Environmental Modelling
Finding Simplicity in Complexity
Herausgegeben von Wainwright, John; Mulligan, Mark
Environmental Modelling
Finding Simplicity in Complexity
Herausgegeben von Wainwright, John; Mulligan, Mark
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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…mehr
- Urban Pollution177,99 €
- Murray GrayGeodiversity168,99 €
- Ioannis VogiatzakisMediterranean Mountain Environments153,99 €
- Ioannis VogiatzakisMediterranean Mountain Environments107,99 €
- Andrew S. GoudieHuman Impact on the Natural Environment75,99 €
- Global Environmental Issues87,99 €
- Global Environmental Issues169,99 €
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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.
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- Produktdetails
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 14574911000
- 2. Aufl.
- Seitenzahl: 496
- Erscheinungstermin: März 2013
- Englisch
- Abmessung: 254mm x 189mm x 35mm
- Gewicht: 990g
- ISBN-13: 9780470749111
- ISBN-10: 0470749113
- Artikelnr.: 36468062
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 14574911000
- 2. Aufl.
- Seitenzahl: 496
- Erscheinungstermin: März 2013
- Englisch
- Abmessung: 254mm x 189mm x 35mm
- Gewicht: 990g
- ISBN-13: 9780470749111
- ISBN-10: 0470749113
- Artikelnr.: 36468062
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
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
"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)