Geospatial assessment of groundwater quality in the Noyyal basin, Tamil Nadu, India using GIS and geostatistics

Water is crucial in agriculture, domestic use and industrial development. In recent years, the demand for groundwater has significantly risen due to industrialization, urbanization, population growth and increased agricultural activities. This study focuses on the groundwater quality spatial distribution and utilizes geostatistical analysis to predict groundwater chemical parameters within the Noyyal sub-basin, employing Geographic Information System (GIS) technology. Data transformation methods were applied to reduce skewness in several chemical parameters to improve the precision of the spatial representation of groundwater chemistry. Comparing the calculated concentrations to the established permissible limits showed that calcium, bicarbonate and sodium absorption ratio concentrations were within acceptable levels. In contrast, parameters such as magnesium, sodium, potassium, chlorine, sulfate, fluoride, pH, total hardness, electrical conductivity and total dissolved solids exceeded the permissible thresholds. The study also identified the most appropriate semi-variogram model for each water quality parameter based on the Root Mean Square Error (RMSE). The Exponential model with log-transformed data was the best fit for Ca, Na, K, HCO3, pH, HAR and EC, providing physically meaningful results. For TDS, Mg, SO4, F and SAR, the Spherical model with log-transformed data yielded the most reliable RMSE values. The Gaussian model produced satisfactory results for Cl and Na %.