Landslides present a significant hazard for humans, but continuous landslide monitoring is not yet possible due to their unpredictability. In recent years, numerical simulation and seismic inversion methods have been used to provide valuable data for understanding the entire process of landslide movement. However, each method has shortcomings. Dynamic inversion based on long-period seismic signals gives the force–time history of a landslide using an empirical Green's function but lacks detailed flowing characteristics for the hazards. Numerical simulation can simulate the entire movement process, but results are strongly influenced by the choice of modeling parameters. Therefore, developing a method for combining those two techniques has become a focus for research in recent years. In this study, we develop such a protocol based on analysis of the 2018 Baige landslide in China. Seismic signal inversion results are used to constrain and optimize the numerical simulation. We apply the procedure to the Baige event and, combined with a field geological survey, show it provides a comprehensive and accurate method for dynamic process reconstruction. We found that the Baige landslide was triggered by detachment of the weathered layer, with severe top fault segmentation. The landslide process comprised four stages: initiation, main slip, blocking, and deposition. Multi-method mutual verification effectively reduces the inherent drawbacks of each method, and multi-method joint analysis improves the rationality and reliability of the results. The approach outlined in this study could help us to better understand the landslide dynamic process.

The catastrophic Wulong landslide occurred at 14:51 (Beijing time, UTC+8) on 5 June 2009, in Wulong Prefecture, Southwest China. This rockslide occurred in a complex topographic environment. Seismic signals generated by this event were recorded by the seismic network deployed in the surrounding area, and long-period signals were extracted from 8 broadband seismic stations within 250 km to obtain source time functions by inversion. The location of this event was simultaneously acquired using a stepwise refined grid search approach, with an error of ~2.2 km. The estimated source time functions reveal that, according to the movement parameters, this landslide could be divided into three stages with different movement directions, velocities, and increasing inertial forces. The sliding mass moved northward, northeastward and northward in the three stages, with average velocities of 6.5, 20.3, and 13.8 m/s, respectively. The maximum movement velocity of the mass reached 35 m/s before the end of the second stage. The basal friction coefficients were relatively small in the first stage and gradually increasing; large in the second stage, accompanied by the largest variability; and oscillating and gradually decreasing to a stable value, in the third stage. Analysis shows that the movement characteristics of these three stages are consistent with the topography of the sliding zone, corresponding to the northward initiation, eastward sliding after being stopped by the west wall, and northward debris flowing after collision with the east slope of the Tiejianggou valley. The maximum movement velocity of the sliding mass results from the largest height difference of the west slope of the Tiejianggou valley. The basal friction coefficients of the three stages represent the thin weak layer in the source zone, the dramatically varying topography of the west slope of the Tiejianggou valley, and characteristics of the debris flow along the Tiejianggou valley. Based on the above results, it is recognized that the inverted source time functions are consistent with the topography of the sliding zone. Special geological and topographic conditions can have a focusing effect on landslides and are key factors in inducing the major disasters, which may follow from them. This landslide was of an unusual nature, and it will be worthwhile to pursue research into its dynamic characteristics more deeply.

A catastrophic landslide struck the Xiaoba village in Fuquan, Guizhou, southwestern China at about 8:30 p.m. (Beijing Time, UTC + 8) on August 27, 2014. The landslide and induced impulse water waves destroyed two villages and killed 23 persons. By reprocessing seismic signals from a seismic network deployed in the surrounding area of the landslide, we recognized the event from low-frequency seismic signals and subsequently performed a long-period seismic waveform inversion to obtain its force–time history. The inversion results reveal that the maximum force for the landslide is 5 × 10⁹ N, and the duration of the landslide is 38.4 s. The landslide reached its maximum velocity of 12.4 m/s at 13.2 s after its initiation, and the mass center plugged into the quarry at 24.2 s. Based on the inversion results, we estimated basal friction of the landslide. We found the friction coefficient rapidly reduces to a relatively steady-state value of ~ 0.4 at a steady-state distance of 35 m and subsequently reduces in a near-linear manner that satisfies the empirical formula $$ \mu = - 1.4d + 0.44 $$μ=-1.4d+0.44 , where $$ d $$d is sliding distance in km. The reduction in friction revealed by the formula is compatible with the finding of previous studies for landslides of similar volume in landslide acceleration stage. However, our result does not make it possible for the friction coefficient to increase again in landslide deceleration stage that a velocity-dependent friction law would allow. The friction variation patterns can be used to constrain input parameters in numerical landslide simulation, which can predicate runout distance and deposit areas for massive landslides to carry out landslide hazard assessment.