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Quantifying the Human Induced Water Level Decline of China’s Largest Freshwater Lake from the Changing Underlying Surface in the Lake Region

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Abstract

In recent years, dramatic decline in China’s largest freshwater lake, Poyang Lake, has raised wide concerns about water supply and ecological crises in the middle–lower Yangtze River reaches. To assist in resolving the debates regarding the low water regime of the lake, the current study quantitatively assessed the enhanced water level decline from the changing underlying surface in the Poyang Lake region. It is the first time that the magnitude, temporal–spatial difference, trend development and background mechanism of lake water level variation and its causes are studied comprehensively. The results revealed that the changing underlying surface in the lake region has caused an average decline of annual water level of 0.26 m ~ 0.75 m across the lake during 2000–2014, which shows great seasonal and spatial differences. The enlarged outflow cross–section due to extensive sand mining was the major reason for the effect on water level decline in the northern lake. While, increased water surface gradient should be attributed to water level decline in the southern lake. The long–term increasing trend of annual lake water level decline reflects the cumulative effects of lake bottom topography change caused by the continuous south movement of sand mining activities.

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Acknowledgements

This work was financially supported by the Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences (WSGS2015003), National Natural Science Foundation of China (41571023, 41561134016), the Natural Science Foundation of Jiangxi Province (20161BAB203103) and the key grant of Chinese Academy of Sciences (KZZD-EW-12).

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Correspondence to Xuchun Ye.

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Ye, X., Xu, CY., Zhang, Q. et al. Quantifying the Human Induced Water Level Decline of China’s Largest Freshwater Lake from the Changing Underlying Surface in the Lake Region. Water Resour Manage 32, 1467–1482 (2018). https://doi.org/10.1007/s11269-017-1881-5

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  • DOI: https://doi.org/10.1007/s11269-017-1881-5

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