Pore-water electrical conductivity assessment: an integrated ground-penetrating radar–electromagnetic induction approach

Abstract

Pore-water electrical conductivity (ECw) is the ideal indicator of soil salinity in agriculture, as it directly represents the salinity experienced by plant roots. However, its practical application is limited by its dependence on soil water content and the labour-intensive, destructive, costly, and time-consuming process of pore-water extraction and analysis, especially for large-scale field applications. Ground-penetrating radar (GPR) and electromagnetic induction (EMI) provide non-destructive, time-efficient, and cost-effective alternatives for estimating soil properties and state variables. This study aimed to develop a method for estimating ECw by integrating GPR and EMI techniques using both stochastic and deterministic approaches at the field scale. EMI and GPR surveys were conducted before and after controlled irrigations, and soil samples were collected for laboratory analysis as ground truthing. The stochastic approach involved developing multiple linear regression (MLR) models, whereas the deterministic approach involved modifying and evaluating Archie's equation. The MLR models demonstrated high predictive accuracy, with an R² of 0.75 between measured and predicted ECw values. Both approaches provided reliable ECw predictions, with low root mean square error (RMSE) during evaluation (<1.67 mS m⁻¹ for MLR and <2.65 mS m⁻¹ for Archie's equation). However, the parameters in Archie's equation deviated from laboratory-estimated values and required modifications. At the study site, the stochastic approach outperformed the deterministic approach. Future research should focus on refining these models to improve their applicability across different soil types and conditions, aiming to improve the accuracy and reliability of soil salinity assessments in various agricultural landscapes.