Journal article
Actual evapotranspiration and energy balance estimation from vineyards using micro-meteorological data and machine learning modeling
S Fuentes, S Ortega-Farías, M Carrasco-Benavides, E Tongson, C Gonzalez Viejo
Agricultural Water Management | ELSEVIER | Published : 2024
Abstract
Actual evapotranspiration (ETa) can be commonly estimated using numerical models based on i) weather and plant-based parameters, ii) from remotely sensed data and energy balance algorithms, and lately, iii) through the development and implementation of machine learning (ML) modeling techniques. In this work, supervised ML models were developed from a vineyard located in Talca, Chile, (i) to estimate actual evapotranspiration (ETa) (Model 1; M1) using the micrometeorological approach [Eddy Covariance; EC; sensible (H), latent (LE), soil heat fluxes (G) and net radiation (Rn)] and data from an automatic meteorological station (AMS) in reference conditions as ground-truth (inputs); (ii) to esti..
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Grants
Awarded by Agencia Nacional de Investigación y Desarrollo
Funding Acknowledgements
The Chilean government provided the funds for this manuscript preparation through the Agencia Nacional de Investigacion y Desarrollo (ANID) "Fondo de Investigacion Estrategica en Sequia (asignacion rapida) ano 2021" (Grant No. FSEQ210004) . This research eas also funded by the ARC Centre of Excellence in Plants for Space, Australia (Grant No. CE230100015) .r preparation through the Agencia Nacional de Investigaci <acute accent> on y Desarrollo (ANID) "Fondo de Investigaci <acute accent> on Estrate <acute accent> gica en Sequia (asignaci <acute accent> on r <acute accent> apida) an o 2021" (Grant No. FSEQ210004) . This research eas also funded by the ARC Centre of Excellence in Plants for Space, Australia (Grant No. CE230100015) .