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Evaluation of surface water quality using multivariate statistical techniques: a case study of Fei-Tsui Reservoir basin, Taiwan

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dc.citedby32
dc.contributor.authorChow M.F.en_US
dc.contributor.authorShiah F.K.en_US
dc.contributor.authorLai C.C.en_US
dc.contributor.authorKuo H.Y.en_US
dc.contributor.authorWang K.W.en_US
dc.contributor.authorLin C.H.en_US
dc.contributor.authorChen T.Y.en_US
dc.contributor.authorKobayashi Y.en_US
dc.contributor.authorKo C.Y.en_US
dc.contributor.authorid57214146115en_US
dc.contributor.authorid7003601734en_US
dc.contributor.authorid36628881300en_US
dc.contributor.authorid36628692800en_US
dc.contributor.authorid55998744700en_US
dc.contributor.authorid56110362400en_US
dc.contributor.authorid58070365400en_US
dc.contributor.authorid55999169700en_US
dc.contributor.authorid55999097100en_US
dc.date.accessioned2023-05-29T06:14:04Z
dc.date.available2023-05-29T06:14:04Z
dc.date.issued2016
dc.descriptionBiochemical oxygen demand; Cluster analysis; Discriminant analysis; Dissolved oxygen; Hierarchical systems; Multivariant analysis; Organic pollutants; Pollution; Potable water; Principal component analysis; Reservoir management; Reservoirs (water); River pollution; Sampling; Statistical methods; Surface waters; Turbidity; Water; Water pollution; Water quality; Hierarchical cluster analysis; Multivariate statistical techniques; Non-point sources pollutions; Restoration and protection; Spatiotemporal patterns; Sustainable management; Total dissolved solids; Water quality variations; Quality control; anthropogenic source; biochemical oxygen demand; cluster analysis; discriminant analysis; dissolved oxygen; drinking water; nonpoint source pollution; organic pollutant; principal component analysis; reservoir; river basin; surface water; water quality; water temperature; Taiwanen_US
dc.description.abstractThe evaluation and interpretation of the spatio-temporal pattern of surface water quality is crucial for the assessment, restoration and protection of drinking water sources. This case study reports different multivariate statistical techniques such as cluster analysis, factor analysis/principal component analysis (FA/PCA) and discriminant analysis, which had been applied for 6�years (2005�2010) water quality data set generated from 19 parameters at 14 different sites within the Fei-Tsui Reservoir basin. Hierarchical cluster analysis grouped 14 sampling sites into three clusters: high-, moderate- and low-pollution regions. This study revealed that water release from the dam outlet will further increase the concentrations of pollutants in the downstream river. PCA/FA did not result in considerable data reduction, as it points to 13 parameters (68�% of original 19) required to explain the 72.8�% of the total variance in the water quality data set. The varifactors obtained from PCA suggested that parameters responsible for water quality variation were mainly related to mineral-related parameters (natural), nutrient group (non-point sources pollution), physical parameters (natural) and organic pollutants (anthropogenic sources). Discriminant analysis used only five parameters: water temperature, dissolved oxygen (DO), calcium, total dissolved solids (TDS) and turbidity; and seven parameters: BOD, DO, nitrate nitrogen, TDS, total alkalinity, turbidity and WT, to discriminate between temporal and spatial with 88 and 90�% correct assignation, respectively. This study illustrated the usefulness of multivariate statistical techniques for designing the sampling and analytical protocol, analysis and interpretation of complex data sets, identification of pollution sources/factors, and provides a reliable guideline for selecting the priorities of possible controlling measures in the sustainable management of Fei-Tsui Reservoir basin. � 2015, Springer-Verlag Berlin Heidelberg.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo6
dc.identifier.doi10.1007/s12665-015-4922-5
dc.identifier.epage15
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84950311513
dc.identifier.spage1
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84950311513&doi=10.1007%2fs12665-015-4922-5&partnerID=40&md5=cbed3111be1e946eec6510ddf6a5eba7
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23003
dc.identifier.volume75
dc.publisherSpringer Verlagen_US
dc.sourceScopus
dc.sourcetitleEnvironmental Earth Sciences
dc.titleEvaluation of surface water quality using multivariate statistical techniques: a case study of Fei-Tsui Reservoir basin, Taiwanen_US
dc.typeArticleen_US
dspace.entity.typePublication
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