Exploratory relationships between selected ground motion parameters and coseismic landslides: A case study of the 2017 Jiuzhaigou MW6.5 earthquake

Ground motion is widely recognized as a fundamental factor in triggering coseismic landslides; however, in regional-scale analyses, it is still commonly represented by a single scalar indicator (i.e. the Peak Ground Acceleration, PGA), which limits an in-depth understanding of landslide hazards. Considering the 2017 Jiuzhaigou M_W 6.5 earthquake and its documented coseismic landslides as a case study, we investigate the relationship between coseismic landslides and the spatial variability of ground motion, as derived by physics- and scenario-based Neo-deterministic Seismic Hazard Assessment (NDSHA). A total of 84 peak ground motion metrics, including PGA, PGV, and PGD across different directional components and frequency bands, are computed and systematically correlated with multiple landslide characteristic parameters. The results show that (i) ground motion components in the radial and north–south directions exhibit the strongest correlation with landslide parameters; (ii) low-frequency ground motion metrics are predominantly and positively associated with landslide point density, area density, and total landslide area, whereas high-frequency metrics are more closely linked to landslide mobility; (iii) PGA- and PGD-related parameters generally outperform PGV in terms of correlation strength across all four landslide descriptors; and (iv) incorporating multiple peak ground motion parameters improves coseismic landslide susceptibility prediction by up to 8.4% compared with the commonly used USGS PGA ShakeMap. The obtained results demonstrate that no single ground motion parameter can fully capture the landslides pattern, and different ground motion parameters should be used for different landslide parameters to improve the accuracy and applicability of the regional coseismic landslide assessment.