Enhanced visualization of rainfall infiltration in landslides using high-resolution 4-D noise-based velocity change imaging

SUMMARY Landslide disasters are typically triggered by various environmental factors, making it crucial to understand the interaction between subtle internal changes and these factors for accurate risk assessment. Noise-based velocity change measurement offers a promising tool, yet its widespread application is limited by the inherent instability of noise sources, constraining temporal resolution. Here, we employ an wave-packet-based nine-component spatial stacking approach with a dense seismic array deployed at the Xishan Village landslide. This advancement allows for the extraction of extraction of high temporal velocity change (20-min) at different frequencies, enabling 4-D dynamic analysis of landslide internal changes. Our findings reveal complex spatial distributions of velocity changes influenced by solar thermal radiation and rainfall at different locations and depths. Notably, during rainfall of approximately 20 mm, the observed maximum velocity reduction correlates closely with a fracture zone at ∼8 m depth, suggesting that pre-existing deformation structures significantly enhance local permeability, and promote the now deeper rainwater infiltration. This infiltration leads to increased pore pressure and velocity reduction. These results highlight the ambient noise method potential for urban landslide monitoring, providing technical support for early warning and risk assessment.