Bouswir et al. (2026) Irrigation optimization and assessment of deep percolation losses for winter wheat in a semi-arid using the SIMDualKc model

Identification

• Journal: BIO Web of Conferences
• Year: 2026
• Date: 2026-01-01
• Authors: Zaineb Bouswir, Salah Er-Raki, Saïd KHABBA, Jamal Ezzahar, Abdelghani Chehbouni
• DOI: 10.1051/bioconf/202621101024

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, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco.
• LMFE, National School of Applied Sciences, Cadi Ayyad University, Safi, Morocco.
• TREMA International Joint Laboratory (UCA/IRD).

Short Summary

This study utilizes the SIMDualKc model to quantify deep percolation losses in Moroccan winter wheat, demonstrating that optimized irrigation scheduling can reduce water consumption by up to 70% and drainage losses by over 90% compared to traditional farmer practices.

Objective

• To quantify water losses through deep percolation (DP) under different irrigation regimes and to optimize irrigation strategies for winter wheat in a semi-arid environment using the SIMDualKc model.

Study Configuration

• Spatial Scale: Two experimental plots (F1 and F2) of 1.5 ha each, located in the Haouz plain, 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: SIMDualKc (a soil water balance model based on the FAO-56 dual crop coefficient approach).
• Data sources:
  • Meteorological data (solar radiation, air temperature, humidity, wind speed, and precipitation) for Penman–Monteith reference evapotranspiration ($ETo$) calculations.
  • Eddy covariance systems for measuring actual crop evapotranspiration ($ETc$).
  • Time Domain Reflectometry (TDR) probes for soil moisture monitoring at depths ranging from 0.05 m to 0.50 m.
  • Downward-looking hemispherical photography for estimating the fraction of vegetation cover ($f_c$).

Main Results

• Farmer Practices: Traditional irrigation led to substantial deep percolation losses, ranging from 203 mm to 435 mm in fully irrigated plots and 120 mm to 207 mm in deficit-irrigated plots.
• Optimization: The SIMDualKc model reduced irrigation volumes by 45% to 70% compared to farmer-applied amounts.
• Loss Reduction: Optimized scheduling reduced deep percolation losses by an average of 88% (in some cases exceeding 90%), effectively eliminating unnecessary drainage.
• Crop Health: Despite significantly lower water application, the optimized strategy maintained the crop under non-stress conditions ($K_s = 1$) throughout the growing season.

Contributions

• Provides a detailed quantitative assessment of deep percolation, a critical but often unmeasured component of the soil water balance in semi-arid regions.
• Demonstrates the mismatch between traditional irrigation timing and crop phenological needs, specifically identifying over-irrigation during early growth stages as a primary cause of water waste.
• Validates the SIMDualKc model as a robust decision-support tool for improving water productivity and reducing environmental risks like nutrient leaching in North African wheat systems.

Funding

• TREMA International Joint Laboratory (funded by Cadi Ayyad University and the French Research Institute for Development).
• PRIMA-AQUEDUCT project.
• RISE-H2020-ACCWA project.
• GEANTech research program.
• CNRST-Morocco (PhD fellowship under the “PhD-Associate Scholarship – PASS” program).

Citation

@article{Bouswir2026Irrigation,
  author = {Bouswir, Zaineb and Er-Raki, Salah and KHABBA, Saïd and Ezzahar, Jamal and Chehbouni, Abdelghani},
  title = {Irrigation optimization and assessment of deep percolation losses for winter wheat in a semi-arid using the SIMDualKc model},
  journal = {BIO Web of Conferences},
  year = {2026},
  doi = {10.1051/bioconf/202621101024},
  url = {https://doi.org/10.1051/bioconf/202621101024}
}

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