Author(s): Makoto Nakatsugawa; Tomohide Usutani; Takayuki Miyazaki
Linked Author(s):
Keywords: Sediment disaster; Snowmelt; Hydrologic processes; Soil Water Index; Water Storage
Abstract: 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. Quantitative evaluation for risk of landslides such as those that have 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 methods to quantitatively estimate soil moisture, which is an important factor in sediment disasters, by using the Soil Water Index (SWI) and Water Storage (WS) estimated as THE water level of the tank model when rainfall and snowmelt are given. Model parameters of the SWI are uniform in all Japan. In contrast, parameters of WS can be changed in depending on watershed characteristics. WS in each 1-km by 1-km mesh is estimated as the water level of the tank model when rainfall and snowmelt are given. 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 WS is indirectly confirmed by the reproducibility of total outflow from the dam catchment that includes the disaster point. Amounts of SWI and WS at the disaster site were estimated, and then it was found that the landslides of 2012 and 2000had occurred under the condition of maximum SWI or maximum WS resulting from heavy rainfall, combined with snowmelt. SWI had slightly underestimated the risk. Thus, this study suggested that the amount of WS based on hydrologic cycle in a catchment area influences large-scale slope disasters such as landslides. It is believed that the risk of slope disasters resulting from high soil moisture content can be predicted by incorporating appropriate weather data into the distributed hydrologic model, which is a model that can consider rainfall as well as snowmelt.
Year: 2015