This study was carried out to understand how land use patterns influence surface water quality in Tien Giang Province using remote sensing and statistical approaches. Surface water quality data were collected at 34 locations with the frequency of four times (March, June, September, and November) in 2019. Water quality parameters were used in the analysis, including pH, temperature, electrical conductivity (EC), total suspended solids (TSS), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), ammonium (N-NH4+), nitrite (N-NO2−), nitrate (N-NO3−), sulfate (SO42−), orthophosphate (P-PO43−), chloride (Cl−), total nitrogen (TN), total phosphorus (TP), and coliform. The relationship between land use patterns and water quality was analyzed using geographic information techniques (GIS), remote sensing (RS), statistical approaches (cluster analysis (CA), principal component analysis (PCA), and Krustal–Wallis), and weighted entropy. The results showed water quality was impaired by total suspended solids, nutrients (N-NH4+, N-NO2−, P-PO43−), organic matters (BOD, COD), and ions (Cl− and SO42−). Kruskal–Wallis analysis results showed that all water quality parameters in the water bodies in Tien Giang Province were seasonally fluctuated, except for BOD and TN. The highest levels of water pollutants were found mostly in the dry season (March and June). The majority of the land in the study area was used for rice cultivation (40.64%) and residential (27.51%). Water quality in the study area was classified into nine groups corresponding to five combined land use patterns comprising residential–aquaculture, residential–rice cultivation, residential–perennials, residential–rice–perennial, and residential–rice–perennial crops–aquacultural. The concentrations of the water pollutants (TSS, DO, BOD, COD, N-NH4+, N-NO2−, Cl−, and coliform) in the locations with aquaculture land use patterns (Clusters 1 and 2) were significantly larger than those of the remaining land use patterns. PCA analysis presented that most of the current water quality monitoring parameters had a great impact on water quality in the water bodies. The entropy weight showed that TSS, N-NO2−, and coliform are the most important water quality parameters due to residential–aquaculture and residential–rice cultivation; EC, DO, N-NH4+, N-NO2−, Cl−, and coliform were the significant variables for the land use type of residential–perennial crops; N-NO2−, P-PO43−, and coliform for the land use pattern of residential–rice cultivation–perennial crops) and N-NH4+, N-NO2−, Cl−, and coliform for the land use pattern of residential–rice cultivation–perennial crops–aquaculture. The current findings showed that that surface water quality has been influenced by the complex land use patterns in which residential and rice cultivation may have major roles in causing water impairment. The results of the water quality assessment and the variation in water properties of the land use patterns found in this study provide scientific evidence for future water quality management.

In this study, spatiotemporal fluctuations in surface water quality in Vinh Long province, Vietnam, were conducted using entropy weighting, water quality index (WQI), and multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA), and discriminant analysis (DA). The samples collected at 63 monitoring locations in March, June, and September were measured for 15 parameters. Compared to the Vietnamese standard, surface water was contaminated with organic matters, nutrients, microorganisms, and salinity. DA identified the most typical parameters (pH, turbidity, TSS, EC, DO, Cl−, E. coli, coliform) in distinguishing temporal variations in water quality with greater than 75% of the correction. CA group 63 sampling sites into 22 clusters representing different land use patterns. WQI determined the worst water quality was found in the agricultural areas. Based on the results of entropy weighting, EC, coliform, N-NH4+, BOD, N-NO3−, and Fe had significantly controlled surface water quality. Four principal components obtained from PCA explained 66.45% of the variance, suggesting the influences of geohydrological factors and anthropogenic activities, such as domestic, market area, agriculture, and industry. The findings of this study can provide useful information for authorities to evaluate the effectiveness of monitoring systems and plan for water quality management strategies.

This study aimed to evaluate the suitability of groundwater for drinking purposes and assess the associated human health risks for different age groups in a coastal province of Mekong Delta, Vietnam. Twenty groundwater samples were collected in Soc Trang Province, and various water quality parameters were analyzed. The data were employed to calculate entropy-weighted groundwater quality index (EWQI), principal component analysis (PCA), cluster analysis (CA), and non-carcinogenic and carcinogenic risks for adult and children health. The results revealed that groundwater in some locations, especially in GW19, was polluted by hardness, total dissolved solids, NH4+, Cl-, Fe, total coliform, and E. coli. In addition, 5 principal components from the PCA results could explain 84.5% of the total variation of groundwater quality, which also suggested that the potential groundwater pollution sources were geochemical processes, agricultural activities, domestic and industrial wastewater, seawater intrusion, and excessive nitrogen fertilizer application. The CA results showed that monitoring locations can be divided into 4 clusters based on their similarities in groundwater quality, and the most polluted group was found at cluster IV (GW19). The computed EWQI values ranged from 20.05 to 738.52, with approximately 45% of total samples classifying good to excellent water quality. The sampling points with undrinkable quality are mainly located in the northeast and center of the province. The ratio of children and adults under the threat of adverse health effects due to drinking groundwater contained non-carcinogenic substances (NH4+, NO2-, NO3-, Cd, Cu, F-, Mn, and As) ranged from 5 to 40%, and children had higher risks compared to adults. Additionally, the consumption of As-contaminated groundwater also poses carcinogenic risks for children, female and male adults ranging from 4.80×10-6 to 1.33×10-4. The findings of this study can provide helpful information for policymakers in the development of long-term water management strategies to protect community health.

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The study was conducted in March 2019 in three areas subject to impacts of agricultural production, residential areas and landfill in An Giang (Area 1), Kien Giang (Area 2) and Can Tho (Area 3), respectively, to assess relationship between water quality and diversity of phytoplankton. The results showed that water quality at 25 study sites is contaminated with organic matters, suspended solids and coliforms. The study found 422 species of phytoplankton belonging to five phyla of Bacillariophyta, Chlorophyta, Dinophyta, Cyanophyta and Euglenophyta. The density of phytoplankton in the three studied areas ranged from 13 to 77,328 individuals L-1. Among the areas, Area 1 has the highest species composition and density, followed by Area 2 and then Area 3. Among the phytoplankton species occurrence, Melosira granualata, Cyclotella meneghiniana, Cyclotella comta, Trachelomonas sp., Glenodinium beronense, Oscillatoria muticola and Skeletonema costatum dominated and indicated the water environment with high organic matters, nutrient-rich and salty condition. Water quality index (WQI=57-88) indicated water quality ranged from good to medium whereas Shannon-Weiner diversity index (H’=0.71-3.89) showed water quality from medium to heavy pollution. Approximate 56% of the studied sites have similarities in water quality evaluated medium pollution using WQI and H’ although the canonical correspondence analysis (CCA) results indicated that the distribution and abundance of phytoplankton was positively correlated with N-NH4+, P-PO43-, BOD and TSS. It was suggested that H’ is a good water quality indicator for uncontaminated freshwater, but not for saline water or highly complicated contaminating water. The findings revealed that H’ only partially indicates water quality, thus examining physicochemical water quality variables for water quality monitoring is essential.