Potential evapotranspiration is one of basic parameter in hydrologic cycle that should be estimate in irrigation design and scheduling, watershed hydrology studies. Many applications in diverse disciplines require estimates of evapotranspiration (ET) at hourly or smaller time steps. The primary objectives of this study were to compare the American Society of Civil Engineers (ASCE) and FAO-56 Penman–Monteith equations for hourly ET0 (ET0,hourly,ASCE and ET0, hourly,FAO) estimations for semiarid climate conditions and to compare the 24 h sum of ASCE (ET0,24 h,ASCE) and FAO-56 hourly ET0 (ET0,24 h,FAO) with the daily ET0 (ET0,d,FAO) computed from the daily FAO-56 equation, which is identical to ASCE daily ET0 equation. 278-days, i.e., 2008–2009 continuous hourly and daily weather data from the automated internet weather station where placed in private Farm in fariman khorasan razavi province were used. It was evident that during the day, ET0,hourly,ASCE was higher than ET0, hourly, FAO due to a lower surface resistance parameter value, while at night ET0, hourly,ASCE was lower than ET0, hourly,FAO due to a higher surface resistance parameter value. The ET0, hourly,FAO was about 18% less than ET0, hourly,ASCE and ET0,24 h,FAO was about 14% lower than ET0,24 h,ASCE. The difference between ET0, hourly,ASCE and ET0, hourly,FAO during the day and night was highly dependent on wind speed. For the entire year, ET0,24 h,FAO was 2.6% higher than ET0,d,FAO while ET0,24 h,ASCE was 17% higher than ET0,d,FAO. These results demonstrated that for applications that require hourly time steps or daily ET0 for the entire year, the use of ET0, hourly, FAO and ET0,24 h,FAO, respectively, will yield more consistent outcomes.

Potential Evapotranspiration (PET) is one of the important elements in hydrologic cycle which is required to be estimated in many fields such as irrigation، drainage and hydrological studies. This element represents potential losses from moist soil layer and vegetation cover. In this research different methods (Blaney-Criddle، Thorenthwaite، Penman and Hargreaves- Samani) are applied and then their results were compared with Fao Penman-Montieth method (as reference) and the best one is selected and suggested to estimate PET in Mazandaran province. The results show that the Blaney-Criddle has the lowest standard error and the highest correlation with the Fao Penman-Montieth method in the province. The results also show that the Blaney-Criddle method estimated PET about 5% lower than the reference method. Furthermore the results indicate that PET decreases from east to west of the province.

Saffron (Crocus sativus L.) is a subtropical plant mostly cultivated in South Khorasan and Khorasan Razavi provinces, Iran. Total saffron production is about 200 ton all over the world, and since it is native to Iran, the country has an important role to produce saffron. In recent years, drought showed a significant effect on water resources in Birjand, South Khorasan. Due to lack of full equipped meteorological stations and sufficient lysimetery studies, over irrigation and deficit irrigation are mostly common among saffron farmers. The cause of saffron yield decline is mostly related to irrigation. In addition, farmers need the simple equation/formula to determine the water demand, so, it is necessary to present a single and simple equation. Regarding to this purpose, this study was conducted to achieve mentioned goals: 1) determination of the best evapotranspiration equation, 2) comparison of saffron water need based on 12 most relevant evapotranspiration equations, and 3) determination a single-parameter model to rapidly and accurately estimate saffron water need based on gamma test (due to lack of all FAO-Penman-Monteith parameters in all Birjand’s meteorological stations).
This study was conducted using meteorological data collected from Birjand´s synoptic station during 1984-2014. This station is located at longitude 59˚ 21' E and latitude 32˚ 87' N and elevation 1491m. Twelve evapot ranspiration equations (Blaney-Criddle, Hargreaves, Turc, Priestley-Taylor, Thornthwaite, Jensen-Haise, Makkink, Modified Jensen-Haise, Irmak (Rn), Irmak (Rs), Lowry-Johnson, Pan-Class A) were evaluate to determine the best accurate one. To compare the 12 evapotranspiration equations results with FAO-Penman-Monteith equation (FAO56-PM), four statistical criteria (R2, MBE, RMSE and EF) were used. In order to comprise saffron water demand to actual water used, amount of irrigation water for saffron cultivation in Birjand plain was measured during 2014. In addition, saffron yield was recorded during this growing season in this region. In order to propose a single parameter and accurate model based on easily accessible meteorological parameters, gamma test was also employed.
Results of coefficient of determination (R2) were acceptable (>0.9) for all equations except Turk. The results showed that Blaney-Criddle, Modified Jensen-Haise and Hargreaves had better accuracy compared to other equations so that their root mean square errors (RMSE) were 0.572, 0.721 and 0.945 mm.d-1, respectively. In addition, saffron water requirement determined with FAO56-PM was equal to 2350 m3.ha-1.y-1. Hargreaves equation, with differences about -161.23 m3.ha-1.y-1 compared with FAO56-PM, was determined as a good equation. Measured irrigation water by saffron farmers was about 1184.17 m3.ha-1.y-1. According to the results it found that deficit irrigation was applied by saffron farmers. Saffron grow in arid regions, however, drought stress have a negative effect on its plant development and yield (Khorramdel et al., 2014; Khashei Siuki et al., 2015). Despite the lack of doing no test about the effect of deficit irrigation on saffron yield during 2014 in this region, it seems that deficit irrigation may be a reason of low saffron yield (SYASK, 2010) compared to average saffron yield in this region.
Results of gamma test revealed that temperature is a key parameter to develop a single model. In addition, results showed that the single parameter model based on temperature had better accuracy compared to above-twelve mentioned equation.
Hargreaves equation was only used the temperature (T) and extraterrestrial radiation (Ra) for estimating evapotranspiration. In addition, single parameter equation based on the mean temperature was only used one parameter (T) to estimate the evapotranspiration. Since both of the equations had an acceptable accuracy to use in this region, it is recommended to use them to determine saffron irrigation demand. It is due to lack of meteorological equipment for estimating all parameters in the plain.

Evapotranspiration is an important factor of hydrological cycle that must be estimated in irrigation and drainage projects. Studies have shown that in the absence of lysimeter, FAO Penman-Monteith method provide acceptable estimate of evapotranspiration values, but this method requires a lot of meteorological parameters. Therefore other hydrological evapotranspiration methods that needs few parameters should be evaluate for each region. In this study reference crop evapotranspiration calculated by Ref-ET software for Sepidan, Fars, by using Sepidan synoptic stations meteorological data during years 2004 to 2015. The results of methods compared with FAO Penman-Monteith standard method. The efficiency of all methods was evaluated using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) statistic parameters. The results showed that Methods based on Penman-Monteith (ASCE st PM, ASCE PM rs, ASCE PM), respectively, with the RMSE of about 0.03, 0.079, 0.079 and with the MAE of about, 0.021, 0.068, 0.069 appropriate methods for estimating reference evapotranspiration are considered. FAO 24Rd Pan and FAO Pan Methods, respectively, with the RMSE of about 1.426, 2.338 and with the MAE of about 1.186, 2.072 has the least compliance with the Penman-Monteith FAO method. So in situation of less data for FAO Penman-Monteith method in Sepidan, it is possible to use of other methods that needs few hydrological parameters.

Estimation of evapotranspiration is,one of the main components of the hydrological cycle, and is essential for irrigation scheduling, water balance, irrigation system design and management and crop yields simulation. Unlike conventional methods remote sensing estimates evapotranspiration in different spatial scales. Therefore, the aim of this study is to estimate evapotranspiration using OLI sensor images and SEBAL algorithm in the Dasht-e-Naz area, Sari, Iran. To evaluate the results, evapotranspiration estimated by the reference method, Penman-Monteith-FAO, was compared with SEBAL algorithm. Strong and significant correlation was obtained between these two methods (R2=0.93), Low error of estimation by SEBAL compared with reference method (RMSE=1.14) and low absolute difference between the SEBAL and Penman-Monteith-FAO (MAE=0.96) indicates that there is a good match between estimated values by SEBAL algorithm and Penman-Monteith-FAO standard method. This study showed that OLI sensor images and SEBAL algorithm could satisfactorily estimate actual evapotranspiration in the Dasht-e-Naz area, Sari.

Evaluation of evapotranspiration is one way to prevent water loss and water resource management. Therefore, in this study, an attempt has been made to calculate the actual evapotranspiration rate in the east of East Azerbaijan province using the SEBAL algorithm. For this purpose, first, based on two Landsat 8 satellite images dated 2017/08/22 and 2017/08/09, the values of Net radiation, soil heat flux, and sensible heat flux are estimated. Then, based on the difference, the amount of instantaneous heat flux was calculated and 24-hour evapotranspiration was obtained for each image. Finally, the amount was compared with the values obtained from the Penman-Monteith method. Also, for processing and analyzing images ENVI4.8 software was used. The results indicated that the amount of evapotranspiration in the Penman-Monteith and SEBAL method on 2017/08/22 was about 6.15 and 7 mm per day, and on 2018/08/09, respectively, about 7.38 for Penman-Monty and 7.94 mm per day for SEBAL. Overall, the amounts of SEBAL actual evapotranspiration and Penman-Monteith potential evapotranspiration have a mean absolute difference (MAD) 0.705 mm per day which indicates that the estimated values are consistent with the SEBAL algorithm and the Penman-Monteith method.

The recent research es indicate that irrigating with mean values of crop reference evapotranspiration (ETo) level will only provide about 50% of plant water demand. In such cases, irrigation level may not provide optimum water for plant and plant may face with water stress or water excess. With respect to the impact of ETo estimation methods, irrigation schedule period, and optimal probability level on plant water requirement, accurate evaluation of each case seems necessary to be studied. Using climatologies (1977-2006) of daily meteorological data, the daily ETo is estimated by means of five commonly used evapotranspiration methods (Blaney-Criddle, Penman, Penman-FAO24, Penman-Montieth and Penman-Montieth FAO-56). To evaluate the influence of each ETo models on actual plant water requirement, the daily evapotranspiration values were determined for wheat (ETc) during the period of study (1977-2006). The dates of starting and ending of maximum water requirement (MWR) were determined by means of moving average approach. Using the extracted dates, mean daily ETo values were plotted for different periods from one day to 30-days of MWR and different probability levels. The results indicated that if we apply the mean daily ETc values in designing irrigation systems (7-day period), at 50% probability level and Blaney-Criddle, Penman-Montieth FAO-56, Penman, Penman-FAO24 and Penman-Montieth ET0 methods, the water capacity of irrigation system will respectively be 12%, 10%, 18%, 14%, and 15% less than the corresponding values of 75% probability level. The statistical analysis of daily (ETc) data also showed that by increasing the MWR period, the estimated mean daily evapotranspiration would decrease. In addition, for a specific period, using higher probability level causes more crop water requirement values.