Abstract
Abstract. Reconstructions of failure surfaces (prior to potential landslides or after their release), landslide deposits, or other palaeotopographic features are important for hazard and erosion assessment. The volumes involved in landslide and failure surfaces constrain the propagation of a landslide, and knowledge of the past topography helps us to understand these hazards. Some methods exist to characterise landslide geometry, but these methods usually require monitoring information. This study tries to assess the validity of the sloping local base level (SLBL) method for this purpose. Two sets of airborne lidar digital elevation models (DEMs) of the Kii Peninsula (Japan) are used: the first one was acquired before Typhoon Talas, and the second one was acquired after. A total of 70 deep-seated landslides occurred during this event between 2 and 5 September 2011. This study shows that the SLBL method is efficient using either the slope deformations identifiable on the DEM before the release of the landslide or a reliable 2.5-D failure surface created by using both DEMs (the 2.5-D corresponds to a surface which has only one z value for each x–y coordinate; in other words, no true vertical topography or overhang can be represented perfectly). In addition, this method allows for the reconstruction of eroded deposits and buried valleys. Most of the volumes estimated are within ±35 % of the estimation made by Chigira et al. (2013), and the coefficients of expansion range from 10 % to 25 %. These results show considerable sensitivity to the parameters used for the reconstruction of the landslide volume estimations and demonstrate the need for an efficient and fast tool to reconstruct potential landslide geometries or histories.
Highlights
Landslides represent an important underestimated threat for society
The volumes can be estimated based on a digital elevation model (DEM) and the assumptions made about the failure surface geometry
We explore the capability of the sloping local base level (SLBL) method to provide models of the 3D failure surfaces of landslides based on DEMs (Jaboyedoff and Derron, 2005; Jaboyedoff et al, 2009)
Summary
Landslides represent an important underestimated threat for society. From 2014 to 2010, 32 322 fatalities occurred worldwide caused by non-seismic landslides (Petley, 2012). Many landslides are the cause of deaths during typhoons (see below) and earthquakes. The coseismic landslides of the Wenchuan earthquake killed more than 20 000 people in 2008 (Tang and van Westen, 2018). Assessing landslide volumes is important for both sedimentary budget calculations (Hovius et al, 1997) and for hazard assessment by providing volume frequency distributions (Dussauge-Peisser et al, 2002). The volumes can be estimated based on a digital elevation model (DEM) and the assumptions made about the failure surface geometry. We present here a method to estimate landslide volumes
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