Assessment of water quality parameters of Khageri Khola (river) in Chitwan, Nepal, from upstream to downstream using physicochemical, correlation, regression, principal component, and hierarchical clustering analyses
In Chitwan, Nepal, the Khageri Khola (river) is an essential water source for domestic use, irrigation, and ecosystem balance; however, comprehensive evaluations of its water quality remain limited. Twelve physicochemical surface water quality parameters were statistically assessed from six sampling sites. The findings were compared with the World Health Organization, Nepal Drinking Water Quality Standards, and Nepal Water Quality Guidelines for Agriculture and Conservation (NWQGAC). Most of the tested parameters were within the recommended limits of the World Health Organization, NWQGAC, and Nepal Drinking Water Quality Standards; however, ammonia (9.53 ± 1.21 mg/L), dissolved oxygen (7.08 ± 0.24 mg/L), and phosphate (7.31 ± 0.82 mg/L) exceeded NWQGAC irrigation limits by 6–7-fold, suggesting a potential risk of eutrophication. The coefficient of variation, mean, standard deviation, minimum, and maximum values were computed. Three potential pollution sources were identified using principal component analysis, including mineral weathering and ionic strength (PC1; 39.41%), agriculture and organic pollution (PC2; 28.49%), and ion-specific anthropogenic inputs (PC3; 17.44%). The dendrogram of hierarchical clustering analyses grouped the sites into Cluster A (Confluence with tributaries, Kalika River; Confluence with Rapti River; and Khageri Bridge, Ratnanagar), suggesting anthropogenic influences, and Cluster B (Confluence with Mani Khola; Confluence with tributaries, Chitrasari; and Khageri Bridge, Khageri River) with enhanced concentrations of nitrate, alkalinity, ammonia, and phosphate, indicating considerable agricultural and organic pollution. Strong linear relationships between various parameters, such as hardness and nitrate (r2 = 0.999) and dissolved oxygen and phosphate (r2 = 0.991), were identified through correlation and regression analyses, suggesting common sources of contamination.

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