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Proposal for the use of daily thermal amplitude for the calibration of the Hargreaves-Samani equation

Zanetti, Sidney Sara, Dohler, Rafael Esteves, Cecílio, Roberto Avelino, Pezzopane, José Eduardo Macedo, Xavier, Alexandre Cândido
Journal of hydrology 2019 v.571 pp. 193-201
air, climate, dry season, equations, evaporative demand, evapotranspiration, forestry, hydrologic cycle, meteorological data, rain, regression analysis, soil, weather stations, wet season
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 (ET0) 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. ET0 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). ET0 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 ET0 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 ET0 estimates, especially on days with higher evaporative demand on air (greater evapotranspiration), when better evapotranspiration estimates for diverse applications were necessary.