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Discussion papers | Copyright
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 18 Dec 2017

Research article | 18 Dec 2017

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).

On the role of building value models for flood risk analysis

Veronika Röthlisberger1,2, Andreas P. Zischg1,2, and Margreth Keiler1 Veronika Röthlisberger et al.
  • 1Institute of Geography and Mobiliar Lab for Natural Risks, University of Bern, Hallerstrasse 12, CH-3012 Bern, Switzerland
  • 2Oeschger Centre for Climate Change Research, University of Bern, Falkenplatz 16, CH-3012 Bern, Switzerland

Abstract. Quantitative flood risk analyses support decisions in flood management policies that aim at cost efficiency. Risk is commonly calculated by a combination of the three quantified factors: hazard, exposure, and vulnerability. Our paper focuses on the quantification of exposure, in particular on the relevance of building value estimation schemes within flood exposure analyses at regional to national scales. We compare five different models that estimate the values of flood exposed building. Four of them refer to individual buildings, whereas one is based on values per surface area, differentiated by land use category. That one follows an approach commonly used in flood risk analyses at regional or larger scales. Apart from the underlying concepts, the five models differ in complexity, in data and in computational expenses required for parameter estimations, and in the data they require for model application.

The model parameters are estimated by using a database of more than half a million building insurance contracts in Switzerland, which are provided by 11 (out of 19) Cantonal insurance companies for buildings that operate under a monopoly within the respective Swiss Cantons. Comparing the five models' results with the spatially referenced insurance data applied directly suggests that models based on individual buildings produce better results than the model based on surface area, but only when they include an individual building's volume.

Applying the five models to all of Switzerland produces results that are very similar with regard to the spatial distribution of exposed building values. Therefore, for spatial prioritizations, simpler models are preferable. In absolute values, however, the five models' results differ remarkably. The two simplest models underestimate the overall exposure, and even more so the extreme high values, upon which risk management strategies generally focus. In decision-making processes based on cost-efficiency, this underestimation would result in suboptimal resource allocation for protection measures. Consequently, we propose that estimating exposed building values should be done based on individual buildings rather than on areas of land use types. In addition, a building's individual volume has to be taken into account in order to provide a reliable basis for cost-benefit analyses. The consideration of other building features further improves the value estimation. However, within the context of flood risk management, the optimal value estimation model depends on the specific questions to be answered. The concepts of the presented building value models are generic. Thus, these models are transferrable with minimal adjustments according to the application's purpose and the data available.

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Veronika Röthlisberger et al.
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Veronika Röthlisberger et al.
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Short summary
We investigate the role of building value estimation schemes within flood exposure analyses at regional to national scales. Our results for Switzerland suggest that models based on individual buildings produce more reliable results than models based on surface area, but only if they consider the buildings' volume. Simple models tend to underestimate the exposure, which results in suboptimal allocation of resources for protection measures in decision making processes based on cost-efficiency.
We investigate the role of building value estimation schemes within flood exposure analyses at...