Evapotranspiração da cana-de-açúcar estimada pelo algoritmo SAFER

Abstract

Sugarcane is the main irrigated crop in Brazil, requiring cumulative rainfall during its 1,000 mm year-1 cycle. The use of remote sensing associated with orbital images and algorithms, aid in the estimation of evapotranspiration when combined with physical models. SAFER is a simplified algorithm when compared to similar ones reported in the literature, as is the case of SEBAL and S-SEBI algorithms, since it is based on the Penman-Monteith equation to obtain evapotranspiration, which is the main reason for choosing this algorithm in this study. Thus, this study aimed to estimate the current evapotranspiration of sugarcane crop by the SAFER energy balance model using images from the Landsat 8 satellite, and comparison with soil water balance method (ETBHS) using soil moisture sensors and reference evapotranspiration. The study was carried out in Goianésia / Go, Brazil from June/2015 to July/2016, in medium textured soil in an irrigated area of 100 ha central pivot, with first cycle sugarcane (IAC 91-1099 variety). The results showed that for the estimation of sugarcane evapotranspiration the SAFER method overestimated the ETBHS by 22.89%, despite the significant correlation (R²= 0.77)between the two methods.