摘要
The 2008 Wenchuan earthquake resulted in a large number of fatalities and caused significant economic losses.Thousands of landslides,many of which are very large,were triggered by the earthquake.A majority of catastrophic landslides were distributed along the central Longmenshan fault system,at the eastern margin of the Tibetan Plateau.Some of the landslides resulted in sudden damming of rivers causing flooding,which in turn induced secondary sliding disasters.Among the most significant landslides,the Daguangbao landslide was the largest in volume with the maximum thickness.For this,a numerical model of the Daguangbao landslide,using the material point method(MPM),was developed to simulate the interaction of the seismic loads imposed on the slope.The numerical results then are compared with the post-earthquake profile.As a consequence of the landslide,a nearly vertical head scarp with a maximum height of about 700 m was generated.This is considered as a high risk situation that requires constant monitoring and evaluation.Finally,we propose a methodology based on Bayesian networks(BNs)to manage the risk associated with the stability of the rockwall at the Daguangbao landslide site.
The 2008 Wenchuan earthquake resulted in a large number of fatalities and caused significant economic losses.Thousands of landslides,many of which are very large,were triggered by the earthquake.A majority of catastrophic landslides were distributed along the central Longmenshan fault system,at the eastern margin of the Tibetan Plateau.Some of the landslides resulted in sudden damming of rivers causing flooding,which in turn induced secondary sliding disasters.Among the most significant landslides,the Daguangbao landslide was the largest in volume with the maximum thickness.For this,a numerical model of the Daguangbao landslide,using the material point method(MPM),was developed to simulate the interaction of the seismic loads imposed on the slope.The numerical results then are compared with the post-earthquake profile.As a consequence of the landslide,a nearly vertical head scarp with a maximum height of about 700 m was generated.This is considered as a high risk situation that requires constant monitoring and evaluation.Finally,we propose a methodology based on Bayesian networks(BNs) to manage the risk associated with the stability of the rockwall at the Daguangbao landslide site.
