Water Quality Indices for Irrigation and Drinking Water Supply: The Importance of Use-Specific Assessment

Water quality indices are generally developed for specific water uses, but direct comparisons of indices designed for public water supply and irrigation using the same monitoring dataset remain limited. This study evaluated surface water quality in the Federal District (FD), Brazil, assessing its suitability for public drinking water supply and irrigation under different land uses. Eighteen sampling sites across rural, urban, and natural hydrographic units were monitored bimonthly from December 2017 to October 2019. A total of 12 sampling campaigns were conducted, resulting in 12 samples per site and 216 samples overall. The reported water quality indices were calculated using the median values obtained over the monitoring period. Twelve physical, chemical, and microbiological parameters were analyzed to calculate the WQICETESB (for raw water intended for public drinking-water supply after treatment) and the IWQIFD (for irrigation). The WQICETESB classified 16 sampling sites as “Good” (52–79) and two as “Reasonable” (37–51), with no sites classified as “Excellent”. The IWQIFD classified six sampling sites as “Excellent” (90–100), seven as “Good” (75–89), and five as “Average” (51–74). No significant differences were detected among broad land use categories, whereas seasonal differences were observed for water temperature, turbidity, total phosphorus, and total nitrogen. Multivariate analyses indicated site-specific patterns associated with anthropogenic and natural hydrogeochemical influences. Even in natural areas, water may not meet optimal conditions for irrigation. The IWQIFD yielded more favorable classifications than the WQICETESB at several sampling sites, reflecting differences in parameter selection, weighting structure, classification thresholds, and intended uses. These findings reinforce the importance of use-specific water-quality assessment and demonstrate the value of WQIs as complementary tools for integrating complex datasets and supporting Integrated Water Resources Management (IWRM). For management purposes, index selection should be aligned with the intended water use, while critical individual parameters should also be evaluated alongside aggregated index scores.