Towards overcoming the limitations of conventional water quality indices: Development and implementation of a...

Conventional Water Quality Indices (WQIs) are commonly used to assess anthropogenic impacts on aquatic systems, but they often oversimplify complex parameter interactions, rely on subjective weighting, and inadequately capture spatial or temporal variations. This study hypothesizes that a parameter-based index can enhance diagnostic precision and provide clearer insights into pollutant behavior. The objective was to develop and apply a Parametric WQI that disaggregates water quality into parameter-specific sub-indices for high-resolution monitoring without subjective weighting. Water samples were collected during the peak rainy season from Wupa Sewage Treatment Plant (WSTP), Abuja, Nigeria-covering influent, effluent, the point of discharge (POD), and sites 1-2 km downstream. Thirteen chemical parameters, including nutrients, organic load indicators, and heavy metals, were analyzed. Pollutant levels peaked at the POD but generally declined downstream due to dilution, sedimentation, and microbial degradation. Dissolved Oxygen (DO) increased downstream in June and August but dropped in July (-4.30% at 2 km). TDS rose at the POD in July (+ 16.67%), while TSS fell sharply near the POD (-86.64% in June). Nutrients exhibited strong variability: NH₄⁺ increased (+ 60%), PO₄³⁻ rose sharply (+ 185%), and NO₃⁻ declined (-38.46%), suggesting eutrophication risk. Cu²⁺ spiked (+ 134.17% at POD), whereas Pb²⁺ and Fe²⁺ declined downstream. PWQI classified water quality as poor to very poor at influent, moderate at effluent, and good to excellent downstream. The approach enhances interpretative accuracy, identifies residual contamination (notably NH₄⁺, TSS, and alkalinity), and offers a robust, transferable framework for sustainable wastewater and river system management in tropical environments.