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<p>The Souss-Massa region in Morocco relies heavily on agriculture, but faces increasing water scarcity and declining groundwater reserves. This study evaluates a combined approach integrating electrical resistivity tomography and eddy covariance data to track soil moisture dynamics and diagnose inefficiencies in drip irrigation systems within an agribusiness citrus orchard in the region – a hub that accounts for 50–70% of Morocco’s citrus exports. Point-scale soil moisture sensors showed that soil moisture varies over time and at different depths with irrigation rates and rainfall events. In order to track the lateral and vertical moisture distribution, eleven electrical resistivity tomography profiles were implemented in the field using the Wenner array during the irrigation events. Consequently, two distinct layers were identified through the geoelectrical survey: a shallow unsaturated resistive layer (70–300 Ω·m) and a deeper saturated conductive layer (30–60 Ω·m). This investigation facilitated the distinction of well- and poorly-irrigated spots by highlighting an uneven water distribution and potential leakage. The quasi-3D resistivity renderings revealed the existence of subsurface storage zones and preferential flow pathways. These geophysical observations are in line with the agrometeorological trends observed by eddy covariance. Together, the findings reveal that electrical resistivity tomography combined with eddy covariance provides a robust, near real-time monitoring of irrigation performance, advancing precision agriculture and sustainable water management in semi-arid environments.</p>

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Enhancing drip irrigation efficiency in semi-arid citrus orchards using agrometeorological sensors and electrical resistivity tomography data

  • 期刊论文

  • 发表日期：

    2026年7月28日

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  • Hamza Ait-Ichou,
  • Mohammed Hssaisoune,
  • Ahmed Fadili,
  • Adnane Chakir,
  • Abdelwahed Chaaou,
  • Mohammed El Hafyani,
  • Asma Abou Ali,
  • Abdellaali Tairi,
  • Fatim-Zahra Ihbach,
  • Lhoussaine Bouchaou

摘要

The Souss-Massa region in Morocco relies heavily on agriculture, but faces increasing water scarcity and declining groundwater reserves. This study evaluates a combined approach integrating electrical resistivity tomography and eddy covariance data to track soil moisture dynamics and diagnose inefficiencies in drip irrigation systems within an agribusiness citrus orchard in the region – a hub that accounts for 50–70% of Morocco’s citrus exports. Point-scale soil moisture sensors showed that soil moisture varies over time and at different depths with irrigation rates and rainfall events. In order to track the lateral and vertical moisture distribution, eleven electrical resistivity tomography profiles were implemented in the field using the Wenner array during the irrigation events. Consequently, two distinct layers were identified through the geoelectrical survey: a shallow unsaturated resistive layer (70–300 Ω·m) and a deeper saturated conductive layer (30–60 Ω·m). This investigation facilitated the distinction of well- and poorly-irrigated spots by highlighting an uneven water distribution and potential leakage. The quasi-3D resistivity renderings revealed the existence of subsurface storage zones and preferential flow pathways. These geophysical observations are in line with the agrometeorological trends observed by eddy covariance. Together, the findings reveal that electrical resistivity tomography combined with eddy covariance provides a robust, near real-time monitoring of irrigation performance, advancing precision agriculture and sustainable water management in semi-arid environments.