期刊
AGRICULTURE-BASEL
卷 12, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/agriculture12070980
关键词
improved TOPSIS model; multiple-criteria decision-making (MCDM); vulnerability assessment; obstacle analysis; G1-Critic; agricultural high-temperature disaster
类别
资金
- National Key Research and Development Program of China [2019YFD1002201]
- National Natural Science Foundation of China [41877520, 42077443]
- Science and Technology Development Planning of Jilin Province [20190303018SF]
- Key Research and Projects Development Planning of Jilin Province [20200403065SF]
- Development and Reform Commission of Jilin Province [2021C0445]
- Science and Technology Planning of Changchun [19SS007]
This study focuses on the vulnerability to agricultural high-temperature disaster in Shaanxi Province, China, using a combined weighting method and an improved TOPSIS model for evaluation. The results indicate that the northern and southern areas of Shaanxi are more vulnerable to high-temperature disaster, with Ankang and Tongchuan being particularly affected. Sensitivity is identified as the main obstacle to reducing vulnerability.
The negative impact of high-temperature disaster on agricultural production is becoming more and more serious, and reducing the vulnerability to high-temperature disaster is fundamental to achieving sustainable agricultural development. This study is mainly focused on the vulnerability to agricultural high-temperature disaster in Shaanxi Province, China. Firstly, 15 indicators were selected from the perspectives of exposure, sensitivity, and adaptability. Secondly, the combined weighting method (Critic-G1 model) was used to determine the weight of each index. Based on the aforementioned procedures, the Kullback-Leibler (KL)-distance-improved TOPSIS model was utilized to evaluate the vulnerability. Lastly, the obstacle model was used to analyze the influencing factors and to make recommendations for disaster prevention and mitigation. The results show that: (1) The improved TOPSIS model was closer to the results of the synthetical index method. (2) The northern and southern area of Shaanxi is more vulnerable to high-temperature disaster, especially in Ankang and Tongchuan. Low values are distributed in the Guanzhong Plain. (3) Sensitivity is the biggest obstacle to reducing the vulnerability to high-temperature disaster. Among the influencing factors, the meteorological yield reduction coefficient of variation, multiple cropping index and per capita net income of rural residents of the obstacle are high. Decreasing sensitivity should be accompanied by increasing adaptability to improve regional disaster preparedness and mitigation. The results of this study can provide a basis for the development of agricultural high-temperature disaster mitigation and loss reduction strategies and provide new ideas for future research.
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