|Budget Amount *help
¥4,400,000 (Direct Cost: ¥4,400,000)
Fiscal Year 1993: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1992: ¥2,900,000 (Direct Cost: ¥2,900,000)
The watershed management is to make plans for constructing banks, erosion control dams, and stream-bed regulators so that human and material damages which may possibly be inflicted by debris flows can be averted. In order to make such plans, it is essential to estimate the amount of sediments on the stream bed and to understand the made of their movements. Sediments are mainly supplied from landsliding on the mountain slope and river banks. Consequently, it is very important to estimate the amount of debris supply to the stream bed from landsliding. For this purpose, we have to construct a landslide susceptibilty map, with which to estimate the amount of debris supply. In turn, we have to know the terrain elements which affect landsliding in order to map the landslide susceptibilty of mountain slopes.
On this premise, we analyzed terrain elements affecting landsliding in Inamata Valley, the largest tributary of Amahata River, located in Yamanashi Prefecture. Vegetation, slope gradient,
azimuth, slope froms (convexity and profiles) are among the most critical elements. Since vegetation changes with time, naturally and artificial, it was excluded from elements for the mapping. A landslide susceptibility map was constructed from superimposing maps of slope gradient, azimuth and slope forms which were digitized by a color drum scanner. The scores were assigned to each categories of elements and based on the total score, the slope unit was first classified as the unstable or the stable, each of which were further subdivided into two categories based on the probability, making a total of four categories.
In the Omichi Valley of Tedori River, Ishikawa Prefecture, we utilized DTM (Digital Terrain Model) to compute slope gradient, azimuth, and elevation, We also constructed a stream map from topographic maps, which was subsequetly digitized. We also digitized the existing geologic, vegetation and soil maps. Using these factors, we run a statistical analysis and extracted the terrain elements affecting landsliding. Superimposing digitally these elements, we produced a landslide susceptibility map of the area, comprising of the unstable (two subcategories) and the stable (two subcategories) categories. Checking this map with the existing landslides, it was found that about 70% of the landslide fell into the category of the unstable. Less