A novel framework for evidence-based assessment of flood resilience integrating multi-source evidence: A case study of the Yangtze River Economic Belt, China

被引:1
|
作者
Wu, Zhixia [1 ,2 ,3 ,4 ]
Chen, Yijun [1 ]
Zheng, Xiazhong [2 ,4 ]
Huang, Shan [5 ,6 ]
Duan, Chenfei [2 ,4 ]
Wang, Ping [7 ]
机构
[1] Sichuan Univ Sci & Engn, Coll Management, Zigong 643000, Peoples R China
[2] China Three Gorges Univ, Coll Hydraul & Environm Engn, Yichang 443002, Peoples R China
[3] China Three Gorges Univ, Coll Econ & Management, Yichang 443002, Peoples R China
[4] China Three Gorges Univ, Hubei Key Lab Construct & Management Hydropower En, Yichang 443002, Peoples R China
[5] Sichuan Agr Univ, Coll Architecture & Urban Rural Planning, Dujiangyan 611830, Peoples R China
[6] Municipal Construct Engn Ctr Cuiping Dist, Yibin 644000, Peoples R China
[7] Sichuan Univ Sci & Engn, Coll Mech Engn, Zigong 643000, Peoples R China
关键词
Multi-source evidence; Flood resilience; Evidence-based assessment; Yangtze River Economic Belt; Flood resilience indicator; COMMUNITY RESILIENCE; RISK;
D O I
10.1016/j.ecolind.2024.112705
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Floods are extremely destructive to the society, economy and nature, and severely restrict sustainable urban development. There is an urgent need to assess the level of flood resilience, analyze its evolutionary characteristics and improve the flood resilience of the region. However, few previous studies have integrated multi- source evidence into a framework for assessing flood resilience over a longer time span. This study integrated multi-source evidence to analyze the Yangtze River Economic Belt, including literature-based evidence, policy texts and social media data. Subsequently, the Kruskal algorithm and Jaccard coefficient were used to construct collinear networks and identify the clustering dimensions of flood resilience. After evidence judgment, a flood resilience indicator system was constructed. The flood resilience index was calculated using the improved Critic method. The dynamic evolution characteristics and key influencing factors were illustrated by the Kernel density and Grey correlation methods, respectively. The principal contribution is to integrate multi-source evidence to assess flood resilience, with a newly constructed indicator system that systematically considers local public demand, policy priorities and common indicators from previous literature. The results show that: the flood resilience index of the Yangtze River Economic Belt is in the range of [0.16, 0.75] from 2000 to 2022, with higher values in the downstream compared to those in the midstream and upstream. The social dimension dominating the overall flood resilience. The kernel density curve of the YREB is characterized by a right trailing. The interregional differences tend to widen and have a polarization effect. The special funds for water conservancy finances and the length of flood prevention levees are key factors influencing the level of flood resilience. Finally, strategies for enhancing flood resilience were proposed. This study provides a feasible framework for constructing an indicator system and assessing flood resilience by integrating multi-source data. It is important for flood risk management and helps to the development of urban flood prevention and resilience strategies.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Urban flood depth-economic loss curves and their amendment based on resilience: evidence from Lizhong Town in Lixia River and Houbai Town in Jurong River of China
    Wu, Xianhua
    Zhou, Lei
    Gao, Ge
    Guo, Ji
    Ji, Zhonghui
    NATURAL HAZARDS, 2016, 82 (03) : 1981 - 2000
  • [42] Urban flood depth-economic loss curves and their amendment based on resilience: evidence from Lizhong Town in Lixia River and Houbai Town in Jurong River of China
    Xianhua Wu
    Lei Zhou
    Ge Gao
    Ji Guo
    Zhonghui Ji
    Natural Hazards, 2016, 82 : 1981 - 2000
  • [43] Integrating flood risk assessment and management based on HV-SS model: A case study of the Pearl River Delta, China
    Zhu, Zhizhou
    Zhang, Shuliang
    Zhang, Yaru
    Yao, Rui
    Jin, Hengxu
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2023, 96
  • [44] Integrating prospect theory and hesitant fuzzy linguistic preferences for enhanced urban flood resilience assessment: A case study of the tuojiang river Basin in western China
    Yuan, Mingkang
    Zhou, Xiaofeng
    Qu, Xiaobing
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2024, 113
  • [45] A coupled PSR-based framework for holistic modeling and flood resilience assessment: A case study of the 2022 flood events in five southern provinces of China
    Fu, Xingfeng
    Liu, Yun
    Xie, Zhiqiang
    Jiang, Fengshan
    Xu, Jiarui
    Yang, Zhibing
    Deng, Zhanting
    Wang, Qisheng
    Liao, Mengfan
    Wu, Xiaodong
    Wang, Zhanhui
    Du, Qingyun
    JOURNAL OF HYDROLOGY, 2024, 636
  • [46] Evidence-Based Indicator Approach to Identify Environmental Impacts of Cascade Dam Projects: A Case Study of Cascade Dam Projects on the Yangtze River
    Chen, Ang
    Wu, Miao
    WATER, 2022, 14 (16)
  • [47] Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm
    Wu, Zhixia
    Zheng, Xiazhong
    Chen, Yijun
    Huang, Shan
    Hu, Wenli
    Duan, Chenfei
    SUSTAINABILITY, 2023, 15 (15)
  • [48] Exploration of Eco-Environment and Urbanization Changes Based on Multi-Source Remote Sensing Data-A Case Study of Yangtze River Delta Urban Agglomeration
    Li, Yuhua
    Wang, Shihang
    SUSTAINABILITY, 2024, 16 (14)
  • [49] What was the spatiotemporal evolution characteristics of high-quality development in China? A case study of the Yangtze River economic belt based on the ICGOS-SBM model
    Zhang, Fengtai
    Tan, Hongmei
    Zhao, Peng
    Gao, Lei
    Ma, Dalai
    Xiao, Yuedong
    ECOLOGICAL INDICATORS, 2022, 145
  • [50] What was the spatiotemporal evolution characteristics of high-quality development in China? A case study of the Yangtze River economic belt based on the ICGOS-SBM model
    Zhang, Fengtai
    Tan, Hongmei
    Zhao, Peng
    Gao, Lei
    Ma, Dalai
    Xiao, Yuedong
    Ecological Indicators, 2022, 145