Complementary geophysical, geomorphometric and pedagogical approaches for characterizing shallow and deep subsurface materials in a colluvial‐alluvial plain in Atlantic rainforest

We evaluate the effectiveness of Ground Penetrating Radar (GPR), soil granulometry and geomorphometric analysis in identifying shallow variations of sandy and clayey materials in a colluvial‐alluvial plain. In addition, 2D Electrical Resistivity Tomography (2D ERT) was used to provide complementary information about deeper subsurface features, beyond the resolution limit of GPR. Geophysical methods were combined with unmanned aerial vehicle (UAV) data and particle size analysis to achieve high‐resolution detections of sediment variations in a colluvial‐alluvial plain. A Digital Terrain Model (DTM) was derived from remote sensing data, providing topographic attributes. Two pieces of equipment were tested for acquiring GPR images: one with a 400 MHz antenna and another with dual frequencies of 250 and 700 MHz. However, GPR data were acquired using a 400 MHz antenna along 16 transects, as it provided the best balance between resolution and electromagnetic (EM) wave penetration depth. The ERT data were collected along a single profile using the dipole–dipole array. Soil cores were sampled at 0.20 m intervals to a depth of 1 m to validate the geophysical interpretations. GPR images showed two distinct patterns: one towards the footslope (West sector) and another towards the lowland (East sector). The topographic attribute LS Factor, with a maximum value of 1.55, on the footslope in the West sector, represents colluvial ramps. Mean TWI (> 10) directly related to mean MrVBF (>2) illustrates areas with higher sediment deposition and moisture accumulation in the East sector. Principal Component Analysis (PCA) and Spearman's correlation demonstrated that the depth of soil core samples is positively correlated with sand (r = 0.26) and negatively correlated with clay (r = −0.18). GPR images revealed variations in sediment composition (horizontal resolution) at depths of up to approximately 4 m (vertical resolution). The GPR efficiently mapped strong returning signals from sandy lenses and weaker signals from clay, highlighting its potential for areas with similar geomorphology. The real resistivity model revealed a resistive surface layer across the entire line, corresponding to massive migmatite gneiss. The inclusion of geomorphometric data in geophysical analyses contributes to interpreting interactions between surface morphology, soil texture and geophysical properties. Our results encourage further on‐site research to characterize materials in terms of colluvial and alluvial origins.