Unraveling rainfall-induced accelerated slope deformation through the integration of GNSS, seismic, and hydrologic data in Lantai, Taiwan

Abstract Studying deep-seated catastrophic landslides is challenging due to their complex geological conditions, slow and imperceptible movements, limited real-time monitoring, and difficulties in accurately assessing sliding behavior. We examine slope instability in a deep-seated landslide-prone area located in Lantai, Taiwan, by analyzing the temporal evolutions of slope movement and rainfall. Using a non-invasive automatic monitoring system that integrates the Global Navigation Satellite System, seismic velocity changes derived from ambient noise interferometry, as well as rainfall and groundwater-level records, we investigate rainfall-induced accelerated slope deformation in 2015–2024. Our findings show that acceleration events are triggered when rainfall lasts over 30 h and cumulative rainfall exceeds 200 mm at the study site. Multiple sliding events show a consistent temporal sequence, in which rainfall triggers an immediate dv/v decrease of 2–4%, followed by GNSS horizontal displacement typically in the range of ~10–30 mm within 1–2 days, and a delayed groundwater-level rise of about ~3 m occurring 4–5 days after peak GNSS displacement rate. This time lag suggests the initial slope acceleration is associated with pore-pressure increases within the landslide mass. The one-dimensional hydrological model successfully simulates rainfall infiltration into the groundwater system, enabling prediction of delayed groundwater responses. This integrated monitoring-modeling framework improves hazard assessment and early warning for rainfall-induced deep-seated landslides and is broadly applicable worldwide.