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dc.contributor.authorZhang, J
dc.contributor.authorSavic, D
dc.contributor.authorXu, Q
dc.contributor.authorLiu, K
dc.contributor.authorQiang, Z
dc.date.accessioned2023-11-14T10:26:27Z
dc.date.issued2023-09-15
dc.date.updated2023-11-14T08:55:15Z
dc.description.abstractThe commonly used Poisson rectangular pulse (PRP) model, employed for simulating high-resolution residential water consumption patterns (RWCPs), relies on calibration via medium-resolution RWCPs obtained from practical measurements. This introduces inevitable uncertainty stemming from the measured RWCPs, which consequently impacts the precision of model simulations. Here we enhance the accuracy of the PRP model by addressing the uncertainty of RWCPs. We established a critical sampling size of 2000 household water consumption patterns (HWCPs) with a data logging interval (DLI) of 15 min to attain dependable RWCPs. Through Genetic Algorithm calibration, the optimal values of the PRP model's parameters were determined: pulse frequency λ = 91 d-1, mean of pulse intensity E(I) = 0.346 m3 h-1, standard deviation of pulse intensity STD(I) = 0.292 m3 h-1, mean of pulse duration E(D) = 40 s, and standard deviation of pulse duration STD(D) = 55 s. Furthermore, validation was conducted at both HWCP and RWCP levels. We recommend a sampling size of ≥2000 HWCPs and a DLI of ≤30 min for PRP model calibration to balance simulation precision and practical implementation. This study significantly advances the theoretical foundation and real-world application of the PRP model, enhancing its role in urban water supply system management.en_GB
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_GB
dc.description.sponsorshipMinistry of Science and Technology of Chinaen_GB
dc.description.sponsorshipYouth Innovation Promotion Association of the Chinese Academy of Sciencesen_GB
dc.identifier.citationVol. 18, article 100317en_GB
dc.identifier.doihttps://doi.org/10.1016/j.ese.2023.100317
dc.identifier.grantnumber52170105en_GB
dc.identifier.grantnumber2019YFD1100105en_GB
dc.identifier.grantnumber2019043en_GB
dc.identifier.urihttp://hdl.handle.net/10871/134519
dc.identifierORCID: 0000-0001-9567-9041 (Savic, Dragan)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/37841652en_GB
dc.rights© 2023 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_GB
dc.subjectModel establishmenten_GB
dc.subjectPoisson rectangular pulse modelen_GB
dc.subjectResidential water consumption patternen_GB
dc.subjectUncertainty analysisen_GB
dc.titlePoisson rectangular pulse (PRP) model establishment based on uncertainty analysis of urban residential water consumption patternsen_GB
dc.typeArticleen_GB
dc.date.available2023-11-14T10:26:27Z
dc.identifier.issn2096-9643
exeter.article-number100317
exeter.place-of-publicationNetherlands
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this record. en_GB
dc.identifier.eissn2666-4984
dc.identifier.journalEnvironmental Science and Ecotechnologyen_GB
dc.relation.ispartofEnviron Sci Ecotechnol, 18
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/ en_GB
dcterms.dateAccepted2023-09-10
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-09-12
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-11-14T10:23:05Z
refterms.versionFCDVoR
refterms.dateFOA2023-11-14T10:26:31Z
refterms.panelBen_GB
refterms.dateFirstOnline2023-09-15


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© 2023 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research
Academy of Environmental Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Except where otherwise noted, this item's licence is described as © 2023 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).