Examination of Changes in Selected Nutrient Concentrations from 1988 to 2018 in the Largest Freshwater Lake in China
Journal of Hydrologic Engineering
American Society of Civil Engineers (ASCE)
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Wang, H., Wu, Y., Deng, Y., Liang, D., Zeng, Y., Zhang, X., & Li, Y. (2022). Examination of Changes in Selected Nutrient Concentrations from 1988 to 2018 in the Largest Freshwater Lake in China. Journal of Hydrologic Engineering https://doi.org/10.1061/(ASCE)HE.1943-5584.0002213
As the largest freshwater lake in China, Poyang Lake has been influenced by the urbanization process since the 1990s. Therefore, nutrient concentration data of Poyang Lake in the past three decades were selected for spatial and temporal heterogeneity analysis. The entropy-based method (EBM) was used to calculate the contribution weight of three independent driving factors (precipitation, agricultural land area, and urban land area) to nutrient concentrations in Poyang Lake in three different periods (1988-1997, 1998-2007, and 2008-2018). The results of this study showed that the concentrations of NH3-N and TN have similar trends over time, both of which have been increasing in this century, while the TP concentration has experienced a "decreasing-increasing" process. The nutrient concentrations in the eastern part of Poyang Lake were at the highest level in the whole lake after 1998, and this area has good conditions for the formation of algal blooms, which need special control and management. The effect of precipitation on the nutrient concentrations of the lake in the last thirty years was most prominent. The weight of agriculture's contribution to nutrient concentrations showed a significant upward trend during the first 20 years, and agriculture and urban construction weights remained stable after experiencing opposite changes in the first 20 years. In the future, precipitation in the Poyang Lake basin needs to be of high concern, and agricultural and urban pollution control measures need to be implemented continuously.
Poyang Lake, Nutrient concentration, Driving factors, Entropy-based method (EBM)
This work was supported by the National Natural Science Foundation of China (No. 51779075), National Natural Science Foundation of China (No. 52179064), Priority Academic Program Development of Jiangsu Higher Education Institutions (No. 51479064), and Qing Lan Project of Jiangsu Province.
External DOI: https://doi.org/10.1061/(ASCE)HE.1943-5584.0002213
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338291
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