Debris flow simulation 2D (DFS 2D): Numerical modelling of debris flows and calibration of friction parameters

Abraham, Minu Treesa; Satyam, Neelima; Pradhan, Biswajeet; Hongling, Tian

doi:10.1016/j.jrmge.2022.01.004

Cited by 13 publications

(8 citation statements)

References 58 publications

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“…The assessment of landslide runout can be conducted in two ways. Forensic back analysis, based on the data from historical events [12][13][14] and predictive forward analysis, is used for risk assessment [15]. The runout analysis can be broadly classified into empirical or statistical methods, based on correlations and analytical methods, based on physical processes [16].…”

Section: Runout Assessment: Past and Current Practicesmentioning

confidence: 99%

“…The mesh is free to move along with the material, but in both the approaches, the neighbouring nodes remain constant throughout the entire simulation. The mesh-based models can be solved using different numerical techniques such as Finite Difference Method (FDM) [12], Finite Element Method (FEM) [48], Finite Volume Method (FVM) [49], Discontinuous Galerkin (DG) [50] and the Spectral Multidomain Penalty Method (SMPM) [51]. These classifications are based on how the information is passed through the nodes and how the computations are done within the grid.…”

Section: Numerical Modelling For Debris Flow Runoutmentioning

confidence: 99%

“…The pre-event surveys can provide the topography before the occurrence of event, and the post event surveys can provide insights on release zone, impact area and the post event topography. Apart from these inputs, a number of parametric inputs are required to define constitutive relationships and the material behaviour [12]. While some of these parameters can be obtained from laboratory or field investigations, such as the bulk density of the material, the complex rheological parameters are difficult to be obtained without calibration.…”

Section: Numerical Modelling For Debris Flow Runoutmentioning

confidence: 99%

“…Here, the simulations are repeated by varying the model parameters, till the simulated area matches the observed area best according to a predefined metric. While most studies do this process of calibration using sensitivity analysis and trial and error [12,57,58], attempts are made recently to use sampling techniques for selecting the parametric inputs and using probabilistic approaches for calibration [20,59]. The advancements in this direction can aid in optimising the model parameters and creating a large database for historical landslides, which can eventually support in forward analysis of debris flows.…”

Section: Numerical Modelling For Debris Flow Runoutmentioning

confidence: 99%

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Numerical Modelling of Debris Flows for Simulation-Based Decision Support: An Indian Perspective

Abraham,

Satyam,

Kowalski

2024

Indian Geotech J

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Debris flows are catastrophic landslides owing to their very high velocities and impact. The number of such flows is likely to increase due to an increase of extreme weather events in a changing climate. At the same time, risk reduction and mitigation plans call for a quantitative assessment of the hazard. Numerical models are powerful tools in quantifying debris flows in terms of flow height and velocity with respect to both space and time, and to derive mitigation-relevant diagnostics such as impacted area. However, the current modelling practices possess critical challenges that limit their application in a forward-directed analysis to predict the debris flow’s impact. This work provides an overview of the past and current practices in debris flow modelling, their potential use in simulation-based decision support and the challenges and future research scope in computational debris flow modelling, based on the recent literature.

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Section: Runout Assessment: Past and Current Practicesmentioning

confidence: 99%

Section: Numerical Modelling For Debris Flow Runoutmentioning

confidence: 99%

Section: Numerical Modelling For Debris Flow Runoutmentioning

confidence: 99%

Section: Numerical Modelling For Debris Flow Runoutmentioning

confidence: 99%

See 2 more Smart Citations

Numerical Modelling of Debris Flows for Simulation-Based Decision Support: An Indian Perspective

Abraham,

Satyam,

Kowalski

2024

Indian Geotech J

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“…The utility of DFS 2D was assessed utilizing the data obtained from a major debris ow occurrence in China on August 13th, 2010. (Abraham et al, 2022) RAMMS (Rapid Mass Movement System) is a hugely popular software tool for assessing and replicating debris ows, offers vital information regarding debris ow behavior. The three essential pre-requisites for RAMMS are the digital elevation model (DEM), the Voellmy rheological inputs, and secondary ground data, or geotechnical characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling the possible Debris Flow events in Swat Mountains Using Flow-R -A Case Study in Pakistan

Hassan,

Ehsan,

Afzal

et al. 2023

Preprint

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Debris flows are dangerous mixtures of water, sediment, and rock that can cause serious problems in mountainous regions.These destructive events happen often in mountain areas, especially during floods and intensive rain fall. The purpose of this study is analyse the possible debris flow events in Swat mountains in Pakistan using Flow-R. Flow-R is a debris flow simulation software that generates susceptibility maps, offering critical insights into the areas most prone to this hazardous phenomenon. The primary inputs required for the Flow-R simulation were digital elevation models (DEM) and the source area file of the region. Two specific algorithms, Holmgren modified and Gamma 2000, have been taken into consideration for this case study. Holmgren Modified considers various factors like topography, climate, vegetation, and land use, while Gamma 2000 focuses on rock type’s influence on debris flow occurrences. By integrating these inputs with the selected algorithms, Flow-R generated susceptibility maps, highlighting three regions: Thal, Kalam, and Kandia Valley, with varying degrees of vulnerability to debris flow events. According to the susceptibility map of Holmgren modified among three regions, the Thal region is highly susceptible to debris flows due to its topography as compared to Kalam and Kandia Valley. On the other hand, the susceptibility map of Gamma 2000 shows that in the Thal region, large rocks contribute more, while in the other two regions, small rocks are mainly responsible for generating debris flow. By identifying the areas most susceptible to debris flows, effective risk mitigation measures can be implemented to reduce potential damage and protect vulnerable communities.

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Landslide Susceptibility Mapping of Chamoli (Uttarakhand) Using Random Forest Machine Learning Method

Mittal,

Gupta,

Satyam

2024

Lecture Notes in Civil Engineering

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Debris flow simulation 2D (DFS 2D): Numerical modelling of debris flows and calibration of friction parameters

Cited by 13 publications

References 58 publications

Numerical Modelling of Debris Flows for Simulation-Based Decision Support: An Indian Perspective

Numerical Modelling of Debris Flows for Simulation-Based Decision Support: An Indian Perspective

Modelling the possible Debris Flow events in Swat Mountains Using Flow-R -A Case Study in Pakistan

Landslide Susceptibility Mapping of Chamoli (Uttarakhand) Using Random Forest Machine Learning Method

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