Geology topics

Gabriel Wolken

Publications and source records attributed to Gabriel Wolken.

4 recordsLinked to original sources

USGS2024

Snow avalanches are a primary climate-linked driver of mountain ungulate populations

Snow is a major, climate-sensitive feature of the Earth’s surface and catalyst of fundamentally important ecosystem processes. Understanding how snow influences sentinel species in rapidly changing mountain ecosystems is particularly critical. Whereas effects of snow on food availability, energy expenditure, and predation are well documented, we report how avalanches exert major impacts on an ecologically significant mountain ungulate - the coastal Alaskan mountain goat ( Oreamnos americanus ). Using long-term GPS data and field observations across four populations (421 individuals over 17 years), we show that avalanches caused 23−65% of all mortality, depending on area. Deaths varied seasonally and were directly linked to spatial movement patterns and avalanche terrain use. Population-level avalanche mortality, 61% of which comprised reproductively important prime-aged individuals, averaged 8% annually and exceeded 22% when avalanche conditions were severe. Our findings reveal a widespread but previously undescribed pathway by which snow can elicit major population-level impacts and shape demographic characteristics of slow-growing populations of mountain-adapted animals.

Alaska↗

USGS2023

Big avalanches in a changing climate: Using tree-ring derived avalanche chronologies to examine avalanche frequency across multiple climate types

Large-magnitude snow avalanches pose a hazard to humans and infrastructure worldwide. Analyzing the spatiotemporal behavior of avalanches and the contributory climate factors is important for understanding historical variability in climate-avalanche relationships as well as improving avalanche forecasting. This study uses established dendrochronological methods to develop long-term regional avalanche chronologies for three different climate types: high-latitude maritime climate of southeast Alaska, intermountain climate of the northern Rocky Mountains, and continental climate of Colorado. In the maritime study area, we collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between year 1720 and 2018 Common Era (CE), which allowed us to reconstruct 82 years with large magnitude avalanche activity across three sub-regions. By combining this tree-ring derived avalanche dataset with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of large magnitude avalanche activity in the southeast Alaska study area. In the intermountain climate study area, tree-rings from 647 trees exhibited 2134 avalanche-related growth disturbances in the northern Rocky Mountains of northwest Montana from 1867 to 2019. The data show that the amount of snowpack across the northern Rocky Mountain region is directly related to avalanche probability. Coincident with warming and regional snowpack reductions, a decline of ~ 14% (~ 2% per decade) in overall large magnitude avalanche probability is apparent through the period 1950–2017 CE. In the continental climate of Colorado, we sampled 24 avalanche paths throughout the state and collected 1188 total samples with 4135 identified growth disturbances from 1698 to 2019. Preliminary results suggest years with large magnitude avalanche activity across the sub-regions of this study area are generally characterized by stormy winters with above average snowpack development but that early and late winter temperature and precipitation also play an important role in large avalanche activity. Characterizing historical climate-avalanche relationships across different climate types provides a broad baseline for understanding potential future changes in avalanche activity. Overall, this work helps forecasters and planners better understand the influence of climate on large magnitude avalanche frequency, and how potential changes in avalanche character and occurrence will affect their operations in the context of a warming climate.

Alaska, Colorado, Montana↗

USGS2020

Deglacierization of a marginal basin and implications for outburst floods, Mendenhall Glacier, Alaska

Suicide Basin is a partly glacierized marginal basin of Mendenhall Glacier, Alaska, that has released glacier lake outburst floods (GLOFs) annually since 2011. The floods cause inundation and erosion in the Mendenhall Valley, impacting homes and other infrastructure. Here, we utilize in-situ and remote sensing data to assess the recent evolution and current state of Suicide Basin. We focus on the 2018 and 2019 melt seasons, during which we collected most of our data, partly using unmanned aerial vehicles (UAVs). To provide longer-term context, we analyze DEMs collected since 2006 and model glacier surface mass balance over the 2006–2019 period. During the 2018 and 2019 outburst flood events, Suicide Basin released ~30 × 10 6 m 3 of water within approximately 4–5 days. Since lake drainage was partial in both years, these ~30 × 10 6 m 3 represent only a fraction (~60%) of the basin's total storage capacity. In contrast to previous years, subglacial drainage was preceded by supraglacial outflow over the ice dam, which lasted ~1 day in 2018 and 6 days in 2019. Two large calving events occurred in 2018 and 2019, with submerged ice breaking off the main glacier during lake filling, thereby increasing the basin's storage capacity. In 2018, the floating ice in the basin was 36 m thick on average. In 2019, ice thickness was 29 m, suggesting rapid decay of the ice tongue despite increasing ice inflow from Mendenhall Glacier. The ice dam at the basin entrance thinned by more than 5 m a –1 from 2018 to 2019, which is approximately double the rate of the reference period 2006–2018. While ice-dam thinning reduces water storage capacity in the basin, that capacity is increased by declining ice volume in the basin and longitudinal lake expansion, with the latter process challenging to predict. The potential for premature drainage onset (i.e., drainage before the lake's storage capacity is reached), intermittent drainage decelerations, and early drainage termination further complicates prediction of future GLOF events.

Alaska↗

USGS2015

End-of-winter snow depth variability on glaciers in Alaska

A quantitative understanding of snow thickness and snow water equivalent (SWE) on glaciers is essential to a wide range of scientific and resource management topics. However, robust SWE estimates are observationally challenging, in part because SWE can vary abruptly over short distances in complex terrain due to interactions between topography and meteorological processes. In spring 2013, we measured snow accumulation on several glaciers around the Gulf of Alaska using both ground- and helicopter-based ground-penetrating radar surveys, complemented by extensive ground truth observations. We found that SWE can be highly variable (40% difference) over short spatial scales (tens to hundreds of meters), especially in the ablation zone where the underlying ice surfaces are typically rough. Elevation provides the dominant basin-scale influence on SWE, with gradients ranging from 115 to 400 mm/100 m. Regionally, total accumulation and the accumulation gradient are strongly controlled by a glacier's distance from the coastal moisture source. Multiple linear regressions, used to calculate distributed SWE fields, show that robust results require adequate sampling of the true distribution of multiple terrain parameters. Final SWE estimates (comparable to winter balances) show reasonable agreement with both the Parameter-elevation Relationships on Independent Slopes Model climate data set (9–36% difference) and the U.S. Geological Survey Alaska Benchmark Glaciers (6–36% difference). All the glaciers in our study exhibit substantial sensitivity to changing snow-rain fractions, regardless of their location in a coastal or continental climate. While process-based SWE projections remain elusive, the collection of ground-penetrating radar (GPR)-derived data sets provides a greatly enhanced perspective on the spatial distribution of SWE and will pave the way for future work that may eventually allow such projections.

Alaska↗