The variability of soil properties in space and time is a challenge to their measurement. Currently, apparent electrical conductivity (ECa) of the soil profile can be used to estimate indirectly the spatial variability of the soil properties: salinity, texture, cation-exchange capacity and moisture content. An electromagnetic induction sensor does not require direct contact with the ground, and data collection is relatively easy, rapid, and inexpensive. This allows a larger number of

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... s and more comprehensive coverage of sites than is possible with traditional soil sampling methods. A quasi-2D electromagnetic conductivity model for a field site was developed using electrical conductivity (ECa) data measured by a multi-coil DUALEM-421 sensor and a DUALEM-1s sensor. Relationships of estimated ECa with volumetric water content (Θv) and cation exchange capacity (CEC) were reasonably accurate (R2 = 0.62 for DUALEM-421 and 0.58 for DUALEM-1s and R2 = 0.68 for DUALEM-421 and 0.58 for DUALEM-1s for Θv and CEC, respectively). These relationships were used to derive depth profile images. As expected, Θv, CEC and the estimated ECa follow similar trends down the soil profile. This soil ECa imaging method shows good potential for predicting 2D depth profiles of certain soil properties.