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  • Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam

    Author(s)
    Dung, Phung
    Huang, Cunrui
    Rutherford, Shannon
    Dwirahmadi, Febi
    Chu, Cordia
    Wang, Xiaoming
    Minh, Nguyen
    Nga, Huy Nguyen
    Cuong, Manh Do
    Trung, Hieu Nguyen
    Tuan, Anh Diep Dinh
    Griffith University Author(s)
    Chu, Cordia M.
    Rutherford, Shannon
    Phung, Dung T.
    Huang, Cunrui
    Dwirahmadi, Febi
    Year published
    2015
    Metadata
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    Abstract
    The 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 ...
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    The 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.
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    Journal Title
    Environmental Monitoring and Assessment
    Volume
    187
    Issue
    5
    DOI
    https://doi.org/10.1007/s10661-015-4474-x
    Subject
    Environmental Monitoring
    Publication URI
    http://hdl.handle.net/10072/101030
    Collection
    • Journal articles

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