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

doi:10.1007/s11442-021-1913-1

摘要/Abstract

Abstract:

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.

Key words: water level, Poyang Lake, machine learning, Three Gorges Dam, Yangtze River

. [J]. 地理学报(英文版), 2021, 31(11): 1598-1614.

HUANG Sheng, XIA Jun, ZENG Sidong, WANG Yueling, SHE Dunxian. Effect of Three Gorges Dam on Poyang Lake water level at daily scale based on machine learning[J]. Journal of Geographical Sciences, 2021, 31(11): 1598-1614.

图/表 10

参考文献 49

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Variables	Models	Training		Testing
Variables	Models	NSE	MAE	NSE	MAE
Dongting ($Q_{1}^{DT}$)	ANN	0.7205	1780.8	0.7154	1914.4
	NARX	0.9412	899.8	0.9206	1035.0
	GRU	0.9612	750.1	0.9410	942.6
Poyang ($Z_{1}^{PY}$)	ANN	0.8654	0.9511	0.8251	1.0735
	NARX	0.9790	0.3745	0.9604	0.4806
	GRU	0.9849	0.3207	0.9746	0.4264