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

Authors

  • Regina Aguilera Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias. Alte. Brown 500. Chacras de Coria. Mendoza. Argentina. M5528AHB.
  • José Francisco Maestre-Valero Universidad Politécnica de Cartagena. Escuela Superior de Ingeniería Agronómica. Murcia. España
  • Victoriano Martínez-Alvarez Universidad Politécnica de Cartagena. Escuela Superior de Ingeniería Agronómica. Murcia. España
  • María Gassmann Universidad Nacional de Buenos Aires. Departamento de Ciencias de la Atmósfera y de los Océanos. Ciudad Autónoma de Buenos Aires. Argentina
  • José Morábito Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias. Alte. Brown 500. Chacras de Coria. Mendoza. Argentina. M5528AHB

Keywords:

reference evapotranspiration, irrigation programming, Hargreaves equation, water scarcity, adjustment coefficient

Abstract

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).

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Published

01-12-2018

Issue

Section

Natural resources and environment