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Exploring the impact of epistemic uncertainty on a regional probabilistic seismic risk assessment model

机译:探讨认知不确定性对区域概率地震风险评估模型的影响

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Probabilistic earthquake loss models are widely used in the (re)insurance industry to assess the seismic risk of portfolios of assets and to inform pricing mechanisms for (re)insurance contracts, as well as by international and national organizations with the remit to assess and reduce disaster risk. Such models include components characterizing the seismicity of the region, the ground motion intensity, the building inventory, and the vulnerability of the assets exposed to ground shaking. Each component is characterized by a large uncertainty, which can be classified as aleatory or epistemic. Modern seismic risk assessment models often neglect some sources of uncertainty, which can lead to biased loss estimates or to an underestimation of the existing uncertainty. This study focuses on exploring and quantifying the impact of a number of sources of uncertainties from each component of an earthquake loss model to the loss estimates. To this end, the residential exposure of Guatemala and Guatemala City were used as case studies. Moreover, a comparison of the predicted losses for an insured portfolio in the country between OpenQuake-engine and a vendor catastrophe platform was performed, assessing the potential application of OpenQuake in the (re)insurance industry. The findings from this study suggest that the uncertainty in the hazard component has the most significant effect on the loss estimates.
机译:概率的地震损失模型广泛用于(RE)保险业,以评估资产组合的地震风险,并通知(重新)保险合同的定价机制,以及国际和国家组织与汇款进行评估和减少灾害风险。这些模型包括表征区域地震性,地面运动强度,建筑物库存的组件,以及暴露于地面摇动的资产的脆弱性。每个组分的特征在于大的不确定性,其可以被归类为杀菌或认识。现代地震风险评估模型往往会忽视一些不确定性的来源,这可能导致偏见的损失估计或低估了现有的不确定性。本研究侧重于探索和量化从地震损失模型的每个部件对损失估计的每个部件的影响。为此,危地马拉和危地马拉市的住宅曝光被用作案例研究。此外,在OpenQuake发动机和供应商灾难平台之间进行了预测投资组合的预测损失,评估了(RE)保险业的潜在应用。本研究的调查结果表明,危险组分的不确定性对损失估计有最大的影响。

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