Research on methodology for assessing social vulnerability to urban flooding: A case study in China

被引:0
|
作者
Wu, Meimei [1 ]
Chen, Min [1 ]
Chen, Guixiang [1 ]
Zheng, Deqian [1 ]
Zhao, Yang [1 ]
Wei, Xuan [1 ]
Xin, Yushan [1 ]
机构
[1] Henan Univ Technol, Coll Civil Engn, Zhengzhou 450001, Henan, Peoples R China
基金
中国博士后科学基金;
关键词
Social vulnerability; Urban flooding; Indicator system; Assessment model;
D O I
10.1016/j.jhydrol.2024.132177
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Cities are economically developed, densely populated, highly concentrated areas of social wealth and high social vulnerability to floods. Assessing social vulnerability to urban flooding (SVUF) is important for improving a city's ability to resist floods and reduce casualties and economic losses caused by disasters. However, owing to the abstract and complex nature of social vulnerability itself, the connotation of SVUF and the indicator system have not been standardised, and the rationality of the assessment methodology is controversial; therefore, assessing the SVUF faces great challenges. In this study, the connotation of SVUF was analysed based on social system theory. We considered the interactions between disasters and groups to construct a system of assessment indicators. The game-theory combinatorial weighting method (GTCWM) was used to determine the weights of indicator combinations, combined with the technique for order preference by similarity to an ideal solution (TOPSIS) to establish the SVUF assessment model. Zhengzhou City was taken as an example to verify the results of the model. The assessment results show that the Huiji District in Zhengzhou City has the lowest SVUF. Erqi and Zhongyuan Districts have similar SVUF, and both are at a medium level. Guancheng District has high SVUF. Jinshui District has the highest SVUF. Jinshui District is an old urban area with a large poor population, high unemployment rate, and old infrastructure, which makes its overall SVUF high and susceptible to flooding. This assessment model can provide a scientific basis for urban flood mitigation measures.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Assessing the vulnerability to climate change of a semi-arid pastoral social-ecological system: A case study in Hulunbuir, China
    Weng, Chuyao
    Bai, Yuping
    Chen, Bihui
    Hu, Yecui
    Shu, Jiayao
    Chen, Qi
    Wang, Pei
    ECOLOGICAL INFORMATICS, 2023, 76
  • [42] Assessing social vulnerability to earthquake disaster using rough analytic hierarchy process method: A case study of Hanzhong City, China
    Guo, Xuesong
    Kapucu, Naim
    SAFETY SCIENCE, 2020, 125
  • [43] Assessing Agricultural Drought Vulnerability by a VSD Model: A Case Study in Yunnan Province, China
    Wu, Jiansheng
    Lin, Xin
    Wang, Meijuan
    Peng, Jian
    Tu, Yuanjie
    SUSTAINABILITY, 2017, 9 (06)
  • [44] The truly disadvantaged? Assessing social vulnerability to climate change in urban India
    Yenneti, Komali
    Tripathi, Sabyasachi
    Wei, Yehua Dennis
    Chen, Wen
    Joshi, Gaurav
    HABITAT INTERNATIONAL, 2016, 56 : 124 - 135
  • [45] Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada
    Pang, Tianze
    Shah, Mohammad Aminur Rahman
    Dau, Quan Van
    Wang, Xiuquan
    ENVIRONMENTAL RESEARCH COMMUNICATIONS, 2024, 6 (07):
  • [47] Modelling the impact of land subsidence on urban pluvial flooding: A case study of downtown Shanghai, China
    Yin, Jie
    Yu, Dapeng
    Wilby, Rob
    SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 544 : 744 - 753
  • [48] Case study: Diagnosing China's prevailing urban flooding-Causes, challenges, and solutions
    Ma, Yang
    Cui, Yantao
    Tan, Huagao
    Wang, Hongyu
    JOURNAL OF FLOOD RISK MANAGEMENT, 2022,
  • [49] Risk assessment of urban infrastructure vulnerability to meteorological disasters: A case study of Dongguan, China
    Li, Fan
    Li, Yan
    Rubinato, Matteo
    Zheng, Yu
    Zhou, Tao
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2024, 114
  • [50] Assessing urban areas vulnerability to pluvial flooding using GIS applications and Bayesian Belief Network model
    Abebe, Yekenalem
    Kabir, Golam
    Tesfamariam, Solomon
    JOURNAL OF CLEANER PRODUCTION, 2018, 174 : 1629 - 1641