Evolutionary characteristics and movement process of the January 2023 Duoxiongla snow avalanche, Tibet

Global warming has led to the frequent occurrence of snow avalanches that pose serious threats to the safety of personnel and projects in high-elevation mountain areas. Currently, the progress in research on snow avalanche dynamics is insufficient, and avalanche protection measures lack scientific guidance. To provide systematic guidance for snow avalanche protection in high-elevation projects, there is an urgent need to study the evolution and movement of avalanches. On January 17, 2023, a large snow avalanche occurred at the southward exit of the Duoxiongla tunnel. An analysis of the factors triggering this avalanche revealed that its occurrence was closely related to windy weather conditions and temperature rebound. On the basis of multiperiod high-definition remote sensing and unmanned aerial vehicle images (UAV), the characteristics of the mountain and historical avalanche events in Duoxiongla were revealed, and the normalized differential snow index (NDSI) was obtained to study the spatiotemporal change pattern of the annual snowpack cover. The remote sensing analysis results indicated that the slope of the release zone is gentle, with glaciers and cracks developing. The NDSI calculation results revealed that the snowpack cover range reached a maximum from January to February every year, and avalanches occurred frequently during this period. Additionally, in this study, avalanches were numerically simulated via the rapid mass movement simulation method (RAMMS), and the results reproduced the avalanche movement process, which can be divided into four stages: start-up, acceleration, deceleration and deposition. Moreover, two suitable locations for catching dams were identified on the basis of the movement and the maximum profile line of dynamic parameters, and the RAMMS method was employed to simulate avalanches after the implementation of protection. Finally, the dynamic mechanisms underlying the four stages were examined, the inadequacy of the RAMMS method for simulating avalanches was analyzed, and ideas for early identification and monitoring-derived warning of avalanches were proposed.