3,- 1National Research Institute of Rural Engineering, Water and Forests LR16 INRGREF02, Non-Conventional Water Valorization, University of Carthage, 17 rue Hédi Karray, B.P no. 10, Ariana 2080, Tunisia (dorsaf.allagui2@gmail.com)
- 2Department of Geology, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis 2092, Tunisia
- 3Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24–25, 14476 Potsdam-Golm, Germany (julien@geo.uni-potsdam.de)
The intensification of irrigation practices often leads to groundwater overexploitation, resulting in soil salinization in the short term and promoting deeper aquifer salinization in the long term. We consider a case study from Kairouan, central Tunisia, a region characterized by a semi-arid climate and severe water scarcity, to assess soil salinity dynamics under irrigated agriculture.
Soil salinity was monitored by combining two mono-channel frequency domain electromagnetic induction (EMI) sensors (EM31 and EM38) and operating them at different heights and orientations along profiles of 50 m length. The resulting multi-configuration FD-EMI profiles were inverted using pseudo-2D inversion approach based on laterally constrained 1D inversion (1D LCI).
The results reveal clear patterns about salinity distribution associated with different irrigation practices using brackish water, both in the short and long term. A systematic transfer of salinity from surface layers to greater depths was observed. However, salinity levels varied among crops, depending on irrigation frequency, applied water volumes and irrigation type (drip versus sprinkler). Seasonal conditions (wet versus dry periods) also show a strong control on salt redistribution.
This study demonstrates that the combined use of two EMI sensors provides an efficient and non-invasive tool for monitoring soil salinity in irrigated agricultural areas. Moreover, the inverse modeling of the EMI data enables a more accurate and quantitative assessment of soil salinity dynamics at different depths under contrasting irrigation systems.
Keywords: Soil salinity, hydrogeophysics, electromagnetic induction, inverse modeling.
How to cite: Allagui, D., Guillemoteau, J., and Hachicha, M.: Assessment of soil salinity using inverse modeling of multi-orientation and multi-elevation EMI data: a case of study from Tunisia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12343, https://doi.org/10.5194/egusphere-egu26-12343, 2026.
