Debris Flow Model Research Articles

Multi-geohazards susceptibility mapping based on machine learning—a case study in Jiuzhaigou, China

Jiuzhaigou, located in the transitional area between the Qinghai–Tibet Plateau and the Sichuan Basin, is highly prone to geological hazards (e.g., rock fall, landslide, and debris flow). High-performance-based hazard prediction models, therefore, are urgently required to prevent related hazards and manage potential emergencies. Current researches mainly focus on susceptibility of single hazard but ignore that different types of geological hazards might occur simultaneously under a complex environment. Here, we firstly built a multi-geohazard inventory from 2000 to 2015 based on a geographical information system and used satellite data in Google earth and then chose twelve conditioning factors and three machine learning methods—random forest, support vector machine, and extreme gradient boosting (XGBoost)—to generate rock fall, landslide, and debris flow susceptibility maps. The results show that debris flow models presented the best prediction capabilities [area under the receiver operating characteristic curve (AUC 0.95)], followed by rock fall (AUC 0.94) and landslide (AUC 0.85). Additionally, XGBoost outperformed the other two methods with the highest AUC of 0.93. All three methods with AUC values larger than 0.84 suggest that these models have fairly good performance to assess geological hazards susceptibility. Finally, evolution index was constructed based on a joint probability of these three hazard models to predict the evolution tendency of 35 unstable slopes in Jiuzhaigou. The results show that these unstable slopes are likely to evolve into debris flows with a probability of 46%, followed by landslides (43%) and rock falls (29%). Higher susceptibility areas for geohazards were mainly located in the southeast and middle of Jiuzhaigou, implying geohazards prevention and mitigation measures should be taken there in near future.

Numerical Modeling of Debris Flows Induced by Dam-Break Using the Smoothed Particle Hydrodynamics (SPH) Method

Dam-break flows may change into debris flows if certain conditions are satisfied, such as abundant loose material and steep slope. These debris flows are typically characterized by high density and can generate strong impact forces. Due to the complexity of the materials that they are made of, it has always been very challenging to numerically simulate these phenomena and accurately reproduce experimentally debris flows’ processes. Therefore, to fill this gap, the formation-movement processes of debris flows induced by dam-break were simulated numerically, modifying the existing smoothed particle hydrodynamics (SPH) method. By comparing the shape and the velocity of dam break debris flows under different configurations, it was found that when simulating the initiation process, the number of particles in the upstream section is overestimated while the number of particles in the downstream area is underestimated. Furthermore, the formation process of dam-break debris flow was simulated by three models which consider different combinations of the viscous force, the drag force and the virtual mass force. The method taking into account all these three kinds of interface forces produced the most accurate outcome for the numerical simulation of the formation process of dam-break debris flow. Finally, it was found that under different interface force models, the particle velocity distribution did not change significantly. However, the direction of the particle force changed, which is due to the fact that the SPH model considers generalized virtual mass forces, better replicating real case scenarios. The modalities of dam failures have significant impacts on the formation and development of debris flows. Therefore, the results of this study will help authorities to select safe sites for future rehabilitation and relocation projects and can also be used as an important basis for debris flow risk management. Future research will be necessary to understand more complex scenarios to investigate mechanisms of domino dam-failures and their effects on debris flows propagation.

Improved Modeling of Subaerial and Subaqueous Muddy Debris Flows

AbstractIn this note, a two-dimensional depth-averaged numerical model (MassFlow2D) previously developed to simulate subaerial and subaqueous muddy debris flows is further improved. The retarding e...

A mechanical model for phase separation in debris flow

Understanding the physics of phase separation between solid and fluid phases as a mixture mass moves down-slope is a long-standing challenge. Here, we propose an extension of a two phase mass flow model (“Pudasaini (2012), A general two-phase debris flow model, Journal of Geophysical Research, 117, F03010, doi:10.1029/2011JF002186”) by including a new mechanism, called separation-flux, that leads to strong phase separation in avalanche and debris flows while balancing the enhanced solid flux with the reduced fluid flux. The relative velocity between the phases is key in triggering the phase separation mechanism, which is induced by the effective forces that appear in the system. The novel separation-flux can be written as a product of the separation-rate, solid and fluid volume fractions, and the flow depth which amplify the separation-flux. Its magnitude is further controlled by the separation-rate-intensities which are functions of volume fractions and the density ratio. The separation-fluxes are multi-directional. One of the most important characteristics of the separation-flux is that phase separation ceases as soon as one of the components in the mixture vanishes. As the solid density approaches the fluid density, the phase separation intensity is reduced. Furthermore, as the drag increases, the phase separation decreases. The separation velocity emerges from the separation-flux as a function of the relative phase velocity, volume fraction of solid or fluid, and the respective separation-rate-intensity. The separation-rate takes into account different dominant physical and mechanical aspects of the mixture flow, such as the hydraulic pressure gradients, topography induced pressure gradients, the gradients of the volume fractions of solid and fluid phases, flow depths, grain size, densities, friction, viscosities, and buoyancy. The separation-flux mechanism is capable of describing the dynamically evolving phase separation and levee formation in a multi-phase, geometrically three-dimensional debris flow. These are often observed phenomena in natural debris flows and industrial processes that involve the transportation of particulate solid-fluid mixture material. Due to the inherent separation mechanism, as the mass moves down-slope, more and more solid particles are transported to the front and the sides, resulting in solid-rich and mechanically strong frontal surge head, and lateral levees followed by a weaker tail largely consisting of viscous fluid. The primary frontal solid-rich surge head followed by secondary fluid-rich surges is the consequence of phase separation. Such typical and dominant phase separation phenomena are revealed for two-phase debris flow simulations. Finally, changes in flow composition, that are explicitly considered by the new modelling approach, result in significant changes of impact pressure estimates. These are highly important in hazard assessment and mitigation planning and highlight the application potential of the new approach.

Comprehensive modelling of runoff-generated debris flow from formation to propagation in a catchment

This study aimed to develop an integrated model of the runoff-generated debris flow that considers the initial conditions, movement mechanisms, and entrainment effect. The study focused on the formation and propagation processes of debris flow within a catchment, and the process is divided into three stages: rainfall infiltration, runoff, and debris flow routing. Soil saturation, rainfall, and entrainment are the main factors that influence the debris flow formation and propagation processes. Existing models for each stage, including Richards’s equations, shallow water equations, and two-phase debris flow equations, were coupled. The tridiagonal matrix algorithm and finite volume method were applied to solve these equations. Finally, several experimental cases and the 2010 debris flow event in the Hongchun catchment in China were simulated by using the proposed model. The results showed that the proposed model could effectively describe the behaviours of each stage during the debris flow formation and propagation processes. Although several aspects of the model require further improvement, the physical-parameter-based prediction of runoff-generated debris flows from formation to propagation is effectively performed by the model.

Numerical Simulation of a Debris Flow on the Basis of a Two-Dimensional Continuum Body Model

A two-dimensional debris and mud flow model that considers both laminar and turbulence flow was developed. Subsequently, the model was applied to a debris flow that occurred in Asaminami, Hiroshima, Japan in August 2014. The applicability of the model and the debris flow characteristics are discussed. The calculated horizontal distribution of sediment deposited in the Asaminami residential area was in good agreement with the horizontal distribution of the deposited large rocks and driftwood. This result indicates that the fine material in the downstream area was transported by water flow resulting from heavy rain that occurred after the debris flow. The scale of the initial debris flow was small; however, it increased with time, because eroded bed material and water were entrained to it. Therefore, it is important to reproduce the development process of debris flows to predict the amount of sediment produced, the deepest flow depth, the maximum flow velocity, and the inundation area. The averaged velocity of the simulated debris flow was about 9 m/s, and the velocity at the entrance to the residential area was about 8 m/s. This kind of information can be used to design sediment deposition dams. The travel time of the simulated debris flow from the upstream end of the main channel to the entrance of the residential area was 96 s. This kind of information can be used for making evacuation plans. Valley bed steps can suppress the deepest flow depth which is very important for the design of check dams; therefore, the high-resolution elevation data and fine numerical grids that reproduce step shapes are required to accurately calculate the deepest flow depth and maximum flow velocity.

THE STUDY OF THE DEBRIS-FLOWS DYNAMICS ON AN EXPERIMENTAL STAND

Designed and manufactured a test stand for the dynamic characteristics of debris-flows and for physical modelling of debris-flows. The stand is a rectangular cross-section tray with a length of 3.0 m, a width of 0.25 m, a depth of 0.25 m. The slopes of the tray vary from 10o to 45o. Rods are installed in the tray to accommodate load cells for measuring pressure, speed and temperature. The process of moving the debris-flow through the transparent wall of the debris-flow tray is filmed by a high-speed video camera. During the experiment, the velocity and high- velocity pressure of water flow and artificial debris-flow were measured. The tray was installed with a slope of 12o. Water flow was started up on the tray (to measure the flow rate and the value of the velocity head, which were then used as reference values). Then the tray was put into the flow of the prepared debris-flow mixture. The debris-flow mixture was prepared from a dredged-crushed proluvial-deluvial deposits of Holocene age with a loamy aggregate with a density of 2210 kg/m3. The density of the prepared debris-flow mixture was 1756 kg/m3. Dynamic viscosity of the debris-flow mass measured by the Stokes method was 0.0498 Poise, kinematic viscosity of the debris-flow mass was 0.0928 Stokes. Data on the debris-flow velocity measured directly during its movement of the debris-flow is not enough. Therefore, methods for calculating the speed of a debris-flow slide in its are important. One of these methods is the method of calculating the debris-flow velocity by the magnitude of the speed head (on the traces of the debris-flow on the trunks of trees). That method is based on the formula of E. Torricelli. The results of the experiment showed that the measured debris-flow velocity, calculated from the magnitude of the velocity head, was lower than the measured velocity before the obstacle and higher than the measured velocity after the obstacle. The measured velocity of the debris-flow passage of the entire tray was close to the calculated one.

Development of a Debris Flow Risk Impact Map Using a 2-D Model of Debris Flow and a Facilities Impact Map

Development of a Debris Flow Risk Impact Map Using a 2-D Model of Debris Flow and a Facilities Impact Map

Post-fire debris flow modeling analyses: case study of the post-Thomas Fire event in California

There is an increased risk in post-fire debris flow (DF) occurrences in the western USA with recent increase in wildfire frequencies. DFs are destructive, causing high loss to lives and infrastructure. A lot of effort is going into possible preventive and/or mitigation measures. Recent research efforts in this niche focus on developing statistical models that assist emergency responders in isolating high-hazard locations after fires. There are two general approaches to this statistical modeling: linear and nonlinear. This study has looked into applying a linear-based logistic regression model and a nonlinear-based C5.0 decision tree model to assess the strength of each in predicting the locations within the Thomas Fire boundary that produced DFs. To do this, DF scars were delineated by running a change detection protocol known as delta normalized difference vegetation index (dNDVI), using high spatial resolution data from Planet Labs. These scars were further validated with data gathered by Santa Barbara County officials on affected areas. Results from the two statistical models were then overlain on the delineated DF scars and compared against each other to determine predictive strengths. The results revealed both models to perform well in predicting high probabilities for locations that were shown to produce DFs. The logistic regression model predicted an overall ~ 44,800 ha (49%) more high-hazard coverage compared to the C5.0 tree and therefore showed greater urgency. However, a closer look at the basin predictions with the delineated DF scars showed that most of these high-hazard basins identified by the logistic regression did not to have any discernible scars. It was projected that most of these locations were likely false positives and further fine-tuning of the model was recommended. Further recommendation was made concerning the development of additional models to predict potential DF inundation paths. Combining origination and inundation models will be most beneficial since the greatest associated danger with DFs is not necessarily where they start, but rather further downstream where most communities and infrastructure are situated.

Run-out distribution of debris-flow materials: case study from some Java landslides

Indonesia is a risk prone country from landslide disasters. The occurrence of landslides followed by the debris flow often make a lot of casualties and very terrible destructions. Accordingly, debris flow modeling of some Java landslides has been conducted in this study to determine run-out distribution characteristics of the debris materials. The concept of debris flow modeling is based on the equations of momentum, continuation, riverbed deformation, erosion/deposition and riverbed shearing stress. From this modeling, it has been indicated the best fit simulation results. In this case, run-out distributions of Pacet landslide at Mojokerto, December 12, 2002 has been properly modeled with a scenario of 0.4 viscosity value for around 5 minutes. At Sijeruk landslide, Banjarnegara, January 4, 2006 run-out distributions have been modeled using viscosity value of 0.45 for 14 minutes 51 seconds. Meanwhile, the modeling for Tenjolaya landslide at southern Bandung, February 23, 2010 with viscosity value of 0.38 shows time needed for debris materials to reach depositional area is estimated for around 12 minutes 37 seconds. From this study, debris flow modeling had given better understandings regarding flow track, velocity and distribution of debris materials from some debris flows in Java.

Initiation and Flow Conditions of Contemporary Flows in Martian Gullies.

Understanding the initial and flow conditions of contemporary flows in Martian gullies, generally believed to be triggered and fluidized by CO2 sublimation, is crucial for deciphering climate conditions needed to trigger and sustain them. We employ the RAMMS (RApid Mass Movement Simulation) debris flow and avalanche model to back calculate initial and flow conditions of recent flows in three gullies in Hale crater. We infer minimum release depths of 1.0–1.5 m and initial release volumes of 100–200 m3. Entrainment leads to final flow volumes that are ∼2.5–5.5 times larger than initially released, and entrainment is found necessary to match the observed flow deposits. Simulated mean cross‐channel flow velocities decrease from 3–4 m/s to ∼1 m/s from release area to flow terminus, while flow depths generally decrease from 0.5–1 to 0.1–0.2 m. The mean cross‐channel erosion depth and deposition thicknesses are ∼0.1–0.3 m. Back‐calculated dry‐Coulomb friction ranges from 0.1 to 0.25 and viscous‐turbulent friction between 100 and 200 m/s2, which are values similar to those of granular debris flows on Earth. These results suggest that recent flows in gullies are fluidized to a similar degree as are granular debris flows on Earth. Using a novel model for mass flow fluidization by CO2 sublimation we are able to show that under Martian atmospheric conditions very small volumetric fractions of CO2 of ≪1% within mass flows may indeed yield sufficiently large gas fluxes to cause fluidization and enhance flow mobility.

Optical granulometry of coarse aggregates and sediments

In order to determine the granularity of the material, image analysis may be used instead of traditional methods such as sieving. Data on granulometry is important in the water management sector for several practical applications, such as calculation of sediment transport capacity in watercourses, design of hydraulic structures, or modeling of debris flows. The WipFrag and Basegrain programs were tested on the case study of the Belca rockfall and the Sava Dolinka River’s gravel bar near the village of Mojstrana. In both cases, multiple images were taken from different heights and sieve analysis was performed. The results of both programs were compared with the results of the sieving analysis. The results showed that WipFrag yielded more comparable results with the sieving analysis than Basegrain. WipFrag gave slightly better results in the case of the Belca rockfall than in the case of the river gravel bar. The Basegrain program, on the other hand, produced similarly comparable results in both case studies. In most cases, both programs underestimated the grain size compared to the results of the sieving analysis. In some cases, the relative differences were close to 100%. On the other hand, the selected statistical test did not show a statistically significant difference between the results of the sieving analysis and the results of the image analysis in both of the programs. Optimal image analysis results were obtained from images taken from the height of about 1.5-2 m, which means that we suggest that photos of aggregates, fluvial sediments, and erosion material should be taken from a height of approximately ten times the maximum grain size.

Identifying post-earthquake debris flow hazard using Massflow

Catastrophic debris flows are common after large earthquakes and pose a significant risk for recovering communities. The depositional volume of these large debris flows is often much greater than the initiation volume, suggesting that bulking of the flow plays an important role in determining their volume, speed, and runout distance. Observations from recent earthquakes have driven progress in understanding the relationship between triggering rainfall events and the timing of post-earthquake debris flows. However, we lack an adequate mechanism for quantifying bulking and applying it within a hazard context. Here we apply a 2D dynamic debris flow model (Massflow) that incorporates a process-based expression of basal entrainment to understand how debris flow bulking may occur within post-earthquake catchments and develop hazard maps. Focussing on catchments in the epicentral area of the 2008 Mw 7.9 Wenchuan Earthquake, we first parameterised the model based on a large debris flow that occurred within the Hongchun catchment, before applying the calibrated model to adjoining catchments. A model sensitivity analysis identified three main controls on debris flow bulking; the saturation level of entrainable material along the flow pathway, and the size and position of initial mass failures. The model demonstrates that the difference between small and very large debris flows occur across a narrow range of pore-water ratios (λ). Below λ = 0.65 flows falter at the base of hillslopes and come to rest in the valley bottom, above λ = 0.70 they build sufficient mass and momentum to sustain channelised flow and transport large volumes of material beyond the valley confines. Finally, we applied the model across different catchments to develop hazard maps that demonstrate the utility of Massflow in post-earthquake planning within the Wenchuan epicentral region.

Deciphering controls for debris‐flow erosion derived from a LiDAR‐recorded extreme event and a calibrated numerical model (Roßbichelbach, Germany)

AbstractDebris flows are among the most destructive and hazardous mass movements on steep mountains. An understanding of debris‐flow erosion, entrainment and resulting volumes is a key requirement for modelling debris‐flow propagation and impact, as well as analysing the associated risks. As quantitative controls of erosion and entrainment are not well understood, total volume, runout and impact energies of debris flows are often significantly underestimated. Here, we present an analysis of geomorphic change induced by an erosive debris‐flow event in the German Alps in June 2015. More than 50 terrestrial laser scans of a 1.2 km long mountain torrent recorded geomorphic change in comparison to an airborne laser scan performed in 2007. Errors were calculated using a spatial variable threshold based on the point density of airborne laser scanning and terrestrial laser scanning and the slope of the digital elevation models. Highest erosion rates approach 5.0 m3/m2 (mean 0.6 m3/m2). During the event 9550 ± 1550 m3 was eroded whereas only 650 ± 150 m3 was deposited in the channel. Velocity, flow pressure, momentum and shear stress were calculated using a carefully calibrated RAMMS Debris Flow model including material entrainment. Here we present a linear regression model relating debris‐flow erosion rates to momentum and shear stress with an R2 up to 68%. Channel transitions from bedrock to loose debris sections cause excessive erosion up to 1 m3/m2 due to previously unreleased random kinetic energy now available for erosion. © 2019 John Wiley & Sons, Ltd.

Investigation of Post-Fire Debris Flows in Montecito

Debris flows in a burned area, post-fire debris flows, are considered as one of the most dangerous geo-hazards due to their high velocity, long run-out distance, and huge destruction to infrastructures. The rainfall threshold to trigger such hazards is often reduced compared with normal debris flow because ashes generated by mountain fires reduce the permeability of the top soil layer, thus increasing surface runoff. At the same time, burnt material and residual debris have very poor geo-mechanical characteristics, e.g., their internal friction angle and cohesion are typically low, and thus an intense rainfall can easily trigger some debris flows. Studying post-fire debris flow enables us to get a deeper understanding of disaster management. In this paper, the debris flow that occurred in Montecito, California, USA, and was affected by the Thomas Fire was used as a case study. Five major watersheds were extracted based on the digital elevation model (DEM). Remote sensing images were used to analyze the wildfire process, the extent of the burned areas, and the burn severity. The hypsometric integral (HI) and short-duration rainfall records of the watersheds around Montecito when the post-fire debris flows occurred were analyzed. Steep terrain, loose and abundant deposits, and sufficient water supply are the important conditions affecting the formation of debris flows. Taking watersheds as the research objects, HI was used to describe the geomorphic and topographic features, open-access rainfall data was used to represent the water supply, and burn severity represented the abundance of material sources. An occurrence probability model of post-fire debris flow based on HI, short-duration heavy rainfall, and burn severity was developed by using a logistic regression model in post-fire areas. By using this model, the occurrence probability of the post-fire debris flow in different watersheds around Montecito was analyzed based on the precipitation with time. Especially, the change characteristics of occurrence probability of debris flows over time based on the model bring a new perspective to observe the obvious change of the danger of post-fire debris flows and it is very useful for early warning of post-fire debris flows.

The potential of PALSAR RTC elevation data for landform semi-automatic detection and landslide susceptibility modeling

ABSTRACT This study demonstrated the potential of methods derived from geomorphometry and regression models to evaluate landslide susceptibility in a study area located in southern Colombia. From a morphometric stance, the first step was to evaluate the quality of DEM sources by comparison to control points obtained by static-mode GPS. The PALSAR_RTC_hi data was selected for having the best accuracy of heights and was used to derivate terrain parameters at SAGA software. Then, the Principal Component Analysis selected variables with low collinearity, and we classified twelve landforms using fuzzy k-means algorithm, which was compared to a geomorphological map by using the multinomial logistic regression method in R software. We got a Kappa coincidence index of about 30%. The resulting landslide susceptibility mapping took dependent (a mask with unstable-stable cells from an existing landslide inventory) and independent variables (selected morphometric ones). The binary logistic regression showed the propensity of the area to be adversely affected by landslides. This model’s performance was tested with a ROC curve over a sample, with 20% of landslide database resulting in an Area Under the Curve of 0,55. This result was contrasted with a spatial prediction model of debris flow, explaining the high frequency of avalanches.

Estimation of the area of sediment deposition by debris flow using a physical-based modeling approach

Debris flow triggered by shallow landslides in hillslope catchments is a main geological phenomenon driving landscape changes, and represents an important natural hazard. Numerous studies have assessed sediment transport and deposition by debris flows in hillslope catchments. Thus, the objective of this study is a development of two-dimensional debris flow model to estimate sediment transport and deposition in hillslope catchments. To simulate debris flow, we implemented a vertically integrated shallow-water governing equation based on the Voellmy rheological model and a simple entrainment model. In addition, we applied a quadtree grid structure to support adaptive mesh refinement, where the mesh for the simulation was automatically generated as the debris flow proceeded. Finally, a well-balanced numerical scheme for wet–dry transition treatment was implemented and implicit discretization of the general source terms, including the rheological term, was included for numerical stability. The developed model was verified based on a debris flow triggered by the 2011 Mt. Umyeon landslides in the Republic of Korea. Sediment transport was successfully generated and the sediment deposition area generally matched the field survey data well. Overall, the simulated sediment volume was in good agreement with the survey results, with an error below 1%.

On the role of pore-fluid pressure evolution and hypoplasticity in debris flows

Abstract For debris flows, two characteristics play a crucial role in their behaviors: (i) the non-linear deformational behavior that stems from the internal contact stress between grains, and (ii) the pore-pressure feedback, which reduces the intergranular friction and, therefore, enhances the mobility of the whole mixture. In a previous work, the constitutive equations of a general grain–fluid multiphase mixture are deduced by exploiting the entropy principle based on the formulation of Muller and Liu. In the work at hand, this thermodynamically consistent and general model is applied to a two-phase debris flow. For this, it is scaled, depth-integrated, compared with other known models and employed for numerical investigations. The extra pore-fluid pressure and the hypoplastic stress are described as internal variables that are, respectively, governed by a pressure diffusion equation and a transport equation related to the hypoplastic material. Numerical investigation of a grain–fluid material, sliding down a slope into a runout, is carried out using a non-oscillatory, shock-capturing central-upwind scheme with the total variation diminishing property. Comparison of the obtained results with those from classical debris flow models shows that the proposed thermodynamic model provides a phenomenological insight into the influence of the pore-pressure feedback and intergranular friction in the flow dynamics. The extra pore-fluid pressure enhances the flow dynamics, while the effect of the intergranular stress is more significant during the settling of the flow and affects the shape of the granular bulk.

Surrogate-based parameter inference in debris flow model

This work tackles the problem of calibrating the unknown parameters of a debris flow model with the drawback that the information regarding the experimental data treatment and processing is not available. In particular, we focus on the evolution over time of the flow thickness of the debris with dam-break initial conditions. The proposed methodology consists of establishing an approximation of the numerical model using a polynomial chaos expansion that is used in place of the original model, saving computational burden. The values of the parameters are then inferred through a Bayesian approach with a particular focus on inference discrepancies that some of the important features predicted by the model exhibit. We build the model approximation using a preconditioned non-intrusive method and show that a suitable prior parameter distribution is critical to the construction of an accurate surrogate model. The results of the Bayesian inference suggest that utilizing directly the available experimental data could lead to incorrect conclusions, including the over-determination of parameters. To avoid such drawbacks, we propose to base the inference on few significant features extracted from the original data. Our experiments confirm the validity of this approach, and show that it does not lead to significant loss of information. It is further computationally more efficient than the direct approach, and can avoid the construction of an elaborate error model.

A unified CFD‐DEM approach for modeling of debris flow impacts on flexible barriers

SummaryThis paper presents a unified modeling framework to investigate the impacts of debris flow on flexible barriers, based on coupled computational fluid dynamics and discrete element method (CFD‐DEM). We consider a debris flow as a mixture of fluid and particles where the fluid and particle phases are modeled by the CFD and the DEM, respectively. The fluid‐particle coupling is considered by the exchange of interaction forces between CFD and DEM calculations. The flexible barrier is simulated by the DEM as a network of bonded particles with remote interactions. The proposed coupled CFD‐DEM approach enables us to conveniently handle the complicated three‐way interactions among the fluid, the particles, and the flexible barrier structure for debris flow impact simulations. The proposed approach is first used to investigate the influences of channel inclination and the volumetric solid fraction in a debris mixture on the impact force, the resultant deformation, and the retained mass in a flexible barrier. The predictions agree well with existing experimental and numerical studies. We further examine the possible failure modes of a flexible barrier under debris flow impact and their underlying mechanisms. The performance of different components in a flexible barrier system, including single wires, double twists and cables, and their load sharing mechanisms, are carefully evaluated. The proposed unified framework offers a novel, promising pathway towards physically based, quantitative analysis and design of flexible barriers for debris flow mitigation.