Groundwater quality evaluation using water quality index and geospatial techniques in semi-arid regions of Telangana, India

Introduction Groundwater is the principal source of drinking and irrigation water in semi-arid hard-rock regions, where natural hydrogeochemical processes and anthropogenic activities strongly influence water quality. However, comprehensive studies integrating hydrochemical characterization, multivariate statistical analysis, geochemical modelling, irrigation suitability assessment, and geospatial analysis remain limited for the crystalline aquifers of southern India. Methods This study presents an integrated framework to evaluate groundwater quality, hydrogeochemical evolution, and irrigation suitability in Warangal District, Telangana, India. A total of 58 groundwater samples collected during the pre-monsoon season were analyzed for physicochemical parameters. Groundwater quality was assessed using the Water Quality Index (WQI), irrigation water quality indices, Piper and Gibbs diagrams, ionic ratio analysis, PHREEQC saturation index modelling, GIS-based spatial interpolation, and multivariate statistical techniques, including Pearson correlation, Principal Component Analysis (PCA), Factor Analysis (FA), and Hierarchical Cluster Analysis (HCA). Results Groundwater exhibited hydrochemical variability, with pH ranging from 6.52 to 8.95, electrical conductivity from 0.26 to 3.29 dS m -1 , and total dissolved solids from 166.4 to 2105.6 mg L -1 . The dominant Na–HCO 3 hydrochemical facies indicates that groundwater evolution is mainly controlled by rock–water interaction, silicate weathering, and ion exchange. WQI indicated that most groundwater samples were poor to unsuitable for drinking, whereas the majority remained suitable for irrigation despite localized salinity and sodium hazards. Combined PCA, FA, HCA, ionic ratio analysis, and PHREEQC modelling identified mineral weathering, ion exchange, and localized agricultural activities as the principal controls on groundwater evolution. Discussion and Conclusion The novelty of this study lies in integrating hydrochemical, geospatial, statistical, and geochemical modelling into a unified framework that identifies groundwater quality hotspots, distinguishes geogenic and anthropogenic influences, and provides a scientific basis for groundwater monitoring, irrigation management, and sustainable water-resource planning in semi-arid hard-rock aquifers.