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Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period
- Ming, Xiaodong, Xu, Wei, Li, Ying, Du, Juan, Liu, Baoyin, Shi, Peijun
- Stochastic environmental research and risk assessment 2015 v.29 no.1 pp. 35-44
- business enterprises, case studies, crop losses, insurance, markets, models, probability distribution, risk, risk assessment process, risk management, river deltas, wind speed, China, Yangtze River
- Risk assessment plays an important role in disaster risk management. Existing multi-hazard risk assessment models are often qualitative or semi-quantitative in nature and used for comparative study of regional risk levels. They cannot estimate directly probability of disaster losses from the joint impact of several hazards. In this paper, a quantitative approach of multi-hazard risk assessment based on vulnerability surface and joint return period of hazards is put forward to assess the risk of crop losses in the Yangtze River Delta region of China. The impact of strong wind and flood, the two most prominent agricultural hazards in the area, is analyzed. The multi-hazard risk assessment process consists of three steps. First, a vulnerability surface, which denotes the functional relationship between the intensity of the hazards and disaster losses, was built using the crop losses data for losses caused by strong wind and flood in the recent 30 years. Second, the joint probability distribution of strong wind and flood was established using the copula functions. Finally, risk curves that show the probability of crop losses in this multi-hazard context at four case study sites were calculated according to the joint return period of hazards and the vulnerability surface. The risk assessment result of crop losses provides a useful reference for governments and insurance companies to formulate agricultural development plans and analyze the market of agricultural insurance. The multi-hazard risk assessment method developed in this paper can also be used to quantitatively assess multi-hazard risk in other regions.