Physics-guided deep learning for rainfall-runoff modeling by considering extreme events and monotonic relationships

Kang Xie; Pan Liu; Jianyun Zhang; Dongyang Han; Guoqing Wang; Chaopeng Shen

doi:10.1016/j.jhydrol.2021.127043

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Physics-guided deep learning for rainfall-runoff modeling by considering extreme events and monotonic relationships

Kang Xie Pan Liu Jianyun Zhang Dongyang Han Guoqing Wang Chaopeng Shen

Year: 2021 Journal: Journal of Hydrology Vol: 603 Pages: 127043-127043 Publisher: Elsevier BV

DOI: 10.1016/j.jhydrol.2021.127043

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Keywords:

Surface runoff Flood myth Computer science Monotonic function Artificial intelligence Streamflow Deep learning Machine learning Sample (material) Environmental science Climatology Drainage basin Meteorology Mathematics Geology Ecology Cartography

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Topics

Hydrology and Watershed Management Studies

Physical Sciences → Environmental Science → Water Science and Technology

Hydrological Forecasting Using AI

Physical Sciences → Environmental Science → Environmental Engineering

Flood Risk Assessment and Management

Physical Sciences → Environmental Science → Global and Planetary Change

Physics-guided deep learning for rainfall-runoff modeling by considering extreme events and monotonic relationships

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