

J.P. NUNES Centre for Environmental and Marine Studies (CESAM), Department of Environment and Planning, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal

A.J. PARSONS Department of Geography, University of Sheffield, Sheffield S10 2TN, United Kingdom

J.W.A. POESEN Physical and Regional Geography Research Group, Department of Earth and Environmental Sciences, Katholieke Universiteit Leuven, GEO-Institute, Celestijnenlaan 200E, B-3001 Heverlee, Belgium

Y. QIU School of Geography, Beijing Normal University, 19 Xinwai Street, Beijing 100875, China

J.N. QUINTON Lancaster Environment Centre, University of Lancaster, Lancaster LA1 4YQ, United Kingdom

K.G. RENARD USDA-ARS, Southwest Watershed Research Center, 2000 East Allen Road, Tucson, AZ 85719-1596, USA

P.R. ROBICHAUD USDA Forest Service, Rocky Mountain Research Station, 1221 South Main Street, Moscow, ID 83843, USA

C.W. ROSE The Griffith School of Environment, Griffith University, Nathan Campus, Brisbane, Queensland, Australia 4111

A. SOARES DA SILVA Federal University of Rio de Janeiro, Rua Hermengarda 151, Apto 906 − Meier. CEP.20710-010 Rio de Janeiro, Brazil

D.B. TORRI IRPI CNR, Via Madonna Alta 126, 06128 Perugia, Italy

T. VANWALLEGHEM Department of Agronomy, Institute for Sustainable Agriculture − CSIC, Finca Alameda del Obispo, Apartado Correos 4084, Córdoba 14080, Spain

J. WAINWRIGHT Department of Geography, University of Sheffield, Sheffield S10 2TN, United Kingdom

G.R. WILLGOOSE School of Engineering, Faculty of Engineering and the Built Environment, The University of Newcastle, Callaghan, New South Wales 2308, Australia

G.A. WOOD Integrated Environmental Systems Institute, Cranfield University, Cranfield, Bedford shire MK43 0AL, United Kingdom

D.C. YODER Biosystems Engineering and Soil Science, University of Tennessee, 2506 E J Chapman Drive, Knoxville, TN 37996-4531, USA

B. YU School of Engineering, Griffith University, Nathan Campus, Brisbane, Queensland, Australia 4111

1

Introduction

R.P.C. MORGAN

National Soil Resources Institute, Cranfield University, Cranfield, Bedfordshire, UK

The movement of sediment and associated pollutants over the landscape and into water bodies is of increasing concern with respect to pollution control, prevention of muddy floods and general environmental protection. This concern exists whether the sediment is derived from farmland, road banks, construction sites, recreation areas or other sources. In today’s environment it is often considered of equal or even greater importance than the effects of loss of soil on-site, with its implications for declining agricultural productivity, loss of biodiversity and decreased amenity and landscape values. With the expected changes in climate over coming decades, there is a need to predict how environmental problems associated with sediment are likely to be affected so that appropriate management systems can be put in place.

Whilst it is possible to instrument a few individual farms and catchments in order to obtain the data to evaluate the current situation and propose best management practices, it is not feasible to study every location on the Earth’s surface in detail. Instead, evaluation and predictive tools need to be applied to assess current problems, predict future trends and provide a scientific base for policy and management decisions. Erosion models can fulfil this function provided that they are robust and used correctly. Despite, or maybe even because of, the vast amount of research over the last 30 years or more on erosion modelling, potential model-users are confronted with a multiplicity of models from which to choose, often with little guidance on which might be the best for particular circumstances or the steps required to apply a selected model to a given situation. Many models have been tested for only a limited range of conditions of climate, soils and land use, and little information is available to enable a user to assess in advance how well a model might perform under different conditions. Models range from empirical to physically- or process-based, and vary considerably in their complexity and the amount of data input required. Very little guidance is available on how accurate that data input has to be, or what effect different levels of accuracy can have on the accuracy of the model output. Further, sediment problems can exist at scales that range from a farmer’s field or a small construction site to the effects of sediment transport and deposition in small and large catchments. Somewhat limited information exists on the range of scales over which different models can operate successfully, leaving the user uncertain on whether a particular model is the most appropriate for a given scale. In the worst case, as a result of a lack of clear guidance, the user may choose a totally inappropriate model.

Users can obtain a list of the leading soil erosion models from the Internet site http://soilerosion.net/doc/models_menu.html. Links are provided to other sites associated specifically with each model from which the software can be downloaded along with the user manual. Whilst the majority of the links are valid and the site is a useful starting point for finding out what models exist, there are some links which are out-of-date and either do not work or are no longer the most appropriate. Clearly no such site can be fully comprehensive, and there will inevitably be some models which are not included. Table 1.1 lists the models which are used in this Handbook together with details of published sources and, where they exist, relevant Internet sites. Knowing which models are available is only a starting point. As indicated above, the user needs advice on how well the models perform and the conditions to which they can be applied. Previous experience with the models is extremely valuable, particularly where the output of several models is compared for the same conditions. Boardman and Favis-Mortlock (1998) discussed the performance of various models when applied to common sets of data at a hillslope scale, and De Roo (1999) presented the results of a similar exercise carried out at a small catchment scale. More recently, Harmon and Doe (2001) provided details of a range of models, physically-based and empirical, which can be used over various spatial and temporal scales to assess the short- and long-term effects of different land management strategies. These publications, however, describe erosion models more from a research than a user perspective. Although they are a source of useful information, they do little to help potential model users to answer the questions raised earlier, or to guide them in the selection of the most appropriate model for a specific application, taking account of the objectives, the environmental conditions and the availability of data. Also, since their publication, there has been an increasing use of geographical information system (GIS) techniques in analysing data for planning and decision-making, and erosion models have been increasingly integrated into geospatial systems, particularly at large catchment and regional scales.

Table 1.1 Erosion models used in the case studies.

Title Sources Case studies EUROSEM Morgan et al. (1998) http://www.es.lancs.ac.uk/people/johnq/EUROSEM.html Chapter 5 GUEST Misra and Rose (1996) Chapter 11 LISEM Jetten and de Roo (2001) http://www.itc.nl/lisei Chapter 12 Modified MMF Morgan and Duzant (2008) Chapter 13 RUSLE Renard et al. (1997) http://fargo.nserl.purdue.edu/rusle2_dataweb/RUSLE2Jndex.htm Chapter 8 SHETRAN Ewen et al. (2000) http://www.ceg.ncl.ac.uk/shetran Chapter 14 SIBERIA Willgoose et al. (1991) http://www.telluricresearch.com/siberia_8.30_manual.pdf Chapter 18 WEPP Flanagan and Nearing (1995) http://topsoil.nserl.purdue.edu/nserlweb/weppmain/wepp.html Chapters 9, 10, 15, 16

The Handbook of Erosion Modelling seeks to address these issues and provide the model user with the tools to evaluate different erosion models and select the most appropriate for a specific purpose, compatible with the type of input data that are available. The book is aimed at model users within government, non-governmental organisations, academic institutions and consultancies involved in environmental assessment, planning, policy and research. The intention is to give existing and potential model users working in the erosion control industry greater confidence in selecting and using models by providing an insight into what users can expect of models in terms of robustness, accuracy and data requirements, and by raising the questions that users need to ask when selecting a model that is appropriate to the type and scale of their problem. It is important that users understand both the advantages and limitations of erosion models.

The Handbook is arranged in two main parts. The first part introduces the user to some important generic issues associated with erosion models. Chapter 2 sets out the various stages that a user should go through when selecting and applying an erosion model, and shows that these are much the same as erosion scientists adopt when developing their models. There is much common ground between model developers and model users, probably more so than most users are aware of. The next four chapters take key issues and discuss them in detail, along with solutions which model users might adopt. Chapter 3 looks at the question of calibration. This is a controversial topic with opinions ranging from those who consider that it is impossible to calibrate the more complex, physically-based models and those who believe that calibration is essential. This chapter is broadly in favour of calibration, showing how it can improve the quality of predictions both in terms of erosion rates and the spatial distribution of erosion. Chapter 4 raises the issue of uncertainty in model predictions. After discussing why we should worry about uncertainty, various approaches are described which can be used to reduce the level of uncertainty. How successful these are depends on the causes of the uncertainty, and model users need to be encouraged to appreciate and understand these. Uncertainty is taken further in Chapter 5, which shows how one approach is used in practice with reference to the application of one specific erosion model. Chapter 6 reviews the issues posed by scale. Many problems faced by users relate to a single scale, be it field, hillslope, small catchment or large catchment, but others need to be addressed at a range of scales. This chapter looks at the problems involved when moving from one scale to another with the difficulty of modelling interconnectivity between hillslope and river systems. At present there are few solutions to the problems that arise when modelling across a range of scales, but several ideas for further research are presented whereby model development and data collection need to become more fully integrated. Chapter 7 shows the importance of choosing the right model for a specific problem and scale, and the implications of using inappropriate models. A frequent occurrence is the misunderstanding by the user of either the problem being addressed or what specific models are able to achieve. Although a dynamic process-based model is often the best choice, there are many situations in which it will not perform better than a simpler statistical model.

Part 2 of the Handbook looks at specific applications and shows how models are used in practice. Each chapter is really a case study in which a problem commonly faced by environmental planners, consultants and managers is presented. An appropriate model is then chosen and the user is taken through the various steps involved in setting-up and applying the model and interpreting its output. Table 1.2 lists the applications under broad subject headings and for each one identifies the relevant chapter and the spatial scale (erosion plot, field, catchment, region) of the problem being considered. Additional information is provided on the temporal scale, which ranges from individual events to mean annual conditions and long-term landform evolution.

Taking each chapter in turn, Chapter 8 reviews the issues typically faced by field officers of the Natural Resources Conservation Service of the US when predicting erosion from agricultural land and planning soil protection measures. Chapter 9 takes a specific example of a small watershed in southwest Missouri and shows how modelling can assist in designing a strategy for sustainable management under both present land use and climatic change. In Chapter 10, modelling is used to predict rates of soil loss in Brazil from hillslopes on forest roads in Sao Paulo State and from agricultural land under different management systems in Minas Gerais State. Chapter 11 examines how a physically-based erosion model can be used to assess soil erodibility and evaluate different soil conservation practices at four different locations on tropical steeplands, one in China, one in Malaysia and two in Thailand.

Table 1.2 Issues covered by the erosion modelling applications in the Handbook, together with their spatial and temporal scales.

Numbers in each cell refer to the chapter, and the letters indicate the temporal scale of model outputs in the applications described (E, event; D, daily; MM, mean monthly; A, annual; MA, mean annual; SP, set period of time; R, return period; LE, long-term landform evolution).

The evaluation of sediment yield from a small catchment in a highly erodible area is the focus of Chapter 12, based on a case study on the loess plateau of China. Chapter 13 addresses a problem at a very different scale, namely the transfer of sediment from individual fields to watercourses in southwest England. Chapter 14 returns to the catchment scale, using a model to examine the impacts of land use and climate change on erosion and sediment yield in small river basins where hillslope erosion, river channel and bank erosion and landslides are all important components of sediment production. Chapter 15 is also concerned with assessing the impacts of climate change, but this time over a range of spatial and temporal scales from hillslope to regional and continental. There is no single model that can apply to all situations, and several models are reviewed. Chapter 16 looks at the risk of erosion in forested areas in Montana, US, following disturbance either by timber harvesting or wildfire. Chapter 17 discusses the potential of the Internet as both a source of data and a vehicle for operating erosion models to address problems of environmental management. Chapter 18 examines the role of longer-term landscape evolution models (LEMs) for designing hillslope landscapes to encapsulate and contain mining waste. Chapter 19 reviews the question of modelling gully erosion. Although there is no specific gully erosion model that can be recommended, various approaches that a user can adopt are described.

The Handbook ends with a review of the state-of-art of erosion modelling, as illustrated by the case studies, and discusses the developments that users can expect in the near future. These include the inclusion of more models within geospatial frameworks, associated improvements to modelling across different scales, and the increasing use of web-based approaches and risk-based applications. It is hoped that, by combining a general review of the principles of erosion modelling with examples of model applications across a range of management issues, the Handbook will enable potential users to employ models in a more informed way. Hopefully, managers, decision-makers and policy-makers within the erosion control industry will be encouraged to make more use of models to evaluate present situations, the impacts of control measures and future policies. In addition, model developers may be encouraged to provide better information to model users about the suitability and limitations of their models and what levels of accuracy in prediction they are likely to achieve.

References

Boardman, J. & Davis-Mortlock, D. (1998) Modelling Soil Erosion by Water. NATO ASI Series: Series 1, Global Environmental Change, Vol. 55. SpringerVerlag, Berlin.

De Roo, A.P.J. (1999) Soil erosion modelling at the catchment scale. Catena37 (3–4).

Ewen, J., Parkin, G. & O’Connell, P.E. (2000) SHETRAN: distributed river basin flow and transport modeling system. Journal of Hydrologic Engineering ASCE5: 250–258.

Flanagan, D.C. & Nearing, M.A. (1995) USDA Water Erosion Prediction Project: Hillslope Profile and Watershed Model Documentation. USDA-ARS National Soil Erosion Laboratory Report No. 10.

Harman, R.S. & Doe III, W.W. (2001) Landscape Erosion and Evolution Modeling. Kluwer, New York.

Jetten, V. & de Roo, A.P.J. (2001) Spatial analysis of erosion conservation measures with LISEM. In Harmon, R.S. & Doe III, W.W. (eds), Landscape Erosion and Evolution Modeling. Kluwer, New York: 429–45.

Misra, R. & Rose, C.W. (1996) Application and sensitivity analysis of process-based erosion model GUEST. European Journal of Soil Science47: 593–604.

Morgan, R.P.C. & Duzant, J.H. (2008) Modified MMF (Morgan-Morgan-Finney) model for evaluating effects of crops and vegetation cover on soil erosion. Earth Surface Processes and Landforms33: 90–106.

Morgan, R.P.C., Quinton, J.N., Smith, R.E., et al. (1998) The European Soil Erosion Model (EUROSEM): a dynamic approach for predicting sediment transport from fields and small catchments. Earth Surface Processes and Landforms23: 527–44.

Renard, K.G., Foster, G.R., Weesies, G.A., et al. (1997) Predicting soil erosion by water. A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). USDA Agricultural Handbook No. 703.

Willgoose, G., Bras, R.L. & Rodriguez-I turbe, I. (1991) A physically based coupled network growth and hillslope evolution model: 1. Theory. Water Resources Research27: 1671–84.

Part 1

Model Development

2

Model Development: A User’s Perspective

R.P.C. MORGAN

National Soil Resources Institute, Cranfield University, Cranfield, Bedfordshire, UK

2.1 Introduction

The last 40 years or so have witnessed the development of a very large number of erosion models operating at different scales and different levels of complexity, with huge variations in the quantity and type of input data required and, at least according to the model developers, covering a wide range of applications. A potential user of erosion models is therefore faced with a bewildering choice when attempting to select the best model for a particular purpose. All too often, the choice of a model is made more difficult because the user is unable to define the problem precisely enough to state what output is required; for example, whether knowledge of erosion rates is needed as a mean annual value or for a specific year, season, month, day or storm, and if the latter, whether it is a storm total or a value at the storm peak which is wanted. The user is sometimes uncertain whether this information is needed for a field, a particular hillslope or a catchment. Perhaps knowledge of actual erosion rates is not needed at all, and all that is required is an idea of the location of erosion within the landscape or an indication of the time of year that it is most likely to occur. Even when the requirements are clearly defined, the user is still confronted with the difficulty that most models are not accompanied by clear statements of the purposes and conditions for which they were designed, their limitations or indicators of the accuracy of their output.

This chapter discusses how the user might deal with these issues. It does so by proposing that users should adopt the same procedures in analysing their problem as model developers adopt in constructing their models. By understanding how model developers operate and following a common methodology, users will be better equipped to decide what questions need to be asked when selecting a model to meet their specific objectives. These questions can then be formulated into a set of design requirements that a model must meet in order to be suitable. Users will also gain an appreciation of whether they will be able to operate the model software unaided, or whether they will need to seek expert advice in how to set up the model to meet their requirements and interpret the results. Table 2.1 sets out the steps followed by model developers and lists the main points that need to be considered at each stage.

2.2 Some Fundamentals

Any model is a simplification of reality and, for some users, this creates an immediate theoretical issue. How can a problem associated with erosion in a particular location be predicted by a model that describes erosion in a generic way? Surely the only way to deal effectively with a problem in a given catchment or at a given field site is to undertake detailed field observations and measurements of erosion and its controlling factors at that site and, based on an analysis of the results, to select appropriate measures to control the problem? Unfortunately, such detailed field measurements are often very costly and must be carried out over many years, probably ten or more, in order to collect representative data. In contrast, many problems must be addressed immediately and cannot wait for a solution some years later by which time considerable environmental damage may have occurred. The value of an erosion model is that it can be applied now. The question that arises, however, is how simple or complex it needs to be for it to be valid.

Table 2.1 Stages in model development.

Stage Requirements Objectives Definition of problem Required temporal and spatial scales Required output, e.g. rates/location of erosion/deposition Required level of accuracy of prediction