Estimation of Daily Actual Evapotranspiration of Tea Plantations Using Ensemble Machine Learning Algorithms and Six Available Scenarios of Meteorological Data

Estimation of Daily Actual Evapotranspiration of Tea Plantations Using Ensemble Machine Learning Algorithms and Six Available Scenarios of Meteorological Data

The tea plant (<i>Camellia sinensis</i>), as a major, global cash crop providing beverages, is facing major challenges from droughts and water shortages due to climate change. The accurate estimation of the actual evapotranspiration (ET<sub>a</sub>) of tea plants is essential...

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Bibliographic Details
Main Authors: Jianwei Geng, Hengpeng Li, Wenfei Luan, Yunjie Shi, Jiaping Pang, Wangshou Zhang
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
evapotranspiration
tea plantations
machine learning
prediction models
Online Access:https://www.mdpi.com/2076-3417/13/23/12961

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