Author(s): H. Apel; G. T. Aronica; H. Kreibich; A. H. Thieken
Linked Author(s): Giuseppe T. Aronica
Keywords: Flood risk; Hydraulic modelling; Damage evaluations; Uncertainty
Abstract: Flood risk assessments, especially in urban areas, very often pose the question how detailed the analysis needs to be in order to give a realistic figure of the expected risk. The methods used in research and practical applications range from very basic approaches with numerous simplifying assumptions up to very sophisticated, data and calculation time demanding applications both on the hazard and vulnerability part of the risk. In order to shed some light on the question of required model complexity in flood risk analyses and outputs sufficiently fulfilling the task at hand, a number of combinations of models of different complexity both on the hazard and vulnerability side were tested in a case study. On the hazard side the approaches/models selected were A) linear interpolation of gauge water levels and intersection with a DEM, B) a mixed1D/2D hydraulic model with simplifying assumptions (LISFLOOD-FP) and C) a full 2D hyperbolic hydraulic model considering the built environment and infrastructure. On the vulnerability side models used are in order of increasing complexity: I) meso-scale stage-damage functions applied to CORINE land cover data, II) a rule-based meso-scale model using census data on the municipal building stock and CORINE land cover data and III) a rule-based microscale model applied to a detailed building inventory. The models were applied in a town in southeast Germany, Eilenburg. It suffered extraordinary damage during the flood of August2002, which was well documented as were the inundated areas and inundation depths. These data provide an almost unique data set for the validation of flood risk assessments. The analysis shows that the combination of the 1D/2D-model and the meso-scale rule-based damage model performed best and provide a good compromise between data requirements, simulation effort, and an acceptable accuracy of the results. The more detailed approaches suffered from the complex model setup and the high data requirements.
Year: 2007