Spatio‐Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology

Abstract Integrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow‐CLM model across th...

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Κύριοι συγγραφείς:	Andrew Bennett, Hoang Tran, Luis De laFuente, Amanda Triplett, Yueling Ma, Peter Melchior, Reed M. Maxwell, Laura E. Condon
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	American Geophysical Union (AGU) 2024-06-01
Σειρά:	Journal of Advances in Modeling Earth Systems
Θέματα:	deep learning surrogate models groundwater hydrologic modeling
Διαθέσιμο Online:	https://doi.org/10.1029/2023MS004095
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