Open AccessIntegrating social vulnerability into federal flood risk management planning
Author(s) -
Cutter S.L.,
Emrich C.T.,
Morath D.P.,
Dunning C.M.
Publication year - 2013
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/jfr3.12018
Subject(s) - flood myth , transferability , social vulnerability , robustness (evolution) , vulnerability (computing) , computer science , scalability , metric (unit) , software deployment , flood control , flooding (psychology) , operations research , risk analysis (engineering) , environmental resource management , environmental science , business , geography , operations management , computer security , engineering , psychological resilience , psychotherapist , archaeology , psychology , database , chemistry , operating system , biochemistry , logit , machine learning , gene
Abstract While flood risk management planning in the U nited S tates has focused on flood control structures designed to protect the economic value of property, it has consistently undervalued other social impacts associated with flooding. The US A rmy C orps of E ngineers ( USACE ) recently initiated research aimed at understanding how to incorporate social characteristics into the measures currently utilised in flood control project evaluation and consideration. This paper proposes a methodology for incorporating a known measure of social vulnerability, the S ocial V ulnerability I ndex ( SoVI ), into USACE civil works planning. Using the USACE S outh A tlantic D ivision as the study area, this paper evaluates eight different variations of the social vulnerability metric and their potential deployment in USACE projects. Each formulation is compared with the original‐computed SoVI as a means to test its spatial and statistical sensitivity, including an assessment of each variant's robustness, reducibility, scalability, and transferability. Results indicate that while it is possible to create simplified, yet robust, versions of SoVI for individual places, such ‘lite’ metrics tend to fall short in areas of scalability and transferability in relation to the original SoVI formulation.