Dynamic Evolution and Triggering Mechanisms of the Simutasi Peak Avalanche in the Chinese Tianshan Mountains: A Multi-Source Data Fusion Approach
Abstract
1. Introduction
2. Study Area and Field Investigation
2.1. Study Area
2.2. Field Investigation
3. Materials and Methods
3.1. Data
3.1.1. Meteorological Data
3.1.2. Satellite and UAV Data Sources
3.2. Methods
3.2.1. UAV Image Processing and High-Resolution DEM Generation
3.2.2. Dynamics Modeling
4. Results
4.1. Meteorological and Terrain Factors Governing Avalanche Initiation
4.1.1. Meteorological Factors
4.1.2. Interaction of Meteorological and Terrain Factors
4.2. Remote Sensing-Based Avalanche Identification
4.3. Numerical Simulation by RAMMS::Avalanche Modeling
4.3.1. Analysis of the Simulation Results
4.3.2. Time Series Analysis of Avalanche Flow Height and Field Validation
5. Discussion
5.1. Meteorological and Topographic Controls on Avalanche Release
5.2. Spatiotemporal Characteristics and Recurrence Analysis of Avalanche Paths
6. Conclusions
- (1)
- Based on high-resolution remote sensing imagery and field survey data, the release zone, flow path, and deposition area of the avalanche were accurately identified. The results show that the avalanche path in the study area demonstrates significant spatial stability. The trajectories of previous avalanches closely coincide with that of the current event, indicating a recurrence interval of approximately 2 to 3 years.
- (2)
- The avalanche was triggered by a combination of meteorological and topographical factors. Continuous heavy snowfall, rapid warming, and significant diurnal temperature fluctuations resulted in a marked weakening of the snowpack structure. The stable southeast (SE) wind direction and northwest (NW) lee-slope topography formed a pronounced snow accumulation effect, enhancing the heterogeneity of snow thickness and increasing structural instability. The evolution of meteorological factors and the rapid growth of the snowpack were closely synchronized, indicating that this event was a typical wet snow slab avalanche driven by local meteorological-topographic coupling mechanisms.
- (3)
- The RAMMS model simulation results were highly consistent with the field survey data. The simulated deposition area and flow height were in good agreement with the observed data, with a maximum flow velocity of 19.22 m/s, a maximum flow height of 12.42 m, and a peak dynamic pressure of 129.3 kPa. The simulated deposition zone was in high accordance with historical avalanche traces identified through remote sensing imagery, further validating the spatial recurrence and strong topographical dependence of avalanche paths in this region.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Station ID | Longitude (°E) | Latitude (°N) | Elevation (m) | Distance to Release (km) | Elevation Difference (m) |
---|---|---|---|---|---|
AWS-1 | 80.6752 | 44.5134 | 2014 | 1.7 | −714 |
AWS-2 | 80.6848 | 44.5315 | 2283 | 2.3 | −445 |
AWS-3 | 80.6753 | 44.5633 | 2548 | 5.7 | −180 |
AWS-4 | 80.6588 | 44.5847 | 2739 | 8.7 | +11 |
AWS-5 | 80.6475 | 44.6055 | 2901 | 12.7 | +173 |
Satellite | Image Acquisition Date | Spatial Resolution (m) | Data Source and Availability |
---|---|---|---|
GF-01 | 29 April 2015 | 2.0 m | Non-open source; Commercial purchase |
Jilin-1 | 15 April 2022 | 2.0 m | Open-access; Jilin-1 Satellite Data Platform (https://www.jl1mall.com/) |
CF-1D1 | 5 October 2023 | 2.0 m | Non-open source |
WV03 | 16 May 2024 | 1.2 m | Open-access; Google Earth |
CF-1B1 | 2 March 2024 | 2.0 m | Non-open source |
UAV | 27 March 2024 | 0.1 m | DJI Mavic 3E |
Parameter Category | Parameter Name | Symbol | Value | Unit |
---|---|---|---|---|
Terrain | DEM | — | 0.4 | m |
Release Zone | Initial snow depth | — | 0.6 | m |
Snow density | ρ | 350 | kg/m3 | |
Release volume | — | 60,681.72 | m3 | |
Friction Model | Dry friction coefficient | μ | 0.28 | — |
Turbulence coefficient | ξ | 1750 | m/s2 | |
Cohesion | N0 | 100 | Pa | |
Simulation | Time step | — | 2 | s |
Max simulation time | — | 300 | s | |
Output interval | — | 5 | s |
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Qiang, X.; Huang, J.; Guo, Q.; Yang, Z.; Wang, B.; Liu, J. Dynamic Evolution and Triggering Mechanisms of the Simutasi Peak Avalanche in the Chinese Tianshan Mountains: A Multi-Source Data Fusion Approach. Remote Sens. 2025, 17, 2755. https://doi.org/10.3390/rs17162755
Qiang X, Huang J, Guo Q, Yang Z, Wang B, Liu J. Dynamic Evolution and Triggering Mechanisms of the Simutasi Peak Avalanche in the Chinese Tianshan Mountains: A Multi-Source Data Fusion Approach. Remote Sensing. 2025; 17(16):2755. https://doi.org/10.3390/rs17162755
Chicago/Turabian StyleQiang, Xiaowen, Jichen Huang, Qiang Guo, Zhiwei Yang, Bin Wang, and Jie Liu. 2025. "Dynamic Evolution and Triggering Mechanisms of the Simutasi Peak Avalanche in the Chinese Tianshan Mountains: A Multi-Source Data Fusion Approach" Remote Sensing 17, no. 16: 2755. https://doi.org/10.3390/rs17162755
APA StyleQiang, X., Huang, J., Guo, Q., Yang, Z., Wang, B., & Liu, J. (2025). Dynamic Evolution and Triggering Mechanisms of the Simutasi Peak Avalanche in the Chinese Tianshan Mountains: A Multi-Source Data Fusion Approach. Remote Sensing, 17(16), 2755. https://doi.org/10.3390/rs17162755