Agricultural Vulnerability Assessment of High-Temperature Disaster in Shaanxi Province of China

Yining Ma, Suri Guga, Jie Xu, Yulin Su, Xingpeng Liu, Zhijun Tong and Jiquan Zhang
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Yining Ma: School of Environment, Northeast Normal University, Changchun 130024, China
Suri Guga: School of Environment, Northeast Normal University, Changchun 130024, China
Jie Xu: School of Environment, Northeast Normal University, Changchun 130024, China
Yulin Su: School of Environment, Northeast Normal University, Changchun 130024, China
Xingpeng Liu: School of Environment, Northeast Normal University, Changchun 130024, China
Zhijun Tong: School of Environment, Northeast Normal University, Changchun 130024, China
Jiquan Zhang: School of Environment, Northeast Normal University, Changchun 130024, China

Agriculture, 2022, vol. 12, issue 7, 1-20

Abstract: 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.

Keywords: improved TOPSIS model; multiple-criteria decision-making (MCDM); vulnerability assessment; obstacle analysis; G1-Critic; agricultural high-temperature disaster (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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