In this article, we developed a method to better understand how soil water moisture and salt content affect electrical signals measured from the surface by electromagnetic induction technique. This helps farmers manage irrigation, especially in areas using salty water. By combining field and lab data, we could tell how much each factor—water or salt—affected the signal. This technique offers a faster, easier way to track soil health and could improve how we use water in farming.

An automated electrical resistivity tomography (A-ERT) system was developed and deployed in Antarctica to monitor permafrost and active-layer dynamics. The A-ERT, coupled with an efficient processing workflow, demonstrated its capability to monitor real-time thaw depth progression, detect seasonal and surficial freezing–thawing events, and assess permafrost stability. Our study showcased the potential of A-ERT to contribute to global permafrost monitoring networks.

Soil hydraulic and hydrodispersive properties are necessary for modeling water and solute fluxes in agricultural and environmental systems. Despite the major efforts in developing methods (e.g., lab-based, pedotransfer functions), their characterization at applicative scales remains an imperative requirement. Thus, this paper proposes a noninvasive in situ method integrating electromagnetic induction and hydrological modeling to estimate soil hydraulic and transport properties at the plot scale.

The rapid decline of the Dead Sea level since the 1960s has provoked a dynamic reaction from the coastal groundwater system, with physical and chemical erosion creating subsurface voids and conduits. By combining remote sensing, geophysical methods, and numerical modelling at the Dead Sea’s eastern shore, we link groundwater flow patterns to the formation of surface stream channels, sinkholes and uvalas. Better understanding of this karst system will improve regional hazard assessment.

Soil salinity is a serious threat in numerous arid and semi-arid areas of the world. Given this threat, efficient field assessment methods are needed to monitor the dynamics of soil salinity in salt-affected lands efficiently. We demonstrate that rapid and non-invasive geophysical measurements modelled by advanced numerical analysis of the signals and coupled with hydrological modelling can provide valuable information to assess the spatio-temporal variability in soil salinity over large areas.