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Environmental Modelling: Finding Simplicity in Complexity, 2nd Edition

John Wainwright (Editor), Mark Mulligan (Editor)
ISBN: 978-0-470-74911-1
494 pages
April 2013
Environmental Modelling: Finding Simplicity in Complexity, 2nd Edition (0470749113) cover image

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:

  1. An overview of methods and approaches to modelling.
  2. State of the art for modelling environmental processes
  3. Tools used and models for management
  4. 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.

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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

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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.
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“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)

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