应对内涝灾害的城市韧性评估模型及应用

李正兆; 傅大放; 王君娴; 闵克东; 张骏彧

doi:10.16511/j.cnki.qhdxxb.2021.22.037

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清华大学学报（自然科学版） ›› 2022, Vol. 62 ›› Issue (2) : 266-276. DOI: 10.16511/j.cnki.qhdxxb.2021.22.037

专题：防灾减灾

应对内涝灾害的城市韧性评估模型及应用

李正兆^1,2, 傅大放¹, 王君娴^1,3, 闵克东¹, 张骏彧^3,4

作者信息 +

Urban resilience assessment model for waterlogging disasters and its application

LI Zhengzhao^1,2, FU Dafang¹, WANG Junxian^1,3, MIN Kedong¹, ZHANG Junyu^3,4

Author information +

文章历史 +

摘要

传统的防灾减灾理念下，内涝风险评估通常只考虑基础设施的抵御能力和气象、地形等自然条件。随着系统韧性理论的发展，政府和市民的防控意识、应急处理和灾后恢复等方面均需要纳入到风险评估和对策之中。该文提出了一套用于评估城市应对内涝灾害的综合能力的指标体系，包含13个方面共41个基础指标，并在该指标体系基础上构建了韧性评估模型；以内涝风险较高的圩区城市江苏省昆山市为例，进行了韧性评估模型的应用，结果表明昆山市高新区韧性最高，应对内涝灾害的能力最强。结合指标体系和评估结果，对韧性较差区域提出了针对性提升策略。

Abstract

In traditional disaster prevention and mitigation analyses, risk assessments for waterlogging disasters usually only consider the infrastructure resilience and natural conditions such as weather and terrain. However, with the development of resilience theory, risk assessment and countermeasures should also include flood prevention and control, emergency responses and post-disaster recovery by the government and residents. This paper presents a set of indicators for evaluating the ability of cities to deal with waterlogging disasters, including 41 basic indicators covering 13 aspects incorporated into a resilience assessment model. The resilience assessment model is then applied to Kunshan, a low lying city in Jiangsu Province, China. The results show that the Kunshan High-Tech Zone has the best resilience and the strongest ability to deal with waterlogging disasters. The index system and model evaluation results are used to develop a targeted improvement strategy for areas with poor resilience to waterlogging disasters.

导出引用

李正兆, 傅大放, 王君娴, 闵克东, 张骏彧. 应对内涝灾害的城市韧性评估模型及应用[J]. 清华大学学报（自然科学版）. 2022, 62(2): 266-276 https://doi.org/10.16511/j.cnki.qhdxxb.2021.22.037

LI Zhengzhao, FU Dafang, WANG Junxian, MIN Kedong, ZHANG Junyu. Urban resilience assessment model for waterlogging disasters and its application[J]. Journal of Tsinghua University(Science and Technology). 2022, 62(2): 266-276 https://doi.org/10.16511/j.cnki.qhdxxb.2021.22.037

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基金

国家“十三五”重点研发计划（2018YFC0809900）

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收稿日期	出版日期
2021-03-29	2022-02-15
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2022-01-22

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