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Quantification of backwater effect in Jingjiang Reach due to confluence with Dongting Lake using a machine learning model

Hai-xin Shang Jun-qiang Xia Chun-hong Hu Mei-rong Zhou Shan-shan Deng

水科学与水工程2025，Vol.18Issue(2)：187-199,13.

水科学与水工程2025，Vol.18Issue(2)：187-199,13.DOI:10.1016/j.wse.2025.02.002

Quantification of backwater effect in Jingjiang Reach due to confluence with Dongting Lake using a machine learning model

Hai-xin Shang ¹Jun-qiang Xia ¹Chun-hong Hu ²Mei-rong Zhou ¹Shan-shan Deng¹

作者信息

1. State Key Laboratory of Water Resources Engineering and Management,Wuhan University,Wuhan 430072,China
2. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research,Beijing 100048,China
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摘要

关键词

Backwater effect/Stage-discharge relationship/Machine learning model/Dongting Lake confluence/Jingjiang reach

Key words

Backwater effect/Stage-discharge relationship/Machine learning model/Dongting Lake confluence/Jingjiang reach

引用本文复制引用

Hai-xin Shang,Jun-qiang Xia,Chun-hong Hu,Mei-rong Zhou,Shan-shan Deng..Quantification of backwater effect in Jingjiang Reach due to confluence with Dongting Lake using a machine learning model[J].水科学与水工程,2025,18(2):187-199,13.

基金项目

The work was supported by the National Key Research and Development Program of China(Grant No.2023YFC3209504),the National Natural Sci-ence Foundation of China(Grants No.U2040215 and 52479075),and the Natural Science Foundation of Hubei Province(Grant No.2021CFA029). （Grant No.2023YFC3209504）

水科学与水工程

ISSN：1674-2370

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