The 2014 Mw 6.2 Ludian earthquake exhibited a structurally complex source rupture process and an unusual spatial distribution pattern of co-seismic landslides. In this study, we constructed a spatial database consisting of 1470 co-seismic landslides, each exceeding 500 m². These landslides covered a total area of 8.43 km² and were identified through a comprehensive interpretation of high-resolution satellite images taken before and after the earthquake. It is noteworthy that the co-seismic landslides do not exhibit a linear concentration along the seismogenic fault; instead, they predominantly extend along major river systems with an NE–SW trend. Moreover, the southwest-facing slopes have the highest landslide area ratio of 1.41. To evaluate the susceptibility of the Ludian earthquake-triggered landslides, we performed a random forest model that considered topographic factors (elevation, slope, aspect, distance to rivers), geological factors (lithology), and seismic factors (ground motion parameters, epicentral distance, distance to the seismogenic fault). Our analysis revealed that the distance to rivers and elevation were the primary factors influencing the spatial distribution of the Ludian earthquake-triggered landslides. When we considered the directional variation in ground motion parameters, the AUC of the model slightly decreased. However, incorporating this variation led to a significant reduction in the proportion of areas classified as “high” and “very high” landslide susceptibility. Moreover, SED^d emerged as the most effective ground motion parameter for interpreting the distribution of the co-seismic landslides when compared to PGA^d, PGV^d, and Ia^d.

The 2017 Jiuzhaigou earthquake, registering a magnitude of 7.0, triggered a series of devastating geohazards, including landslides, collapses, and mudslides within the Jiuzhaigou World Natural Heritage Site. These destructive events obliterated extensive tracts of vegetation, severely compromising carbon storage in the terrestrial ecosystems. Net Primary Productivity (NPP) reflects the capacity of vegetation to absorb carbon dioxide. Accurately assessing changes in NPP is crucial for unveiling the recovery of terrestrial ecosystem carbon storage after the earthquake. To this end, we designed this study using the Moderate Resolution Imaging Spectroradiometer (MODIS) Net Primary Productivity datasets. The findings are as follows. NPP in the co-seismic landslide areas remained stable between 525 and 575 g C/m² before the earthquake and decreased to 533 g C/m² after the earthquake. This decline continued, reaching 483 g C/m² due to extreme rainfall events in 2018, 2019, and 2020. Recovery commenced in 2021, and by 2022, NPP had rebounded to 544 g C/m². The study of NPP recovery rate revealed that, five years after the earthquake, only 18.88% of the co-seismic landslide areas exhibited an NPP exceeding the pre-earthquake state. However, 17.14% of these areas had an NPP recovery rate of less than 10%, indicating that recovery has barely begun in most areas. The factor detector revealed that temperature, precipitation, and elevation significantly influenced NPP recovery. Meanwhile, the interaction detector highlighted that lithology, slope, and aspect also played crucial roles when interacting with other factors. Therefore, the recovery of NPP is not determined by a single factor, but rather by the interactions among various factors. The ecosystem resilience study demonstrated that the current recovery of NPP primarily stems from the restoration of grassland ecosystems. Overall, while the potential for NPP recovery in co-seismic landslide areas is optimistic, it will require a considerable amount of time to return to the pre-earthquake state.

The erodibility and erosion resistance of Quaternary sediments play a pivotal role in both the hydrologic and erosion processes of soil cut slopes. To investigate the runoff and sediment yield of soil cut slopes along the Pai-Mo road, we performed indoor simulated rainfall experiments under a 50° steep slope and high rainfall intensity (120 mm/h), based on the area’s climatic characteristics and Quaternary sediment properties. The experiments included various rock fragment contents (30%, 40%, and 50%), different levels of rock fragment roundness (i.e., rounded gravel, angular gravel), and varying soil cohesion. The results indicated that the average infiltration rate of the uncemented rounded gravel soil slope (URGSS) was higher than that of the uncemented angular gravel soil slope (UAGSS), resulting in less runoff and a delayed initial runoff time. The runoff shear stress, runoff power, drag coefficient, and Reynolds number of the URGSS were smaller than those of the UAGSS. In contrast, the Froude number and flow velocity of the URGSS were larger, resulting in a stronger runoff erosion capacity. The sediment yield of the URGSS was approximately two times that of the UAGSS, and the cumulative sediment yield was about 20% higher. The cemented angular gravel soil slope (CAGSS) had a larger runoff rate, runoff shear stress, runoff power, and flow velocity than those of the UAGSS, leading to less sediment yield. Overall, a more rounded shape and a larger radius of curvature of the spherical particles resulted in stronger erosion, due to local turbulence. Therefore, the rill density and cumulative sediment yield of the steep alluvial cut slope were greater than that of the steep colluvial cut slope under heavy rainfall. Moreover, due to its strong cohesion, only raindrop splash erosion and inter-rill erosion occurred on the steep moraine cut slopes under heavy rainfall.