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dc.contributor.authorWebber, JL
dc.contributor.authorBalbi, M
dc.contributor.authorLallemant, D
dc.contributor.authorGibson, MJ
dc.contributor.authorFu, G
dc.contributor.authorButler, D
dc.contributor.authorHamel, P
dc.date.accessioned2021-07-27T09:42:08Z
dc.date.issued2021-07-24
dc.description.abstracthis paper presents the advantages and opportunities for rapid preliminary intervention screening to enhance inclusion of green infrastructures in regional scale stormwater management. Stormwater flooding is widely recognised as a significant and worsening natural hazard across the globe; however, current management approaches aimed at the site scale do not adequately explore opportunities for integrated management at the regional scale at which decisions are made. This research addresses this gap through supporting the development of stormwater management strategies, including green infrastructure, at a regional scale. This is achieved through upscaling a modelling approach using a spatially explicit inundation model (CADDIES) coupled with an economic model of inundation loss (OpenProFIA) to support widescale evaluation of green infrastructure during the informative early-stage development of stormwater management strategies. This novel regional scale approach is demonstrated across a case study of the San Francisco Bay Area, spanning 8300 sq km. The main opportunity from this regional approach is to identify spatial and temporal trends which are used to inform regional planning and direct future detailed modelling efforts. The study highlights several limitations of the new method, suggesting it should be applied as part of a suite of landscape management approaches; however, highlights that it has the potential to complement existing stormwater management toolkitsen_GB
dc.description.sponsorshipNatural Capital Projecten_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipBetty and Gordon Moore Foundationen_GB
dc.description.sponsorshipNanyang Technological University and National Research Foundation, Prime Minister’s Office, Singaporeen_GB
dc.description.sponsorshipEngineering School, Universidad de Buenos Airesen_GB
dc.identifier.citationVol. 13 (15), article 2027en_GB
dc.identifier.doi10.3390/w13152027
dc.identifier.grantnumberEP/N010329/1en_GB
dc.identifier.grantnumberNE/P011217/1en_GB
dc.identifier.grantnumberNRF-NRFF12-2020-0009en_GB
dc.identifier.grantnumberNRF-NRFF2018-06en_GB
dc.identifier.urihttp://hdl.handle.net/10871/126563
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectflood modellingen_GB
dc.subjectgreen infrastructureen_GB
dc.subjectregional planningen_GB
dc.subjectstormwater managementen_GB
dc.titleTowards Regional Scale Stormwater Flood Management Strategies through Rapid Preliminary Intervention Screeningen_GB
dc.typeArticleen_GB
dc.date.available2021-07-27T09:42:08Z
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this recorden_GB
dc.descriptionData Availability Statement: Data underpinning this study is available upon reasonable request through contacting the authors.en_GB
dc.identifier.eissn2073-4441
dc.identifier.journalWateren_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2021-07-21
exeter.funder::Engineering and Physical Sciences Research Council (EPSRC)en_GB
exeter.funder::Natural Environment Research Council (NERC)en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2021-07-24
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-07-27T09:38:41Z
refterms.versionFCDVoR
refterms.dateFOA2021-07-27T09:42:22Z
refterms.panelBen_GB


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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).