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Physics-guided networks for probabilistic hydrodynamic forecasting in canal systems

Wangjiayi Liu Guanghua Guan Xiaonan Chen Liangsheng Shi Guangtao Fu Dragan Savic

环境科学与生态技术（英文）2026，Vol.31Issue(3)：111-123,13.

环境科学与生态技术（英文）2026，Vol.31Issue(3)：111-123,13.DOI:10.1016/j.ese.2026.100703

Physics-guided networks for probabilistic hydrodynamic forecasting in canal systems

Wangjiayi Liu ¹Guanghua Guan ¹Xiaonan Chen ²Liangsheng Shi ¹Guangtao Fu ³Dragan Savic⁴

作者信息

1. State Key Laboratory of Water Resources Engineering and Management,Wuhan University,Wuhan,430072,China
2. Construction and Administration Bureau of the Middle-Route of the South-to-North Water Division Project of China,Beijing,100038,China
3. Centre for Water Systems,University of Exeter,Exeter,EX4 4QF,United Kingdom
4. Centre for Water Systems,University of Exeter,Exeter,EX4 4QF,United Kingdom||KWR Water Research Institute,Groningenhaven 7,Nieuwegein,3430 BB,Netherlands
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摘要

关键词

Uncertainty quantification/Physics-guided neural network/Deep probabilistic learning/Hydrodynamic model/Canal system

Key words

Uncertainty quantification/Physics-guided neural network/Deep probabilistic learning/Hydrodynamic model/Canal system

引用本文复制引用

Wangjiayi Liu,Guanghua Guan,Xiaonan Chen,Liangsheng Shi,Guangtao Fu,Dragan Savic..Physics-guided networks for probabilistic hydrodynamic forecasting in canal systems[J].环境科学与生态技术（英文）,2026,31(3):111-123,13.

基金项目

This work is funded by the National Key Research and Devel-opment Program of China[Grant No.2024YFC3211800]and the China Scholarship Council(CSC)[Grant No.202406270118].The authors would also like to acknowledge the Construction and Administration Bureau of the Middle-Route of the South-to-North Water Diversion Project of China for supporting the data collection. （CSC）

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