E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||11|
|Section||Non-structural measures and instruments|
|Published online||20 October 2016|
Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany
1 University of Potsdam, Institute of Earth and Environmental Science, Karl-Liebknecht-Strasse 24-25, 14476 Potsdam-Golm, Germany
2 GFZ German Research Centre for Geosciences, Section 5.4 Hydrology, Telegrafenberg, 14473 Potsdam, Germany
3 Deutsche Rückversicherung AG, Hansaallee 177, 40549 Düsseldorf, Germany
a Corresponding author: firstname.lastname@example.org
Common models that are used for flood loss assessments today rarely include multiple loss influencing factors, e.g. private precautionary measures, which is increasingly gaining attention in the course of the changes towards an integrated flood risk management. Furthermore, these models are often transferred to other flood events or regions without knowing to what extent this results in reliable estimates. Since data on explanatory variables and losses are often missing, model validation is scarcely performed. The aim of this study was therefore to investigate whether the multifactorial flood loss model FLEMO can be transferred in time and space, using the examples of the August 2002 and May/June 2013 flood events in Germany, with particular consideration of changes in property-level mitigation measures and loss reduction effects for residential buildings. The study revealed that the spatio-temporal transferability of flood loss models remains highly uncertain, since the models could only partially reproduce changes in property-level mitigation measures. This indicates that flood loss influencing processes and factors are still not yet sufficiently understood and represented in models due to complex interrelations and different flood and site specific characteristics. More research on changes in loss explanatory parameters and standardised data collection is needed to enhance the understanding of damage processes and to improve flood loss model validation.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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