Effect of Three Gorges Dam on Poyang Lake water level at daily scale based on machine learning  

基于机器学习方法日尺度下模拟三峡对鄱阳湖水位的影响

作　　者：HUANG Sheng XIA Jun ZENG Sidong WANG Yueling SHE Dunxian 黄绳;夏军;曾思栋;王月玲;佘敦先(State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan 430072,China;Hubei Key Laboratory of Water System Science for Sponge City Construction,Wuhan University,Wuhan 430072,China;Key Laboratory of Water Cycle and Related Land Surface Processes,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;Chongqing Institute of Green and Intelligent Technology,CAS,Chongqing 400714,China)

机构地区：[1]State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan 430072,China [2]Hubei Key Laboratory of Water System Science for Sponge City Construction,Wuhan University,Wuhan 430072,China [3]Key Laboratory of Water Cycle and Related Land Surface Processes,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China [4]Chongqing Institute of Green and Intelligent Technology,CAS,Chongqing 400714,China

出　　处：《Journal of Geographical Sciences》2021年第11期1598-1614,共17页地理学报（英文版）

基　　金：Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA23040500;National Natural Science Foundation of China,No.41890823。

摘　　要：Lake water level is an essential indicator of environmental changes caused by natural and human factors.The water level of Poyang Lake,the largest freshwater lake in China,has exhibited a dramatic variation for the past few years,especially after the completion of the Three Gorges Dam(TGD).However,there is a lack of more accurate assessment of the effect of the TGD on the Poyang Lake water level(PLWL)at finer temporal scales(e.g.,the daily scale).Here,we used three machine learning models,namely,an Artificial Neural Network(ANN),a Nonlinear Autoregressive model with exogenous input(NARX),and a Gated Recurrent Unit(GRU),to simulate the daily lake level during 2003-2016.We found that machine learning models with historical memory(i.e.,the GRU model)are more suitable for simulating the PLWL under the influence of the TGD.The GRU-based results show that the lake level is significantly affected by the TGD regulation in the different operation stages and in different periods.Although the TGD has had a slight but not very significant impact on the yearly decline of the PLWL,the blocking or releasing of water at the TGD at certain moments has caused large changes in the lake level.This machine-learning-based study sheds light on the interactions between Poyang Lake and the Yangtze River regulated by the TGD.

关 键 词：water level Poyang Lake machine learning Three Gorges Dam Yangtze River 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TV632[自动化与计算机技术—控制科学与工程] P333[水利工程—水利水电工程]