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cje ›› 2011, Vol. 30 ›› Issue (10): 2370-2380.

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Risk assessment of rainstorm climate and its induced agricultural disasters in east-central China. 

WEN Quan-pei1,2, HUO Zhi-guo1**, MA Zhen-feng3, XIAO Jing-jing1   

  1. 1Chinese Academy of Meteorological Sciences, Beijing 10081, China;2Chengdu University of Information Technology, Chengdu 610225, China; 3Climate Center of Sichuan Province, Chengdu 610072, China
  • Online:2011-10-08 Published:2011-10-08

Abstract: By using the 1961-2008 rainstorm climate observation data from 292 meteorological stations in east-central China and the historical information about the agricultural disasters in each of the provinces, a rainstorm climatic risk index and an agricultural relative disaster index as well as their risk assessment models were constructed by principal component analysis, soft histogram estimation, grey correlation analysis, and normal information diffusion, aimed to analyze the risks of rainstorm climate and its induced agriculture disasters in east-central China. In the study area, the rainstorm climatic risk had a decreasing trend from south to north, with the high-value area in Hainan and coastal are as of Guangdong and Guangxi, the medium-value area in north-central part of Guangdong and Guangxi, Jianghuai Region’s Anhui, Hubei, and Jiangxi, and Xianggan Region’s Hunan, and the low-value area in Northeast China except its coastal areas of Liaoning and in Shanxi and Hebei of North China. The high-value area of agricultural relative disaster risk was in Anhui, Hubei, Hunan, and Guangdong, and the low-value area was in Hebei, Henan, and Liaoning. The correlation coefficient between the rainstorm climatic index and the agricultural relative disaster index for each of the provinces except Guangdong was >0.6 (P<0.01). Through the verification with many years’ actual agricultural disasters, it was suggested that the rainstorm climatic risk index and the agricultural relative disaster index could be applied to better assess the actual rainstorm strength and the possible rainstorm-induced agriculture loss, respectively.

Key words: Land resources, Spatial database, GIS application