Environmental Modelling Finding Simplicity in Complexity 2nd Edition by John Wainwright, Mark Mulligan 1118351479 9781118351475

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ISBN 10: 1118351479 

ISBN 13: 9781118351475

Author: John Wainwright, Mark Mulligan

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 2^nd 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.

Table of contents:

Part I Model Building

1 Introduction
John Wainwright and Mark Mulligan
1.1 Introduction
1.2 Why model the environment?
1.3 Why simplicity and complexity?
1.4 How to use this book
1.5 The book’s web site
References

2 Modelling and Model Building
Mark Mulligan and John Wainwright
2.1 The role of modelling in environmental research
2.2 Approaches to model building: chickens, eggs, models and parameters?
2.3 Testing models
2.4 Sensitivity analysis and its role
2.5 Errors and uncertainty
2.6 Conclusions
References

3 Time Series: Analysis and Modelling
Bruce D. Malamud and Donald L. Turcotte
3.1 Introduction
3.2 Examples of environmental time series
3.3 Frequency-size distribution of values in a time series
3.4 White noises and Brownian motions
3.5 Persistence
3.6 Other time-series models
3.7 Discussion and summary
References

4 Non-Linear Dynamics Self-Organization and Cellular Automata Models
David Favis-Mortlock
4.1 Introduction
4.2 Self-organization in complex systems
4.3 Cellular automaton models
4.4 Case study: modelling rill initiation and growth
4.5 Summary and conclusions
4.6 Acknowledgements
References

5 Spatial Modelling and Scaling Issues
Xiaoyang Zhang, Nick A. Drake and John Wainwright
5.1 Introduction
5.2 Scale and scaling
5.3 Causes of scaling problems
5.4 Scaling issues of input parameters and possible solutions
5.5 Methodology for scaling physically based models
5.6 Scaling land-surface parameters for a soil-erosion model: a case study
5.7 Conclusion
References

6 Environmental Applications of Computational Fluid Dynamics
N.G. Wright and D.M. Hargreaves
6.1 Introduction
6.2 CFD fundamentals
6.3 Applications of CFD in environmental modelling
6.4 Conclusions
References

7 Data-Based Mechanistic Modelling and the Emulation of Large Environmental System Models
Peter C. Young and David Leedal
7.1 Introduction
7.2 Philosophies of science and modelling
7.3 Statistical identification, estimation and validation
7.4 Data-based mechanistic (DBM) modelling
7.5 The statistical tools of DBM modelling
7.6 Practical example
7.7 The reduced-order modelling of large computer-simulation models
7.8 The dynamic emulation of large computer-simulation models
7.9 Conclusions
References

8 Stochastic versus Deterministic Approaches
Philippe Renard, Andres Alcolea and David Ginsbourger
8.1 Introduction
8.2 A philosophical perspective
8.3 Tools and methods
8.4 A practical illustration in Oman
8.5 Discussion
References

Part II The State of The Art in Environmental Modelling

9 Climate and Climate-System Modelling
L.D. Danny Harvey
9.1 The complexity
9.2 Finding the simplicity
9.3 The research frontier
9.4 Online material
References

10 Soil and Hillslope (Eco)Hydrology
Andrew J. Baird
10.1 Hillslope e-c-o-hydrology?
10.2 Tyger tyger…
10.3 Nobody loves me everybody hates me…
10.4 Memories
10.5 I’ll avoid you as long as I can?
10.6 Acknowledgements
References

11 Modelling Catchment and Fluvial Processes and their Interactions
Mark Mulligan and John Wainwright
11.1 Introduction: connectivity in hydrology
11.2 The complexity
11.3 The simplicity
11.4 Concluding remarks
References

12 Modelling Plant Ecology
Rosie A. Fisher
12.1 The complexity
12.2 Finding the simplicity
12.3 The research frontier
12.4 Case study
12.5 Conclusions
12.6 Acknowledgements
References

13 Spatial Population Models for Animals
George L.W. Perry and Nick R. Bond
13.1 The complexity: introduction
13.2 Finding the simplicity: thoughts on modelling spatial ecological systems
13.3 The research frontier: marrying theory and practice
13.4 Case study: dispersal dynamics in stream ecosystems
13.5 Conclusions
13.6 Acknowledgements
References

14 Vegetation and Disturbance
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
14.2 The model simplification: simulation of plant growth under grazing and after fire
14.3 New developments in ecological modelling
14.4 Interactions of fire and grazing on plant competition: field experiment and modelling applications
14.5 Conclusions
14.6 Acknowledgements
References

15 Erosion and Sediment Transport: Finding Simplicity in a Complicated Erosion Model
Richard E. Brazier
15.1 The complexity
15.2 Finding the simplicity
15.3 WEPP – The Water Erosion Prediction Project
15.4 MIRSED – a Minimum Information Requirement version of WEPP
15.5 Data requirements
15.6 Observed data describing erosion rates
15.7 Mapping predicted erosion rates
15.8 Comparison with published data
15.9 Conclusions
References

16 Landslides Rockfalls and Sandpiles
Stefan Hergarten
References

17 Finding Simplicity in Complexity in Biogeochemical Modelling
Hördur V. Haraldsson and Harald Sverdrup
17.1 Introduction to models
17.2 The basic classification of models
17.3 A ‘good’ and a ‘bad’ model
17.4 Dare to simplify
17.5 Sorting
17.6 The basic path
17.7 The process
17.8 Biogeochemical models
17.9 Conclusion
References

18 Representing Human Decision-Making in Environmental Modelling
James D.A. Millington, John Wainwright and Mark Mulligan
18.1 Introduction
18.2 Scenario approaches
18.3 Economic modelling
18.4 Agent-based modelling
18.5 Discussion
References

19 Modelling Landscape Evolution
Peter van der Beek
19.1 Introduction
19.2 Model setup and philosophy
19.3 Geomorphic processes and model algorithms
19.4 Model testing and calibration
19.5 Coupling of models
19.6 Model application: some examples
19.7 Conclusions and outlook
References

Part III Models for Management

20 Models Supporting Decision-Making and Policy Evaluation
Mark Mulligan
20.1 The complexity: making decisions and implementing policy in the real world
20.2 The simplicity: state-of-the-art policy-support systems
20.3 Addressing the remaining barriers
20.4 Conclusions
20.5 Acknowledgements
References

21 Models in Policy Formulation and Assessment: The WadBOS Decision-Support System
Guy Engelen
21.1 Introduction
21.2 Functions of WadBOS
21.3 Decision-support systems
21.4 Building the integrated model
21.5 The integrated WadBOS model
21.6 The toolbase
21.7 The database
21.8 The user-interface
21.9 Discussion and conclusions
21.10 Acknowledgments
References

22 Soil Erosion and Conservation
Mark A. Nearing
22.1 The problem
22.2 The approaches
22.3 The contributions of modelling
22.4 Lessons and implications
22.5 Acknowledgements
References

23 Forest-Management Modelling
Mark J. Twery and Aaron R. Weiskittel
23.1 The issue
23.2 The approaches
23.3 Components of empirical models
23.4 Implementation and use
23.5 Example model
23.6 Lessons and implications
References

24 Stability and Instability in the Management of Mediterranean Desertification
John B. Thornes
24.1 Introduction
24.2 Basic propositions
24.3 Complex interactions
24.4 Climate gradient and climate change
24.5 Implications
24.6 Plants
24.7 Lessons and implications
References

25 Operational European Flood Forecasting
Hannah Cloke, Florian Pappenberger, Jutta Thielen and Vera Thiemig
25.1 The problem: providing early flood warning at the European scale
25.2 Flood forecasting at the European scale: the approaches
25.3 The European Flood Alert System (EFAS)
25.4 Lessons and implications
References

26 Assessing Model Adequacy
Michael Goldstein, Allan Seheult and Ian Vernon
26.1 Introduction
26.2 General issues in assessing model adequacy
26.3 Assessing model adequacy for a fast rainfall-runoff model
26.4 Slow computer models
26.5 Acknowledgements
References

Part IV Current and Future Developments

27 Pointers for the Future
John Wainwright and Mark Mulligan
27.1 What have we learned?
27.2 Research directions
27.3 Technological directions
27.4 Is it possible to find simplicity in complexity?

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Tags: John Wainwright, Mark Mulligan, Modelling, Simplicity