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A GIS-Based Index of Physical Susceptibility to Flooding as a Tool for Flood Risk Management

Author

Listed:
  • Francis Miranda

    (Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil)

  • Anna Beatriz Franco

    (Programa de Engenharia Civil, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-450, Brazil)

  • Osvaldo Rezende

    (Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil)

  • Bruno B. F. da Costa

    (Instituto Politécnico, Universidade Federal do Rio de Janeiro, Macaé 27930-560, Brazil)

  • Mohammad Najjar

    (Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil)

  • Assed N. Haddad

    (Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil)

  • Marcelo Miguez

    (Programa de Engenharia Ambiental, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
    Programa de Engenharia Civil, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-450, Brazil
    Programa de Engenharia Urbana, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil)

Abstract

The identification and classification of flood-prone areas comprise a fundamental step in the Flood Risk Management approach, providing subsidies for land use planning, floodproofing policies, the design of mitigation measures and early warning systems. To address this issue, a frequently used preliminary tool is the flood susceptibility mapping of a region using a range of widely available data. Therefore, the present study introduces an index-based approach able to qualitatively assess flood-prone areas, named Physical Susceptibility to Floods Index (PhySFI), based on a multi-criteria decision-making method and developed in a GIS environment. The methodology presupposes a critical discussion of variables commonly used in other flood indexes, intending to simplify the proposed representation, and emphasizes the role of the user/modeler. PhySFI is composed of just four indicators, based on physical parameters of the assessed environment. This index was developed and first applied in the city of Rio de Janeiro, as part of the Rio de Janeiro Climate Change Adaptation Plan. The validation process was based on a comparative analysis with flood extent and height simulated by the hydrodynamic modeling of four watersheds within the study area, with different urbanization processes for each one. The results indicate that the index is a powerful preliminary tool to assess flood-prone areas in coastal cities.

Suggested Citation

  • Francis Miranda & Anna Beatriz Franco & Osvaldo Rezende & Bruno B. F. da Costa & Mohammad Najjar & Assed N. Haddad & Marcelo Miguez, 2023. "A GIS-Based Index of Physical Susceptibility to Flooding as a Tool for Flood Risk Management," Land, MDPI, vol. 12(7), pages 1-22, July.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1408-:d:1193187
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    References listed on IDEAS

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    1. Wanderson Luiz-Silva & Antonio Carlos Oscar-Júnior, 2022. "Climate extremes related with rainfall in the State of Rio de Janeiro, Brazil: a review of climatological characteristics and recorded trends," 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. 114(1), pages 713-732, October.
    2. Joshy Jacob, 2018. "A Note from the Editor," Vikalpa: The Journal for Decision Makers, , vol. 43(3), pages 1-1, September.
    3. Claudia Tebaldi & Roshanka Ranasinghe & Michalis Vousdoukas & D. J. Rasmussen & Ben Vega-Westhoff & Ebru Kirezci & Robert E. Kopp & Ryan Sriver & Lorenzo Mentaschi, 2021. "Extreme sea levels at different global warming levels," Nature Climate Change, Nature, vol. 11(9), pages 746-751, September.
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