Deep-seated landslides generate seismic signals that can be used to determine their magnitude and location. Establishing a numerical approach for calculating the generation and propagation of ground vibrations would improve the estimation of landslide properties. In this study, a numerical model coupling 3D particle flow and the continuum model was developed to calculate the landslide movement and subsequent propagation of seismic signals over large areas. Two sediment transport scenarios were considered for the deep-seated landslide that occurred in 2011 in Akadani, Gojo City, Nara Prefecture. After the landslide in the model, a low-frequency (0.01-0.1 Hz) signal was received at a seismic station located 34.4 km apart. The simulation results adequately reproduced the signals observed when the landslide was assumed to be in two blocks rather than one. At the generation of ground vibrations caused by sediment transport, it was confirmed that the scenario of sediment transport affects the amplitude of ground vibration at low frequency in despite of the same sediment volume. Particle motion during sediment movement result of the simulation results around deep-seated landslide slope is bigger at upper points than lower ones. In particular, the direction of low-frequency horizontal displacement during sediment movement in the simulation coincided with the direction at the distant observation point, supporting that the direction of sediment movement can be estimated. On the other hand, a high-frequency (>about 1 Hz) signal was not represented on this study. More smaller mesh model or including the effect of water might be taken into account to simulate a high-frequency signal. It is an issue for the future.

In this study, we propose a method to estimate the peak discharge of debris flow by surveying debris flow traces using digital elevation model (DEM) and DEM of difference (DoD) generated from airborne LiDAR data. The accuracy of the DoD was affected by slope and point density. In particular, areas with slopes greater than 40°or point densities less than 10 points / 25 m² showed an increase in the DoD error, with the error of at least 0.2-0.3 m. When areas with topographic changes greater than the DoD error were considered as trace areas, these areas were close to the areas considered by conventional field survey. Hence, it is likely that topographic changes beyond the DoD error have occurred in the area where debris flow occurred. At the survey points in this study, we considered areas where the topographic change on the DoD was 0.2-0.4 m or greater as trace areas. When peak discharges were estimated from these trace areas, the probability that peak discharges were in the range of half to twice that of conventional field surveys was about 50%. Furthermore, the probability was about 70%, when peak discharges were estimated only from the survey points where the superelevation was 1 m or higher. In the future, it is necessary to study the method of setting the radius of curvature and to verify the validity of the results of estimating flow velocity and peak discharge.

SABO facilities require daily maintenance, and maintenance plans are necessary considering life cycle costs. Changes in socio economic conditions have necessitated improvements in social and public services and the advancement of businesses, organizations, processes, and working styles within the construction industry. Digital transformation (DX) can help to improve safety, security, and prosperity within the construction industry. When maintaining SABO facilities, it is important to clarify specific policies for life cycle cost reductions in the form of short term numerical targets, using new technologies related to inspections, repairs, and cost reduction effects. To facilitate DX in the infrastructure field, the introduction of BIM/CIM (Building/Construction Information Modeling) promotes design verification, visualization of construction plans, and efficiency improvement. Furthermore, safety and labor savings are supported in terms of construction and maintenance performed using unmanned construction and aerial vehicles. In particular, in the field of SABO, the development of new technologies related to topographical analysis, performance verification of structures, monitoring, data collection/analysis/transfer, etc. is expected. Here, we present an overview of an our SABO maintenance system and propose the development of a new system through DX. By introducing the basics of the maintenance system that has been built to date, we expect that the maintenance of SABO facilities that utilize DX will be further enhanced using the findings of this study.