Avalanche Risk Research Articles

The role of local knowledge in snow observation and applied snow avalanche forecasting in Longyearbyen, Svalbard

In this article, we present the results of our study of knowledge in the actor-network of snow avalanche forecasters and observers in Longyearbyen, Svalbard. Our study aimed to understand how observers and forecasters make sense of snow conditions and snow avalanche risks. To do so, we conducted empirical investigations, which included interviews with key observation, forecasting, and decision-making actors in Longyearbyen’s risk governance system and autoethnographic participatory observation by the first author during the 36 months they worked closely with several informants in Longyearbyen. We draw on perspectives from literature on sensemaking, sensework, and tacit knowledge to conceptualize the modus operandi of observers and forecasters in a manner that allows for generalization to contexts beyond snow avalanche forecasting in Longyearbyen. We find that avalanche-related knowledge construction is highly dependent on the experiences of the observers from their non-professional interaction with the local topography and snow as part of their leisurely activities. Further, social relations and communication among observers and forecasters are essential in knowledge construction. Based on the different processes and resources entering the knowledge construction, we describe three dimensions of local knowledge involved in snow avalanche forecasting: situated, social knowledge; embodied knowledge; and synthetic knowledge. We elaborate on these dimensions of knowledge and discuss implications for the development and administration of avalanche warning systems in contexts characterized by a high degree of transience and change in phenomena.

AutoATES v2.0: Automated Avalanche Terrain Exposure Scale mapping

Abstract. Avalanche risk assessment is complex and challenging, with terrain assessment as one of the most fundamental factors. To aid people's terrain assessment, Parks Canada developed the Avalanche Terrain Exposure Scale (ATES), a system that classifies the severity of avalanche terrain into five classes from non-avalanche terrain to extreme terrain. Manual classification is laborious and dependent on expert's assessments. To ease the process Larsen et al. (2020) developed an automated ATES model (AutoATES v1.0). Although the model allowed large-scale mapping, it had some significant limitations. This paper presents an improved AutoATES v2.0 model improving the potential release area (PRA) model, utilizing the new Flow-Py runout simulation package. Furthermore, it incorporates forest density data in the PRA, in Flow-Py, and in a newly developed post-forest-classification step. AutoATES v2.0 has also been rewritten in open-source software, making it more widely available. The paper includes a validation of the model measured against two consensus maps made by three experts at two different locations in western Canada. For Bow Summit, the F1 score (a measure of how well the model performs) improved from 64 % to 77 %. For Connaught Creek, the F1 score improved from 40 % to 71 %. The main challenge limiting large-scale ATES classification is the determination of optimal input parameters for different regions and climates. In areas where AutoATES v2.0 is applied, it can be a valuable tool for avalanche risk assessment and decision-making. Ultimately, our goal is for AutoATES v2.0 to enable efficient, regional-scale, and potentially global ATES mapping in a standardized manner rather than based solely on expert judgment.

Dating of avalanches in Pirin mountains in Bulgaria by tree-ring analysis of Pinus peuce and Pinus heldriechii trees

Snow avalanches are among the most important disturbances in mountain ecosystems. The effects of avalanches on the endemic Pinus heldreichii and Pinus peuce forests in the Pirin Mountains in Bulgaria are poorly understood. These forests are among the few remaining old-growth forests with preserved natural dynamics in Europe. However, the ongoing development of tourist infrastructure at the borders of some of the best-preserved Pinus heldreichii and Pinus peuce forests close to Bansko ski resort leads to increased tourist pressure. Many backcountry skiers and snowboarders venture beyond the resort boundaries, practicing their activities in these forests and avalanche tracks and couloirs within them. The objective of our study was to collect tree-ring cores from Pinus peuce and Pinus heldreichii trees affected by avalanches and verify the specific types of damages and tree responses characteristic for the species and region. Then using the collected data, we aimed at reconstructing the years in which specific areas were affected by avalanches and in this way obtain data on the magnitude of larger events. Our study shows that large magnitude avalanches (LMA) in the vicinity of Bansko ski resort in the Pirin Mountains in Bulgaria occurred dozens of times in the 20th century. On average the period between LMAs ranged between 9 and 20 years with the shortest period between two such events in one couloir being 2 years. Avalanches affected forests high on the couloir banks and left traces in the tree rings related to the mechanical impact that snow avalanches had on the surviving trees. In the studied tree-ring cores of Pinus peuce and Pinus heldreichii the most informative types of responses were sharp growth suppressions, including missing rings, followed by reaction wood and in less cases visible scars and callus tissue. Our data for frequent large avalanches shows that is necessary to address the avalanche risk with high priority especially for the Palashica couloir, which directly threatens the lower parts of the ski runs as well as other facilities in Bansko ski resort.

GIS-based determination of potential snow avalanche areas: A case study of Rize Province of Türkiye

Natural hazards are a part of critical issues affecting people and the environment. One of these natural hazards is snow avalanches. With the increase in the world population, it has emerged that decision-makers should take precautions against such natural hazards for population movements, construction, transportation, and tourism. Essential solution parts of this problem lay behind surveying, GIS, and spatial analysis-planning. This situation will be primarily due to the snow conditions, but certain terrain areas are susceptible. Snow avalanches' release mechanism depends on many factors, such as terrain, meteorological reports, snowpack, and other triggering parameters. Areas with certain topographical features that allow the deposition of snow masses are called avalanche-release areas. GIS helps to make decisions concerning spatial planning within avalanche release areas and finding risky zones. This study aimed to determine the potential avalanche release areas in the GIS environment in Rize, Türkiye, which was chosen as the pilot region. In the study, the detection of these avalanche areas was estimated using a mathematical equation model proposed by Hreško (1998) and determined with the help of GIS. Factors such as elevation, curvature, aspect, slope, and land cover type were used to estimate avalanche risk areas. A Model Builder workflow has also been created to automate the process stages. As a result of the study, avalanche risk areas were determined and mapped for the Rize mountainous region.

Frequency and size change of ice–snow avalanches in the central Himalaya: A case from the Annapurna II glacier

Glaciers have retreated and shrunk in High Mountain Asia since the mid-20th century because of global warming, leading to glacier instability and hazardous ice–snow avalanches. However, the complex relationship between ice–snow avalanches and factors such as climate and potential triggers are difficult to understand because of the lack of observational data. Here, we addressed ice–snow avalanches on the Annapurna II glacier in Nepal, Central Himalaya. We constructed an ice–snow avalanche history using long-term multi-source remote sensing images (1988–2021) and mapped the velocity fields of glaciers using cross-correlation analysis on SAR and optical images. Then, we investigated the impact of climate change and earthquakes on the frequency and size of ice–snow avalanches. The results demonstrate that the frequency of ice–snow avalanches has increased from 10 in 1988 to 27 in 2020, but the average area of ice–snow avalanche deposits has decreased by approximately 70%, from 3.4 × 105 m2 in 1988 to 1.2 × 105 m2 in 2020. The evolutionary characteristic of ice avalanches is linked to the impact of glacier retreat (reduction in ice material supply) and increased activity under climate change. The glacier movement velocity controls the size of ice–snow avalanches and can be set as an indicator for ice–snow avalanche warnings. On the Annapurna II glacier, an ice–snow avalanche occurred when the glacier velocities were greater than 1.5 m d−1. These results offer insights into ice–snow avalanche risk assessment and prediction in high-mountain areas, particularly in regions characterised by dense glacier distribution.

Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada

Abstract. The Avalanche Terrain Exposure Scale (ATES) is a system for classifying mountainous terrain based on the degree of exposure to avalanche hazard. The intent of ATES is to improve backcountry recreationist's ability to make informed risk management decisions by simplifying their terrain analysis. Access to ATES has been largely limited to manually generated maps in high-use areas due to the cost and time to generate ATES maps. Automated ATES (AutoATES) is a chain of geospatial models which provides a path towards developing ATES maps on large spatial scales for relatively minimal cost compared to manual maps. This research validates and localizes AutoATES using two ATES benchmark maps which are based on independent ATES maps from three field experts. We compare the performance of AutoATES in two study areas with unique snow climate and terrain characteristics: Connaught Creek in Glacier National Park, British Columbia, Canada, and Bow Summit in Banff National Park, Alberta, Canada. Our results show that AutoATES aligns with the ATES benchmark maps in 74.5 % of the Connaught Creek study area and 84.4 % of the Bow Summit study area. This is comparable to independently developed manual ATES maps which on average align with the ATES benchmark maps in 76.1 % of Connaught Creek and 84.8 % of Bow Summit. We also compare a variety of DEM types (lidar, stereo photogrammetry, Canadian National Topographic Database) and resolutions (5–26 m) in Connaught Creek to investigate how input data type affects AutoATES performance. Overall, we find that DEM resolution and type are not strong indicators of accuracy for AutoATES, with a map accuracy of 74.5 % ± 1 % for all DEMs. This research demonstrates the efficacy of AutoATES compared to expert manual ATES mapping methods and provides a platform for large-scale development of ATES maps to assist backcountry recreationists in making more informed avalanche risk management decisions.

SLABS: An improved probabilistic method to assess the avalanche risk on backcountry ski tours

The main danger to which backcountry skiers are exposed are dry slab avalanches triggered by skiers themselves. In this paper we present a new probabilistic method to assess the avalanche risk when planning a ski tour: SLABS (Screening the Likelihood of Avalanches on Backcountry Ski tours). The SLABS method is the first fully statistically derived probabilistic method for backcountry skiing. We used a data set with GPS (Global Positioning System) tracks of backcountry ski tours (57.8 thousand km) and a data set of 1250 accidents recorded in Switzerland during the last 20 winter seasons. A GAM (Generalised Additive Model) with binomial link discriminating between accidents and non-accidents was fitted to these data. As predictors the model uses a non-linear relation with the slope angle, and a linear relation with the danger level, the elevation and the aspect. Conditions with elevated and high risk were defined such that the accident prevention rate is 80% and 60%, respectively. A comparison of the SLABS method with the Graphical Reduction Method (GRM), the Professional Reduction Method (PRM) and the Quantitative Reduction Method (QRM) shows that it offers more freedom of movement for a given accident prevention rate. It is the first time that probabilistic methods are compared in terms of their trade-off between accident prevention and freedom of movement. Because the SLABS method is not suited for mental arithmetic it is implemented in the website www.skitourenguru.ch. This website evaluates on a daily basis the avalanche risk along thousands of backcountry tours throughout the Alps to help skiers plan their next tour. For a single slope the risk assessment of SLABS provides a starting point that has to be supplemented with local observations.

Landslide disaster risk analysis at Karanganyar district, Central Java province

The condition of Karanganyar Regency is formed by fragile and volcanic rocks weathered soil thickness and supported by high rainfall is a condition that has the potential to cause landslides. increasing population and intensive land use led to high risk of landslides. Landslides have occurred many times in the district Karanganyar. A combination of anthropogenic and natural factors often becomes cause of landslides that killed local residents and property loss. Large landslides have occurred in Karanganyar on December 26, 2007 which claimed 62 people died world. Landslide risk analysis research was carried out by entering several main components, namely hazard, susceptibility, and capacity. A qualitative approach was applied to carry out the analysis in the districts Karanganyar. The output of this study is a landslide risk map. Avalanche risk analysis was carried out at 3 selected locations experience landslides and the potential for such disasters in the Regency Karanganyar. The results of research on this topic are expected to be able to socialized so that local governments are able to develop plans sustainable development.

ASSESSING THE MEASUREMENT QUALITY OF UAV-BORNE LASER SCANNING IN STEEP AND SNOW-COVERED AREAS

Abstract. Avalanche monitoring in the Norwegian mountains has potential for preventing disasters and informing hikers. Using a Unmanned Aerial Vehicle (UAV)-borne laser scanner, this work proposes a protocol to assess the quality of point cloud data for monitoring avalanche risks. Roof models are used as control planes to analyze the collected points. The distances to the control planes are used to investigate error measures, and inliers and plane equations are compared with the roof model dimensions. These parameters provide insights into the reliability of the point cloud data. The comparison shows the impact of flight speed and altitude on accuracy. While varying flight speed does not affect error measures, both speed and altitude significantly affect the number of collected points. Point coverage is concentrated near the top of the roof models, resulting in a calculated model volume that is only 50% of the expected value. Comparing the Random Sample Consensus (RANSAC)-derived plane equations with the roof model planes reveals that more points are collected above the roof model planes. The standard deviations of the inliers range from 0.011 m to 0.023 m, and the root mean square error (RMSE) ranges from 0.060 m to 0.019 m. These findings indicate the reliability of UAVs for monitoring steep and snow-covered areas without the need for reference points to correct positions.

The composition of avalanche hazard maps with the help of ArcGIS on the base of geomorphological analysis for the mountainous areas of Chernivtsi region

An analysis of the geomorphological factors of avalanche formation in the mountains of Chernivtsi region has been. With the use of ArcGis, a geomorphological analysis has been carried out and classes of avalanche danger were identified. An avalanche danger map for the mountainous territory of the Chernivtsi region has been constructed. Territories with increased avalanche risk have been identified, thanks to GIS technologies, the areas of territories with certain classes of avalanche danger have been calculated. A description of the territories with the highest classes of avalanche danger has been carried out. Keywords: avalanche hazard, relief, underlying surface, spatial analysis, GIS technology.

Snow Avalanche Hazard Mapping Using a GIS-Based AHP Approach: A Case of Glaciers in Northern Pakistan from 2012 to 2022

Snow avalanches are a type of serious natural disaster that commonly occur in snow-covered mountains with steep terrain characteristics. Susceptibility analysis of avalanches is a pressing issue today and helps decision makers to implement appropriate avalanche risk reduction strategies. Avalanche susceptibility maps provide a preliminary method for evaluating places that are likely to be vulnerable to avalanches to stop or reduce the risks of such disasters. The current study aims to identify areas that are vulnerable to avalanches (ranging from extremely high and low danger) by considering geo-morphological and geological variables and employing an Analytical Hierarchy Approach (AHP) in the GIS platform to identify potential snow avalanche zones in the Karakoram region in Northern Pakistan. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was used to extract the elevation, slope, aspect, terrain roughness, and curvature of the study area. This study includes the risk identification variable of land cover (LC), which was obtained from the Landsat 8 Operational Land Imager (OLI) satellite. The obtained result showed that the approach established in this study provided a quick and reliable tool to map avalanches in the study area, and it might also work with other glacier sites in other parts of the world for snow avalanche susceptibility and risk assessments.

Snow avalanches in relation to tourism and transportation activities in the Făgăraş Mountains, Romanian Carpathians

In mountainous regions, avalanches can seriously damage tourist infrastructure, roads, and forests and lead to loss of human life. The analyses were performed in the Făgăraş Mountains, Southern Carpathians-Romania. This study addresses the following questions: How does risk differ over time depending on the snow avalanche activity? (ii) How reliable are complementary, statistical, and dendrogeomorphological approaches for analysing the avalanche activity? Our analysis was based on extensive documentation, using old photographs, maps, papers and database statistics. We also utilized dendrogeomorphological data, satellite images and event simulations using the RAMMS avalanche module. The study data was collected between 1880 and 2020, in three different periods, each with socioeconomic peculiarities: the Romanian Kingdom Period, communist period, and post-communist period. In the first period, the tourist infrastructure was modest and the avalanche hazard was not recognized. Only three avalanche accidents were recorded. In the communist period, 25 avalanche accidents were recorded. In the postcommunist period, 75 avalanche accidents were recorded. Avalanche activity strongly interfered with the emergence of new elements of tourist infrastructure, such as huts, alpine refuges, and the Transfăgărăşan highway. Our results show that despite protection measures, avalanche risk awareness information, use of the European risk scale, and the issuing of danger bulletins, especially in the last 20 years, the risk has remained high due to increased exposure and vulnerability of tourist infrastructure and tourists.

Avalanche Education Is Associated with Increased Avalanche Safety Practices in the New Hampshire Backcountry

Avalanche risk can be mitigated by adhering to certain safety practices. Previous studies of these practices have focused on western United States and European cohorts. We conducted a survey of backcountry users in the White Mountains of New Hampshire to determine local adherence to 5 previously studied avalanche safety practices. We assessed whether participants were carrying transceiver, probe, and shovel (TPS); had formal avalanche education; had awareness of the day's avalanche danger level; had a route plan; and were traveling in a group. Backcountry users in the White Mountains were directed to an online survey from December 2020 to June 2021. The survey was completed individually and queried demographics and avalanche safety practices. A total of 133 users participated. Not all surveyed participants answered all questions. Avalanche training was reported by 87% of users, 86% checked the avalanche forecast prior to recreating, 93% had a travel plan, 87% traveled in a group, and 59% carried TPS. All 3 items were carried by all group members only 48% of the time. Only 28% of users metall 5 safety practices. White Mountains backcountry users are less likely to meet avalanche safety practices than users in previous studies. There is an association between meeting these defined safety practices and formal avalanche education.

Characteristics of Rain-Snow Transitions Over the Canadian Rockies and their Changes in Warmer Climate Conditions

ABSTRACT The southern Canadian Rockies are prone to extreme precipitation that often leads to high streamflow, deep snowpacks, and avalanche risks. Many of these precipitation events are associated with rain–snow transitions, which are highly variable in time and space due to the complex topography. A warming climate will certainly affect these extremes and the associated rain–snow transitions. The goal of this study is to investigate the characteristics and variability of rain–snow transitions aloft and how they will change in the future. Weather Research and Forecasting (WRF) simulations were conducted from 2000 to 2013 and these were repeated in a warmer pseudo-global warming (PGW) future. Rain–snow transitions occurred aloft throughout the year over the southern Canadian Rockies, but their elevations and depths were highly variable, especially across the continental divide. In PGW conditions, with future air temperatures up to 4–5°C higher on average over the Canadian Rockies, rain–snow transitions are projected to occur more often throughout the year, except during summer. The near-0°C conditions associated with rain–snow transitions are expected to increase in elevation by more than 500 m, resulting in more rain reaching the surface. Overall, this study illustrates the variability of rain–snow transitions, which often impact the location of the snowline. This study also demonstrates the non-uniform changes under PGW conditions, due in part to differences in the types of weather patterns that generate rain–snow transitions across the region.

Large-scale risk assessment on snow avalanche hazard in alpine regions

Abstract. Snow avalanches are recurring natural hazards that affect the population and infrastructure in mountainous regions, such as in the recent avalanche winters of 2018 and 2019, when considerable damage was caused by avalanches throughout the Alps. Hazard decision makers need detailed information on the spatial distribution of avalanche hazards and risks to prioritize and apply appropriate adaptation strategies and mitigation measures and thus minimize impacts. Here, we present a novel risk assessment approach for assessing the spatial distribution of avalanche risk by combining large-scale hazard mapping with a state-of-the-art risk assessment tool, where risk is understood as the product of hazard, exposure and vulnerability. Hazard disposition is modeled using the large-scale hazard indication mapping method RAMMS::LSHIM (Rapid Mass Movement Simulation::Large-Scale Hazard Indication Mapping), and risks are assessed using the probabilistic Python-based risk assessment platform CLIMADA, developed at ETH Zürich. Avalanche hazard mapping for scenarios with a 30-, 100- and 300-year return period is based on a high-resolution terrain model, 3 d snow depth increase, automatically determined potential release areas and protection forest data. Avalanche hazard for 40 000 individual snow avalanches is expressed as avalanche intensity, measured as pressure. Exposure is represented by a detailed building layer indicating the spatial distribution of monetary assets. The vulnerability of buildings is defined by damage functions based on the software EconoMe, which is in operational use in Switzerland. The outputs of the hazard, exposure and vulnerability analyses are combined to quantify the risk in spatially explicit risk maps. The risk considers the probability and intensity of snow avalanche occurrence, as well as the concentration of vulnerable, exposed buildings. Uncertainty and sensitivity analyses were performed to capture inherent variability in the input parameters. This new risk assessment approach allows us to quantify avalanche risk over large areas and results in maps displaying the spatial distribution of risk at specific locations. Large-scale risk maps can assist decision makers in identifying areas where avalanche hazard mitigation and/or adaption is needed.

Avalanche risk in the Khibiny mountains at the beginning of the 21st century

Avalanche risk in the Khibiny mountains at the beginning of the 21st century

A user perspective on the avalanche danger scale – insights from North America

Abstract. Danger ratings are used across many fields to convey the severity of a hazard. In snow avalanche risk management, danger ratings play a prominent role in public bulletins by concisely describing existing and expected conditions. While there is considerable research examining the accuracy and consistency of the production of avalanche danger ratings, far less research has focused on how backcountry recreationists interpret and apply the scale. We used 3195 responses to an online survey to provide insight into how recreationists perceive the North American Public Avalanche Danger Scale and how they use ratings to make trip planning decisions. Using a latent class mixed-effect model, our analysis shows that 65 % of our study participants perceive the avalanche danger scale to be linear, which is different from the scientific understanding of the scale, which indicates an exponential-like increase in severity between levels. Regardless of perception, most respondents report avoiding the backcountry at the two highest ratings. Using conditional inference trees, we show that participants who recreate fewer days per year and those who have lower levels of avalanche safety training tend to rely more heavily on the danger rating to make trip planning decisions. These results provide avalanche warning services with a better understanding of how recreationists interact with danger ratings and highlight how critical the ratings are for individuals who recreate less often and who have lower levels of training. We discuss opportunities for avalanche warning services to optimize the danger scale to meet the needs of these users who depend on the ratings the most.

Snow Avalanche Risk Assessment using GIS-Based AHP for Bitlis Province

Bitlis province, located in the Eastern Anatolia of Turkey, is the region with the highest snowfall in the country. Due to its highland and steep structure, the region is under high avalanche risk. Assessment of the snow avalanche risks is important in terms of modern disaster management. In this study, the avalanche risks were assessed by using the analytical hierarchy process (AHP), which is an effective multiple criteria decision-making methods. The avalanche risk was considered depend on many factors such as temperature, slope, elevation, aspect, land use, soil, lithology, precipitation, distance to fault and population. The outputs obtained from the method were mapped in the GIS environment and thus the avalanche risks of the region were determined. According to the results, especially the highland and steep southern parts and the two volcanic mountain foothills in the region were evaluated as high risk. The study results were validated by comparing past avalanche events and some previous researches.

Impacts of Climate Change on Snow Avalanche Activity Along a Transportation Corridor in the Tianshan Mountains

Snow avalanches can repeatedly occur along the same track under different snowpack and meteorological conditions during the snow season in areas of snow avalanche activity. The snowfall, air temperature, and snow cover can change dramatically in a warming climate, causing significant changes in the snow avalanche risk. But how the risk of snow avalanche activity during the snow season will change under a warming climate remains an open question. Based on the observed meteorological and snowpack data from 1968 to 2021 and the snow avalanche activity data during the 2011–2021 snow seasons along a transportation corridor in the central Tianshan Mountains that has a typical continental snow climate, we analyzed the temporal distribution of the snow avalanche activity and the impacts of climate change on it. The results indicate that the frequency of the snow avalanche activity is characterized by a Gaussian bimodal distribution, resulting from interactions between the snowfall, air temperature, and snowpack evolution. In addition, the active period of wet snow avalanches triggered by temperature surges and high solar radiation has gradually moved forward from the second half to the first half of March with climate warming. The frequency and size of snowfall-triggered snow avalanches showed only a slight and insignificant increase. These findings are important for rationally arranging snow avalanche relief resources to improve the risk management of snow avalanche disasters, and highlight the necessity to immediately design risk mitigation strategies and disaster risk policies to improve our adaptation to climate change.

The sensitivity and evolutionary trajectory of the mountain cryosphere: Implications for mountain geomorphic systems and hazards

AbstractGlobal climate change gives rise to changing spatial patterns of snow and ice, especially over mountain blocks where orographic and synoptic circulation effects play significant roles in creating patterns of precipitation and glacier development. The presence of snow and ice results in heat balance changes and other land surface feedbacks that have implications for patterns of mountain glacier retreat and the dynamics of mountain geomorphic systems. This study considers the sensitivity of the mountain cryosphere (snow, ice, permafrost) to global climate change, and the implications of this sensitivity analysis for evaluating mountain surface stability, geomorphic change, and the generation of mountain geohazards. Consideration of these issues is informed by evidence from case studies reported in the literature and by field observations of mountain system dynamics worldwide. Results show that ‘sensitivity’ to climate forcing has been interpreted and defined in different ways in mountain snow, ice, and permafrost systems, with respect to properties such as albedo, mass balance or rapidity of system change. There are also significant spatial differences in sensitivity between different mountain blocks for snow, ice and permafrost, and these regions are therefore likely to follow different trajectories of geomorphic change in response to climate forcing, related to their physiographic properties and the extent of cryospheric coverage. Within glaciated mountains in particular, the relative timing of different geomorphic events, and the interplay between slope, glacier front, and proglacial sediment sources and environments, may vary depending on glacier size, geomorphic setting, and microclimate. By contrast, responses to permafrost warming (increased surface instability and mass movements) and changes in snow patterns (avalanche risk, floods) may have quite different spatial and temporal patterns and influenced by different environmental controls. An integrated evolutionary model for mountain system development under a changing cryosphere is proposed, highlighting the critical role of energy balance as a forcing factor that then triggers downstream mountain system responses. This suggests that different elements of mountain systems exhibit different sensitivities, and furthermore that these sensitivities change over time and space through the period of anthropogenic global warming and paraglacial relaxation.