Analysis of triggering conditions and dynamic evolution of the January 2024 snow avalanche in Kanas, Xinjiang, China using numerical simulation and multi-source data

Snow avalanches represent a major natural hazard in high-mountainous regions, especially under extreme weather conditions. On 11 January 2024, a large snow avalanche occurred in the Kanas region of Xinjiang, China, causing severe disruptions to local transportation and posing significant risks to life and infrastructure. To better understand its triggering mechanisms and dynamic behavior, this study integrates multi-source data, including UAV-derived high-resolution topography, meteorological records, and in-situ snowpack tests (ECT and STM). A mechanically weak snow layer was identified between 0.2 and 0.4 m depth, associated with strong temperature and density gradients, and further destabilized by rapid warming, intense snowfall, and fluctuating wind speeds. RAMMS::Avalanche was applied to simulate the full process of release, flow, and deposition. The simulation yielded a peak velocity of 29.1 m/s, impact pressure up to 219 kPa, and a deposition volume of 1.1 × 10⁵ m³, with a recall of 95.7% and precision of 81.9%. Field data confirmed weather-driven instability; simulations matched runout and deposits, showing observations and modeling are complementary for understanding avalanche dynamics. This study provides insights into snowpack–meteorological interactions in cold mountains. The results support RAMMS::Avalanche modeling applicability and contribute to risk assessment and early warning under climate change.