Applying the water quality indices, geographical information system, and advanced decision-making techniques to assess the suitability of surface water for drinking purposes in Brahmani River Basin (BRB), Odisha.

Surface water is used for a variety of purposes, including agriculture, drinking water, and other services. Therefore, its quality is crucial for irrigation, human welfare, and health. Thus, the main objective is to improve surface water quality assessment and geochemical analysis to evaluate anthropogenic activities' impact on surface water quality in the Brahmani Watershed, Odisha. In the present paper, emerging techniques such as CRITIC (Criteria Importance Through Inter-criteria Correlation), Additive Ratio Assessment (ARAS), Weighted Aggregated Sum-Product Assessment (WASPAS), SHAP (Shapley Additive Explanation), and Geographical Information System (GIS) were used to locate the origins of pollution in the surface water. The 5-year (2018-2023) database was created by analysing samples that varied geographically over seven sampling locations. The dataset was categorized according to its intended usage. The study employed Inverse Distance Weighting (IDW) tool, to forecast quantities and their geographical arrangement. The water temperature detected at several locations along the river revealed minor variations. The pH variations indicate that the surface water in the studied area is alkaline. Notably, the water's lowest temperature ever recorded was 25.72 °C, at Q-(1). In addition, sufficient DO concentrations are monitored to ensure optimal water quality. The major parts of the study area were found to be majorly affected with high concentrations of PO, EC, Ca, Mg, and SO. To determine the degree of contamination, a basic standard reference is necessary to interpret the values, which range from the anthropogenic to the natural contribution. The statistical results reveal the dominant decreasing order amongst the cations, such as: Ca  > Mg  > Na  > K and in anions, namely, SO > Cl > NO > F > PO, respectively. It displays seasonal variations in dissolved and specific phase metal fractions that are not statistically significant at any of the seven sites. Proceeding further, the water quality index showed that the four samples fall in the poor water quality class, whereas the rest, 3 samples, were of good water quality. The surface water is contaminated and negatively affected due to percolation of ions from landfill leachate as per the data of C-WQI. Based on ARAS and WASPAS, Q-(1) and Q-(2) were mainly not fit for consumption. Meanwhile, the SHAP-WQI showed an increase in the number of samples (71.43%) with unsuitable quality for drinking. This emphasizes on the importance of weathering, dissolution, terrigenous, leaching, ion exchange, lithological and evaporation as the primary processes. Human influences were the secondary factors. Overall, the findings indicate that the study area's surface water is safe to drink, with the exception of a few locations including, Q-(1), (2), (3), (4), and (7), in the river water. Integrating GIS using WQ methods gives a new knowledge on the spatial variation in surface water characteristics for designated use. When enforcing regulations and carrying out pollution control operations, this will help determine the precise sampling sites or the sections of the river that show significant degradation. Thus, the integrated model provides insightful data on surface watershed management for urban planners and decision-makers. In overall, these findings underscore the importance of coordinated efforts across administrative boundaries within the basin to reduce water governance costs, providing valuable insights for fostering the coordinated development of regional economies and environmental sustainability. As a result, future studies should be conducted in the area to precisely state the quality of water used for drinking and domestic purposes.