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Landslide dams are formed mostly in V-shaped valleys, with poor stability and a high risk of failure. Once landslide dams fail, they may cause floods or debris flows that endanger lives, property, and infrastructure downstream. Therefore, it is important to evaluate the stability immediately once a landslide dam is formed. The geometry of a landslide dam is the most critical to its stability assessment. However, the complex terrain and geomorphological conditions in the disaster area often make field surveys difficult. Aerial photography and satellite imagery technology are usually limited by poor weather conditions, which bring severe restrictions to the timely acquisition of the geometry of a landslide dam. In this paper, a discrete element simulation model was proposed and verified by two experiments, and then a series of numerical simulations were performed to investigate the geometry and formation process of landslide dams under different topographic factors including the motion path dip-angle, the river bed inclination, and the angle between valley slopes (valley angle). The results show that the geometry and formation process of landslide dams are significantly affected by the topographic factors. According to the results of comprehensive numerical analysis, a simple predictive model for landslide dam geometry in V-shaped valleys was established, and two landslide dams with data collected from early events were employed to validate the predictive model. Based on the easily accessible topographical factors, the proposed model accomplished the fast prediction of landslide dam geometry. This research provides a vital basis for the stability evaluation of landslide dams and can be used for the disaster emergency response before the dams break. [ABSTRACT FROM AUTHOR]

This study is a revised inventory of landslides triggered by the Rudbar-Manjil earthquake (Mw = 7.3), 1990, obtained through the study of Komak Panah and Hafezi Moghadas (1993), interpretations of the stereoscopic aerial photos, and field data. We mapped the 223 coherent landslides with a total area of 11.3 km2 and a calculated volume of 3.8 × 108 m3 using a digital elevation model (DEM, 12.5 m) within the geographical information system (GIS) software. The correlation between landslide occurrence (size and distribution) and the controlling factors was analyzed using the bivariate model and the linear automated modeling (LINEAR) procedure in the SPSS software. Both LINEAR models of landslide volume (LV, m3) and landslide area (LA, m2) indicate the distance from the fault surface rupture is the most influencing factor on size prediction of coseismic landslides. The LA is more dependent on seismic factors, whereas the LV is on the lithology and topographic factors. The result of principal component analysis (PCA) model, using the GIS, showed that most landslides occurred in the red band (including 95% of the variance of controlling factors). Thus, the selected factors to investigate the landslide occurrence are valid and the PCA can be used to identify regions prone to coseismic landslides. The curves of landslide number density (LND, landslides/km2), landslide area percentage (LAP, landslide area/total area%), LA, and LV have a multimodal distribution (several patterns of response) by the topographic and seismic factors. It is recommended that other models be applied to better investigate the local effects of factors on the coseismic landslides. [ABSTRACT FROM AUTHOR]

The article presents the authors comments on the research study on the performance of the susceptibility model debris than the rock fall/rockslide susceptibility model in susceptibility maps in Canada. The authors evaluates the landslide susceptibility mapping for land-use planning, hazard mitigation and disaster management. The authors also discusses the importance of preparation of a landslide inventory for future failures.