水利学报2025，Vol.56Issue(3)：364-374,11.DOI:10.13243/j.cnki.slxb.20240212
基于深度学习与HEC-HMS模型的小流域暴雨洪水耦合预报
Coupled forecasting of rainstorms and floods in small watershed based on Deep Learning and HEC-HMS Model
摘要
Abstract
The rainfall runoff process in small watershed is so quick that the forecast lead time of conventional flood monitoring and forecasting is short,which is difficult to provide effective support for flood prevention and disaster relief.In this study,a coupled forecasting framework for rainstorm and flood forecasting is established.In this framework,the hydrological model is driven by the rainfall nowcasting to prolong the forecast lead time of flooding,which is of great importance for flood prevention in small watershed.In the rainfall nowcasting method,this paper proposes a Rainfall Nowcasting Method with Combined Reflectance and Wind Field as Inputs(RNMCW),the combined reflection and radar-retrieved wind field that can effectively reflect the water vapor content and water va-por transportation are selected as inputs,and the deep learning model is proposed to extract the temporal and spa-tial characteristics of inputs to forecast the rainfall in the basin.The results show that the correlation coefficient of the rainfall nowcasting method is higher than 0.75 at each station,which is about 5％higher than that of the con-ventional optical flow method.Then,the parameters of the HEC-HMS model are calibrated with the rainfall pre-dicted by RNMCW,and the rainfall forecast results are used as the input of the hydrological model to build a storm and flood coupling forecast model.Compared with the HEC-HMS model,the coupled model reduces the flood peak prediction error of 2016 flood by 2.17％,and increases the Nash coefficient of 20180722 flood prediction by 0.002.The model can effectively forecast the flood process and extend the effective prediction period by up to 2 hours,thus significantly improving the flood prediction effect and providing better support for practical application.关键词
短临降雨预报/深度学习/雷达反演风场/暴雨洪水耦合预报Key words
rainfall nowcasting/deep learning/radar-retrieved wind field/coupled forecasting of rainstorms and floods分类
天文与地球科学引用本文复制引用
刘万,谢帅,钟德钰,王永强,包淑萍,朱旭东..基于深度学习与HEC-HMS模型的小流域暴雨洪水耦合预报[J].水利学报,2025,56(3):364-374,11.基金项目
国家自然科学基金项目(U2040211,U2040212,52379011) （U2040211,U2040212,52379011）
湖北省自然科学基金(2024AFA011,2023AFB039) （2024AFA011,2023AFB039）
中央级基本科研业务费(CKS20241021/SZ) （CKS20241021/SZ）
宁夏重点研发项目(2020BCF01002) （2020BCF01002）
