Regression and Cluster Analysis of Water Quality Parameters of Mahanadi River at Rajim

DOI

No DOI

Published In

Volume 6, Issue 3 (2025)

Published Online

May-June 2025

Pages

140-143

Article Type

Original Article

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This study presents a comprehensive analysis of the water quality of the Mahanadi River at Rajim, India, using regression and cluster analysis. Over a five-year period, monthly water samples were collected and analyzed for key physicochemical parameters including pH, turbidity, Total Dissolved Solids (TDS), conductivity, dissolved oxygen (DO), Chemical Oxygen Demand (COD), total hardness, alkalinity, calcium, and magnesium. The study employed Pearson correlation, linear regression, and K-means clustering to interpret the complex relationships among these parameters. The results reveal strong positive correlations between turbidity, TDS, and conductivity, and significant seasonal variation in water quality. The regression models identified key predictive relationships, while clustering categorized the data into meaningful seasonal groups. The findings provide actionable insights for environmental monitoring and management.