Elsadek et al. (2026) Comparing Cotton ET Data from a Satellite Platform, In Situ Sensor, and Soil Water Balance Method in Arizona

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Agriculture
• Year: 2026
• Authors: Elsayed Ahmed Elsadek, Said Attalah, Clinton F. Williams, Kelly R. Thorp, D. Wang, Diaa Eldin M. Elshikha
• DOI: 10.3390/agriculture16020228

Research Groups

• LI-COR Inc. (Lincoln, NE, USA)
• Research conducted in Gila Bend, Arizona, USA (Affiliations not explicitly listed in text, but context implies agricultural and environmental research institutions in the Southwest US).

Short Summary

This study evaluates the accuracy of six satellite-based OpenET models, their ensemble, and the LI-710 field-based system in estimating evapotranspiration (ET) for late-planted cotton in an arid environment. The results identify eeMETRIC, SIMS, SSEBop, the OpenET Ensemble, and the LI-710 as reliable tools for irrigation management, while other models significantly underestimated ET.

Objective

• To evaluate the performance of various simulated ET (ETSIM) models from the OpenET platform and the LI-710 field system against ground-truth soil water balance (SWB) measurements for cotton crops in an arid climate.

Study Configuration

• Spatial Scale: Field-scale study located in Gila Bend, Arizona, USA.
• Temporal Scale: Growing season from June to October 2025.

Methodology and Data

• Models used: ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, SSEBop, OpenET Ensemble, and the LI-710 field-based system.
• Data sources: Satellite-based imagery (via OpenET platform), field-based sensors (LI-710), and soil water balance (SWB) measurements used as the reference (ETSWB).
• Evaluation Metrics: Normalized root-mean-squared error (NRMSE), mean bias error (MBE), simulation error (Se), and coefficient of determination (R²).

Main Results

• Underperforming Models: ALEXI/DisALEXI, geeSEBAL, and PT-JPL substantially underestimated cotton ET, with simulation errors (Se) ranging from −26.92% to −20.57%.
• High-Performing Models: eeMETRIC, SIMS, SSEBop, and the Ensemble provided acceptable estimates with NRMSE between 22.57% and 29.85%, and Se between −7.58% and 3.42%.
• LI-710 Performance: The field-based system showed a slight tendency to overestimate daily ET by 0.21 mm/day but maintained a strong positive correlation with ETSWB (Se of 4.40% and NRMSE of 23.68%).
• Statistical Range: Acceptable models showed MBE between −0.36 mm/day and 0.16 mm/day and R² values between 0.57 and 0.74.

Contributions

• Provides a critical validation of the OpenET platform's accuracy for specific crop types (cotton) in arid and semi-arid regions.
• Identifies specific satellite-based models (eeMETRIC, SIMS, SSEBop) that can be used individually as reliable alternatives to ensemble averages.
• Demonstrates the field-level efficacy of the LI-710 system for real-time irrigation decision-making.

Funding

• Not specified in the provided text.

Citation

@article{Elsadek2026Comparing,
  author = {Elsadek, Elsayed Ahmed and Attalah, Said and Williams, Clinton F. and Thorp, Kelly R. and Wang, D. and Elshikha, Diaa Eldin M.},
  title = {Comparing Cotton ET Data from a Satellite Platform, In Situ Sensor, and Soil Water Balance Method in Arizona},
  journal = {Agriculture},
  year = {2026},
  doi = {10.3390/agriculture16020228},
  url = {https://doi.org/10.3390/agriculture16020228}
}

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