Afrasiabikia et al. (2026) A satellite-driven approach to estimating delivered irrigation water via SM-based inversion algorithm: A case study of the Doroodzan irrigation district, Iran

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Authors: Peyman Afrasiabikia, Atefeh Parvaresh Rizi, Luca Brocca
• DOI: 10.1016/j.agwat.2026.110141

Research Groups

• Irrigation and Reclamation Engineering Department, University of Tehran, Karaj, Iran.
• Research Institute for Geo-Hydrological Protection, National Research Council (CNR), Perugia, Italy.

Short Summary

This study utilizes a high-resolution (1 km) soil moisture-based inversion algorithm to estimate irrigation water use in the Doroodzan district, Iran. The findings reveal that actual irrigation efficiency (26–37%) is significantly lower than the 53% reported by local authorities, highlighting substantial conveyance and distribution losses.

Objective

• To evaluate the performance of a soil moisture (SM)-based inversion algorithm (derived from SM2RAIN) using high-resolution satellite data to quantify spatio-temporal irrigation water use (IWU).
• To identify operational inefficiencies and water losses within a large-scale irrigation network in a semi-arid region.

Study Configuration

• Spatial Scale: Regional/District scale (Doroodzan irrigation network, Fars Province, Iran), covering approximately 76,000 ha with a 1 km pixel resolution.
• Temporal Scale: September 2016 to May 2021, with primary IWU analysis focused on the 2018–2020 operational periods.

Methodology and Data

• Models used: SM-based inversion algorithm (an adaptation of the SM2RAIN algorithm) calibrated during non-irrigation periods to optimize drainage parameters ($a, b$), effective soil water storage ($Z$), and an evapotranspiration correction factor ($Kc$).
• Data sources:
  • Soil Moisture: NASA SMAP 1-km downscaled surface soil moisture (primary), compared against SMAP 9-km and ASCAT Soil Water Index (~11 km).
  • Precipitation: ERA5-Land reanalysis (~11 km resolution).
  • Evapotranspiration: GLEAM v4.1a Actual (ETc act) and Potential (ETp) evapotranspiration (~11 km resolution).
  • Validation: Canal release data from the Fars Regional Water Company and in-situ observations from the Zarghan and Mehrabad Ramjerd stations.

Main Results

• Algorithm Performance: The SMAP 1-km dataset outperformed coarser products. Calibration using actual evapotranspiration (ETc act) was superior to potential evapotranspiration (ETp), achieving a Nash-Sutcliffe Efficiency (NS) of 0.82 and a correlation coefficient (R) of 0.88.
• Quantitative IWU Estimates: The model accurately captured seasonal irrigation cycles and inter-annual dynamics. At a specific rain gauge pixel, validation showed R = 0.9742 and NS = 0.9347.
• Efficiency Discrepancy: Satellite-based conveyance and distribution efficiencies were calculated at 26% (2018), 36% (2019), and 37% (2020). These are significantly lower than the 53% efficiency factor officially reported by local authorities.
• Loss Identification: The results identified significant conveyance delays and water losses (seepage and evaporation), with spatial variability across the six construction units of the network.

Contributions

• High-Resolution Monitoring: Advances the application of SM-based inversion by integrating 1-km downscaled SMAP data, enabling the detection of sub-field scale irrigation signals and localized inefficiencies.
• Independent Validation Framework: Provides a method to independently verify official irrigation efficiency benchmarks using open-access satellite data, which is critical for regions with unmetered canals or sparse monitoring.
• Scalable Management Tool: Offers a cost-effective, near-real-time monitoring framework for water-scarce regions to support targeted infrastructure interventions (e.g., canal lining) and equitable water allocation.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Afrasiabikia2026satellitedriven,
  author = {Afrasiabikia, Peyman and Rizi, Atefeh Parvaresh and Brocca, Luca},
  title = {A satellite-driven approach to estimating delivered irrigation water via SM-based inversion algorithm: A case study of the Doroodzan irrigation district, Iran},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110141},
  url = {https://doi.org/10.1016/j.agwat.2026.110141}
}

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