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. The evapotranspiration-based scheduling method is the most common method for irrigation programming in agriculture. There is no doubt thatthe 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 bestperformance were the following three models: PMT CUH (Penman–Monteith temperature with calibration of Hargreaves empirical coefficient – kRS , average monthly value of wind speed, and average monthly value of maximum and minimum relative humidity), HS C (Hargreaves–Samani with calibration of  kRS ) and PMT OUH (Penman–Monteith temperature without calibration of  kRS , 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 ( kRS ). In the PMT CUH model, kRS 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 kRS was not calibrated. These results are very useful for adoptingappropriate measures for efficient water management, especially in theintensive agriculture in semi-arid zones, under the limitation ofagrometeorological data.

natural hazards and earth system sciences

Estimation of evapotranspiration by the Food and Agricultural Organization of the United Nations (FAO) Penman–Monteith temperature (PMT) and Hargreaves–Samani (HS) models under temporal and spatial criteria – a case study in Duero basin (Spain)