Abstract
Accurate estimation of reference evapotranspiration is vital to hydrological and ecological processes. The FAO-56 Penman–Monteith (PM) model has the higher accuracy for ET0 estimation, but it requires many meteorological inputs that are not commonly available. Therefore an ideal method is needed requiring as minimal as possible input data variables without affecting the accuracy of estimation. The temperature-based models are especially interesting due to its input data, air temperature, can be monitored easily and is one of the commonly available climatic inputs. Among the temperature-based models, the Hargreaves (HG) model requiring maximum and minimum air temperature as the inputs is considered as one of the simplest and accurate ET0 methods, but this method needed a local calibration. The present study calibrated the HG model using Bayesian theory at 19 meteorological stations in Sichuan basin of southwest China. Meteorological data during 1961–1990 were used for the calibration and data during 1991–2014 were used for the validation. The results confirmed that the locally calibrated HG model (with average RRMSE, MAE and NS of 0.284, 0.433mm/d and 0.783) performed better than the original HG model (with average RRMSE, MAE and NS of 0.567, 0.959mm/d and 0.134). Both of the calibrated and original HG models overestimated ET0 at daily, monthly and annual timescale, but the calibrated HG model provided closer average values with PM ET0, which could confirm the good performances of the calibrated HG model. Therefore, the calibrated HG model could be highly recommended for estimating ET0 when only temperature data are available.
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