Abstract

Heavy precipitation accompanied by a typhoon and a seasonal rain front fell over the main island of Japan on 9–11 September 2015, causing severe damage due to landslides and river flooding. In the Kanto and Tohoku regions, some automated meteorological data acquisition system observatories recorded high precipitation rates; rainfall on the first 2 days of the disaster (9–10 September) was more than twice the average monthly rainfall in September 1981–2010. The rainfall, known as the Kanto-Tohoku heavy rain, triggered shallow landslides on a relatively gentle hillslope behind some residences in Kanuma city, Tochigi Prefecture. The source areas of the landslides appeared neither along a clear longitudinal hollow nor around a transverse concave. To reveal the geophysical features affecting the induction of shallow landslides, seismic and electrical resistivity surveys were conducted. Portable cone penetration tests and soil sampling were also carried out to determine the physical properties of the soil. For surface geophysical surveys, a longitudinal survey line was situated on the left bank of a shallow landslide to measure the surface geophysical properties of the landslide area, based on the assumption that the slope next to the landslide has the same properties as the landslide area. Also, two transverse survey lines were situated just upslope of two shallow landslides to capture lateral variations in surface geophysical properties between the landslide and the area around the landslide. Topsoil in the source areas exhibited lower S-wave velocity, higher electrical resistivity, greater soil depth, and lower dry bulk density than soil along other parts of the survey line. These features indicate that the topsoil in the source area was composed of loose relatively deep sand and could be considered to be potentially susceptible to rainfall-induced landslides. Thus, combining surface geophysical surveys with other methods, such as airborne surveys and satellite observations, to detect landslide-prone zones in vast areas may effectively locate areas that do not initially appear different from their surroundings but are high risk of landslides.

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