A unified framework for assessing water quality indices under data and model weight uncertainty

Area of Science:

• Environmental Science
• Water Resource Management
• Analytical Chemistry

Background:

• Water Quality Indices (WQIs) are crucial for assessing water body health.
• Quantifying parameter contributions and uncertainties in WQIs is essential for reliable assessment.
• Existing WQI frameworks often lack robust uncertainty analysis.

Purpose of the Study:

• To develop and apply a global sensitivity framework for WQI assessment.
• To explicitly quantify the contribution and uncertainty of each parameter in WQI formulation.
• To provide a basis for uncertainty-aware water quality assessment and monitoring strategy design.

Main Methods:

• Development of a global sensitivity framework integrating data and weight uncertainties.
• Application to diverse water systems (lakes, springs, groundwater wells).
• Use of a probability-based index and moment-based Global Sensitivity Analysis.

Main Results:

• Major ions influence WQI exceedance at lower thresholds (good quality).
• Redox-sensitive metals and particulates become important at higher thresholds (poor quality).
• System-specific patterns identified: turbidity (lakes), Cu/Mg (springs), Mg/hardness (groundwater).

Conclusions:

• The framework provides critical insights into WQI reliability and interpretation under uncertainty.
• It establishes a rigorous basis for uncertainty-aware water quality assessment.
• Supports the design of optimized, source-specific water quality monitoring strategies.