Articles | Volume 18, issue 5
https://doi.org/10.5194/nhess-18-1297-2018
https://doi.org/10.5194/nhess-18-1297-2018
Research article
 | 
03 May 2018
Research article |  | 03 May 2018

Multi-model ensembles for assessment of flood losses and associated uncertainty

Rui Figueiredo, Kai Schröter, Alexander Weiss-Motz, Mario L. V. Martina, and Heidi Kreibich

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Cited articles

Apel, H., Aronica, G. T., Kreibich, H., and Thieken, A. H.: Flood risk analyses – how detailed do we need to be?, Nat. Hazards, 49, 79–98, https://doi.org/10.1007/s11069-008-9277-8, 2009.
Bröcker, J.: Evaluating raw ensembles with the continuous ranked probability score, Q. J. Roy. Meteor. Soc., 138, 1611–1617, https://doi.org/10.1002/qj.1891, 2012.
Buck, W. and Merkel, U.: Auswertung der HOWAS-Schadendatenbank, Institut für Wasserwirtschaft und Kulturtechnik der Universität Karlsruhe, 1999.
Budiyono, Y., Aerts, J., Brinkman, J. J., Marfai, M. A., and Ward, P.: Flood risk assessment for delta mega-cities: a case study of Jakarta, Nat. Hazards, 75, 389–413, https://doi.org/10.1007/s11069-014-1327-9, 2015.
Cammerer, H., Thieken, A. H., and Lammel, J.: Adaptability and transferability of flood loss functions in residential areas, Nat. Hazards Earth Syst. Sci., 13, 3063–3081, https://doi.org/10.5194/nhess-13-3063-2013, 2013.
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Short summary
Flood loss modelling is subject to large uncertainty that is often neglected. Most models are deterministic, and large disparities exist among them. Adopting a single model may lead to inaccurate loss estimates and sub-optimal decision-making. This paper proposes the use of multi-model ensembles to address such issues. We demonstrate that this can be a simple and pragmatic approach to obtain more accurate loss estimates and reliable probability distributions of model uncertainty.
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