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dc.contributor.authorUddin, Md Galal
dc.contributor.authorNash, Stephen
dc.contributor.authorOlbert, Agnieszka Indiana
dc.date.accessioned2021-01-07T14:19:22Z
dc.date.available2021-01-07T14:19:22Z
dc.date.issued2020-12-17
dc.identifier.citationUddin, Md Galal, Nash, Stephen, & Olbert, Agnieszka I. (2021). A review of water quality index models and their use for assessing surface water quality. Ecological Indicators, 122, 107218. doi:https://doi.org/10.1016/j.ecolind.2020.107218en_IE
dc.identifier.issn1470-160X
dc.identifier.urihttp://hdl.handle.net/10379/16426
dc.description.abstractThe water quality index (WQI) model is a popular tool for evaluating surface water quality. It uses aggregation techniques that allow conversion of extensive water quality data into a single value or index. Globally, the WQI model has been applied to evaluate water quality (surface water and groundwater) based on local water quality criteria. Since its development in the 1960s, it has become a popular tool due to its generalised structure and ease-of-use. Commonly, WQI models involve four consecutive stages; these are (1) selection of the water quality parameters, (2) generation of sub-indices for each parameter (3) calculation of the parameter weighting values, and (4) aggregation of sub-indices to compute the overall water quality index. Several researchers have utilized a range of applications of WQI models to evaluate the water quality of rivers, lakes, reservoirs, and estuaries. Some problems of the WQI model are that they are usually developed based on site-specific guidelines for a particular region, and are therefore not generic. Moreover, they produce uncertainty in the conversion of large amounts of water quality data into a single index. This paper presents a comparative discussion of the most commonly used WQI models, including the different model structures, components, and applications. Particular focus is placed on parameterization of the models, the techniques used to determine the sub-indices, parameter weighting values, index aggregation functions and the sources of uncertainty. Issues affecting model accuracy are also discussed.en_IE
dc.description.sponsorshipThe authors would like to acknowledge the Hardiman Research Scholarship of the National University of Ireland Galway, which funded the first author as part of his PhD program. The reserach was also supported by MaREI, the SFI Research Centre for Energy, Climate, and Marine [Grant No: 12/RC/2302_P2].en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherElsevieren_IE
dc.relation.ispartofEcological Indicatorsen
dc.subjectwater quality index (WQI)en_IE
dc.subjectSurface water qualityen_IE
dc.subjectWater quality parametersen_IE
dc.subjectSub-indexen_IE
dc.subjectAggregation functionen_IE
dc.subjectModel uncertainty and sensitivityen_IE
dc.titleA review study of water quality index models and their use for assessing surface water qualityen_IE
dc.typeArticleen_IE
dc.date.updated2021-01-06T11:25:43Z
dc.identifier.doi10.1016/j.ecolind.2020.107218
dc.local.publishedsourcehttps://doi.org/10.1016/j.ecolind.2020.107218en_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderHardiman Research Scholarship, National University of Ireland Galwayen_IE
dc.contributor.funderMarine Instituteen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.internal.rssid23663844
dc.local.contactAgnieszka Olbert, Civil Engineering, Neb Room 2030, Nui Galway. 3208 Email: indiana.olbert@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionSUBMITTED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2302/IE/Marine Renewable Energy Ireland (MaREI) - The SFI Centre for Marine Renewable Energy Research/en_IE
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