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<p>Precise assessment of actual evapotranspiration (AET) is significant for promoting efficient water resource management, particularly in rice-dominated agrosystems. This research utilizes the Surface Energy Balance Algorithm for Land (SEBAL) to evaluate AET from the rice fields of Odisha, India, relying on meteorological data and remote sensing data. The SEBAL approach calculates AET using energy balance components derived from Landsat 8 imagery, as well as ground-based meteorological datasets. The study analyzed the spatial and temporal variations in AET across four critical crop growth stages of the rice: initial, development, mid-season, and late season. The model quantified spatial and temporal variations in AET and related energy fluxes, highlighting the peak evapotranspiration during the mid-season stage, aligning with the crop’s maximum water demand. Net radiation and latent heat flux were found to be the primary drivers of AET, while sensible heat flux exhibited an inverse relationship. Spatial analysis revealed higher AET in central and eastern coastal zones, linked to denser canopy cover and favourable microclimatic conditions. The model demonstrated strong performance, with a low RMSE (0.965), MAE (0.27), and favourable agreement with FAO reference values (KGE = 0.735, R² = 0.79), indicating reliable and consistent estimation of crop coefficients. Overall, results suggest that the adopted energy balance model for the study is useful in managing the water resources in rice-based cropping systems to improve irrigation water use efficiency. This study illustrates the potential of integrating meteorological data and remote sensing to enhance the accuracy of evapotranspiration estimates and contribute to the capacity of policymakers and farmers to make informed water-use decisions.</p>

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Evaluation of Actual Evapotranspiration from Rice Fields of Odisha Using Remote Sensing Based Surface Energy Balance Approach

  • 期刊论文

  • 发表日期：

    2025年11月5日

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  • Kiran Bala Behura,
  • Sanjay Kumar Raul,
  • Jagadish Chandra Paul,
  • Sheelabhadra Mohanty,
  • Prachi Pratyasha Jena,
  • Sanat Kumar Dwibedi

摘要

Precise assessment of actual evapotranspiration (AET) is significant for promoting efficient water resource management, particularly in rice-dominated agrosystems. This research utilizes the Surface Energy Balance Algorithm for Land (SEBAL) to evaluate AET from the rice fields of Odisha, India, relying on meteorological data and remote sensing data. The SEBAL approach calculates AET using energy balance components derived from Landsat 8 imagery, as well as ground-based meteorological datasets. The study analyzed the spatial and temporal variations in AET across four critical crop growth stages of the rice: initial, development, mid-season, and late season. The model quantified spatial and temporal variations in AET and related energy fluxes, highlighting the peak evapotranspiration during the mid-season stage, aligning with the crop’s maximum water demand. Net radiation and latent heat flux were found to be the primary drivers of AET, while sensible heat flux exhibited an inverse relationship. Spatial analysis revealed higher AET in central and eastern coastal zones, linked to denser canopy cover and favourable microclimatic conditions. The model demonstrated strong performance, with a low RMSE (0.965), MAE (0.27), and favourable agreement with FAO reference values (KGE = 0.735, R² = 0.79), indicating reliable and consistent estimation of crop coefficients. Overall, results suggest that the adopted energy balance model for the study is useful in managing the water resources in rice-based cropping systems to improve irrigation water use efficiency. This study illustrates the potential of integrating meteorological data and remote sensing to enhance the accuracy of evapotranspiration estimates and contribute to the capacity of policymakers and farmers to make informed water-use decisions.