基于耦合预测模型的大通河月径流预测

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中图分类号：P338

文献标志码：A

doi：10.3969/j.issn.1000-1379.2026.05.008

引用格式： ， . 基于耦合预测模型的大通河月径流预测 [J]. 人民黄河， 2026， 48（5）： 50-58， 71.

Prediction of Monthly Runoff in the Datong River Based on a Coupled Prediction Model

XIAO Ping 1 ， DONG Guotao 2

（1. Hydrology and Water Resources Survey Center of Lanzhou Gansu Province， Lanzhou 730030， China;2. Heihe Water Resources and Ecological Protection Research Center， Lanzhou 730030， China）

Abstract： The simulation and prediction of river runoff are of great significance for controlling basin water volume and ensuring optimal allocation of basin water resources. However， due to the influence of abnormal climate and human activities， the instability of medium- and long-term runoff sequences has increased the difficulty of runoff prediction. To improve prediction accuracy， a coupled deep learning model framework based on variational mode decomposition （VMD）， mutual information （MI）， and bidirectional long short-term memory （Bi-LSTM） networks， called the VMD-Bi-LSTM model， was established. First， VMD was used to decompose the original runoff data into intrinsic mode components; Then， Bi-LSTM was applied to each component to build prediction models， with the input lag time determined by the mutual information method; Finally， the prediction results of each subsequence were superimposed to obtain the final prediction result. The paper explored the performance of the proposed model in predicting the monthly runoff at Tiantang hydrological station in the Datong River Basin and compared it with other models. The results show that： Compared to other models， this model exhibits significant advantages in both point and interval predictions. The Nash-Sutcliffe efficiency coefficient （ NSE ） of the prediction results reaches 0.95， and the coverage rates of interval predictions are 0.92 and 0.85 at the 95% and 90% confidence intervals， respectively.

Key words： VMD; runoff prediction; Bi-LSTM; interval prediction; Datong River

0 引言

作为水文预测的重要环节，准确的径流预测在防洪抗旱、水利调度、水资源可持续利用等方面具有重要意义 [1-3] 。（剩余16081字）