Traceability of nitrate polluted hotspots in plain river networks of the Yangtze River delta by nitrogen and oxygen isotopes coupling bayesian model.

The adverse effects of increased nitrate (NO3-) pollution especially from the non-point source on the hydrosphere and anthroposphere are becoming more prominent. The non-point-derived NO3- in the rivers supplying the upstream threatens the aquatic ecosystem of Taihu Lake. Here, dual-stable isotopes (δ15N and δ18O) of NO3- were applied to the Bayesian model (SIAR) for quantitative source identification of reactive nitrogen (Nr) in a mixed agricultural and urban region along the complex river network of the Yangze River delta. The results showed that the NO3- concentrations in the rivers ranged from 1.09 to 4.44 mg L-1 and decreased from the highly urbanized areas to the lakeside rural areas. The specific isotopic characteristics of four sources (atmospheric deposition, AD; chemical fertilizer, CF; manure and sewage, MS; and soil leachate, SL) by the SIAR isotope model indicated that the MS source made the greatest contribution (46.56%) to the total NO3- load, followed by SL (27.86%), CF (23.77%), and AD (1.81%). The highly urbanized areas and the hybrid areas, which contained a mix of industrialized, populated, and agricultural areas, were identified as hotspot areas with heavy Nr pollution, responsible for spatial patterns of δ15N-NO3- and δ18O-NO3-. These hotspot areas were characterized by a less well-developed sewage pipeline system with high Nr emissions from cash crops. The changes in wastewater treatment level, the agricultural production structure, and meteorological changes were the main factors of spatial variation of Nr concentration and source in the upstream Taihu Lake Basin. The variation in Nr concentration across Taihu Lake would respond to these anthropogenic-driven Nr loads. These findings suggest that MS was the predominant source had the strongest effect on the overall riverine NO3- source which was the primary problem that needed to be solved.