Rules for responsible modeling - 4th edition

Now available from CHI, this is the fourth edition (2003) of a popular and well-used book that provides important background to the functions and attributes of the PCSWMM program. Seventeen chapters (listed below) are presented, all peer-reviewed for relevance and clarity. The 303 page book is presented in a beautiful, glossy, wire bound, soft cover format complete with references and glossary.

James, William, 1937- , Editor

Compiled and published by CHI, Guelph, Ontario, Canada.

International Standard Book Number 0-9683681-5-8

CHI Catalog Number: R184

1. Introduction 1

1.1 What is a model? 2

1.2 Introduction to the development of deterministic models 5

1.3 Newtonian mechanics, partial differential equations, finite difference equations and computer programs 6

1.4 When to use a model 10

1.5 How a model relates to design problems 11

1.6 Concluding remarks 13

References 14

Bibliography 14

2. How to Discretize and Disaggregate, and More on Complexity 15

2.1 Introduction 15

2.2 The procedure of discretization 15

2.3 Introduction to spatial discretization 18

2.4 Introduction to temporal resolution 19

2.5 More introductory discussion of model complexity 20

2.6 Brief introduction to data collection 28

2.7 Introduction to graphical data management 29

2.8 Summary 30

References 31

Bibliography 31

3. Reliability of Input Parameters, Good Input Data Files and File Management. 33

3.1 Introduction 33

3.2 Short-term time series dataset for calibration. 34

3.3 Long-term dataset for inference. 34

3.4 Categories of uncertain data 35

3.5 Some samples of well-documented data files 52

3.6 Urban water systems GIS concepts 58

3.7 Summary 60

References 60

Bibliography 60

4. Optimal Model Complexity 61

4.1 Introduction 61

4.2 Earlier work on complexity 63

4.3 Choosing the best complexity 65

4.4 Distinguishing between level of detail and complexity 66

4.5 Objective measures of model complexity 68

4.6 Data availability and model complexity 70

4.7 Complexity, reliability and uncertainty 71

4.8 Relationship between complexity and available data 73

4.9 Concluding remarks 75

References 76

Bibliography 77

5. Continuous Models 79

5.1 Summary 79

5.2 Introduction 79

5.3 "Populution" issues 81

5.4 Coming to terms with sustainability issues 82

5.5 Some eco-ethical concerns 84

5.6 Processes relevant to ecosystems 86

5.7 Concluding discussion 88

References 89

Bibliography 90

6. Introduction to Generation of Long-Term Rain Input 91

6.1 Introduction 91

6.2 Review of rainfall modeling and analysis techniques 93

6.3 Stochastic models 94

6.4 Disaggregation models 96

References 97

Bibliography 98

7. Dynamic Rain Systems 103

7.1 Introduction 103

7.2 Kinematics of storm cells 104

7.3 Uncertainty 109

7.4 Sensitivity of storm velocity to timing error 109

7.5 Sensitivity of storm velocity to timing resolution 111

7.6 Conclusions 112

References 118

Bibliography 118

8. Decision Support Systems 119

8.1 Introduction 119

8.2 DSSs in water quality modeling 122

8.3 SWMM shells 124

8.4 PCSWMM (this section written 1993) 127

8.5 Concluding remarks 134

References 135

Bibliography 136

9. Objective Functions 139

9.1 Introduction 139

9.2 Another question of terminology 140

9.3 Response functions and statistical objective functions in SWMM 141

9.4 Multi-objective functions 143

9.5 Concluding remarks 144

References 145

Bibliography 145

10. Uncertainty Analysis 147

10.1 Introduction 147

10.2 Previous work on model uncertainty 150

10.3 Sources of error 152

10.4 Discretization and observation error 155

10.5 Uncertainty due to estimates of the limiting values of parameters 157

10.6 How to carry out an uncertainty analysis 158

10.7 Uncertainty analysis for a water distribution model 160

10.8 Model reliability 163

10.9 Concluding remarks 164

References 165

Bibliography 168

11. Sensitivity Analysis 171

11.1 Introduction 171

11.2 Sensitivity analysis and hydrological models 175

11.3 Sensitivity gradients 180

References 181

12. State Variable Space 183

12.1 Introduction 183

12.2 State variable sub-spaces 184

References 192

13. Performance Evaluation Functions 193

13.1 Introduction 193

13.2 Survey of evaluation functions 194

13.3 Concluding remarks 202

References 203

14. Parameter Optimization and Process Calibration 205

14.1 Introduction 205

14.2 Model Validation 208

14.3 When is a model “sufficiently calibrated”? 208

14.4 Sensitivity-based calibration 209

14.5 Robustness and efficiency 210

14.6 Limiting values of parameters 211

14.7 Automatic calibration 213

14.8 Genetic algorithm 216

14.9 Application of the genetic algorithm to calibration 219

References 236

Bibliography 237

15. On Using a Little Fuzzy Logic 241

15.1 Introduction 241

15.2 Fuzzification 243

15.3 Defuzzification. 260

15.4 Conclusion. 261

References 262

Bibliography 262

16. Presenting Continuous Uncertainty and Model Reliability in Real Time 263

16.1 Introduction 263

16.2 Parameter uncertainty 265

16.3 Sensitivity analysis 267

16.4 Error analysis 268

References 271

Bibliography 272

17. Conclusions And Recommendations 273

17.1 Framework for continuous modeling: 273

17.2 Recommendations: 274

The Last Word 278

References 279

Glossary 293

SI-US Units Conversion Table 299

Programs and Models 301

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