Major rivers worldwide face escalating threats from complex mixtures of conventional and emerging pollutants. Existing prioritization frameworks often fail to accommodate spatial variations in ecosystem service protection targets across functional zones, leading to imprecise risk management. To address this gap, we developed a spatial prioritization framework that operationalizes ecosystem service protection by linking it to statutory functional zones with explicit management mandates. Applied to the Yangtze River, sampling sites were classified into drinking water sources, ecologically sensitive zones (nature reserves and aquatic germplasm protection areas), and general zones. The framework integrated multi-criteria decision analysis with a hybrid objective and subjective weighting method that dynamically adjusts criterion importance according to each zone's primary protection objective. The subsequent NR-TOPSIS ranking generated distinct, zone-specific priority pollutant profiles. The prioritization yielded distinct, zone-specific profiles. Beyond mutual concerns for perfluorooctane sulfonate (PFOS), fluoride (F − ), di(2-ethylhexyl) phthalate (DEHP), and nitrite (NO 2 − -N), drinking water sources prioritized human health toxicants like arsenic, chromium and dichlorodiphenyltrichloroethane (DDT), whereas ecologically sensitive areas emphasized ecological toxicity (e.g., nitrate (NO 3 − -N), pyrene, copper, and zinc). Conversely, conventional water quality parameters and metals remained the focus in other general zones. The hybrid weighting successfully integrated expert-driven objectives with data-derived patterns, yielding results more robust than any single method. These findings demonstrate that ecosystem service protection goals can be systematically translated into zone-specific priority pollutant lists. This translation of protection goals into zone-specific priority lists provides a scientifically grounded and replicable methodology for transitioning from uniform regulation toward targeted, zone-specific management in large, heterogeneous river basins globally.
Gong et al. (Sun,) studied this question.