Distribution Pattern of Coseismic Landslides Triggered by the 2017 Jiuzhaigou Ms 7.0 Earthquake of China: Control of Seismic Landslide Susceptibility

• Main Authors: Xiao-li Chen, Xin-jian Shan, Ming-ming Wang, Chun-guo Liu, Na-na Han
• Format: Article
• Language: English
• Published: MDPI AG 2020-03-01
• Series: ISPRS International Journal of Geo-Information
• Subjects: coseismic landslides; seismic landslide susceptibility; Newmark method; 2017 M_S 7.0 Jiuzhaigou earthquake; potential landslide area generation rate
• Online Access: https://www.mdpi.com/2220-9964/9/4/198

On 8 August 2017 an earthquake (<i>M_S</i>7.0) occurred within Jiuzhaigou County, Northern Aba Prefecture, Sichuan Province, China, triggering 4834 landslides with an individual area greater than 7.8 m² over a more than 400 km² region. Instead of correlating geological and topographic factors with the coseismic landslide distribution pattern, this study has attempted to reveal the control from seismic landslide susceptibility mapping, which relies on the calculation of critical acceleration values using a simplified Newmark block model. We calculated the average critical acceleration for each cell of the gridded study area (1 km×1 km), which represented the seismic landslide susceptibility of the cell. An index of the potential landslide area generation rate was defined, i.e., the possible landsliding area in each grid cell. In combination with <i>PGA</i> (peak ground acceleration) distribution, we calculated such indexes for each cell to predict the possible landslide hazard under seismic ground shaking. Results show that seismic landslide susceptibility plays an important role in determining the coseismic landslide pattern. The places with high seismic landslide susceptibility tends to host many landslides. Additionally, the areas with high potential landslide area generation rates have high real landslide occurrence rates, consistent with dominant small-medium scale landslides by this earthquake. This approach can aid assessment of seismic landslide hazards at a preliminary stage. Additionally, it forms a foundation for further research, such as the rapid evaluation of post-earthquake landslides and identifying highly impacted areas to help decision makers prioritize disaster relief efforts.