Hydrogeochemical evaluation of groundwater in Deccan Volcanic Province, Maharashtra, India through GIS and statistical techniques.

In the present work statistical techniques and GIS approach has been used to understand the hydrogeochemical evaluation of groundwater and its influencing factors in the region of Deccan Volcanic Province (DVP), Maharashtra, India. A network of 60 groundwater sampling stations was identified by considering geology, geomorphology, land use pattern etc. The groundwater samples were collected subsequently for pre-monsoon (PRM) and post-monsoon (POM) seasons of the year 2022. Hydrochemical analysis include pH, EC, TDS, cations (Ca, Mg, Na, K), anions (CO, HCO, NO, SO, Cl, F) were performed by following standard analytical protocols of American Public Health Association (APHA). As per the Bureau of Indian Standards (BIS) for drinking, the parameters like pH, TH, NO, F and K are surpassed the threshold limits in both the seasons. Also recognize the geological formations with different lithologies from the study region to identify the geogenic causes of contamination. Box plots are prepared for better illustration of average, median, minimum and maximum values for various water ions. Pollution Index of Groundwater (PIG) tool is used to classify the water quality for beneficial use and results depicted that only 1.67% sample from POM season indicates very high pollution. Spatial distribution maps of PIG are prepared in GIS platform to demarcate the different zones of groundwater pollution and observed that south-westerly part having more groundwater pollution than other regions. Statistical techniques like Correlation Matrix (CM), Principal Component Analysis (PCA) and Cluster Analysis (CA) used to know the degree of association among hydrogeochemical data and their collective influence on groundwater quality. Piper trilinear plot has been used to categorize the dominant water facies and types of water in the study region, and results shows that 100% samples having calcium-magnesium and bicarbonate-carbonate types. Bivariate plots for major ions were prepared to signify the natural and anthropogenic factors which alter groundwater quality. Gibb's diagram suggested that 98.34% samples influenced by mechanism of rock domain and only 1.66% sample shows evaporation dominance. Wilcox plot suggested that majority of the groundwater samples are fall in good to moderate categories for agriculture use; while, 95% and 75% samples in excellent to good zone and 5% and 23.34% samples show good to permissible zones in PRM and POM seasons respectively.