Estimating actual evapotranspiration of soil-vegetation system by combining a physics-based model and machine learning

A synergistic integration of physics-based and data-driven approaches has emerged as promising research field for terrestrial evapotranspiration (ET) estimation, enabling robust modeling of land-atmosphere interactions. This study proposes a hybrid model by integrating machine learning (ML)-based ca...

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Bibliografische gegevens

Hoofdauteurs:	Yiqing Zhang, Li Jia, Chaolei Zheng, Massimo Menenti, Guangcheng Hu, Jing Lu, Qiting Chen
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Taylor & Francis Group 2026-01-01
Reeks:	International Journal of Digital Earth
Onderwerpen:	Evapotranspiration hybrid model deep learning Shuttleworth-Wallace dual-source model ETMonitor canopy surface resistance
Online toegang:	https://www.tandfonline.com/doi/10.1080/17538947.2026.2624207
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