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    Quantifying the Impact of Compounding Influencing Factors to the Water Level Decline of China’s Largest Freshwater Lake

    Source: Journal of Water Resources Planning and Management:;2020:;Volume ( 146 ):;issue: 006
    Author:
    Xu-chun Ye
    ,
    Fu-hong Liu
    ,
    Zeng-xin Zhang
    ,
    Chong-Yu Xu
    DOI: 10.1061/(ASCE)WR.1943-5452.0001211
    Publisher: ASCE
    Abstract: As a large open lake that connects to the lower Yangtze River, the Poyang Lake, China, has persisted dramatic water level decline since 2003. For better management of lake water resources and ecosystem, this study quantitatively examined the contributions and spatiotemporal differences of compounding influencing factors to this hydrological change. Attempts were achieved through the reconstruction of lake water level series by two combined neural network models. The results indicate that with reference to the period 1980–1999, the average contributions to lake decline during 2003–2014 of lake-bottom topography change, the operation of the Three Gorges Dam (TGD), and climate change and other human activities over the Yangtze River basin were 50%, 18%, and 32%, respectively. The response of the lake water level to the three factors shows obvious spatiotemporal differences due to different influencing mechanisms. It is worth noting that the effect of lake-bottom topography change is still increasing across the lake. In addition, the reduction of precipitation in the Yangtze River basin should be highly correlated to the water level decline of the lake. From the perspective of maintaining a certain water level of the lake and preventing continuous decline and shrinkage, constructing the proposed water control structure would be an effective solution.
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      Quantifying the Impact of Compounding Influencing Factors to the Water Level Decline of China’s Largest Freshwater Lake

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4267862
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    contributor authorXu-chun Ye
    contributor authorFu-hong Liu
    contributor authorZeng-xin Zhang
    contributor authorChong-Yu Xu
    date accessioned2022-01-30T21:14:21Z
    date available2022-01-30T21:14:21Z
    date issued6/1/2020 12:00:00 AM
    identifier other%28ASCE%29WR.1943-5452.0001211.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4267862
    description abstractAs a large open lake that connects to the lower Yangtze River, the Poyang Lake, China, has persisted dramatic water level decline since 2003. For better management of lake water resources and ecosystem, this study quantitatively examined the contributions and spatiotemporal differences of compounding influencing factors to this hydrological change. Attempts were achieved through the reconstruction of lake water level series by two combined neural network models. The results indicate that with reference to the period 1980–1999, the average contributions to lake decline during 2003–2014 of lake-bottom topography change, the operation of the Three Gorges Dam (TGD), and climate change and other human activities over the Yangtze River basin were 50%, 18%, and 32%, respectively. The response of the lake water level to the three factors shows obvious spatiotemporal differences due to different influencing mechanisms. It is worth noting that the effect of lake-bottom topography change is still increasing across the lake. In addition, the reduction of precipitation in the Yangtze River basin should be highly correlated to the water level decline of the lake. From the perspective of maintaining a certain water level of the lake and preventing continuous decline and shrinkage, constructing the proposed water control structure would be an effective solution.
    publisherASCE
    titleQuantifying the Impact of Compounding Influencing Factors to the Water Level Decline of China’s Largest Freshwater Lake
    typeJournal Paper
    journal volume146
    journal issue6
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0001211
    page12
    treeJournal of Water Resources Planning and Management:;2020:;Volume ( 146 ):;issue: 006
    contenttypeFulltext
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