Long‐Runout‐Landslide‐Induced Debris Flow: The Role of Fine Sediment Deposition Processes in Debris Flow Propagation

Nishiguchi, Yuki; Uchida, Tatsuo

doi:10.1029/2021jf006452

Cited by 15 publications

(4 citation statements)

References 48 publications

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“…Our independent measurements of basal normal stress and flow height (Nagl et al., 2022) yielded an average bulk density between 2,150 kg/m³ for DF2019 and 2,000 kg/m³ for DF2020, respectively, which can be interpreted as a slightly higher sediment concentration for DF2019 than DF2020. What these measurements do not explicitly reveal is the overall grain size distribution, especially the fines content in the form of clay and silt, which controls the bulk flow resistance (Kaitna et al., 2016) and runout distance (Nishiguchi & Uchida, 2022) of the flow. Based on visual video analysis, we speculate that DF2020 had a higher fines content than DF2019, causing super‐critical Froude numbers and lower deposition heights.…”

Section: Discussionmentioning

confidence: 99%

A Perspective of Surge Dynamics in Natural Debris Flows Through Pulse‐Doppler Radar Observations

Schöffl,

Nagl,

Koschuch

et al. 2023

JGR Earth Surface

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As a consequence of their natural occurrence and the frequent formation of multiple surges with high sediment loads, debris flows are considered one of the most hazardous gravity‐driven mass movements in mountain regions. Field measurements of surge dynamics are an essential link in the chain of understanding fundamental process dynamics and engineering protection against debris flows. However, continuous information on the velocities of multiple consecutive surges within a single debris‐flow event with high temporal resolution is rare. In this study we present a new pulse‐Doppler radar (PD radar) for high‐resolution real‐time debris‐flow monitoring. We analyse PD radar data sets over a torrent length of 250 meters for two debris flows that occurred at the Gadria creek (IT), on July 26, 2019 and August 10, 2020. The radar data was validated with independently derived data from particle image velocimetry (DPIV) and manually tracked velocities. We observe that between surges the flow frequently comes to a complete halt and is re‐mobilized by subsequent surges, resembling erosion‐deposition waves in granular flows. In addition, our data confirm that surges can superimpose and merge. We anticipate that the outcomes of this work serve as a blueprint for future high‐resolution observations of debris‐flow surge dynamics with PD radar and that our findings provide new insights into the physical principles of natural debris flows.

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Section: Discussionmentioning

confidence: 99%

A Perspective of Surge Dynamics in Natural Debris Flows Through Pulse‐Doppler Radar Observations

Schöffl,

Nagl,

Koschuch

et al. 2023

JGR Earth Surface

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“…Debris flow is a natural phenomenon, usually originated from landslides, with high impact force, characterized by no signs and rapid movement [ 12 ]. Generally, debris flow is characterized by rapid movement, sudden occurrence, fluid-like movements and long travel distances from their outlet.…”

Section: Analysis and Discussionmentioning

confidence: 99%

Cause Analysis and Preventive Measures of Guizhou D2809 Train Derailment Accident in Guizhou, China on 4 June 2022

Wang

Chen

Jiang

et al. 2022

IJERPH

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This paper summarizes the cause of the debris flow impact train accident by investigating the local geological condition, meteorological data and field investigation that happened in Guizhou, China on 4 June 2022. The result showed that the major reason is the continuous heavy rain in the surrounding area, which led to a small landslide at the upper right of the tunnel entrance. Besides, the construction of the Jianrong Expressway in the upper reaches increased the catchment area, which makes the water content of the upper soil increase while the shear strength decreases. Such large-scale catastrophic accidents significantly threaten the local environment and public safety. Therefore, it is urgent to pay special attention to the changes in geological conditions along the line, especially the adverse effects of construction, to improve the early risk warning and post-accident treatment ability.

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“…Natural landslide inundation areas have been reproduced using landslide models that assume a uniform grain size and utilize a representative value for grain size distribution [1]. However, large-scale landslides often extend to gentler slopes than those predicted by models [5]. This discrepancy may arise from the suspension of fine grains within the landslide pore fluid.…”

Section: Introductionmentioning

confidence: 99%

“…Turbulence caused by the strong shear of coarse grains can suspend fine grains, leading to an increase in apparent pore fluid density and an enhanced buoyancy effect on coarse grains. Factoring this effect into numerical models as an increase in apparent pore fluid density has improved their accuracy in predicting large-scale landslide runout distances [5].…”

Section: Introductionmentioning

confidence: 99%

A numerical model for large-scale landslides based on digital elevation models

Sakai,

Hotta,

Tobe

2024

Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet

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Landslides, which are triggered by heavy rainfall or seismic activity, pose serious threats in mountainous regions, necessitating the implementation of structural mitigations, early warning systems, and hazard maps. Traditionally, hazard maps have been empirically derived based on topographical parameters; however, recent advancements have seen the integration of numerical models with digital elevation models (DEMs) to calculate hazard maps. These numerical models are grounded in a comprehensive understanding of landslide dynamics. Large-scale landslides often inundate a larger area than predicted by existing models, which is attributed to the impact of suspended fine sediment reducing bottom friction. To address the inadequacies of existing models in reflecting these effects, we developed a new numerical model for largescale landslides that considers the suspension of fine sediment. First, we investigated the relationship between the quantity of suspended fine sediment and the kinematic conditions of a landslide through flume experiments, resulting in a regression equation for estimating the quantity of suspended fine sediment. This equation was incorporated into a two-dimensional depth-averaged model, forming the basis for the new large-scale landslide model. When this model is integrated with a DEM, it accurately calculates the inundated area associated with a landslide. We tested the model using data for a largescale landslide event in Japan, where pre-and post-landslide DEMs were available for model validation. The results showed that our model successfully replicated the actual inundation area, demonstrating its potential utility in generating hazard maps based on numerical simulations.

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Long‐Runout‐Landslide‐Induced Debris Flow: The Role of Fine Sediment Deposition Processes in Debris Flow Propagation

Cited by 15 publications

References 48 publications

A Perspective of Surge Dynamics in Natural Debris Flows Through Pulse‐Doppler Radar Observations

A Perspective of Surge Dynamics in Natural Debris Flows Through Pulse‐Doppler Radar Observations

Cause Analysis and Preventive Measures of Guizhou D2809 Train Derailment Accident in Guizhou, China on 4 June 2022

A numerical model for large-scale landslides based on digital elevation models

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