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Comprehensive Statistical Analysis for Characterizing Water Quality Assessment in the Mekong Delta: Trends, Variability, and Key Influencing Factors

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  • Vu Thanh Doan

    (Hydro-Meteorology and Water Resource Faculty, Ho Chi Minh City University of Natural Resources and Environment, Ho Chi Minh City 70000, Vietnam
    Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam)

  • Chinh Cong Le

    (Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam)

  • Hung Van Tien Le

    (Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam)

  • Ngoc Anh Trieu

    (Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam)

  • Phu Le Vo

    (Faculty of Environment & Natural Resources, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City 70000, Vietnam
    Vietnam National University Ho Chi Minh, Linh Trung Ward, Ho Chi Minh City 70000, Vietnam)

  • Dang An Tran

    (Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam)

  • Hai Van Nguyen

    (Faculty of Water Resources Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 10000, Vietnam)

  • Toshinori Tabata

    (Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-Environmental Sciences, Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan)

  • Thu Thi Hoai Vu

    (The Institute of Civil Engineering, University of Transport Ho Chi Minh City, Ho Chi Minh City 70000, Vietnam)

Abstract

The Mekong Delta, an important agricultural and economic hub in Vietnam, has suffered from severe water quality issues caused by both natural and anthropogenic forces. This paper aims to conduct a rational statistical approach to evaluate the current situation of surface water quality in the Mekong Delta, applying Factor Analysis (FA), Principal Component Analysis (PCA), and Agglomerative Hierarchical Clustering (AHC) to a database of 3117 samples collected by national and provincial monitoring stations. The results revealed significant contamination with organic pollutants (BOD5: 3.50–172.870 mg/L, COD: 6.493–472.984 mg/L), pesticides (e.g., DDTs: n.d to 1.227 mg/L), trace metals (As: 0.006–0.046 mg/L, Cr: n.d–1.960 mg/L), and microbial indicators (Coliforms: n.d–45,100 MPN/100 mL), often higher than the WHO drinking water threshold. PCA/AHC analysis identified the following five major pollution components: (1) organic pollution and sewage/industrial and deposited chemicals (PCA1—23.08% variance); (2) pesticide and agricultural runoff derived contamination with Hg (PCA2—15.44%); (3) microbial pollution of the water was found to correlate positively with Zn and Cu content (PCA3—8.90%); (4) salinity was found to mobilize As and Cr (PCA4—8.00%); (5) nutrient/microbial pollution presumably from agricultural and sewage inputs (PCA5—7.22%). AHC showed some spatial variability that grouped samples in urban/industrial (Cluster 1), rural/agricultural (Cluster 2), and a highly contaminated one, where water was toxic and presented with microbial and Cd contamination (Cluster 3). Levels of pesticides, Cr, and microbial pollution were higher than reported in previous Mekong Delta studies and exceeded regional trends. These results emphasize the importance of holistic water management strategies, including better wastewater treatment, pesticide control, sustainable farming, and climate-adaptive measures to reduce saltwater intrusion and safeguard drinking water quality for the Mekong Delta.

Suggested Citation

  • Vu Thanh Doan & Chinh Cong Le & Hung Van Tien Le & Ngoc Anh Trieu & Phu Le Vo & Dang An Tran & Hai Van Nguyen & Toshinori Tabata & Thu Thi Hoai Vu, 2025. "Comprehensive Statistical Analysis for Characterizing Water Quality Assessment in the Mekong Delta: Trends, Variability, and Key Influencing Factors," Sustainability, MDPI, vol. 17(12), pages 1-18, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:12:p:5375-:d:1676436
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    References listed on IDEAS

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    1. Wenjie Yang & Yue Zhao & Dong Wang & Huihui Wu & Aijun Lin & Li He, 2020. "Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China," IJERPH, MDPI, vol. 17(8), pages 1-14, April.
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