摘要
在改进新安江水文预报模型的基础上,利用预报值与实测值之间的误差,构建了基于长短期记忆网络(Long Short-Term Memory,LSTM)洪水预报误差校正模型。以山西省岚河流域50场代表性洪水为研究对象,对改进新安江模型预报结果进行了实时校正。研究结果表明:基于LSTM算法的预报误差校正模型可以较好地提高岚河流域的洪水预报精度,可为当地防洪减灾和水资源管理提供一定的技术支持。
On the basis of improving the Xin′anjiang Hydrological Forecasting Model,an error correction model for flood forecasting based on the Long Short-Term Memory(LSTM)network was constructed by using the error between the forecasted value and the measured value.Taking 50 representative floods in the Lanhe River Basin of Shanxi Province as the research object,and the forecast results of the improved Xin′anjiang Model were corrected in real time.The research results indicate that the forecast error correction model based on the LSTM algorithm can effectively improve the accuracy of flood forecasting in the Lanhe River Basin,providing valuable technical support for local flood prevention,disaster mitigation,and water resource management.
作者
王旭东
周全保
张惠茹
程彬彬
WANG Xudong;ZHOU Quanbao;ZHANG Huiru;CHENG Binbin(Shanxi Water Resources Development Center,Taiyuan 030002;College of Hydro Science and Engineering,Taiyuan University of Technology,Taiyuan 030024)
出处
《中国防汛抗旱》
2025年第8期73-76,共4页
China Flood & Drought Management
基金
山西省水利科学技术研究与推广项目(2024ZF04)
山西省基础研究计划(20210302124370)。
关键词
岚河流域
LSTM算法
洪水预报
误差校正
Lanhe River Basin
LSTM algorithm
flood forecasting
error correction
