Leakage in urban shallow-buried non-metallic drainage pipelines changes the moisture distribution and dielectric properties of surrounding soil, producing diffuse and overlapping anomalies in GPR B-scan images that are difficult to quantify. This study proposes a GPR-based framework for leakage detection and extent estimation to support pipeline localization and excavation-oriented decision-making. Unsaturated seepage simulation, moisture-dielectric parameter conversion, and FDTD forward modeling were integrated to generate B-scan responses under different pipe diameters, leakage apertures, and development stages. An equivalent leakage radius was defined to characterize the leakage influence range, and a range regression head was embedded into the Detection Transformer framework to develop DETR-GP for joint prediction of pipe diameter category, anomaly location, and equivalent leakage radius. A multi-source dataset comprising 1,473 FDTD-generated images and 981 field-measured B-scan images was used, and the model outputs were mapped into GIS space. DETR-GP achieved an mAP(0.5) of 90.5% on the field test set for leakage anomaly detection. Because field samples lack physically measured radius labels, the equivalent leakage radius regression was quantitatively evaluated only on FDTD validation samples, yielding a mean absolute error of 0.071 m; field radius estimates are therefore interpreted as a simulation-referenced engineering indicator rather than a field-validated physical measurement. Sandbox experiments and a representative excavation case further supported the applicability of the method for rapid screening, field reinspection, and targeted excavation.
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Chen et al. (2026) studied this question.
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