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Gabriel J. Wolken

Publications and source records attributed to Gabriel J. Wolken.

5 recordsLinked to original sources

2024 Surprise Inlet landslides: Insights from a prototype landslide‐triggered tsunami monitoring system in Prince William Sound, Alaska

Alaska's coastal communities face growing landslide hazards owing to glacier retreat and extreme weather intensified by the warming climate, yet hazard monitoring remains challenging. As part of ongoing experimental monitoring in Prince William Sound, we detected three large landslides (0.5–2.3 M m 3 ) at Surprise Inlet on 20 September 2024, within the span of an hour. These events were identified in near real-time through seismic data and later confirmed using satellite imagery, tidal records, and infrasound. The landslides generated a modest tsunami, and a 4 cm wave was recorded by a tide gauge 18 km away, marking the first recorded landslide to reach water since monitoring began in this region in 2021. Here, we examine the detection and interpretation of these landslides using multiple data sources and modeling. We demonstrate the effectiveness of this regional seismic monitoring system and show how complementary instrumentation, where available, can enhance detection capabilities.

Alaska↗

An analytical approach for simulating effects of avalanches on mountain goat population dynamics: Implications for management and conservation

Mountain environments with snow avalanche hazard cover about 6% of Earth’s land area and occur on all continents. Whereas human risks associated with avalanche hazard have been widely studied, little is known about how avalanche activity affects population dynamics in mountain wildlife. Globally, 32 species of mountain ungulates across 70 countries occupy avalanche-prone terrain. Avalanches comprise the leading cause of mortality in coastal Alaskan mountain goats (mean = 36%, range = 23 - 65%, depending on area), and disproportionately remove prime-aged individuals from populations. The implications of such rates and patterns of mortality on population growth rate are likely to be significant given the species’ low reproductive productivity, but further clarity is needed. To fill this knowledge gap, we developed a sex- and age-specific population modeling approach that integrates both reproduction and mortality to simulate the effects of avalanche-caused mortality on population growth rate across a range of empirically-observed states of avalanche-caused mortality (minimum, mean, maximum). Simulations were conducted to illustrate model functionality, and also provide insight about potential avalanche impacts on population demographic processes. For example, when severe avalanche years occur populations can experience significant additive mortality and declines (up to 15%). Due to low reproductive rates and slow life-history strategy of the species, such impacts can lead to long demographic recovery times (up to 11 years). From a species conservation perspective, such impacts are striking, and highlight the utility of employing a quantitative modeling approach to predict possible effects of avalanches on mountain ungulate population dynamics and viability. Our work explicitly builds upon recent findings about the importance of avalanches on mountain-adapted animal populations, and associated implications for the cultural and ecological communities that depend on them.

Alaska↗

Kinematic evolution of a large paraglacial landslide in the Barry Arm fjord of Alaska

Our warming climate is adversely affecting cryospheric landscapes via glacial retreat, permafrost degradation, and associated slope destabilization. In Prince William Sound, Alaska, the rapid retreat of Barry Glacier has destabilized the slopes flanking the glacier, resulting in numerous landslides. The largest of these landslides (∼500 Mm 3 in volume) is more than 2 km wide and has the potential to generate a tsunami that could affect nearby recreationists, marine traffic, infrastructure, natural and cultural resources, and the community of Whittier, located 60 km from the landslide. Here, we combine landslide structural and kinematic element mapping with data acquired from bi-yearly airborne lidar, multi-week satellite-based synthetic aperture radar (SAR), sub-hourly ground-based SAR, and seismic monitoring from 2020 to 2022 to characterize this landslide and examine its evolution. While some methods serve as a snapshot in time that is a culmination of events, others emphasize the ever-evolving nature of the landslide and associated hazards. Four major kinematic elements define the overall structure of the landslide, which vary in deformation type and rate, from creep (5 mm per day over several months) to episodic movement (2 m in 30 days) and landslide-wide to localized events. In some areas of the landslide, short-term deformation deviates from structures formed by cumulative movement, implying structural and kinematic evolution associated with glacier retreat. These insights are important for assessing landslide hazards and hazard evolution for large, slow-moving bedrock landslides in actively deglaciating environments.

Alaska↗

Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate

Snow avalanches are a natural hazard in mountainous areas worldwide with severe impacts that include fatalities, damage to infrastructure, disruption to commerce, and landscape disturbance. Understanding long-term avalanche frequency patterns, and associated climate and weather influences, improves our understanding of how climate change may affect avalanche activity. We used dendrochronological techniques to evaluate the historical frequency of large magnitude avalanches (LMAs) in the high-latitude climate of southeast Alaska, United States. We collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between 1720 and 2018, which allowed us to reconstruct 82 years with LMA activity across three sub-regions. By combining this tree-ring-derived avalanche data set with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found that February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of LMA activity in the study area. Specifically, LMA activity occurred during winters with substantial February and March precipitation and neutral or negative (cold) ONI values, while years not characterized by LMAs occur more frequently during warm winters (positive ONI values). Our examination of the climate-avalanche relationship in southeast Alaska sheds light on important climate variables and physical processes associated with LMA years. These results can be used to inform long-term infrastructure planning and avalanche mitigation operations in an urban area, such as Juneau, where critical infrastructure is subject to substantial avalanche hazard.

Alaska↗

Mountain Glaciers and Ice Caps

In addition to the Greenland Ice Sheet, the Arctic contains a diverse array of smaller glaciers ranging from small cirque glaciers to large ice caps with areas up to 20 000 km 2 . Together, these glaciers cover an area of more than 400 000 km 2 , over half the global area of mountain glaciers and ice caps. Their total volume is sufficient to raise global sea level by an average of about 0.41 m if they were to melt completely. These glaciers exist in a range of different climatic regimes, from the maritime environments of southern Alaska, Iceland, western Scandinavia, and Svalbard, to the polar desert of the Canadian Arctic. Glaciers in all regions of the Arctic have decreased in area and mass as a result of the warming that has occurred since the 1920s (in two pulses – from the 1920s to the 1940s and since the mid-1980s). A new phase of accelerated mass loss began in the mid-1990s, and has been most marked in Alaska, the Canadian Arctic, and probably Greenland. Current rates of mass loss are estimated to be in the range 150 to 300 Gt/y; comparable to current mass loss rates from the Greenland Ice Sheet. This implies that the Arctic is now the largest regional source of glacier contributions to global sea-level rise. Most of the current mass loss is probably attributable to a change in surface mass balance (the balance between annual mass addition, primarily by snowfall, and annual mass loss by surface melting and meltwater runoff). Iceberg calving is also a significant source of mass loss in areas such as coastal Alaska, Arctic Canada, Svalbard, and the Russian Arctic. However, neither the current rate of calving loss nor its temporal variability have been well quantified in many regions, so this is a significant source of uncertainty in estimates of the total rate of mass loss. It is, however, clear that the larger Arctic ice caps have similar variability in ice dynamics to that of the Greenland Ice Sheet. That is to say, areas of relatively slow glacier flow (which terminate mainly on land) are separated by faster-flowing outlet glaciers (which terminate mainly in the ocean). Several of these outlet glaciers exhibit surge-type behavior, while others have exhibited substantial velocity changes on seasonal and longer timescales. It is very likely that these changes in ice dynamics affect the rate of mass loss by calving both from individual glaciers and the total ice cover. Projections of future rates of mass loss from mountain glaciers and ice caps in the Arctic focus primarily on projections of changes in the surface mass balance. Current models are not yet capable of making realistic forecasts of changes in losses by calving. Surface mass balance models are forced with downscaled output from climate models driven by forcing scenarios that make assumptions about the future rate of growth of atmospheric greenhouse gas concentrations. Thus, mass loss projections vary considerably, depending on the forcing scenario used and the climate model from which climate projections are derived. A new study in which a surface mass balance model is driven by output from ten general circulation models (GCMs) forced by the IPCC (Intergovernmental Panel on Climate Change) A1B emissions scenario yields estimates of total mass loss of between 51 and 136 mm sea-level equivalent (SLE) (or 13% to 36% of current glacier volume) by 2100. This implies that there will still be substantial glacier mass in the Arctic in 2100 and that Arctic mountain glaciers and ice caps will continue to influence global sea-level change well into the 22nd century.

Book chapter↗