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Combining the multivariate statistics and dual stable isotopes methods for nitrogen source identification in coastal rivers of Hangzhou Bay,China
Authors:Zhou  Jia  Hu  Minpeng  Liu  Mei  Yuan  Julin  Ni  Meng  Zhou  Zhiming  Chen  Dingjiang
Institution:1.College of Environmental & Resource Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang Province, China
;2.Agriculture Ministry Key Laboratory of Healthy Freshwater Aquaculture, Key Laboratory of Fish Health and Nutrition of Zhejiang Province, Zhejiang Institute of Freshwater Fisheries, Huzhou, 313001, China
;3.Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou, 310058, China
;4.Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou, 310058, China
;
Abstract:

Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes (\({\updelta}^{15}\mathrm{N}-{\mathrm{NO}}_3^{\hbox{-} }\) and \({\updelta}^{18}\mathrm{O}-{\mathrm{NO}}_3^{\hbox{-} }\)) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine \({\mathrm{NO}}_3^{\hbox{-} }\) in the Cao’e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.

Keywords:
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