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Hossein Jafari; ali morshedi
Abstract
Estimation of crop water requirement and evapotranspiration by lysimeter is costly and time-consuming and could not be applied to larger field scale. Remote sensing technology can overcome this limitation. The goal of this research was to estimate alfalfa actual evapotranspiration using satellite imagery ...
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Estimation of crop water requirement and evapotranspiration by lysimeter is costly and time-consuming and could not be applied to larger field scale. Remote sensing technology can overcome this limitation. The goal of this research was to estimate alfalfa actual evapotranspiration using satellite imagery and compare it with the in-situ measurement by lysimeter. The study was carried out from 2017 to 2020 in the agricultural lands of Alborz and Charmahal and Bakhtiari provinces employing Surface Energy Balance Algorithm for Land (SEBAL) method. Lysimeter has been implemented under standard conditions. The cold pixels of each satellite image were extracted to estimate net alfalfa crop water requirement. In-situ net crop water requirement for Alborz and Charmahal and Bakhtiari provinces were obtained as 1383 and 1087 mm, respectively. The coefficients of determination (R2) were 73% and 76%, respectively, for the two studied provinces. The statistical analysis showed that there were small deviations from the mean values. The standard evapotranspiration measurements using lysimeter were higher than the satellite estimations. This technique can be useful for the estimation of crop water consumption since it is simple, cheap, fast, and can be used for large areas.
7
Ali Morshedi; Hossein Jafari; azhdar Onabi Milani
Abstract
The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat ...
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The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat during the growing seasons were calculated by two methods: a) using Landsat 8 satellite data through SEBAL, and b) using drained lysimeter data. Considering that evapotranspiration in SEBAL is in actual conditions and lysimeters provide evapotranspiration in potential conditions (standard situation without any limitation), to reduce errors, remote sensing data were used for pixels that had moisture conditions similar to standard lysimeters conditions. Comparison of actual evapotranspiration obtained from SEBAL and lysimeter in both sites showed relatively good correlation. The coefficients of determination (R2) were 0.73 and 0.65 in, respectively, Karaj and Tabriz sites. In addition, using statistical parameters such as NRMSE, RMSE, MAE, and MBE showed that SEBAL actual evapotranspiration data and lysimeteric data were, relatively, in agreement in the two study sites. However, in most cases, evapotranspiration values by SEBAL were greater than values measured by the lysimeter. In general, considering the advantages of the SEBAL, it is suggested this technology be used to estimate the actual evapotranspiration of wheat in large-scale areas.
A M
Abstract
Reference crop evapotranspiration (ETref) is measured directly (lysimetermethod) or estimated indirectly (mathematical models). In this study, dailyevapotranspiration (ET) was calculated by some mathematical models foralfalfa and was compared with ET data gathered daily from a drainagelysimeter during ...
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Reference crop evapotranspiration (ETref) is measured directly (lysimetermethod) or estimated indirectly (mathematical models). In this study, dailyevapotranspiration (ET) was calculated by some mathematical models foralfalfa and was compared with ET data gathered daily from a drainagelysimeter during six months. To evaluate and select the best model, ETdata values were compared using statistical criteria including R2, NRMSE,MAE, MBE, and d. Results showed that the best models in the daily timeframewere: Hargreaves-Samani (HS), Jensen-Haise (JH) and Turc. Forthe HS model, values of NRMSE and d were 0.126 and 0.930, and MAEwas 0.477 (mm.d-1), respectively. The best models for monthly time-framewere HS, American Society of Civil Engineering-Penman-Monteith(ASCE-PM), and Turc. Generally, HS model had the highest R2 values of0.985, 0.998 and 0.998 for daily and monthly periods, respectively, andASCE-PM had the lowest MBE compared to lysimeter data. To estimatetotal ET during the alfalfa growth period in the Shahrekord plain, resultsshowed that, models have over-estimated, except Turc and Priestley –Taylor models. ASCE-PM had the nearest ET (1161.7 mm) to lysimeterdata (1157.6 mm). In the national document of irrigation, the alfalfairrigation water requirement was reported at 649 mm (in the correspondingperiod), which is much less than the value measured.