河海大学学报（自然科学版）2026，Vol.54Issue(2)：28-37,117,11.DOI:10.3876/j.issn.1000-1980.2026.02.004
并发式复合灾害系统脆弱性评估
Vulnerability assessment of concurrent compound disaster systems
摘要
Abstract
To improve the research system for concurrent compound disaster vulnerability,the superimposition(reduction)effects among concurrent disasters and the different characteristics of each dimension of vulnerability were considered,and the theoretical formulas for exposure index,sensitivity index,and adaptive capacity index of the concurrent compound disaster system were derived.Moreover,a assessment index system for vulnerability of the concurrent compound disaster system was established.This system used convolutional neural networks(CNNs)to evaluate sensitivity and employed the entropy weight-TOPSIS evaluation method to evaluate exposure and adaptability,and it utilized ArcGIS technology to conduct a comprehensive assessment of system vulnerability and obtained the distribution of vulnerability grade intervals.The verification results of the avalanche-landslide example in the Guangdong-Hong Kong-Macao Greater Bay Area show that this assessment system is logically reasonable and methodologically reliable,and it has accurate assessment results,with strong scientificity and applicability.It can be effectively applied to the quantitative assessment of concurrent compound disaster vulnerability.The high and medium-high vulnerability areas of avalanche-landslide in the Guangdong-Hong Kong-Macao Greater Bay Area are concentrated in the central areas of the bay such as Yuexiu District and Tianhe District,as well as in the middle and southern areas of the bay such as Nanshan District,Futian District,and Luohu District.The districts and counties with vulnerability rankings in the top ten,such as Yuexiu District and Futian District,need to particularly consider strengthening disaster-resistant infrastructure and enhancing disaster management.关键词
脆弱性评估/并发式复合灾害/评估模型/卷积神经网络/崩塌-滑坡/粤港澳大湾区Key words
vulnerability assessment/concurrent compound disaster/assessment model/convolutional neural network/avalanche-landslide/the Guangdong-Hong Kong-Macao Greater Bay Area引用本文复制引用
宋月,王伟,徐峥辉,黄莉..并发式复合灾害系统脆弱性评估[J].河海大学学报（自然科学版）,2026,54(2):28-37,117,11.基金项目
国家自然科学基金面上项目(71974052) （71974052）
国家自然科学基金委员会-联合国环境规划署(NSFC-UNEP)可持续发展国际合作科学计划重点项目(42361144873) （NSFC-UNEP）
国家重点研发计划项目(2021YFC3001002) （2021YFC3001002）
