AUTOMATED AVALANCHE MONITORING: ENGINEERING AND SOFTWARE SOLUTIONS
DOI:
https://doi.org/10.37943/25TVYE5927Keywords:
avalanche hazard, avalanche monitoring, software-hardware complex, sensor network, automated detection, modular electronic systemAbstract
An autonomous avalanche hazard monitoring system has been developed and piloted in the East Kazakhstan Region to enable continuous, data-driven early detection and prediction of snow avalanches in mountainous environments. The system integrates a hardware–software ecosystem that overcomes the limitations of traditional manual observations by combining real-time data acquisition, transmission, and predictive analytics. The prototype includes base stations, autonomous snow-temperature measuring rails, meteorological sensors, and a secure web interface with an API for reliable data management.
Field deployments were conducted in three avalanche-prone areas with diverse terrain and climate conditions: Glubokoe district (Mountain Ulbinka), Altai district (Zubovsk), and Ulan district (Taynty river basin). The hardware, including 6-meter modular aluminum masts and sensor-equipped snow rails, was designed for extreme environments, operating reliably within a temperature range of –60 °C to +50 °C and withstanding strong winds and snow loads. The system supports autonomous operation in remote regions with minimal maintenance requirements.
The monitoring network collects high-resolution environmental data, including air temperature, humidity, wind parameters, atmospheric pressure, snow depth, and vertical snow temperature gradients. Data are transmitted every 15 minutes via LoRa, with LTE/Wi-Fi as backup, and stored in a centralized MySQL database. A dedicated software platform enables data visualization, processing, and integration with analytical modules, while a mobile application provides real-time monitoring and alerts.
Logistic regression models were applied to estimate avalanche probability based on meteorological and snowpack data, demonstrating the effectiveness of combining continuous monitoring with statistical forecasting. The system provides a scalable and adaptable framework for avalanche hazard assessment, early warning, and informed decision-making, contributing to improved safety in mountainous regions.
References
Taishibekov, K., others Midterm review of the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030, 2019. Available online: https://www.preventionweb.net/media/84800/download?startDownload=20251207 (accessed on 08.12.2025).
V.P. Blagoveshchensky V.V. Zhdanov Avalanche risk in Kazakhstan at different levels of avalanche danger. December 2021, Hydrosphere Dangerous processes and phenomena, 2(3), 122-132, https://doi.org/10.34753/HS.2021.3.2.122
Medeu, A.R., Blagoveshchenskij, V.P., Zhdanov, V.V. Innovacionnye tekhnologii ocenki i prognoza urovnya lavinnoj opasnosti v gorah Ile Alatau. Habarshy. Geografiya seriyasy 2021, №2 (61), pp. 76-87. https://doi.org/10.26577/JGEM.2021.v61.i2.07
Bianchi F.M., Grahn J., Eckerstorfer M., Malnes E., Vickers H. Snow avalanche segmentation in SAR images with Fully Convolutional Neural Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, vol. 14, pp. 75–82. https://doi.org/10.1109/JSTARS.2020.3036914
Avalanche warnings from «SensAlpin», Lawinenwarnung-Schneemeteorologie. Available online: https://www.sensalpin.ch/messnetze/imis/ (accessed on 08.12.2025).
Alpine Automated Weather Instrumentation. Available online: https://www.campbellsci.co.uk/alpine-weather (accessed on 31.01.2025).
Eckerstorfer, M.; Vickers, H.; Malnes, E.; Grahn, J. Near-Real Time Automatic Snow Avalanche Activity Monitoring System Using Sentinel-1 SAR Data in Norway. Remote Sens. 2019, 11, 2863. https://doi.org/10.3390/rs11232863
Turquet, A.; Wuestefeld, A.; Svendsen, G.K.; Nyhammer, F.K.; Nilsen, E.L.; Persson, A.P.-O.; Refsum, V. Automated Snow Avalanche Monitoring and Alert System Using Distributed Acoustic Sensing in Norway. GeoHazards 2024, 5, 1326-1345. https://doi.org/10.3390/geohazards5040063
Franz Kleine, Charlotte Bruland, Andreas Wuestefeld, Volker Oye, Martin Landrо Seismic Signal Classification of Snow Avalanches using Distributed Acoustic Sensing in Grasdalen, Western Norway. Nat. Hazards Earth Syst. Sci., 25, 2771–2782, 2025 https://doi.org/10.5194/nhess-25-2771-2025
Bian, R.; Huang, K.; Liao, X.; Ling, S.; Wen, H.; Wu, X. Snow avalanche susceptibility assessment based on ensemble machine learning model in the central Shaluli Mountain. Front. Earth Sci. 2022, 10, 880711. https://doi.org/10.3389/feart.2022.880711
Blagoveshchenskiy, V.; Myrzakhmetov, M.; Sadvakasov, E. Scientific Foundations of the Organization of Remote Monitoring of Avalanche Hazards in the Alatau Ile. Institute of Geography of the Ministry of Education and Science of the Republic of Kazakhstan, Kazntu Named After Satpayev [Electronic Resource]. Available online: https://чс-ник.kz/opasnosti/sel/item/760-nauchnye-osnovy-organizatsii-distantsionnogo-monitoringa-lavinnoj-opasnosti-v-ile-alatau (accessed on 08.12.2025).
Mayer, S.; van Herwijnen, A.; Ulivieri, G.; Schweizer, J. Evaluating the performance of an operational infrasound avalanche detection system at three locations in the Swiss Alps during two winter seasons. Cold Reg. Sci. Technol. 2020, 173, 102962, https://doi.org/10.1016/j.coldregions.2019.102962
Aydin A.; Eker R. GIS-Based snow avalanche hazard mapping: Bayburt-AşağıDere catchment case. J. Environ. Biol. 2017, 38, 937-943, https://doi.org/10.22438/jeb/38/5(SI)/GM-10
Aydin A.; Eker R.; Odabasi Y.B. Generating Avalanche Hazard Indication Map and Determining Snow Avalanche Protection Forests in Caykara-Trabzon (NE-Turkey). Forestist 2021, 72, 62–72, https://doi.org/10.5152/forestist.2021.20060
Soteres R. L.; Pedraza J.; Carrasco R. M. Snow avalanche susceptibility of the Circo de Gredos (Iberian Central System, Spain). J. Maps 2020, 16, 155–165, https://doi.org/10.1080/17445647.2020.1717655
Rakhymberdina, M., Levin, E., Daumova, G., Bekishev Y., Assylkhanova, Z., Kapasov, A. Combined Remote Sensing and GIS Methods for Detecting Avalanches in Eastern Kazakhstan // ES Energy and Environment – 2024. – Vol. 26, 1350, https://doi.org/10.30919/esee1350
Denissova, N.; Nurakynov, S.; Petrova, O.; Chepashev, D.; Daumova, G.; Yelisseyeva, A. Remote Sensing Techniques for Assessing Snow Avalanche Formation Factors and Building Hazard Monitoring Systems. Atmosphere. 2024, 15(11), 1343, https://doi.org/10.3390/atmos15111343.
Larsen H. T.; Hendrikx J.; Slatten M. S.; Engeset R.V. Developing nationwide avalanche terrain maps for Norway. Nat. Hazards 2020, 103, 2829–2847, https://doi.org/10.1007/s11069-020-04104-7
Choubin B.; Borji M.; Mosavi A.; Sajedi-Hosseini F.; Singh V. P.; Shamshirband S. Snow avalanche hazard prediction using machine learning methods. J. Hydrol. 2019, 577, 123929, https://doi.org/10.1016/j.jhydrol.2019.123929
Denissova N., Petrova O., Pankov M., Zuyev V. Avalanche monitoring in the ERA of climate change for mountain regions with diverse conditions. International Journal of Innovative Research and Scientific Studies, 8(6) 2025, pages: 1790-1810 https://doi.org/10.53894/ijirss.v8i6.10034
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