摘要
荆南三口是江湖关系变化的核心,其分流规律变化会对三峡大坝下游江湖关系造成影响,因此需对不断演变的荆南三口分流变化规律及其驱动因子进行量化研究。本文基于1991—2020年的实测资料,通过回归分析与基于Tensorflow搭建的人工神经网络(ANN)模型,探究了三峡水库及上游水库群调蓄、荆南三口河道与干流不对等冲刷等驱动因子对三口分流变化规律的影响。分析结果表明:三峡水库蓄水运用前后,荆南三口分流量发生了较大变化,2003—2020年多年平均分流量比1991—2002年减少约20%,二者相差124.4亿m^(3)。进一步对荆南三口分流演变的驱动因子进行探究,三口洪道和荆江不对等冲刷对三口分流量的影响为主要因素,约为75.7亿m^(3) a;其次是三峡水库调蓄作用的影响,约为28.6亿m^(3) a;而径流变化及三峡上游梯级水库群调蓄等因素对三口分流量的影响约为20.1亿m^(3) a。2003年三峡水库蓄水运用后,水库调节径流和不对等冲刷在三口分流演变的驱动因子中占主导地位,应持续优化三峡水库及其上游梯级水库群联合调度,采取疏、挖等措施,增加三口分流量,以维系江湖关系。
The three outlets along Jingjiang river are the core of the change of river-lake relationship,and the change of diversion law will affect the river-lake relationship in the downstream of the Three Gorges Dam.Therefore,it is necessary to quantitatively study the changing law and driving factors of the three outlets along Jingjiang river.Based on the measured data from 1991 to 2020,through regression analysis and artificial neural network(ANN)model based on Tensorflow,this paper explores the influence of driving factors such as the regulation and storage of the Three Gorges Reservoir and the upstream reservoir group,and the mismatch scour between the three channels of Jingnan outlets and the main stream on the variation law of the three outlets.The results show that before and after the impoundment of the Three Gorges Reservoir in 2003,the diversion volume of the three outlets along Jingjiang river has changed greatly,and the average annual discharge from 2003 to 2020 is reduced by about 20%compared with that from 1991 to 2002,with a difference of 12.44 billion m^(3).Further explore the driving factors of the evolution of the three outlets diversions along Jingjiang river,the influence of mismatch scour between the three channels of Jingnan outlets and the main stream is the main factor,which is about 7.57 billion m^(3) a;The second is the influence of the Three Gorges Reservoir regulation,about 2.86 billion m^(3) a;the influence of runoff change and storage of cascade reservoirs in the upper reaches of the Three Gorges on the diversion of the three outlets is about 2.01 billion m^(3) a.After the impoundment of the Three Gorges Reservoir in 2003,the regulating runoff and unequal erosion of the reservoir dominated the driving factors of the diversion capacity of the three outlets.The joint operation of the Three Gorges Reservoir and its upstream cascade reservoirs should be continuously optimized,and measures such as dredging and excavation should be taken to increase the diversion capacity of the three outlets to m
作者
赵伟
毛继新
关见朝
王大宇
ZHAO Wei;MAO Jixin;GUAN Jianzhao;WANG Dayu(China Institute of Water Resources and Hydropower Research,State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,Beijing 100048)
出处
《水利学报》
EI
CSCD
北大核心
2023年第8期1005-1014,共10页
Journal of Hydraulic Engineering
基金
中国水利水电科学研究院基本科研专项(SE0199A102021,SE0145B042021)
国家自然科学基金青年科学基金项目(52009145)。
关键词
荆南三口
分流比
人工神经网络
Tensorflow
the three outlets along Jingjiang River
flow diversion
artificial neural network
Tensorflow
