Multidimensional assessment of riverine water quality through statistical tools and pollution indices in Birbhum...

Rivers are encountering numerous challenges from increasing anthropogenic threats globally. This study aimed to examine how the water quality differs spatio-temporally across the rivers of Birbhum district, West Bengal, India and identify primary contributing factors to the differences. Field surveys were conducted across three seasons in fifteen sites of five major rivers of the district. Several physico-chemical parameters were measured to assess water quality and pollution status by employing the Weighted Arithmetic Water Quality Index (WAWQI) and the Comprehensive Pollution Index (CPI). Both descriptive and inferential statistics were utilised for data interpretation. The linear correlation among fifteen parameters was determined using the Pearson correlation analysis. Further two-way hierarchical cluster analysis (HCA) grouped the sampling sites and parameters based on their similarity. Principal component analysis (PCA) revealed the highest contributing parameters. The MANOVA was conducted to identify the effect of independent variables such as locations and season on the dependent physico-chemical variables. Locations near urban areas and tourist spots exhibited higher WAWQI and CPI values in "very poor" category. Most deteriorated water quality was found in the Ajoy river with the highest WQI [104.36 ± 22.04] and CPI [1.70 ± 0.19]. Furthermore, Inverse Distance Weighting (IDW) method was employed for visualising the spatial and temporal variations of the water quality and pollution level. The findings showed the sites affected by agricultural runoff, sewage disposal, and mining activities have increased solids and nutrient concentration. Overall, these outcomes may provide essential baseline data and recommendations for reducing water pollution and will contribute to several policy making and resource management.