Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.

Geophysical methods like ground-penetrating radar (GPR) and electromagnetic induction (EMI) offer non-destructive, high-resolution alternatives for soil sampling. This study aims to understand subsurface stratifications in boreal podzolic soil employing an integrated GPR–EMI technique and soil sampling. The GPR and EMI confirmed each technique's findings. They provided insights into the spatial variability of electrical conductivity, textural changes, and stratification (detected mainly by GPR reflections) in the soil profile. The assessed soil properties revealed the existence of two contrasting layers within 0–0.60 m depth. The study highlights the potential of using integrated GPR–EMI to identify subsurface stratification in boreal podzolic soil.

An integrated GPR–EMI technique offers a fast, non-destructive, and cost-effective alternative for pore-water electrical conductivity estimation in agricultural fields.

Incorporating biochar (BC) as a soil amendment has become a prominent agricultural management practice since it has many advantages. Most soils amended with BC have shown improvements in soil physical and hydraulic properties, including bulk density, soil porosity, water retention, field capacity, and permanent wilting point. Ground-penetrating radar (GPR) is a non-destructive geophysical technique that is used to study soil properties and state variables. Yet, there is a lack of research studying the influence of amendments on soil hydrology using GPR. Therefore, this study was aimed at evaluating the ability of GPR in assessing the effect of BC on soil hydrology. The experiment was conducted under laboratory conditions using plastic containers measuring 28.6 cm in length, 20 cm in width and 16.4 cm in height. These plastic containers were filled up to 14 cm height with three different treatments (T); T1 (100% Sand+0% BC), T2 (99.5% Sand+0.5% BC), and T3 (98% Sand+2% BC) on a mass basis. Soil moisture sensors were placed horizontally at 2, 7, and 12 cm depths while packing the containers. The GPR data were collected using 1000 MHz center frequency transducers by keeping transmitter and receiver on opposite sides of the container (zero-offset profiling survey) at 20 cm antenna offset. Data were collected before, during, and after the wetting process over a one-hour timeframe. A 204 mL of water was applied every 4 min (13 times) to increase the soil water content at each time by 2% from initial water content. The GPR data were processed, and radargrams were prepared to observe the wetting front movement. Soil water contents were estimated utilizing the travel time of the GPR direct wave through the treatment media. GPR travel time and moisture sensor data were compared in each treatment. The GPR estimated soil water contents correlated well with moisture sensor data (correlation coefficient (r)>0.93) in all three treatments. Results have shown that the travel time of GPR direct wave responded differently for three treatments. The rate of change in GPR estimated soil water content over time exhibits an increase with the percentage of BC (T1