Surface water is an essential and priceless resource on Earth that provides water for industrial processes, agricultural production, and human life. It is essential to maintaining human existence and advancing society. In this study, we carried out a thorough examination of the hydrochemical properties and governing elements of surface water in the Mahanadi River Basin, Odisha. Nineteen water samples were gathered from 19 zones throughout the river basin for a total of 20 physicochemical parameters. The water quality index (WQI) models, namely the Entropy Water Quality Index (EWQI), and reliability-based MCDM (multiple-criteria decision-making) tool like Weighted Aggregated Sum Product Assessment-Technique for Order Preference by Similarity to Ideal Solution (WAPAS-TOPSIS/W-TOP) were implemented to assess drinking water quality. Multivariate methods such as Principal Component Analysis (PCA) have been widely applied to understand the interactions within and between the water quality parameters. Thus, combining many methods frequently yields a more accurate and reliable assessment of water quality. Based on physicochemical data, 18 water quality indicators were generally below the permissible limits, while most of the sampling sites show values close to WHO standards, indicating better water quality. Significant variability is observed in TKN, coliform, and major cations and anions. The EWQI obtained for all water sampling stations explained that 52.63% and 5.26% of tested locations correspond towards poor/extremely poor water quality, while the remaining 31.58% renders inside the excellent water quality group. The primary sources of the river’s water quality adulteration behind its poor water class may include agricultural runoff, improperly disposed of solid waste from the municipality, and residential water deterioration. Decision-making approaches, such as WAPAS-TOPSIS (W-TOP), were adopted to alleviate contradictions involving the WQI index. The factor weights and field data were considered in order to arrive at the final ranking. According to the suggested methods, SP-(9) was the most polluted location. In this case, pollution levels were more strongly associated with a range of expanding human activities, including industrial activity inside and near the river flow, fertilizer effects, excessive water consumption, and agricultural runoff. However, Site-(8) and (19) corresponds to second and third polluted site. The outcomes were quite evident from the highest EWQI values of 310, 196, and 160 at this location. Considering PCA findings, hydrochemical patterns are elucidated, which illustrate that the cumulative explained variance for the first five PCs reaches 93.77%, with PC-1 contributing 35.88%, PC-2 as 25.23% (eigenvalue 1.59), PC-3 as 16.20%, PC-4 as 9.67%, and PC-5 as 6.79%, respectively. The results indicate that surface water chemistry stems from geogenic processes and anthropogenic sources. Additionally, E. coli and total coliform were among the bacteria that were detected in the majority of the zones. With the projected increase in population density, there is a high likelihood of further contamination of drinking water sources. As a result, delineating the relative contributions of geogenic and human activities to the contamination of drinking water sources was accomplished through the successful use of different models for quantifying contamination. However, both models showed that anthropogenic inputs are the primary cause of the decline in water quality. Therefore, adopting an appropriate water management policy and altering one’s lifestyle are recommended.