Water pollution and water quality assessment and application of criterion impact loss (CILOS), geographical information system (GIS), artificial neural network (ANN) and decision-learning technique in river water quality management: An experiment on the Mahanadi catchment, Odisha, India
River water quality has grown in importance since river water needs to be treated to ensure safe, sustainable use because it is being contaminated by a variety of human activities. Methods like Water Quality Index (WQI) and Geographical Information System (GIS) are both blended together, thereby com...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Desalination and Water Treatment |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1944398624204793 |
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| Summary: | River water quality has grown in importance since river water needs to be treated to ensure safe, sustainable use because it is being contaminated by a variety of human activities. Methods like Water Quality Index (WQI) and Geographical Information System (GIS) are both blended together, thereby combine several sources of information on water quality into a comprehensible format that offers a means of succinctly summarising the overall state of the water quality in a form that policymakers can understand. In this context, nineteen examined locations were gathered and investigated during 3-year interval (2020–2023), to test 20 physicochemical parameters in the Mahanadi River Basin (MRB), Odisha. This study has brought attention to a drinking water quality assessment of surface water, by integrated use of CILOS (Criterion Impact Loss) based WQI (CILOS-WQI), with association by reliability based MCDMs (Multiple-criteria decision making) techniques namely: Evaluation based on Distance from Average Solution (EDAS) and Machine Learning (ML) based-Artificial Neural Network (ANN) technique. Inverted Distance Weighted (IDW) based spatial interpolation technique, was employed to create a map of the area's potential for pollution. The research also determines the important contaminants that are influencing the river's water quality as it passes through the city. Further, the CILOS-WQI revealed that 31.58 % i.e., sites SP-(2), (8), (10), (11), (13), and (19) and 5.26 % (site SP-9) of evaluated sites are kept under poor/very poor water quality, while, rest 47.37 % of tested locations fall within the purview of excellent water. It turned out that the primary sources of the river's water quality adulteration were agricultural runoff and illegally deposited municipal solid waste, which may have contributed to the decline of domestic water. However, parameters such as TC, TKN, EC, TDS, and Cl- were emerged as essential elements for water quality degradation. Based on the results, the strongest association between the best qualities and the WQI was shown by the ANN, which proved to be the most accurate prediction model. The 13 characteristics found in the model were quite significant and demonstrated good performance in predicting the WQI with a respectable level of accuracy. The R2 value for the process like training, cross-validation, and test data, was recorded as 0.96. In consequence, MCDM models utilizing the WQI index, such EDAS, were implemented to resolve discrepancies. The factor weights and field data were taken into account while calculating the final ranking. Comparing the suggested methods to other regions, SP-(9) may have been the most polluted area, followed by SP-(8) and SP-(19) respectively. This was validated by the findings of CILOS-WQI values. Additionally, it also came with high concentrations of relevant parameters, which includes SAR, Cl-, SO42-, coliform, TKN, EC, and TH. The water quality indicators are found exceeding the desired threshold and were signified as polluting agents for water quality degradation. However, it was relevant that the pollution levels at these stations were more closely linked to numerous human-caused activities that were occurring within and outside the river course, such as excessive water consumption, fertilizer effects, irrigation return flow, and industrial use activity. From these two models, according to the study's findings, the main source of pollution in the river is organic debris from homes. Hence, the present study's general picture of the WQ showed that the majority of the research area, together with twelve localities that are included under excellent, good, and medium water category. In this context, the immediate steps to restore and improve the water quality are to control the downstream in compliance with regional spatial planning requirements, followed by a conservation movement, and to alter people's behaviour to be more considerate of environmental management for catchment areas. Therefore, it is advised that river water be utilized for household purposes, and with the application of disinfection can be used for drinking. |
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| ISSN: | 1944-3986 |