Journal
LANDSLIDES
Volume 15, Issue 7, Pages 1359-1375Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s10346-018-0953-9
Keywords
Landslide; Numerical modeling; Landslide risk assessment; Rock avalanche; Discrete element method; Continuum model method
Funding
- National Science Fund for Distinguished Young Scholars of China [41225011]
- Fund for International Cooperation (NSFC-RCUK_NERC)
- Resilience to Earthquake-induced landslide risk in China [41661134010]
- Fund for Creative Research Groups of China [41521002]
- National Science Fund for Outstanding Young Scholars of China [41622206]
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Rock avalanches represent a serious risk for human lives, properties, and infrastructures. On June 24, 2017, a catastrophic landslide destroyed the village of Xinmo (Maoxian County, Sichuan, China) causing a large number of fatalities. Adjacent to the landslide source area, further potentially unstable masses were identified. Among them, a 4.5-million m(3) body, displaced during the landslide event by about 40 m, raised serious concerns. Field monitoring and a reliable secondary risk assessment are fundamental to protect the infrastructure and the population still living in the valley. In this framework, the use of distinct element methods and continuum model methods to simulate the avalanche process was discussed. Various models (PFC, MatDEM, MassMov2D, Massflow) were used with the aim of reproducing the Xinmo landslide and, as predictive tools, simulating the kinematics and runout of the potentially unstable mass, which could cause a new catastrophic event. The models were all able to reproduce the first-order characteristics of the landslide kinematics and the morphology of the deposit, but with computational times differing by several orders of magnitude. More variability of the results was obtained from the simulations of the potential secondary failure. However, all models agreed that the new landslide could invest several still-inhabited buildings and block the course of the river again. Comparison and discussion of the performances and usability of the models could prove useful towards the enforcement of physically based (and multi-model) risk assessments and mitigation countermeasures.
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