The probabilistic flood damage model for residential buildings – BN-FLEMOps [en] Das probabilistische Hochwasserschadensmodell für Wohngebäude – BN-FLEMOps [de]
Article
Steinhausen, M., Lüdtke, S., Schröter, K., Figueiredo, R. and Kreibich, H. 2020. The probabilistic flood damage model for residential buildings – BN-FLEMOps [en] Das probabilistische Hochwasserschadensmodell für Wohngebäude – BN-FLEMOps [de]. Hydrologie und Wasserbewirtschaftung. 64 (4), pp. 188-199. https://doi.org/10.5675/HYWA_2020.4_2
Type | Article |
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Title | The probabilistic flood damage model for residential buildings – BN-FLEMOps [en] Das probabilistische Hochwasserschadensmodell für Wohngebäude – BN-FLEMOps [de] |
Authors | Steinhausen, M., Lüdtke, S., Schröter, K., Figueiredo, R. and Kreibich, H. |
Abstract | Flood risk analyses and particularly estimates of flood loss are often associated with a high degree of uncertainty. Deterministic models are unable to reflect and account for these uncertainties, or they are only able to do this to a very limited extent. This study presents the probabilistic flood loss estimation model for the private sector BN-FLEMOps remove. Taking the 2002 flood at the Mulde river as an example, the BN-FLEMOps is compared with a model ensemble of established flood loss models and the advantages of probabilistic models for decision-making under uncertainty are discussed. Furthermore, the implementation of the model in the OASIS Loss Modeling Framework (LMF) is described, which enables its easy application. The validation at the Mulde river shows that the median loss estimates by the BN-FLEMOps are closer to the observed loss in 12 out of 19 municipalities in comparison with the ensemble median. |
Keywords | Flood loss model, probabilistic, validation, uncertainty, decision-making [en] Hochwasserschadensmodell, probabilistisch, Validierung, Unsicherheit, Entscheidungsfindung [de] |
Publisher | Bundesanstalt für Gewässerkunde (BfG) |
Journal | Hydrologie und Wasserbewirtschaftung |
Publication dates | |
01 Aug 2020 | |
Publication process dates | |
Deposited | 05 Nov 2021 |
Accepted | 01 Jun 2020 |
Output status | Published |
Web address (URL) | http://doi.bafg.de/HyWa/2020/HyWa_2020.4_2.pdf |
Digital Object Identifier (DOI) | https://doi.org/10.5675/HYWA_2020.4_2 |
Language | English |
https://repository.mdx.ac.uk/item/898y7
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