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

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. Sentinel-1 C-band imagery accurately estimated soil moisture in small-scale irrigation schemes. Satellite-derived soil moisture improved irrigation scheduling precision, enhancing water use efficiency in water-scarce environments. This study demonstrates the practical applicability of Sentinel-1 data for sustainable wheat production, supporting evidence-based irrigation management at field scale.

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Publication Details

Journal
Discover Water
Published
2026-05-23
DOI
https://doi.org/10.1007/s43832-026-00396-1
Primary Topic
Soil Moisture and Remote Sensing
Type
article
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article

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

Ayele Desalegn Woldemariam, Belihu Nigatu Gorfie, Tsegaye Getachew Mengistu, Hailu Kendie Addis et al.
Discover Water
Soil Moisture and Remote Sensing
article

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

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

Abstract

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. Sentinel-1 C-band imagery accurately estimated soil moisture in small-scale irrigation schemes. Satellite-derived soil moisture improved irrigation scheduling precision, enhancing water use efficiency in water-scarce environments. This study demonstrates the practical applicability of Sentinel-1 data for sustainable wheat production, supporting evidence-based irrigation management at field scale.

Discover Water
Amhara Agricultural Research Institute (ET)
Zero hunger
Openalex Percentile: Top 8%
Soil Moisture and Remote Sensing
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