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dc.contributor.authorSadr, SMK
dc.contributor.authorCasal-Campos, A
dc.contributor.authorFu, G
dc.contributor.authorFarmani, R
dc.contributor.authorWard, S
dc.contributor.authorButler, D
dc.date.accessioned2020-06-18T14:32:19Z
dc.date.issued2020-06-06
dc.description.abstractEmerging threats such as climate change and urbanisation pose an unprecedented challenge to integrated management of urban wastewater systems, which are expected to function in a reliable, resilient and sustainable manner regardless of future conditions. Traditional long term planning is rather limited in developing no-regret strategies that avoid maladaptive lock-ins in the near term and allow for flexibility in the long term. In this study, a novel adaptation pathways approach for urban wastewater management is developed in order to explore the compliance and adaptability potential of intervention strategies in a long term operational period, accounting for different future scenarios and multiple performance objectives in terms of reliability, resilience and sustainability. This multi-criteria multi-scenario approach implements a regret-based method to assess the relative performance of two types of adaptation strategies: (I) standalone strategies (i.e. green or grey strategies only); and (II) hybrid strategies (i.e. combined green and grey strategies). A number of adaptation thresholds (i.e. the points at which the current strategy can no longer meet defined objectives) are defined to identify compliant domains (i.e. periods of time in a future scenario when the performance of a strategy can meet the targets). The results obtained from a case study illustrate the trade-off between adapting to short term pressures and addressing long term challenges. Green strategies show the highest performance in simultaneously meeting near and long term needs, while grey strategies are found less adaptable to changing circumstances. In contrast, hybrid strategies are effective in delivering both short term compliance and long term adaptability. It is also shown that the proposed adaption pathways method can contribute to the identification of adaptation strategies that are developed as future conditions unfold, allowing for more flexibility and avoiding long term commitment to strategies that may cause maladaptation. This provides insights into the near term and long term planning of ensuring the reliability, resilience and sustainability of integrated urban drainage systems.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.identifier.citationArticle 116013en_GB
dc.identifier.doi10.1016/j.watres.2020.116013
dc.identifier.grantnumberEP/G037094/1en_GB
dc.identifier.grantnumberEP/N010329/1en_GB
dc.identifier.grantnumberEP/K006924/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/121525
dc.language.isoenen_GB
dc.publisherElsevier / IWA Publishingen_GB
dc.relation.urlhttps://doi.org/10.24378/exe.2443en_GB
dc.rights© 2020 Published by Elsevier Ltd.. Open access under a Creative Commons license: https://creativecommons.org/licenses/by/4.0/en_GB
dc.subjectAdaptation pathwaysen_GB
dc.subjectGreen strategiesen_GB
dc.subjectHybrid strategiesen_GB
dc.subjectResilienceen_GB
dc.subjectSustainabilityen_GB
dc.subjectUrban wastewater systemsen_GB
dc.titleStrategic planning of the integrated urban wastewater system using adaptation pathways (article)en_GB
dc.typeArticleen_GB
dc.date.available2020-06-18T14:32:19Z
dc.identifier.issn0043-1354
exeter.article-number116013en_GB
dc.descriptionThis is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recorden_GB
dc.descriptionThe dataset associated with this article is located in ORE at: https://doi.org/10.24378/exe.2443en_GB
dc.identifier.journalWater Researchen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dcterms.dateAccepted2020-06-02
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2020-06-02
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-06-18T14:29:07Z
refterms.versionFCDAM
refterms.dateFOA2020-06-18T14:32:25Z
refterms.panelBen_GB


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© 2020 Published by Elsevier Ltd.. Open access under a Creative Commons license: https://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's licence is described as © 2020 Published by Elsevier Ltd.. Open access under a Creative Commons license: https://creativecommons.org/licenses/by/4.0/