جستجوی مقالات مرتبط با کلیدواژه "الگوریتم sebal" در نشریات گروه "آب و خاک"

Accurate estimation of evapotranspiration plays an important role in quantification of water balance at awatershed, plain and regional scale. Moreover, it is important in terms ofmanaging water resources such as water allocation, irrigation management, and evaluating the effects of changing land use on water yields. Different methods are available for ET estimation including Bowen ratio energy balance systems, eddy correlation systems, weighing lysimeters.Water balance techniques offer powerful alternatives for measuring ET and other surface energy fluxes. In spite of the elegance, high accuracy and theoretical attractions of these techniques for measuring ET, their practical use over large areas might be limited. They can be very expensive for practical applications at regional scales under heterogeneous terrains composed of different agro-ecosystems. To overcome aforementioned limitations by use of satellite measurements are appropriate approach. The feasibility of using remotely sensed crop parameters in combination of agro-hydrological models has been investigated in recent studies. The aim of the present study was to determine evapotranspiration by two methods, remote sensing and soil, water, atmosphere, and plant (SWAP) model for wheat fields located in Neishabour plain. The output of SWAP has been validated by means of soil water content measurements. Furthermore, the actual evapotranspiration estimated by SWAP has been considered as the “reference” in the comparison between SEBAL energy balance models.
Surface Energy Balance Algorithm for Land (SEBAL) was used to estimate actual ET fluxes from Modis satellite images. SEBAL is a one-layer energy balance model that estimates latent heat flux and other energy balance components without information on soil, crop, and management practices. The near surface energy balance equation can be approximated as: Rn = G H λET
Where Rn: net radiation (Wm2); G: soil heat flux (Wm2); H: sensible heat flux (Wm2); and λET: latent heat flux (Wm2). Simulations were carried out by SWAP model for two different sites in Faroub and Soleimani fields. The SWAP is a physically based one-dimensional model which simulates vertical transport of water flow, solute transport, heat flow and crop growth at the field scale level. The period of simulation covered the whole wheat growing season (from 1st of December2008 to 30th of July2009. 16 MODIS images was used to determine evapotranspiration during wheat growing season. Inverse modeling of evapotranspiration (ET) fluxes was followed to calibrate the soil hydraulic. While SWAP model has the advantage of producing the right amount of irrigation and evapotranspiration at high temporal resolution, SEBAL can estimate crop variables like leaf area index, NDVI index, net radiation, Soil heat flux, Sensible heat flux and evapotranspiration athigh spatial resolution.
Actual and potential evapotranspiration were estimated for SWAP Model during the whole wheat growing season around669.5 and 1259.6 mm for Farub field and 583.7 and 1331.2 mm for Soleimani field, respectively. In contrast with NDVI and net radiation,spatial distribution of SEBAL parameters indicated that soil heat flux, sensible heat flux, and surface temperature of land have the same behavior. At the planting date, evapotranspiration was low and about 1 mm/day, but at the peak of plant growth, it was about 9 mm/day. Moreover, evapotranspiration declined at late growing season to about 3 mm/ day. SWAP model has been calibrated and validated with meteorological data and the data of field measurements of soil moisture. The amount of RMSE of 0.635 and 0.674 (mm/day) and MAE of 0.15 and 0.53 (mm/day) and also coefficient of determination (R2) of 0.915 and 0.964 obtained from comparison of SEBAL algorithm with SWAP model for Farub and Soleimani fields showed that no significant differences was seen between results of two models.
The present study supports the use of SEBAL as the most promising algorithm that requires minimum input data of ground based variables. Results of comparison of SEBAL and SWAP model showed that SEBAL can be a viable tool for generating evapotranspiration maps to assess and quantify spatiotemporal distribution of ET at large scales. Also, it feels that SEBAL and SWAP models can be applied in a wide variety of irrigation conditions without the need for extensive field surveys. This helps significantly in identifying performance indicators and water accounting procedures in irrigated agriculture, and to obtain their likely ranges.

Spatial estimation of evapotranspiration (ET) rates is essential for agriculture and water resources management. This study aimed to estimate ET v an ET estimation algorithm called Surface Energy Balance Algorithms for Land (SEBAL) and also by using TM June 2009 satellite data in Damaneh region of Isfahan province. To calculate the ET, all the energy balance components and related parameters including net radiation, surface albedo, incoming and emitting shortwave and longwave radiation, surface emissivity, soil heat flux, sensible heat flux, NDVI vegetation index, Leaf Area Index(LAI), and surface temperature were extracted from the geometrically and radiometrically corrected TM images. Results showed that ET rate was about 7.2 mm day-1 in agricultural areas, which was almost equal to 6.99 mm day-1 extracted from the FAO Penman-Monteith method in the synoptic weather station of Daran. Results here indicate that the extraction of ET rate which is almost equal to plant water requirements from remote sensing data can be used in selecting appropriate plants for agriculture and rehabilitation purposes in extensive arid and semi-arid regions of Isfahan province where severe droughts and water shortage are major problems.

Irrigation scheduling means applying the right amount of water at the right time. In this research, the current irrigation scheduling implemented in the Mirza-kuchak-khan Sugarcane Agro-Industry farms located in Ahwaz was compared with the actual sugarcane crop water requirement using SWAP model. Due to lack of field measured data, the SWAP model was calibrated and evaluated using LANDSAT 7 ETM+ images taken over the study area at twelve different dates during the sugarcane growing season. According to the results simulated by the SWAP model, the seasonal irrigation depth applied (2640 mm) was much more than that required by the crop and, as a result, a significant amount of irrigation water was wasted in the form of deep percolation. The water productivity was estimated to be 0.35 ton/ha.cm. In order to decrease deep percolation and improve water productivity, six irrigation plans including the possibility to reduce irrigation depth or eliminate some irrigation events, or change irrigation times were evaluated by the SWAP model. For every plan studied, an improved irrigation scheduling was suggested. According to the SWAP simulations, implementations of the suggested irrigation scheduling by eliminating some irrigation events or changing irrigation times can reduce seasonal irrigation depth by 27% and improve the water productivity by 30%. Reducing irrigation depth by 20% can also increase the water productivity by 26%. In case both scenarios mentioned can be applied together, the irrigation depth would decrease 42% and water productivity would increase 68%.

Estimation of evapotranspiration (ET) is essential for agricultural water resources management. Usually it is estimated indirectly based on (daily) weather data at the weather stations because of difficulties in its direct measurement. Considering the spatial variations of the weather parameters and subsequently of ET، application of the methods which can consider these variations are interested. Developed algorithms to estimate ET based on satellite images are among those interested methods. Surface Energy Balance Algorithm for Land (SEBAL); a remote sensing-based technique for estimation of evapotranspiration has been used in some regions in the world. The aims of the current study were 1) to test the accuracy of estimated ET based on SEBAL algorithm using LANDSAT5 TM images and 2) estimation of regional evapotranspiration over a plain. The study area was Mahidasht plain in Kermanshah، Iran. For this purpose، the ET of maize and regional ET was estimated based on four images of LANDSAT during the growing season of maize in the year 2010. Maximum difference between maize simulated ET and measured data was less than 10%.