Characterization of groundwater potability and irrigation potential in Uttar Pradesh, India using water quality index and multivariate statistics

• Published in: Journal of hydroinformatics Vol. 26; no. 5; pp. 1100 - 1121
• Main Authors: Chaudhary, Supriya, Singh, Gurudatta, Gupta, Deepak, Singh Maunas, Suruchi, Mishra, Virendra Kumar
• Format: Journal Article
• Language: English
• Published: London IWA Publishing 01.05.2024
• Subjects: Anthropogenic factors; Calcium ions; Cluster analysis; Correlation analysis; Drinking water; Electrical conductivity; Electrical resistivity; Environmental monitoring; Fluorides; Groundwater; Groundwater data; Groundwater irrigation; Groundwater quality; Hydrologic cycle; Irrigation; Magnesium; Multivariate analysis; multivariate statistics; Pollution control; Statistical analysis; Statistical methods; suitability of drinking and irrigation; Sustainable development; Water analysis; Water hardness; Water quality; water quality index; Water sampling; Himalaya Mountains; Uttar Pradesh India; India
• ISSN: 1464-7141; 1465-1734
• DOI: 10.2166/hydro.2024.291

This study includes groundwater quality data from 290 monitoring sites from 69 districts of Uttar Pradesh, India. The analysis of the data showed that 98.97, 24.48, 52.07, and 68.97% of groundwater samples had concentrations of electrical conductivity (EC), total hardness (TH), Mg2+, and HCO3−, respectively, higher than the maximum permissible limit. Groundwater quality index (GWQI) was calculated for these 290 monitoring sites which revealed that 21 sites (7.24%) had inappropriate GWQI for drinking water, and 18 sites (6.21%) had an unsuitable index for irrigation. Most of the sampling sites (98.97%) showed high EC contents in groundwater with a mean value of 999.33 μS/cm. Fluoride content was found within the permissible limits in 95.52% of the samples, while 4.48% had high concentrations. The use of hierarchical cluster analysis differentiated all the sites into two clusters: one with high pollution and the other with low pollution. Significant correlations exist between physicochemical and irrigation indicators in the correlation matrix. High loadings of EC, TH, Ca2+, Mg2+, Na+, Cl−, and SO42− were identified in the first principal component, which are thought to be pollution-controlled processes from anthropogenic sources. According to the Chadha diagram, CaHCO3 and Ca–Mg–HCl were the two most prevalent chemicals in the water.