Snowmelt-triggered reactivation of a loess landslide in Yili, Xinjiang, China: mode and mechanism

As the global climate warms, the frequency of soil slope failures induced by snowmelt is gradually increasing, especially loess landslide disasters in seasonally frozen areas. Landslide disasters in seasonally frozen areas pose a serious threat to human lives and engineering constructions and are gradually drawing greater public attention around the world. However, the mechanism that regulates deformation and failure processes, resulting in snowmelt-driven landslides, remains elusive. The Yili River Valley in Xinjiang, China, is an ideal location for exploring the mechanism of snowmelt-driven landslides. Based on detailed field surveys, remote sensing image identification, meteorological data analysis and loess characteristic tests, this paper takes a representative high-level loess landslide in north-west China as a case in order to explore its evolution history, movement process and resurrection mechanism. It was found that this loess slope had suffered two large-scale sliding failures and different degrees of inherited slope deformation had been found between the two slope failures. The 32 surface cracks identified have a total length of 3,505.10 m, and the total area of the landslide was found to be 135,462m 2 . The average thickness of the sliding body was about 30 m, and the volume was approximately 504,000 m 3 . The actual movement time lasted for 32 s with an average moving speed of about 15 m/s. Human grazing activities dominate the formation and development of slope surface cracks in the early stage. The strong water sensitivity of distinctive loess controls soil strength deterioration in the slip zone. Rapid snow removal and infiltration, driven by an abnormal temperature rise in Spring, is the most important triggering factor for slope deformation, evolution and failure. As regional grazing activities increase and global warming intensifies, the potential for resurrection landslides will increase. The results provide essential information for a comprehensive understanding of early warning systems and risk assessment for snowmelt-triggered landslides in cold areas.