Estimating effective rainfall using remote sensing and SEBAL energy balance algorithm and comparing it with experimental methods (case study: dry wheat cultivation plain of Khomein city).

Document Type : Research Paper


1 Department of Irrigation & Reclamation Engineering, Faculty of agriculture. College of Agriculture & Natural Resources. University of Tehran, Karaj, Iran

2 Assistant Prof., Department of Irrigation & Reclamation Engineering, Faculty of agriculture. College of Agriculture & Natural Resources. University of Tehran, Karaj, Iran



Considering the importance of water in the agricultural sector, it is necessary to know the usable and effective amount of precipitation. Therefore, in this research, using remote sensing and implementing the Surface Energy Balance Algorithm (SEBAL) on 28 images from Landsat 8 for the crop years 2014 to 2022 in During the growth period of dry wheat in fields of Khomein city, the rate of evapotranspiration and effective rainfall were estimated. The accuracy of SEBAL has been evaluated with Penman-Monteith and pan evaporation methods, and then the results obtained with experimental methods of effective rainfall estimation have been compared and their relative error (RE) has been estimated. The results showed that the USDA method with a RE of 12.2% had the lowest error and the FAO with a RE of 60% had the highest error compared to the SEBAL.


In order to make the best possible use of rainfall for the agricultural sector in rainfed lands, estimating the effective rainfall (ER) is vital. the ER is all spent on evapotranspiration and by accurately estimating the amount of evapotranspiration, the amount of ER can be achieved. Therefore, in this research, the amount of ER was estimated by estimating evapotranspiration using SEBAL in rainfed areas.

Materials and Methods

The study area of this research is the dry wheat cultivation plain located in Khomein city. the SEBAL was implemented on the available images from 2014 to 2022 crop years and evapotranspiration was estimated during the growth period in the desired crop years. Two methods of Penman and pan evaporation were used to verify the validity of SEBAL. In addition, a comparison was made between ER and experimental methods of estimating ER such as FAO, USDA, experimental and percentage, and the error of each experimental method was estimated.

Results and Discussion

Validation tests showed that the Penman method, with a lower RMSE, had a closer estimate compared to the pan evaporation method compared to the SEBAL. Among all the ER estimation methods, the SEBAL is The base method was chosen for comparison with other methods. Because, experimental methods have been developed based on the information collected for specific areas and also do not consider the distribution of ER in the spatial extent. The studies showed that the USDA with the RE of 12.20% has the lowest and the FAO with the RE of 60.07% has the highest error compared to the SEBAL.

The results of the comparisons showed that the experimental methods of estimating the ER are not universal and the generalization of these relationships in the field of agriculture to all regions are not error-free. be Therefore, these methods should be calibrated by taking into account factors affecting the amount of ER.


Main Subjects