Debris Flow Simulation by Applying the Hyper KANAKO System for Water and Sediment Runoff from Overtopping Erosion of a Landslide Dam

Abstract

Large-scale sediment-related disasters have been increasing in recent years [Uchida et al., 2009;Inoue and Doshida, 2012], such as the deep-seated catastrophic landslides caused by Typhoon Talas (T1112) in the Kii Peninsula, southwest Japan, in 2012. The formation and collapse processes of landslide dams strongly influence water and sediment runoff. When a large-scale landslide dam collapses, the peak discharge of downstream flooding can sometimes become several times as large as the inflow discharge upstream. Such abrupt increases in flow discharge often cause serious disasters in downstream areas. The objective of this study was to support prediction systems for hazards caused by debris flows. We developed a crisis management system to contribute to evacuation decisions and actions by providing information to residents. We adopted Hyper KANAKO as the basic tool of the crisis management system. This system can also provide results of temporal changes such as flow depth and sedimentation depth for the administrator. The time-series images are associated with a world file that responds to geographic information from a 2D topographic model. It is possible to check the simulation results on a GIS as soon as calculations have been performed. In addition to the existing system, we developed functions to reproduce the side-bank erosion caused by landslide dam overtopping. This new system requires setting the height of the landslide dam, the width of the river channel, the initial overflow channel width of the landslide dam, and the numerical constant for side-bank erosion velocity as calculation conditions. The system can display the widening of the overflow channel of the landslide dam caused by overtopping, and analyze a series of phenomena related to flooding from the overtopping erosion of the landslide dam. Moreover this system can assist in developing more effective countermeasures and hazard maps for disaster mitigation.

Debris Flows, Boulders and Constrictions: A Simple Framework for Modeling Jamming, and Its Consequences on Outflow

“…Finally, our new program does not model the flow explicitly. Other numerical methods such as Hyper KANAKO (Nakatani et al., 2016; Yanagisaki et al., 2016), which implements depth‐averaged equations for flows, could be used in a complementary fashion. This type of complementary modeling would be especially helpful for checking the edge cases (i.e., “best” and “worst”‐case scenarios).…”

“…One method is to use fully 2D or 3D fluid mechanics solvers coupled with the Discrete Element Method (e.g., Canelas et al., 2017; Horiguchi & Komatsu, 2018; Leonardi et al., 2014; Shan & Zhao, 2014). Other methods such as HyperKANAKO (e.g., Nakatani et al., 2016; Yanagisaki et al., 2016) which use shallow‐water formulations together with relationships for the deposition and trapping of sediment of two specific sizes, also exist. These depth‐averaged methods are relatively numerically efficient, although there are open questions relating to whether the assumptions underpinning models such as HyperKANAKO still hold in debris basins with very thick layers of debris, which are pertinent to slit‐dams or canyons that can be more than 20 m high.…”

Modelling Debris Flow Runout: A Case Study on the Mesilau Watershed, Kundasang, Sabah

“…The heights of the post-landslide dam and the Liwagu Dam the laser-range finder during a field investigation on 31 August 201 within the initiation area was set to the height of 30.0 m (Figure 12a), within the downstream area was adjusted to a height of 5.0 m (Figu Additionally, the modelling parameters were calibrated through the open-source Li-breOffice 5 software with three primary tabs, i.e., the "DEM, Dams, and Observation", "riverbed", and "hydrograph". Table 3 shows the calibrated parameters for the "DEM, Dams, and Observation"; these parameters were calibrated by reviewing the available historical records of the study area with modifications based on global events, such as Japan [63,65] and Indonesia [66]. Additionally, several parameters, such as mass density of bed materials, mass density of fluids, coefficient of erosion and deposition rate, and acceleration of gravity of the study area were set as the default.…”