Abstract—This study aims to assess the quality, location and monitoring parameters of surface water quality in the water bodies of Vinh Long province using multivariate statistical methods. Water quality parameters including pH, temperature, turbidity, TSS, EC, DO, BOD, COD, NH₄⁺-N, NO₃^--N, PO₄^3--P, Cl-, E. coli, coliform and Fe were used in the analysis. Cluster analysis (CA) was employed to analyze spatial variations of water quality, while principal component analysis (PCA) was used to identify key indicators affecting water quality. The findings showed that surface water quality in Vinh Long province was contaminated with organic matters (high BOD, COD and low DO), nutrients (NH₄⁺-N, PO₄^3--P), and microorganisms (E. coli, coliforms). The value of water quality health comprehensive was mainly evaluated at a “poor” to “medium” level. The CA results revealed that the water monitoring locations could be reduced from 63 to 48 locations, saving 23.8% of the total monitoring cost. PCA identified seven parameters that considerably influenced surface water due to four polluting water sources: runoff, residential areas, industrial and agricultural activities. Further studies need to identify specific sources and scales of water pollution for appropriate water management strategies.

Index Terms—CA, nutrients, surface water quality, organic pollution, PCA, microorganism.

N. T. Giao is with College of Environment and Natural Resources, Can Tho University, Can Tho 900000, Vietnam (e-mail: ntgiao@ctu.edu.vn).

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Cite: Nguyen Thanh Giao, "Evaluating Surface Water Quality Using Multivariate Statistical Methods: A Case Study in a Province of the Mekong Delta, Vietnam," International Journal of Environmental Science and Development vol. 13, no. 6, pp. 209-215, 2022.

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