M. Kiani, M. Gheysari, B. Mostafazadeh-Fard, M. M. Majidi and E. Landi, , , , ,
Volume 18, Issue 67 (6-2014)
Abstract
The purpose of this study was to measure daily and seasonal evapotranspiration and daily crop coefficient of two common varieties of sunflower (Sirna and Euroflor) via drip-tape irrigation system. For this purpose, the sunflower water use was determined by daily monitoring of soil moisture at the depths of 10, 20, 30, 40 and 60 cm, and the crop evapotranspiration (ETC) was measured using volume balance method. According to the equation recommended by FAO, the obtained value of KC for Euroflor and Sirna varieties at the initial stage was 0.32. According to volume balance method, the Euroflor KC value for development, middle, and late stages were found to be 0.75, 1.18 and 0.9 and for Sirna were found to be 0.72, 1.15 and 0.84 respectively. Seasonal amount of evapotranspiration for Euroflor and Sirna varieties was equal to 601 and 575 mm, which was 26 and 30 percent less than seasonal ET0 in Isfahan. The average value of during the sunflower growing season was 0.77, which was greater than that offered by Doorenbose and Pruitt (0.55). As the crop coefficients of two varieties were different during the growing season and they were also different from FAO KC, measuring the actual amount of KC as a function of growing degree days can increase the accuracy of the estimated ETc and help develop the crop models in order to improve the irrigation management.
R. Ziaee, M. Moghaddasi, S. Paimozd, M. H. Bagher,
Volume 22, Issue 4 (3-2019)
Abstract
Evaporation is one of the important components in water body’s management, leading to changes in the water level and water balance. Also, its accurate estimation is faced with certain difficulties and complexities. Because of the limitations of physical and empirical methods based on the meteorological data, remote sensing technology can be widely used for evaporation calculation due to its capabilities for spatial data estimation and minimization of the meteorological data application. Many models have been developed to estimate evapotranspiration using remote sensing technology. Regarding the use of these algorithms for estimating evaporation from water surface, a few studies have been done; however, there is yet no comparison between them to estimate evaporation from the water surface. For this purpose, in this study, the output from two models estimating spatially distributed evaporation of water surfaces from remotely sensed imagery is compared. In order to implement these models, Terra/MODIS Images for four months including June, July, August and September in of 2006, 2007, 2008 and 2009 were prepared. Comparisons were made using pan data from Urmia synoptic station. In general, there was a reasonable agreement between the evaporation outputs from both models versus a pan data observation. The statistical analysis also showed that the SEBS algorithm (by applying the salinity factor), despite being simple in its implementation, has higher accuracy than the SEBAL algorithm.
M.j Amiri, M. Bahrami, M. Mousavi Poor, A. Shabani,
Volume 26, Issue 4 (3-2023)
Abstract
Class A pan evaporation method as one of the most common methods for reference evapotranspiration (ET0) estimation has been widely used in the world due to its simplicity, relatively low cost, and ability to estimate daily ET. In this study, the performance of 8 empirical methods consisting of Allen and Pruitt (1991), Cuenca (1989), Snyder (1992), modified Snyder, Pereira, et al. (1995), Orang (1998), Raghuwanshi and Wallender (1998), and FAO/56 were analyzed to estimate class A pan coefficient and ET0 at Fasa synoptic station located in Fars province. The calculated pan evaporation coefficients from the above equations were compared with measured pan evaporation coefficients which were obtained from the ratio of evapotranspiration calculated by the FAO-Penman-Monteith method to the rate of evaporation from the pan. The results showed that all empirical methods did not predict pan coefficient values well (R2 < 0.3 and NRMSE > 0.25). The comparison results between ET0 from empirical methods and ET0 obtained from FAO-Penman–Monteith indicated that the FAO/56 method had the best performance (R2 = 0.72 and NRMSE = 0.3). To increase the accuracy of empirical pan coefficient equations, these equations were modified with eight years (2007-2015) of meteorological data from the Fasa synoptic station and validated using two years of independent data (2015-2017). The results showed that the accuracy of all empirical models was improved and the Cuenca equation with NRMSE = 0.16 and R2= 0.63 was selected as the best equation for pan coefficient estimation and ET0 (R2 =0.85; NRMSE =0.18) in Fasa region. The sensitivity analysis revealed that the estimated pan coefficient is more sensitive to wind speed, followed by relative humidity, fetch distance, the slope of the saturation vapor pressure curve, sunshine hours, and air pressure. According to statistical results and sensitivity analysis, an equation was expanded for the Fasa region and other areas with the same climate.
