Table of Contents

Preface to the Second Edition, xiii Preface to the First Edition, xv List of Contributors, xvii PART I MODEL BUILDING, 1 1 Introduction, 3 John Wainwright and Mark Mulligan 1.1 Introduction, 3 1.2 Why model the environment?, 3 1.3 Why simplicity and complexity?, 3 1.4 How to use this book, 5 1.5 The book s web site, 6 References, 6 2 Modelling and Model Building, 7 Mark Mulligan and John Wainwright 2.1 The role of modelling in environmental research, 7 2.2 Approaches to model building: chickens, eggs, models and parameters?, 12 2.3 Testing models, 16 2.4 Sensitivity analysis and its role, 18 2.5 Errors and uncertainty, 20 2.6 Conclusions, 23 References, 24 3 Time Series: Analysis and Modelling, 27 Bruce D. Malamud and Donald L. Turcotte 3.1 Introduction, 27 3.2 Examples of environmental time series, 28 3.3 Frequency-size distribution of values in a time series, 30 3.4 White noises and Brownian motions, 32 3.5 Persistence, 34 3.6 Other time-series models, 41 3.7 Discussion and summary, 41 References, 42 4 Non-Linear Dynamics, Self-Organization and Cellular Automata Models, 45 David Favis-Mortlock 4.1 Introduction, 45 4.2 Self-organization in complex systems, 47 4.3 Cellular automaton models, 53 4.4 Case study: modelling rill initiation and growth, 56 4.5 Summary and conclusions, 61 4.6 Acknowledgements, 63 References, 63 5 Spatial Modelling and Scaling Issues, 69 Xiaoyang Zhang, Nick A. Drake and John Wainwright 5.1 Introduction, 69 5.2 Scale and scaling, 70 5.3 Causes of scaling problems, 71 5.4 Scaling issues of input parameters and possible solutions, 72 5.5 Methodology for scaling physically based models, 76 5.6 Scaling land-surface parameters for a soil-erosion model: a case study, 82 5.7 Conclusion, 84 References, 87 6 Environmental Applications of Computational Fluid Dynamics, 91 N.G. Wright and D.M. Hargreaves 6.1 Introduction, 91 6.2 CFD fundamentals, 92 6.3 Applications of CFD in environmental modelling, 97 6.4 Conclusions, 104 References, 106 7 Data-Based Mechanistic Modelling and the Emulation of Large Environmental System Models, 111 Peter C. Young and David Leedal 7.1 Introduction, 111 7.2 Philosophies of science and modelling, 113 7.3 Statistical identification, estimation and validation, 113 7.4 Data-based mechanistic (DBM) modelling, 115 7.5 The statistical tools of DBM modelling, 117 7.6 Practical example, 117 7.7 The reduced-order modelling of large computer-simulation models, 122 7.8 The dynamic emulation of large computer-simulation models, 123 7.9 Conclusions, 128 References, 129 8 Stochastic versus Deterministic Approaches, 133 Philippe Renard, Andres Alcolea and David Ginsbourger 8.1 Introduction, 133 8.2 A philosophical perspective, 135 8.3 Tools and methods, 137 8.4 A practical illustration in Oman, 143 8.5 Discussion, 146 References, 148 PART II THE STATE OF THE ART IN ENVIRONMENTAL MODELLING, 151 9 Climate and Climate-System Modelling, 153 L.D. Danny Harvey 9.1 The complexity, 153 9.2 Finding the simplicity, 154 9.3 The research frontier, 159 9.4 Online material, 160 References, 163 10 Soil and Hillslope (Eco)Hydrology, 165 Andrew J. Baird 10.1 Hillslope e-c-o-hydrology?, 165 10.2 Tyger, tyger..., 169 10.3 Nobody loves me, everybody hates me..., 172 10.4 Memories, 176 10.5 I ll avoid you as long as I can?, 178 10.6 Acknowledgements, 179 References, 180 11 Modelling Catchment and Fluvial Processes and their Interactions, 183 Mark Mulligan and John Wainwright 11.1 Introduction: connectivity in hydrology, 183 11.2 The complexity, 184 11.3 The simplicity, 196 11.4 Concluding remarks, 201 References, 201 12 Modelling Plant Ecology, 207 Rosie A. Fisher 12.1 The complexity, 207 12.2 Finding the simplicity, 209 12.3 The research frontier, 212 12.4 Case study, 213 12.5 Conclusions, 217 12.6 Acknowledgements, 217 References, 218 13 Spatial Population Models for Animals, 221 George L.W. Perry and Nick R. Bond 13.1 The complexity: introduction, 221 13.2 Finding the simplicity: thoughts on modelling spatial ecological systems, 222 13.3 The research frontier: marrying theory and practice, 227 13.4 Case study: dispersal dynamics in stream ecosystems, 228 13.5 Conclusions, 230 13.6 Acknowledgements, 232 References, 232 14 Vegetation and Disturbance, 235 Stefano Mazzoleni, Francisco Rego, Francesco Giannino, Christian Ernest Vincenot, Gian Boris Pezzatti and Colin Legg 14.1 The system complexity: effects of disturbance on vegetation dynamics, 235 14.2 The model simplification: simulation of plant growth under grazing and after fire, 237 14.3 New developments in ecological modelling, 240 14.4 Interactions of fire and grazing on plant competition: field experiment and modelling applications, 242 14.5 Conclusions, 247 14.6 Acknowledgements, 248 References, 248 15 Erosion and Sediment Transport: Finding Simplicity in a Complicated Erosion Model, 253 Richard E. Brazier 15.1 The complexity, 253 15.2 Finding the simplicity, 253 15.3 WEPP The Water Erosion Prediction Project, 254 15.4 MIRSED a Minimum Information Requirement version of WEPP, 256 15.5 Data requirements, 258 15.6 Observed data describing erosion rates, 259 15.7 Mapping predicted erosion rates, 259 15.8 Comparison with published data, 262 15.9 Conclusions, 264 References, 264 16 Landslides, Rockfalls and Sandpiles, 267 Stefan Hergarten References, 275 17 Finding Simplicity in Complexity in Biogeochemical Modelling, 277 Hordur V. Haraldsson and Harald Sverdrup 17.1 Introduction to models, 277 17.2 The basic classification of models, 278 17.3 A good and a bad model, 278 17.4 Dare to simplify, 279 17.5 Sorting, 280 17.6 The basic path, 282 17.7 The process, 283 17.8 Biogeochemical models, 283 17.9 Conclusion, 288 References, 288 18 Representing Human Decision-Making in Environmental Modelling, 291 James D.A. Millington, John Wainwright and Mark Mulligan 18.1 Introduction, 291 18.2 Scenario approaches, 294 18.3 Economic modelling, 297 18.4 Agent-based modelling, 300 18.5 Discussion, 304 References, 305 19 Modelling Landscape Evolution, 309 Peter van der Beek 19.1 Introduction, 309 19.2 Model setup and philosophy, 310 19.3 Geomorphic processes and model algorithms, 313 19.4 Model testing and calibration, 318 19.5 Coupling of models, 321 19.6 Model application: some examples, 321 19.7 Conclusions and outlook, 324 References, 327 PART III MODELS FOR MANAGEMENT, 333 20 Models Supporting Decision-Making and Policy Evaluation, 335 Mark Mulligan 20.1 The complexity: making decisions and implementing policy in the real world, 335 20.2 The simplicity: state-of-the-art policy-support systems, 341 20.3 Addressing the remaining barriers, 345 20.4 Conclusions, 347 20.5 Acknowledgements, 347 References, 347 21 Models in Policy Formulation and Assessment: The WadBOS Decision-Support System, 349 Guy Engelen 21.1 Introduction, 349 21.2 Functions of WadBOS, 350 21.3 Decision-support systems, 351 21.4 Building the integrated model, 351 21.5 The integrated WadBOS model, 354 21.6 The toolbase, 359 21.7 The database, 359 21.8 The user-interface, 360 21.9 Discussion and conclusions, 362 21.10 Acknowledgments, 363 References, 363 22 Soil Erosion and Conservation, 365 Mark A. Nearing 22.1 The problem, 365 22.2 The approaches, 367 22.3 The contributions of modelling, 369 22.4 Lessons and implications, 375 22.5 Acknowledgements, 376 References, 376 23 Forest-Management Modelling, 379 Mark J. Twery and Aaron R. Weiskittel 23.1 The issue, 379 23.2 The approaches, 379 23.3 Components of empirical models, 383 23.4 Implementation and use, 386 23.5 Example model, 390 23.6 Lessons and implications, 390 References, 391 24 Stability and Instability in the Management of Mediterranean Desertification, 399 John B. Thornes 24.1 Introduction, 399 24.2 Basic propositions, 400 24.3 Complex interactions, 403 24.4 Climate gradient and climate change, 408 24.5 Implications, 409 24.6 Plants, 410 24.7 Lessons and implications, 411 References, 411 25 Operational European Flood Forecasting, 415 Hannah Cloke, Florian Pappenberger, Jutta Thielen and Vera Thiemig 25.1 The problem: providing early flood warning at the European scale, 415 25.2 Flood forecasting at the European scale: the approaches, 416 25.3 The European Flood Alert System (EFAS), 422 25.4 Lessons and implications, 429 References, 430 26 Assessing Model Adequacy, 435 Michael Goldstein, Allan Seheult and Ian Vernon 26.1 Introduction, 435 26.2 General issues in assessing model adequacy, 435 26.3 Assessing model adequacy for a fast rainfall-runoff model, 438 26.4 Slow computer models, 446 26.5 Acknowledgements, 449 References, 449 PART IV CURRENT AND FUTURE DEVELOPMENTS, 451 27 Pointers for the Future, 453 John Wainwright and Mark Mulligan 27.1 What have we learned?, 453 27.2 Research directions, 459 27.3 Technological directions, 459 27.4 Is it possible to find simplicity in complexity?, 463 References, 463 Index, 465

About the Author

John Wainwright is Professor in the Department of Geography at Durham University. Mark Mulligan is Reader within the Dept of Geography at King's College, London.

Reviews

Those caveats aside, this book will provide an interesting and stimulating read for scientists with some familiarity with modelling who want to extend their understanding and to see how modelling has been usefully applied across a very wide range of problems in environmental science. (European Journal of Soil Science, 1 December 2013) Summing Up: Recommended. Graduate students, researchers/faculty, and professionals/practitioners. (Choice, 1 January 2014) To conclude, the book offers important information on how to use models to develop our understanding of the processes that form the environment around us. (Environmental Engineering and Management Journal, 1 April 2013)