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Yoshinori Yajima, Public Works Research Institute (Japan)
Yasuhito Sasaki, Public Works Research Institute (Japan)
Toshiyuki Kurahashi, Public Works Research Institute (Japan)
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About 70% of Japan?fs land area is mountainous. Weak geological features and the pluvial climate cause frequent slope disasters that may damage national roads. Inspections and measures without overlooking the road slopes are necessary to reduce road damage from slope disasters. However, there are 54,000 kilometers of national roads alone in Japan (the total length of all roads exceeds one million km), so there are also huge numbers of road slopes. Therefore, for countermeasures to be effective, priority sections must be appropriately screened, which requires a macro risk evaluation based on the accumulation and analysis of data on past slope disasters in each section. Therefore we used a road slope disaster database to clarify the geological and topographical features where disasters tend to occur. The database includes information on 1,310 slope disasters on designated sections of national roads (those directly managed by the Ministry of Land, Infrastructure and Transport) in Japan from April 1990 to December 2004. From the results of the disaster analysis, we developed a geological risk map for road slope hazards that shows the potential risk of road slope disasters.
The risk map was made for the Kyushu region in southwest Japan. This region has various geological characteristics that make it susceptible to disaster, such as Shirasu pumiceous deposit of volcanic origin, and is often struck by typhoons and local severe rain. Therefore, many slope disasters tend to occur in Kyushu. During 1990-2004, 645 road slope disasters occurred in Kyushu; the disaster frequency (case/km/15 years) is about nine times the average for other areas.
Road slope disaster risk is expressed as the product of the disaster occurrence coefficient based on geological features (Cg), by disaster occurrence coefficient based on topographical features (Ct). In our calculations, first we identified the slope angle and geological features along national roads and disaster locations using the 50-m mesh DEM and a 1/1,000,000 geological map, and calculated the occurrence frequency (case/10 km/15 years) for geological and slope angle classification. We then obtained Cg and Ct by dividing each occurrence frequency by the average occurrence frequency for the whole of Kyushu. This risk map was made based on disaster factors such as geological and topographical features. If the disaster occurrence coefficient (Cr) caused by the amount of rainfall as a trigger is added to this map, it may be possible to evaluate the disaster risk based on differences in the amount of rainfall.
The map shows the approximate risk of road slope disaster based on disaster experiences. It could be used to screen countermeasure priority sections and inspection sections by adding road information such as traffic volume and detours. Additional disaster information for statistical analysis needs to be gathered to improve the reliability of this risk map.
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