Exploring Electrical Resistivity Tomography ( <scp>ERT</scp> ) to Detect Soil Pipes: Theoretical Modeling and Field Experiments

ABSTRACT Soil erosion research remains critical for sustainable development as it impacts soil health through different erosive processes. Recent studies on soil piping highlight advancements in detecting surface features (using UAV); however, detecting underground pipes still remains challenging. This study aims to evaluate electrical resistivity tomography (ERT), a frequently used geophysical method, for detecting soil pipes. The study was based on field experiments conducted in the Bieszczady Mountains (the Carpathians, SE Poland) and theoretical modeling using Resistivity 2D modeling software. The results were compared with the existing research and confirmed by the trench. We evaluated various measurement settings, including array configurations (Wenner—W, Wenner‐Schlumberger—WS and dipole–dipole—DD), electrode spacing, and measurement orientation through the pipe system to determine their impact on detecting pipes regarding their size, shape, and depth. We performed six ERT profiles in the field, and we modeled the electrical response of a theoretical void at varying subsurface positions. In the theoretical modeling, we considered two scenarios with root‐mean‐squared errors (RMS) of 0% and 5%. The results confirmed that higher resistivity anomalies indicated pipes, with the DD configuration showing lower resistivity (105 Ωm) compared to W and WS configurations (268–427 Ωm). The comparison with other studies indicates that there is no universal threshold confirming soil pipe presence; instead, a clear electrical contrast with surroundings is crucial. Our findings suggest that while all tested configurations effectively detect pipes, their choice impacts image quality in the case of anomaly contrast and shape dependent on the sensitivity of the selected configuration. We recommend using the WS configuration for detecting both vertical and horizontal features. The number of anomalies influences RMS and should be critically evaluated during surveys. Our findings can assist researchers and practitioners in designing ERT studies in different environments.