International Journal of Environmental Science and Development

Abstract—The aim of this study is to assess the spatial variability and to determine the main contamination sources in surface water quality of the Nhue River, Viet Nam by using multivariate statistical analysis techniques, including principal component analysis (PCA) and cluster analysis (CA). Eight water quality parameters were measured at 21 sites along the Nhue River and its tributaries during irrigated periods from 2016 to 2019. The spatial variability of water quality in the Nhue River and its tributaries was determined separately from cluster analysis. The result determined two tributaries, including Yen Xa Canal (NT9 monitoring site) and To Lich River (NT3 monitoring site) leading to severe pollution at To Bridge (N4 monitoring site) region in the Nhue River. The PCA determined a reduced number of two principal components that explained 47.75% of the total variation in the data. The first PC indicated that water temperature (WT) and pH are the dominant polluting factors which are attributed to craft villages, domestic sewage and industrial wastewater. Following is nitrate nitrogen NO3¯ in the second PC which is related to fertilizer application in the farms nearby. The results indicated that CA multivariate statistical analysis technique is useful for the assessment of the spatial water quality variability in a river which has a number of tributaries.
Index Terms—Water quality, principal component analysis, cluster analysis, multivariate statistical analysis.

Nguyen Huu Hue is with the Faculty of Civil Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi, Vietnam (e-mail: nguyenhuuhue@tlu.edu.vn).
Nguyen Huu Thanh is with the Institute of Civil Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi, Vietnam (e-mail: nguyenhuuthanhtla@gmail.com).

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Cite: Nguyen Huu Hue and Nguyen Huu Thanh, "Assessment of Surface Water Quality by Using Multivariate Statistical Analysis Techniques: A Case Study of Nhue River, Vietnam," International Journal of Environmental Science and Development vol. 11, no. 10, pp. 488-492, 2020.

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