Geology topics

Erich Peitzsch

Publications and source records attributed to Erich Peitzsch.

9 recordsLinked to original sources

USGS2026

Stability changes after weak layer collapse: Insights from an unexpected dataset

While conducting avalanche mitigation or traveling through the backcountry, avalanche professionals sometimes experience a "whumpf": a collapse-mode crack accompanied by surface cracking that does not produce an avalanche. These whumpfs are a clear warning sign of instability in the surrounding terrain. But assessing the collapsed slope itself, if it is steep enough to avalanche, carries much more uncertainty. Can slopes that whumpf and are steep enough to slide still avalanche? The answer to this question supports avalanche mitigators and ski guides in assessing whether to open such slopes. Previous research on collapsed slopes is limited to one study conducted before tests that estimate crack propagation propensity, such as the Propagation Saw Test (PST), were developed. This work showed that weak layer shear strength decreased immediately after collapsing and then increased over time. However, no research has examined crack propagation propensity after a whumpf. Studying propagation propensity is key for assessing how whumpfs immediately affect slope stability. To improve our understanding of changes in propagation propensity following weak layer collapse, we conducted PSTs on a test slope in the hours and days after an unexpected collapse occurred on a layer of surface hoar. Two PSTs at our study site three days prior to this collapse provided an estimate of weak layer propagation propensity. PST cut lengths decreased immediately following the collapse, suggesting that the collapse increased the propagation propensity. However, over the next 4-5 hours, PST cut lengths steadily increased at our site, likely due to ongoing sintering and strengthening in the collapsed weak layer. By the end of day two, we were no longer able to initiate propagation, suggesting substantial stabilization of the weak layer. Our results support prior findings and observations suggesting that slopes may remain capable of producing avalanches immediately after a collapse but likely stabilize over the next day or two. Although this research does not provide answers about precisely when a slope becomes stable after a collapse, it does highlight uncertainties in our understanding and interpretation of the stability of slopes that have whumped.

Montana↗

USGS2026

Revisiting avalanche destructive scale and associated mass estimates

Avalanche destructive (D) size classifications are essential for forecasting, communication, and risk management, yet size estimation remains one of the more subjective elements of avalanche assessment. Practitioners typically rely on visual impressions of destructive potential, path length, and estimated mass and volume. Recent work indicates that size is often underestimated even by experienced observers, especially when based on photographs or distant observations. Although mass is central to defining destructive size, the empirical foundations of mass–size relationships have rarely been revisited, and expert variability in size assignment could be decreased if more consistent operational tools were available. We evaluated whether a simple, practitioner-focused calculation tool using slab dimensions, snow density, and snow water equivalent can provide reliable mass estimates that correspond meaningfully with existing destructive size classes. Using this tool, we estimated avalanche mass and compared the results to observer-assigned D sizes. We also simulated mass outputs using a dense flow avalanche simulation module and compared observer estimates and simple-tool outputs to recent volume-based methods for D-size classification. Across 143 well-documented dry snow avalanches from multiple avalanche climates, the size estimation tool tends to classify avalanches larger than field-based observers. We found a mean bias of 0.47 D-size units and a typical (mean absolute) disagreement of 0.56. Our results show that 95% of events landed within one whole D-class of each other and 71% within a half-class. Agreement between the simple tool mass estimates and dense flow avalanche simulations was generally strong, though discrepancies emerged in cases with substantial entrainment or complex terrain. We compared the size tool to the simulation module with entrainment (n=4) and without entrainment (n=8). With entrainment, the two methods estimate the same D-size class in 4 of 4 comparable events and 7 of 8 events without entrainment. Also, the simulation module estimates larger sizes than the observer in 7 of 8 cases without entrainment and all 4 cases with entrainment. These findings support that development of practical, mass-based tools could improve D-size consistency and emphasize the value of revisiting historical mass–size relationships. The accompanying application offers practitioners an accessible and operationally useful resource for improving D-size estimation from field observations.

Conference Paper↗

USGS2026

Start-zone characteristics and timing of wet slab avalanches In Colorado

Wet slab avalanches (WSAs) release when liquid water reduces the strength of a buried weak layer or interface, and their timing is governed primarily by the snowpack energy balance and the movement of meltwater. We classified 717 WSAs from the Colorado Avalanche Information Center database (2011–2025) into five start-zone terrain categories and analysed the timing of naturally triggered, near- and above-treeline events using rank-based and Bayesian hierarchical methods. Start-zone terrain strongly governs the natural occurrence of WSAs: approximately 64% released in Rocky start zones (Cliffs/Rocks), while only ≈4% occurred on Open Slopes. After controlling for latitude and aspect, Rocky start zones released approximately five days before Open Slopes (90% CrI: 0.6–9.9 days). Latitude was the dominant timing predictor, shifting release by roughly 3–4 weeks from southern to northern Colorado. Cornice start zones concentrated WSA activity in early to mid-spring, with 40 of 41 releasing before mid-May. These findings support start-zone terrain classification as a low-cost addition to observation protocols for improving the spatial targeting of wet slab outlooks.

Colorado↗

USGS2026

Patterns of glide avalanche release: Insights from 23 years of observations along the Going-to-the-Sun Road, Montana, USA

Glide avalanches pose a notable hazard during annual spring snow removal operations along the Going-to-the-Sun Road (GTSR) in Glacier National Park (GNP), USA. Glide cracks consistently form on specific slopes near and above the GTSR. Some glide crack locations produce glide avalanches most years (known as repeater paths), whereas others are less predictable and either release or melt in place. Previous studies of glide avalanches have focused on different meteorological, snow-pack, and terrain parameters that influence glide release. The timing of glide avalanche release remains difficult to predict, which can be a challenge. To the authors' knowledge, no previous work has approached the issue of timing by comparing the chronological release order of glide paths within an operation. To address this, we examine the release order of repeater paths along the GTSR and investigate different topographical factors that may influence release timing. To investigate the timing of glide avalanche release, we analyzed a dataset of annually recorded glide avalanches from 2003 to 2025 along the GTSR from mid-March to June. We identified 359 glide avalanches with starting zones covering all aspects between 1,600 and 2,700 meters, and performed analysis on topographic factors including elevation, aspect, slope angle, and bed surface. Additionally, we assessed the likelihood and sequence of the release of seven repeater paths. Seven repeater paths along the GTSR generate glide avalanches nearly every year (65–100% of the study period), with two paths (Peak 7774 and Peak 7850) releasing first in over half of the years observed (p-value < 0.01). These paths have been informally recognized as "indicator paths," though this distinction has not been quantified until now. Identifying factors that drive the timing of glide avalanches using a days-scale operational signal can support the safeguarding of infrastructure and personnel. By examining release order and related variables, this study provides practical insights to inform operations managing glide avalanche hazards. Our methods may help forecasters pinpoint indicator paths and potentially recognize the onset of glide avalanche cycles, offering a framework for other operations.

Montana↗

USGS2026

Tracking water in snow: Bridging sensor and and model simulations

Forecasting wet slab avalanches remains one of the most demanding challenges in operational avalanche forecasting. A key obstacle is the difficulty of observing and quantifying liquid water content (LWC) and tracking its infiltration into the snowpack. Field measurements are labor-intensive, highly variable in space, and often influenced by user application or sensor design — making them impractical for forecasting operations. In this study, we evaluated LWC measurements obtained from two capacitive sensors, the SLF SnowPro-17 and -25, and compared them with simulations from the snow cover model SNOWPACK. We analyzed five selected days with pronounced melt events during spring 2025 at Bridger Bowl Ski Area, Montana. The SnowPro-17 measured LWC on the sidewall and the SnowPro-25 was inserted into the pit wall. We then analyzed measurements from the two sensors to assess consistency and potential bias. For each of the five days, we also analyzed liquid water infiltration by layer, comparing field measurements with model-simulated LWC. This allowed us to assess how well the model captured both the timing and magnitude of infiltration processes relative to in-situ observations. Our results show that, the absolute LWC values differ by approximately 1% by vol. on average between measurements from the capacitive sensors, but the timing of liquid water infiltration is largely consistent across both measurements and model simulations. Within our sample, the SnowPro-17 consistently reports higher mean LWC values than the SnowPro-25, and exhibits greater variability, indicated by a larger standard deviation. We found good agreement when we compared in-situ sensor measurements to LWC infiltration in snow cover model simulations. This suggests that, despite measurement challenges and sensor variability, SNOWPACK can provide valuable information on the timing of LWC infiltration. For practitioners, this work highlights that reliable forecasting of wet slab avalanches depends on understanding when and how liquid water reaches critical layers. Because direct LWC measurements are rarely feasible in operational settings, using physically based models may offer a practical pathway forward.

Montana↗

USGS2026

Applying automated avalanche terrain mapping to wildlife ecology: A case study of Dall's sheep in southcentral Alaska

Avalanche hazard has been studied extensively in the context of human risk, but its role in alpine wildlife ecology remains poorly understood. Long-term telemetry studies have revealed that avalanches are an important source of mortality for some mountain ungulates. Investigating the processes underlying these events is challenging because avalanche activity and snowpack conditions are rarely monitored across the spatial and temporal extent of wildlife studies. Recent advances in automated avalanche terrain mapping provide a new opportunity to address this knowledge gap by quantifying wildlife exposure to modeled avalanche terrain across large landscapes. We demonstrate this application using Dall's sheep (Ovis dalli dalli) in southcentral Alaska, where a 12-year study identified avalanches as the leading known cause of adult mortality. We used GPS locations from 134 adult Dall's sheep (385 sheep-years) collected between 2012 and 2024 across Chugach State Park and the Talkeetna Mountains, Alaska, USA. We characterized seasonal patterns of terrain exposure using the Automated Avalanche Terrain Exposure Scale and complementary metrics representing potential release areas, runout terrain, slope, and aspect. Guided by previous studies of Dall's sheep habitat selection, we developed a priori ecological expectations for seasonal exposure and used descriptive summaries of GPS locations to examine patterns of sheep use. Sheep locations occurred almost exclusively within avalanche terrain throughout the year, with Complex terrain accounting for 61–67% of locations across seasons. Winter and spring locations occurred on slightly steeper slopes while simultaneously having lower potential release area values and lower-value runout terrain than summer and autumn locations. Use of south-facing terrain increased from 64% of locations in summer to 70% in autumn and winter and 83% in spring—coinciding with the highest seasonal concentration of avalanche mortality. These descriptive patterns illustrate how complementary avalanche-terrain metrics can reveal patterns of wildlife exposure that would not be apparent from slope angle and aspect alone. Integrating automated avalanche terrain mapping with wildlife telemetry provides a new approach for identifying patterns of terrain exposure to guide further investigation into factors influencing wildlife avalanche risk.

Alaska↗

USGS2026

Climate-driven shifts in snowpack conditions favorable for wet snow avalanches: Insights from snow cover model simulations

Forecasting wet snow avalanches remains a major challenge due to their temporal and spatial variability. Long-term climate trends are producing more variable and extreme weather, creating conditions outside historical experience, and increasing forecasting uncertainties. To assess how climate change affects the frequency and timing of wet snow avalanches, we examined the long-term conditions that support wet snow formation. Specifically, we ask: Will the onset of wet snow avalanche conditions or season end shift toward the mid century? And will maximum snow height decrease in avalanche starting zones? To address these questions, we analyze long-term snow cover simulations across our study site in Glacier National Park, Montana, located in an intermountain snow climate. We examined trends in simulated snow depth, and timing of liquid water infiltration over the past four decades (1979–2023) using a physically based snow cover model. To force the model with meteorological data, we use the long-term regional hydroclimate reanalysis dataset U.S. Geological Survey CONUS404 with 4 km spatial resolution and 1h temporal resolution. The use of gridded meteorological inputs to drive a one-dimensional point model introduces inherent scale mismatches. To address this limitation, we use multiple grid points within the study area to simulate a more representative, generalized snowpack, and filter the grid points based on elevation to distinguish between upper- and mid-elevation starting zones. Finally, we analyzed shifts in snow depth, melt-out-day, and LWCindex (bulk liquid water content (LWC) normalized by the residual water content). We use snow depth as a proxy for changes in slab thickness, the LWCindexas an indicator of wet snow avalanche conditions, and melt-out date as a measure of shifts in season length. We ran simulations on flat terrain and on north- and south-facing virtual slopes (38°), across mid-elevation (1,600–1,900 m) and upper-elevation (≥1,900 m) sites for the historical dataset as baseline and a Pseudo-Global-Warming (PGW) dataset to identify a warming driven shift. Across all aspects and both elevation bands, PGW forcing produces a consistent reduction in annual maximum snow depth (median shift −0.15 to −0.26 m, p<0.001) over 44 seasons, with the largest reductions on north-facing slopes and a modest but significant strengthening of this reduction over the 44-year simulated record. Melt-out starts 10–14 days earlier under PGW across all aspect–elevation combinations (p<0.001), again most pronounced on north-facing, higher-elevation terrain. The LWCindex threshold-crossing dates likewise shift earlier under PGW, indicating an earlier onset of wet snow avalanche conditions across the domain. Together, these results point to a snowpack that is both thinner and wetter earlier in the season under future warming, with the strongest signal consistently on north-facing slopes at higher elevation. This work lays the groundwork for climate-informed forecasting and mitigation and offers historical context for avalanche operations in a changing climate. Understanding long-term trends can help avalanche professionals interpret current observations, improve wet snow avalanche forecasting, and develop more effective mitigation strategies in a warming climate.

Montana↗

USGS2019

Research Note: How old are the people who die in avalanches? A look into the ages of avalanche victims in the United States (1950-2018)

Since the winter of 1950-1951, 1084 individuals perished in snow avalanches in the United States. In this study, we analyze the ages of those killed (n=900) by applying non-parametric methods to annual median ages and for age groups and primary activity groups. Change point detection results suggest a significant change in 1990 in the median age of avalanche fatalities. Significant positive trends exist for both the 1950 to 2018 and 1990 to 2018 median age of victims. The median age of victims from 1950 to 1989 is 27 and 33 from 1990 to 2018. Since 1990, the 30-39 and 40-49 age groups are the only age category to exhibit a positive trend in the number of fatalities. There is no significant difference in median ages between snowmobilers and other categories. These results can be used to enhance avalanche education and forecasting efforts in the United States.

Journal of Outdoor Recreation and Tourism↗

USGS2018

Forecasting for dry and wet avalanches during mixed rain and snow storm events

Natural wet slab avalanches release when rain or melt water decreases snowpack strength, and natural dry slab avalanches release when an increased load overcomes snowpack strength. This study investigates avalanche activity resulting from mixed rain and snow falling on a faceted snowpack. This scenario produced an extensive slab avalanche cycle in March 2018 in the mountains near Ketchum, Idaho, when a 24 hour storm deposited 50 to 65 mm of water. We investigate the contributions of the pre-existing snowpack structure and weather to avalanching, and suggest possible mechanisms for the observed slab avalanche activity. At upper elevations, expected widespread, 0.5 to 3 m deep, dry slab avalanche activity occurred on many aspects. However, at middle elevations (2300 m to 2700 m) near the fluctuating rain-snow line, a low frequency return period avalanche cycle occurred in a much smaller geographical area, and was concentrated around north-northwest aspects. This differs significantly from avalanches above this elevation that spanned all aspects. This scenario illustrates the challenges forecasting and communicating these events. In our experience, some avalanche cycles exist in a continuum of avalanche types that are not easily sorted into simple “wet” and “dry” categories. We discuss challenges in using current advisory and bulletin communication tools. Furthermore, it is possible that a changing climate will increase the frequency of mixed rain-snow events in areas with traditionally drier and colder climates. We believe the avalanche community will benefit from the refinement and development of tools and techniques to describe and forecast this challenging problem.

Conference Paper↗