Journal of the Japanese Society of Snow and Ice
Online ISSN : 1883-6267
Print ISSN : 0373-1006
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Volume 84, Issue 5
Displaying 1-4 of 4 articles from this issue
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Article
  • Multi-parametric Experiments on Infrasound Monitoring for Snow-Avalanche at Mt. Fuji
    Wataru IKEDA, Mie ICHIHARA, Ryo HONDA, Hiroshi AOYAMA, Hidetoshi TAKAH ...
    2022 Volume 84 Issue 5 Pages 421-432
    Published: September 15, 2022
    Released on J-STAGE: October 08, 2022
    DOIhttps://doi.org/10.5331/seppyo.84.5_421
    JOURNAL FREE ACCESS
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    We tried infrasonic monitoring of snow avalanche at Mt. Fuji. We installed infrasound sensors, a thermometer-probe snow-depth meter, and seismometers for two winter seasons from 2018 to 2020 and made integrated analyses of their data. Although no significant snow avalanche event occurred during our observation, we found many infrasound waveforms similar to the reported snow avalanche infrasound. Because the infrasound events accompanied little seismic power, we inferred surface phenomena, if not necessarily snow avalanches, generated them. The events’ occurrences were concentrated during and right after snow-falls and during snow melting. The infrasonic array analyses of the 2019-2020 dataset exhibited most of the events are from the north slopes below the observation site. From the summit direction, continuous infrasonic noise was frequently detected, by which detecting events from there might have been difficult. This study has shown that the multi-parameter observation method is practical and useful in the severe environment of Mt. Fuji in winter. Also, it revealed the particular problems of infrasound observation at the huge volcanic edifice. We expect our results will help design future observations.

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Recent Research
Research Note
  • Measurement of snow depth and avalanche accumulation distribution in avalanche zones using unmanned aerial vehicle photogrammetry with post-processing kinematic positioning
    Satoru ADACHI, Takafumi KATSUSHIMA, Hayato ARAKAWA
    2022 Volume 84 Issue 5 Pages 439-452
    Published: September 15, 2022
    Released on J-STAGE: October 08, 2022
    DOIhttps://doi.org/10.5331/seppyo.84.5_439
    JOURNAL FREE ACCESS
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    In this study, we proposed a method to measure snow depth and avalanche accumulation distribution in avalanche zones by using a small rotorcraft unmanned aerial vehicle (UAV) for avalanche inspection and survey. Snow depth was determined by comparing the differences between the results of a high-resolution digital elevation model (DEM), created by interpolating an aerial laser survey using light detection and ranging (LiDAR) as the elevation of the ground surface, and a digital surface model, created via post-processing kinematic-structure-from-motion with UAV photogrammetry as the elevation of the snow surface. This method provided the snow depth distribution while excluding the effect of vegetation in the avalanche zone. It also showed that a time series of the snow depth distribution can be used to detect the occurrence and expansion of cracks in the snowpack and development of cornice. Moreover, the amount of avalanche deposits can be determined by measuring the snow depth distribution after avalanche occurrence.

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Review Article
  • Finger formation in snow avalanche deposit
    Yoichi ITO
    2022 Volume 84 Issue 5 Pages 453-457
    Published: September 15, 2022
    Released on J-STAGE: October 08, 2022
    DOIhttps://doi.org/10.5331/seppyo.84.5_453
    JOURNAL FREE ACCESS
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    Finger-like debris are sometimes observed in the deposition area of snow avalanches. Particle segregation within the flow is a key factor for finger formation during debris flow; however, investigation of the particle size distribution in snow avalanche debris led to a contrasting conclusion. A novel hypothesis is proposed herein for explaining finger formation by constructing a model in which debris continue to flow or get deposited depending on the distribution of velocity and random kinetic energy within the flow.

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