Environmental Modelling

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)

Editors John Wainwright, Department of Geography, Durham University, UK Mark Mulligan, Department of Geography, King's College London, UK

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 books 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 Ill 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