Identification of Surface Water Contamination Zones and its Sources on Mahanadi River, Odisha Using Entropy-Based WQI and MCDM Techniques

Abstract

Information entropy, geographic information systems (GIS), and an examination of the use of TOPSIS and ELECTRE as multi-objective decision-making tools, this study demonstrates an integrated approach to investigating surface water quality for drinking purposes and applying it to the Mahanadi River in Odisha. 19 distinct locations and 20 physicochemical factors were examined for this aim over a 7-year period (2016-2023). EWQI's classification depicts 84.21% of the samples belongs to good category, 10.53% falls under the poor group, and eventually, 5.26% belongs to extremely poor class. To classify different levels of pollution, multivariate statistical analysis framework namely, Principal Component Analysis (PCA), Cluster Analysis (CA) and Discriminant Analysis (DA) were implemented in the on-going work. In case of CA, the results suggests that by separating the locations into three major groupings, such as relatively more polluting, medium-polluted, and less polluted locations, it depicts site similarity. Also, DA analysis highlights the linkages between the stations. PC could provide a good explanation for 93.92 % total fluctuation in the water quality. In addition, this study clearly justifies the effectiveness of all finding’s outcomes discussed above by the application of TOPSIS and ELECTRE in prioritizing decisions, based on their comparative levels of pollution. Spatial variation maps of all water quality parameters and all methods illustrated above specify that St. (8), (9) and (19) have poor water quality. Leaching, organic, and natural pollutants, industrial and home waste water, soil erosion and weathering, have all been identified as major contributors to river water pollution.