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Numerical modeling and dynamic analysis of the 2017 Xinmo landslide in Maoxian County, China
- Source :
- Journal of Mountain Science. 14:1701-1711
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- A catastrophic landslide occurred at Xinmo village in Maoxian County, Sichuan Province, China, on June 24, 2017. A 2.87×106 m3 rock mass collapsed and entrained the surface soil layer along the landslide path. Eighty-three people were killed or went missing and more than 103 houses were destroyed. In this paper, the geological conditions of the landslide are analyzed via field investigation and high-resolution imagery. The dynamic process and runout characteristics of the landslide are numerically analyzed using a depth-integrated continuum method and MacCormack-TVD finite difference algorithm. Computational results show that the evaluated area of the danger zone matchs well with the results of field investigation. It is worth noting that soil sprayed by the high-speed blast needs to be taken into account for such kind of large high-locality landslide. The maximum velocity is about 55 m/s, which is consistent with most cases. In addition, the potential danger zone of an unstable block is evaluated. The potential risk area evaluated by the efficient depth-integrated continuum method could play a significant role in disaster prevention and secondary hazard avoidance during rescue operations.
- Subjects :
- Global and Planetary Change
Potential risk
Landslide classification
Geography, Planning and Development
0211 other engineering and technologies
Numerical modeling
Geology
Landslide
02 engineering and technology
010502 geochemistry & geophysics
01 natural sciences
Landslide mitigation
Geotechnical engineering
Danger zone
China
Rock mass classification
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Nature and Landscape Conservation
Earth-Surface Processes
Subjects
Details
- ISSN :
- 19930321 and 16726316
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- Journal of Mountain Science
- Accession number :
- edsair.doi...........4dec2bd3249db942a87e9faea3af4a41