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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.
H J; P A; M D; M T
Abstract
Evapotranspiration of orchard crops is often determined by indirect method and based on meteorological data due to the difficulties inherent in direct measurement instruments such as installation of large lysimeters or precision equipment, and long growing seasons of tree crops. Evapotranspiration estimation ...
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Evapotranspiration of orchard crops is often determined by indirect method and based on meteorological data due to the difficulties inherent in direct measurement instruments such as installation of large lysimeters or precision equipment, and long growing seasons of tree crops. Evapotranspiration estimation with sufficient accuracy is not feasible due to spatial variability of meteorological parameters and, sometimes, due to inappropriate distribution of meteorological stations. Therefore, using methods based on remote sensing, which account for these variations, is much more desirable. In this research, evapotranspiration of olive trees at different phonologic stages was measured using direct and indirect methods in Tarom district of Zanjan Province. In the direct method, actual evapotranspiration was determined by measuring moisture balance components, whilst in the indirect one, it was specified with the help of satellite imagery, the SEBAL algorithms, and Penman-Monteith equation. Olive crop coefficient was subsequently calculated and evaluated by determining reference crop evapotranspiration. The results indicated that evapotranspiration calculated by the remote sensing method at different stages of the growth had acceptable conformity with soil moisture balance data and evapotranspiration values obtained from the Penman–Monteith equation (the respective correlation coefficients were 0.95 and 0.88) and both evapotranspiration curves along the growing season had a similar increasing and decreasing trend. Moreover, crop coefficient obtained by the SEBAL algorithm and the water balance methods were well correlated (R2=0.86) and the remote sensing method with the aforementioned advantages can be used in predicting evapotranspiration.