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<p>Accurate estimation of soil moisture in irrigated agriculture is essential for optimizing irrigation water management and scheduling decisions. Sentinel-1 offers a freely available, open-access radar dataset with 10&#xa0;m spatial resolution, making it highly suitable for estimating soil moisture in smallholder agricultural fields. The study aimed to evaluate the effectiveness of Sentinel-1&#xa0;C-band SAR imagery for soil moisture estimation and its application in optimizing wheat irrigation scheduling. During the 2024 irrigation season, a field study was conducted at the Mush and Cheki small-scale irrigation schemes in the North Shewa Zone, Ethiopia. Sentinel-1–derived soil moisture estimates were validated against gravimetric measurements obtained from 150 soil samples collected across both irrigation schemes. The results demonstrated strong agreement between satellite-derived and in situ soil moisture measurements. The coefficients of variation (CV) were 17% at Mush and 21% at Cheki, while percent bias (PBIAS) values were low, at 1.98% and 0.93%, respectively. High coefficients of determination (R<sup>2</sup>) of 0.75 at Mush and 0.82 at Cheki were obtained, along with satisfactory Nash–Sutcliffe Efficiency (NSE) values of 0.61 and 0.68, respectively. These performance metrics confirm the reliability of Sentinel-1 imagery for spatial soil moisture assessment. Furthermore, the integration of satellite-based soil moisture information into irrigation scheduling enhanced the precision of water application, improved water use efficiency, and contributed to more sustainable wheat production in water-scarce environments.</p>

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Evaluating sentinel-1 soil moisture imagery for irrigation management of wheat in small-scale irrigation schemes in North Shewa, Ethiopia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月23日

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  • Biruk Getaneh Ayele,
  • Tsegaye Getachew Mengistu,
  • Belihu Nigatu Gorfie,
  • Demisew Getu Zelelew,
  • Ayele Desalegn Woldemariam,
  • Hailu Kendie Addis

摘要

Accurate estimation of soil moisture in irrigated agriculture is essential for optimizing irrigation water management and scheduling decisions. Sentinel-1 offers a freely available, open-access radar dataset with 10 m spatial resolution, making it highly suitable for estimating soil moisture in smallholder agricultural fields. The study aimed to evaluate the effectiveness of Sentinel-1 C-band SAR imagery for soil moisture estimation and its application in optimizing wheat irrigation scheduling. During the 2024 irrigation season, a field study was conducted at the Mush and Cheki small-scale irrigation schemes in the North Shewa Zone, Ethiopia. Sentinel-1–derived soil moisture estimates were validated against gravimetric measurements obtained from 150 soil samples collected across both irrigation schemes. The results demonstrated strong agreement between satellite-derived and in situ soil moisture measurements. The coefficients of variation (CV) were 17% at Mush and 21% at Cheki, while percent bias (PBIAS) values were low, at 1.98% and 0.93%, respectively. High coefficients of determination (R2) of 0.75 at Mush and 0.82 at Cheki were obtained, along with satisfactory Nash–Sutcliffe Efficiency (NSE) values of 0.61 and 0.68, respectively. These performance metrics confirm the reliability of Sentinel-1 imagery for spatial soil moisture assessment. Furthermore, the integration of satellite-based soil moisture information into irrigation scheduling enhanced the precision of water application, improved water use efficiency, and contributed to more sustainable wheat production in water-scarce environments.