This case study is about a landslide that occurred after 4 days of heavy rainfall,in the morning of June 29,2012,in Cengong County,Guizhou Province of China,geographical coordinated 108°20′-109°03′E,27...This case study is about a landslide that occurred after 4 days of heavy rainfall,in the morning of June 29,2012,in Cengong County,Guizhou Province of China,geographical coordinated 108°20′-109°03′E,27°09′-27°32′N,with an estimated volume of 3.3×106 m3.To fully investigate the landslide process and formation mechanism,detailed geotechnical and geophysical investigations were performed including borehole drilling,sampling,and laboratory tests coupled with monitoring of displacement.Also,a combined seepage-slope stability modeling was performed to study the behavior of the landslide.After the heavy rainfall event,the sliding process started in this area.The landslide development can be divided into different parts.The man-made fill area,spatially distributed in the south side of the landslide area with low elevations,slid first along the interface between the slope debris and the strongly weathered bedrock roughly in the EW direction.Consequently,due to severe lateral shear disturbance,the slope in the main sliding zone slid next towards the SW direction,along the sliding surface developed within the strongly weathered calcareous shale formation located at a depth of 25-35 m.This means it was a rainfall triggered deep-seated landslide.Finally,retrogressive failure of a number of upstream blocks occurred,which moved in more than one direction.The initial failure of the man-made fill area was the‘engine’of the whole instability framework.This artificial material with low permeability,piled up in the accumulation area of surface and sub-surface and destroyed the drainage capacity of the groundwater.The numerical modeling results agreed with the analysis results obtained from the laboratory and field investigations.A conceptual model is given to illustrate the formation mechanism and development process of the landslide.展开更多
Objective The 2014 Ludian Mw6.1 earthquake in Yunnan occurred in a mountainous area with complex tectonics and topography, which caused serious damage as well as co-seismic landslides of an unusual large scale. Becau...Objective The 2014 Ludian Mw6.1 earthquake in Yunnan occurred in a mountainous area with complex tectonics and topography, which caused serious damage as well as co-seismic landslides of an unusual large scale. Because the suspected seismogenic faults on the surface, distribution of aftershocks and focal mechanism solutions are not consistent, it remains difficult to determine what is the real causal fault or seismogenic structure for this event. Actually, it may imply the complicity of the seismic source at depth. In addition, the distribution of the co- seismic landslides also exhibits some diffusion that is different from general eases, likely associated with the seismic focus structure.展开更多
This paper analysed the evolution of landslide research and research foci in different countries. The data comprise 3105 landslide SCI articles published between January 1977 and June 2015 from the Web of Science. The...This paper analysed the evolution of landslide research and research foci in different countries. The data comprise 3105 landslide SCI articles published between January 1977 and June 2015 from the Web of Science. The data are extracted under interaction constraints of the journal title, category, and keywords. The complex network method is used for the analysis. First, from the perspective of topics and methods, the evolution is systematically assessed by generating a co-citation network of the articles and a semantic cluster analysis. Second, from the perspective of topics and landsliderelated disasters, the focus in different countries is discussed by generating co-occurrence networks. These networks are the co-occurrence of the countries and keywords, and the co-occurrence of countries and landslide-related disaster phrases. The main conclusions are as follows:(1) landslide susceptibility analysis and methods of machine learning are popular research topics and methods, respectively. The topics change through time, and the article output is influenced by increasing landslide-related disasters, increasing economic losses and casualties, a desire for a more complete and accurate landslide inventory, and the use of effective methods, such as geographical information Science(GIS) and machine learning.(2) The research focus in each country is related with the country-specific disasters or economic costs caused by landslides to some degree. In addition to Italy and the USA, China is the country most commonly affected by landslides, and it should develop its own landslide database and complete in-depth studies of disaster mitigation.展开更多
During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to inv...During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on?dynamic landslides were studied. Both macroscopic analysis on slope?landslide?and mesoanalysis on structure evolution of contact networks, including the?average degree, clustering coefficient?and N-cycle, were done during the process?of landslide. The analysis results demonstrate that: 1) with increasing inter-particle?frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle;2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller,?the average degree there changes more greatly with increasing inter-particle?frictional coefficient;3) during the initial stage of landslide, the clustering coefficient?reduces sharply, which may leads to easily slide of slope. As the landslide?going?on, however, the clustering coefficient?increases denoting increasing stability?with?increasing inter-particle frictional coefficients. When the inter-particle?frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient?and stable inclination of slope post-failure greatly;and 4) the number of?3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.展开更多
基金financed by the Research Foundation of SKLGP(Nos.SKLGP2015Z014,SKLGP2016Z013,SKLGP2016Z018)the SKLGP and CDUT for providing a scholarship to conduct a part of the reported research at the University of Arizona as a Visiting Research scholar
文摘This case study is about a landslide that occurred after 4 days of heavy rainfall,in the morning of June 29,2012,in Cengong County,Guizhou Province of China,geographical coordinated 108°20′-109°03′E,27°09′-27°32′N,with an estimated volume of 3.3×106 m3.To fully investigate the landslide process and formation mechanism,detailed geotechnical and geophysical investigations were performed including borehole drilling,sampling,and laboratory tests coupled with monitoring of displacement.Also,a combined seepage-slope stability modeling was performed to study the behavior of the landslide.After the heavy rainfall event,the sliding process started in this area.The landslide development can be divided into different parts.The man-made fill area,spatially distributed in the south side of the landslide area with low elevations,slid first along the interface between the slope debris and the strongly weathered bedrock roughly in the EW direction.Consequently,due to severe lateral shear disturbance,the slope in the main sliding zone slid next towards the SW direction,along the sliding surface developed within the strongly weathered calcareous shale formation located at a depth of 25-35 m.This means it was a rainfall triggered deep-seated landslide.Finally,retrogressive failure of a number of upstream blocks occurred,which moved in more than one direction.The initial failure of the man-made fill area was the‘engine’of the whole instability framework.This artificial material with low permeability,piled up in the accumulation area of surface and sub-surface and destroyed the drainage capacity of the groundwater.The numerical modeling results agreed with the analysis results obtained from the laboratory and field investigations.A conceptual model is given to illustrate the formation mechanism and development process of the landslide.
基金supported by the National Natural Science Foundation of China(grant No.41572194)the Institute of Geology,China Earthquake Administration(grant No.IGCEA1604)the National Key Basic Research Program of China(grant No.2013CB733205)
文摘Objective The 2014 Ludian Mw6.1 earthquake in Yunnan occurred in a mountainous area with complex tectonics and topography, which caused serious damage as well as co-seismic landslides of an unusual large scale. Because the suspected seismogenic faults on the surface, distribution of aftershocks and focal mechanism solutions are not consistent, it remains difficult to determine what is the real causal fault or seismogenic structure for this event. Actually, it may imply the complicity of the seismic source at depth. In addition, the distribution of the co- seismic landslides also exhibits some diffusion that is different from general eases, likely associated with the seismic focus structure.
基金under the auspices of National Key Research and Development Plan of China (Grant No. 2017YFB0504102)the Fundamental Research Funds for the Central Universities
文摘This paper analysed the evolution of landslide research and research foci in different countries. The data comprise 3105 landslide SCI articles published between January 1977 and June 2015 from the Web of Science. The data are extracted under interaction constraints of the journal title, category, and keywords. The complex network method is used for the analysis. First, from the perspective of topics and methods, the evolution is systematically assessed by generating a co-citation network of the articles and a semantic cluster analysis. Second, from the perspective of topics and landsliderelated disasters, the focus in different countries is discussed by generating co-occurrence networks. These networks are the co-occurrence of the countries and keywords, and the co-occurrence of countries and landslide-related disaster phrases. The main conclusions are as follows:(1) landslide susceptibility analysis and methods of machine learning are popular research topics and methods, respectively. The topics change through time, and the article output is influenced by increasing landslide-related disasters, increasing economic losses and casualties, a desire for a more complete and accurate landslide inventory, and the use of effective methods, such as geographical information Science(GIS) and machine learning.(2) The research focus in each country is related with the country-specific disasters or economic costs caused by landslides to some degree. In addition to Italy and the USA, China is the country most commonly affected by landslides, and it should develop its own landslide database and complete in-depth studies of disaster mitigation.
文摘During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on?dynamic landslides were studied. Both macroscopic analysis on slope?landslide?and mesoanalysis on structure evolution of contact networks, including the?average degree, clustering coefficient?and N-cycle, were done during the process?of landslide. The analysis results demonstrate that: 1) with increasing inter-particle?frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle;2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller,?the average degree there changes more greatly with increasing inter-particle?frictional coefficient;3) during the initial stage of landslide, the clustering coefficient?reduces sharply, which may leads to easily slide of slope. As the landslide?going?on, however, the clustering coefficient?increases denoting increasing stability?with?increasing inter-particle frictional coefficients. When the inter-particle?frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient?and stable inclination of slope post-failure greatly;and 4) the number of?3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.
