Estimation of the Evapotranspiration of Irrigated Acai (Euterpe oleracea M.), through the Surface Energy Balance Algorithm for Land-SEBAL, in Eastern Amazonia

The culture of acai (Euterpe oleraceae M.), originating from floodplain areas, was planted on dry land in many properties in Para, Brazil, making necessary the use of irrigation. To irrigate adequately with less waste, it is necessary that studies aim at increasing efficiency in the use of water in this sector, and one of the ways to do so is to estimate evapotranspiration (ET). The objective of this study was to estimate the actual daily evapotranspiration using the Surface Energy Balance Algorithm for Land (SEBAL) in eastern Amazonia. Six images from the Landsat 8 satellite were used, and the estimates of evapotranspiration with the SEBAL algorithm showed good agreement with the results obtained by the Bowen ratio method in the area of acai planting, including the mean absolute error (MAE), mean relative error (MRE), root of mean square error (RMSE), and the concordance index (d index) equal to 0.45 mm day(-1), 4.23%, 0.52 mm day(-1), and 0.80, respectively. SEBAL showed the ability to distinguish the soil cover, demonstrating the sensitivity of the model, which provided the mapping of the components analyzed. The use of the algorithm helps in decision making regarding irrigation management and reducing costs and water losses.