Machine Learning Calibration of Groundwater Table Depth in ELM: Impact on Land Surface Hydrology and Land‐Atmosphere Fluxes

Abstract Accurate representation of groundwater table depth (GWTD) is crucial for simulating hydrological cycling in Earth system models (ESM). Nevertheless, there is a notable gap in the literature regarding the validation of GWTD simulations in ESMs and their subsequent impact on downstream hydrol...

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Autors principals:	Yilin Fang, L. Ruby Leung
Format:	Artigo
Idioma:	Inglês
Publicat:	American Geophysical Union (AGU) 2026-03-01
Col·lecció:	Journal of Advances in Modeling Earth Systems
Matèries:	Energy Exascale Earth System Model (E3SM) groundwater table depth machine learning calibration land‐atmosphere interactions
Accés en línia:	https://doi.org/10.1029/2025MS005184
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