Cover -- Title Page -- Copyright -- Contents -- Preface -- Preface to the First Edition -- List of Contributors -- Part I Model Building -- Chapter 1 Introduction -- 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 -- Chapter 2 Modelling and Model Building -- 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 -- Chapter 3 Time Series: Analysis and Modelling -- 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 -- Chapter 4 Non-Linear Dynamics, Self-Organization and Cellular Automata Models -- 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 -- Chapter 5 Spatial Modelling and Scaling Issues -- 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 -- Chapter 6 Environmental Applications of Computational Fluid Dynamics -- 6.1 Introduction -- 6.2 CFD fundamentals -- 6.3 Applications of CFD in environmental modelling -- 6.4 Conclusions -- References.

Chapter 7 Data-Based Mechanistic Modelling and the Emulation of Large Environmental System Models -- 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 -- Chapter 8 Stochastic versus Deterministic Approaches -- 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 -- Chapter 9 Climate and Climate-System Modelling -- 9.1 The complexity -- 9.2 Finding the simplicity -- 9.3 The research frontier -- 9.4 Online material -- References -- Chapter 10 Soil and Hillslope (Eco)Hydrology -- 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 -- Chapter 11 Modelling Catchment and Fluvial Processes and their Interactions -- 11.1 Introduction: connectivity in hydrology -- 11.2 The complexity -- 11.3 The simplicity -- 11.4 Concluding remarks -- References -- Chapter 12 Modelling Plant Ecology -- 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 -- Chapter 13 Spatial Population Models for Animals -- 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 -- Chapter 14 Vegetation and Disturbance -- 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 -- Chapter 15 Erosion and Sediment Transport: Finding Simplicity in a Complicated Erosion Model -- 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 -- Chapter 16 Landslides, Rockfalls and Sandpiles -- References -- Chapter 17 Finding Simplicity in Complexity in Biogeochemical Modelling -- 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 -- Chapter 18 Representing Human Decision-Making in Environmental Modelling -- 18.1 Introduction -- 18.2 Scenario approaches -- 18.3 Economic modelling -- 18.4 Agent-based modelling -- 18.5 Discussion -- References -- Chapter 19 Modelling Landscape Evolution -- 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 -- Chapter 20 Models Supporting Decision-Making and Policy Evaluation -- 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 -- Chapter 21 Models in Policy Formulation and Assessment: The WadBOS Decision-Support System -- 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 -- Chapter 22 Soil Erosion and Conservation -- 22.1 The problem -- 22.2 The approaches -- 22.3 The contributions of modelling -- 22.4 Lessons and implications -- 22.5 Acknowledgements -- References -- Chapter 23 Forest-Management Modelling -- 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 -- Chapter 24 Stability and Instability in the Management of Mediterranean Desertification -- 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 -- Chapter 25 Operational European Flood Forecasting -- 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 -- Chapter 26 Assessing Model Adequacy -- 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 -- Chapter 27 Pointers for the Future -- 27.1 What have we learned? -- 27.2 Research directions -- 27.3 Technological directions -- 27.4 Is it possible to find simplicity in complexity? -- References -- Index.