Seismic Characterization of Debris Flows: Insights into Energy Radiation and Implications for Warning

Abstract

Debris flows represent a major hazard in mountainous areas, due to their rapid motion along steep channels and to the transport of large sediment volumes, including large boulders. In this paper, we present data of channelized debris flows characterized by different velocities and sediment concentrations recorded in an instrumented channel reach of the Gadria basin (eastern Italian Alps). From the analysis of the seismic energy produced by the interaction of solid particles with channel boundaries, we show that (i) the peak amplitudes are representative of the kinetic energy of each surge and (ii) most energy transfer occurs during the passage of the surge fronts. Then, we propose a debris flow detection algorithm based on the amplitude information gathered from a linear array of geophones installed along the channel. The short time average over long time average ratio of the seismic signal is used to early detect the debris flow occurrence in a continuous stream of seismic data. The algorithm recognizes moving, long‐lasting sources of ground vibration (i.e., debris flows) and filters out different seismic sources (i.e., anthropic noise, earthquakes, and rockfalls). The alarm is triggered when the short time average/long time average threshold is exceeded on two geophones, progressively with time from upstream to downstream. The algorithm is employed in the early warning system installed for research purposes at Gadria. Complementary data (rainfalls, flow stage measurements, and video recordings) permitted a detailed event characterization and alarm validation. During three monitoring seasons, all debris flows were successfully detected, with the alarm lasting for their entire duration, and no false positives were produced.

Insights Into the Internal Dynamics of Natural Lahars From Analysis of 3-Component Broadband Seismic Signals at Volcán de Colima, Mexico

“…Seismic monitoring techniques are convenient for characterizing fluvial processes because they can provide continuous data at safe distances from the channel (Coviello et al, 2019;Hürlimann et al, 2019). However, correct interpretation of the seismicity induced by flow processes depends on many factors related to source and medium characteristics.…”

Revision of manuscript esurf-2019-25

“…In studies investigating seismic signals generated by rockfalls (e.g., Deparis et al, 2008;Levy et al, 2015), a scaling relationship between the duration of the process and its seismic energy and potential energy loss was shown. Coviello et al (2019) proposed a scaling relation between kinetic energy and seismic amplitude indicating that for debris flows a little portion of the kinetic energy of each surge is converted into seismic energy.…”

A framework for temporal and spatial rockfall early warning using micro-seismic monitoring

“…Considering that rockfalls generate ground vibrations during crack nucleation, crack propagation, and eventually the collapse and the subsequent movement along the slope and to the ground, a geophones network can be used to record them. Important information on the characteristics of the seismic source could be derived from a three-components seismogram (e.g., the event type, energy, duration, location, back-azimuth, and developing process) that not only occurred on the surface but also in the subsurface (Deparis et al 2008;Vilajosana et al 2008;Helmstetter and Garambois 2010;Hibert et al 2011;Coviello et al 2019). Therefore, an early warning system can be set up by monitoring the seismic signals emitted by surface and subsurface slope dynamics (Amitrano et al 2005;Lacroix and Helmstetter 2011;Lenti et al 2012;Walter and Joswig 2012;Van Herwijnen et al 2016;Schöpa et al 2018).…”