Landslides

Huangtupo landslide, volumetrically the largest, most complex landslide in the Three Gorges Reservoir region of China, is a dangerous mass on which the district of Badong has been inadvertently situated. Risk remediation efforts include the construction of a large observational tunnel and monitoring system that are unique in the world. This tunnel and its side branches permit detailed mapping of its 3D structure while providing samples for laboratory analysis. The new investigations validate that the Huangtupo landslide is a composite of several independent landslides and that movement occurs along the major rupture zones as well as on interlayer sliding zones in the underlying Badong Formation. Uranium–thorium disequilibrium dating establishes that the northern part of the landslide, called the Riverside Slump, underwent at least two periods of movement at about 100 and 40 ka (ka stands for a thousand years). These events were induced by the steep slope created by the downcutting of the Yangzte River. The results from in situ displacement monitoring over a 7-year period confirm that the central part of the landslide is creeping at a slow, relatively stable rate of about 15 mm/year rather than being in a stage of acceleration under the protection of anchored concrete beams and other defense structures at its toe. Available data suggest that engineering measures can control the independent landslides that together constitute the huge Huangtupo mass, which will avoid the need for costly relocation of thousands of people.

An analysis of landslide occurrence in the low permeability terrain of Porretta-Vergato, Italy, related to prolonged rainfall patterns is presented. Data sets collected over nearly a century are statistically analysed. The pattern of the landslide hazard is considered and related to precipitation at the basin scale in order to enhance the understanding between the two parameters and assess their temporal changes, as well as interrelationships. Landslide incidence generally follows the periodic pattern of precipitation with a lag of approximately six months, which is believed to relate to the time necessary for the ground water to reach a critical level to initiate slope failure. There also appears to be a two-stage pattern of precipitation which induces most landslides: a preparatory period, where the landslide is destabilized and conditioned for slope failure, followed by a more intense period of rainfall that triggers or provokes the event. These initial findings point to the need for further studies to verify such unstable situations.

A high-position destructive rockfall, significantly influenced by post-seismic effect of Wenchuan earthquake in 2008 and associated aftershocks, was reported in Miansi Town of Wenchuan County, Sichuan Province, China. About 3,000 m3 of rock at high position detached from a dipping rocky slope, which manifested as a translational motion. Detailed field investigation, geological mapping, kinematic analysis, and numerical modelling are presented to comprehensively analyze the complex failure mode of the post-seismic rockfall. The results demonstrated that the sliding surfaces are mainly controlled by the internal shear discontinuity sets. The backscarps are progressively evolved from the tensile cracks at rear slopes caused by the Wenchuan earthquake. Because of the combination effect of heavily shocks of previous earthquake and local geomorphology of the rockfall with beneficial for facilitating the magnification effect on peak ground acceleration (PGA), the rock mass of slopes is dramatically damaged and fractured. The original intact slopes finally developed to the shattered slopes as an optimum birthplace for the post-seismic rockfalls. It should be noticed that intensive precipitation plays a triggering factor that generates the hydrostatic water pressure in the rear cracks and the uplift pressure at the bottom sliding surface within a short time. The evolution processes are divided into three stages: slope relaxation stage, rock shattering and disaggregation stage, and high-speed falling stage. Velocities, energy, and bounce heights of falling rock blocks are computed by the RocPro3D software for understanding the corresponding kinematics. The paper can provide an insight into post-seismic rockfalls in the tectonic areas associated with the combination of seismic activities and intense rainfall.

In this paper, the effect of cyclic loading on drained residual strength of over-consolidated silty clay is examined based on the results from ring shear tests which were conducted with a sophisticated ring shear apparatus. Initially sheared to form shear zones under different pre-consolidation pressures and at different shear rates (SRs), soil samples were then tested under cyclic loading. After the cyclic loading application, the samples were re-sheared while the corresponding shear strengths were measured. The results show that the effect of cyclic loading on residual strength is noticeable. The effect is related to pre-consolidation history and SR of the soil samples. Under conditions of relatively low over-consolidation ratio (OCR), the soil samples show an increase in residual strength with decreasing SR after cyclic loading. Most of the peak strength values after cyclic loading are higher than the residual strength values obtained before cyclic loading. Two effects of cyclic loading on the residual strength are identified: (a) If OCR is less than or equal to 3.0, the residual strengths measured after cyclic loading are larger than those before cyclic loading; (b) If OCR is greater than or equal to 3.5, the residual strengths after cyclic loading tend to become lower than those in the shear tests before cyclic loading.

The 2010 Mw = 8.8 Maule earthquake, which occurred in the subduction contact between the Nazca and the South American tectonic plates off the coast of Chile, represents an important opportunity to improve understanding of the distribution and controls for the generation of landslides triggered by large megathrust earthquakes in subduction zones. This paper provides the analysis of the comprehensive landslide inventory for the Maule earthquake between 32.5° S and 38.5° S. In total, 1226 landslides were mapped over a total area of c. 120,500 km2, dominantly disrupted slides. The total landslide volume is c. 10.6 Mm3. The events are unevenly distributed in the study area, the majority of landslides located in the Principal Andean Cordillera and a very constrained region near the coast on the Arauco Peninsula, forming landslide clusters. Statistical analysis of our database suggests that relief and lithology are the main geological factors controlling coseismic landslides, whilst the seismic factor with higher correlation with landslide occurrence is the ratio between peak horizontal and peak vertical ground accelerations. The results and comparison with other seismic events elsewhere suggest that the number of landslides generated by megathrust earthquakes is lower than events triggered by shallow crustal earthquakes by at least one or two orders of magnitude, which is very important to consider in future seismic landslide hazard analysis.

Interferometric synthetic aperture radar (InSAR) has gained considerable attention as a landslide monitoring strategy owing to its high accuracy, large coverage, and relatively low associated costs. A crucial drawback of InSAR, however, has limited its further incorporation: one-dimensional estimations along the sensor’s line-of-sight (LOS). This leads to an ambiguity in results and a less intuitive understanding of landslide kinematics. A frequently exercised approach to address this issue has been taking inspiration from the topography to establish compatibility assumptions between velocity components, yet little insight exists on the performance of these methods. The objective of this paper is to investigate the performance of four renowned topography-based methods—Surface Parallel Flow Model (SPFM), SPFM coupled with least-squares method (SPF-LSM), Aspect Parallel Flow Model (APFM), and Steepest Terrain Following Model (STFM)—in evaluating the magnitude and geometry of total velocity vectors. To this end, the analysis is performed on 202 Radarsat-2 and 243 Sentinel-1 scenes acquired over a section of the Thompson River valley, a critical railway corridor in Western Canada traversing 14 landslides. The results indicate that the APFM provides estimations with the lowest magnitude error (15–19 mm/yr or 18.75–23.75% of in situ measurements) compared to the other approaches. SPFM and SPF-LSM are highly sensitive to LOS variance and tend to bias the interpreted vectors toward the north orientation. However, APFM and STFM reflect more realistic aspect angles, with the former inclined to steeper travel angles and the latter suffering from erratic upward travel angles due to local topographies.

Landslides in Himalaya cause widespread damage in terms of property and human lives. It the present study, an attempt is made to derive information on causative parameters and preparation of landslide-susceptible map using fuzzy data integration in one of the seismically active region of Garhwal Himalaya that was recently devastated by a huge landslide. High-resolution remotely sensed data products acquired from Indian Remote Sensing Satellite before and after the landslide event were processed to improve interpretability and derivation of causative parameters. Spatial data sets such as lithology, rock weathering, geomorphology, lineaments, drainage, land use, anthropogenic factor, soil type and depth, slope gradient, and slope aspect were integrated using fuzzy gamma operator. The final map was reclassified in to five classes such as highly to lowly susceptible classes based on cumulative cutoff. The result shows around 72% of known landslide areas including the large Uttarkashi landslide in the high and very high susceptibility classes comprising of only 37% of the total area. The precipitation data from ground- and satellite-based observations were compared; the precipitation threshold and the role of seismic activity were analyzed for initiation of landslide.

Thermokarst landslides (TL) caused by the thaw of ground ice in permafrost slopes are increasing on the Qinghai-Tibet Plateau (QTP), but the understanding of the spatially suitable environmental conditions including terrains and climate for them has not been fully established. Here, we applied multiple machine learning models and their ensemble to explore factors controlling the TL and map its susceptibility at a fine resolution. The models were calibrated and validated using a split-sample approach based on an inventory of TLs from the remote sensing data. The models indicated that summer air temperature and rainfall were the most two important factors controlling the occurrence and distribution of TLs, provided that other geomorphic conditions (i.e., slope, solar radiation, and fine soil) were suitable. The final ensemble susceptibility map based on downscaled climate data and terrain data suggested that ca. 1.4% of the QTP land was classified in high- to very high-susceptibility zone, which is likely to increase in response to future climate change. This study integrated local topography and climate in susceptibility modeling and provided new insights into the geomorphic sensitivity to climate change but also the engineering support over the QTP.