水资源与水工程学报2024，Vol.35Issue(2)：71-82,12.DOI:10.11705/j.issn.1672-643X.2024.02.08
基于相关性检验的VMD-LSTM耦合模型月径流模拟研究
Simulation of monthly runoff by VMD-LSTM coupled model based on correlation testing
摘要
Abstract
In recent years,the frequent occurrence of extreme heavy rainfall and drought events has in-tensified the uncertainty changes of hydrological processes in the basin,making it more difficult for the prediction of medium and long-term runoff in the basin.In order to improve the ability of LSTM(long short-term memory)model in capturing and fitting temporal changes in runoff,taking the Boyang River Basin as the study area,we collected the data of monthly rainfall,evaporation and flow for the simula-tion.Then,VMD(variational modal decomposition)and correlation testing are used to eliminate the in-terference of irrelevant frequency components on the regular learning of LSTM model for the purpose of model input optimization.In addition,the effects of different coupling methods between VMD and LSTM model on the accuracy and stability of the model are considered,by which the VMD-LSTM monthly run-off coupled model which takes the advantages of both is finally selected.The simulation results show that the VMD-LSTM coupled model can significantly improve the simulation accuracy but it is lacking in model stability,the VMD-LSTM coupled model based on correlation testing can not only further improve the model accuracy,but also improves the stability of the model.In the comparison of the different cou-pling methods of the VMD-LSTM coupled model based on the correlation testing,scheme D1 which de-composes both inputs and outputs with VMD and optimizes inputs has the best simulation accuracy and stability,with an NSEvalue of 0.98 and above for 60 simulations.In addition,when analyzing the inter-pretability of scheme D1,it is found that historical runoff has a greater impact on the LSTM model than rainfall and evaporation.The results of this study can provide accurate and reliable medium and long-term runoff simulations for the water resources management in the basin.关键词
相关性检验/变分模态分解/长短期记忆神经网络/径流模拟/博阳河流域Key words
correlation testing/variational modal decomposition(VMD)/long short-term memory(LSTM)neural network/runoff simulation/the Boyang River Basin分类
天文与地球科学引用本文复制引用
刘声洪,SOOMRO Shan-E-Hyder,李颖,李英海,程雄,杨少康..基于相关性检验的VMD-LSTM耦合模型月径流模拟研究[J].水资源与水工程学报,2024,35(2):71-82,12.基金项目
国家自然科学基金项目(52179018,51909010) （52179018,51909010）
国家重点研发计划课题(2022YFC3203902-3) （2022YFC3203902-3）
智慧长江与水电科学湖北省重点实验室(中国长江电力股份有限公司)开放基金项目(ZH2002000103) （中国长江电力股份有限公司）
长江科学院开放研究基金项目(CKWV2021889/KY) （CKWV2021889/KY）
