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  1. Rock glaciers are common landforms in mountainous areas of the western US. The motion of active rock glaciers is a key indicator of ice content, offering connections to climate and hydrologic systems. Here, we quantified the movement of six rock glaciers in the La Sal and Uinta Mountains of Utah through repeat differential GPS surveying. Networks of 10–41 points on each rock glacier were surveyed in September 2021; July 2022; September 2022; and July 2023. We found that all features are moving with average annual rates of motion from 1.5 ± 0.8 to 18.5 ± 7.5 cm/yr. Rock glaciers move up to 3× faster in the summer than in the winter, and rates of motion were greater in 2023 after a winter with above-average snowfall, emphasizing the role of liquid water availability. Velocities of individual points in the winter of 2021–22 are positively correlated with velocities during the winter of 2022–23, suggesting that spatial variability of motion is not stochastic, but rather reflects internal properties of each rock glacier. Bottom temperature of snow measurements during winter, and the temperature of springs discharging water in summer, suggest that these rock glaciers contain modern permafrost. Radiocarbon data document advance of one rock glacier during the Little Ice Age. Our GPS dataset reveals complicated patterns of rock glacier movement, and the network of survey points we established will be a valuable baseline for detecting future cryosphere change in these mountains. 
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    Free, publicly-accessible full text available June 1, 2025
  2. Rock glaciers are common geomorphic features in alpine landscapes and comprise a potentially significant but poorly quantified water resource. This project focused on three complementary questions germane to rock glacier hydrology: 1) Does the composition of rock glacier meltwater vary from year to year? 2) How dependent is the composition of rock glacier meltwater on lithology? And 3) How does the presence of rock glaciers in a catchment change stream water chemistry? To address these questions, we deployed automated samplers to collect water from late June through mid-October 2022 in two rock-glacierized mountain ranges in Utah, United States characterized by different lithologies. In the Uinta Mountains of northern Utah, where bedrock is predominantly quartzite, water was collected at springs discharging from two rock glaciers previously shown to release water in late summer sourced from internal ice. In the La Sal Mountains of southeastern Utah, where trachyte bedrock is widespread, water was collected at a rock glacier spring, along the main stream in a watershed containing multiple rock glaciers, and from a stream in a watershed where rock glaciers are absent. Precipitation was also collected, and data loggers for water temperature and electric conductivity were deployed. Water samples were analyzed for stable isotopes with cavity ring-down spectroscopy and hydrochemistry with ICP-MS. Our data show that water discharging from rock glaciers in the Uinta Mountains exhibits a shift from a snowmelt source to an internal ice source over the course of the melt season that is consistent from year to year. We also found that the chemistry of rock glacier water in the two study areas is notably different in ways that can be linked back to their contrasting bedrock types. Finally, in the La Sal Mountains, the properties of water along the main stream in a rock-glacierized basin resemble the properties of water discharging from rock glaciers, and strongly contrast with the water in a catchment lacking rock glaciers. Collectively these results underscore the role of rock glaciers as an agent influencing the hydrochemistry of water in high-elevation stream systems. 
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  3. Abstract. Water draining from rock glaciers in the Uinta Mountains of Utah(USA) was analyzed and compared with samples of groundwater and water fromthe primary stream in a representative 5000 ha drainage. Rock glacier water resembles snowmelt in the early summer but evolves to higher values of d-excess and greatly elevated Ca and Mg content as the melt season progresses. This pattern is consistent with models describing a transition from snowmelt to melting of seasonal ice to melting of perennial ice in the rock glacier interior in late summer and fall. Water derived from this internal ice appears to have been the source of ∼25 % of the streamflow in this study area during September of 2021. This result emphasizes the significant role that rock glaciers can play in the hydrology of high-elevation watersheds, particularly in summers following a winter with below-average snowpack. 
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  4. Abstract

    Rock glaciers are common in alpine landscapes, but their evolution over time and their significance as agents of debris transport are not well‐understood. Here, we assess the movement of an ice‐cemented rock glacier over a range of timescales using GPS surveying, satellite‐based radar, and cosmogenic10Be surface‐exposure dating. GPS and InSAR measurements indicate that the rock glacier moved at an average rate of ∼10 cm yr−1in recent years. Sampled boulders on the rock glacier have cosmogenic surface‐exposure ages from 1.2 to 10 ka, indicating that they have been exposed since the beginning of the Holocene. Exposure ages increase linearly with distance downslope, suggesting a slower long‐term mean surface velocity of 3 ± 0.3 cm yr−1. Our findings suggest that the behavior of this rock glacier may be dominated by episodes of dormancy punctuated by intervals of relatively rapid movement over both short and long timescales. Our findings also show that the volume of the rock glacier corresponds to ∼10 m of material stripped from the headwall during the Holocene. These are the first cosmogenic surface‐exposure ages to constrain movement of a North American rock glacier, and together with the GPS and satellite radar measurements, they reveal that rock glaciers are effective geomorphic agents with dynamic multi‐millennial histories.

     
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  5. The Chaos Canyon landslide, which collapsed on the afternoon of 28 June 2022 in Rocky Mountain National Park, presents an opportunity to evaluate instabilities within alpine regions faced with a warming and dynamic climate. Video documentation of the landslide was captured by several eyewitnesses and motivated a rapid field campaign. Initial estimates put the failure area at 66 630 m2, with an average elevation of 3555 m above sea level. We undertook an investigation of previous movement of this landslide, measured the volume of material involved, evaluated the potential presence of interstitial ice and snow within the failed deposit, and examined potential climatological impacts on the collapse of the slope. Satellite radar and optical measurements were used to calculate deformation of the landslide in the 5 years leading up to collapse. From 2017 to 2019, the landslide moved ∼5 m yr−1, accelerating to 17 m yr−1 in 2019. Movement took place through both internal deformation and basal sliding. Climate analysis reveals that the collapse took place during peak snowmelt, and 2022 followed 10 years of higher than average positive degree day sums. We also made use of slope stability modeling to test what factors controlled the stability of the area. Models indicate that even a small increase in the water table reduces the factor of safety to <1, leading to failure. We posit that a combination of permafrost thaw from increasing average temperatures, progressive weakening of the basal shear zone from several years of movement, and an increase in pore-fluid pressure from snowmelt led to the 28 June collapse. Material volumes were estimated using structure from motion (SfM) models incorporating photographs from two field expeditions on 8 July 2022 – 10 d after the slide. Detailed mapping and SfM models indicate that ∼1 258 000 ± 150 000 m3 of material was deposited at the slide toe and ∼1 340 000 ± 133 000 m3 of material was evacuated from the source area. The Chaos Canyon landslide may be representative of future dynamic alpine topography, wherein slope failures become more common in a warming climate.

     
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  6. Abstract

    Slow-moving landslides move downslope at velocities that range from mm year−1to m year−1. Such deformations can be measured using satellite-based synthetic aperture radar interferometry (InSAR). We developed a new method to systematically detect and quantify accelerations and decelerations of slowly deforming areas using InSAR displacement time series. The displacement time series are filtered using an outlier detector and subsequently piecewise linear functions are fitted to identify changes in the displacement rate (i.e., accelerations or decelerations). Grouped accelerations and decelerations are inventoried as indicators of potential unstable areas. We tested and refined our new method using a high-quality dataset from the Mud Creek landslide, CA, USA. Our method detects accelerations and decelerations that coincide with those previously detected by manual examination. Second, we tested our method in the region around the Mazar dam and reservoir in Southeast Ecuador, where the time series data were of considerably lower quality. We detected accelerations and decelerations occurring during the entire study period near and upslope of the reservoir. Application of our method results in a wealth of information on the dynamics of the surface displacement of hillslopes and provides an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of accelerations and decelerations can be used to study the physical behavior of a slow-moving slope or for regional hazard assessment by linking the timing of changes in displacement rates to landslide causal and triggering factors.

     
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  7. Abstract. Rapid detection of landslides is critical for emergency response, disaster mitigation, and improving our understanding of landslide dynamics. Satellite-based synthetic aperture radar (SAR) can be used to detect landslides, often within days of a triggering event, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Here we present a SAR backscatter change approach in the cloud-based Google Earth Engine (GEE) that uses multi-temporal stacks of freely available data from the Copernicus Sentinel-1 satellites to generate landslide density heatmaps for rapid detection. We test our GEE-based approach on multiple recent rainfall- and earthquake-triggered landslide events. Our ability to detect surface change from landslides generally improves with the total number of SAR images acquired before and after a landslide event, by combining data from both ascending and descending satellite acquisition geometries and applying topographic masks to remove flat areas unlikely to experience landslides. Importantly, our GEE approach does not require downloading a large volume of data to a local system or specialized processing software, which allows the broader hazard and landslide community to utilize and advance these state-of-the-art remote sensing data for improved situational awareness of landslide hazards. 
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