Infrasound array criteria for automatic detection and front velocity estimation of snow avalanches: towards a real-time early-warning system

Marchetti, E.; Ripepe, Maurizio; Ulivieri, Giacomo; Kogelnig, Arnold

doi:10.5194/nhess-15-2545-2015

Cited by 44 publications

(46 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Detecting a stable source position in case of moving sources is not unexpected and is a consequence of infrasound array analysis that, in case of multiple sources, detects preferentially the most energetic one. Such a behavior has been observed already for snow avalanches (Marchetti et al, ) and pyroclastic density currents (Delle Donne et al, ) passing a discontinuity in the topography where infrasound energy radiation focuses in a stable position. However, snow avalanches and pyroclastic density currents produce a coherent infrasonic signal all along their downhill moving front and array analysis allows to clearly track their movement (Delle Donne et al, ; Marchetti et al, ).…”

Section: Discussionsupporting

confidence: 61%

“…Therefore, array processing is not really useful to track and investigate the flow, unless discontinuity points of the topography, such as change of slopes or dams, result in stable sources of infrasound clearly detectable by the array. We suggest therefore that the mechanism of infrasound radiation by debris flow is different from other density currents like snow avalanches or pyroclastic density currents, where a turbulent head develops radiating elastic energy in the atmosphere, that allows to nicely track the flow evolution through time with an infrasound array (e.g., Delle Donne et al, 2014;Marchetti et al, 2015;Ulivieri et al, 2011). Figure 11 shows the mean power spectral density of seismic and infrasound signals for the three debris flow events.…”

Section: Numerical Simulation Of Infrasound Radiated By An Extended Smentioning

confidence: 99%

“…Array techniques are widespread in infrasound (see, e.g., Szuberla & Olson, 2004) and seismic (see, e.g., Rost & Thomas, 2002) monitoring. They have been used for the detection and monitoring of different kinds of gravity currents such as snow avalanches (Kogelnig et al, 2011;Marchetti et al, 2015;Ulivieri et al, 2011;Scott et al, 2007), pyroclastic flows (Barfucci & Ripepe, 2018;Ripepe et al, 2010), alpine glacier collapses (Preiswerk et al, 2016) and lahars (Johnson & Palma, 2015) but have yet to be applied to debris flows.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Infrasound Array Analysis of Debris Flow Activity and Implication for Early Warning

et al. 2019

Self Cite

View full text Add to dashboard Cite

Debris flows constitute a severe natural hazard and studies are performed to investigate triggering mechanisms and to identify and evaluate early warning systems. We present a seismoacoustic analysis of debris flow activity at Illgraben, Switzerland, with infrasound data collected with a small aperture array. Events are recorded as emergent signals of long duration, with seismic and infrasound amplitudes scaling with the flow discharge. The spectral content is stable and peaking at 8 Hz for the seismic and at 5 Hz for the infrasound that suggests two separate processes of elastic energy radiation, most likely bed‐load transport for the seismic and waves at the free surface for the infrasound. Although amplitude and frequency content of the infrasound signal are well within the processing limits, most of the signal is not showing any correlation among the array elements. We suggest that this is a consequence of the contribution of multiple sources of infrasound acting with variable amplitude and phase along the surface of the debris flow. At Illgraben, coherent infrasound is recorded only from fixed sources, corresponding to check dams within the channel. Here infrasound radiation is increased and the dams turn into predominant sources of energy. This allows to unambiguously identify the occurrence of debris flow at Illgraben with the infrasound array, from a remote and safe position and with a timing that is similar to the early warning system based on in‐channel sensors. This clearly shows how infrasound arrays could be used as an efficient early warning systems.

show abstract

Section: Discussionsupporting

confidence: 61%

Section: Numerical Simulation Of Infrasound Radiated By An Extended Smentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Infrasound Array Analysis of Debris Flow Activity and Implication for Early Warning

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the usage of infrasound for automatic detection of avalanches was rare (Chritin et al 2003;Scott et al 2007;Ulivieri et al 2011), because infrasound is strongly contaminated by noise produced by natural (wind, earthquakes) and artificial sources (planes, helicopters, industry). But the increasing demand for automated avalanche monitoring systems in order to verify artificial avalanche release and for mitigation efforts at facilities and transportation corridors has led to improvement of sensor set-ups, data processing, and algorithms for infrasound avalanche detections in the recent years (Ulivieri et al 2011Thüring et al 2014;Marchetti et al 2015).…”

Section: Infrasound Signals Of Avalanchesmentioning

confidence: 99%

Automatic detection of avalanches: evaluation of three different approaches

Schimmel

Hübl

Koschuch³

et al. 2017

Nat Hazards

View full text Add to dashboard Cite

Automated detection of snow avalanches is an important tool for avalanche forecasting and for assessing the effectiveness of avalanche control measures at bad visibility. Avalanche detection systems are usually based on infrasound, seismic, or radar signals. Within this study, we compared three different types of avalanche detection systems: one avalanche radar, one infrasound array system consisting of four infrasound sensors, and a newly developed single sensor infrasound system. A special focus is given to the new single sensor system, which is a low cost, easy to install system, originally designed for the detection of debris flows and debris floods. Within this work, we analysed how this single sensor system could be adapted to detect also snow avalanches. All three systems were installed close to a road near Ischgl (Tyrol, Austria) at the avalanche-exposed Paznaun Valley. The valley is endangered by two avalanche paths which are controlled by several avalanche towers. The radar system detected avalanches accurately and reliably but was limited to the particular avalanche path towards which the radar beam was directed. The infrasound array could detect avalanches from all surrounding avalanche paths, however, with a higher effort for installation. The newly tested single infrasound sensor system was significantly cheaper and easier to install than the other two systems. It could also detect avalanches form all directions, although without information about the direction. In summary, each of the three different systems was able to successfully detect avalanches and had its particular strengths and weaknesses, which should be considered according to the specific requirements of a particular practical application.

show abstract

“…In a final step, we therefore used the MUSIC method to estimate the median back-azimuth path, as suggested by Heck et al (2018b), to further dismiss false detections. Similar approaches were 15 suggested for the automatic detection of avalanches in infrasonic data by Marchetti et al (2015) and Thüring et al (2015). In those studies, the back-azimuth of continuous infrasound data was calculated on the fly using cross-correlation techniques, and only events with slight changes in back-azimuth over a predefined minimal duration were assumed as avalanche events.…”

mentioning

confidence: 99%

Automatic detection of avalanches using a combined array classification and localization

Heck

Hammer

Hobiger

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract.We use a seismic monitoring system to automatically determine the avalanche activity at a remote field site near Davos, Switzerland. By using a recently developed approach based on hidden Markov models (HMMs), a machine learning algorithm, we were able to automatically identify avalanches in continuous seismic data by providing as little as one single training event. Furthermore, we implemented an operational method to provide near real-time classification results. For the 2016-2017 5 winter period 117 events were automatically identified. False classified events such as airplanes and local earthquakes were filtered using a new approach containing two additional classification steps. In a first step, we implemented a second HMM based classifier at a second array 14 km away to automatically identify airplanes and earthquakes. By cross-checking the results of both arrays we reduced the amount of false classifications by about 50 %. In a second step, we used multiple signal classifications (MUSIC), an array processing technique to determine the direction of the source. Although avalanche events 10 have a moving source character only small changes of the source direction are common for snow avalanches whereas false classifications had large changes in the source direction and were therefore dismissed. From the 117 initially detected events during the 4 month period we were able to identify 90 false classifications based on these two additional steps. The obtained avalanche activity based on the remaining 27 avalanche events was in line with visual observations performed in the area of Davos.

show abstract

Infrasound array criteria for automatic detection and front velocity estimation of snow avalanches: towards a real-time early-warning system

Cited by 44 publications

References 25 publications

Infrasound Array Analysis of Debris Flow Activity and Implication for Early Warning

Infrasound Array Analysis of Debris Flow Activity and Implication for Early Warning

Automatic detection of avalanches: evaluation of three different approaches

Automatic detection of avalanches using a combined array classification and localization

Contact Info

Product

Resources

About