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<p>Accurate estimation of actual evapotranspiration (ET) is essential for irrigation management in semi-arid regions, yet it remains challenging due to sparse meteorological observations and strong spatial variability of water use. To address this issue, this study estimates actual evapotranspiration (ET) in the semi-arid Dashte Abbas Plain, Ilam Province, Iran, using remote sensing data and the Surface Energy Balance Algorithm for Land (SEBAL). Landsat 8 imagery was processed to derive daily ET during the 2021 wheat growing season, and model outputs were validated against the FAO-56 Penman–Monteith method, showing strong agreement (R² = 0.972, RMSE = 0.467&#xa0;mm/day). Seasonal ET dynamics corresponded closely with wheat phenology, peaking from late winter to mid-spring with daily values exceeding 4.0&#xa0;mm/day during critical growth stages. Average seasonal ET over cultivated lands was about 169&#xa0;mm, significantly higher than in rangelands and fallow areas. Irrigation requirement analysis revealed the greatest deficits between late February and April, when water demand reached critical levels. Spatial patterns indicated localized irrigation shortages of up to − 80&#xa0;mm in eastern and northeastern sectors, while small zones with negligible irrigation demand (&lt; 5&#xa0;mm) benefited from sufficient rainfall. These results highlight pronounced spatial and temporal variability in crop water requirements. Overall, the integration of SEBAL-derived ET with local weather and soil data provides a reliable framework for operational water monitoring, adaptive irrigation scheduling, and improved water-use efficiency. Such tools can support sustainable and climate-resilient agricultural practices in arid and semi-arid environments.</p>

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Remote sensing-based estimation of actual evapotranspiration using the SEBAL model: application to the Dashte Abbas Plain, Iran

  • 期刊论文

  • 发表日期：

    2026年4月20日

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  • Parisa Mirkhorli,
  • Hossein Mohammadnezhad,
  • Amir Ghaderi,
  • Maryam Shokri

摘要

Accurate estimation of actual evapotranspiration (ET) is essential for irrigation management in semi-arid regions, yet it remains challenging due to sparse meteorological observations and strong spatial variability of water use. To address this issue, this study estimates actual evapotranspiration (ET) in the semi-arid Dashte Abbas Plain, Ilam Province, Iran, using remote sensing data and the Surface Energy Balance Algorithm for Land (SEBAL). Landsat 8 imagery was processed to derive daily ET during the 2021 wheat growing season, and model outputs were validated against the FAO-56 Penman–Monteith method, showing strong agreement (R² = 0.972, RMSE = 0.467 mm/day). Seasonal ET dynamics corresponded closely with wheat phenology, peaking from late winter to mid-spring with daily values exceeding 4.0 mm/day during critical growth stages. Average seasonal ET over cultivated lands was about 169 mm, significantly higher than in rangelands and fallow areas. Irrigation requirement analysis revealed the greatest deficits between late February and April, when water demand reached critical levels. Spatial patterns indicated localized irrigation shortages of up to − 80 mm in eastern and northeastern sectors, while small zones with negligible irrigation demand (< 5 mm) benefited from sufficient rainfall. These results highlight pronounced spatial and temporal variability in crop water requirements. Overall, the integration of SEBAL-derived ET with local weather and soil data provides a reliable framework for operational water monitoring, adaptive irrigation scheduling, and improved water-use efficiency. Such tools can support sustainable and climate-resilient agricultural practices in arid and semi-arid environments.