The evapotranspiration-based scheduling method is the most common method for irrigation programming in agriculture. There is no doubt that the estimation of the reference evapotranspiration (ET_o) is a key factor in irrigated agriculture. However, the high cost and maintenance of agrometeorological stations and high number of sensors required to estimate it make it non-plausible, especially in rural areas. For this reason, the estimation of ET_o using air temperature, in places where wind speed, solar radiation and air humidity data are not readily available, is particularly attractive. A daily data record of 49 stations distributed over Duero basin (Spain), for the period 2000–2018, was used for estimation of ET_o based on seven models against Penman–Monteith (PM) FAO 56 (FAO – Food and Agricultural Organization of the United Nations) from a temporal (annual or seasonal) and spatial perspective. Two Hargreaves–Samani (HS) models, with and without calibration, and five Penman–Monteith temperature (PMT) models were used in this study. The results show that the models' performance changes considerably, depending on whether the scale is annual or seasonal. The performance of the seven models was acceptable from an annual perspective (R²>0.91, NSE > 0.88, MAE < 0.52 and RMSE < 0.69 mm d⁻¹; NSE – Nash–Sutcliffe model efficiency; MAE – mean absolute error; RMSE – root-mean-square error). For winter, no model showed good performance. In the rest of the seasons, the models with the best performance were the following three models: PMT_CUH (Penman–Monteith temperature with calibration of Hargreaves empirical coefficient – k_RS, average monthly value of wind speed, and average monthly value of maximum and minimum relative humidity), HS_C (Hargreaves–Samani with calibration of k_RS) and PMT_OUH (Penman–Monteith temperature without calibration of k_RS, average monthly value of wind speed and average monthly value of maximum and minimum relative humidity). The HS_C model presents a calibration of the Hargreaves empirical coefficient (k_RS). In the PMT_CUH model, k_RS was calibrated and average monthly values were used for wind speed and maximum and minimum relative humidity. Finally, the PMT_OUH model is like the PMT_CUH model except that k_RS was not calibrated. These results are very useful for adopting appropriate measures for efficient water management, especially in the intensive agriculture in semi-arid zones, under the limitation of agrometeorological data.

The impact of climate change and its relation with evapotranspiration was evaluated in the Duero River Basin (Spain). The study shows possible future situations 50 yr from now from the reference evapotranspiration (ET_o). The maximum temperature (T_max), minimum temperature (T_min), dew point (T_d), wind speed (U) and net radiation (R_n) trends during the 1980–2009 period were obtained and extrapolated with the FAO-56 Penman-Montheith equation to estimate ET_o. Changes in stomatal resistance in response to increases in CO₂ were also considered. Four scenarios were done, taking the concentration of CO₂ and the period analyzed (annual or monthly) into consideration. The scenarios studied showed the changes in ET_o as a consequence of the annual and monthly trends in the variables T_max, T_min, T_d, U and R_n with current and future CO₂ concentrations (372 ppm and 550 ppm). The future ET_o showed increases between 118 mm (11 %) and 55 mm (5 %) with respect to the current situation of the river basin at 1042 mm. The months most affected by climate change are May, June, July, August and September, which also coincide with the maximum water needs of the basin's crops.

The evapotranspiration (ET _c) of a table grape vineyard (Vitis vinifera, cv. Red Globe) trained to a gable trellis under netting and black plastic mulching was determined under semiarid conditions in the central Ebro River Valley during 2007 and 2008. The netting was made of high-density polyethylene (pores of 12 mm²) and was placed just above the ground canopy about 2.2 m above soil surface. Black plastic mulching was used to minimize soil evaporation. The surface renewal method was used to obtain values of sensible heat flux (H) from high-frequency temperature readings. Later, latent heat flux (LE) values were obtained by solving the energy balance equation. For the May–October period, seasonal ET _c was about 843 mm in 2007 and 787 mm in 2008. The experimental weekly crop coefficients (K _cexp) fluctuated between 0.64 and 1.2. These values represent crop coefficients adjusted to take into account the reduction in ET _c caused by the netting and the black plastic mulching. Average K _cexp values during mid- and end-season stages were 0.79 and 0.98, respectively. End-season K _cexp was higher due to combination of factors related to the precipitation and low ET _o conditions that are typical in this region during fall. Estimated crop coefficients using the Allen et al. ( 1998 ) approach adjusting for the effects of the netting and black plastic mulching (K _cFAO) showed a good agreement with the experimental K _cexp values.

Estimation of reference evapotranspiration (${\mathrm{ET}}_{\mathrm{o}}$ ) using air temperature is particularly attractive for places where solar radiation, wind speed, and air humidity data are not readily available. In this study, seven temperature-based (TET) models and the standardized reference evapotranspiration equation for short canopies method were compared. Using only temperature data from the Yucatán Peninsula, México, the Food and Agriculture Organization of the United Nations (FAO)-Penman-Monteith (PMT) model was used to estimate ${\mathrm{ET}}_{\mathrm{o}}$ . Results from the temperature-based models are compared with FAO-56 daily ${\mathrm{ET}}_{\mathrm{o}}$ calculations using the Nash-Sutcliffe model efficiency coefficient (NSE), the coefficient of determination ($R^2$ ), mean absolute bias error (MAE), mean absolute percentage error (MAPE) and root mean square (RMSE). The results show that the noncalibrated PMT expression using temperatures alone produced the best results, with $\mathrm{RMSE}=0.7\mathrm{mm}{\mathrm{d}}^{-1}$ . The Hargreaves-Samani calibrated ($\mathrm{RMSE}=0.74\mathrm{mm}·{\mathrm{d}}^{-1}$ ) and Camargo calibrated ($\mathrm{RMSE}=0.78$ ) models exhibited the next best performance. RMSE values were as high as $1.56\mathrm{mm}·{\mathrm{d}}^{-1}$ for the other models.