Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Nat. Hazards Earth Syst. Sci., 18, 1297-1314, 2018
https://doi.org/10.5194/nhess-18-1297-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
03 May 2018
Multi-model ensembles for assessment of flood losses and associated uncertainty
Rui Figueiredo1,2, Kai Schröter2, Alexander Weiss-Motz2, Mario L. V. Martina1, and Heidi Kreibich2 1Scuola Universitaria Superiore IUSS Pavia, Pavia, Italy
2GFZ German Research Centre for Geosciences, Sect. 5.4: Hydrology, Potsdam, Germany
Abstract. Flood loss modelling is a crucial part of risk assessments. However, it is subject to large uncertainty that is often neglected. Most models available in the literature are deterministic, providing only single point estimates of flood loss, and large disparities tend to exist among them. Adopting any one such model in a risk assessment context is likely to lead to inaccurate loss estimates and sub-optimal decision-making. In this paper, we propose the use of multi-model ensembles to address these issues. This approach, which has been applied successfully in other scientific fields, is based on the combination of different model outputs with the aim of improving the skill and usefulness of predictions. We first propose a model rating framework to support ensemble construction, based on a probability tree of model properties, which establishes relative degrees of belief between candidate models. Using 20 flood loss models in two test cases, we then construct numerous multi-model ensembles, based both on the rating framework and on a stochastic method, differing in terms of participating members, ensemble size and model weights. We evaluate the performance of ensemble means, as well as their probabilistic skill and reliability. Our results demonstrate that well-designed multi-model ensembles represent a pragmatic approach to consistently obtain more accurate flood loss estimates and reliable probability distributions of model uncertainty.
Citation: Figueiredo, R., Schröter, K., Weiss-Motz, A., Martina, M. L. V., and Kreibich, H.: Multi-model ensembles for assessment of flood losses and associated uncertainty, Nat. Hazards Earth Syst. Sci., 18, 1297-1314, https://doi.org/10.5194/nhess-18-1297-2018, 2018.
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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.
Flood loss modelling is subject to large uncertainty that is often neglected. Most models are...
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