Study on Resilience Assessment of Flood and Landslide Disasters in Mountainous Urban Areas

WEN Haijia; QIAN Long; LI Zhuohang; HUANG Junhao

doi:10.13409/j.cnki.jdpme.20240616002

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Study on Resilience Assessment of Flood and Landslide Disasters in Mountainous Urban Areas

更新时间：2024-09-07

- Study on Resilience Assessment of Flood and Landslide Disasters in Mountainous Urban Areas
- Journal of Disaster Prevention and Mitigation Engineering Vol. 44, Issue 4, Pages: 751-761(2024)
- 作者机构：
  
  1.重庆大学土木工程学院，重庆 400045
  2.山地城镇建设新技术教育部重点实验室（重庆大学），重庆 400045
- 作者简介：
- 基金信息：
- DOI：10.13409/j.cnki.jdpme.20240616002
  CLC： TU984
- Received：16 June 2024，
  
  Revised：2024-07-15，
  
  Published：30 August 2024
- 稿件说明：
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文海家,钱龙,李卓航等.山地城镇洪涝滑坡灾害韧性评估研究[J].防灾减灾工程学报,2024,44(04):751-761.

WEN Haijia,QIAN Long,LI Zhuohang,et al.Study on Resilience Assessment of Flood and Landslide Disasters in Mountainous Urban Areas[J].Journal of Disaster Prevention and Mitigation Engineering,2024,44(04):751-761.
文海家,钱龙,李卓航等.山地城镇洪涝滑坡灾害韧性评估研究[J].防灾减灾工程学报,2024,44(04):751-761. DOI： 10.13409/j.cnki.jdpme.20240616002.

WEN Haijia,QIAN Long,LI Zhuohang,et al.Study on Resilience Assessment of Flood and Landslide Disasters in Mountainous Urban Areas[J].Journal of Disaster Prevention and Mitigation Engineering,2024,44(04):751-761. DOI： 10.13409/j.cnki.jdpme.20240616002.

摘要

为实现对山地城镇灾害韧性的有效评估，以受洪灾‑滑坡灾害链影响的中国典型山地城镇重庆市主城都市区为研究区，基于城市灾害韧性的内涵特征和作用机理，结合“压力‑状态‑响应”模型的因果逻辑，在多源数据收集分析的基础上，构建承载洪涝、滑坡灾害韧性评估指标体系。采用机器学习方法评估滑坡压力韧性，采用主客观组合权重分析及VIKOR法评估洪涝压力韧性和状态‑响应韧性，采用秩和比综合评价法构建综合韧性评估模型，度量城市灾害韧性水平，划分韧性等级，分析评估结果。结果表明：①研究区西部与西北部滑坡压力韧性高，中部滑坡压力韧性处于中等水平，南部与东北部滑坡压力韧性低；②研究区中部洪涝压力韧性水平较低，而研究区东部和西部洪涝压力韧性普遍较高，整体呈现外圈高内圈低的态势，其中位于研究区东南部的南川区是洪涝压力韧性最高的区；③重庆市核心城区的渝中区是状态‑响应韧性最高的区，整体的状态‑响应韧性空间分布呈现出一种明显的中心至外围递减趋势；④综合韧性的空间分布没有明显的特征，但研究区普遍存在一个行政区会出现多种不同韧性等级的情况，体现了各阶段韧性发展的不平衡。

Abstract

To effectively evaluate disaster resilience in mountainous urban areas

the study focused on the central urban area of Chongqing

a typical mountainous city in China influenced by the flood-landslide disaster chain. Based on the concept and mechanisms of urban disaster resilience and combined with the causal logic of the Pressure-State-Response (PSR) model

a resilience evaluation index system for floods and landslides was constructed through the collection and analysis of multi-source data. Landslide pressure resilience was evaluated using machine learning techniques

and the flood pressure and state-response resilience were assessed through a combination of subjective and objective weighting analyses with the VIKOR method. The rank-sum ratio comprehensive evaluation method was employed to construct an overall resilience assessment model

measure urban disaster resilience levels

classify resilience grades

and analyze the assessment results. The findings indicated that: (1) High landslide pressure resilience was observed in the western and northwestern regions of the study area

moderate resilience in the central area

and low resilience in the southern and northeastern regions. (2) Flood pressure resilience was lower in the central region of the study area

while the eastern and western regions generally displayed higher resilience

with the outer regions being more resilient than the inner regions. Nanchuan District in the southeastern region of the study area had the highest flood pressure resilience. (3) Yuzhong District

the core urban area of Chongqing

showed the highest state-response resilience

with the spatial distribution of state-response resilience exhibiting an evident decreasing trend from center to periphery. (4) The spatial distribution of comprehensive resilience did not show distinct patterns

but it was common for an administrative region within the study area to exhibit varying resilience levels

reflecting the uneven development of resilience across different stages.

关键词

Keywords

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