A Novel Approach Combining Entropy-Water Quality Index (WQI) and Multi-Criteria Decision-Making (MCDM) Analysis for Monitoring Water Quality in Mahanadi River Basin, Odisha

The severeness of pollution from non-point sources (NPS) was highlighted by the high amount of organic matter in the watersheds' downstream areas. The evaluation of the significant physical and chemical variables of 19 samples of surface water quality from the Mahanadi River Basin (MRB), Odisha and it demonstrated that, apart from TKN and TC, the majority of the parameter levels are below the WHO's recommended upper drinking limits. The dataset was submitted to a widely recognised coherence technique using the entropy water quality index (e-WQI) and Multi-Criteria Decision-Making analysis, entitled Additive Ratio Assessment (ARAS), to identify the spatial-temporal variation and its pollution source identification and apportionment. It is observed that samples mostly contained the anions Cl- greater than SO42-greater than NO3-greater than F-, while the primary cations were Fe2+ greater thanB+. For each of the sampling sites, e-WQI was calculated to be 14.55-1065.20, respectively. According to the e-WQI, most of the test locations were in the excellent to extremely poor zone. The results revealed that 84.21% samples excellent for drinking, 10.53% poor and 5.26% extremely poor and thus, unsuitable for consumption. Additionally, the main causes of the poor water quality at sites CS-8, 9 and 19 are industrial and agricultural inputs. However, a mathematical method called ARAS has been adopted to find a better alternative in estimating the level of ranking of pollution. It is adaptable, unbiased, simple to compute, and time-saving, and it will offer valuable details to prioritise and sustain the water quality of potable sources and lessen the effects of using lowquality surface water resources on human health. Moreover, the results showed that the score and its rank at CS-9, signified as mostly polluted site, in comparison to other locations. Longterm wastewater use, human actions, excessive surface water extraction, and modifications to land use patterns could all be contributing factors. The detection of elemental correlations is ultimately permitted by both e-WQI and ARAS, and their possible source was anthropogenic rather than natural. These results are crucial for comprehending the sustainability of surface water for drinking in the research area