Using dual isotopes and a Bayesian isotope mixing model to evaluate sources of nitrate of Tai Lake, China

Identification and quantification of sources of nitrate (NO3-) in freshwater lakes provide useful information for management of eutrophication and improving water quality in lakes. Dual N-15- and O-18-NO3- isotopes and a Bayesian isotope mixing model were applied to identify sources of NO3- and estimate their proportional contributions to concentrations of NO3- in Tai Lake, China. In waters of Tai Lake, values for N-15-NO3- ranged from 3.8 to 10.1, while values of O-18 ranged from 2.2 to 12.0. These results indicated that NO3- was derived primarily from agricultural and industrial sources. Stable isotope analysis in R called SIAR model was used to estimate proportional contributions from four potential NO3- sources (agricultural, industrial effluents, domestic sewage, and rainwater). SIAR output revealed that agricultural runoff provided the greatest proportion (50.8%) of NO3- to the lake, followed by industrial effluents (33.9%), rainwater (8.4%), and domestic sewage (6.8%). Contributions of those primary sources of NO3- to sub-regions of Tai Lake varied significantly (p<0.05). For the northern region of the lake, industrial source (35.4%) contributed the greatest proportion of NO3-, followed by agricultural runoff (27.4%), domestic sewage (21.3%), and rainwater (15.9%). Whereas for the southern region, the proportion of NO3- contributed from agriculture (38.6%) was slightly greater than that contributed by industry (30.8%), which was similar to results for nearby inflow tributaries. Thus, to improve water quality by addressing eutrophication and reduce primary production of phytoplankton, NO3- from both nonpoint agricultural sources and industrial point sources should be mitigated.