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The importance of daily data on reference evapotranspiration (ET0) has increased in recent years due to its relevance in planning and decision making regarding irrigated agriculture, water production, and forest restoration. Facing the scarcity of this information measured in loco, the study of interpolation methods capable of representing ET0 becomes important. Therefore, this study aimed to evaluate the adequacy of the Random Forest (RF) method in the spatialization of ET0 in the watersheds of the Mid-South region of the Espírito Santo State, located within the Atlantic Forest biome, Brazil. From this study, it was found that the RF method is the most suitable one for ET0 spatialization when compared to the Angular distance weighting (ADW) and the inverse distance weighting (IDW) techniques. Also, the spatializations carried out by this method were transformed into databases in a grid format and made available online. Furthermore, the RF database was also compared to other ET0 grid databases, and it was concluded that the RF database also carried out a better performance than the other ones. [ABSTRACT FROM AUTHOR]

Highlights • Daily thermal amplitude classes were used to calibrate Hargreaves-Samani equation. • The proposal was tested to several climates under tropical conditions. • Thermal amplitude classes can improve the Hargreaves-Samani equation's calibration. • Thermal amplitude classes can improve the evapotranspiration estimation. Abstract Rationalized water use has become increasingly important in recent years, due to deficient rain distribution and increased water demands, such as in forestry and agricultural production. Evapotranspiration is an important variable of the hydrological cycle and one of the main components of the hydrological balance in the soil. The use of simplified equations is a potential alternative to estimate reference evapotranspiration (ET 0) when meteorological data is limited. The objective of this study was to apply and test different methods to estimate reference evapotranspiration with limitations on meteorological data in the state of Espírito Santo, using the Hargreaves and Samani method under different meteorological conditions, adopting the Penman-Monteith FAO-56 as a reference. ET 0 was calibrated using the Hargreaves and Samani equation with different adjustments by linear regression, considering all the weather stations used in this study (general adjustment), different climate types (adjustment by climate), by dry and rainy season (dry and rainy season adjustments), thermal amplitude class (adjustment by class) and climate type combined with thermal amplitude class (adjustment by climate and class). ET 0 was also estimated for the aims of comparison, using the Hargreaves and Samani original (HS) and Penman-Monteith with limitation of climatic data (PML). In increasing order of efficiency, quantified by the average absolute error (MAE, mm day−1), the methods to estimate evapotranspiration with limitation of meteorological data were: PML (1.46); original HS equation (0.68); general adjustment of ET 0 estimated by the HS equation (0.53) adjustment by thermal amplitude class (0.51); adjustment by climate type (0.51); adjustment for rainy or dry season (0.51); and adjustment by climate and class (0.49). The adjustment by climate and thermal amplitude class provided better ET 0 estimates, especially on days with higher evaporative demand on air (greater evapotranspiration), when better evapotranspiration estimates for diverse applications were necessary. [ABSTRACT FROM AUTHOR]