中国防汛抗旱2024，Vol.34Issue(2)：8-15,8.DOI:10.16867/j.issn.1673-9264.2023467
基于循环神经网络的山前平原型城市河道洪水预报研究
Study of flood forecasting based on recurrent neural network for urban river in the piedmont plain
摘要
Abstract
The floods in the piedmont plain city with complex underlying surface conditions exhibits characteristics of both mountain and urban floods,posing challenges for hydrological simulation and flood forecasting.In this study,we developed several flood forecasting models based on recurrent neural network variations in the Xiaoqing River Watershed above the Huangtaiqiao Hydrological Station in Jinan City,and assessed its predictive performance.The research findings demonstrate that the constructed flood forecasting model is suitable for forecasting both single flood events and providing continuous predictions for long series of processes.It has the capability to flexibly generate discharge and water level processes,while maintaining a high level of prediction accuracy within a specific forecast step.Among them,the model based on BiGRU(Bidirectional Gate Recurrent Unit)network exhibits the best prediction performance,with the weakest performance degradation as the length of the prediction step increases.Therefore,it can be regarded as a novel approach for riverine flood forecasting in piedmont plain cities.关键词
洪水预报/城市河道/山前平原型城市/神经网络/BiGRUKey words
flood forecasting/urban river/piedmont plain city/neural network/BiGRU分类
建筑与水利引用本文复制引用
陈畅,王帆,张大伟,向立云,芦昌兴..基于循环神经网络的山前平原型城市河道洪水预报研究[J].中国防汛抗旱,2024,34(2):8-15,8.基金项目
水灾害防御全国重点实验室"一带一路"水与可持续发展科技基金资助项目(2021491511) （2021491511）
水利部重大科技项目(SKS-2022007) （SKS-2022007）
中国水利水电科学研究院科研专项(WH0145B022021、WH0145B042021、JZ110145B0022023) （WH0145B022021、WH0145B042021、JZ110145B0022023）
2023年度中国科协科技智库青年人才计划(20230504ZZ07240108). （20230504ZZ07240108）
