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A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

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  • Klaus Schneeberger
  • Matthias Huttenlau
  • Benjamin Winter
  • Thomas Steinberger
  • Stefan Achleitner
  • Johann Stötter

Abstract

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.

Suggested Citation

  • Klaus Schneeberger & Matthias Huttenlau & Benjamin Winter & Thomas Steinberger & Stefan Achleitner & Johann Stötter, 2019. "A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 125-139, January.
    • Handle: RePEc:wly:riskan:v:39:y:2019:i:1:p:125-139
    DOI: 10.1111/risa.12863
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    References listed on IDEAS

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    1. Stanley Kaplan & B. John Garrick, 1981. "On The Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 11-27, March.
    2. Bruno Merz & Annegret Thieken, 2009. "Flood risk curves and uncertainty bounds," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 51(3), pages 437-458, December.
    3. Caroline Keef & Jonathan A. Tawn & Rob Lamb, 2013. "Estimating the probability of widespread flood events," Environmetrics, John Wiley & Sons, Ltd., vol. 24(1), pages 13-21, February.
    4. H. Moel & J. Aerts, 2011. "Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 58(1), pages 407-425, July.
    5. Keef, Caroline & Papastathopoulos, Ioannis & Tawn, Jonathan A., 2013. "Estimation of the conditional distribution of a multivariate variable given that one of its components is large: Additional constraints for the Heffernan and Tawn model," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 396-404.
    6. Janet E. Heffernan & Jonathan A. Tawn, 2004. "A conditional approach for multivariate extreme values (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 497-546, August.
    7. Ralf Merz & Günter Blöschl & Günter Humer, 2008. "National flood discharge mapping in Austria," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 46(1), pages 53-72, July.
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    1. Nikolaos Argyris & Valentina Ferretti & Simon French & Seth Guikema & Gilberto Montibeller, 2019. "Advances in Spatial Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 1-8, January.

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