1 4 0 m m d a y − 1, RMSE = 0.247 mm day −1) and FAO-56 Penman–Monteith model at Belgrade station (MAE = 0.208 mm day −1, RMSE = 0.277 mm day −1, R 2 = 0.975).Įvaluation of simple reference evapotranspiration (ETo) methods has received considerable attention in developing countries where the weather data needed to estimate ETo by the Penman–Monteith FAO 56 (PMF-56) model are often incomplete and/or not available. The best performances are achieved by Priestley–Taylor model at Nis s t a t i o n (R 2 = 0. RMSE is ranged between 0.247 and 0.485 mm day −1 at Nis station and between 0.277 and 0.451 mm day −1 at Belgrade station, while MAE is between 0.140 and 0.337 mm day −1 at Nis and between 0.208 and 0.360 mm day −1 at Belgrade station. The proposed tensor approach has a R 2 value of greater than 0.9 for all selected ET 0 methods at both selected stations, which is acceptable for the ET 0 prediction.
Models are compared with respect to coefficient of determination (R 2), mean absolute error (MAE), and root-mean-square error (RMSE). The suggested method is valuable as it takes into account simultaneous relations between elements, boosts the prediction precision, and determines latent associations. Afterward, the latent correlations among ET 0 parameters were found by the multiway analysis to enhance the quality of the prediction. Three-order tensor is used to capture three-way correlations among months, years, and ET 0 information. The FAO-56 Penman–Monteith, adjusted Hargreaves, Blaney–Criddle, Priestley–Taylor, and Jensen– Haise equations were utilized in this study for estimating ET 0 for two stations of Belgrade and Nis in Serbia using collected data for the period of 1980 to 2010. Thus, one of the main issues in ET 0 estimation is the appropriate integration of time information and different empirical ET 0 equations to determine ET 0 and boost the precision. Most of the available models for reference evapo-transpiration (ET 0) estimation are based upon only an empirical equation for ET 0.
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