Simulating the propagation of wet snow avalanches: challenges and perspectives

Author(s):  
Guillaume Chambon ◽  
Thierry Faug ◽  
Mohamed Naaim ◽  
Nicolas Eckert

<p>Recent winters saw a striking increase in wet snow avalanche activity. Compared to dry avalanches, wet snow avalanches present uniquely distinctive features such as slower velocities, larger depths, unusual trajectories and deposit shapes, and a paste-like rheology that can result in large shear and normal stresses. In addition, the behavior of wet avalanches may strongly vary depending on the actual snow liquid water content. Complex transitions between dry (cold) and wet (hot) behaviors have also been observed during the propagation of single avalanche events. Current numerical models of avalanche dynamics are challenged when it comes to capturing the full spectrum of these different regimes, and the transitions in between. In this contribution, we critically review the various rheological models that have been proposed in the literature to simulate dry and wet snow avalanches in the frame of depth-averaged shallow-flow approaches. On this basis, a simplified parametric rheological law is proposed, with the objective of representing both dry-like and wet-like behaviors and allowing for smooth transitions between them. The law is implemented in a robust 2D shallow-flow simulation code, and systematic sensitivity studies are performed on synthetic and real topographies. Simulation outcomes are analysed in terms of propagation dynamics and deposition patterns, and the ability of the model to capture both dry and wet regimes is discussed. Lastly, a specific calibration methodology is proposed to infer the relevant mechanical parameters from documented avalanche events.</p>

2021 ◽  
Author(s):  
Guillaume Chambon ◽  
Thierry Faug ◽  
Mohamed Naaim

<p>Wet snow avalanches present distinctive features such as unusual trajectories, peculiar deposit shapes, and a rheological behavior displaying a combination of granular and pasty features depending on the actual snow liquid water content. Complex transitions between dry (cold) and wet (hot) flow regimes can also occur during a single avalanche flow. In an attempt to account for this complexity, we report on numerical simulations of avalanches using a frictional-cohesive rheology implemented in a depth-averaged shallow-flow model. Through extensive sensitivity studies on synthetic and real topographies, we show that cohesion plays a key role to enrich the physics of the simulated flows, and to represent realistic avalanche behaviors. First, when coupled to a proper treatment of the yielding criterion, cohesion provides a way to define objective stopping criteria for the flow, independently of the issues incurred by artificial diffusion of the numerical scheme. Second, and more importantly, the interplay between cohesion and friction gives raise to a variety of nontrivial physical effects affecting the dynamics of the avalanches and the morphology of the deposits. The relative weights of frictional and cohesive contributions to the overall stress are investigated as a function of space and time during the propagation, and related to the formation of specific features such as lateral levées, hydraulic jumps, etc. This study represents a first step towards robust avalanches simulations, spanning the wide range of possible flow regimes, through shallow-flow approaches. Future improvements involving more refined cohesion parameterizations will be discussed.</p>


2011 ◽  
Vol 52 (58) ◽  
pp. 201-208 ◽  
Author(s):  
Christoph Mitterer ◽  
Hiroyuki Hirashima ◽  
Jürg Schweizer

AbstarctWet-snow avalanches are difficult to forecast, as the change from stable to unstable snow conditions occurs rapidly in a wet snowpack, often in response to water production and movement. Snow stratigraphy plays a vital role in determining flux behaviour. Capillary barriers or melt–freeze crusts can impede and divert water horizontally over large areas and thus may act as a failure layer for wet-snow avalanches. We present a comparison of measured and modelled liquid water content, θw, and snow stratigraphy during periods of wet-snow instabilities. Special attention is given to the reproducibility of capillary barriers, ponding of water on melt–freeze crusts and the timing of first wetting and of water arrival at the bottom of the snowpack, because these factors are believed to play a major role in the formation of wet-snow avalanches. In situ measurements were performed in the vicinity of automatic weather stations or close to recent wet-snow avalanches in order to compare them with model results. The simulations are based on two different water flux models incorporated within the 1-D snow-cover model SNOWPACK. The comparison of the two model runs with observed θw and stratigraphy revealed that both water-transport models reproduced the ponding of water on melt–freeze crusts. However, in both models melt–freeze crusts were transformed to normal melt forms earlier than observed in nature, so still existing ponding was not captured by the models. Only one of the models was able to reproduce capillary barriers in agreement with observations. The time of the first wetting at the surface was well predicted, but the simulated arrival time of the wetting front at the bottom of the snowpack differed between the simulations; it was either too early or too late compared with the observation.


2017 ◽  
Author(s):  
Cesar Vera Valero ◽  
Nander Wever ◽  
Marc Christen ◽  
Perry Bartelt

Abstract. Snow avalanche motion is strongly dependent on the temperature and water content of the snowcover. In this paper we use a snowcover model, driven by measured meteorological data, to set the initial and boundary conditions for wet snow avalanche calculations. The snowcover model provides estimates of snow depth, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion depths for an avalanche dynamics model. We compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density) in the release and erosion zones is identified to be more important than an exact specification of temperature and water content. For wet snow avalanches, this implies that the layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. This is an interesting result because it indicates the critical role of fracture depth as an input parameter in avalanche simulations. Advanced thermomechanical models appear to be better suited than existing guideline procedure to simulate wet snow avalanches when accurate snowcover information is available.


2013 ◽  
Vol 54 (62) ◽  
pp. 19-24 ◽  
Author(s):  
Yukari Takeuchi ◽  
Hiroyuki Hirashima

AbstractThe Makunosawa valley, Myoko, Japan, experiences frequent avalanches and is therefore ideally suited to study how meteorological elements influence avalanche activity. Since 2000, five large-scale snow avalanches with running distances >2000 m have been observed and some characteristics of these avalanches have been obtained. However, the characteristics of the snowpack in the starting zones could not be observed because they are too difficult to approach and no snow-pit observations have been carried out. We simulated the variations in the snowpack in the starting zone using the numerical snowpack model SNOWPACK with local meteorological data. The results indicate a layer of faceted crystals with low shear strength followed by rapid loading from snowfall was the cause of three avalanches in February. Conversely, no layer of faceted crystals was shown by the model before a January avalanche and we assume the sliding surface of the avalanche to be precipitation particles. The only wet-snow avalanche is attributed to a decrease in shear strength due to infiltration of meltwater and an increase in liquid water content in the boundary of two layers of different grain sizes.


1992 ◽  
Vol 16 ◽  
pp. 7-10 ◽  
Author(s):  
Hu Ruji ◽  
Ma Hong ◽  
Wang Guo

The seasonal snow cover in the Tien Shan mountains is characterized by low density, low liquid-water content and low temperature. It is known as typical dry snow. Large temperature gradients in the basal layer of the snow cover exist throughout the entire period of snow accumulation, and depth hoar is therefore extremely well-developed. Full-depth depth-hoar avalanches, however, seldom occur. Avalanches in the Tien Shan mountains are mostly loose snow avalanches. Although normally not large in size, they are the most dangerous type. The occurrence of hazardous avalanches shows cycles of about ten years because of periodic climatic variations.


2005 ◽  
Vol 5 (6) ◽  
pp. 821-832 ◽  
Author(s):  
A. Zischg ◽  
S. Fuchs ◽  
M. Keiler ◽  
G. Meißl

Abstract. The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.


1998 ◽  
Vol 27 ◽  
pp. 427-432 ◽  
Author(s):  
Anthony P. Worby ◽  
Xingren Wu

The importance of monitoring sea ice for studies of global climate has been well noted for several decades. Observations have shown that sea ice exhibits large seasonal variability in extent, concentration and thickness. These changes have a significant impact on climate, and the potential nature of many of these connections has been revealed in studies with numerical models. An accurate representation of the sea-ice distribution (including ice extent, concentration and thickness) in climate models is therefore important for modelling global climate change. This work presents an overview of the observed sea-ice characteristics in the East Antarctic pack ice (60-150° E) and outlines possible improvements to the simulation of sea ice over this region by modifying the ice-thickness parameterisation in a coupled sea-ice-atmosphere model, using observational data of ice thickness and concentration. Sensitivity studies indicate that the simulation of East Antarctic sea ice can be improved by modifying both the “lead parameterisation” and “rafting scheme” to be ice-thickness dependent. The modelled results are currently out of phase with the observed data, and the addition of a multilevel ice-thickness distribution would improve the simulation significantly.


2021 ◽  
Vol 21 (8) ◽  
pp. 2447-2460
Author(s):  
Stuart R. Mead ◽  
Jonathan Procter ◽  
Gabor Kereszturi

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (“actual”) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano, as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This “fuzzification” of simulated results yields improvements in targeted performance metrics relative to a length scale parameter at the expense of decreases in opposing metrics (e.g. fewer false negatives result in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision-making from simulated data.


Author(s):  
Benjamin Hatchett

On 5-7 April 2018 a landfalling atmospheric river resulted in widespread heavy precipitation in the Sierra Nevada of California and Nevada. Observed snow levels during this event were among the highest snow levels recorded since observations began in 2002 and exceeded 2.75 km for 31 hours in the northern Sierra Nevada and 3.75 km for 12 hours in the southern Sierra Nevada. The anomalously high snow levels and over 80 mm of precipitation caused flooding, debris flows, and wet snow avalanches in the upper elevations of the Sierra Nevada. The origin of this atmospheric river was super typhoon Jelawat, whose moisture remnants were entrained and maintained by an extratropical cyclone in the northeast Pacific. This event was notable due to its April occurrence, as six other typhoon remnants that caused heavy precipitation with high snow levels (mean = 2.92 km) in the northern Sierra Nevada all occurred during October.


2021 ◽  
Author(s):  
Stuart R. Mead ◽  
Jonathan Procter ◽  
Gabor Kereszturi

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (actual) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This fuzzification of simulated results yields improvements in targeted performance metrics relative to a length scale parameter, at the expense of decreases in opposing metrics (e.g. less false negatives results in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated, and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision making from simulated data.


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