Chain‐Style Landslide Hazardous Process: Constraints From Seismic Signals Analysis of the 2017 Xinmo Landslide, SW China

Abstract

Landslides generally involve rapid acceleration and deceleration of huge mass in just several minutes, and their unpredictability have made real‐time detections of their rapid processes difficult. Seismic signals generated by landslides provide an excellent opportunity to obtain the time‐dependent observations on landslide's processes. We invert the force‐time function by fitting long‐period seismic signals generated by Xinmo landslide on 23 June 2017, SW China, and determine three‐stage dynamic processes within 104‐s duration of this event. Constrained by the field observed runout distance, we deduce the landslide's mass of about 9 × 109 kg with corresponding maximum velocity and acceleration of 58.8 m/s and 4.38 m/s2, respectively. Combining dynamic parameters, apparent friction coefficient, and seismic signal features, we depict a dynamic landslide process initiated by high‐position rockslide, traveled by rapid long runout debris, and deposited over an old landslide's deposition fan. The rapid process of the landslide is affected by multiple preconditions such as the structure, topography, and meteorology of the site, which is characteristic of a typical chain‐style landslide hazard and could be helpful to recognize potential slope instabilities.

Relocation of the 17 June 2017 Nuugaatsiaq (Greenland) Landslide Based on Green's Functions From Ambient Seismic Noises

“…This suggests that the landslide is mainly composed of two subevents. Similar complex waveforms have also been observed for other landslides, such as the 2017 Xinmo landslide in Maoxian of Sichuan, China, which consists of multiple ruptures (Li et al, 2019). Chao et al (2016) found strong late-arriving seismic phase in many dam-forming landquake events.…”

Variation patterns of landslide basal friction revealed from long-period seismic waveform inversion

“…One approach parameterizes the time-varying force as a sequence of partially overlapping isosceles triangles and solve for the amplitude of each triangle by best fitting the synthetic and recorded seismograms in a least-square sense (e.g., Ekström and Stark 2013;Hibert et al 2014aHibert et al , 2015Chao et al 2016;Kääb et al 2018;Schöpa et al 2018). The other approach directly deconvolves Green's Functions with seismic records to obtain time series of force vectors with or without prior constraints on start and end times of the event (e.g., Allstadt 2013;Yamada et al 2013;Moretti et al 2015;Li et al 2017;Gualtieri and Ekström 2018;Li et al 2019a). Basically, these two approaches can give similar results and main differences come from the different frequency bands of seismic data used in the inversion (Moore et al 2017).…”

A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties

“…Human activities, such as deforestation and mining, can also trigger landslides [7]. As a consequence of their unpredictability [8,9], landslides have always caused a large number of casualties and property losses and threatened basic infrastructure [10][11][12][13]. Mapping the runout zone of potentially unstable slopes is critical for regional hazard evaluations and the maintenance of major engineering facilities in alpine countries.…”