Heavy metal contamination poses significant environmental risks to groundwater and soil, necessitating efficient early-warning technologies for leakage detection. This study proposes a novel early-warning approach for heavy metal leakage using the self-potential (SP) method. A coupled numerical model integrating seepage, ion diffusion, and electric potential fields was developed within the COMSOL Multiphysics platform in order to elucidate the dynamic response mechanism of SP signals to advancing seepage fronts. Key findings reveal that the SP signal responds 1.5 h earlier than the contaminant diffusion front (Case 1), providing a critical early-warning window. The leakage process exhibits a distinct bipolar SP anomaly pattern (negative upstream/positive downstream), with the most significant response observed at the downstream toe area. Consequently, an optimized monitoring strategy prioritizing downstream deployment is proposed and validated using a representative landfill model. This SP-based technology offers a promising solution for real-time environmental risk monitoring, particularly in ecologically sensitive zones.

Slope landslide risk presents a critical challenge throughout high-speed railway construction and operation. Precise detection of sliding surfaces is essential for disaster prevention. This study develops an electrical detection method using complex electrode arrays, specifically addressing high-speed railway slope exploration constraints including confined spaces, significant investigation depths, and complex terrain. Numerical simulations analyzed the electric field distribution characteristics of power supply electrodes under various spatial constraints (half-space and full-space), revealing resolution differences between power supply combinations for target areas. Further comparative numerical modeling demonstrated that complex electrode arrays significantly enhance imaging quality over simple arrays in complex terrain. Finally, field validation confirmed the high reliability of complex observation systems for detecting slip surfaces along high-speed railway slopes. Therefore, under complex terrain conditions, utilizing complex observation systems to acquire multi-dimensional spatial data, integrated with topography-incorporated inversion technology, enables precise slip surface detection. This approach provides a reliable method for geological hazard mitigation in high-speed railway operations.