Advancing Culture of Living With Landslides 2017
DOI: 10.1007/978-3-319-53485-5_47
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Observation and Numerical Simulation of Debris Flow Induced by Deep-Seated Rapid Landslide

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Cited by 3 publications
(4 citation statements)
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“…We don't have any information about number of debris flow surges in Koslanda. However a number of disaster reports in Japan showed several debris flow surges occurred in a single event [e.g., Nishiguchi et al, 2011 ;Uchida et al, 2017]. From these evidences and results of the simulation, in Koslanda, multi debris flow surges might occur and the flow path of later debris flow surge might be affected by the topographic change due to deposition of the first debris flow surge, However, by calculation using simulation software, it was confirmed that we could estimate to some extent that it was not able to be estimated only by field survey.…”
Section: Resultsmentioning
confidence: 99%
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“…We don't have any information about number of debris flow surges in Koslanda. However a number of disaster reports in Japan showed several debris flow surges occurred in a single event [e.g., Nishiguchi et al, 2011 ;Uchida et al, 2017]. From these evidences and results of the simulation, in Koslanda, multi debris flow surges might occur and the flow path of later debris flow surge might be affected by the topographic change due to deposition of the first debris flow surge, However, by calculation using simulation software, it was confirmed that we could estimate to some extent that it was not able to be estimated only by field survey.…”
Section: Resultsmentioning
confidence: 99%
“…In this disaster, it is thought that fluidized landslide sediment became debris flow. Previous studies showed that runout processes, such as travel distance of debris flow, erosion and deposition patterns, of landslide incurred debris flow has been described by a debris flow simulation [e.g., Egashira et al, 1998 ;Nishiguchi et al, 2011 ;Uchida et al, 2017]. We tried to describe the debris flow processes by using the one-dimensional debris flow numerical simulation program, Kanako-LS.…”
Section: Strategy Of Numerical Simulationmentioning
confidence: 99%
“…where P is the Rouse number, w 0 is the settling velocity (cm), κ is the von Kármán constant (0.41), u * is the friction velocity (= √ gRI ), R is the hydraulic radius (m), I is the energy gradient, d is the particle size (cm), ν is the coefficient of kinematic viscosity (cm 2 s −1 ), and s is the weight per unit volume of sediment in water (= ρ s ρ −1 f − 1). The Rouse number determining the threshold condition of suspension in debris flow (ranging from 0.116 to 0.813) is smaller than the threshold of suspended sediment in fluvial channels due to the shading effect by boulders inside of the flow (Nishiguchi, 2014;Sakai et al, 2019). By assuming that R was the average flow height of monitored surges (1.07 m; Table 3), I was the local channel gradient (= sin 16 • ), ρ s = 2650 (kg m −3 ), ρ f = 1000 (kg m −3 ), and ν = 0.01 (cm 2 s −1 ), the particle sizes that provide P = 0.11 and 0.813 were 0.07 and 3.0 cm, respectively.…”
Section: Pore Water Pressure In Debris Flowmentioning
confidence: 91%
“…Numerical simulation is a novel approach for simulating landslides, and numerous scholars have employed this method to conduct landslide simulation experiments and compare the results with on-site tests [11][12][13]. Arbanas [14] utilized the strength reduction method to perform a numerical analysis on slopes, aiming to determine the shape of the fracture zone.…”
Section: Introductionmentioning
confidence: 99%