Monitoring snow avalanches in Northwestern Italian Alps using an infrasound array

Ulivieri, Giacomo; Marchetti, E.; Ripepe, Maurizio; Chiambretti, Igor; Rosa, Giuseppe De; Segor, V.

doi:10.1016/j.coldregions.2011.09.006

Cited by 64 publications

(54 citation statements)

References 9 publications

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“…The use of infrasound for avalanche monitoring has been increasing rapidly in the last decades, with significant improvements also on avalanche dynamics research (Bedard, 1989;Chritin et al, 1996;Adam et al, 1998;Comey and Mendenhall, 2004;Scott et al, 2007;Ulivieri et al, 2011;Kogelnig et al, 2011;Havens et al, 2014;Thüring et al, 2015). After the initial works with single infrasound sensors (e.g., Bedard, 1989), the use of infrasound arrays has improved significantly the signal-to-noise ratio (e.g., Scott et al 2007;Ulivieri et al, 2011;Havens et al, 2014), thus resulting in a larger efficiency of infrasound in detecting snow avalanches even at larger (few km) distances.…”

Section: E Marchetti Et Al: Automatic Detection and Front Velocity mentioning

confidence: 99%

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

Marchetti

Ripepe

Ulivieri³

et al. 2015

Nat. Hazards Earth Syst. Sci.

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Abstract. Avalanche risk management is strongly related to the ability to identify and timely report the occurrence of snow avalanches. Infrasound has been applied to avalanche research and monitoring for the last 20 years but it never turned into an operational tool to identify clear signals related to avalanches. We present here a method based on the analysis of infrasound signals recorded by a small aperture array in Ischgl (Austria), which provides a significant improvement to overcome this limit. The method is based on array-derived wave parameters, such as back azimuth and apparent velocity. The method defines threshold criteria for automatic avalanche identification by considering avalanches as a moving source of infrasound. We validate the efficiency of the automatic infrasound detection with continuous observations with Doppler radar and we show how the velocity of a snow avalanche in any given path around the array can be efficiently derived. Our results indicate that a proper infrasound array analysis allows a robust, real-time, remote detection of snow avalanches that is able to provide the number and the time of occurrence of snow avalanches occurring all around the array, which represent key information for a proper validation of avalanche forecast models and risk management in a given area.

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Section: E Marchetti Et Al: Automatic Detection and Front Velocity mentioning

confidence: 99%

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

Marchetti

Ripepe

Ulivieri³

et al. 2015

Nat. Hazards Earth Syst. Sci.

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“…Highly correlated signals (.0.8) have a time residual approaching 0. This procedure (see Ulivieri et al 2011 THERMAL, ACOUSTIC AND SEISMIC SIGNALSamong others) is performed for all the possible triplets of sensors of the array, and we consider a detection to be valid if the mean of time residuals is below the consistency threshold of 0.015 s, which corresponds to a 70% correlation for a signal with a peak frequency of 1 Hz. The propagation back-azimuth and apparent velocity is calculated as the mean value between all the possible combination of sensors within the different triplets using the distances and the time delays, and assuming a constant propagation velocity (see Cansi 1995;Ulivieri et al 2011 for details).…”

mentioning

confidence: 99%

Chapter 9 Thermal, acoustic and seismic signals from pyroclastic density currents and Vulcanian explosions at Soufrière Hills Volcano, Montserrat

Donne

Ripepe

Angelis

et al. 2014

Memoirs

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Abstract:We show two examples of how integrated analysis of thermal and infrasound signal can be used to obtain, in real time, information on volcanic activity. Soufrière Hills Volcano (SHV) on Montserrat offers the opportunity to study a large variety of processes related to lava-dome activity, such as pyroclastic density currents (PDCs) and large Vulcanian eruptions. Infrasound and thermal analysis are used to constrain the propagation of PDCs and their velocities, which are calculated here to range between 15 and 75 m s 21 . During the Vulcanian eruption of 5 February 2010, infrasound and thermal records allow us to identify an approximately 13 s seismic precursor possibly related to the pressurization of the conduit before the explosion onset. The associated very long period (VLP) seismic signal is correlated with the gas-thrust phase detected by thermal imagery, and may reflect a change in the upward momentum induced by the mass discharge. Moreover, from infrasound and thermal analysis, we estimate a gas-thrust phase lasting 22 s, with an initial plume velocity of approximately 170 m s 21 and a mean volumetric discharge rate of 0.3 Â 10 5 -9.2 Â 10 5 m 3 s 21 . This information provided in real time gives important input parameters for modelling the tephra dispersal into the atmosphere.Gold Open Access: This article is published under the terms of the CC-BY 3.0 license.Lava dome eruptions represent a style of volcanism of distinctive interest because of their potential consequences, such as the generation of pyroclastic density currents (PDCs) down the volcano's flanks and large explosive eruptions following partial-dome collapse. Lava domes are formed by silica-rich lava that is too viscous to flow and, instead, builds-up over the point of extrusion. The hazards from lava-dome eruptions are well known owing to unpredictable transitions from the slow extrusion of viscous lava to vigorous explosions, and to the propensity of lava domes to suddenly collapse, spawning devastating PDCs down the flanks of volcanic edifices (Young et al. 1998;. As a lava dome grows, parts of it may collapse because of gravitational instability or as the result of gas explosions within the dome itself, thus forming PDCs. The ability to detect and track the propagation of these fast-moving density currents is of utmost importance in understanding the evolution of lava dome eruptions and mitigating related hazards.Methods for the location of PDCs, based on seismic amplitudes, have been proposed in the past (e.g. Jolly et al. 2002) and have proved quite effective for the characterization of large collapse events. These techniques require dense seismic networks and optimal azimuthal coverage; both conditions are rarely met on lava dome volcanoes where seismic networks are sparse because of the restrictions imposed by rough terrain and eruption hazards. The use of seismic amplitudes requires understanding of local site effects and frequency-dependent attenuation, thus introducing another layer of complexity. Finally, these methods are ...

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“…The infrasonic ray path is determined by the time shifts dt ij between different pairs of sensors i, j of a planar wave field propagating across the array (Ulivieri et al 2011). Based on these time shifts between different sensors, the back azimuth a and the apparent velocity c a of an event can be identified.…”

Section: Infrasound Array Systemmentioning

confidence: 99%

“…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

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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.

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Monitoring snow avalanches in Northwestern Italian Alps using an infrasound array

Cited by 64 publications

References 9 publications

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

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

Chapter 9 Thermal, acoustic and seismic signals from pyroclastic density currents and Vulcanian explosions at Soufrière Hills Volcano, Montserrat

Automatic detection of avalanches: evaluation of three different approaches

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