Seismic landslide probabilistic assessment using Newmark displacement and remote-sensing: insights from 2017 Milin Ms 6.9 earthquake, eastern Himalayan Syntaxis

On November 18, 2017, a magnitude Ms 6.9 earthquake struck the Yarlung Tsangpo Grand Canyon area, Tibet Autonomous Region, China, with a focal depth of 10 km, and the area of the intensity VIII zone was about 310 km2, triggering thousands of coseismic landslides. The assessment of landslide hazard risks is of great significance for emergency response. To enhance the computational accuracy of the Newmark displacement model while preserving its simplicity, efficiency, and practical applicability. This paper proposes a refined landslide susceptibility assessment method that comprehensively considers geological and dynamic surface deformation information. According to the InSAR deformation monitoring results, the maximum deformation in the ascending track images exceeded 11 cm, and the maximum deformation in the descending track images exceeded 7 cm. Using InSAR to obtain the spatial distribution characteristics of surface deformation before and after the earthquake, we corrected the Newmark displacement results and found that the maximum displacement reached 28.86 cm, with the main deformation concentrated within about 17 km on both sides of the fault, consistent with the InSAR results. Based on the corrected model parameters, the probability of potential earthquake-induced landslides in the study area was calculated for four ground motion exceedance probabilities over 50 years: 63%, 10%, 2%, and 0.01%. Under the 0.01% exceedance probability, the area of extremely high-risk zones is 1040.05 km2, widely distributed on steep glacier slopes and slope areas along rivers and valleys, with a total area of potential landslides reaching 9695.89 km2.Under different exceedance probabilities, parts of the area near Gyala Peri Peak and Namjagbarwa remain in high-risk zones, and are prone to high-altitude remote geological hazards under strong earthquakes and extreme rainfall, requiring close attention. The results support the prediction and assessment of potential earthquake-induced landslide hazards in the region, as well as the rapid post-earthquake landslide evaluation.