Implementation of a Two-Source Model for Estimating the Spatial Variability of Olive Evapotranspiration Using Satellite Images and Ground-Based Climate Data

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datacite.alternateIdentifier.citationWater, Vol. 10, N° 3, 339, 2018en_US
datacite.alternateIdentifier.doi10.3390/w10030339en_US
datacite.creatorFuentes Peñailillo, Fernando
datacite.creatorOrtega Farías, Samuel
datacite.creatorAcevedo Opazo, Cesar
datacite.creatorFonseca Luengo, David
datacite.date2018
datacite.subjectEvapotranspiraciónen_US
datacite.subjectOlivoen_US
datacite.subjectVariabilidad espacialen_US
datacite.subjectSensores remotosen_US
datacite.titleImplementation of a Two-Source Model for Estimating the Spatial Variability of Olive Evapotranspiration Using Satellite Images and Ground-Based Climate Dataen_US
dc.date.accessioned2019-12-11T19:18:12Z
dc.date.available2019-12-11T19:18:12Z
dc.description.abstractA study was carried out to evaluate the potential use of the two-source Shuttleworth and Wallace (SW) model to compute the intra-orchard spatial variability of actual evapotranspiration (ET) of olive trees using satellite images and ground-based climate data. The study was conducted in a drip-irrigated olive orchard using satellite images (Landsat 7 ETM+), which were acquired on clear sky days during the main phenological stages (2009/10 growing season). The performance of the SW model was evaluated using instantaneous latent heat flux (LE) measurements that were obtained from an eddy correlation system. At the time of satellite overpass, the estimated values of net radiation (Rni) and soil heat flux (Gi) were compared with ground measurements from a four-way net radiometer and soil heat flux plates, respectively. The results indicated that the SW model subestimated instantaneous LE (W m−2) and daily ET (mm d−1), with errors of 12% and 10% of observed values, respectively. The root mean square error (RMSE) and mean absolute error (MAE) values for instantaneous LE were 26 and 20 W m−2, while those for daily values of ET were 0.31 and 0.28 mm d−1, respectively. Finally, the submodels computed Rni and Gi with errors of between 4.0% and 8.0% of measured values and with RMSE and MAE between 25 and 39 W m−2en_US
dc.formatPDFen_US
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/2120
dc.language.isoenen_US
dc.sourceWateren_US
oaire.resourceTypeArtículo de Revistaen_US
uct.catalogadorpopen_US
uct.comunidadRecursos Naturalesen_US
uct.facultadFacultad de Recursos Naturalesen_US
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