Comparative Analysis of Crop Coefficient Approaches and Machine Learning Models for Predicting Water Requirements in Three Major Crops in Coastal Saline-Alkali Land

Comparative Analysis of Crop Coefficient Approaches and Machine Learning Models for Predicting Water Requirements in Three Major Crops in Coastal Saline-Alkali Land

The accuracy of the crop coefficient approaches recommended by the FAO-56 guidelines for evapotranspiration (<i>ET</i>) in saline environments is limited due to complex soil–water–crop interactions, highlighting the need for advanced methods to improve <i>ET</i> estimation fo...

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Bibliographic Details
Main Authors: Shide Dong, Qian Ma, Chunxiao Yu, Linbo Li, Hanwen Liu, Guangxu Cui, Haonan Qiu, Shihong Yang, Guangmei Wang
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Agronomy
Subjects:
actual ET
crop coefficient approach
gradient-boosting decision tree
random forest
extreme gradient-boosting regression
Online Access:https://www.mdpi.com/2073-4395/15/2/492

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https://www.mdpi.com/2073-4395/15/2/492

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