Prognose der Bauwerksschädigung unter Hochwassereinwirkung

Abstract

Reliable prognoses of building damage caused by flood impact require realistic correlations between action and loss describing parameters. Due to the fact that commonly applied damage relationships between inundation level and loss are related to the costs for the different insurance sectors or usage classes (i. e. private housing), the required differentiation according to the parameters on the resistance side is still missing. The large scatter in the damage data has complicated the derivation of reliable general loss predictions and specific cost-benefit analyses. On the basis of the August 2002 Saxony flood data base, a method to determine the structural damage of a single building or of the affected building stock for any given flood scenario is developed. Repeatedly observed damage patterns are transformed into a classification scheme of damage grades. With this tool, the structural damage of all damage cases can be analysed in a systematic way and related to the parameters describing flood impact. Vulnerability classes for the different building types are defined by using the data for determining characteristic ranges of damage expectation. Basic steps of the procedure are illustrated for a fictive data-set, and subsequently applied to the existing database. As one of the main results, a new type of vulnerability function is proposed, describing the empirically-based relationship between inundation height and the introduced damage grades D j. With these vulnerability functions the damage distribution caused by the August 2002 flood can be reinterpreted for test areas with close agreement to the observed effects. A similar good prognosis could be achieved for the reported loss in monetary terms by correlating vulnerability class and impact parameter (inundation level) in specific loss functions. Thus, the prerequisites for the practical application of the procedure and presented tools are given. © Ernst & Sohn Verlag für Architektur und technische Wissenschaften GmbH & Co. KG.