Bouswir et al. (2025) Assessment of empirical and physically-based approaches to simulate surface resistance for improved evapotranspiration modeling of winter wheat in semi-arid region, Morocco

Identification

• Journal: Agricultural Water Management
• Year: 2025
• Date: 2025-12-12
• Authors: Zaineb Bouswir, Salah Er‐Raki, Jamal Ezzahar, Saïd Khabba, Abdelhakim Amazirh, Hazem Ahmed Mohammed Ahmed, Lamia Jallal, A. Chehbouni
• DOI: 10.1016/j.agwat.2025.110066

Research Groups

• AgroBiotech Center, Faculty of Sciences and Techniques, Cadi Ayyad University, Marrakesh, Morocco.
• Center for Remote Sensing Applications, Mohammed VI Polytechnic University (UM6P), Ben Guerir, Morocco.
• LMFE, National School of Applied Sciences, Safi, Morocco.
• LMFE, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco.
• TREMA International Joint Laboratory (UCA, Morocco and IRD, France).

Short Summary

The study evaluates two different methods for parameterizing surface resistance ($r_c$) in the Penman-Monteith model to improve evapotranspiration (ET) estimation for winter wheat in Morocco. It finds that while mechanistic models (Jarvis) excel under full irrigation, empirical models based on Land Surface Temperature (LST) are more effective at capturing rapid water stress dynamics under deficit irrigation.

Objective

• To compare the accuracy and operational relevance of a mechanistic approach (Jarvis model) versus an empirical approach (thermal stress index) for estimating surface resistance ($r_c$) and actual evapotranspiration (ET) in winter wheat under contrasting irrigation regimes.

Study Configuration

• Spatial Scale: Field scale (two 1.5 ha fields, F1 and F2) located in the Haouz plain, Tensift watershed, Morocco (31°25′36.4′′N, 8°39′05.9′′W).
• Temporal Scale: Two consecutive growing seasons (2016–2017 and 2017–2018).

Methodology and Data

• Models used:
  • Penman-Monteith (PM): The core model for ET estimation.
  • Mechanistic Approach: Jarvis model incorporating vapor pressure deficit (VPD) and soil water content ($\theta$).
  • Empirical Approach: Stress Index (SI) derived from the Vegetation Temperature Condition Index (VTCI) using Land Surface Temperature (LST).
• Data sources:
  • Eddy Covariance (EC): Used for direct measurement of latent heat flux and model calibration/validation.
  • Meteorological Station: Recorded solar radiation, air temperature, humidity, wind speed, and precipitation.
  • Sensors: Apogee IRTS-P infrared sensors (LST), TDR sensors (soil moisture), and hemispherical photography (LAI and cover fraction).

Main Results

• Mechanistic Performance: Reproduced ET dynamics well under full irrigation ($R^2 \ge 0.73$; RMSE < 0.6 mm/day) but systematically underestimated surface resistance and ET under severe water stress.
• Empirical Performance: Outperformed the mechanistic model under deficit irrigation ($R^2 \ge 0.79$; RMSE < 0.6 mm/day) due to the high sensitivity of LST to rapid stomatal closure.
• Irrigation Threshold: Identified a critical Stress Index (SI) threshold of 0.5, which serves as a practical indicator for triggering irrigation to prevent yield-limiting stress.
• Temporal Dynamics: The empirical approach showed better synchronization with ET peaks following rapid hydric events (irrigation/rainfall) compared to the mechanistic approach.

Contributions

• Provides the first systematic comparison of mechanistic versus LST-based empirical $r_c$ parameterization within the PM framework specifically for semi-arid winter wheat.
• Demonstrates that LST-based indicators are more robust for operational irrigation management in water-limited environments where soil moisture data may be sparse or slow to respond.
• Establishes a quantitative link between a remote-sensing-compatible stress index and optimal irrigation timing.

Funding

• TREMA International Joint Laboratory (University Cadi Ayyad and French Research Institute for Development).
• PRIMA projects: IDEWA and AQUEDUCT.
• RISE-H2020-ACCWA.
• Moroccan Ministry of Higher Education, Scientific Research and Innovation.
• OCP Foundation, UM6P, and CNRST (GEANTech research program).
• OCP Nutritrops S.A. (FIRMA project, grant agreement no: AS 140).
• CNRST-Morocco (PhD fellowship under the "PASS" program).

Citation

@article{Bouswir2025Assessment,
  author = {Bouswir, Zaineb and Er‐Raki, Salah and Ezzahar, Jamal and Khabba, Saïd and Amazirh, Abdelhakim and Ahmed, Hazem Ahmed Mohammed and Jallal, Lamia and Chehbouni, A.},
  title = {Assessment of empirical and physically-based approaches to simulate surface resistance for improved evapotranspiration modeling of winter wheat in semi-arid region, Morocco},
  journal = {Agricultural Water Management},
  year = {2025},
  doi = {10.1016/j.agwat.2025.110066},
  url = {https://doi.org/10.1016/j.agwat.2025.110066}
}

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