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Agriculture

Improving Irrigation Water Management in Syria through Mathematical Modeling

Strategic Insights

— 1 min read

A new study published in Acta Agriculturae Slovenica has highlighted the potential of linear programming methodology in efficiently managing irrigation water for cropping patterns in Swaida Province, Syria. The research, conducted by the General Commission for Scientific Agricultural Research (GCSAR), targeted 106 farmers in the region between 2021-2022. The study's findings suggest that by adopting a proposed cropping pattern model, irrigation water usage could be reduced by 44.86%, from an estimated 5.9 million m3 to 3.25 million m3. The model also showed significant increases in crop yields for various crops, including peas, dry broad beans, and parsley.

Key Takeaways:

  • The study used a linear programming methodology to optimize irrigation water management for cropping patterns in Swaida Province, Syria.
  • The proposed cropping pattern model reduced irrigation water usage by 44.86%, from 5.9 million m3 to 3.25 million m3.
  • Crop yields increased significantly for various crops, including peas (691.96%), dry broad beans (656.21%), and parsley (398.72%).
  • The study recommended relying on correct scientific methodologies to prepare agricultural plans for cropping patterns and achieving self-sufficiency and preservation of available resources.
  • The research has implications for sustainable agriculture and water management in Syria and other regions with scarce water resources.
  • The study highlighted the importance of mathematical modeling in optimizing irrigation water management and improving crop yields.

Statistics:

  • Irrigation water usage: 5.9 million m3 (actual) vs. 3.25 million m3 (proposed).
  • Reduction in irrigation water usage: 44.86%.
  • Crop yield increases:

+ Peas: 691.96%.

+ Dry broad beans: 656.21%.

+ Parsley: 398.72%.

Sources:

  • Acta Agriculturae Slovenica
  • General Commission for Scientific Agricultural Research (GCSAR)
  • University of Ljubljana Press (Zalozba Univerze v Ljubljani)
  • DOI: https://doi.org/10.14720/aas.2025.121.3.16443
  • Maya Al-ABDALA, Socio Economic Directorate, General Commission for Scientific Agricultural Research (GCSAR), Syria
  • Safwan ABOASSAF, Afraa SALLOWM, additional authors
  • NewsRx LLC, October 30, 2025

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