Journal of Climate Research

Journal of Climate Research

Estimation of Actual Evapotranspiration Using Two Algorithms: Triangular and S-SEBI (Case Study: Mashhad Plain)

Document Type : Original Article

Authors
Mojdeh Salimifard 1
Seyed Hossein Sanaeinejad 2
Alireza Rashki 2
1 ferdowsi university
2 Ferdowsi University
10.22034/jcr.2025.519372.1695
Abstract
Introduction

Evapotranspiration is the largest component of water loss from the Earth’s land surface, accounting for the consumption of more than 80% of the annual available water in semi-arid environments. Evapotranspiration (ET) plays an important role in regional and global climates. ET computation is of prime importance in the evaluation of groundwater recharge, forecasting crop yield, land use planning, irrigation scheduling, streamflow estimation, regional water resource management, drought analyses, enhancing crop water productivity, and climate change variability. This study estimates evapotranspiration (ET) in arid and semi-arid regions, where water scarcity poses major agricultural challenges. Accurate water resource management is crucial for agricultural productivity, and precise ET estimation plays a key role. Remote sensing methods based on energy balance equations have become effective tools for large-scale ET estimation, offering advantages over direct methods like lysimeters and eddy covariance. A variety of remote sensing methods with varying complexity have been developed to generate regional AET estimates based on surface energy balance or vegetation status. The Triangular Algorithm and Simplified Surface Energy Balance Index (S-SEBI) are widely used for ET estimation in these areas. The Triangular Algorithm is especially useful for managing spatial variations in vegetation and surface temperature. This study aims to improve the spatial accuracy of ET estimation by using high-resolution satellite imagery.

Materials & Methods

The estimation of spatially variable actual evapotranspiration (AET) is a critical challenge to regional water resources management. In this study, two algorithms: the Triangle Method and the Simplified Surface Energy Balance Index (S-SEBI), were utilized to estimate actual evapotranspiration based on the triangular Ts/VI feature space. The commonly applied surface temperature–vegetation index (Ts–VI) triangle method is used to estimate regional evapotranspiration (ET) in arid and semi-arid regions. A practical algorithm based on the Ts–VI triangle method is developed to determine quantitatively the dry and wet edges of this triangle space. The triangle methods only require satellite images of vegetation indices (e.g., normalized difference vegetation index or NDVI) and land surface temperature (Ts). They can yet yield accuracies comparable to more complex methods. The Simplified Surface Energy Balance Index (S-SEBI) has been developed to solve the surface energy balance with remote sensing techniques on a pixel-by-pixel basis. The input data included Landsat 8 imagery of the Mashhad plain. After identifying the dry and wet edges in both algorithms and calculating the evaporative fraction (EF) and daily net radiation, actual evapotranspiration was estimated. The results of both algorithms were validated against standard reference evapotranspiration values for wheat and maize farms.

Result & discussion

First, the dry and wet edges were identified in both algorithms. Then, the corresponding regression equations for the dry and wet edges were derived. The correlation coefficient values associated with the dry edges regression equation were above 0.8 in the Triangular algorithm on all of the study days. The evaporative fraction (EF) values were calculated for the selected study dates. The results of the Triangle and S-SEBI algorithms were relatively similar. Both algorithms showed the highest actual evapotranspiration on August 11, 2020, and the lowest on September 16, 2020. Validation results indicated that the Triangle algorithm performed better than the S-SEBI algorithm over wheat farms. However, over the maize farm, both algorithms produced comparable results.

Conclusion

The results from the Triangle and S-SEBI algorithms applied to the Mashhad plain demonstrated that both methods effectively captured variations in evapotranspiration influenced by vegetation cover and soil moisture. Triangle and S-SEBI algorithms can effectively address the combined influence of terrain and water stress on AET estimates in semi-arid environments. The Triangle algorithm showed higher accuracy, particularly over wheat farms, achieving an R² value greater than 0.90. In contrast, the S-SEBI algorithm displayed increased uncertainty due to its sensitivity to detecting dry and wet edges. The result showed that the S-SEBI is a practical tool for estimating ET at the command scale using the remote sensing-based reflectance data under data-scarce conditions and diversified cropping systems. Both algorithms produced similar outcomes over the maize farm, likely because of the minimal crop residue left after harvest. Given their simplicity and lower data requirements, these algorithms are well-suited for arid regions with limited data availability. To enhance the accuracy of topographic zoning and high-resolution imagery is recommended.

Key words: Actual Evapotranspiration, Triangle algorithm, S-SEBI algorithm, Arid & Semi-arid areas.
Keywords
Actual Evapotranspiration
Triangle algorithm
S-SEBI algorithm
Arid &؛ Semi-arid areas
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Journal of Climate Research
Volume 1404, Issue 61 - Serial Number 61
Vol. 16 , No. 61, Spring 2025
Summer 2025
Pages 127-143