Articles | Volume 20, issue 8
https://doi.org/10.5194/bg-20-1635-2023
https://doi.org/10.5194/bg-20-1635-2023
Research article
 | 
26 Apr 2023
Research article |  | 26 Apr 2023

Long-term changes of nitrogen leaching and the contributions of terrestrial nutrient sources to lake eutrophication dynamics on the Yangtze Plain of China

Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers

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Cited articles

Batjes, N. H.: Harmonized soil property values for broad-scale modelling (WISE30sec) with estimates of global soil carbon stocks, Geoderma, 269, 61–68, https://doi.org/10.1016/j.geoderma.2016.01.034, 2016. 
Cai, S., Zhao, X., Pittelkow, C. M., Fan, M., Zhang, X., and Yan, X.: Optimal nitrogen rate strategy for sustainable rice production in China, Nature, 615, 73–79, 10.1038/s41586-022-05678-x, 2023. 
Chen, F., Hou, L., Liu, M., Zheng, Y., Yin, G., Lin, X., Li, X., Zong, H., Deng, F., and Gao, J.: Net anthropogenic nitrogen inputs (NANI) into the Yangtze River basin and the relationship with riverine nitrogen export, J. Geophys. Res.-Biogeo., 121, 451–465, 2016. 
Chen, Q., Huang, M., and Tang, X.: Eutrophication assessment of seasonal urban lakes in China Yangtze River Basin using Landsat 8-derived Forel-Ule index: A six-year (2013–2018) observation, Sci. Total Environ., 745, 135392, https://doi.org/10.1016/j.scitotenv.2019.135392, 2020. 
Chen, S., Ge, Q., Chu, G., Xu, C., Yan, J., Zhang, X., and Wang, D.: Seasonal differences in the rice grain yield and nitrogen use efficiency response to seedling establishment methods in the Middle and Lower reaches of the Yangtze River in China, Field Crop. Res., 205, 157–169, 2017. 
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Short summary
Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
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