The characteristics of the seismic signals induced by landslides using a coupling of discrete element and finite difference methods

Landslide seismic signals support researchers to estimate magnitudes and locations of landslides. They can serve as a crucial data for landslide warning systems. However, the randomness of landslide locations makes the acquisition of landslide-induced seismic signals difficult and limits the number of available field data. The objectives of this study are to establish a numerical modeling approach to examine the characteristics of seismic signals induced by landslides and perform parametrical study. The two-dimensional particle flow code (PFC) and Fast Lagrangian Analysis of Continua (FLAC) are coupled to simulate the landslide process. The force and velocity data at the coupled interfaces of FLAC and PFC are transferred back and forth via a Socket I/O connection. Four locations were monitored for the induced vertical seismic signals, including velocity, acceleration, and stress histories. The signals were analyzed by Hilbert-Huang transform to obtain the time-frequency spectrograms for examining the characteristics of the signals. The particle size, wall friction, particle friction, and parallel bond of PFC input parameters were parametrically investigated. The Xiaolin landslide in 2009 was successfully simulated, and the characteristics of the seismic signals were studied and compared with the data from a broadband seismic station. These results demonstrate that terrain and transition in the movement type of a complex landslide do influence the seismic signals. A landslide with larger rock particles generates lower-frequency content seismic signals. Also, there can be approximately 40 s to escape before a large-scale landslide hits if seismic instrumentation is installed. The method proposed can be further applied for studies on many other large-scale rock avalanches to verify recorded signals and further correlate the signals with the landslide characteristics.