Dam Failure Research Articles

Numerical Simulation of Tailings Flow from Dam Failure over Complex Terrain.

A tailings dam failure can lead to disastrous impacts on people’s livelihood and the surrounding ecological environment. Due to interactions among water, tailings and ground, the mechanism of a tailings flow is more complicated than that of a flood flow. In this paper, the tailings flow is regarded as a homogeneous and incompressible non-Newtonian fluid. Its rheological properties were studied through rheological tests conforming to the Bingham model. The rheological parameters were further used in a Computational Fluid Dynamics (CFD) simulation over complex terrain to explore the tailings flow characteristics. The method was validated with experimental results of a non-Newtonian dam-break flow from literature. The flow characteristics, including flow velocity, runout distance, inundation area and depth, were analyzed in the case of the Dagangding tailings dam. The results showed that the downstream railway and village would not be affected in a conservative scenario. Finally, the effects of two measures for preventing tailings flow hazards were discussed. Setting the check dam and planting grasses and trees can effectively mitigate the damage of tailings flow.

Hazards identification and characterisation of the tailings storage facility dam failure and engineering applications

ABSTRACT To characterise the relationships among the hazards associated with tailings storage facility (TSF) dam failure, interpretive structural modelling (ISM) is used to hierarchise, structuralise and visualise them. Based on evidence, 15 hazards in four categories are identified, and are classified into seven levels and four clusters. The results show that seven hazards can be regarded as the fundamental hazards. The majority of hazards associated with technology factor can be seen as transactional hazards and are closely related to the water balance problem. The proposed ISM method offers theoretical reference and improves risk management for the TSF and the mining industry.

Failure modes of concrete gravity dam subjected to near-field underwater explosion: Centrifuge test and numerical simulation

Concrete gravity dams are often referred to as vertical cantilever structures with approximately fixed bottoms due to their massive gravity, frictions with the foundation, and additional anti-sliding techniques. Given this, when modeling concrete gravity dams subjected to underwater explosions, should the dam bottom be considered as the fixed boundary or the frictional boundary? In this study, two small-scale centrifuge tests and numerical simulations were used to investigate the dam failure modes due to near-field underwater explosions. Emphasis was placed on the effect of dam bottom boundary condition (DB-BC) to improve understanding of dam failure mechanisms and provide references for constructing experimental and numerical dam models. To this end, the current research began with a combined experimental and numerical investigation on the failure modes of dams with fixed bottoms. Then, a numerical study was conducted to evaluate the effect of DB-BC. Results revealed that dams with frictional bottoms demonstrated essentially the same failure mode as those with fixed bottoms. Both exhibited mainly the structural bending-induced tensile failure mode. To the authors’ knowledge, this is the first time the effect of DB-BC has been explored. In particular, by centrifuge tests, this paper presented the urgently needed experimental data in this field including dam failure patterns and strain histories as well as test videos.

Catastrophe process of outburst debris flow triggered by the landslide dam failure

Strong earthquakes can induce large amounts of loose solid materials, forming landslide dams and blocking narrow flow channels. Under extreme rainfall conditions, instability can lead to an outburst of debris flow once the landslide dam has formed it. On July 10, 2013, a volume of 4.5 × 104 m3 of debris flow occurred in the Yangling gully, Wenchuan County, China. This event can be categorized as an outburst of the debris flow that might seriously threaten valley residents, existing sediment transport countermeasure works, and road infrastructures. This paper describes a typical outburst of debris flow, calculates its obstructive coefficient, simulates the process under various recurrence intervals, and analyzes the efficacy of a new mitigation project.Related research results have laid the foundation for further study of the risk assessment and early warning of debris flow due to landslide dam failure. In this paper, an accurate computational model for the obstructive coefficient, closely related to the flow amplification effect, is established based on a dam break's physical experiments. Combined with the numerical calculation method, the movement process of the Yangling gully was simulated under the old artificial dam and the flow channel engineering conditions. By comparing the measured and the simulated accumulation area, the verification results illustrate that the accumulation area considering the obstructive coefficient model is closer to the measured value. Based on the obstructive coefficient computational model, the results illustrate the outburst of debris flow discharge for various recurrence intervals (50, 100, and 200 years respectively) to perform scenario simulations of Yangling gully under the new mitigation project conditions.

Prototype Scale Evaluation of Non-Newtonian Algorithms in HEC-RAS: Mud and Debris Flow Case Studies of Santa Barbara and Brumadinho

The Santa Barbara post-wildfire debris flows and the Brumadinho tailing-dam failure were two of the most catastrophic flood events of the late 2010s. Both these events carried so much solid-phase material, that classic, clear-water, flood risk approaches cannot replicate them, or forecast other events like them. This case study applied the new non-Newtonian features in HEC-RAS 6.1 to these two events, testing the most widely used flood risk model on the two most common mud and debris flow hazards (post-wildfire floods and mine tailing dam failures). HEC-RAS reproduced the inundation boundaries and the event timing (where available) for both events. The ratio between the largest debris flow clasts and the channel size, parametric trade-offs, the “convex” alluvial plain topography, and the stochasticity introduced by urban infrastructure made the Santa Barbara modeling more difficult and less precise than Brumadinho. Despite these challenges, the results provide prototype scale validation and verification of these new tools in this widely applied flood risk model.

Application of inspection and monitoring in the reduction of risk for mine tailings dams

Recent high-profile failures of mine tailings dams across the globe have once again raised geotechnical interest in these structures. Much of the recent discussion in the technical literature has focused on the prediction of the ultimate stress state and thus of the failure potential of tailings materials. Concentration solely on geomechanical properties is important in the understanding of the fundamental characteristics of extractive waste but limits the appraisal of risk potential in these complex and multi-faceted structures. It is evident from the author's study of failures of extractive waste facilities over a period of some 50 years that knowledge of geomechanical properties alone would not have prevented disasters in many instances. The fundamental risks posed by these structures are reviewed in this paper with respect not only to their design but also to their construction, operation and eventual closure. The analysis confirms that other crucial elements of design and construction, if neglected, potentially pose higher risks than a lack of knowledge of geomechanics alone. A broad list of risk reduction criteria that should be applied to mine tailings dams is presented and examples of where and how such neglect has resulted in recent high-profile failures are cited. A review of general risk reduction criteria is presented and compared with existing standards and guidelines.

Experimental Investigation on the Breaching Process of Landslide Dams with Differing Materials under Different Inflow Conditions.

Landslide dams are dangerous because the outburst floods produced by dam failures seriously threaten life and property downstream. In this study, a series of physical flume tests were conducted to investigate the breaching process of landslide dams with fine-grained, well graded, and coarse-grained material under different inflow conditions. The effects of dam material and inflow discharge on the breach development, outflow discharge and erosion characteristics were studied. The erosion resistance of materials and lateral collapses were also discussed. Experimental results reveal that the whole breaching process is determined by the water-sediment interaction. For the fine-grained dams, a general constant downstream slope angle is maintained during the breaching process. For the well-graded dams, a step-pool structure is generated due to the scarp erosion. For the coarse-grained dams, they can remain stable under normal circumstances but fail by overtopping in a short duration under the extreme inflow condition. The final breach of the dam with higher fine content or larger inflow discharge is deeper and narrower. In addition, many fluctuations are observed in the changing curve of the erosion rates along the flow direction for the well-graded and coarse-grained dams. The erosion resistance of materials increases along the flow direction, which needs to be further considered in physically based breach models. Furthermore, the lateral collapse is affected by the dam material instead of inflow discharge. The lower fine content causes more lateral collapses with smaller volumes.

Hybrid Differential Evolution-Based Regression Tree Model for Predicting Downstream Dam Hazard Potential

There are a large number of dams throughout the United States, and a considerable portion of them are categorized as having high hazard potential. This state of affairs constitutes a challenge, especially when coupled with their rapid deterioration. As such, this research paper proposes an optimized data-driven model for the fast and efficient prediction of dam hazard potential. The proposed model is envisioned on two main components, namely model development and model assessment. In the first component, a hybridization of the differential evolution algorithm and regression tree to forecast downstream dam hazard potential is proposed. In this context, the differential evolution (DE) algorithm is deployed to: (1) automatically retrieve the optimal set of input features affecting dam hazard potential; and (2) amplify the search mechanism of regression tree (REGT) through optimizing its hyper parameters. As for the second component, the developed DE-REGT model is validated using four folds of comparative assessments to evaluate its prediction capabilities. In the first fold, the developed DE-REGT model is trialed against nine highly regarded machine learning and deep learning models. The second fold is designated to structure, an integrative ranking of the investigated data-driven models, counting on their scores in the performance evaluation metrics. The third fold is used to study the effectiveness of using differential evolution for the hyper parameter optimization of regression tree. The fourth fold aims at testing the usefulness of using differential evolution as a feature extractor algorithm. Performance comparative analysis demonstrated that the developed DE-REGT model outperformed the remainder of the data-driven models. It accomplished mean absolute percentage error, relative absolute error, mean absolute error, root squared error, root mean squared error and a Nash–Sutcliffe efficiency of 9.62%, 0.27, 0.17, 0.31, 0.41 and 0.74, respectively. Results also revealed that the developed model managed to perform better than other meta-heuristic-based regression tree models and classical feature extraction algorithms, exemplifying the appropriateness of using differential evolution for hyper parameter optimization and feature extraction. It can be argued that the developed model could assist policy makers in the prioritization of their maintenance management plans and reduce impairments caused by the failure or misoperation of dams.

Drones, virtual reality, and modeling: communicating catastrophic dam failure

ABSTRACT Dam failures occur worldwide and can be economically and ecologically devastating. Communicating the scale of these risks to the general public and decision-makers is imperative. Two-dimensional (2D) dam failure hydraulic models inform owners and floodplain managers of flood regimes but have limitations when shared with non-specialists. This study addresses these limitations by constructing a 3D Virtual Reality (VR) environment to display the 1976 Teton Dam disaster case study using a pipeline composed of (1) 2D hydraulic model data (extrapolated into 3D), (2) a 3D reconstructed dam, and (3) a terrain model processed from UAS (Uncrewed Airborne System) imagery using Structure from Motion photogrammetry. This study validates the VR environment pipeline on the Oculus Quest 2 VR Headset with the criteria: immersion fidelity, movement, immersive soundscape, and agreement with historical observations and terrain. Through this VR environment, we develop an effective method to share historical events and, with future work, improve hazard awareness; applications of this method could improve citizen engagement with Early Warning Systems. This paper establishes a pipeline to produce a visualization tool for merging UAS imagery, Virtual Reality, digital scene creation, and sophisticated 2D hydraulic models to communicate catastrophic flooding events from natural or human-made levees or dams. Abbreviations: ASDSO: Association of State Dam Safety Officials; DEM: digitalelevation model; EWS: Early Warning System; HEC-RAS: Hydrologic EngineeringCenter-River Analysis System; HMD: Head-Mounted Display; NOAA: NationalOceanic and Atmospheric Administration; Reclamation: Bureau of Reclamation; United States Agency; SfM: Structure from Motion; 1D: one-dimensional; 2D:two-dimensional; 3D: three-dimensional; UAS: Uncrewed Aerial System (drone); US:United States; USACE: United States Army Corps of Engineers; VR: VirtualReality

Estimating widespread beaver dam loss: Habitat decline and surface storage loss at a regional scale

AbstractThe loss of beaver populations has commonly been accompanied by the failure of beaver dams, leading to stream incision, water table lowering, and the eventual transition from a beaver meadow to a drier riparian corridor. Widespread decline in North American beaver populations (Castor canadensis) has been documented from pre‐European settlement to the current day, representing an estimated 80% to 98% loss of historical populations. While individual case studies have investigated the ecosystem impacts of local beaver population loss, few studies have quantified large‐scale changes associated with widespread population decline. Here, we use the Beaver Restoration Assessment Tool to model landscape‐scale habitat suitability and beaver dam capacity in Colorado, USA, in order to determine whether a widespread loss in beaver population corresponds to a similar scale decline in the capacity to sustain beaver on the landscape and declines in physical benefits associated with beaver, such as surface water and sediment storage. Currently, the statewide stream network (298,119 stream kilometers) can support approximately 1.36 million beaver dams, compared with 2.39 million dams historically. All regions of Colorado have seen a decline in beaver dam capacity from historical conditions, likely due to agriculture, urbanization, and loss of vegetation necessary to beaver. Beaver dam capacity loss is accompanied by an approximate 40% decline in beaver‐mediated surface water and sediment storage potential across the state. Regions with high percent loss in storage potentials also had a high percentage of drainage network that had experienced beaver dam capacity losses of 15 or more dams per kilometer, which highlights the disproportionate impacts of losing high dam density reaches (i.e., beaver meadows). Extreme dam density declines were rare, and instead, most reaches have undergone a shift from high to moderate capacity. Statewide shifts in beaver dam capacity highlight the opportunity for using beaver‐related restoration in Colorado and across the American West.

Modeling and Risk Analysis of Dam-Break Flooding in a Semi-Arid Montane Watershed: A Case Study of the Yabous Dam, Northeastern Algeria

The risk related to embankment dam breaches needs to be evaluated in order to prepare emergency action plans. The physical and hydrodynamic parameters of the flood wave generated from the dam failure event correspond to various breach parameters, such as width, slope, and formation time. This study aimed to simulate the dam breach failure scenario of the Yabous dam (northeast Algeria) and analyze its influence on the related areas (urban and natural environments) downstream of the dam. The simulation was completed using the sensitivity analysis method to assess the impact of breach parameters and flooding on the dam break scenario. The flood wave propagation associated with the dam break was simulated using the one-dimensional HEC-RAS hydraulic model. This study applied a sensitivity analysis of three breach parameters (slope, width, and formation time) on five sites selected downstream of the embankment dam. The simulation showed that the maximum flow of the flood wave recorded at the level of the breach was 8768 m3/s, which gradually attenuated along the river course to reach 1972.7 m3/s at about 8.5 km downstream the dam. This study established the map of flood risk areas that illustrated zones threatened by the flooding wave triggered by the dam failure due to extreme rainfall events. The sensitivity analysis showed that flood wave flow, height, and width revealed positive and similar changes for the increases in adjustments (±25% and ±50%) of breach width and slope in the five sites. However, flood wave parameters of breach formation time showed significant trends that changed in the opposite direction compared to breach slope and width. Meanwhile, the adjustments (±25% and ±50%) of the flood hydrograph did not significantly influence the flood parameters downstream of the dam. In the present study, the HEC-RAS 1-D modeling demonstrated effectiveness in simulating the propagation of flood waves downstream of the dam in the event of dam failure and highlighted the impact of the breach parameters and the flood hydrographical pattern on flood wave parameters.

IMPACTOS PSICOSSOCIAIS DOS DESASTRES DA MINERAÇÃO EM MARIANA E BRUMADINHO: uma revisão integrativa

The failures of mining tailings dams in Mariana, in 2015, and in Brumadinho, in 2019, are identified as the biggest environmental disaster and the biggest work accident in the history of Brazil, respectively. This article aimed to analyze the background of these tragedies, their environmental and socioeconomic impacts, as well as the psychosocial consequences for the population directly and indirectly affected by these tragedies. The method used was the integrative literature review. Searches for scientific articles were carried out in the SciELO, PePSIC and BVS Salud BIREME databases, using the following combination of descriptors: “Brumadinho” & “desastre” and “Mariana” & “desastre”. Fourteen articles were analyzed, published between 2015 and 2020. The results show the weaknesses of the State in the prevention, resolution, and accountability of such crimes, demarcating a history of impunity for the companies involved, lack of reparation for socio-environmental damage, and helplessness to the affected population. Furthermore, the role of emergency and disaster psychology in these scenarios was analyzed, highlighting the ethical commitment of this profession to the promotion of mental health and the guarantee of rights.

Assessment of life loss due to dam breach using improved variable fuzzy method

In recent years, several factors, such as frequent extreme weather, disrepair of dams, and improper management, have caused frequent dam failures, posing a significant threat to people's lives downstream. At present, the life loss is evaluated using the empirical formula method, in which the recommended approximate and threshold results are obtained through linear regression or statistical analysis. However, this method is sometimes insufficient because of the lack of a historical dataset and low availability, and it tends to simplify or ignore the influence of some factors in regression. During the research, most objects are considered as individual cases, and thus, the universality and scientificity of the application of evaluation models or parameters need further discussion. The variable fuzzy set theory features rigorous mathematical clarity and fuzziness of things and is widely used in the optimal decision evaluation model. Although, the traditional variable fuzzy evaluation method is widely used to deal with the linear variation in the index, some indexes, such as dam storage capacity and downstream population at risk, can cause non-linear problems, directly affecting the accuracy of membership evaluation results. Therefore, an improved model was proposed, where the relative difference formula was improved through logarithmic transformation and boundary constraint. The improved method was applied to the sequencing of life loss risk consequences for four reservoirs. The evaluation result was consistent with the actual situation of the disaster and the actual mortality rate. The scientificity and practicability of the improved model were verified, providing a new perspective for reservoir risk ranking and enriching the risk management theory.

Errors in finite element analysis of backward erosion piping

Backward erosion piping (BEP) is a type of internal erosion responsible for the failure of many dams and levees. BEP occurs when small, shallow erosion channels progress upstream through foundation sands beneath the structure. As analysis of BEP involves coupling two different sets of flow equations to describe the groundwater flow and erosion pipe flow, the solution contains a singularity in the gradient field at the juncture of the soil and pipe domains. In addition, the erosion process is highly localized, often occurring over length scales of 1 cm or less. While it is well known that singularities and localized phenomena cause high errors in numerical solutions, there has been no assessment of the magnitude of these errors in BEP numerical models. This study evaluates the magnitude of error in BEP finite element models through comparison of numerical results to measurements from a highly instrumented BEP experiment. The results indicate that discretization errors related to the pipe geometry can cause 50%–300% error in the solution near the pipe tip when the pipe is represented via linear, 1D elements. These errors are significant and must be considered for models that assess pipe progression based on the local solution near the pipe tip. Results also indicate that the pipe width must be modeled as twice the physical pipe width to accurately represent the pipe flow when assuming a rectangular cross sectional shape for the erosion pipe.

Flow Discharge Prediction Study Using a CFD-Based Numerical Model and Gene Expression Programming

The significance of spillways is to allow the flood to be safely discharged from downstream. There is a strong correlation between the poor design of spillways and the failures of dams. In order to address this concern, the present study investigates the flow over the Nazloo-ogee spillway using the CFD 3D numerical model and an artificial intelligence method called Gene Expression Programming (GEP). In a physical model, discharge and flow depths were calculated for 21 different total heads. Among different turbulence models, the RNG turbulence model achieved the maximum compatibility in computational fluid dynamic simulation. In addition, GEP was used to estimate Q, in which 70% of collected data was dedicated to training and 30% to testing. R2, RMSE, and MAE were obtained as performance criteria, and the new mathematical equation for the prediction of discharge was obtained using this model. Finally, the numerical model and GEP outputs were compared with the experimental data. According to the results, the numerical model and GEP exhibited a high level of correspondence in simulating flow over an ogee-crested spillway.

Graph based knowledge models for capitalizing, predicting and learning: A proof of concept applied to the dam systems

The capitalization and the analysis of historical information is nowadays a prerequisite for any effective risk management and assessment in a wide range of domains. Despite the development of mathematical models, procedures, support decision systems and databases, some engineering disciplines, such as civil engineering, remain resistant to the use of new digital technology due to the gap between the expectations of the engineers and the support that the tools may really provide. It is essential to propose a tool able to process both cross disciplinary and interdisciplinary knowledge flux and feedback from experience in a common and convenient unifying framework. The aim is to assist and to support engineering work and to make the task of knowledge modelling easier. The domain of dam systems is no exception to the rule. Dam failures are still commonplace. These failures stem from a lack of understanding about the complex relationships between three different factors: random hazards, the limit states of dam structures along with human activities and decisions. No generic and holistic approach is currently available that permits the processing of both knowledge and data, performs inferences and is easily usable for all types of users. This paper proposes the basic principles of a convenient design methodology for capitalizing, learning and predicting based on the formalism of conceptual graphs. The aim is to provide an easily usable tool able to (1) capitalise heterogeneous knowledge and store a database about dams, (2) issue alerts on current projects, (3) draw lessons from past dam failures and (4) tackle key issues in forensic civil engineering.

Tailings Dam Failures: A Historical Analysis of the Risk

Tailings Dam Failures: A Historical Analysis of the Risk

Terrestrial and aquatic ecotoxicity of iron ore tailings after the failure of VALE S.A mining dam in Brumadinho (Brazil)

This study consists of an ecotoxicological assessment related to one the most important environmental Brazilian disasters: the failure of an iron mining dam of the Vale S.A. in Brumadinho (Minas Gerais State, Brazil). Tailing samples (mixed with many other materials) were collected in three areas: (i) Zona Quente (n = 9) – close to the dam collapse; (ii) Parque das Cachoeiras (n = 3) – downstream of the Zona Quente; and (iii) Alberto Flores (n = 3), closer to Paraopeba river (an important tributary of one of the most important Brazilian watersheds). Acute ecotoxicological tests with Eisenia andrei and Daphnia similis and chronic reproduction tests with Folsomia candida and Chlorella vulgaris were performed. The bioassays with aquatic organisms were carried out with elutriates of the samples. Metal concentrations and physical, chemical and mineralogical properties of the samples were determined to support the interpretation of the ecotoxicological data. The increase of the particle density values (significantly correlated to an anomalous iron-enrichment and positive ΔpH values) seem to play a relevant role in the toxicity. As a result of iron-enrichment, the reduction of organic matter contents and water holding capacity were also crucial in the toxicity. Metal-enrichment factors showed abnormally high values, especially for Fe, Mn and Ni, while toxic metals concentrations exceeded the limits established by Brazilian law. Reproduction chronic effects were more intense than the acute ones, for both aquatic and soil organisms. Such extremely low reproduction levels of F. candida and C. vulgaris should be highlighted, since such organisms have a key ecological relevance. The samples collected in the Zona Quente were significantly different from the samples collected in downstream areas — fact that might be related to a high energy and turbulent flux of tailings in zones closer to dam, and the reduction of its energy in downstream areas.

Scenario simulation of the geohazard dynamic process of large-scale landslides: a case study of the Xiaomojiu landslide along the Jinsha River

Large-scale landslides often cause severe damage due to their long run-out distances and having disaster chain effects. Scenario simulation has been adopted in the current work in order to analyze the Xiaomojiu landslide dynamic processes. The landslide characteristics and topography data are obtained via field investigations, whereas high-resolution topographic data (0.17 m) are obtained using an Unmanned Aerial Vehicle. The landslide sliding velocity, deposition characteristics, and flood outburst after a landslide dam failure were obtained using Particle Flow Code (PFC-3D) which introduced the changeable friction coefficient and the HEC-RAS software. The results showed that: 1. The landslide presents a scallop shape with a length of 1110 m, an average width of 950 m, and an area of 1.05 × 106 m2. The average thickness and volume of the sliding body are approximately 50 m and 5.45 × 107 m3. The InSAR (Interferometric Synthetic Aperture Radar) deformation analysis showed that the Xiaomojiu landslide has a maximum annual displacement rate of 60 mm/y and a maximum accumulation deformation of 180 mm since November 25, 2017. 2. The failure process of the Xiaomojiu landslide lasted for 65 s with a maximum velocity of 78.2 m/s. According to the landslide simulation results, the deposited area is approximately 2023 m long, 900 m wide, and has a maximum height of approximately 149 m. 3. A landslide-dammed lake with an elevation of 2940 m and a storage capacity of 4.13 × 109 m3 is formed after the landslide blocks the Jinsha River, and the maximum peak flow rate of the breach is 12051.7 m3/s, 43,451.4 m3/s, 148,635.6 m3/s, and 304,544.7 m3/s for the landslide-dammed failure degrees of 15%, 25%, 50%, and 75%, respectively. These results provide a reference for the risk analysis and mitigation of the landslide.

Quantifying multiple uncertainties in modelling shallow water-sediment flows: A stochastic Galerkin framework with Haar wavelet expansion and an operator-splitting approach

The interactive processes of shallow water flow, sediment transport, and morphological evolution constitute a hierarchy of multi-physical problems of significant interests in a spectrum of engineering and science areas. To date, modelling shallow water hydro-sediment-morphodynamic (SHSM) processes is subject to multiple sources of uncertainty arising from input data and incomplete understanding of the underlying physics. A stochastic SHSM model with multiple uncertainties has yet to be developed as most SHSM models still concern deterministic problems and only one has been recently extended to a stochastic setting, but is restricted to a single source of uncertainty. Here we first present a new probabilistic SHSM model incorporating multiple uncertainties within the stochastic Galerkin framework using a multidimensional tensor product of Haar wavelet expansion to capture local, nonlinear variations in joint probability distributions and an operator-splitting-based method to ensure that the modelling system remains hyperbolic. Then, we verify the proposed model via benchmark probabilistic numerical tests with joint uncertainties introduced in initial and boundary conditions, matching established experiments of flow-sediment-bed evolutions driven by a sudden dam break and by a landslide dam failure and large-scale rapid flow-sediment-bed evolution in response to flash flood. The present work facilitates a promising modelling framework for quantifying multiple uncertainties in practical shallow water hydro-sediment-morphodynamic modelling applications.