Characterizing the complexity of seismic signals at slow-moving clay-rich debris slides: The Super-Sauze (Southeastern France) and Pechgraben (Upper Austria) case studies

Abstract

Abstract. Soil and debris slides are prone to rapid and dramatic reactivation. Deformation within the instability is accommodated by sliding, whereby weak seismic energies are released through material deformation. Thus, passive microseismic monitoring provides information that relate to the slope dynamics. In this study, passive seismic data acquired at Super-Sauze (Southeastern France) and Pechgraben (Upper Austria) slow-moving clay-rich debris slides ("clayey 10 landslides") are investigated. Observations are benchmarked to previous similar case studies to provide a comprehensive and homogenized typology of seismic signals at clayey landslides. A well knowledge of the various seismic signals potentially triggered by the slope deformation is crucial for the future development of automatic detection systems to be implemented in early-warning systems. Detected seismic events range from short duration (< 2 s) quake-like signals to a wide variety of longer duration tremor-like radiations. Complex seismic velocity structures, low-quality signal onsets and non-optimal 15 seismic network geometry severely impedes the source location procedure, thus rendering source processes characterization challenging. Therefore, we constrain sources location using the prominent waveform attenuation pattern characteristic of near (< ~50 m) seismic events. A local magnitude scale (ML) for clayey landslides is empirically calibrated using calibration shots and hammer blows data. The derived ML scale returns landslide seismicity rates that correlate in general with higher displacement rates. However, high temporal and spatial resolution analyses of the landslide dynamics and hydrology are 20 required to better decipher the potential relations linking landslide-induced seismic signals to landslide deformation.

Dynamics of the Askja caldera July 2014 landslide, Iceland, from seismic signal analysis: precursor, motion and aftermath

“…Future work could attempt to establish bounds for the observability of small, infrequently repeating events that might be near the noise level. Furthermore, some alreadymonitored slow-moving landslides show displacement rates that scale with the seismicity rates of cracks and stick-slip tremor signals (Tonnellier et al, 2013;Vouillamoz et al, 2017) and could serve as test sites.…”

“…Bradley P. Lipovsky was supported by a postdoctoral fellowship from the Department of Earth and Planetary Sciences at Harvard University. Some figures were created with the help of GMT, Generic Mapping Tools, developed by Wessel et al (2013). Eva P. S. Eibl is thanked for fruitful discussions.…”

Automatic approach for increasing the location accuracy of slow-moving landslide endogenous seismicity: the APOLoc method

“…5c.). The second type of endogenous signals is generated by slopequakes; these sources are assumed to result from stress release by both fracture opening or shearing (Helmstetter & Garambois 2010;Walter et al 2013;Tonnellier et al 2013;Vouillamoz et al 2017;Provost et al 2018). The recorded signals last less than 5 s and different waveforms and frequency content may be observed (Provost et al 2018).…”

“…The recorded signals last less than 5 s and different waveforms and frequency content may be observed (Provost et al 2018). It must be noted that some events are only recorded by one of the seismic arrays (Walter et al 2012;Tonnellier et al 2013;Vouillamoz et al 2017) and that the intertrace correlation of the whole signal is low due to scattering and dispersion of the seismic waves (Walter et al 2012;Tonnellier et al 2013). P-wave arrivals of most of the slopequakes are identifiable on the seismic signal vertical component (Fig.…”