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 N; B GH; K D; A A; H D; A T
Abstract
In order to evaluate the role of a limited irrigation and agronomic management scenarios on improving yield and rain water productivity (WP) of rainfed wheat, a field study was conducted at multiple farms of Honam (Lorestan Province) in the upper Karkheh River Basin (KRB), Iran. The calibrated and validated ...
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In order to evaluate the role of a limited irrigation and agronomic management scenarios on improving yield and rain water productivity (WP) of rainfed wheat, a field study was conducted at multiple farms of Honam (Lorestan Province) in the upper Karkheh River Basin (KRB), Iran. The calibrated and validated AquaCrop model was used to define the best management scenario in order to enhance yield and WP of rainfed wheat in upper KRB in 2013-2014. In the next step, the best management scenarios were carried out in three research fields of rainfed wheat in 2014-2015. In field experiments, the treatments included two main management (traditional and advanced management) and two levels of limited irrigation (rainfed, single irrigation of 60 mm at spring time). According to the best scenario of AquaCrop model, spring single irrigation with constant depth of 60 mm was applied at three times (the first, middle and end of flowering period). The result shows that under rainfed conditions, by using the advanced management, rain water productivity of wheat increased by 36% as compared to traditional management. The results of this study showed that a single irrigation application at spring time (during flowering stage) increased the average total water productivity of wheat to 0.70 kg m-3, an increase of 74% as compared to the traditional management. The optimum program was obtained by a combination of advanced agronomic management package with single irrigation of 60 mm at the middle of flowering stage, which increased yield and WP of rainfed wheat to 176% and 134%, respectively, as compared to traditional management. Results of field experiments were in good agreement with the proposed scenarios by AquaCrop model.