To characterize the hypermobility mechanism of rock avalanches, a series of rotary shear tests at different shearing velocities (V_eq) ranging from 0.07 m/s to 1.31 m/s and at a normal stress of 1.47 MPa were carried out on soil sampled from the basal facies of the Yigong rock avalanche that occurred in the Tibetan plateau in China. Through conducting these tests, the macroscale and microscale features of the deformed samples were analyzed in detail with the following valuable conclusions being reached: (1) soil subjected to rotary shear exhibits a clear velocity‐dependent weakening characteristic with an apparent steady state friction of 0.13 being reached at V_eq ≥ 0.61 m/s, (2) high‐temperature rises and layers with high porosity were observed in the samples sheared at V_eq ≥ 0.61 m/s, and (3) the cooperation of thermal pressurization and moisture fluidization induced by friction heating plays an important role in explaining the marked frictional weakening of the soil. In addition, the appearance of nanoparticles due to particle fragmentation should facilitate the weakening of the soil but is not the key reason for the marked frictional weakening.

For the interpretation of the storm event-induced landslide distribution for an area, deterministic methods are frequently used, while a region's landslide susceptibility is commonly predicted via a statistical approach based upon multi-temporal landslide inventories and environmental factors. In this study we try to use an event-based landslide inventory, a set of environmental variables and a triggering factor to build a susceptibility model for a region which is solved using a multivariate statistical method. Data for shallow landslides triggered by the 2002 typhoon, Toraji, in central western Taiwan, are selected for training the susceptibility model. The maximum rainfall intensity of the storm event is found to be an effective triggering factor affecting the landslide distribution and this is used in the model. The model is built for the Kuohsing region and validated using data from the neighboring Tungshih area and a subsequent storm event – the 2004 typhoon, Mindulle, which affected both the Kuohsing and the Tungshih areas. The results show that we can accurately interpret the landslide distribution in the study area and predict the occurrence of landslides in the neighboring region in a subsequent typhoon event. The advantage of this statistical method is that neither hydrological data, strength data, failure depth, nor a long-period landslide inventory is needed as input.