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基于模态筛选与LSTM-Transformer的渭河流域月径流预报

赵心语 李伶杰 尹思睿 乐逸艺 康艳

水资源与水工程学报2026,Vol.37Issue(4):12-19,28,9.
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水资源与水工程学报2026,Vol.37Issue(4):12-19,28,9.DOI:10.11705/j.issn.1672-643X.2026.04.02

基于模态筛选与LSTM-Transformer的渭河流域月径流预报

Forecasting monthly runoff in the Wei River Basin based on mode screening and LSTM-Transformer

赵心语 1李伶杰 2尹思睿 3乐逸艺 3康艳3

作者信息

  • 1. 水利部水旱灾害防御重点实验室,江苏 南京 210029||西北农林科技大学 水利与建筑工程学院,陕西 杨凌 712100
  • 2. 水利部水旱灾害防御重点实验室,江苏 南京 210029||南京水利科学研究院水灾害防御全国重点实验室,江苏 南京 210029
  • 3. 西北农林科技大学 水利与建筑工程学院,陕西 杨凌 712100
  • 折叠

摘要

Abstract

Accurate monthly runoff forecasting is crucial for flood and drought disaster prevention and wa-ter resources regulation in river basins.To improve the accuracy of runoff forecasting under changing en-vironments,we proposed a TP-LT monthly runoff forecasting framework that integrates TVF-EMD de-composition,PCMCI causal analysis,and the LSTM-Transformer hybrid model.Key driving factors in-cluding modal components of the runoff series,meteorological variables,and atmospheric circulation indi-ces were considered to develop a forecasting model that can capture both short-term and long-term de-pendencies in runoff.Then the model was applied to the forecasting of monthly runoff in the Wei River Basin.The results show that the medium-and high-frequency IMF components can reflect the key fluctu-ation characteristics of monthly runoff.Meteorological factors such as precipitation and relative humidity,along with atmospheric circulation indices including Nino3.4 and AO,are the main meteorological driv-ers.The comparative analysis indicates that the LSTM-Transformer model outperforms any individual model.When only meteorological drivers are used as inputs,the NSE of all models during the validation period is below 0.45,indicating insufficient accuracy.After introducing the key modal drivers,the NSE of the LSTM-Transformer model increases to 0.63-0.78,KGE reaches 0.62-0.82,and R exceeds 0.80.Moreover,the RMSE and MAE are significantly reduced compared with all individual models,and the model captures the timing and process of peak flows more accurately during the flood season.In sum-mary,the TP-LT monthly runoff forecasting framework can effectively improve forecasting performance and provide a reliable method for runoff forecasting in river basins under changing environments.

关键词

径流预报/TVF-EMD/PCMCI/LSTM-Transformer/模态分量/渭河流域

Key words

runoff forecasting/TVF-EMD/PCMCI/LSTM-Transformer/modal component/the Wei River Basin

分类

天文与地球科学

引用本文复制引用

赵心语,李伶杰,尹思睿,乐逸艺,康艳..基于模态筛选与LSTM-Transformer的渭河流域月径流预报[J].水资源与水工程学报,2026,37(4):12-19,28,9.

基金项目

水利部水旱灾害防御重点实验室开放基金项目(KF202602) (KF202602)

国家自然科学基金面上项目(52579022、52379026) (52579022、52379026)

内蒙古自治区水利科技专项(202501010505A) (202501010505A)

水资源与水工程学报

1672-643X

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