Storm flooding disaster risk assessment based on scenarios simulation of spatial and temporal distributions of precipitation
JIANG Zhihuai1, GONG Zhiyu1, LI Chang2, YU Yanwen3, CAI Zhe4
（1. Jiangxi Climate Centre, Nanchang 330046; 2. Jiangxi Atmospheric Sounding Technology Centre, Nanchang 330046;3. Jiangsu Key Lab of Agricultural Meteorology, University of Information Science and Technology, Nanjing 210044；4. Meteorological Disaster Emergency Warning Centre of Jiangxi，Nanchang 330046)
Abstract：
Risk assessment of disaster-inducing factors is an important part of risk regionalization. Using the precipitation over alerting water level in the Gongshui River region in Jiangxi province for rainstorm disaster-inducing factor, in this study we have calculated the area rainfall of different return periods by using the optimal extreme value distribution function method. In addition, the temporal distribution index of peak rainfall in the precipitation events over alerting water level and the analysis of spatial precipitation based on Empirical Orthogonal Function (EOF) are used to simulate flood evolution at the different distribution scenarios of precipitation on the basis of FloodArea model.Using the inundated depth simulated for an index to build the assessment level, the risk of rainstorm disaster-inducing in the Gongshui River region is assessed in the different scenarios of spatial and temporal distributions of precipitation. The results show that different spatial and temporal distributions of precipitation can have a distinct effect on the danger assessment of rainstorm disaster-inducing. Based on risk regionalization and estimate of rainstorm flooding disasters in the precipitation area, developing vulnerability and exposure assessment of different hazard affected bodies can provide a valuable reference for the development of disaster mitigation planning and plans of local governments.
.2016. Storm flooding disaster risk assessment based on scenarios simulation of spatial and temporal distributions of precipitation[J].
Torrential Rain and Disasters, 35(5): 464-470.
