Mechanism of colluvial landslide induction by rainfall and slope construction:A case study

The landslide hazards occurring in the complex geological genesis accumulation body are usually controlled by the coupling action of many internal and external factors.Therefore,this paper takes the dam-front Danbo accumulation body landslide of Yangfanggou hydropower station on the Yalong River as the geological prototype,and discusses the process and mechanism of slope stability degradation under the combined action of rainfall and slope construction.Based on the detailed understanding of the basic characteristics of the accumulation body,the development characteristics of the landslide and the construction situation of the slope engineering,the study conducted correlation analysis between rainfall and landslide displacement,the physical and mechanical tests of all types of rocksoil masses,and the numerical simulation testing of seepage field variation of the landslide section.It is found that the special slope structure and material composition of the old landslide accumulation layer on the upper part of the Danbo accumulation body are the internal factors for the occurrence of thrust loadinduced landslide,and the construction of the slope engineering not only creates free space conditions for sliding,but also provides channels for the infiltration of rainfall into the slope after confluence,which is an external factor that caused the mechanical properties of the sliding zone soil to gradually weaken from the trailing edge to the leading edge.The geomechanical model of such landslide is that the active section of the trailing edge produces the"source of force",the transition section of the middle section affects the occurrence of sliding,and the anti-sliding section of the leading edge controls the occurrence of landslide hazards.The results of this research provide not only a useful supplement to the theory of landslide formation mechanisms but also a scientific basis for guiding the prevention and control of similar hazards.

Effect of rainfall on a colluvial landslide in a debris flow valley

A colluvial landslide in a debris flow valley is a typical phenomena and is easily influenced by rainfall. The direct destructiveness of this kind of landslide is small, however, if failure occurs the resulting blocking of the channel may lead to a series of magnified secondary hazards. For this reason it is important to investigate the potential response of this type of landslide to rainfall. In the present paper, the Goulingping landslide, one of the colluvial landslides in the Goulingping valley in the middle of the Bailong River catchment in Gansu Province, China, was chosen for the study. Electrical Resistivity Tomography(ERT), Terrestrial Laser Scanning(TLS), together with traditional monitoring methods, were used to monitor changes in water content and the deformation of the landslide caused by rainfall. ERT was used to detect changes in soil water content induced by rainfall. The most significant findings were as follows:(1) the water content in the centralupper part(0~41 m) of the landslide was greaterthan in the central-front part(41~84 m) and(2) there was a relatively high resistivity zone at depth within the sliding zone. The deformation characteristics at the surface of the landslide were monitored by TLS and the results revealed that rainstorms caused three types of deformation and failure:(1) gully erosion at the slope surface;(2) shallow sliding failure;(3) and slope foot erosion. Subsequent monitoring of continuous changes in pore-water pressure, soil pressure and displacement(using traditional methods) indicated that long duration light rainfall(average 2.22 mm/d) caused the entire landslide to enter a state of creeping deformation at the beginning of the rainy season. Shear-induced dilation occurred for the fast sliding(30.09 mm/d) during the critical failure sub-phase(EF). Pore-water pressure in the sliding zone was affected by rainfall. In addition, the sliding L1 parts of the landslide exerted a discontinuous pressure on the L2 part. Through the monitoring and analysis, we conclude that this kind of landslide may have large deformation at the beginning and the late of the rainy season.

Uncertainties of landslide susceptibility prediction considering different landslide types

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.