Abstract
The provision of safe, high-quality drinking water is becoming increasingly important due to the growing anthropogenic pressure on water resources, the deterioration of environmental conditions, and stricter requirements for the sanitary and hygienic characteristics of water. Drinking water quality is one of the key factors determining public health, ecosystem stability, and regional environmental safety. Therefore, a comprehensive investigation of natural and drinking water is of considerable scientific and practical significance. The aim of this study was to conduct a comprehensive assessment of groundwater quality based on physicochemical and radiological parameters using modern statistical methods. The parameters evaluated included total mineralization, acidity (pH), total hardness, and the concentrations of calcium, magnesium, iron, manganese, copper, and other components. Experimental data were processed using descriptive statistics, Pearson’s correlation analysis, Student’s t-test, one-way analysis of variance (ANOVA), and multiple regression analysis. In addition, mathematical modelling was performed to determine the dependence of the integral water quality indicator on the chemical composition and mineralization level of groundwater. The results revealed statistically significant relationships among total mineralization, water hardness, and the concentrations of major ions. Total dissolved solids (TDS), as well as calcium and magnesium concentrations, were found to have the greatest influence on the integral water quality assessment. The developed regression model enables the evaluation and prediction of changes in groundwater quality depending on its chemical composition. The radiological parameters of the analysed samples were within the established regulatory limits. The findings may be applied to drinking water quality monitoring, environmental control, the improvement of water treatment technologies, and the assessment of natural and anthropogenic impacts. The practical significance of the study lies in the potential application of the developed model to support evidence-based management decisions in regional water supply and water resource management.