Scenario-based risk framework selection and assessment model development for natural disasters: a case study of typhoon storm surges

Mengya Li (), Jun Wang () and Xiaojing Sun ()

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2016, vol. 80, issue 3, 2037-2054

Abstract: Many studies have revealed the importance of risk assessment of natural disasters for public safety management, emergency responses and insurance purchases. This paper focuses on three aspects of a risk assessment process: (1) comparing the existing risk frameworks and assessment methods, (2) conceptualizing a scenario-based risk analysis approach and (3) specifying a quantitative assessment model. After a close examination of relevant research, we selected the triad of Hazard, Vulnerability and Adaptation Capability as the risk framework for the present study. We also prescribed several scenarios based on the spatiotemporal dynamic environment leading to given disasters. The assessment model is tested with six scenarios of typhoon storm surges striking Yuhuan County in Zhejiang Province, China. Three findings are highlighted in this paper. First, scenario-based simulation has become a dominant approach in risk analysis under the circumstances where disasters of high intensity, complexity and variability tend to occur frequently. This approach allows identification of acceptable risk with a certain probability. Second, the assessment model can reveal the collective enhancing effect of Hazard and Vulnerability and the mitigation effect of Adaptation Capability to the comprehensive risk. Lastly, the empirical study of Yuhuan indicates that R = 0.90 × H × V − 0.10 × C is the most feasible model for assessing the risk of typhoon storm surges. In general, the proposed methodology may be adapted for risk analysis of diverse disaster scenarios. Copyright Springer Science+Business Media Dordrecht 2016

Keywords: Risk framework; Risk assessment model; Scenario-based; Typhoon storm surges (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11069-015-2059-1

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