Assessing Groundwater Quality in Dong Thap Province Using Multi-variate Statistical Approach

IJEP 42(9): 1061-1070 : Vol. 42 Issue. 9 (September 2022)

Nguyen Thanh Giao1* and Tran Vang Phu2

1. Can Tho University, College of Environment and Natural Resources, Can Tho 900000, Vietnam
2. Can Tho University, School of Law, Can Tho 900000, Vietnam


This study aimed to assess groundwater quality in Dong Thap province of Vietnam using multivariate statistical analysis. The monitoring data were collected in April and September 2019 at 24 locations (namely GW1-GW24) with 20 parameters, namely temperature, pH, turbidity, hardness, chloride (Cl), total dissolved solids (TDS), sulphates (SO42-), nitrates (N-NO3), nitrite (N-NO2), heavy metals (As, Fe, Mn, F, Pb, Cu, Zn, Cd, Hg) and microorganisms (coliform and E. coli). Groundwater quality was compared with national technical regulations on groundwater quality (QCVN 09-MT:2015/BTNMT). Principal component analysis (PCA) and cluster analysis (CA) were used to evaluate the main parameters and to group groundwater quality on similarity. The results showed that groundwater was contaminated by coliform, E. coli, Cl, TDS and Mn2+. The remaining groundwater parameters were still within the allowable limits. PCA results showed pH, turbidity, Cl, TDS, N-NO3, coliform, As, Pb, Cu, Zn, Hg and Mn2+ were the main parameters affecting groundwater quality. PCA suggested that the potential sources of groundwater pollution were human and animal wastes, geohydrological characteristics of the aquifer, quality of the surface water, underground saline intrusion, industrial and agricultural activities. CA results showed that groundwater quality in the study area formed six clusters from 24 monitoring positions due to the difference in the concentrations of Cl-, TDS, Mn2+ and coliform. The results of the present study indicated that groundwater quality was not suitable for human consumption. Proper treatments are needed. Investigating specific sources of groundwater pollution and current management practices to provide sufficient scientific information for better groundwater management are urgently needed.


Cluster analysis, Coliform, Dong Thap, Groundwater, Principal component analysis


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