Estimation of Actual Evapotranspiration Using the Remote Sensing Method and SEBAL Algorithm: A Case Study in Ein Khosh Plain, Iran
TL;DR: In this paper, the authors used remote sensing and the Surface Energy Balance Algorithm for Land (SEBAL) in the Ilam province, Iran Landsat 8 satellite images were used to calculate evapotranspiration (ET) during the cultivation and harvesting of wheat crops.
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Abstract: The aim of this study was to estimate evapotranspiration (ET) using remote sensing and the Surface Energy Balance Algorithm for Land (SEBAL) in the Ilam province, Iran Landsat 8 satellite images were used to calculate ET during the cultivation and harvesting of wheat crops The evaluation using SEBAL, along with the FAO-Penman–Monteith method, showed that SEBAL has a sufficient accuracy for estimating ET The values of the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), and correlation coefficient were 0466, 29%, 0222 mm/day, and 097, respectively Satellite images showed that rainfall, except for the last month of cultivation, provided the necessary water requirements and there was no requirement for the use of other water resources for irrigation, with the exception of late May and early June The maximum ET on the Ein Khosh Plain occurred in March The irrigation requirements showed that the Ein Khosh Plain in March, which witnessed the highest ET, did not experience any deficiency of rainfall that month However, during April and May, with maxima of 50 and 70 mm, respectively, water was needed for irrigation During the plant growth periods, the greatest and least amount of water required were 23123 and 1947 mm/hr, respectively
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Estimation of Actual Evapotranspiration along the Middle Rio Grande of New Mexico Using MODIS and Landsat Imagery with the METRIC Model
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Evaluation of SEBS, SEBAL, and METRIC models in estimation of the evaporation from the freshwater lakes (Case study: Amirkabir dam, Iran)
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