Assessment of provincial waterlogging risk based on entropy weight TOPSIS–PCA method

Zaohong Liu, Zhangzejun Jiang, Chen Xu, Guanjun Cai and Jian Zhan ()
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Zaohong Liu: Nanchang University
Zhangzejun Jiang: Nanchang University
Chen Xu: Nanchang University
Guanjun Cai: Nanchang University
Jian Zhan: Nanchang University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 108, issue 2, No 7, 1545-1567

Abstract: Abstract Over the past few years, urban waterlogging disasters have caused serious losses to the national economy of China; therefore, creating technology for assessing waterlogging risk levels has become an important goal. Based on 25 post-screened evaluation indexes regarding the construction of waterlogging facilities, social and economic developments, and investments in scientific and technological innovation, the capacity of 31 provinces to prevent and mitigate waterlogging was comprehensively evaluated. The scores of six principal component factors were calculated by using the entropy weight TOPSIS method, and the coupled entropy weight TOPSIS–principal component analysis evaluation model was established. Moreover, in accordance with the evaluation results, measures for waterlogging prevention and disaster reduction are proposed. The results show that Beijing, Shanghai and Tianjin are the top three provinces regarding the capacity to control floods and mitigate disasters; this agrees well with the actual flood drainage standards and disaster losses of all provinces.

Keywords: Waterlogging risk assessment; Evaluation indicators; Principal component analysis; Entropy weight TOPSIS method; Coupled entropy weight TOPSIS–PCA model (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11069-021-04744-3

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