ABSTRACT
Water quality indices use biological, chemical, and physical data and information to classify the condition of surface waters, ultimately contributing to their management. We used multicollinearity and principal components analyses to develop the Revised Iranian Water Quality Index (RIWQI) as an indicator of agricultural and urban effects in the Karun River Basin of southwestern Iran. Seasonal sampling and analysis of water quality parameters from 54 sites across 18 rivers of the Karun River Basin include fecal coliform, total dissolved solid, phosphate, biological and chemical oxygen demand, nitrate, dissolved oxygen saturation, turbidity, pH, and water temperature. This study updates the previous version of Iranian Water Quality Index (IWQI) by differentially weighting individual variables, refining the main sub-indices, adding phosphate (PO4-), biological oxygen demand (BOD), chemical oxygen demand (COD), and temperature (T), and improving the aggregation calculation. Sensitivity testing of the RIWQI resulted in a mean value for discrimination efficiency (DE) > 85.6%, the highest of other indices calculated with the same dataset.