Estimativa de evapotranspiração potencial no semiárido baiano a partir das imagens termais - Lima, Naiara da Silva (2019)
Brazil’s Northeast region is composed of a great semi-arid climate area in which high temperatures and low rainfall indexes are predominant with an unequal distribution of rainfalls. The deficit observed in the annual hydric balance is a serious problem for agricultural activities, once hydric deficiency limits the agricultural production, reduces the availability of water for animals thirst-quenching and for human consumption, being, though, a fountain of agricultural risks in those areas. Thus, the quantification of evapotranspiration assumes a particular meaning due to these events of hydric deficit, helping the agricultural planning and indicating the period of water shortage.Therefore, the main objective of this research was to estimate the potential evapotranspiration of the municipality of Serrinha from the SAFER algorithm along with local meteorological station data for the 2013 year. The aim was to understand the climatic dynamics of the semi-arid region, to organize the data base with the acquisition of satellite images and meteorological station data for the area of study; it was also sought to estimate ET, using the Penman-Monteith, Samani-Hargrave and Thornthwaite methods with data from the meteorological station of of Serrinha. Finally, the aim was also compare the results of the estimates obtained through the satellite image and empirical mathematical methods. The studied area comprised the entire municipality of Serrinha / BA. The Landsat-8 satellite OLI (Operational Land Imager) image, corresponding to orbit 216 and point 68, was selected through the methodology used to obtain Surface Albedo (α0), Surface Temperature (T0) and the NDVI, SAFER input variables, as well as potential evapotranspiration (ETo) by the Penman-Monteith, Thornthwait and Samani and Hargrave equations with data from the Serrinha-Bahia Conventional Meteorological Station. As results, it was verified that there was no marked difference between the three methods used. The lowest values were those calculated by the Thornthwaite method, and the higher values were those calculated by the Penman-Monteith (PM) methods, followed by the Hargraves-Samani method. ETo was calculated for the entire year 2013, but the values of the date of the chosen image were selected. SAFER computed the highest values for the areas with the presence of more intense vegetation, with maximum values of 5,159 to 6 mm day-1 and the lowest values were found in the urban center and in strips of exposed soil, where there is little or no vegetation