A Reference-Value-Based Drinking-Water Quality Deterioration Index for Sustainable Monitoring of Water Supply Network Points

Drinking-water management requires tools that can support the interpretation of multiparameter monitoring data beyond binary compliance assessment. The novelty of this study lies in adapting a reference-value-based deterioration logic to treated drinking water monitored at network points and combining it with parameter eligibility rules, treatment of results below LoQ, contribution analysis, and sensitivity testing. This study proposes the Drinking-Water Quality Deterioration Index (DWQDI) as a simple, transparent tool for screening reference-value-based water-quality deterioration signals in chemical and physicochemical monitoring data from water supply network points. This index is based on the ratio of concentration to a reference value and was developed for treated drinking water monitored in the distribution network; it expresses reference-value proximity within monitored samples rather than temporal change in water quality. It does not replace formal compliance assessment or health risk assessment but rather provides a complementary tool for sustainable and risk-oriented monitoring. The proposed index was applied to an extended chemical monitoring dataset comprising 25 drinking-water samples collected from 16 anonymized network locations between 2021 and 2026. The dataset included 59 chemical and physicochemical parameters, and a significant proportion of results were below the analytical limits of quantification. Baseline DWQDI values ranged from 0.030 to 0.147, with all samples classified as having very low deterioration. Despite the absence of deterioration due to exceedances, the index differentiated samples and identified the main factors contributing to the deterioration signal. The permanganate index, Total THM, and nickel accounted for most of the total normalized load. The proposed index can help water utilities identify network samples, locations, and parameters requiring further diagnostic investigation and can be implemented in other water supply systems using routinely available monitoring data.