Bahare Bahman abadi; Abbas Kaviani; peyman daneshkar; Rasta Nazari
Abstract
Reference Evapotranspiration is a complex and multivariate phenomenon that depends on several factors and the most accurate way to estimate is lysimeter, though it is costly and time-consuming. Therefore, the main objective of this study was to estimate actual evapotranspiration based on single-source ...
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Reference Evapotranspiration is a complex and multivariate phenomenon that depends on several factors and the most accurate way to estimate is lysimeter, though it is costly and time-consuming. Therefore, the main objective of this study was to estimate actual evapotranspiration based on single-source energy balance, i.e. SEBAL and SSEB, and two-source energy balance algorithm, i.e. TSEB, in three sensors MODIS, ETM+ and OLI & TIRS in three steps. In evapotranspiration estimating by SEBAL, Soil Adjusted Vegetation Index and the correction factor for soil effects (L) are particularly important. For this purpose, this index was used as calibration coefficient that is selected based on percentage of vegetation coverage. According to the results, the actual evapotranspiration with L calibrated (L=0/5) had lower error in each of the three sensors (RMSE=1/76, 0/84, and 1/49 mm/day). For verification of calibration results, 30% of the remaining lysimeter data was used. The results of the statistical indices showed significant difference between the predicted data at the 95% level and also in the predictions. Finally, by comparing the three algorithms in the three sensors i.e. MODIS, ETM +, and OLI & TIRS, SSEB algorithm in ETM + sensor was introduced as the best algorithm in Qazvin plain area, at 95% significance level and RMSE of 0/41 mm/day.
r n; a k
Abstract
Increasing crop production depends on supplying crop water demands, thus, accurate estimation of crop water requirement helps not only to crop production, but also is effective in the management of water resources. Based on this, the purpose of the present research was to investigate the estimates of ...
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Increasing crop production depends on supplying crop water demands, thus, accurate estimation of crop water requirement helps not only to crop production, but also is effective in the management of water resources. Based on this, the purpose of the present research was to investigate the estimates of reference evapotranspiration from SEBAL and METRIC models using satellite imageries of Landsat 7 and 8 and Terra in the Qazvin plain. In the first step, the estimates of METRIC and SEBAL models with a total of 10 images obtained from MODIS sensor, Terra satellite, and ETM+ sensor, Landsat 7 satellite, were evaluated using lysimeter data for grass reference crop in 2001. Estimates of MODIS sensor with r =0.88, RMSE =1.91, and SE =0.85 mm/day and Landsat ETM + with r =1.00, RMSE =0.91, and SE=0.09 in METRIC model were closer to the lysimeter data compared with the SEBAL model. In the next step, the results of the METRIC and SEBAL models obtained from OLI & TIRS sensor images of Landsat 8 satellite were evaluated with the results of METRIC model on ETM+ due to lack of lysimeter data at the time of checking. Evaluation of the results indicate that the METRIC model with r=0.96, RMSE=0.28 and SE=0.29 mm/day may be recommended as a superior model compared with SEBAL model, for estimating reference crop evapotranspiration in the Qazvin plain.