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dc.contributor.authorRodriguez, M
dc.contributor.authorFu, G
dc.contributor.authorButler, D
dc.contributor.authorYuan, Z
dc.contributor.authorCook, L
dc.date.accessioned2023-08-01T09:27:04Z
dc.date.issued2023-07-13
dc.date.updated2023-08-01T08:48:30Z
dc.description.abstractManaging and reducing combined sewer overflow (CSO) discharges is crucial for enhancing the resilience of combined sewer systems (CSS). However, the absence of a standardised resilience analysis approach poses challenges in developing effective discharge reduction strategies. To address this, our study presents a top-down method that expands the existing Global Resilience Analysis to quantify resilience performance in CSS. This approach establishes a link between threats (e.g., rainfall) and impacts (e.g., CSOs) through continuous and long-term simulation, accommodating various rainfall patterns, including extreme events. We assess CSO discharge impacts from a resilience perspective by introducing eight new metrics. We conducted a case study in Fehraltorf, Switzerland, analysing the performance of three green infrastructure (GI) types (bioretention cells, green roofs, and permeable pavements) over 38 years. The results demonstrated that GI enhanced all resilience indices, with variations observed in individual CSO performance metrics and their system locations. Notably, in Fehraltorf, green roofs emerged as the most effective GI type for improving resilience, while the downstream outfall displayed the highest resilience enhancement. Overall, our proposed method enables a shift from event-based to continuous simulation analysis, providing a standardised approach for resilience assessment. This approach informs the development of strategies for CSO discharge reduction and the enhancement of CSS resilience.en_GB
dc.description.sponsorshipQUEX Instituteen_GB
dc.description.sponsorshipEawagen_GB
dc.format.extent118607-
dc.format.mediumPrint-Electronic
dc.identifier.citationVol. 344, article 118607en_GB
dc.identifier.doihttps://doi.org/10.1016/j.jenvman.2023.118607
dc.identifier.urihttp://hdl.handle.net/10871/133680
dc.identifierORCID: 0000-0003-1045-9125 (Fu, Guangtao)
dc.identifierScopusID: 55499297600 | 57212739920 (Fu, Guangtao)
dc.identifierResearcherID: ABE-3874-2021 (Fu, Guangtao)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/37453297en_GB
dc.rights© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectCombined sewer overflowsen_GB
dc.subjectGreen infrastructureen_GB
dc.subjectResilienceen_GB
dc.subjectStormwateren_GB
dc.subjectThreaten_GB
dc.subjectTop-down approachen_GB
dc.titleGlobal resilience analysis of combined sewer systems under continuous hydrologic simulationen_GB
dc.typeArticleen_GB
dc.date.available2023-08-01T09:27:04Z
dc.identifier.issn0301-4797
exeter.article-number118607
exeter.place-of-publicationEngland
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this recorden_GB
dc.descriptionData availability: Data will be made available on request.en_GB
dc.identifier.eissn1095-8630
dc.identifier.journalJournal of Environmental Managementen_GB
dc.relation.ispartofJ Environ Manage, 344
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2023-07-07
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-07-13
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-08-01T09:21:36Z
refterms.versionFCDVoR
refterms.dateFOA2023-08-01T09:27:10Z
refterms.panelBen_GB


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© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).