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Urban flood susceptibility analysis using a GIS-based multi-criteria analysis framework

Author

Listed:
  • Lin Lin

    (Zhengzhou University)

  • Zening Wu

    (Zhengzhou University)

  • Qiuhua Liang

    (Loughborough University)

Abstract

Pluvial flooding is a common type of natural hazard caused by rainfall events with high intensity and short duration, which may lead to substantial property damages, transportation interruptions, and casualties. Modern cities are susceptible to pluvial flooding due to dense population and advanced economic development. To facilitate the development of better flood control and risk mitigation strategies, this study presents a new quantitative flood susceptibility analysis framework to estimate the potential flood extents and scale. The framework is based on the multi-criteria decision-making methods within a platform of the geographic information system (GIS). A composite urban flood risk index (FRI) is derived from various flood conditioning factors. The FRI consists of flood vulnerability index, hazard factors, and resilience capacity indicators. The flood-susceptible map is generated using the GIS spatial analysis tools and the analytic hierarchy process method. Zhengzhou city, China, is selected as the case study area. The result map shows that the highly susceptible areas are mainly located in Jinshui District, accounting for 64% of the total area of the risk zone. To further validate this framework, a flood inventory map is produced by mapping 74 test locations identified through survey data in this area, followed by plotting a receiver operating characteristic (ROC) curve. The ROC shows an area under the curve of 74.27%, which validates the proposed framework. Compared with other methods, the proposed framework is particularly suitable for application in data-scarce cases.

Suggested Citation

  • Lin Lin & Zening Wu & Qiuhua Liang, 2019. "Urban flood susceptibility analysis using a GIS-based multi-criteria analysis framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(2), pages 455-475, June.
    • Handle: RePEc:spr:nathaz:v:97:y:2019:i:2:d:10.1007_s11069-019-03615-2
    DOI: 10.1007/s11069-019-03615-2
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    References listed on IDEAS

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    Cited by:

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    3. Raymond Seyeram Nkonu & Mary Antwi & Mark Amo-Boateng & Benjamin Wullobayi Dekongmen, 2023. "GIS-based multi-criteria analytical hierarchy process modelling for urban flood vulnerability analysis, Accra Metropolis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(2), pages 1541-1568, June.
    4. Gabriela Reis & Francisco Assis Souza Filho & Donald Robert Nelson & Renan Vieira Rocha & Samiria Maria Oliveira Silva, 2020. "Development of a drought vulnerability index using MCDM and GIS: study case in São Paulo and Ceará, Brazil," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(2), pages 1781-1799, November.
    5. Jinping Tong & Fei Gao & Hui Liu & Jing Huang & Gaofeng Liu & Hanyue Zhang & Qiong Duan, 2023. "A Study on Identification of Urban Waterlogging Risk Factors Based on Satellite Image Semantic Segmentation and XGBoost," Sustainability, MDPI, vol. 15(8), pages 1-15, April.
    6. Sadhan Malik & Subodh Chandra Pal & Alireza Arabameri & Indrajit Chowdhuri & Asish Saha & Rabin Chakrabortty & Paramita Roy & Biswajit Das, 2021. "GIS-based statistical model for the prediction of flood hazard susceptibility," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16713-16743, November.
    7. Anna Palla & Ilaria Gnecco, 2021. "The Web-GIS TRIG Eau Platform to Assess Urban Flood Mitigation by Domestic Rainwater Harvesting Systems in Two Residential Settlements in Italy," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    8. Chao Ma & Wenchao Qi & Hongshi Xu & Kai Zhao, 2022. "An integrated quantitative framework to assess the impacts of disaster-inducing factors on causing urban flood," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(3), pages 1903-1924, September.
    9. Ahmed M. Youssef & Ali M. Mahdi & Hamid Reza Pourghasemi, 2023. "Optimal flood susceptibility model based on performance comparisons of LR, EGB, and RF algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1071-1096, January.

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    Keywords

    Susceptibility; MCDM; GIS; AHP;
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