High-resolution vertical profiles of groundwater electrical conductivity (EC) and chloride from direct-push EC logs

Elevated groundwater salinity associated with produced water, leaching from landfills or secondary salinity can degrade arable soils and potable water resources. Direct-push electrical conductivity (EC) profiling enables rapid, relatively inexpensive, high-resolution in-situ measurements of subsurface salinity, without requiring core collection or installation of groundwater wells. However, because the direct-push tool measures the bulk EC of both solid and liquid phases (EC_a), incorporation of EC_a data into regional or historical groundwater data sets requires the prediction of pore water EC (EC_w) or chloride (Cl⁻) concentrations from measured EC_a. Statistical linear regression and physically based models for predicting EC_w and Cl⁻ from EC_a profiles were tested on a brine plume in central Saskatchewan, Canada. A linear relationship between EC_a/EC_w and porosity was more accurate for predicting EC_w and Cl⁻ concentrations than a power-law relationship (Archie’s Law). Despite clay contents of up to 96%, the addition of terms to account for electrical conductance in the solid phase did not improve model predictions. In the absence of porosity data, statistical linear regression models adequately predicted EC_w and Cl⁻ concentrations from direct-push EC_a profiles (EC_w = 5.48 EC_a + 0.78, R ² = 0.87; Cl⁻ = 1,978 EC_a – 1,398, R ² = 0.73). These statistical models can be used to predict EC_w in the absence of lithologic data and will be particularly useful for initial site assessments. The more accurate linear physically based model can be used to predict EC_w and Cl⁻ as porosity data become available and the site-specific EC_w–Cl⁻ relationship is determined.