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Two- and three-dimensional avalanche dynamics models are being increasingly used in hazard-mitigation studies. These models can provide improved and more accurate results for hazard mapping than the simple one-dimensional models presently used in practice. However, two- and three-dimensional models generate an extensive amount of output data, making the interpretation of simulation results more difficult. To perform a simulation in three-dimensional terrain, numerical models require a digital elevation model, specification of avalanche release areas (spatial extent and volume), selection of solution methods, finding an adequate calculation resolution and, finally, the choice of friction parameters. In this paper, the importance and difficulty of correctly setting up and analysing the results of a numerical avalanche dynamics simulation is discussed. We apply the two-dimensional simulation program RAMMS to the 1968 extreme avalanche event In den Arelen. We show the effect of model input variations on simulation results and the dangers and complexities in their interpretation.
The powerful avalanche simulation toolbox RAMMS (Rapid Mass Movements) is based on a depth-averaged
hydrodynamic system of equations with a Voellmy-Salm friction relation. The two empirical friction parameters
μ and correspond to a dry Coulomb friction and a viscous resistance, respectively. Although μ and lack a
proper physical explanation, 60 years of acquired avalanche data in the Swiss Alps made a systematic calibration
possible. RAMMS can therefore successfully model avalanche flow depth, velocities, impact pressure and run
out distances. Pudasaini and Hutter (2003) have proposed extended, rigorously derived model equations that
account for local curvature and twist. A coordinate transformation into a reference system, applied to the actual
mountain topography of the natural avalanche path, is performed. The local curvature and the twist of the
avalanche path induce an additional term in the overburden pressure. This leads to a modification of the Coulomb
friction, the free-surface pressure gradient, the pressure induced by the channel, and the gravity components
along and normal to the curved and twisted reference surface. This eventually guides the flow dynamics and
deposits of avalanches. In the present study, we investigate the influence of curvature on avalanche flow in
real mountain terrain. Simulations of real avalanche paths are performed and compared for the different models
approaches. An algorithm to calculate curvature in real terrain is introduced in RAMMS. This leads to a curvature
dependent friction relation in an extended version of the Voellmy-Salm model equations. Our analysis provides
yet another step in interpreting the physical meaning and significance of the friction parameters used in the
RAMMS computational environment.
Numerical avalanche dynamics models have become an essential part of snow engineering. Coupled with field observations and historical records, they are especially helpful in understanding avalanche flow in complex terrain. However, their application poses several new challenges to avalanche engineers. A detailed understanding of the avalanche phenomena is required to construct hazard scenarios which involve the careful specification of initial conditions (release zone location and dimensions) and definition of appropriate friction parameters. The interpretation of simulation results requires an understanding of the numerical solution schemes and easy to use visualization tools. We discuss these problems by presenting the computer model RAMMS, which was specially designed by the SLF as a practical tool for avalanche engineers. RAMMS solves the depth-averaged equations governing avalanche flow with accurate second-order numerical solution schemes. The model allows the specification of multiple release zones in three-dimensional terrain. Snow cover entrainment is considered. Furthermore, two different flow rheologies can be applied: the standard Voellmy–Salm (VS) approach or a random kinetic energy (RKE) model, which accounts for the random motion and inelastic interaction between snow granules. We present the governing differential equations, highlight some of the input and output features of RAMMS and then apply the models with entrainment to simulate two well-documented avalanche events recorded at the Vallée de la Sionne test site.
Digital elevation models (DEMs), represent the three-dimensional terrain and are the basic input for numerical snow avalanche dynamics simulations. DEMs can be acquired using topographic maps or remote-sensing technologies, such as photogrammetry or lidar. Depending on the acquisition technique, different spatial resolutions and qualities are achieved. However, there is a lack of studies that investigate the sensitivity of snow avalanche simulation algorithms to the quality and resolution of DEMs. Here, we perform calculations using the numerical avalance dynamics model RAMMS, varying the quality and spatial resolution of the underlying DEMs, while holding the simulation parameters constant. We study both channelized and open-terrain avalanche tracks with variable roughness. To quantify the variance of these simulations, we use well-documented large-scale avalanche events from Davos, Switzerland (winter 2007/08), and from our large-scale avalanche test site, Valĺee de la Sionne (winter 2005/06). We find that the DEM resolution and quality is critical for modeled flow paths, run-out distances, deposits, velocities and impact pressures. Although a spatial resolution of ~25 m is sufficient for large-scale avalanche modeling, the DEM datasets must be checked carefully for anomalies and artifacts before using them for dynamics calculations.
This paper examines the positive and negative aspects of a range of interpretations of nearest-neighbours models. Measures-oriented and distributionoriented verification methods are applied to categorial, probabilistic and descriptive interpretations of nearest neighbours used operationally in avalanche forecasting in Scotland and Switzerland. The dependence of skill and accuracy measures on base rate is illustrated. The purpose of the forecast and the definition of events are important variables in determining the quality of the forecast. A discussion of the application of different interpretations in operational avalanche forecasting is presented.