Abstract:
In this study, a comprehensive multiplicative water quality index, -WQI, for surface water quality assessment has been developed that uses sub-index functions based on deviation from maximum contaminant level of respective parameters. The parametric weights in -WQI were computed using entropy based approach to eliminate subjectivity. Using a synthetic dataset the performance of -WQI has been compared with Composite WQI (CWQI) that is based on Saaty’s analytical hierarchical process. The results indicated that in comparison to CWQI, -WQI approach provides an objective and rational framework that eliminates clustering effect in providing the water quality status. Further, -WQI has been applied to an exhaustive water quality dataset of river Ganga, one of the major perennial rivers of India. Out of 224 sampling locations, 167 sites have been associated with excellent or good water quality class whereas 57 sites are identified with either fair, poor, or heavily-polluted water quality class. Furthermore, the water quality classes correlated well with the type of anthropogenic activities carried out at the site.
