Urban Flooding Disaster Risk Assessment Based on Combined Empowerment-Fuzzy Mathematics

Yixuan Chen

doi:10.54097/xcnpkg22

Authors

Yixuan Chen

DOI:

https://doi.org/10.54097/xcnpkg22

Keywords:

Urban flooding; Risk assessment; Hierarchical analysis; Fuzzy mathematical analysis; Entropy weight approach.

Abstract

Purpose In recent years, flooding disasters have occurred frequently in major cities, in order to improve urban safety and reduce flooding disaster losses. With four urban areas in Zhengzhou City as the research object, it aims to provide a reference basis for the risk management and control of heavy rainfall and flooding disaster in Zhengzhou City. Methods From the four aspects of urban flooding disaster causative factor risk, sensitivity of the breeding environment, vulnerability of the disaster-bearing body and disaster prevention and mitigation capacity, 12 evaluation indicators were selected to construct the Zhengzhou city flood disaster risk assessment system. Based on the hierarchical analysis method (AHP) and entropy weight method (EWM) to get the weights of the combination of indicators, and using fuzzy mathematical analysis method to analyse the risk of urban flooding disaster. Results The assessment results were analysed to conclude that Jinshui District has the highest urban flood risk disaster as high risk, followed by Erqi District, Guancheng District and Zhongyuan District as medium risk, and Huiji District has the lowest risk as low risk. Conclusion Develop a set of flood risk assessment model, and accordingly draw a flood risk coefficient map of Zhengzhou City, and then derive the engineering and non-engineering measures to deal with the flood disaster in Zhengzhou City.

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References

[1] Zhang Chenming, Fan Qindong, Li Yanfeng, etc Change in traffic efficiency of urban road network and restoration strategy under rainstorm and waterlogging scenario -- Taking rainstorm disaster in Zhengzhou on July 20 as an example [J]. Economic Geography, 2022,42 (07): 62-72. DOI: 10.15957/j.cnki.jjdl.2022.07.007.

[2] Hall J W, Sayers P B, Dawson R J. National-scale assessment of current and future flood risk in England and Wales[J]. Natural Hazards, 2005, 36(1-2): 147-164.

[3] Benito G, Lang M, Barriendos M, et al. Use of systematic, palaeoflood and historical data for the improvement of flood risk estimation, review of scientific methods[J].Natural Hazards, 2004, 31(3): 623-643.

[4] Hategekimana Y, Yu L, Nie Y, et al. Integration of multi-parametric fuzzy analytic hierarchy process and GIS along the UNESCO world heritage: a flood hazard index, Mombasa county, Kenya[J]. Natural Hazards, 2018, 92(2): 1137-1153.

[5] Li Yanfang, Zhao Jingbo Research on Flood and Drought Disasters in Guanzhong Region in the Past 200 Years [J]. Resources and Environment in Arid Regions, 2008, 22 (4): 96-99.

[6] Cao Jinhu. Research on the Risk Assessment of Flood Disasters in the Main Urban Area of Xuzhou City [D]. Beijing: China University of Mining and Technology, 2018.

[7] Cao Luodan, Li Jialin Research on Comprehensive Risk Assessment of Flood and Drought Disasters in Zhejiang Province Based on Remote Sensing and GIS [J]. Journal of Natural Disasters, 2015 (04): 111-119.

[8] Wang Zhenya, Yao Cheng, Dong Junling, etc Precipitation characteristics and waterlogging effects of the "July 20" extremely heavy rainstorm in Zhengzhou [J]. Journal of Hohai University (Natural Science Edition), 2022,50 (03): 17-22.

[9] Zhang Xiaokui, Feng Lichao, Cui Xiaoli Research on the construction of urban resilient waterlogging prevention system under the "7.20" rainstorm scenario in Zhengzhou -- Taking the core area of Fuzhou Binhai New Town as an example [J]. Disaster Science, 2022,37 (02): 79-83.

[10] Liu Mingyang, Wang Qunying, Xu Xiangzhou, etc Assessment of waterlogging resilience in Zhengzhou City considering waterlogging cycles [J]. Water Resources Protection, 2024, 40 (04): 48-55+91.

[11] Mi Yinyu, Kong Feng International Comparison and Implications of Urban Flood Risk Management Systems under the Background of Climate Change: Taking London, New York, and Zhengzhou as Examples [J]. Water Resources and Hydropower Technology (Chinese and English), 2023, 54 (03): 2134. DOI: 10.13928/j.cnki. wrahe. 2023, 03.002.

[12] Li Xin Multi center structure recognition of cities based on POI feature spatial aggregation characteristics: a case study of Zhengzhou City [J]. Journal of Peking University (Natural Science Edition), 2020, 56 (04): 692702. DOI: 10.13209/j.04798023.2020.044.

[13] Zhang Jinping, Zhang Chaoyang, Left Qiting Urban waterlogging simulation and risk assessment of "7.20" extreme rainfall in Zhengzhou [J]. Journal of North China University of Water Resources and Electric Power (Natural Science Edition), 2023, 44 (02): 17+63. DOI: 10.19760/j.ncwu. zk.2023014.

[14] Liu Jiahong, Pei Yujia, Mei Chao, etc Causes of waterlogging and disaster prevention and control during the "July 20" extremely heavy rainstorm in Zhengzhou [J]. Journal of Zhengzhou University (Engineering Edition), 2023,44 (02): 38-45. DOI: 10.13705/j.issn.1671-6833.2023.02.019.