Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/170323
Title: Methodology to Prioritize Climate Adaptation Measures in Urban Areas. Barcelona and Bristol Case Studies
Author: Herrero-Hidalga, Maria
Martínez-Gomariz, Eduardo
Evans, Barry
Webber, James
Termes, Montserrat
Russo, Beniamino
Locatelli, Luca
Keywords: Canvi climàtic
Gestió del risc
Avaluació
Sociologia
Climatic change
Risk management
Evaluation
Sociology
Issue Date: Jun-2020
Publisher: MDPI
Abstract: In the current context of fast innovation in the field of urban resilience against extreme weather events, it is becoming more challenging for decision-makers to recognize the most beneficial adaptation measures for their cities. Detailed assessment of multiple measures is resource-consuming and requires specific expertise, which is not always available. To tackle these issues, in the context of the H2020 project RESCCUE (RESilience to cope with Climate Change in Urban arEas), a methodology to effectively prioritize adaptation measures against extreme rainfall-related hazards in urban areas has been developed. It follows a multi-phase structure to progressively narrow down the list of potential measures. It begins using less resource-intensive techniques, to finally focus on the in-depth analysis on a narrower selection of measures. It involves evaluation of risks, costs, and welfare impacts, with strong focus on stakeholders' participation through the entire process. The methodology is adaptable to different contexts and objectives and has been tested in two case studies across Europe, namely Barcelona and Bristo
Note: Reproducció del document publicat a: https://doi.org/10.3390/su12124807
It is part of: Sustainability, 2020, vol. 12, num. 4807, p. 01-25
URI: http://hdl.handle.net/2445/170323
Related resource: https://doi.org/10.3390/su12124807
ISSN: 2071-1050
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

Files in This Item:
File Description SizeFormat 
703166.pdf1.63 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons