Ratshiedana et al. (2026) Evaluation of four remote sensing algorithms in estimating actual evapotranspiration in agricultural environments

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Identification

• Journal: Hydrology and earth system sciences
• Year: 2026
• Date: 2026-07-16
• Authors: Phathutshedzo Eugene Ratshiedana, Mohamed A. M. Abd Elbasit, Elhadi Adam, George Chirima
• DOI: 10.5194/hess-30-4383-2026

Research Groups

Not explicitly mentioned in the provided text, but the study focuses on agricultural water management in South Africa, suggesting involvement of research groups in hydrology, remote sensing, and agricultural science.

Short Summary

This study evaluated the variability and accuracy of four remote sensing-based actual evapotranspiration (ETa) algorithms across an irrigation scheme in South Africa, finding the Vegetation Index (VI)-based algorithm to be the most reliable and computationally efficient for supporting agricultural water management.

Objective

• To evaluate the variability of actual evapotranspiration (ETa) from farm level to irrigation scheme level in South Africa using remote sensing algorithms.
• To validate the accuracy of four remote sensing-based ETa algorithms (SEBAL, SEBS, VI-based ETa, CWSI-based ETa) against ground measurements (lysimeter and weather station extrapolation).

Study Configuration

• Spatial Scale: Farm level to an irrigation scheme, covering over 360,000,000 square meters (36,000 hectares).
• Temporal Scale: Three years (2019 to 2021), utilizing 22 Landsat 8 satellite images.

Methodology and Data

• Models used: Surface Energy Balance Algorithm for Land (SEBAL), Surface Energy Balance System (SEBS), Vegetation Index (VI)-based ETa, Crop Water Stress Index (CWSI)-based ETa.
• Data sources: Landsat 8 satellite images, smart field weighing lysimeter (for field-scale validation), weather-station-based extrapolation (for irrigation-scheme scale evaluation).

Main Results

• The VI-based algorithm demonstrated the best performance with a correlation coefficient (r) of 0.92, a coefficient of determination (R²) of 0.85, a Root Mean Square Error (RMSE) of 0.58 mm d⁻¹, and a Mean Absolute Error (MAE) of 0.44 mm d⁻¹.
• SEBAL was the second-best performing algorithm (r = 0.92, R² = 0.84, RMSE = 0.83 mm d⁻¹, MAE = 0.69 mm d⁻¹).
• The SEBS algorithm showed moderate performance, while the CWSI algorithm performed poorly.
• Uncertainty analysis indicated that extrapolated ETa estimates were reliable within ±7 % to ±12 %.

Contributions

• Provides a crucial validation of remote sensing-based ETa algorithms in South Africa, a region with significant data gaps for agricultural water management.
• Identifies the VI-based ETa algorithm as a reliable and computationally efficient alternative for accurate ETa estimation, particularly valuable in water-scarce environments.
• Demonstrates the potential of remote sensing algorithms to support irrigation scheduling, contributing to reduced water overuse.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Ratshiedana2026Evaluation,
  author = {Ratshiedana, Phathutshedzo Eugene and Elbasit, Mohamed A. M. Abd and Adam, Elhadi and Chirima, George},
  title = {Evaluation of four remote sensing algorithms in estimating actual evapotranspiration in agricultural environments},
  journal = {Hydrology and earth system sciences},
  year = {2026},
  doi = {10.5194/hess-30-4383-2026},
  url = {https://doi.org/10.5194/hess-30-4383-2026}
}