Monitoring snow avalanches in Northwestern Italian Alps using an infrasound array

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Abstract

Risk assessment of snow avalanches is mostly related to weather conditions and snow cover. However, a robust risk validation requires avalanche activity data, in order to compare predictions to actual events. For this purpose in December 2009 we installed a temporary 4-element, small aperture (150 m), infrasound array in the northwestern Italian Alps. The array was installed south of Mt. Rosa, at an elevation of 2000 m a.s.l. in the valley of Gressoney, Italy, where natural avalanches are expected and avalanche control by explosives is regularly performed. A multi-channel correlation analysis is carried out on the continuous infrasound data set recorded by the array as a function of apparent velocity, back-azimuth and frequency of recorded infrasound. This allowed detectionof infrasonic signals propagating across the array from the background noise. During the 5-month-long experiment, 343 infrasonic events have been detected and characterized. These include sharp infrasonic transients (99 events) produced by explosions during avalanche control as well as longer lasting signals (244 events) possibly caused by avalanches. Although only few of these events were validated by direct avalanche observation, obtained results are promising and encouraging application of infrasound for long-term avalanche observation on wide areas, as the peak in avalanche activity in winter 2009–2010 was observed shortly after the infrasound events peaked as well.

Highlights

► Avalanche infrasound is fully characterized from know events. ► Continuous raw data is array processed for back-azimuth and propagation velocity. ► Comparison with observed activity is promising for large-range (> few km) analysis.

Introduction

Snow avalanches generate infrasonic waves, low frequency (< 20 Hz) acoustic waves propagating through the atmosphere at the speed of sound. While infrasound generated by avalanches is well documented (e.g. Bedard, 1994, Naugolnykh and Bedard, 2002), so far the use of infrasound to monitor avalanches has been sparse (Chritin et al., 1996, Comey and Mendenhall, 2004, Scott et al., 2007). This is in part because infrasound is not easily measured, being strongly contaminated by noise produced both by natural (e.g. wind, microseism, earthquakes) and human (e.g. industrial activity, traffic) sources.

Recently, the use of infrasound arrays rather than single sensors has improved the identification of signals generated by avalanches (Scott et al., 2007). Arrays consist of different infrasonic sensors deployed in a particular geometry to be used as an antenna. Array monitoring techniques allow increasing the signal-to-noise ratio and improving infrasound signal detection. However avalanche infrasound monitoring is commonly limited to relatively small areas (few km2) around the deployment (Scott et al., 2007). This is mostly related to the great amount of infrasound detected by an array, as a result of the small attenuation of infrasonic wave in the atmosphere.

In the last two decades, infrasound technology has been improving greatly, in terms of sensor design, noise reduction systems and processing procedures. This has allowed infrasound to be applied as an efficient research and monitoring tool for a wide variety of sources spanning from man-made and industrial explosions (e.g. Ceranna et al., 2009), explosive volcanism (e.g. Ripepe and Marchetti, 2002), drill and blast activity (e.g. Ripepe et al., 2010), lightning activity, bolides (e.g. Evers and Haak, 2003) and atmospheric processes (Le Pichon et al., 2009).

Here we describe results obtained from an infrasound array that operated during the 2009–2010 winter season in the Northwestern Italian Alps (Gressoney la Trinité, Valle d'Aosta, Italy) south of Monte Rosa. Continuous infrasound recorded by the array was analyzed in order to monitor avalanche activity, with the aim of validating avalanche observations and thus improving danger assessments. Infrasonic results were compared to the local avalanche observations that are used by regional avalanche warning offices to issue daily bulletins. Avalanches are recorded on the type 1 module of AINEVA (Associazione Interregionale Neve e Valanghe, www.aineva.it), which allows a description of avalanche activity according to international standards.

Section snippets

The infrasound array

The infrasound monitoring system deployed in December 2009 in the northwestern Italian Alps consisted of a 4-element infrasound array with a triangular geometry and an aperture (maximum distance between two elements) of ~ 150 m (Fig. 1). The array was installed in the Lys valley immediately south of Monte Rosa, at an elevation of ~ 2000 m. Each array element was equipped with a differential pressure transducer (Marchetti et al., 2009), with a sensitivity of 25 mV/Pa in the frequency band 0.001–50 Hz

Array signal processing

The array signal processing is based on the assumption that a signal is coherent at the different sensors, while noise does not show any correlation (Fig. 3). We applied a multi-channel correlation method to identify signals from noise in terms of wave propagation back-azimuth (α) apparent velocity (c) and time residual (ΔT). The propagation back-azimuth indicates the direction where the signal is coming from and is related to the location of the source of the signal. The apparent velocity is

Artificially released avalanches

Artificially released avalanches provide useful information for characterizing the infrasonic wavefield generated by snow avalanches and to test the source localization accuracy. During the 2009–2010 winter season frequent avalanche control work was carried out at distances up to 4 km from the array. In particular four explosions on 4 December 2010 at a distance of about 2 km from the array triggered four small loose snow avalanches and one small- to medium-sized snow slab avalanche (Fig. 5). The

Infrasonic activity during the 2009–2010 winter season

During the 2009–2010 winter season, almost 10.000 infrasonic detections were obtained from array analysis. This corresponds to a mean of about 65 detections every day. As it is evident from Fig. 7, a single event can be associated to multiple detections, as a consequence of the processing window length and signal duration. Accordingly, we further grouped all detections into discrete events, considering time consistency of successive detections, as well as the stability of back-azimuth and

Conclusions

Our results confirm that infrasonic array monitoring of avalanches is feasible and promising. However, a proper instrument design and array installation as well as adequate treatment of environmental noise and careful data processing are needed.

Analysis of infrasonic data during the 2009–2010 winter season allowed detection of signals related to explosions and possible avalanches, with an accuracy of infrasonic back-azimuth of about 1°. The comparison of infrasonic detections with avalanche

Acknowledgements

We are grateful to two anonymous reviewers for their careful review that greatly improved the manuscript and the Monterosa Ski for their support in the field and for the video of the controlled avalanche. The work was supported in the frame of the Dynaval project.

References (17)

  • E.D. Scott et al.

    Single and multiple sensor identification of avalanche-generated infrasound

    Cold Regions Science and Technology

    (2007)
  • V. Adam et al.

    Infrasonic monitoring of snow-avalanche activity: what do we know and where do we go from here?

    Annals of Glaciology

    (1998)
  • S. Baggi et al.

    Characteristics of wet-snow avalanche activity: 20 years of observations from a high alpine valley (Dischma, Switzerland)

    Natural Hazards

    (2009)
  • A. Bedard

    An evaluation of atmospheric infrasound for monitoring avalanches

  • J.R. Bowman et al.

    Ambient infrasound noise

    Geophysical Research Letters

    (2005)
  • L. Ceranna et al.

    The Buncefield explosion: a benchmark for infrasound analysis across Central Europe

    Geophysical Journal International

    (2009)
  • V. Chritin et al.

    Acoustic detection system for operational avalanche forecasting

  • R.H. Comey et al.

    Recent studies using infrasound sensors to remotely monitor avalanche activity

There are more references available in the full text version of this article.

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