Combined Remote Sensing and GIS Methods for Detecting Avalanches in Eastern Kazakhstan
Rakhymberdina M. Levin E. Daumova G. Denissova N. Bekishev Y. Assylkhanova Z. Kapasov A.
December 2024Engineered Science Publisher
ES Energy and Environment
2024#26
This research integrates remote sensing technologies with geographic information systems (GIS) to investigate the causes of avalanches in mountains up to 1,000 meters high and enhance avalanche forecasting in East Kazakhstan. The slopes in the study area have steepness ranging from 15 to 20 degrees. Statistical analysis of meteorological data revealed significant warming, with temperatures rising by more than 10 °C atmospheric pressure decreasing in the two weeks leading up to the avalanche, particularly at altitudes between 480 and 550 meters. Avalanche modeling conducted at snow cover heights of 0.66 m and 1.5 m produced the following results: the maximum snow flow velocity reached 24.92 m/s at a snow cover height of 1.5 m, indicating the high dynamic intensity of the avalanche. Particular focus was placed on assessing avalanche hazards to critical infrastructure, such as roads and rivers. The impact pressure of the snow mass on the road was measured at 13.68 kPa, underscoring the urgent need for protective measures. Furthermore, the snow cover height on the slope increased to 4.43 m due to avalanche movement, highlighting the significant redistribution of snow mass. The collected data enabled the refinement of avalanche-prone zone boundaries and the creation of detailed risk maps, providing valuable insights for hazard mitigation and risk management.
Avalanche monitoring , Digital elevation model , GIS technologies , Remote sensing
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School of Earth Sciences, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, 070000, Kazakhstan
School of Applied Computational Sciences, Meharry Medical College, Nashville, 37208, TN, United States
Department of Information Technology, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, 070000, Kazakhstan
School of Earth Sciences
School of Applied Computational Sciences
Department of Information Technology
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