Correlation-regression model for physico-chemical quality of groundwater in the South Indian city of Gulbarga

Abstract

Groundwater is a major source of municipal and private water supply in Gulbarga city. Water samples were collected from spatially referenced bore wells located in various wards of the city. 150 bore well water samples were analyzed for electrical conductivity (EC), pH, total dissolved solids (TDS), total hardness (TH), Ca2+, Mg2+, Na+, K+, HCO3-, CO32- Cl¡¥, SO42- ,NO3¡¥, F and Fe. All tests were performed as per standard methods and water quality was compared for both Indian and WHO drinking water standards. Significantly positive correlation at 1 and 5% was found between many parameters. EC prediction with multiple R2 value of 0.999 indicated that 99.9% variability in observed EC could be ascribed to Cl¡¥ (76%), HCO3¡¥ (12.5%), NO3- (10.3%) and SO42- (1.1%). Multiple regression models can predict EC at 5% level of significance. Nitrate, chlorides, TDS and fluoride concentration exceed permissible level of drinking water in 75, 41, 95 and 3.33% of the samples respectively. It is recommended to treat groundwater prior to domestic use.

Key words: Groundwater, water quality, bore well, water supply, correlation, regression.