Makoto Nakatsugawa, Tomohide Usutani, Takayuki Miyazaki
Wednesday 1 july 2015
9:00 - 9:15h at North America (level 0)
Themes: (T) Extreme events, natural variability and climate change, (ST) Hydrological extremes: floods and droughts
Parallel session: 8I. Extreme events - Flood Drought
This study addresses risk assessment for sediment disasters based on watershed-wide estimations of soil moisture resulting from long-term hydrologic processes. Sediment disasters have recently occurred throughout Japan due to heavy rainfall and rapid snowmelt. Climate change is expected to exacerbate such disasters in snowy regions, due to global warming. The quantitative evaluation of landslide risk such as that which has occurred at Nakayama Pass in Sapporo, Northern Japan, during the snowmelt season has remained an issue. A method for determining the soil moisture at potential sediment disaster sites was proposed and applied to the Nakayama Pass disaster. This site is in the Hoheikyo Dam watershed and thus is influenced by its hydrologic characteristics. We propose a method to quantitatively estimate soil moisture, which is an important factor in sediment disasters, by using the storage for each mesh as estimated in the distributed hydrologic model of the watershed. In this hydrologic model, snowmelt is estimated on the basis of the heat balance between the snowpack layer and the atmosphere. The storage in each 1-km by 1-km mesh is estimated as the water level of the tank model when rainfall and snowmelt are provided. Then, the total outflow from the watershed is estimated by synthesizing the outflow for each mesh using a channel routing method based on kinematic waves. The validity of the estimated storage is indirectly confirmed by the reproducibility of total outflow from the dam catchment that includes the disaster point. Storage amount at the disaster site was estimated by using the proposed method. It was found that the landslides of 2012 and 2000 occurred at the condition of maximum storage resulting from heavy rainfall, combined with snowmelt. Thus, this study suggested that the storage amount which consists of hydrologic cycle in a catchment area influences large-scale sediment disasters such as landslides. It is believed that the risk of sediment disasters resulting from high soil moisture content can be predicted by combining the distributed hydrologic model, which can consider rainfall as well as snowmelt, with appropriate weather information.