Environmental Modelling
Finding Simplicity in Complexity
(Sprache: Englisch)
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...
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Klappentext zu „Environmental Modelling “
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.
Inhaltsverzeichnis zu „Environmental Modelling “
Preface to the Second Edition, xiiiPreface 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
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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<
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<
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Autoren-Porträt
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.
Bibliographische Angaben
- 2012, 2. Aufl., 494 Seiten, Maße: 19,3 x 24,9 cm, Gebunden, Englisch
- Herausgegeben: John Wainwright, Mark Mulligan
- Verlag: Wiley & Sons
- ISBN-10: 0470749113
- ISBN-13: 9780470749111
- Erscheinungsdatum: 01.04.2013
Sprache:
Englisch
Rezension zu „Environmental Modelling “
"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)
Pressezitat
"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)
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