基于循环神经网络的山前平原型城市河道洪水预报研究

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国家科技期刊平台
NETL
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中文摘要：山前平原型城市拥有复杂的下垫面条件,其洪水兼具了山洪和城市洪水的特征,为水文模拟和洪水预报增加了难度.以小清河济南市黄台桥水文站以上流域为研究对象,构建了基于循环神经网络变体的洪水预报模型,并评估了模型的预测性能.研究结果表明,所构建的洪水预报模型既适用于对场次洪水的预报,又适用于对长系列洪水过程的连续预测,且能够灵活地输出流量、水位过程,在一定预测步长内拥有较高的预测精度,其中基于双向门控循环单元(Bidirectional Gate Recurrent Unit,BiGRU)网络构建的模型预测性能最佳,且随预测步长的延长,其性能衰减最弱,能够作为山前平原型城市河道洪水预报的新方法新手段.

外文标题：Study of flood forecasting based on recurrent neural network for urban river in the piedmont plain

外文摘要：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.

外文关键词：

flood forecastingurban riverpiedmont plain cityneural networkBiGRU

作者：

陈畅、王帆、张大伟、向立云、芦昌兴

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作者单位：

中国水利水电科学研究院,北京 100038

水利部防洪抗旱减灾工程技术研究中心(水旱灾害防御中心),北京 100038

水发规划设计有限公司,济南 250000

关键词：

洪水预报城市河道山前平原型城市神经网络 BiGRU

基金：

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水利部重大科技项目中国水利水电科学研究院科研专项中国水利水电科学研究院科研专项中国水利水电科学研究院科研专项2023年度中国科协科技智库青年人才计划

项目编号：

2021491511SKS-2022007WH0145B022021WH0145B042021JZ110145B002202320230504ZZ07240108

出版年：

2024

DOI：

10.16867/j.issn.1673-9264.2023467

中国防汛抗旱

中国水利学会

中国防汛抗旱

影响因子：0.286

ISSN：1673-9264

年,卷(期)：2024.34(2)

参考文献量21