Simulation models are an established method used to investigate processes and solve practical problems in a wide variety of disciplines. Central to the concept of this second edition is the idea that environmental systems are complex, open systems. The authors present the diversity of approaches to dealing with environmental complexity and then encourage readers to make comparisons between these approaches and between different disciplines. Environmental Modelling: Finding Simplicity in Complexity 2nd edition is divided into four main sections: An overview of methods and approaches to modelling. State of the art for modelling environmental processes Tools used and models for management Current and future developments. The second edition evolves from the first by providing additional emphasis and material for those students wishing to specialize in environmental modelling. This edition: Focuses on simplifying complex environmental systems. Reviews current software, tools and techniques for modelling. Gives practical examples from a wide variety of disciplines, e.g. climatology, ecology, hydrology, geomorphology and engineering. Has an associated website containing colour images, links to WWW resources and chapter support pages, including data sets relating to case studies, exercises and model animations. This book is suitable for final year undergraduates and postgraduates in environmental modelling, environmental science, civil engineering and biology who will already be familiar with the subject and are moving on to specialize in the field. It is also designed to appeal to professionals interested in the environmental sciences, including environmental consultants, government employees, civil engineers, geographers, ecologists, meteorologists, and geochemists.

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 Hördur 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