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Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Author

Listed:
  • Fatemeh Jalayer
  • Raffaele Risi
  • Francesco Paola
  • Maurizio Giugni
  • Gaetano Manfredi
  • Paolo Gasparini
  • Maria Topa
  • Nebyou Yonas
  • Kumelachew Yeshitela
  • Alemu Nebebe
  • Gina Cavan
  • Sarah Lindley
  • Andreas Printz
  • Florian Renner

Abstract

Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia. Copyright Springer Science+Business Media Dordrecht 2014

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  • Fatemeh Jalayer & Raffaele Risi & Francesco Paola & Maurizio Giugni & Gaetano Manfredi & Paolo Gasparini & Maria Topa & Nebyou Yonas & Kumelachew Yeshitela & Alemu Nebebe & Gina Cavan & Sarah Lindley , 2014. "Probabilistic GIS-based method for delineation of urban flooding risk hotspots," 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. 73(2), pages 975-1001, September.
    • Handle: RePEc:spr:nathaz:v:73:y:2014:i:2:p:975-1001
    DOI: 10.1007/s11069-014-1119-2
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    1. Meyer, Volker & Messner, Frank, 2005. "National flood damage evaluation methods: A review of applied methods in England, the Netherlands, the Czech Republik and Germany," UFZ Discussion Papers 21/2005, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
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    1. Senait Nigussie & Tilahun Mulatu & Li Liu & Kumelachew Yeshitela, 2024. "The impact of land use/cover change on the supply, demand, and budgets of ecosystem services in the Little Akaki River catchment, Ethiopia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 27975-28006, November.
    2. Shuqi Wu & Shisong Cao & Zhiheng Wang & Xinyuan Qu & Shanfei Li & Wenji Zhao, 2019. "Spatiotemporal Variations in Agricultural Flooding in Middle and Lower Reaches of Yangtze River from 1970 to 2018," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
    3. Agraw Ali Beshir & Jaemin Song, 2021. "Urbanization and its impact on flood hazard: the case of Addis Ababa, Ethiopia," 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. 109(1), pages 1167-1190, October.
    4. Salvatore Manfreda & Caterina Samela & Andrea Gioia & Giuseppe Consoli & Vito Iacobellis & Luciana Giuzio & Andrea Cantisani & Aurelia Sole, 2015. "Flood-prone areas assessment using linear binary classifiers based on flood maps obtained from 1D and 2D hydraulic models," 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. 79(2), pages 735-754, November.
    5. Peng Gao & Wei Gao & Nan Ke, 2021. "Assessing the impact of flood inundation dynamics on an urban environment," 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. 109(1), pages 1047-1072, October.
    6. Raffaele De Risi & Fatemeh Jalayer & Francesco De Paola & Stefano Carozza & Nebyou Yonas & Maurizio Giugni & Paolo Gasparini, 2020. "From flood risk mapping toward reducing vulnerability: the case of Addis Ababa," 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. 100(1), pages 387-415, January.
    7. Cavalieri, Francesco & Franchin, Paolo & Giovinazzi, Sonia, 2023. "Multi-hazard assessment of increased flooding hazard due to earthquake-induced damage to the natural drainage system," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

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