Abstract
The present study was conceptualized to develop the Enhanced River Pollution Index (ERPI) model. The ERPI model was used to evaluate the river water quality (RWQ) for its beneficial usage, i.e., drinking with (DCD) and without (DD) conventional treatment, outdoor-bathing (OB), wildlife and fisheries (WF), and industrial and irrigation (IIW). The adequacy of multiple linear regression (MLR) and support vector regression (SVR) models was also investigated to predict the ERPI for estimating the RWQ. The accuracy of the MLR and SVR models was tested by using the statistical parameters, i.e., root mean squared error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). The results revealed that the MLR models performed well (RMSE = 0.004 ± 0.0043, R2 = 0.998 ± 0.001, and MAE = 0.002 ± 0.003) for the DD, DCD, and OB. However, the SVR models estimated the RWQ more accurately (RMSE = 0.041 ± 0.001, R2 = 0.962 ± 0.010, and MAE = 0.026 ± 0.002) than the MLR models for WF and IIW. Moreover, this study disclosed that the RWQ was not excellent for DD, OB, and DCD. However, the RWQ was categorized from excellent to poor classes for WF, while it was suitable for IIW.
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The authors acknowledge the Department of Environmental Science & Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India, for providing the support in carrying out the research work.
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Conceptualization: Suyog Gupta; methodology: Suyog Gupta; formal analysis and investigation: Suyog Gupta; writing - original draft preparation: Suyog Gupta; writing - review and editing: Suyog Gupta, Sunil Kumar Gupta; resources: Sunil Kumar Gupta; supervision: Sunil Kumar Gupta.
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Gupta, S., Gupta, S.K. Development and evaluation of an innovative Enhanced River Pollution Index model for holistic monitoring and management of river water quality. Environ Sci Pollut Res 28, 27033–27046 (2021). https://doi.org/10.1007/s11356-021-12501-z
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DOI: https://doi.org/10.1007/s11356-021-12501-z