Mixed hydrometeorological processes explain regional landslide susceptibilities

During December 2022–January 2023, nine atmospheric rivers (ARs) struck California consecutively, causing catastrophic flooding and 600+ landslides. The extensive footprints of landslide-triggering storms and their diverse hydrometeorological forcings highlight the urgent need to incorporate regional-scale hydrometeorology into landslide research. Here, using a meteorologically-informed hydrologic model, we simulate the time-evolving water budget during the nine AR event and identify hydrometeorological conditions that contributed to widespread landslide occurrences across California. Our analysis reveals that 89% of observed landslides occurred under excessively wet conditions, driven by precipitation exceeding the capacities of infiltration, storage, evapotranspiration, and soil drainage. Using K-means clustering, we identify three distinct hydrometeorological pathways that increased landslide potential: intense precipitation-induced runoff (~32% of reported landslides), rain on pre-wetted soils (~53%), and snowmelt and soil ice thawing (~15%). Our findings highlight the importance of constraining the compounding factors that influence slope stability over spatial scales consistent with landslide-triggering weather systems.