Prediction of Soil Solution Electrical Conductivity by the Permittivity Corrected Linear Model Using a Dielectric Sensor

In the present study, the electrical conductivity of the soil solution (${\sigma }_p$) was predicted using a linear model in which the bulk soil electrical conductivity (${\sigma }_b$) effect on the apparent dielectric permittivity (${ϵ}_s$) was considered. The performance of the proposed model was evaluated by measurements with a dielectric sensor (the WET sensor) in four porous media at four different levels of electrical conductivity of the moistening KCl solution (${\sigma }_w$). It was found that the relationship between the square root of the permittivity (${ϵ}_s$) and soil volumetric water content ($\theta$) was dependent on soil type, which is consistent with the low operating frequency of the sensor. Establishing a soil specific ${\theta }_m–{\sqrt{ϵ}}_s$ relationship substantially increased the $\theta$ measurement accuracy compared to the factory calibration. It was shown that the new approach for the ${\sigma }_p$ prediction gave reasonably accurate results in sands irrespective of the ${\sigma }_p$ values. For the finer porous media, it improved the prediction of ${\sigma }_p$ only for the higher salinity levels, but the ${\sigma }_p$ values appear to be underestimated. The relationship between the corrected dielectric permittivity ${ϵ}_R$ and ${\sigma }_b$ is strongly linear for ${\sigma }_w$ and ${\sigma }_b$ values up to 6 and $1.7\mathrm{dS}·{\mathrm{m}}^{-1}$, respectively.