Abstract
Due to their complexity, hazard interactions are often neglected in current studies of multi-hazard risk assessment. As a result, the assessment results are qualitative or semi-quantitative and are difficult to use in regional risk management. In this paper, the crop loss risk due to heavy rain and strong wind in the Yangtze River Delta (YRD) region of China was quantitatively assessed, based on the joint return periods of these hazards and a vulnerability surface. The joint return period is obtained with a copula function based on the marginal distribution of each hazard. The vulnerability is fitted by considering the joint hazard intensity, the sown area of crops, elevation, and GDP per capita. The results show that counties with a high value of joint hazard probability are clustered in the southeast coastal area and that the value gradually decreases from south to north and from east to west. The multi-hazard risk has a similar pattern, with a large value in the southeast coastal area and a low value in the northwest. The proposed method can be used for quantitative assessment of multi-hazard risk, and the results can be used for regional disaster risk management and planning.
Highlights
Along with global climate change and rapid economic development, our societies are facing great threats from natural disasters
Frequent and intense natural disasters may threaten to reverse much of the developmental progress that has been made in recent decades
For better disaster risk management, it is important to assess the regional risks of multiple hazards
Summary
Along with global climate change and rapid economic development, our societies are facing great threats from natural disasters. The information diffusion method is used for quantitatively calculating multi-hazard risks, e.g., the risks of typhoon and flood in the Yangtze River Delta (YRD) region of China [14] and multiple climatic hazards of China [15]. In both the Global Risk Model and the diffusion method, the interactions between the different hazards are not considered. In the risk assessment method, the joint distributions of heavy rain and strong wind were calculated by using the copula theory, and the vulnerability surface was fitted by applying trend surface analysis and multiple regression estimation. Based on the joint distributions of multiple hazards and the vulnerability surface, the expected crop loss risks were quantitatively calculated
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