Abstract. r.avaflow represents an innovative open-source computational tool for routing rapid mass flows, avalanches, or process chains from a defined release area down an arbitrary topography to a deposition area. In contrast to most existing computational tools, r.avaflow (i) employs a two-phase, interacting solid and fluid mixture model (Pudasaini, 2012); (ii) is suitable for modelling more or less complex process chains and interactions; (iii) explicitly considers both entrainment and stopping with deposition, i.e. the change of the basal topography; (iv) allows for the definition of multiple release masses, and/or hydrographs; and (v) serves with built-in functionalities for validation, parameter optimization, and sensitivity analysis. r.avaflow is freely available as a raster module of the GRASS GIS software, employing the programming languages Python and C along with the statistical software R. We exemplify the functionalities of r.avaflow by means of two sets of computational experiments: (1) generic process chains consisting in bulk mass and hydrograph release into a reservoir with entrainment of the dam and impact downstream; (2) the prehistoric Acheron rock avalanche, New Zealand. The simulation results are generally plausible for (1) and, after the optimization of two key parameters, reasonably in line with the corresponding observations for (2). However, we identify some potential to enhance the analytic and numerical concepts. Further, thorough parameter studies will be necessary in order to make r.avaflow fit for reliable forward simulations of possible future mass flow events.

No abstract

No abstract

Changing high‐mountain environments are characterized by destabilizing ice, rock or debris slopes connected to evolving glacial lakes. Such configurations may lead to potentially devastating sequences of mass movements (process chains or cascades). Computer simulations are supposed to assist in anticipating the possible consequences of such phenomena in order to reduce the losses. The present study explores the potential of the novel computational tool r.avaflow for simulating complex process chains. r.avaflow employs an enhanced version of the Pudasaini (2012) general two‐phase mass flow model, allowing consideration of the interactions between solid and fluid components of the flow. We back‐calculate an event that occurred in 2012 when a landslide from a moraine slope triggered a multi‐lake outburst flood in the Artizón and Santa Cruz valleys, Cordillera Blanca, Peru, involving four lakes and a substantial amount of entrained debris along the path. The documented and reconstructed flow patterns are reproduced in a largely satisfactory way in the sense of empirical adequacy. However, small variations in the uncertain parameters can fundamentally influence the behaviour of the process chain through threshold effects and positive feedbacks. Forward simulations of possible future cascading events will rely on more comprehensive case and parameter studies, but particularly on the development of appropriate strategies for decision‐making based on uncertain simulation results. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Abstract. r.avaflow represents an innovative open source computational tool for routing rapid mass flows, avalanches or process chains from a defined release area down an arbitrary topography to a deposition area. In contrast to most existing computational tools, r.avaflow (i) employs a two-phase, interacting solid and fluid mixture model; (ii) is suitable for modelling more or less complex process chains and interactions; (iii) explicitly considers both entrainment and stopping i.e. the change of the basal topography; (iv) allows for the definition of multiple release masses and/or hydrographs; and (v) serves with built-in functionalities for validation, parameter optimization and sensitivity analysis. r.avaflow is freely available as a raster module of the GRASS GIS software, employing the programming languages Python and C along with the statistical software R. We exemplify the functionalities of r.avaflow by means of two sets of computational experiments: (1) generic process chains consisting in bulk mass and hydrograph release into a reservoir with entrainment of the dam and impact downstream; (2) the prehistoric Acheron rock avalanche, New Zealand. The simulation results are generally plausible for (1) and, after the optimization of two key parameters, reasonably in line with the corresponding observations for (2). However, we identify some potential to enhance the analytic and numerical concepts. Further, thorough parameter studies are necessary in order to make r.avaflow fit for reliable forward simulations of possible future mass flow events.

No abstract

An innovative approach for the analysis and interpretation of snow avalanche simulation in three dimensional terrain is presented. Snow avalanche simulation software is used as a supporting tool in hazard mapping. When performing a high number of simulation runs the user is confronted with a considerable amount of simulation results. The objective of this work is to establish an objective, model independent framework to evaluate and compare results of different simulation approaches with respect to indicators of practical relevance, providing an answer to the important questions: how far and how destructive does an avalanche move down slope. For this purpose the Automated Indicator based Model Evaluation and Comparison (AIMEC) method is introduced. It operates on a coordinate system which follows a given avalanche path. A multitude of simulation runs is performed with the snow avalanche simulation software SamosAT (Snow Avalanche MOdelling and Simulation – Advanced Technology). The variability of pressure-based run out and avalanche destructiveness along the path is investigated for multiple simulation runs, varying release volume and model parameters. With this, results of deterministic simulation software are processed and analysed by means of statistical methods. Uncertainties originating from varying input conditions, model parameters or the different model implementations are assessed. The results show that AIMEC contributes to the interpretation of avalanche simulations with a broad applicability in model evaluation, comparison as well as examination of scenario variations

Snow avalanche simulation software is a commonly used tool for hazard estimation and mitigation planning. In this study a depth-averaged flow model, combining a simple entrainment and friction relation, is implemented in the software SamosAT. Computational results strongly depend on the simulation input, in particular on the employed model parameters. A long-standing problem is to quantify the influence of these parameters on the simulation results. We present a new multivariate optimization approach for avalanche simulation in three-dimensional terrain. The method takes into account the entire physically relevant range of the two friction parameters (Coulomb friction, turbulent drag) and one entrainment parameter. These three flow model parameters are scrutinized with respect to six optimization variables (runout, matched and exceeded affected area, maximum velocity, average deposition depth and mass growth). The approach is applied to a documented extreme avalanche event, recorded in St Anton, Austria. The final results provide adjusted parameter distributions optimizing the simulation-observation correspondence. At the same time, the degree of parameter-variable correspondence is determined. We show that the specification of optimal values for certain model parameters is near-impossible, if corresponding optimization variables are neglected or unavailable.