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<p>Research about natural hazards has expanded from single-hazard to multi-hazard ones. While single hazards have been extensively studied in the past and many quantitative statements about intensities and severities are available, empirical studies about multi-hazard events and corresponding dependencies are still rare. This paper introduces statistical models for estimating&#xa0;the dependencies between different hazard types based on Poisson-type event processes. Moreover, the models are applied to data for several natural hazard events from the Danube Region within Europe. We found several&#xa0;multi-hazard interactions between extreme temperature, wildfire, drought, and flood hazards. The analysis should help to bridge the gap between the more conceptual contributions to this discussion by providing empirical evidence on interactions on a large-scale region as well as providing statistical models how to estimate them.</p>

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Statistical dependence models for multi-hazard events: an application to the Danube Region

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月3日

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  • Georg Ch. Pflug,
  • Viktoria Kittler,
  • Stefan Hochrainer-Stigler

摘要

Research about natural hazards has expanded from single-hazard to multi-hazard ones. While single hazards have been extensively studied in the past and many quantitative statements about intensities and severities are available, empirical studies about multi-hazard events and corresponding dependencies are still rare. This paper introduces statistical models for estimating the dependencies between different hazard types based on Poisson-type event processes. Moreover, the models are applied to data for several natural hazard events from the Danube Region within Europe. We found several multi-hazard interactions between extreme temperature, wildfire, drought, and flood hazards. The analysis should help to bridge the gap between the more conceptual contributions to this discussion by providing empirical evidence on interactions on a large-scale region as well as providing statistical models how to estimate them.