On the value of indicators for large-scale water quality assessments

Global efforts to improve water quality under UN SDG 6.3.2 are undermined by disparate national monitoring standards that prevent coherent assessment. Additionally, water quality modeling can help to provide spatially continuous monitoring data for a set of water quality constituents, but not for all relevant indicators. This inconsistency hinders accountability in supply chains, management of biogeochemical cycles, and mitigation of transboundary pollution. To address this inconsistency, we evaluate and propose a core set of water quality indicators. We compare this proposed set against the against water quality constituents currently included in major international monitoring frameworks (e.g. nutrients, heavy metals, and microbial contaminants) and modeling projects, which simulate outputs like nutrient concentrations and pollutant loads, to identify key areas where modeling efforts could focus. Finally, we propose a tiered roadmap designed to achieve implementation of these core metrics, focusing on harmonizing existing outputs, filling model gaps, and incorporating emerging indicators.