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<p>Accelerating growth of the global population, coupled with rapid urbanization, industrial expansion, intensive agriculture, and mining activities, has increasingly deteriorated groundwater quality, posing serious public health risks. Addressing this challenge requires water quality assessment frameworks that are both scientifically rigorous and explicitly sensitive to health risks. This study proposes a Rational Water Quality Index (RWQI), a structurally reformulated, concentration-responsive framework that overcomes limitations of conventional Subjective (SWQI) and Objective (OWQI) indices characterized by static or globally normalized weighting schemes. The primary objective was to develop and validate a site-specific weighting function that integrates regulatory exceedance, toxicological severity, and hydrogeochemical similarity within a unified computational structure. RWQI dynamically computes parameter weights as a function of local concentration exceedance relative to drinking water standards, ensuring risk-adjusted representation of individual water quality parameters (WQPs). Comparative evaluation using Pearson correlation, confusion matrix classification, receiver operating characteristic (ROC) analysis, multiple linear regression (MLR), and principal component analysis (PCA) demonstrated consistent performance superiority. RWQI achieved the highest classification accuracy (91.56%) and diagnostic efficiency (AUC = 0.980), while maintaining strong structural coherence (R² = 0.989). PCA further confirmed improved alignment with dominant hydrogeochemical gradients relative to conventional indices. By coupling dynamic risk-weighted computation with parameter interdependence screening, RWQI enhances sensitivity to spatial heterogeneity and contaminant exceedance, providing a mathematically defensible and health-centric framework for groundwater quality evaluation in environmentally stressed and fluoride-prone regions.</p> Graphical Abstract <p></p>

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Advancing Water Quality Assessment Through a Rational, Health-Risk-Sensitive WQI Framework

  • 期刊论文

  • 发表日期：

    2026年3月18日

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  • Rahul Singh,
  • Subhasish Tripathy,
  • Ashok Kumar Gupta,
  • Venkatesh Uddameri

摘要

Accelerating growth of the global population, coupled with rapid urbanization, industrial expansion, intensive agriculture, and mining activities, has increasingly deteriorated groundwater quality, posing serious public health risks. Addressing this challenge requires water quality assessment frameworks that are both scientifically rigorous and explicitly sensitive to health risks. This study proposes a Rational Water Quality Index (RWQI), a structurally reformulated, concentration-responsive framework that overcomes limitations of conventional Subjective (SWQI) and Objective (OWQI) indices characterized by static or globally normalized weighting schemes. The primary objective was to develop and validate a site-specific weighting function that integrates regulatory exceedance, toxicological severity, and hydrogeochemical similarity within a unified computational structure. RWQI dynamically computes parameter weights as a function of local concentration exceedance relative to drinking water standards, ensuring risk-adjusted representation of individual water quality parameters (WQPs). Comparative evaluation using Pearson correlation, confusion matrix classification, receiver operating characteristic (ROC) analysis, multiple linear regression (MLR), and principal component analysis (PCA) demonstrated consistent performance superiority. RWQI achieved the highest classification accuracy (91.56%) and diagnostic efficiency (AUC = 0.980), while maintaining strong structural coherence (R² = 0.989). PCA further confirmed improved alignment with dominant hydrogeochemical gradients relative to conventional indices. By coupling dynamic risk-weighted computation with parameter interdependence screening, RWQI enhances sensitivity to spatial heterogeneity and contaminant exceedance, providing a mathematically defensible and health-centric framework for groundwater quality evaluation in environmentally stressed and fluoride-prone regions.

Graphical Abstract