Performance evaluation of soil quality indices in agricultural landscapes

Soil contamination from polluted irrigation water poses a major threat to agricultural productivity in the Kali River (East) basin of Aligarh, Uttar Pradesh, where long-term discharge of untreated municipal and industrial waste has degraded river water quality and affected nearby farmlands. This study evaluates salt-affected soil quality in agricultural fields irrigated with river water and develops robust Soil Quality Indices (SQIs) to support sustainable soil management and river restoration. Seventy soil samples were analyzed for 19 saline–sodic parameters, major anions, major cations, and heavy metals indicators, and Principal Component Analysis (PCA) identified a Minimum Dataset of seven key parameters (pH, SAR, HCO 3 , SO 4 , TH, Mn, Ni). A new Standard Weight Scoring (SWS) approach was introduced for more reliable indicator weighting. Using this MDS, twelve SQIs were constructed under additive and weighted additive frameworks viz. Simple Additive (SQI A ) indices based on two linear (S1, S2) and one nonlinear (S3) scoring functions, and Weighted Additive (SQI WA ) indices integrating the scoring methods with three weighting approaches, AHP, PCA-derived weights, and the proposed SWS approach. Among them, SWS-driven indices, SQI-6 and SQI-12, showed the highest sensitivity and variability, outperforming traditional weighting methods and effectively capturing subtle seasonal and spatial shifts in salt-affected soil quality. GIS mapping revealed significant spatial heterogeneity, reflecting the cumulative impact of long-term polluted irrigation. The study demonstrates that SWS-based SQIs offer a more robust tool for chemically soil health assessment and provide actionable insights for soil fertility improvement, land-use planning, and ongoing river restoration initiatives.