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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Bibliografski detalji

Glavni autori:	Andrew Bennett, Hoang Tran, Luis De laFuente, Amanda Triplett, Yueling Ma, Peter Melchior, Reed M. Maxwell, Laura E. Condon
Format:	Artigo
Jezik:	Inglês
Izdano:	American Geophysical Union (AGU) 2024-06-01
Serija:	Journal of Advances in Modeling Earth Systems
Teme:	deep learning surrogate models groundwater hydrologic modeling
Online pristup:	https://doi.org/10.1029/2023MS004095
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