The research of stream flow simulation using Long and Short Term Memory (LSTM) network in Fuhe River Basin of Poyang Lake
JIANG Songchuan1， LU Jianzhong1， CHEN Xiaoling1,2， LIU Zixuan1
1.State Key Laboratory of Information Engineering in Surveying， Mapping and Remote Sensing， Wuhan University， Wuhan 430079， China；2.Key Laboratory of Poyang Lake Wetland and Watershed Research， Ministry of Education， Jiangxi Normal University， Nanchang 330022， China
Abstract：Studies of the changing trend of runoff through hydrological prediction can provide auxiliary decision-making for flood control work， which is also an important method for reservoir regulation. Compared with the traditional SWAT model， the runoff simulation model based on LSTM network is more practical and accurate. Focusing on the Fuhe river basin of Poyang Lake， we use rainfall and runoff data collected from Fuhe river basin as model driving data and label data respectively， and achieve the runoff simulation through LSTM network. The results show as follows. In the daily runoff prediction using data observed from meteorological stations， the correlation between measured and simulated runoff is above 0.9 and Pbias is within ±5%， indicating that the model performs well. In the monthly runoff prediction using TRMM dataset， the overall correlation between measured and simulated runoff is above 0.9 and Pbias is within ±5%， illustrating the excellent performance of the model.
姜淞川,陆建忠,陈晓玲,刘子旋. 基于LSTM网络鄱阳湖抚河流域径流模拟研究[J]. 华中师范大学学报(自然科学版), 2020, 54(1): 128-139.
JIANG Songchuan,LU Jianzhong,CHEN Xiaoling,LIU Zixuan. The research of stream flow simulation using Long and Short Term Memory (LSTM) network in Fuhe River Basin of Poyang Lake. journal1, 2020, 54(1): 128-139.
2020, Vol. 54 
