Influence of landslide depth and geology on α‐ and γ‐parameters in the landslide volume estimation equation:
A case study of sediment disasters caused by the August 2014
heavy rainfall in the Tamba and Hiroshima areas, western Japan
Hiromi AKITA Tsuyoshi WAKATSUKI
Abstract
The method for estimating the sediment volume of landslide using the landslide area is expected to be useful for wide‐area damage assessment immediately after sediment disaster. In this study, we calculated the sediment volume of landslide (V) from elevation changes in LiDAR DEMs before and after the disaster in mountainous areas underlain by6different geological materials in Tamba City, Hyogo Prefecture and Hiroshima City, Hiroshima Prefecture. We investigated the influence of both landslide depth and basement geology on α‐and γ‐parameters in the landslide volume estimation equation, i.e., V=αA^γ, where A is landslide area, and we compared the parameters in this study with those in previous studies. The results showed high correlations between the landslide area and the sediment volume in each geology. A negative correlation was shown between the α‐and γ‐values, with the γ‐value increasing as the ratio of the landslide depth to the landslide area increased. Igneous rocks (Hiroshima granitic rocks, Takada rhyolites and Hikimi group rhyolite welded tuff, gabbroic rocks) had larger α‐values and smaller γ‐values because of small increasing ratio in landslide depth to the landslide area. Sedimentary rocks (Tamba belt shale, ultra‐Tamba belt sandstone, Karita and Kuga formation mudstone) had a wide range of α‐and γ‐values because the landslide depths change largely due to lithology. Metamorphic rocks (Hornfels, Biotite‐gneiss, Green hornblende amphibolite) had smaller α‐values and larger γ‐values. The sediment volumes of landslides estimated using the α‐and γ‐values proposed by Guzzetti et al. (2009) and Larsen et al. (2010) were smaller than the actual volume in these study areas.
Key words
Sediment volume, Landslide depth, Igneous rocks, Sedimentary rocks, LiDAR DEMs