Improving time upscaling of instantaneous evapotranspiration based on machine learning models

Improving time upscaling of instantaneous evapotranspiration based on machine learning models

Evapotranspiration (ET) plays a crucial role in the global water and energy cycle. Upscaling instantaneous ET ([Formula: see text]) to daily ET ([Formula: see text]) is vital for thermal-based ET estimation. Conventional methods – such as the constant evaporative fraction method (ConEF), radiation-b...

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Bibliographic Details
Main Authors: Danni Yang, Shanshan Yang, Jiaojiao Huang, Shuyu Zhang, Sha Zhang, Jiahua Zhang, Yun Bai
Format: Article
Language:English
Published: Taylor & Francis Group 2025-01-01
Series:Big Earth Data
Subjects:
Constant evaporative fraction method (ConEF)
evapotranspiration (ET)
machine learning (ML)
time upscaling
Online Access:https://www.tandfonline.com/doi/10.1080/20964471.2024.2423431
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https://www.tandfonline.com/doi/10.1080/20964471.2024.2423431

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