The reasonable design of protective structures to mitigate the hazards from rock fall depends on the knowledge of motion behaviors of falling stones,such as the falling paths,velocities,jump heights and distances.Nume...The reasonable design of protective structures to mitigate the hazards from rock fall depends on the knowledge of motion behaviors of falling stones,such as the falling paths,velocities,jump heights and distances.Numerical simulation is an effective way to gain such kind of knowledge,In this paper,the discontinuous deformation analysis (DDA) is applied to rock fall analysis.In order to obtain more reliable results,the following improvements and extensions are made on the original DDA.(1)Solve the problem of block expansions due to rigid body rotation error.(2) Add the function of modeling the drag resistance from air and plants so that the velocities of falling stones obtained by simulations are good enough in agreement with those by experiments in situ.(3)Add the capability to consider energy loss due to block collisions so that the jumping heights and distances obtained by simulations are good enough in agreement with thos by experiments even for the slope with very soft layer on its surface.One of application examples is presented to show that the extended DDA is very effective and useful in rock fall analysis.Therefore,the presented method is expected to be put into wide use in slop stability analysis.展开更多
Accurate volume calculation of each individual landslide triggered by strong historical earthquakes can help understand the characteristics of the typical earthquake-induced landslides,thus providing significant infor...Accurate volume calculation of each individual landslide triggered by strong historical earthquakes can help understand the characteristics of the typical earthquake-induced landslides,thus providing significant information for the modification of the focal parameters of historical earthquakes.In this study,we select one rock fall and three loess landslides triggered by the 1556 AD Huaxian M8⅟earthquake,compute their volumes using the low-altitude high-precision Unmanned Aerial Vehicle(UAV)photogrammetry and landslide profile restoration methods.The results show that:①the whole influencing area of the Huangjiagou Rock Fall is approximately 3.03×105 m2 and the area of the collapsed rock accumulated at the slope foot is 3.33×104 m2,accounting for approximately 10%of the entire influencing range.However,the estimated volume of the collapsed rock is only 0.699×106 m3,indicating a rock fall with large influencing range but limited collapsed rock;②the geological form of thethree loess landslides are preserved intactly,with volumes of 0.283×108 m3,0.074×108 m3,and 0.377×108 m3.These important geological hazard relics reflect the strong vibrations and severe casualties in the meizoseismal area;③loess landslides are the key reason of the serious death toll in the hilly-gully loess area.Our new method can be used to estimate the influencing area and the actual volume of each individual landslide,and rationally evaluate the role of earthquake landslides in the disaster.In addition,quantitative research on secondary disasters triggered by strong historical earthquakes is beneficial for understanding the surface process and focal parameters of the earthquakes.展开更多
Most literature related to landslide susceptibility prediction only considers a single type of landslide,such as colluvial landslide,rock fall or debris flow,rather than different landslide types,which greatly affects...Most literature related to landslide susceptibility prediction only considers a single type of landslide,such as colluvial landslide,rock fall or debris flow,rather than different landslide types,which greatly affects susceptibility prediction performance.To construct efficient susceptibility prediction considering different landslide types,Huichang County in China is taken as example.Firstly,105 rock falls,350 colluvial landslides and 11 related environmental factors are identified.Then four machine learning models,namely logistic regression,multi-layer perception,support vector machine and C5.0 decision tree are applied for susceptibility modeling of rock fall and colluvial landslide.Thirdly,three different landslide susceptibility prediction(LSP)models considering landslide types based on C5.0 decision tree with excellent performance are constructed to generate final landslide susceptibility:(i)united method,which combines all landslide types directly;(ii)probability statistical method,which couples analyses of susceptibility indices under different landslide types based on probability formula;and(iii)maximum comparison method,which selects the maximum susceptibility index through comparing the predicted susceptibility indices under different types of landslides.Finally,uncertainties of landslide susceptibility are assessed by prediction accuracy,mean value and standard deviation.It is concluded that LSP results of the three coupled models considering landslide types basically conform to the spatial occurrence patterns of landslides in Huichang County.The united method has the best susceptibility prediction performance,followed by the probability method and maximum susceptibility method.More cases are needed to verify this result in-depth.LSP considering different landslide types is superior to that taking only a single type of landslide into account.展开更多
文摘The reasonable design of protective structures to mitigate the hazards from rock fall depends on the knowledge of motion behaviors of falling stones,such as the falling paths,velocities,jump heights and distances.Numerical simulation is an effective way to gain such kind of knowledge,In this paper,the discontinuous deformation analysis (DDA) is applied to rock fall analysis.In order to obtain more reliable results,the following improvements and extensions are made on the original DDA.(1)Solve the problem of block expansions due to rigid body rotation error.(2) Add the function of modeling the drag resistance from air and plants so that the velocities of falling stones obtained by simulations are good enough in agreement with those by experiments in situ.(3)Add the capability to consider energy loss due to block collisions so that the jumping heights and distances obtained by simulations are good enough in agreement with thos by experiments even for the slope with very soft layer on its surface.One of application examples is presented to show that the extended DDA is very effective and useful in rock fall analysis.Therefore,the presented method is expected to be put into wide use in slop stability analysis.
基金Received on April 29th,2020revised on June 5th,2020.This project is sponsored by Fundamental Scientific Research Fund in the IEF,CEA(2017IES010102,2019IEF0201,2017IES010101,)+1 种基金the National Natural Science Foundation of China(42072248)the Seismic Active Fault Exploration Project based on Highresolution Remote Sensing Interpretation Technology by Department of Earthquake Damage Defense,CEA(15230003).
文摘Accurate volume calculation of each individual landslide triggered by strong historical earthquakes can help understand the characteristics of the typical earthquake-induced landslides,thus providing significant information for the modification of the focal parameters of historical earthquakes.In this study,we select one rock fall and three loess landslides triggered by the 1556 AD Huaxian M8⅟earthquake,compute their volumes using the low-altitude high-precision Unmanned Aerial Vehicle(UAV)photogrammetry and landslide profile restoration methods.The results show that:①the whole influencing area of the Huangjiagou Rock Fall is approximately 3.03×105 m2 and the area of the collapsed rock accumulated at the slope foot is 3.33×104 m2,accounting for approximately 10%of the entire influencing range.However,the estimated volume of the collapsed rock is only 0.699×106 m3,indicating a rock fall with large influencing range but limited collapsed rock;②the geological form of thethree loess landslides are preserved intactly,with volumes of 0.283×108 m3,0.074×108 m3,and 0.377×108 m3.These important geological hazard relics reflect the strong vibrations and severe casualties in the meizoseismal area;③loess landslides are the key reason of the serious death toll in the hilly-gully loess area.Our new method can be used to estimate the influencing area and the actual volume of each individual landslide,and rationally evaluate the role of earthquake landslides in the disaster.In addition,quantitative research on secondary disasters triggered by strong historical earthquakes is beneficial for understanding the surface process and focal parameters of the earthquakes.
基金funded by the Natural Science Foundation of China(Grant Nos.52079062 and 41807285)the Interdisciplinary Innovation Fund of Natural Science,Nanchang University,China(Grant No.9167-28220007-YB2107).
文摘Most literature related to landslide susceptibility prediction only considers a single type of landslide,such as colluvial landslide,rock fall or debris flow,rather than different landslide types,which greatly affects susceptibility prediction performance.To construct efficient susceptibility prediction considering different landslide types,Huichang County in China is taken as example.Firstly,105 rock falls,350 colluvial landslides and 11 related environmental factors are identified.Then four machine learning models,namely logistic regression,multi-layer perception,support vector machine and C5.0 decision tree are applied for susceptibility modeling of rock fall and colluvial landslide.Thirdly,three different landslide susceptibility prediction(LSP)models considering landslide types based on C5.0 decision tree with excellent performance are constructed to generate final landslide susceptibility:(i)united method,which combines all landslide types directly;(ii)probability statistical method,which couples analyses of susceptibility indices under different landslide types based on probability formula;and(iii)maximum comparison method,which selects the maximum susceptibility index through comparing the predicted susceptibility indices under different types of landslides.Finally,uncertainties of landslide susceptibility are assessed by prediction accuracy,mean value and standard deviation.It is concluded that LSP results of the three coupled models considering landslide types basically conform to the spatial occurrence patterns of landslides in Huichang County.The united method has the best susceptibility prediction performance,followed by the probability method and maximum susceptibility method.More cases are needed to verify this result in-depth.LSP considering different landslide types is superior to that taking only a single type of landslide into account.
