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Index-based Approach to Evaluate City Resilience in Flooding Scenarios

Author(s):



Medium: journal article
Language(s): English
Published in: Civil Engineering Journal, , n. 2, v. 7
Page(s): 197-207
DOI: 10.28991/cej-2021-03091647
Abstract:

Intense rainfall events combined with high tide levels frequently result in urban floods in riverine or coastal cities. Their increasing variability and uncertainty demand urgent but sustained responses. Thus, resilience-driven approaches are emerging in contrast to the traditional technical-economic frameworks, as urban resilience reflects the overall capacity of a city to survive, adapt and thrive when experiencing stresses and shocks. This paper presents a simplified index-based methodology for the evaluation and quantification of urban resilience to flooding, based on the works developed in the EU H2020 RESCCUE project. A set of five indicators are proposed to compute the Integrated Urban Resilience Index (IURI), allowing to classify resilience according to a proposed range of rankings. This methodology considers simultaneously a multisectoral approach, reflecting services interdependences, and a sectorial approach, applying 1D/2D computational modelling of the urban drainage network. It was applied to the study case of Lisbon downtown, involving the analysis of interdependencies between 124 infrastructures of 10 urban services. Two scenarios were considered, respecting the current and future situations, considering climate changes. Results enhance the usefulness, practicability, and potential of the proposed approach, and improvement opportunities were also identified for future developments. 

Copyright: © 2021 João Barreiro, Ruth Lopes, Filipa Ferreira, José Saldanha Matos
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10560253
  • Published on:
    03/02/2021
  • Last updated on:
    02/06/2021
 
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