期刊
NATURAL HAZARDS
卷 98, 期 2, 页码 621-642出版社
SPRINGER
DOI: 10.1007/s11069-019-03722-0
关键词
RADV; Key factors; Panel data; CGRA; Max-CGRA clustering
资金
- National Natural Science Foundation of China [71771119, 71371098, 71701105]
- Postgraduate Research and Practice Innovation Program of Jiangsu Province [SJKY19_0143]
- Key Research Project of Social Science Fund in Jiangsu Province [16GLA001]
- Fundamental Research Funds for the Central Universities [2017301]
Regional agricultural drought vulnerability (RADV) is a complex problem caused by the interaction of various factors, and the combination of multiple dimensions of each subregion, factor index and time affects the RADV. Therefore, panel data should be used to reflect the actual situation of the region objectively and comprehensively. Current research on identifying key factors of affecting RADV is relatively scarce from the perspective of panel data. In view of this, in order to classify and identify the key factors, a new panel data grey combined method of comprehensive grey relational analysis (CGRA) and Max-CGRA clustering is proposed, which is applied to identify the key factors of RADV in China's Henan Province. According to the identification results of key factors, the reasons for the change of RADV are further discovered, and the corresponding drought policies and countermeasures that need to be strengthened and controlled are presented. In addition, these results can also provide scientific basis for regional agricultural drought risk control.
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