Preface	5
	Contents	7
	Contributors	9
	1 Introduction -- Hydrological Aspects of Risk Management	11
	1.1 Determinants of Flood Risk	11
	1.2 Importance of Detailed Flood Characterisations in Risk Estimations	12
	1.3 Hydrological Information for Flood Risk Management	15
	1.4 The Content of This Book	17
	References	20
	2 Uncertainties in Weather Forecast -- Reasons and Handling	21
	2.1 Introduction	22
	2.2 Background and Current Uncertainties in Weather Forecast	24
	2.3 Data Assimilation Strategies	27
	2.4 Reasons for Uncertainties	32
	2.5 Handling of Uncertainties	34
	2.6 Verification and Applications	38
	2.7 Outlook	39
	References	40
	3 Interpolation of Precipitation for Flood Modelling	44
	3.1 Introduction	45
	3.2 Interpolation Principle and Conventional Methods	46
	3.3 Geostatistical Interpolation	47
	3.3.1 Statistical Model	47
	3.3.2 Variograms	48
	3.3.3 Ordinary Kriging (OK)	50
	3.3.4 Simple Kriging (SK)	50
	3.3.5 Residual Kriging (RK)	51
	3.3.6 External Drift Kriging (EDK)	51
	3.4 Validation of Interpolation Methods	52
	3.5 Simulation Methods	53
	3.5.1 Sequential Simulation	53
	3.5.2 Simulated Annealing	54
	3.6 Example for Rainfall Interpolation	55
	3.7 Example for Rainfall Simulation	57
	References	59
	4 Framing Uncertainties in Flood Forecasting with Ensembles	62
	4.1 Introduction	63
	4.2 Sources of Uncertainties	66
	4.3 Treatment of Uncertainties in Operational Flood Forecasts Using Ensemble Methods	67
	4.3.1 Overview	67
	4.3.2 Updating of State Parameters by Data Assimilation Using the Ensemble Kalman Filter (EnKF)	68
	4.3.2.1 Meteorological Ensemble Forecasts	71
	4.3.2.2 Utilisation of Parameter Ensembles	72
	4.4 Case Study: Ensembles as a Part of a Flood Forecast System for the Mulde River Basin	76
	4.5 Summary	83
	References	84
	5 Design of Artificial Neural Networks for Flood Forecasting	86
	5.1 The Challenge of Flood Forecasting	86
	5.2 Representation of Rainfall-Runoff Processes with Artificial Neural Networks	88
	5.2.1 Multi Layer Feed Forward Nets	88
	5.2.1.1 Principles of Multi Layer Nets	89
	5.2.1.2 Structure of Multi Layer Neural Networks	89
	5.2.1.3 Training of Multi Layer Nets	91
	5.2.2 Polynomial Neural Nets	92
	5.2.2.1 Basics of Polynomial Neural Networks	93
	5.2.2.2 Training of Polynomial Nets	94
	5.2.3 Comparative Analysis of Multi Layer Net and Polynomial Network Structures with Regard to Hydrological Problems	95
	5.2.4 Optimal Polynomial Network Forecast Strategy	100
	5.3 Conclusions	103
	References	104
	6 Advances in Regionalising Flood Probabilities	106
	6.1 Introduction	107
	6.2 Regionalisation Approaches	108
	6.2.1 Pooling Schemes	108
	6.2.2 Functional Relationships to Catchment Attributes	112
	6.2.3 Geostatistical Methods	115
	6.3 Performance of Regionalisation Approaches	119
	6.4 Discussion	121
	References	122
	7 Rainfall Generators for Application in Flood Studies	125
	7.1 Introduction	126
	7.2 Precipitation as Stochastic Process	127
	7.3 Alternating Renewal Models	129
	7.4 Time Series Models	131
	7.4.1 Markov Chains	131
	7.4.2 ARMA Models	132
	7.4.3 DARMA Models	133
	7.4.4 Advantages and Disadvantages	134
	7.5 Point Process Models	134
	7.6 Disaggregation Models	136
	7.7 Resampling Models	137
	7.7.1 k-Nearest Neighbourhood Bootstrapping	138
	7.7.2 Simulated Annealing	139
	7.7.3 Advantages and Disadvantages	139
	7.8 Example for Daily Rainfall Synthesis	139
	7.8.1 The Modelling Steps	141
	7.8.2 Simulation of Daily Precipitation	144
	7.9 Example for Hourly Rainfall Synthesis	147
	7.9.1 Methodology of Precipitation Synthesis	148
	7.9.2 Data, Study Region and Hydrological Model	149
	7.9.3 Application	150
	References	153
	8 Copulas -- New Risk Assessment Methodology for Dam Safety	156
	8.1 Introduction	157
	8.2 Copula Theory	158
	8.2.1 Basic Principles of Copula Theory	159
	8.2.2 Archimedian Copulas	161
	8.2.3 Parameter Estimation	161
	8.2.4 Identification of the Appropriate Copula Model	163
	8.2.4.1 Graphical Diagnostics	163
	8.2.4.2 Goodness-of-Fit Statistics	164
	8.2.5 Bivariate Frequency Analysis	165
	8.3 Case Study 1: Risk Analysis for the Wupper Dam	168
	8.3.1 Study Area	169
	8.3.2 Stochastic-Deterministic Generation of Flood Events	169
	8.3.3 Bivariate Frequency Analysis of Annual Flood Peaks and Corresponding Volumes	170
	8.3.3.1 Marginal Distributions	171
	8.3.3.2 Copula Estimation	171
	8.3.3.3 Bivariate Frequency Analysis	176
	8.3.4 Evaluation of the Effect of the Wupper Dam on Flood Control	176
	8.4 Case Study 2: Unstrut River Basin	178
	8.4.1 Description of the River Basin	179
	8.4.2 Stochastic-Deterministic Generation of Flood Events	180
	8.4.3 Bivariate Frequency Analysis of Corresponding Flood Peaks at the Reservoir Sites	181
	8.4.3.1 Marginal Distributions	182
	8.4.3.2 Copula Estimation	182
	8.4.3.3 Bivariate Frequency Analysis	184
	8.4.4 Bivariate Frequency Analysis of the Annual Flood Peaks and the Corresponding Volumes	184
	8.4.4.1 Marginal Distributions	185
	8.4.4.2 Copula Estimation	185
	8.4.4.3 Bivariate Frequency Analysis	186
	8.4.5 Evaluation of the Effect of the Reservoir Straussfurt on Flood Control	187
	8.5 Conclusions	189
	References	190
	9 Hydraulic Modelling	193
	9.1 Fundamentals	194
	9.1.1 Preface	194
	9.1.2 Flow Characteristics	195
	9.1.3 Model Types	196
	9.1.4 Base Data	199
	9.1.4.1 Terrain Topography (River Channel/Flood Plain)	199
	9.1.4.2 Water Level Information and Flood Boundaries	200
	9.1.5 Investigation	201
	9.2 Flood Management Models	202
	9.2.1 Case Study of a Region with Well Defined Flow Characteristics	203
	9.2.2 Case Study of a Region with Complex Flow Characteristics	205
	9.2.2.1 Characterisation of the Investigated Area	205
	9.2.2.2 Modelling Techniques	206
	9.3 GIS-Based User Interface	209
	9.3.1 Hydraulic Computation	210
	9.3.2 Visualisation of Results	211
	9.3.3 Specific Flood Analysis Tools	212
	9.3.3.1 Freeboard Analyses Along Dikes	212
	9.3.3.2 Hazard Analysis of Buildings	212
	9.3.3.3 Intervention in Model Topography	213
	9.3.3.4 Analysis of Protected Areas	213
	9.3.3.5 Superposition of Other Flood-Related Data	213
	9.4 Summary	213
	References	215
	10 Groundwater -- The Subterranean Part of Flood Risk	216
	10.1 Introduction	217
	10.2 Flood and Groundwater Characteristics, Impacts and Parameters	218
	10.2.1 Characteristics	218
	10.2.2 Impacts	218
	10.2.3 Parameters	220
	10.3 Model Coupling	222
	10.3.1 Coupling Concept	222
	10.3.2 Model Coupling	224
	10.3.3 Spatial and Time Step Coupling	224
	10.4 Case Study Dresden	225
	10.4.1 Introduction of Study Area	225
	10.4.2 Flood and Groundwater in the Study Area	226
	10.4.3 Results of Modelling	228
	10.5 Conclusions	230
	References	231
	11 Quantification of Socio-Economic Flood Risks	233
	11.1 Increasing Demand for Flood Damage Assessments	233
	11.2 Basics of Direct Economic Damage Assessment	236
	11.2.1 Types of Flood Damage	236
	11.2.2 Spatial and Temporal Scales	237
	11.2.3 Procedure for Direct Economic Damage Estimation	238
	11.2.4 Classification of Elements at Risk	238
	11.2.5 Exposure and Asset Analysis	239
	11.3 Susceptibility Analysis	243
	11.3.1 Damage Influencing Flood Characteristics	243
	11.3.2 Damage Functions	244
	11.4 The FLEMOps Model	244
	11.5 Conclusions	249
	References	249
	12 Application of Scenarios and Multi-Criteria Decision Making Tools in Flood Polder Planning	252
	12.1 Introduction	253
	12.2 Estimation of Flood Scenarios and Their Plausibility	255
	12.3 Impact Assessments of Flood Control Measures	257
	12.4 Multi-Criteria Decision Making	258
	12.4.1 A Distance Based MCDM Tool -- the TOPSIS Approach	258
	12.4.2 A Fuzzyfied Version of the Analytic Hierarchy Process Method (FAHP)	260
	12.5 Case Study	264
	12.5.1 Specification of Hydrological Loads	265
	12.5.2 Comparison of Damages	271
	12.5.3 Application of TOPSIS	272
	12.5.4 Application of Fuzzy-AHP	274
	12.6 Conclusions	277
	References	277
	Index	279