Amini et al. (2025) Participatory evaluation of an irrigation decision support system for water-saving and productivity gains in Lake Urmia Basin

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-11-27
• Authors: Abdollah Amini, Somayeh Emami, Hossein Dehghanisanij
• DOI: 10.1038/s41598-025-26567-z

Research Groups

• Department of Water Engineering, Urmia University, Urmia, Iran
• Department of Water Engineering, University of Tabriz, Tabriz, Iran
• Agricultural Research, Education and Extension Organization, Agricultural Engineering Research Institute, Karaj, Alborz, Iran

Short Summary

This study evaluated a participatory irrigation decision support system (DSS) in the Lake Urmia Basin, demonstrating significant agricultural water savings (41% for drip, 14% for sprinkler) and improved water productivity across various irrigation systems under actual farm conditions.

Objective

• To evaluate an irrigation decision support system (DSS) for irrigation planning based on actual farm conditions and types of irrigation systems, with farmer participation, to achieve water-saving and productivity gains in the Lake Urmia Basin.

Study Configuration

• Spatial Scale: Eight farms across four villages (Tot Aghaj, Qom Qale, Yousef Kandi, Darlak) within the Mahabad Plain irrigation and drainage network, West Azerbaijan province, Iran. The total network area is approximately 12,000 hectares, at an altitude of 1320 meters above sea level.
• Temporal Scale: 2021–2022 crop year. The DSS utilized long-term climate data and short-term (seven-day) weather forecasts.

Methodology and Data

• Models used:
  • Irrigation Decision Support System (IrrigDSS)
  • FAO-56 Penman-Monteith method for reference evapotranspiration (ETo) estimation
  • ARIMA statistical model for short-term weather forecasting
  • Green-Amp model for soil infiltration
  • Stewart et al. (1977) equation for yield-transpiration relationship
  • FAO CROPWAT 8.0 for DSS validation
• Data sources:
  • Field measurements: Soil samples (0–30 cm and 30–60 cm depths), water flow rates (WSC flumes for surface irrigation, volumetric method for sprinkler and drip), crop yield.
  • Participatory Rural Appraisal (PRA) techniques: Semi-structured interviews, historical discussions, paired matrix method, before and after chart technique with farmers.
  • Virtual weather stations: Online meteorological data, historical climate data, and seven-day weather forecasts.
  • Laboratory analysis: Soil physical and chemical characteristics.

Main Results

• Water Savings: Optimized irrigation with DSS led to significant agricultural water savings compared to control plots: 41% for drip systems and 14% for sprinkler systems. In surface irrigation systems, water use slightly increased by 2.8% in some cases due to long water advance times, but overall system optimization is recommended.
• Water Productivity (WP) Improvement: Water productivity improved with DSS implementation across all systems: 3.87% in drip, 7.20% in sprinkler, and 1.5% in surface irrigation systems.
• Crop Yield: Crop yield increased in all irrigation systems in the treatment sections, with the highest increase observed in basin irrigation (e.g., sugar beet yield increased by 11.7 tonnes per hectare).
• Participatory Evaluation: Farmers prioritized reduced irrigation water consumption, increased crop yield, reduced energy consumption, reduced costs, and reduced time spent on the farm as key benefits. The DSS had the most significant impact on pressurized drip irrigation systems.
• DSS Validation: Seasonal irrigation depths predicted by the DSS showed an average difference of less than ±7% when compared with FAO CROPWAT 8.0, confirming its reliability.

Contributions

• Developed and evaluated a participatory irrigation decision support system (IrrigDSS) under real-world farm conditions in the Lake Urmia Basin, integrating farmer knowledge and feedback.
• Quantified significant water savings and water productivity improvements across diverse irrigation systems (drip, sprinkler, basin) through DSS implementation.
• Highlighted the critical role of social capital and stakeholder participation in the successful adoption and effectiveness of advanced irrigation technologies.
• Provided practical recommendations for optimizing traditional surface irrigation systems (e.g., reducing plot lengths) to enhance DSS efficiency and water distribution.

Funding

• Agricultural Engineering Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Alborz, Iran.
• Conservation of Iranian Wetlands Project (CIWP).
• "Modeling local community participation in Lake Urmia restoration via the establishment of sustainable agriculture."

Citation

@article{Amini2025Participatory,
  author = {Amini, Abdollah and Emami, Somayeh and Dehghanisanij, Hossein},
  title = {Participatory evaluation of an irrigation decision support system for water-saving and productivity gains in Lake Urmia Basin},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-26567-z},
  url = {https://doi.org/10.1038/s41598-025-26567-z}
}