Time-Lapse Electromagnetic Conductivity Imaging for Soil Salinity Monitoring in Salt-Affected Agricultural Regions

Mohamed G. Eltarabily, Abdulrahman Amer, Mohammad Farzamian (), Fethi Bouksila, Mohamed Elkiki and Tarek Selim
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Mohamed G. Eltarabily: Civil Engineering Department, Faculty of Engineering, Port Said University, Port Said 42523, Egypt
Abdulrahman Amer: Civil Engineering Department, Faculty of Engineering, Port Said University, Port Said 42523, Egypt
Mohammad Farzamian: Instituto Nacional de Investigação Agrária e Veterinária (INIAV), 2780-157 Oeiras, Portugal
Fethi Bouksila: University of Carthage, National Institute for Research in Rural Engineering, Water, and Forestry (INRGREF), LR Valorization of Non-Conventional Waters (LR 16INRGREF02), BP10, Ariana 2080, Tunisia
Mohamed Elkiki: Civil Engineering Department, Faculty of Engineering, Port Said University, Port Said 42523, Egypt
Tarek Selim: Civil Engineering Department, Faculty of Engineering, Port Said University, Port Said 42523, Egypt

Land, 2024, vol. 13, issue 2, 1-21

Abstract: In this study, the temporal variation in soil salinity dynamics was monitored and analyzed using electromagnetic induction (EMI) in an agricultural area in Port Said, Egypt, which is at risk of soil salinization. To assess soil salinity, repeated soil apparent electrical conductivity (EC a ) measurements were taken using an electromagnetic conductivity meter (CMD2) and inverted (using a time-lapse inversion algorithm) to generate electromagnetic conductivity images (EMCIs), representing soil electrical conductivity (σ) distribution. This process involved converting EMCI data into salinity cross-sections using a site-specific calibration equation that correlates σ with the electrical conductivity of saturated soil paste extract (EC e ) for the collected soil samples. The study was performed from August 2021 to April 2023, involving six surveys during two agriculture seasons. The results demonstrated accurate prediction ability of soil salinity with an R 2 value of 0.81. The soil salinity cross-sections generated on different dates observed changes in the soil salinity distribution. These changes can be attributed to shifts in irrigation water salinity resulting from canal lining, winter rainfall events, and variations in groundwater salinity. This approach is effective for evaluating agricultural management strategies in irrigated areas where it is necessary to continuously track soil salinity to avoid soil fertility degradation and a decrease in agricultural production and farmers’ income.

Keywords: electromagnetic induction; soil salinity; inversion; monitoring (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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