Environmental Modelling
Finding Simplicity in Complexity
2. Auflage März 2013
494 Seiten, Hardcover
Wiley & Sons Ltd
ISBN:
978-0-470-74911-1
John Wiley & Sons
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.
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
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
"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)
"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)
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.
Mark Mulligan is Reader within the Dept of Geography at King's College, London.
