title: Nitrate behaviors and source apportionment in an aquatic system from a watershed with intensive agricultural activities.
abstract: Nitrate pollution in aquatic systems caused by intensive agricultural activities is a serious problem in the Sanjiang Plain. In this study, a dual isotope approach (δ(15)N-NO3(-) and δ(18)O-NO3(-)) was employed to identify potential nitrate sources (atmospheric deposition, AD; NO3(-) derived from soil organic matter nitrification, NS; NO3(-) derived from chemical fertilizer nitrification, NF; and manure and sewage, M&S) and transformation processes occurring in the Abujiao River watershed located in the Sanjiang Plain. The Bayesian model (stable isotope analysis in R, SIAR) was utilized to apportion the contribution of the potential sources. In this watershed, the nitrate concentrations in the surface water were low (mean ± SD = 1.15 ± 0.84 mg L(-1)), and were greatly influenced by precipitation and land use conditions during the two sampling periods (the high flow period, September; the low flow period, November). On the contrary, in the ground water, high NO3(-) concentrations were observed (7.84 ± 5.83 mg L(-1)) and no significant temporal variation in NO3(-) was found during the sampling periods. The sampled water δ(18)O-NO3(-) values suggest that the nitrification process was not the main N cycling process, because most of the measured δ(18)O-NO3(-) values were above the expected δ(18)O-NO3(-) from nitrification throughout the sampling periods. Both the chemical and isotopic characteristics indicated that the signs of de-nitrification were absent in the surface water. However, significant de-nitrification processes were observed in the ground water for all sample periods. Results from the SIAR model showed that source contributions differed significantly during the two sampling periods. During the high flow period, chemical fertilizers and soil N fertilizer equally contributed to the major sources of nitrate in the surface water. In contrast, manure and sewage sources dominated the source contribution during the low flow period (November). This study suggested that with the assessment of the behaviors and sources of NO3(-), effective nitrate reduction strategies and better management practices can be implemented to protect water quality.
authors.affiliation: School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing, 100875, China. chg@bnu.edu.cn.
authors.forename: Lu
authors.initials: L
authors.lastname: Lu
authors.forename: Hongguang
authors.initials: H
authors.lastname: Cheng
authors.forename: Xiao
authors.initials: X
authors.lastname: Pu
authors.forename: Xuelian
authors.initials: X
authors.lastname: Liu
authors.forename: Qianding
authors.initials: Q
authors.lastname: Cheng
mesh_terms: D000383:Agriculture / Q000379:methods / Q000706:statistics & numerical data*; D001499:Bayes Theorem; D004784:Environmental Monitoring; D005308:Fertilizers / Q000706:statistics & numerical data; D060587:Groundwater / Q000737:chemistry; D008956:Models, Chemical; D009566:Nitrates / Q000032:analysis; D058465:Nitrification; D014874:Water Pollutants, Chemical / Q000032:analysis; D014877:Water Pollution, Chemical / Q000706:statistics & numerical data*
chemical_list: D005308:Fertilizers; D009566:Nitrates; D014874:Water Pollutants, Chemical