Parameterization of the Hargreaves equation in the northern oasis of Mendoza, Argentina

Revista de la Facultad de Ciencias Agrarias

María Gassmann¹  Regina Aguilera²  José Morábito³  José Francisco Maestre-Valero⁴  Victoriano Martínez-Alvarez⁴ 

[1] Universidad Nacional de Buenos Aires. Departamento de Ciencias de la Atmósfera y de los Océanos. Ciudad Autónoma de Buenos Aires. Argentina;Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias. Alte. Brown 500. Chacras de Coria. Mendoza. Argentina. M5528AHB. ;Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias. Alte. Brown 500. Chacras de Coria. Mendoza. Argentina. M5528AHB;Universidad Politécnica de Cartagena. Escuela Superior de Ingeniería Agronómica. Murcia. España;

关键词: reference evapotranspiration;    irrigation programming;    Hargreaves equation;    water scarcity;    adjustment coefficient;   

DOI  :  

来源: DOAJ

【 摘 要 】

In view of the water scarcity that affects the province of Mendoza, Argentina, information on reference crop evapotranspiration (ET0) is crucial for irrigation scheduling. Data that are not generally available is required for the determination of ET0, with the Penman-Monteith FAO56 equation (PM). The Hargreaves equation (HG), which only requires air temperature data, represents an alternative to calculate ET0, after its local or regional calibration with PM. In this paper, the Hargreaves equation was calibrated locally by means of annual (Ca) and monthly (Cm,j) adjustment coefficients for the northern oasis of Mendoza. Also, a regionalisation of the Ca was performed considering environmental variables. The local adjustment with both coefficients made it possible to correct the positive bias that indicated an overestimation of HG with respect to PM in 12 meteorological stations. The mean value of the root mean square error decreased from 0.80 mm day-1 to 0.57 mm day-1 with the Ca adjustment coefficient, and to 0.55 mm day-1 with the Cm,j adjustment coefficient, while the absolute error decreased from 0.63 to 0.42 and 0.39, respectively. Wind speed was the variable that best explained the regional variability of the Ca (R2 = 0.64).

【 授权许可】

Unknown