Natural Avalanches Research Articles

Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Abstract. Predicting the timing and size of natural snow avalanches is crucial for local and regional decision makers but remains one of the major challenges in avalanche forecasting. So far, forecasts are generally made by human experts interpreting a variety of data and drawing on their knowledge and experience. Using avalanche data from the Swiss Alps and one-dimensional physics-based snowpack simulations for virtual slopes, we developed a model predicting the probability of dry-snow avalanches occurring in the region surrounding automated weather stations based on the output of a recently developed instability model. This new avalanche day predictor was compared with benchmark models related to the amount of new snow. Evaluation on an independent data set demonstrated the importance of snow stratigraphy for natural avalanche release, as the avalanche day predictor outperformed the benchmark model based on the 3 d sum of new snow height (F1 scores: 0.71 and 0.65, respectively). The averaged predictions of both models resulted in the best performance (F1 score: 0.75). In a second step, we derived functions describing the probability for certain avalanche size classes. Using the 24 h new snow height as proxy of avalanche failure depth yielded the best estimator of typical (median) observed avalanche size, while the depth of the deepest weak layer, detected using the instability model, provided the better indicator regarding the largest observed avalanche size. Validation of the avalanche size estimator on an independent data set of avalanche observations confirmed these findings. Furthermore, comparing the predictions of the avalanche day predictors and avalanche size estimators with a 21-year data set of re-analysed regional avalanche danger levels showed increasing probabilities for natural avalanches and increasing avalanche size with increasing danger level. We conclude that these models may be valuable tools to support forecasting the occurrence of natural dry-snow avalanches.

Tree Blow‐Down by Snow Avalanche Air‐Blasts: Dynamic Magnification Effects and Turbulence

AbstractSnow avalanche‐induced air‐blasts are capable of breaking trees, damaging buildings and causing fatalities. Predicting their destructive properties is an essential part of snow avalanche hazard mitigation. Here, we propose a depth‐averaged model that involves turbulent fluctuations to simulate the air‐blast dynamics. The turbulent energy of the air‐blast arises from that of dust‐mixed air transferred from the avalanche core, shearing work in the cloud and entrained air, and is exploited to improve the air entrainment and drag relationships. We further present a unique data set of air blast‐induced tree breakage, providing type, status, diameter and falling direction of the measured trees. Through case studies of two artificially released avalanches with measured powder heights and three natural avalanches with tree‐breakage information, we test the model and investigate the turbulence effect on air‐blast dynamics. The proposed model and tree‐breakage data set quantify the air‐blast destructiveness and can be applied for avalanche hazard assessment.

Immiscible two-phase model for air blasts created during natural avalanches

An immiscible two-phase model based on the incompressible Navier-Stokes (N-S) equations is used to simulate the air blast generated by an avalanche. For simplicity, the avalanche is treated as an assembly of monodisperse spherical grains and described as a continuous media. The constitutive law of local µ(I) rheology is introduced to model the moving granular material. The motion of the avalanche and the induced air blast fits into a unified framework that combines the N-S−type governing equations with a µ(I)-rheology−based kinematic viscosity and a constant viscosity. The avalanche-air interface is treated using the volume-of-fluid method. A numerical program was developed on the open-source platform OpenFOAM specifically for this model to simulate the entire evolutionary process of the avalanche as well as the air blast generated. The model was validated by comparing the results of numerical simulations with those from inclined-plane laboratory experiments. With terrain input from the Shuttle Radar Topography Mission data, the model was further applied to simulate the air blast generated in two natural avalanches, namely, the Baige and Wenjia valley avalanches fo China, which occurred in 2008 and 2018, respectively. The simulation results were found to be consistent with field observations following a statistical analysis of the properties of the air blast including flow speed and area of impact of the above-mentioned natural events.

Including μ(I) rheology in three-dimensional Navier–stokes-governed dynamic model for natural avalanches

An avalanche dynamic model is proposed for the three-dimensional simulation of avalanche dynamics that adopts the Navier–Stokes equations as the governing framework and introduces μ(I) granular rheology in the constitutive law. Using the finite–volume method as the numerical scheme, a simulation program based on the OpenFOAM open-source platform was developed. The validity of the model as well as the program was verified by numerical simulations of a laboratory-scale granular flow test. An interface developed between the natural terrain data and the calculation program enables the simulation of natural avalanches. The Baige avalanche, a natural event, was reproduced. Comparisons between simulations and real data further verify the feasibility and accuracy of the full avalanche dynamic model. In addition, the evolution of the hydrostatic pressure, shear strain rate, inertial number, and kinematic viscosity over the duration of the avalanche were analyzed to extract the underlying internal mechanism.

Two-phase SPH modelling of a real debris avalanche and analysis of its impact on bottom drainage screens

Rapid flow-like landslides, particularly debris flows and debris avalanches, cause significant economic damage and many victims worldwide every year. They are usually extremely fast with the capability of travelling long distances in short times, sweeping away everything in their path. The principal objective of this paper is to test the ability of the ‘GeoFlow-SPH’ two-phase model developed by the authors, to reproduce the complex behaviour of natural debris avalanches where pore-water pressure evolution plays a key role. To reach this goal, the model is applied to reproduce the complex dynamic behaviour observed in Johnsons Landing debris avalanche including the observed bifurcation caused by the flowing out of part of the moving mass from the mid-channel. Initial thickness deposit trim-line, distribution of deposit volume, and the average velocities were provided for this real case, making it an appropriate case to validate the developed model. The paper also contributes to evaluate the SPH-FD model’s potentialities to simulate the structural countermeasure, like bottom drainage screens, used to reduce the impact of debris flows. The analysis of the results shows the adequacy of the proposed model to solve this complicated geophysical problem.

ОЦЕНКА ЭФФЕКТИВНОСТИ ПРОТИВОЛАВИННЫХ МЕРОПРИЯТИЙ НА ГОРНОЛЫЖНОМ КУРОРТЕ «КРАСНАЯ ПОЛЯНА»

For the first time, a qualitative and quantitative evaluation of the effectiveness of anti-avalanche measures was carried out for the territory of the «Krasnaya Polyana» ski resort, located in the Western Caucasus on the Aibga ridge. The following materials were used for this work: the results of field survey in 2019, which made it possible to map the resort's infrastructure exposed to possible snow avalanches and protected by existing preventive (anti-avalanche) measures, experience of similar studies from other regions as well as identification of the avalanche release zones by means of digital elevation model and analysis of remote sensing data, archive data on the snow avalanches regime at the site, and numerical modeling of the snow avalanches with different starting conditions. Modeling of the avalanches was performed in the RAMMS program basing on three scenarios: 1) taking account of the successful operation of existing anti-avalanche measures; 2) with regard for the failures in the work of existing anti-avalanche measures that were recorded earlier during the operation of the resort; 3) without considering any anti-avalanche measures, which corresponded to the conditions at the stage of the territorial planning of the resort. Differences in the impact of simulated avalanches on the resort infrastructure were interpreted as «high», «medium» and «low» effectiveness of existing antiavalanche measures. It was found that the dynamical characteristics of the local avalanches (run-out distance, volume, velocity, and pressure) had different importance for different types of the infrastructure with regard to the effectiveness of anti-avalanche measures. Under existing conditions of the relief, climate and vegetation of the investigated territory the artificial triggering (at the ski resort it is mainly made by the Gazex systems) is the most efficient. Snow-retaining structures often do not perform their functions, while dams and avalanche cutters can be successful only in combination with the properly functioning artificial triggering. It was found that there are areas where the run-out distance of artificially controlled avalanches is smaller than that of possible natural avalanches, and these areas can still be dangerous for the infrastructure of the resort due to the high values of the avalanche speed and pressure.

Granular roll waves along a long chute: From formation to collapse

Most simulation findings regarding granular roll waves are based on the analysis of steady uniform flows with an initial artificial perturbation. The difference in the scenario used in our study is that roll waves are generated by applying a zero-mean fluctuant flux inflow condition over the upstream boundary. Only the upstream section of the inclined chute is covered with a sheet of granules with no supplementary application of a boundary condition. Starting with the depth-averaged governing framework, the μ(Fr,h)-dynamic basal friction law, and the μ(I)-rheology-based second-order viscous terms, and adopting a second-order shock-capturing total variation diminishing–MacCormack scheme, we captured self-destabilized roll waves generated in an unsteady granular chute flow. In the simulated unsteady flow, three stages—wave spreading, wave forming and wave-collapse—are identified and discussed. The simulation results are confirmed by observations in laboratory granular flow experiment and natural avalanches from other literatures.

Simulation of natural shallow avalanches with the μ(I) rheology

A μ(I) rheology–based avalanche flow model whose governing equations are established in a rectangular Cartesian coordinate system is proposed in this paper. The motivation is updating the term related to gradients of the depth-averaged pressure and extending the application of μ(I) rheology to natural avalanche simulation. The main advantage of the proposed method is that it captures the constitutive properties of the avalanche by introducing the μ(I) rheology. The main novelty of the present model that distinguishes other μ(I) rheology–based approaches is that the in-plane shear is not considered in our model (consistent with the traditional Savage–Hutter theory); thus, the μ(I) rheology only plays a part in describing the normal transverse stresses. Experimental example shows that the proposed model can predict the moving process of granular flow satisfactorily. Simulation of a natural case (the Ermanshan avalanche in China) demonstrates that the simulation can approximately reproduce real avalanches tolerably well.

Modeling snow slab avalanches caused by weak-layer failure – Part 2: Coupled mixed-mode criterion for skier-triggered anticracks

Abstract. Using the analytical model presented in Part 1 of this two-part paper, a new conceptual understanding of anticrack nucleation in weak layers is proposed. To obtain a sufficient condition for onset of failure, two necessary conditions must be satisfied simultaneously: (i) the weak layer must be overloaded in terms of stress and (ii) the initiating crack must release enough energy for the formation of new surfaces. This so-called coupled criterion was proposed by Leguillon (2002). No assumptions on initial defects within the weak layer are needed. Instead, the failure criterion provides both critical loading and the size of initiating cracks. It only requires the fundamental material properties strength and fracture toughness as inputs. Crack initiation and subsequent propagation are covered by a single criterion containing both a strength-of-materials and a fracture mechanics condition. Analyses of skier-loaded snowpacks show the impact of slab thickness and slope angle on critical loading and crack initiation length. In the limit cases of very thick slabs and very steep slopes, we obtain natural avalanche release. A discussion of different mixed-mode stress and energy criteria reveals that a wrong choice of mixed-mode hypotheses can yield unphysical results. The effect of material parameters such as density and compliance on weak-layer collapse is illustrated. The framework presented in this two-part series harnesses the efficiency of closed-form solutions to provide fast and physically sound predictions of critical snowpack loads using a new conceptual understanding of mixed-mode weak-layer failure. It emphasized the importance of both stress and energy in avalanche release.

Психология устойчивого развития: проблемы и перспективы

Today the task of practical implementation of sustainable development has become even more important than three decades ago, when the corresponding concept was formulated. The coronavirus pandemic, which caused natural avalanche of negative consequences in the economy and society at the global, national, local, and individual levels, is just one of the tragic evidences of this. Initially, the term “sustainability” was put forward in natural sciences, but it is currently used in a wider context, which leads to misunderstanding. In this regard, the important role of the humanities, particularly psychology, is difficult to overestimate. The article is devoted to the review of problems and prospects in the field of psychology of sustainable development as a new and very relevant scientific area. The study presents the results of scientometric analysis of dissertational studies on this topic conducted in the USSR / Russian Federation from 1987 to 2019. It has been established that the vast majority of them was done in economic sciences (85.4%), and only a few in the field of psychology (0.5%). The content of the main, critical and alternative domestic and foreign discourse in the field of sustainable development has been disclosed. Methodological approaches, i.e. phenomenological, metacentric, ecopsychological have been described; they can serve as the basis for the psychology of sustainable development. In general, sustainable development is a dynamic process, the study of which includes many academic subjects and points of view and is constantly transformed as scientific knowledge, including psychological knowledge, develops.

Seismically induced snow avalanches at Nubra–Shyok region of Western Himalaya, India

Snow avalanche can be triggered by different mechanisms including metrological conditions, snow pack stability together with external factor such as seismic tremor and explosions. The snow avalanche triggered by seismic event is very important hazard phenomena in the snow covered region. In the present paper, investigation of earthquake-induced snow avalanches is introduced in Nubra–Shyok region of Western Himalaya, India. Compilation of seismogenic snow avalanche and earthquakes occurred in the Nubra–Shyok region during the period of 2010–2012 is made, which reveals that out of 393 natural avalanches, 81 avalanches was triggered due to the earthquake during this period. The local earthquakes occurred in Nubra–Shyok region, recorded by a local seismic network, are utilized for this work. The same date of occurrence of earthquakes and snow avalanches confirm seismogenic snow avalanche in this region. In the present work, avalanches triggered due to natural seismicity during the period of 2010–2012 related with earthquakes of magnitude 1.7 ≤ Mw ≤ 4.4 and distance of induced snow avalanche from epicenter of earthquakes, i.e., 4–92 km. In this study, lower bound limits of earthquake magnitudes, which cause avalanches, are established up to the distance of 92 km. Relation between earthquake magnitude and distance of induced snow avalanche from epicenter reveals that an earthquake of magnitude 1.4 (Mw) can trigger a snow avalanche as distance approaches to zero from earthquake epicenter. The comparison of obtained relation with other similar types of studies, i.e., Keefer (Geol Soc Am Bull 95:406–421, 1984), Podolskiy et al. (J Glaciol 56(197):431–446, 2010a) confirms the reliability of the present work.

Numerical investigation of the mixed-mode failure of snow

The failure of a weak snow layer underlying a cohesive slab is the primary step in the release process of a dry snow slab avalanche. The complex and heterogeneous microstructure of snow limits our understanding of failure initiation inside the weak layer, especially under mixed-mode shear–compression loading. Further complication arises from the dependence of snow strength on the loading rate induced by the balance between bond breaking and bond formation (sintering) during the failure process. Here, we use the discrete element method to investigate the influence of mixed-mode loading and fast sintering on the failure of a weak layer generated using cohesive ballistic deposition. Both fast and slow loading simulations resulted in a mixed-mode failure envelope in good agreement with laboratory experiments. We show that the number of broken bonds at failure and the weak layer strength significantly decreases with increasing loading angle, regardless of the loading rate. While the influence of loading rate appears negligible in shear-dominant loading (for loading angles above 30^{circ }), simulations suggest a significant increase in the weak layer strength at low loading angles and low loading rates, characteristic of natural avalanches, due to the presence of an active sintering mechanism.

Avalanche activity and characteristics of its triggering factors in the western Tianshan Mountains, China

Snow avalanche is a serious threat to the safety of roads in alpine mountains. In the western Tianshan Mountains, large scale avalanches occur every year and affect road safety. There is an urgent need to identify the characteristics of triggering factors for avalanche activity in this region to improve road safety and the management of natural hazards. Based on the observation of avalanche activity along the national road G218 in the western Tianshan Mountains, avalanche event data in combination with meteorological, snowpack and earthquake data were collected and analyzed. The snow climate of the mountain range was examined using a recently developed snow climate classification scheme, and triggering conditions of snow avalanche in different snow climate regions were compared. The results show that snowfall is the most common triggering factor for a natural avalanche and there is high probability of avalanche release with snowfall exceeding 20.4 mm during a snowfall period. Consecutive rise in temperature within three days and daily mean temperature reaching 0.5°C in the following day imply a high probability of temperaturerise-triggered avalanche release. Earthquakes have a significant impact on the formation of large size avalanches in the area. For the period 2011–2017, five cases were identified as a consequence of earthquake with magnitudes of 3.3≤ML≤5.1 and source-to-site distances of 19~139 km. The Tianshan Mountains are characterized by a continental snow climate with lower snow density, lower snow shear strength and high proportion depth hoar, which explains that both the snowfall and temperature for triggering avalanche release in the continental snow climate of the Tianshan Mountains are lower than that in maritime snow climate and transitional snow climate regions. The findings help forecast avalanche release for mitigating avalanche disaster and assessing the risk of avalanche disaster.

An ArcGIS Model for Avalanche Risk Assessment in the North Cascades, Washington

ABSTRACTReports of avalanche-related deaths have increased over the last fifty years in the United States. Although incidents occurring in Washington State and in the North Cascades do not reflect the bulk of avalanche-related casualties in the United States, it remains an annual concern for both recreational safety and transportation. This research seeks to apply and update methods from previous studies to evaluate avalanche risk in the North Cascades. Hazardous areas are identified by naturally occurring avalanche trigger zones. This study involves a mixed-method analysis using predefined geomorphic conditions, such as constant slope and sudden slope change, as well vegetation density, to identify natural avalanche trigger zones using ArcGIS. The outcome of the hazard assessment model is then evaluated using coordinates for reported avalanche debris sites and imagery interpretation. The postprocess evaluation also uses onsite ground photos of avalanche debris, captured by skiers, that help further assess how accurately the geographic information systems process is able to depict high-risk avalanche zones. A non-region-specific tool was produced in the form of an ArcGIS model that can be used to evaluate the avalanche hazard criteria in any regional area of interest.

A decision support tool for dry persistent deep slab avalanches for the transitional snow climate of western Canada

A decision support tool to aid in forecasting the likelihood of dry persistent deep slab avalanches was created from three separate data sources in western Canada. Data were obtained from an expert opinion survey of avalanche professionals, a dataset of avalanched starting zones that were field-investigated, and a dataset of avalanches from the Canadian information sharing system. The survey and the tool consisted of three sections: snowpack conditions, weather conditions, and avalanche observations. Parameters in the tool were assigned importance values derived from the survey responses. A classification tree was used to determine the threshold tool sum for increasing the likelihood of observing natural persistent deep slab avalanches. Based on some of the data used to create the tool, the tool correctly explained 75% of days with natural avalanches (16 out of 18) and non-avalanche days (61 out of 85), but the false alarm ratio was high (60%). The tool also indicates if triggered avalanches from localized dynamic loads are possible, depending on responses in the snowpack conditions section of the tool. Avalanche forecasters must apply the tool to certain terrain characteristics, at a local to regional scale. The tool may benefit from location-based calibration. The tool only indicates the likelihood of persistent deep slab avalanches based on the datasets used and it cannot determine when or where they will occur.

Automatic detection of wet-snow avalanche seismic signals

Avalanche activity is an important factor when estimating the regional avalanche danger. Moreover, a complete and detailed picture of avalanche activity is needed to understand the processes that lead to natural avalanche release. Currently, information on avalanche activity is mainly obtained through visual observations. However, this involves large uncertainties in the number and release times, influencing the subsequent analysis. Therefore, alternative methods for the remote detection of snow avalanches in particular in non-observed areas are highly desirable. In this study, we use the excited ground vibration to identify avalanches automatically. The specific seismic signature of avalanches facilitates the objective detection by a recently developed classification procedure. A probabilistic description of the signals, called hidden Markov models, allows the robust identification of corresponding signals in the continuous data stream. The procedure is based upon learning a general background model from continuous seismic data. Then, a single reference waveform is used to update an event-specific classifier. Thus, a minimum amount of training data is required by constructing such a classifier on the fly. In this study, we processed five days of continuous data recorded in the Swiss Alps during the avalanche winter 1999. With the restriction of testing large wet-snow avalanches only, the presented approach achieved very convincing results. We successfully detect avalanches over a large volume and distance range. Ninety-two percentage of all detections (43 out of 47) could be confirmed as avalanche events; only four false alarms are reported. We see a clear dependence of recognition capability on run-out distance and source–receiver distance of the observed events: Avalanches are detectable up to a source-receiver distance of eight times the avalanche length. Implications for analyzing a more comprehensive data set (smaller events and different flow regimes) are discussed in detail.

Learning from the Nepal's Earthquake for Preparedness through Transboundary Collaboration among Experts of Himalayan Countries

As a water source for over a billion people and a region of exceptional cultural richness and biodiversity, the Himalayan terrain is a global asset. The young and rising Himalayan Mountains are highly vulnerable to natural disasters, including earthquakes, landslides, avalanches and floods. The risk is compounded by low capacities of most Himalayan countries to deal with disasters, remoteness and difficult terrain, and in several cases, political instability. These factors also make scientific research in the region difficult.

Variability of the snow avalanche danger in the Tatra Mountains during the past nine decades

In order to recognise the variability of the snow avalanche danger in the Tatra Mountains, the danger levels on consecutive days with snow cover over the last nine decades were calculated. To accomplish this task, the longest series of meteorological data were used from the Tatras along with an empirical method for determining the regional avalanche danger on the basis of elementary meteorological data. The results point to the fact that over the last 25 years the number of days with a level 2 avalanche danger significantly decreased, whereas the number of days with level 1 increased. This should result in a decreasing trend in the incidence of small and medium-sized natural avalanches. In the structure of snow cover, the percentage of melt forms might increase. However, this should not correlate with a significant increase in wet-snow avalanches, because the number of days with wet snow also reduces. The contemporary changes in the snow conditions and avalanche danger in the subalpine belt of the Tatras have been primarily associated with an increase in the air temperature (shorter winters and less snow).

Snow avalanches in western Canada: investigating change in occurrence rates and implications for risk assessment and mitigation

Snow avalanche frequency and magnitude, required for risk analysis, are best determined using historical occurrence records. In Canada, reliable records are sparse and relatively short term, extending back 30–50 years. Some Canadian avalanche forecasters suspect that climate change has increased avalanche activity in recent years. Should an increasing trend exist, analyses based on historical occurrence rates would underestimate future risk to people and infrastructure in mountain regions. We analyse 30 years of occurrence records to investigate whether a trend exists, and assess its strength. A Bayesian hierarchical model is used to estimate occurrence rate trends across six geographical zones in western Canada. The results suggest that natural avalanche occurrence rates have decreased or stayed constant; however, there is a very high level of uncertainty. This uncertainty will need to be factored into decision-making processes. To assist in this, we discuss the effect of long-term changes in avalanche occurrence rates in terms of consequences and vulnerability. We also recommend strategies for improving mitigation practices so that avalanche control operations can better adapt to changing and less predictable environments.

Quantifying snowfall and avalanche release synchronization: A case study

AbstractWe quantify the synchronization between snowfall and natural avalanches in relation to terrain properties at the detachment zone. We analyze field statistics of 549 avalanche events in terms of slope, aspect, timing, coordinate, and release area, identified by a georeferencing procedure applied on terrestrial photography. The information from the digital pictures, together with associated meteorological data, provides us with the input needed for model calibration, namely, the magnitude of snowfall, the snow compaction rate, and the timing of precipitation and of avalanche events. Synchronization between snowfall and avalanches is established for different slope categories. We obtain an average probability of release after a snow event of 30% and 16% for the high‐ and low‐slope categories (average slope 44° and 36°, respectively). Using the notion of information entropy, we quantify the uncertainty in predicting avalanche occurrence from a snow event. The steeper slopes correspond to a larger entropy in avalanche prediction. Further, the presented method allows us to establish the return period of avalanches without requiring a long series of data. When considering events regardless of their release depth, the avalanches had a return period of 48 days (higher slopes) and 88 days (lower slopes). Finally, we determine the average daily detachment rate as a function of snow depth and the return period of avalanches as a function of the release depth.