Global resilience analysis of combined sewer systems under continuous hydrologic simulation
dc.contributor.author | Rodriguez, M | |
dc.contributor.author | Fu, G | |
dc.contributor.author | Butler, D | |
dc.contributor.author | Yuan, Z | |
dc.contributor.author | Cook, L | |
dc.date.accessioned | 2023-08-01T09:27:04Z | |
dc.date.issued | 2023-07-13 | |
dc.date.updated | 2023-08-01T08:48:30Z | |
dc.description.abstract | Managing 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.sponsorship | QUEX Institute | en_GB |
dc.description.sponsorship | Eawag | en_GB |
dc.format.extent | 118607- | |
dc.format.medium | Print-Electronic | |
dc.identifier.citation | Vol. 344, article 118607 | en_GB |
dc.identifier.doi | https://doi.org/10.1016/j.jenvman.2023.118607 | |
dc.identifier.uri | http://hdl.handle.net/10871/133680 | |
dc.identifier | ORCID: 0000-0003-1045-9125 (Fu, Guangtao) | |
dc.identifier | ScopusID: 55499297600 | 57212739920 (Fu, Guangtao) | |
dc.identifier | ResearcherID: ABE-3874-2021 (Fu, Guangtao) | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/37453297 | en_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.subject | Combined sewer overflows | en_GB |
dc.subject | Green infrastructure | en_GB |
dc.subject | Resilience | en_GB |
dc.subject | Stormwater | en_GB |
dc.subject | Threat | en_GB |
dc.subject | Top-down approach | en_GB |
dc.title | Global resilience analysis of combined sewer systems under continuous hydrologic simulation | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2023-08-01T09:27:04Z | |
dc.identifier.issn | 0301-4797 | |
exeter.article-number | 118607 | |
exeter.place-of-publication | England | |
dc.description | This is the final version. Available on open access from Elsevier via the DOI in this record | en_GB |
dc.description | Data availability: Data will be made available on request. | en_GB |
dc.identifier.eissn | 1095-8630 | |
dc.identifier.journal | Journal of Environmental Management | en_GB |
dc.relation.ispartof | J Environ Manage, 344 | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023-07-07 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-07-13 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2023-08-01T09:21:36Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2023-08-01T09:27:10Z | |
refterms.panel | B | en_GB |
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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/).