Using Ensembles of Machine Learning Techniques to Predict Reference Evapotranspiration (ET<sub>0</sub>) Using Limited Meteorological Data

Using Ensembles of Machine Learning Techniques to Predict Reference Evapotranspiration (ET<sub>0</sub>) Using Limited Meteorological Data

To maximize crop production, reference evapotranspiration (ET<sub>0</sub>) measurement is crucial for managing water resources and planning crop water needs. The FAO-PM56 method is recommended globally for estimating ET<sub>0</sub> and evaluating alternative methods due to it...

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Bibliographic Details
Main Authors: Hamza Salahudin, Muhammad Shoaib, Raffaele Albano, Muhammad Azhar Inam Baig, Muhammad Hammad, Ali Raza, Alamgir Akhtar, Muhammad Usman Ali
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Hydrology
Subjects:
reference evapotranspiration
machine learning techniques
ensemble approach
limited meteorological data
Online Access:https://www.mdpi.com/2306-5338/10/8/169

Internet

https://www.mdpi.com/2306-5338/10/8/169

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