DOI: 10.1007/s11069-021-04744-3
论文题名: Assessment of provincial waterlogging risk based on entropy weight TOPSIS–PCA method
作者: Liu Z. ; Jiang Z. ; Xu C. ; Cai G. ; Zhan J.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 108, 期: 2 起始页码: 1545
结束页码: 1567
语种: 英语
中文关键词: Coupled entropy weight TOPSIS–PCA model
; Entropy weight TOPSIS method
; Evaluation indicators
; Principal component analysis
; Waterlogging risk assessment
英文摘要: 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. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169183
Appears in Collections: 气候变化与战略
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作者单位: School of Civil Engineering and Architecture, Nanchang University, Nanchang, China; School of Resources Environmental & Chemical Engineering, Nanchang University, Nanchang, China
Recommended Citation:
Liu Z.,Jiang Z.,Xu C.,et al. Assessment of provincial waterlogging risk based on entropy weight TOPSIS–PCA method[J]. Natural Hazards,2021-01-01,108(2)