詳細地形の影響を考慮したメソα スケールの気象現象時間の降雨量予測に基づく土砂災害（土石流）警戒判定について

抄録

Sediment disasters are often caused by rainfall. However, the occurrence of rainfall sufficient to cause a sediment disaster requires the convergence and rise of moist air in a certain area and its continuous supply and cooling. Typical sources of moist air are typhoons and fronts. In both cases, it is known that topographic factors lead to the convergence and rise of a warm and wet air flow and amplification of rainfall (orographic rainfall). This amplification effect may cause rainfall to the extent that a sediment disaster occurs. Therefore, in order to predict the rainfall that causes a sediment disaster, it is indispensable to examine weather models that reflect the detailed topography and take the influence of topography into consideration. In this research, focusing on the relationship between topography and rainfall that caused sediment disasters in the basin of the Kanna and Kabura River, the basin of the Uono River, and the upper basin of the Yoshino River from the above mentioned viewpoint, the rainfall prediction is performed by using the WRF weather model, which can express detailed topography with 1 km-mesh, using the time corresponding to seasonal rain fronts, typhoons, or other meso-α-scale phenomena that frequently caused sediment disasters as the prediction time and the GPV of MSM (every 3 hours in 39 hours (meso-α time)) published by the Japan Meteorological Agency as the initial and boundary conditions. In addition, the results are applied to CL and potential rainfalls that might cause a sediment disaster (a debris flow) are assessed. As a result, it was confirmed that the values predicted by WRF exceeded CL, half a day to 1 day (meso-α time) before the occurrence time of 4 debris flow disasters in the above 3 basins. However, it was also confirmed that any values predicted by MSM did not exceed CL within this period of time. Although this result does not mean that it is possible to assess the sediment disaster alert risk in meso-α time for all rainfalls, it does imply a way for technology to predict the sediment disaster alert risk based on rainfall prediction in meso-α time with WRF.