Groundwater Quality Assessment of a Crystalline Terrain at Semi-arid Region in Southern Parts of India

Groundwater quality assessment has been carried out at Jagalur Taluk in Karnataka State, India. This semi-arid region is considered as a drought-prone area. Water quality analysis was carried out during post-monsoon (October 2018) and pre-monsoon (April 2019) seasons at 30 locations. The analyses include spatial auto-correlation, Spearman rank correlation, factor analysis, graphical representations, computation of Groundwater Quality Index, and spatial mapping. Spatial auto-correlation was carried out to examine the spatial distribution of sample locations. The Moran’s index showed the value from − 0.351686 to − 0.06034, and from − 0.046327 to 0.091605 during post-monsoon and pre-monsoon, respectively. Spearman rank correlation coefficient was used to examine the measurement and associations between the variables chosen for the groundwater quality assessment. Significant correlations were noticed at 0.01 level (2-tailed) and 0.05 level (2-tailed) during both post- and pre-monsoon seasons. Factor analysis was employed to extract the interrelation between the water quality parameters. The principal component analysis resulted in the generation of 5 and 4 components for the post-monsoon and pre-monsoon seasons, respectively. The results revealed that the quality of water was affected by agricultural practices, excessive withdrawal of groundwater, and other natural conditions. Piper diagram was used to identify the dissolved constituents in water. It was found that the quality of groundwater of study area was highly dominated by calcium bicarbonate and slightly by calcium sulfate types of water. The controlling mechanism in the groundwater chemistry was identified through Gibb’s plot, and the result depicted the rock dominance in determining the quality of groundwater during post-monsoon season compared to that of pre-monsoon season. Groundwater Quality Index (GQI) was used to understand the suitability of water quality. Spatial variability of groundwater quality was carried in GIS (Geographic Information System).