Numerical Simulation of Landslide Dam Deformation by Overtopping Flow

Akazawa, Fumiaki; Ikeda, Akikazu; Hayami, Satoshi; Harada, Norio; Satofuka, Yoshifumi; Miyata, Sumiko; Tsutsumi, Daizo

doi:10.13101/ijece.7.85

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Previous studies have proposed numerical simulation methods for overtopping and slope failures of a landslide dam. Numerical simulation methods for overtopping failure involve a surface flow model and side bank collapse model, which successfully reproduce the experimental or observed flood hydrographs (Takahashi and Nakagawa 1994;Chang and Zhang 2010;Satofuka et al 2010;Cao et al 2011;Akazawa et al 2014;Zhong et al 2018). Numerical simulation methods for slope failure involve a seepage flow model and dam slope stability model, which predict slope failure occurrence (Awal et al 2007).…”

Section: Introductionmentioning

confidence: 90%

Numerical simulation method for predicting a flood hydrograph due to progressive failure of a landslide dam

et al. 2021

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Reducing the damage due to landslide dam failures requires the prediction of flood hydrographs. Although progressive failure is one of the main failure modes of landslide dams, no prediction method is available. This study develops a method for predicting progressive failure. The proposed method consists of the progressive failure model and overtopping erosion model. The progressive failure model can reproduce the collapse progression from a dam toe to predict the longitudinal dam shape and reservoir water level when the reservoir water overflows. The overtopping erosion model uses these predicted values as the new initial conditions and reproduces the dam erosion processes due to an overtopping flow in order to predict a flood hydrograph after the reservoir water overflows. The progressive failure model includes physical models representing the intermittent collapse of a dam slope, seepage flow in a dam, and surface flow on a dam slope. The intermittent collapse model characterizes the progressive failure model. It considers a stabilization effect whereby collapse deposits support a steep slope. This effect decreases as the collapse deposits are transported downstream. Such a consideration allows the model to express intermittent, not continuous, occurrences of collapses. Field experiments on the progressive failure of a landslide dam were conducted to validate the proposed method. The progressive failure model successfully reproduced the experimental results of the collapse progression from the dam toe. Using the value predicted by the progressive failure model, the overtopping erosion model successfully reproduced the flood hydrograph after the reservoir water started to overflow.

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Section: Introductionmentioning

confidence: 90%

Numerical simulation method for predicting a flood hydrograph due to progressive failure of a landslide dam

et al. 2021

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“…Satofuka et al [2007] proposed a one-dimensional model that incorporated a two-layer model for immature debris flow [Takahama et al, 2000].and the side erosion model. In order to enable estimation of the range affected by flooding, the side-bank erosion velocity formula [Ashida et al, 1983;Takahashi and Nakagawa, 1993;Satofuka et al, 2007;Akazawa et al, 2014], which assumes range is proportional to the square of friction velocity, is employed in addition to the conventional one-dimensional riverbed variation calculation of Hyper KANAKO to consider the various types of sediment transport and their effect upon outflow discharge by overtopping, as shown in Fig. 9 and Formula (1).…”

Section: Supporting Installation Of Sabo Dams For Measures Against Lamentioning

confidence: 99%

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

Yanagisaki

Aono

Takenaka

et al. 2016

IJECE

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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.

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Dynamic deformation monitoring and scenario simulation of the Xiaomojiu landslide in the Jinsha River Basin, China

Zhang,

Li,

Ding

et al. 2023

Landslides

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The Xiaomojiu landslide is a typical high-elevation, long-runout landslide located in the Jinsha River Corridor. In this study, sequential InSAR time-series estimation was used to calculate the line of sight (LOS) surface displacements with descending and ascending Sentinel-1 images, and it turned out that the cumulative LOS surface displacement of the landslide was up to −78.4 mm during the period from October 2017 to April 2021 with the maximum LOS surface displacement rate of −38.5 mm/year. The landslide body could be divided into five zones (A, B1, B2, B3, and C) according to its topographical characteristics together with the LOS surface displacement time series. Combining engineering geological characteristics, LOS cumulative surface displacements with site investigation suggest that the Xiaomojiu landslide is likely to be a precipitation-triggered ancient traction rock landslide at the accelerated deformation stage. A dynamic simulation of the Xiaomojiu landslide with the PFC3D software shows that it could take approximately 65 s for the Xiaomojiu landslide from start-up to acceleration to deceleration to build-up of a barrier lake, followed by a simulation from the barrier lake to outburst floods with the HEC-RAS software indicating that the maximum depth of the outburst floods could be 13.5 m (15%), 24.6 m (25%), 42.1 m (50%), and 50.3 m (75%) along Qinghai-Tibet Plateau Transportation Corridor (QTPTC). It is believed that the results of this study provide a reference for landslide prevention along the QTPTC and the Jinsha River.

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Numerical Simulation of Landslide Dam Deformation by Overtopping Flow

Cited by 5 publications

References 4 publications

Numerical simulation method for predicting a flood hydrograph due to progressive failure of a landslide dam

Numerical simulation method for predicting a flood hydrograph due to progressive failure of a landslide dam

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

Dynamic deformation monitoring and scenario simulation of the Xiaomojiu landslide in the Jinsha River Basin, China

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