Abstract

Abstract. As a result of the severe floods in Europe at the turn of the millennium, the ongoing shift from safety oriented flood control towards flood risk management was accelerated. With regard to technical flood control measures it became evident that the effectiveness of flood control measures depends on many different factors, which cannot be considered with single events used as design floods for planning. The multivariate characteristics of the hydrological loads have to be considered to evaluate complex flood control measures. The effectiveness of spatially distributed flood control systems differs for varying flood events. Event-based characteristics such as the spatial distribution of precipitation, the shape and volume of the resulting flood waves or the interactions of flood waves with the technical elements, e.g. reservoirs and flood polders, result in varying efficiency of these systems. Considering these aspects a flood control system should be evaluated with a broad range of hydrological loads to get a realistic assessment of its performance under different conditions. The consideration of this variety in flood control planning design was one particular aim of this study. Hydrological loads were described by multiple criteria. A statistical characterization of these criteria is difficult, since the data base is often not sufficient to analyze the variety of possible events. Hydrological simulations were used to solve this problem. Here a deterministic-stochastic flood generator was developed and applied to produce a large quantity of flood events which can be used as scenarios of possible hydrological loads. However, these simulations imply many uncertainties. The results will be biased by the basic assumptions of the modeling tools. In flood control planning probabilities are applied to characterize uncertainties. The probabilities of the simulated flood scenarios differ from probabilities which would be derived from long time series. With regard to these known unknowns the bias of the simulations was considered by imprecise probabilities. Probabilities, derived from measured flood data were combined with probabilities which were estimated from long simulated series. To consider imprecise probabilities, fuzzy sets were used to distinguish the results between more or less possible design floods. The need for such a differentiated view on the performance of flood protection systems is demonstrated by a case study.

Highlights

  • Flooding is the major cause of damage of all natural catastrophes in Germany (Thieken et al, 2007)

  • In order to provide the information to decision makers in a structured way, the flood risk data should be characterized within a MultiCriteria Decision Making (MCDM), which can be integrated in a decision support system (DSS)

  • The damage functions were combined in a Geographic Information System (GIS) with landuse and hydraulic data in order to automate the calculation of geographically distributed economic risks, risks for affected persons, and vulnerable localities for all 186 flood events

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Summary

Introduction

Flooding is the major cause of damage of all natural catastrophes in Germany (Thieken et al, 2007). For example the meteorological load has a probability as well as the initial state of the deterministic hydrological model, the model parameters itself are uncertain, the behaviour of the model for extreme events, which are often higher than any observed flood, is uncertain, the impact of technical flood retention measures depends on unknown operation schemes and so on These problems aggravate if such analyses are done for a large river basin with spatially distributed hydrological loads, where many different combinations of influencing factors are possible. The interdependencies between simulated volumes and peaks and interactions of tributaries during the simulated flood events were characterized with multivariate statistical means Based on these analyses single scenarios were selected and used to assess the performance of planned extensions of the flood retention system. Often the retention capacity is exhausted before the peak of an extreme flood is reached

Stochastic-deterministic generation of flood scenarios for large river basins
Categorising hydrological loads with multivariate statistics
Characterisation of hydrological loads with imprecise probabilities
Impact assessments of flood control measures
Description of the case study basin
Specification of hydrological loads
Socio-economic assessments
Simulation results
Considering the varieties of multiple effects of flood control
Summary and conclusions
Full Text
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