The objective of the present study was to evaluate the geochemical processes controlling the groundwater chemistry and also to assess the groundwater quality suitability criteria for irrigation purposes. An agricultural region of Telangana, South India, was selected for the present study. A total of 100 groundwater samples were collected and estimated for pH, electrical conductivity (EC), total dissolved solids (TDS), calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), potassium (K⁺), bicarbonate ( $${\text{HCO}}_{3}^{ - }$$HCO 3 - ), chloride (Cl⁻), sulfate ( $${\text{SO}}_{4}^{2 - }$$SO 4 2 - ), nitrate ( $${\text{NO}}_{3}^{ - }$$NO 3 - ), and fluoride (F⁻). The groundwater was characterized by mostly alkaline conditions with a dominance of Na⁺ and $${\text{HCO}}_{3}^{ - }$$HCO 3 - ions, indicating the prevailing conditions of weathering and dissolution of silicate minerals. The various geochemical signatures such as Na⁺ vs Cl⁻, Ca²⁺ + Mg²⁺ vs $${\text{HCO}}_{3}^{ - }$$HCO 3 - , Ca²⁺ + Mg²⁺ vs $${\text{HCO}}_{3}^{ - }$$HCO 3 - + $${\text{SO}}_{4}^{2 - }$$SO 4 2 - , $${\text{HCO}}_{3}^{ - }$$HCO 3 - vs Cl⁻ + $${\text{SO}}_{4}^{2 - }$$SO 4 2 - , Ca²⁺ + Mg²⁺ vs total cations, and Ca²⁺ + Mg²⁺ vs Na⁺ + K⁺ and the saturation indices with respect to calcite, halite, and gypsum suggest obviously the dominant conditions of carbonate weathering associated with the reverse ion exchange and evaporation processes as the geogenic factors. The linear trend of TDS vs $${\text{NO}}_{3}^{ - }$$NO 3 - + Cl⁻/ $${\text{HCO}}_{3}^{ - }$$HCO 3 - clearly specifies the influence of non-geogenic sources on the aquifer system. These are the important contributors to the variation in the groundwater chemistry. However, the impact of the geogenic source is masking the influence of the anthropogenic source in some areas of the present study region. According to the salinity vs sodium adsorption ratio, residual sodium carbonate, magnesium ratio, and Kelly ratio, 99.9%, 7.06%, 63.07%, and 51.27% of the total study region come under the unsuitable categories for irrigation purposes, respectively. Therefore, the findings of this study recommended some site-specific appropriate management strategies for the safe supply of groundwater for proper crop growth and consequently for sustainable development of the rural environment.

The Pandameru River Basin, South India, is affected by high levels of contamination from human activities and the over-exploitation of groundwater for agriculture, both of which pose significant threats to water quality and its availability for drinking and irrigation. To explore sustainable groundwater management, this study presents a machine learning-driven approach to basin-scale groundwater potential zone (GWPZ) mapping by integrating remote sensing (RS), a geographic information system (GIS), and the random forest (RF) algorithm. The research leverages ten thematic layers—including lithology, geomorphology, soil type, lineament density, slope, drainage density, land use/land cover (LULC), NDVI, SAVI, and rainfall—to assess groundwater availability. The RF model, trained with well-distributed groundwater data, provides an optimized classification of GWPZs into five categories: very good (5.84%), good (15.21%), moderate (27.25%), poor (27.22%), and very poor (24.47%). The results indicate that excellent groundwater zones are predominantly located along highly permeable alluvial deposits, whereas low-potential zones coincide with impermeable geological formations and steep terrains. Field validation using piezometric readings and well data confirmed significant variations in water table depths, ranging from 5 m to over 150 m. The groundwater potential map achieved an accuracy of 86%, underscoring the effectiveness of the RF model in predicting groundwater availability. This high-precision mapping technique enhances decision-making for sustainable groundwater management, supporting long-term water conservation, equitable resource allocation, and climate-resilient water strategies. By providing reliable insights into groundwater distribution, this study contributes to the sustainable utilization of groundwater resources in semiarid regions, aiding policymakers and planners in mitigating water scarcity challenges and ensuring water security for future generations.