Analyzing the Surface Energy Balance Algorithm for Land (SEBAL) in Estimating Crop Evapotranspiration

Document Type : Complete scientific research article

Author

Corresponding Author, Assistant Prof., Dept. of Water Science, University of Torbat-e Jam, Torbat-e Jam, Iran.

Abstract

Background and objectives: One of the key stages in water management involves accurately estimating water budget components. Proper estimations of the plant ET and water requirements of plants are very important for improving water management and increasing the water consumption efficiency. Although ground-based ET measurement methods provide high-accuracy point measurements, regional ET maps are needed for monitoring water resources. In this regard, satellite ET estimation models such as SEBAL can be useful. Of course, the efficiency of this model is different in various climates and crops. Therefore, The aim of this study is to calculate ET rates using the SEBAL model with Landsat 8 satellite imagery On the Google Earth Engine platform and assess the model's accuracy against FAO–Penman-Monteith method (ET0) and crop evapotranspiration (ETc).
Materials and methods: This study was conducted in Jangah area of Torbat-e Jam city located in Razavi Khorasan province, from 2013 to 2023. A Java program was developed using the provided equations in Google Earth Engine for this algorithm. Daily evapotranspiration images were acquired for the study area, and evapotranspiration data were extracted using QGIS software. The prediction performance of the SEBAL model against the reference ET0 and ETc was evaluated using widely accepted statistical indices such as the correlation coefficient (CC), relative bias (RBIAS), root mean squared error (RMSE), and mean absolute error (MAE).
Results: Results revealed a strong correlation between the model and ETc estimates (R²=0.85). The model slightly overestimated daily total ET values by only 0.016 mm (positive bias). Validation of the model against ETc indicated relatively minor errors, with daily mean absolute and root mean square errors of 0.76 mm and 0.97 mm, respectively.
Conclusion: The growing accessibility of open-access satellite data and advancements in remote sensing technologies are opening the door to systems capable of monitoring water usage by different stakeholders in near-real-time across various spatial scales. In this regard, satellite ET estimation models such as SEBAL can be useful. Of course, the efficiency of this model is different in various climates and crops. Based on the research findings, it was observed that the SEBAL method calculates actual evapotranspiration values with acceptable results. These results indicate that the use of this method can be suitable for the studied area. In summary, the findings indicate that the SEBAL algorithm is a suitable approach for estimating crop evapotranspiration and can serve as an effective tool for water resource management in farms, and other similar contexts.

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References

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Journal of Water and Soil Conservation
Volume 31, Issue 3
July 2024
Pages 155-175

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