Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using Different Interpolation Methods to Determine Evapotranspiration in a Citrus Orchard

Abstract

A surface energy balance algorithm for land (SEBAL) for estimating evapotranspiration (ET) has been parameterized and tested in a 400-ha drip irrigated citrus orchard. Simultaneously, during three growing seasons, energy fluxes were measured using Eddy Covariance. Instantaneous fluxes obtained with SEBAL using 10 images from Landsat-5 were compared with the measured fluxes. The Perrier function was the best method for properly estimating the roughness momentum length for discontinuous canopies, as in citrus orchards. Crop height was estimated using LIDAR data. In general, SEBAL performed well for net radiation estimation but failed in soil heat flux estimation. Latent heat estimations from the SEBAL model had a relative root mean square error (rRMSE) of 0.06 when compared with measurements obtained by Eddy Covariance. Three procedures were tested for up-scaling the instantaneous ET estimates from SEBAL to daily ET values: 1) assuming the fraction between the actual ET and the reference ET is constant throughout the day; 2) using actual local crop coefficient curves; and 3) using an up-scaling factor where the fraction of hourly ET to daily ET equals the ratio of hourly to daily global solar radiation. This last method gave acceptable results for daily ET estimations (rRMSE = 0.09) and for 15day ET (rRMSE = 0.19), and its main advantage is that no local data are required. It is concluded that the SEBAL methodology can be successfully applied for determining actual ET, even in discontinuous citrus canopies. However, additional parameterizations of momentum roughness length were needed in order to obtain reliable ET determinations.