Show simple item record

dc.contributor.authorDung, Phung
dc.contributor.authorHuang, Cunrui
dc.contributor.authorRutherford, Shannon
dc.contributor.authorDwirahmadi, Febi
dc.contributor.authorChu, Cordia
dc.contributor.authorWang, Xiaoming
dc.contributor.authorMinh, Nguyen
dc.contributor.authorNga, Huy Nguyen
dc.contributor.authorCuong, Manh Do
dc.contributor.authorTrung, Hieu Nguyen
dc.contributor.authorTuan, Anh Diep Dinh
dc.date.accessioned2018-01-04T04:38:14Z
dc.date.available2018-01-04T04:38:14Z
dc.date.issued2015
dc.identifier.issn0167-6369
dc.identifier.doi10.1007/s10661-015-4474-x
dc.identifier.urihttp://hdl.handle.net/10072/101030
dc.description.abstractThe present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70 % of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH3 are the discriminating parameters in space, affording 67 % correct assignation in spatial analysis; pH and NO2 are the discriminating parameters according to season, assigning approximately 60 % of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto13
dc.relation.ispartofissue5
dc.relation.ispartofjournalEnvironmental Monitoring and Assessment
dc.relation.ispartofvolume187
dc.subject.fieldofresearchEnvironmental Monitoring
dc.subject.fieldofresearchcode050206
dc.titleTemporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, Griffith School of Environment
gro.hasfulltextNo Full Text
gro.griffith.authorChu, Cordia M.
gro.griffith.authorRutherford, Shannon
gro.griffith.authorPhung, Dung T.
gro.griffith.authorDwirahmadi, Febi


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record