Classification of Groundwater Samples from Two Major Districts of the Malwa Region of Punjab, India Based on their Physicochemical Properties

Groundwater is one of the most valuable natural resources on the planet. Human activities such as urbanization, agriculture, and industry contribute to the contamination of groundwater in developing nations. Due to unchecked human activity, the Malwa region of the state of Punjab is facing significant water contamination issues. Consequently, in this study, the quality of groundwater samples (n = 50) taken from the Ferozepur and Fazilka districts of the Malwa region of Punjab, India was examined. These samples were gathered from various urban, rural, and industrial areas. In order to assess the variation in contamination levels among samples from distinct categories, additional samples were obtained from water boxes (WB), submersible pumps (SS), and hand pumps (HP) within each category (HP). Each sample was analyzed for pH, total dissolved solids (TDS), electrical conductivity (EC), and chloride concentration (CC). The quality criteria of samples collected from water boxes deeper than 100 feet were found to be within the permitted standards established by the World Health Organization (WHO) and the Bureau of Indian Standards (BIS). It was determined that the water samples collected from submersible and hand pumps (at depths of less than 100 feet) were unfit for human consumption. All metrics for the Ferozepur samples (mean values for pH, TDS, EC, and CC: 7.310, 589.84 mg/L, 1290.62 μS/cm, and 303.78 mg/L, respectively) were found to be within the acceptable range. The pH readings of samples exhibit the least variance, with a standard deviation of 0.205, while TDS, EC, and CC indicate significant fluctuation, with standard deviations of 305.08, 951.14, and 221.66 correspondingly. In addition, the chemical data of a sample were subjected to Principal Component Analysis (PCA) in order to clarify. Principal Component Analysis was then used to verify this result (PCA). Using PCA, a similar categorization was also seen. Overall, all parameters differ. All parameters have been analyzed for correlation and regression using data with granularity. PCA was utilized to classify samples according to districts (Ferozepur and Fazilka), regions (urban, rural, and industrial), and groundwater sources (hand pump, submersible, and water box).