Understanding Delayed Landslides: A Study of 1,118 Fatal Incidents in China Influenced by Post-Precipitation Runoff

The common understanding of landslides points to intense precipitation as a primary trigger. However, this explanation falters when considering landslides occurring with minimal or no rainfall, challenging the basis of empirical and numerical analyses. Taking advantage of a dataset documenting 1,118 landslide disasters with casualties in China since 1984, this study incorporates field investigations, laboratory experiments, and numerical simulations to unravel the mechanisms behind the delayed initiation of landslides influenced by post-precipitation runoff and infiltration. A noteworthy finding emerges: over 75% of catastrophic landslides in China exhibit a temporal delay compared to triggering rainfalls, typically manifesting within one week following peak precipitation. The temporal dynamics of precipitation-induced landslide delays show a range from months to hours, with the delay positively correlated to both landslide scale and the severity of regional drought. Spatially, delayed landslides are frequently related to runoff recharge by upstream catchment, playing a pivotal role in the initiation process. Consideration of topography, climate, and human activities leads to the identification of four typical runoff recharge patterns. We use such patterns to investigate the relationships with the upstream catchment area and delay time, influenced by surface runoff migration and supplied runoff infiltration. Hydrological and slope stability calculations underscore the significance of the catchment area to landslide area ratio while delay time is predominantly governed by surface runoff migration and supplied runoff infiltration into the sliding soil. Results unveil a consistent sequence: robust runoff recharge facilitates water infiltration into weak rock fractures or soil mass, resulting in a gradual increase of pore water pressure. This sequence culminates in the delay of landslide initiation compared to the peak precipitation. These findings may contribute to a scientific foundation for early warning and prediction related to such landslides, thereby mitigating associated risks.