Ameneh Miananadi; a a; Hossein Sanaeinejad; b gh; kamran davary
Abstract
The SEBAL algorithm is used to estimate spatial distribution of actual evapotranspiration using remote sensing imageries of MODIS or Landsat. Despite having a better spatial resolution than MODIS imageries (30 m instead of 1000 m), Landsat imageries do not have an appropriate temporal resolution (every ...
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The SEBAL algorithm is used to estimate spatial distribution of actual evapotranspiration using remote sensing imageries of MODIS or Landsat. Despite having a better spatial resolution than MODIS imageries (30 m instead of 1000 m), Landsat imageries do not have an appropriate temporal resolution (every 16 days instead of daily). On the other hand, the daily imageries of MODIS can be difficult to use under cloudy condition. Additionally, it is also a time-consuming process to interpret all the imageries. In this research, we chose the appropriate imageries from MODIS to be able to monitor the sudden weather changes as well as rainfall events and to reduce the interpretation time, while keeping the important information of the daily MODIS imageries in order to obtain the better actual evapotranspiration estimates. Due to the importance of hot and cold pixel selection, whose selection needs time and proficiency, we applied the automated method of hot and cold pixel selection (without user-intervention) using Landsat imageries. To integrate evapotranspiration over time, we used linear-logarithmic interpolation method in addition to linear interpolation method. The estimated actual evapotranspiration by SEBAL was compared to the estimated actual evapotranspiration from water balance equation and SWAT model for 3 years including a wet year (2004-2005), a normal year (2005-2006) and a dry year (2007-2008) in the Neishaboor-Rokh watershed. Furthermore, we used the Budyko framework to validate the evapotranspiration estimated by SEBAL and SWAT. The results showed that in comparison to SWAT, the linear-logarithmic interpolation method performed better than the linear method to estimate evapotranspiration. For linear-logarithmic method, RMSE, MBE, and MAE were 20.4, 0.09, and 18.4 mm year-1, respectively; and for the linear method, they were 21.8, -2.4, and 20.8 mm year-1, respectively. The results also demonstrated that the SEBAL algorithm with automated cold and hot pixel selection is able to have a good estimate of actual evapotranspiration at annual time scale and watershed scale. But, the algorithm does not perform well at HRUs and monthly scale in comparison to SWAT model. Results showed that by taking irrigation into account, evaporation estimated by SEBAL and SWAT follows the Budyko framework.
M Dastoorani; S. Poormohammadi; Mohammad Hassan Rahimian
Abstract
Reliable estimation of actual evapotranspiration of the plants plays an important role on planning and optimization of water use especially in dry land environments, where water scarcity is an important problem. In this study, Surface Energy Balance Algorithm for Land (SEBAL) was used for estimation ...
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Reliable estimation of actual evapotranspiration of the plants plays an important role on planning and optimization of water use especially in dry land environments, where water scarcity is an important problem. In this study, Surface Energy Balance Algorithm for Land (SEBAL) was used for estimation of actual evapotranspiration (ETa) in Ardakan pistachio orchards, Yazd province, Iran. For this purpose, a time series of satellite images including 13 cloud free MODIS data were employed to generate actual ET map of pistachio orchards. Results of this study indicated that seasonal ETa for pistachio trees was about 1150 mm, which was significantly less than the applied irrigation depth, Results of this study emphasize the necessity of a proper irrigation scheduling, irrigation interval, and depth in Ardakan pistachio orchards. Consequently, water productivity will improve and considerable amounts of water will be saved as the result of these improvements.
Mohammad Hassan Rahimian; s pourmohamadi
Abstract
Use of Surface Energy Balance Algorithm for Land (SEBAL) and satellite imagery is a relatively new procedure for estimation of actual ET at different scales e.g. farm, catchments and basin levels. This method is based on computation of latent heat flux as the residual of energy budget equation (LE=Rn-G-H) ...
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Use of Surface Energy Balance Algorithm for Land (SEBAL) and satellite imagery is a relatively new procedure for estimation of actual ET at different scales e.g. farm, catchments and basin levels. This method is based on computation of latent heat flux as the residual of energy budget equation (LE=Rn-G-H) and is now used widely around the world, including Iran, for computation of evapotranspiration under standard and non-standard conditions. Azadegan plain is one of the plains that is now faced with waterlogging and salinity problems due to its special topographic, climatic, and hydrologic situations and also due to improper management of its water and soil resources. The main objective of this study was to use the SEBAL to calculate actual ET (ETa) of winter wheat in 2007-2008 cropping season. For this purpose, a seasonal time series of 19 MODIS satellite images and also ancillary climatic data were acquired and used. Finally, time series of daily ETa maps and also a seasonal ETa map were generated and analyzed. Since the crops of the region are under salinity stress, the calculated ETa is an explanatory of crop water requirement under non-standard conditions. The results could help in advising a proper water management plan and also strategies for control and management of salinity and water logging in the region.