Acoustic emission monitoring and analyses for avalanche release and slab fracturing events observed in Great Himalaya

ABSTRACT

The acoustic emission (AE) monitoring of failures, fractures and instabilities evolving within a snowpack may provide vital information about the avalanche formation preceding release processes. In this work, AE activity was collected continuously over five years from the snowpack built on avalanche starting zone in Great Himalaya, and the analyses are presented in the context of an avalanche release and two slab fracturing events detected successfully during this study period. For non-invasive detection of AE activity from snow, a specialised sensor-arrestor array was deployed over the avalanche slope. In our investigations, an abnormal AE activity was observed both during the slab fracturing as well as the avalanche occurrence periods. For AE-based direct assessment of snow instability, a method is proposed to estimate instability index (β_in), based on AE count and amplitude values of a hit, and it is applied for analyses of avalanche formation preceding release and slab fracturing cases. The prominent AE attributes including β_in-variations are also analysed at appropriate window scales for a smooth representation of the ongoing instability and failure processes underneath the slab. The AE spectral analyses of avalanche release and slab fracturing reveal the dominant frequencies around 45–47 kHz and 34–43 kHz, respectively. A progressively increasing behaviour was observed with an abrupt increase in the relevant AE parameters and also the β_in-values, nearly 13 hours before the avalanche release, and it continued until the avalanche released which can be associated to the instability development prior to avalanche release.

KEYWORDS:

• AE energy
• signal strength
• avalanche spectrogram
• instability index
• non-destructive testing

Acknowledgments

Authors are sincerely thankful to Director DGRE (erstwhile SASE) for administrative as well as financial support to carry out this research work. Authors are also thankful to P K Satyawali and P K Srivastava for the administrative support. Authors acknowledge the technical support provided by P. Datt, V. Kumar, M. Midya and V. Bharti and also to other field team members involved in deployments of AE sensor-arrestor array and collection of field data. The supports provided by workshop staff for fabrication of AE arrestor assembly are sincerely acknowledged. Authors express their sincere thanks to the editor in chief as well as to the reviewers for their insightful comments and thorough reviews of the manuscript.

Author contributions

All the authors have contributed significantly in present research work and preparing this manuscript. The original idea behind AE-based monitoring of avalanche terrain and development of methodology for AE data acquisition including computational approach for AE-based instability index are conceptualised and formulated by J C Kapil. He has also contributed in collection, analysis and interpretation of AE data along with structuring and preparation of this paper. Sakshi Sharma developed the MATLAB codes for window-wise analysis and carried out a comprehensive data analysis for relevant AE parameters, instability index, snow pit profiles and snow-met parameters. She has contributed in preparation of the manuscript along with the graphs, tables, figures, etc. Karmjeet Singh was involved in fabrication of AE arrestors, deployment of AE sensor-arrestor array over avalanche terrain and collection of field data on AE, snow – met, snow profiles, stability and slope images. JS Shahi contributed in AE signal analysis and presentation of this paper. Rama Arora contributed in material selection and design of AE arrestor.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10589759.2023.2208717.