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中国长三角地区暴雨灾害风险评估及影响因素分析。

Rainstorm Disaster Risk Assessment and Influence Factors Analysis in the Yangtze River Delta, China.

机构信息

Business School, Hohai University, Nanjing 210098, China.

Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China.

出版信息

Int J Environ Res Public Health. 2022 Aug 2;19(15):9497. doi: 10.3390/ijerph19159497.

DOI:10.3390/ijerph19159497
PMID:35954847
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9368372/
Abstract

Rainstorm disasters have had a serious impact on the sustainable development of society and the economy. However, due to the complexity of rainstorm disasters, it is difficult to measure the importance of each indicator. In this paper, the rainstorm disaster risk assessment framework was systematically proposed based on the disaster system theory and a system of corresponding indicators was established. Furthermore, the genetic algorithm optimized projection pursuit and XGBoost were coupled to assess the rainstorm disaster risk and to measure the relative importance of each indicator. Finally, the Yangtze River Delta was taken as the case study area. The results show that: the rainstorm disaster risk in the eastern and southeast is higher than those in the central and northwest of the Yangtze River Delta; the total precipitation from June to September and the top ten indicators contribute 9.34% and 74.20% to the rainstorm disaster risk assessment results, respectively. The results can provide references for decision makers and are helpful for the formulation of rainstorm adaptation strategies.

摘要

暴雨灾害对社会和经济的可持续发展造成了严重影响。然而,由于暴雨灾害的复杂性,很难衡量每个指标的重要性。本文基于灾害系统理论,系统地提出了暴雨灾害风险评估框架,并建立了相应的指标体系。此外,采用遗传算法优化的投影寻踪和 XGBoost 对暴雨灾害风险进行了评估,并对各指标的相对重要性进行了度量。最后,以长江三角洲为研究区进行实证分析。结果表明:长江三角洲东部和东南部的暴雨灾害风险高于中部和西北部;6 月至 9 月的总降水量和前 10 个指标对暴雨灾害风险评估结果的贡献分别为 9.34%和 74.20%。研究结果可为决策者提供参考,有助于制定暴雨适应策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/a58c1ead2924/ijerph-19-09497-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/c4b0c6166f97/ijerph-19-09497-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/a937158768a7/ijerph-19-09497-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/d14fb5e70529/ijerph-19-09497-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/53570399ca34/ijerph-19-09497-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/bdb6a9ee02e9/ijerph-19-09497-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/9861d5a31d51/ijerph-19-09497-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/a58c1ead2924/ijerph-19-09497-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/c4b0c6166f97/ijerph-19-09497-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/a937158768a7/ijerph-19-09497-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/d14fb5e70529/ijerph-19-09497-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/53570399ca34/ijerph-19-09497-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/bdb6a9ee02e9/ijerph-19-09497-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/9861d5a31d51/ijerph-19-09497-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffde/9368372/a58c1ead2924/ijerph-19-09497-g007.jpg

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本文引用的文献

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