Quantitative identification of riverine nitrate sources and uncertainty analysis in the Nanxi River
JI Xiao-liang1, SHU Lie-lin1, CHEN Zheng1, MEI Kun1, XU Feng-ran2, Baiyinbaoligao2, MENDES Ana3, ZHANG Ming-hua1, SHANG Xu1
1. Key Laboratory of Watershed Science and Health of Zhejiang Province, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China; 2. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 3. Evora University, Evora 7002554, Portugal
Abstract:Accurate identification of nitrate sources is the key step for effectively mitigate riverine nitrate pollution. In this study, the Nanxi River watershed located in Wenzhou city was selected as the research area. Hydrochemical analysis and nitrogen and oxygen stable isotopes in nitrate were used to identify spatio-temporal variation, migration and transformation, and pollution sources of nitrate. Then, combining the stable isotope analysis in R (SIAR) model to quantitatively identify the contributions for different pollution sources. On this basis, the probabilistic method was employed to analyze the uncertainty of modelling results. Nitrate was the main form of nitrogen in this study area; there existed significant spatio-temporal variation of riverine nitrate content, temporally, the nitrate concentration in wet season was higher than that in dry season, spatially, the nitrate concentration in tributary was higher than that in main stream. Microbial nitrification was the primary nitrogen transformation process within the Nanxi River watershed, chemical nitrogen, soil organic nitrogen and manure and sewage were the main contributors of nitrate to the river; SIAR modeling revealed that the contributions of atmospheric deposition, chemical nitrogen, soil organic nitrogen, and manure and sewage were 3.0%~12.9%, 25.5%~32.7%, 28.7%~36.2%, and 24.7%~37.5%, respectively, in the dry season, and 2.5%~14.3%, 28.5%~40.0%, 28.8%~39.7%, and 18.9%~29.9%, respectively, in the wet season. The uncertainty analysis demonstrated that uncertainties existed in some extent during nitrate source identification, the uncertainty for different sources followed:soil organic nitrogen > chemical nitrogen > manure and sewage > atmospheric deposition.
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