When setting hydrographs for simulating sediment and flood damages in mountainous watersheds, it is critical to consider the effects of the difference in the spatial concentration of precipitation and the way of river channel routing. In this study, we investigated how the 3 factors, that are (1) the type of rainfall data used, (2) the application of spatial variation of rainfall distribution, and (3) the application of flood propagation processes in river channel, affect the runoff calculation of the flood that causes sediment and flood damages. We calculated and analyzed each of the factors mentioned above for the event of the sediment and flood damages of the Uchikawa River in Marumori Town in the northeastern Japan, and discussed the effects of the factors, focusing mainly on the peak discharge and the shape of the hydrograph. Then, it was clarified that (1) the type of rainfall data used and (3) the application of flood propagation processes in river channel to runoff calculation affect both of the peak discharge and the shape of hydrograph, and (2) the application of spatial variation of rainfall distribution had an effect on peak discharge. We compared them with the previous studies and considered the validity of the calculation results.

Surrogate bedload monitoring can be applied to test bed deformation models and to acquire basin sediment runoff characteristics. Japanese pipe hydrophone (JPH) sensors have been deployed in many government-controlled basins; using JPH data, bedloads are typically estimated by calculating the number of pulses with amplitude exceeding a threshold level or by integrating sound pressure with respect to time. However, because there has been no evaluation of the deviation of the latter method, application of bedload flux values based on this method to the purposes mentioned above is limited. In this study, we conducted experiments using natural sediment particles and JPH sensors, and calculated bedloads using the sound-pressure integration method. The deviation of the calculated bedloads was then estimated statistically. The recorded bedloads were found to deviate by approximately one order of magnitude.