ASSESSMENT OF PHYSICOCHEMICAL WATER QUALITY PARAMETERS ASSOCIATED WITH DRINKING WATER POTABILITY
DOI:
https://doi.org/10.69980/5y2x9v67Keywords:
Drinking water quality, Water potability, Physicochemical parameters, logistic regression model, Water quality assessmentAbstract
Safe drinking water is essential for public health, yet deterioration in physicochemical water quality continues to pose significant environmental and health challenges. Identifying key physicochemical predictors of water potability is important for improving water quality monitoring and management. This quantitative secondary data analysis utilized the publicly available Water Potability dataset from the Kaggle repository, comprising 1,000 water samples. Nine physicochemical parameters, including pH, hardness, solids, chloramines, sulfate, conductivity, organic carbon, trihalomethanes, and turbidity, were analyzed. Descriptive statistics, independent sample t-tests, correlation, variance inflation factor analysis, regression, and model performance evaluation were performed. Statistical significance was established at p < 0.05. Most physicochemical parameters showed comparable distributions among potable and non-potable water samples. Trihalomethanes emerged as the only significant independent predictor of water potability in the multivariable logistic regression model. Correlation and multicollinearity analyses indicated weak associations among predictor variables and the absence of substantial multicollinearity. The logistic regression model demonstrated moderate predictive performance, achieving an accuracy of 60.5%, specificity of 69.3%, sensitivity of 46.5%, and an area under the receiver operating characteristic curve of 0.582. Physicochemical assessment combined with multivariable logistic regression provides an interpretable approach for identifying important predictors of drinking water potability. Monitoring trihalomethanes alongside routine water quality parameters may strengthen drinking water surveillance and support evidence-based environmental management.
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