Generalized calibration of the Hargreaves equation for evapotranspiration under different climate conditions

Abstract

Accurate estimation of evapotranspiration (ETo) is a key factor in weather-based irrigation scheduling methods. To estimate ETo using the Hargreaves equation, just the data on the minimum and maximum temperature and solar radiation are required. However, this procedure cannot offer consistent accuracy for different climate conditions. To attain the accuracy, calibration of the equation constants (C_Hand E_H) for different climate conditions have successfully been attempted by many researchers. Because these calibration procedures are lengthy and location-specific, there is a need of a generalized calibration method to make the Hargreaves equation more pertinent and effective. In this paper, fuzzy logic based calibration method for the Hargreaves equation is proposed and validated. The fuzzy inference system is developed to compute appropriate values of the constants C_Hand E_H on the basis of past data on humidity and wind velocity of a selected location. The underlying relationship between weather conditions and the best values of the constants C_Hand E_H are used to establish a fuzzy rule base. The performance of the method is checked at eight geographically different locations of India with diverse climate conditions. The Mean Absolute Error (MAE) in ETovalues estimated by the calibrated modified Hargreaves equation and the Penman-Monteith (PM) equation is in the range of 0.3220–1.0325. It is far more lower than if the error is calculated using the original Hargreaves equation. It confirms the correctness of the calibration method for different climate conditions.