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We assess the composition and geometry of four individual rock glaciers in Alaska, Wyoming and Colorado by measuring their radio wave speed and applying these results to ground-penetrating radar depth corrections and dielectric mixing models. Our method includes a correction for subsurface reflector dip angle, which we show can lead to an incorrect determination of wave speeds using common midpoint configurations. By observing the radar properties of the rock glaciers and their supraglacial debris, we find that some of the sites exhibit nearly pure ice cores, and all of the sites indicate volumetric ice fractions >50%. These results have implications for terrestrial glaciology and hydrology because the present ice volume is connected to past ice accumulation and subsurface ice preservation, which may affect the future availability of alpine water resources. An understanding of the processes that govern rock glacier evolution over a wide range of latitudes and elevations will also contribute to the exploration of planetary surfaces such as Mars, which hosts a significant population of debris-covered glaciers. Our subsurface composition and geometry estimates will inform simulations of rock glacier formation and evolution to test hypothesized ice origin mechanisms along with the preservation of climate signals. [ABSTRACT FROM AUTHOR]

Glaciers in the western USA contribute summer meltwater to regional hydrological systems. In the San Juan Mountains of Colorado, where glaciers do not exist, rock glaciers serve that function during the summer runoff period. Most rock glaciers in Colorado are located on northern slopes in mountainous areas; however, some rock glaciers in southwest Colorado have different aspects. In this study, we asked how slope aspect and rising air temperatures influence the hydrological processes of streams sourced from rock glaciers in the San Juan Mountains. We focused on three adjacent basins, Yankee Boy basin, Blue Lakes basin, and Mill Creek basin, which share a common peak, Gilpin Peak. Using HOBO® U20-001–04 water-level loggers, streamflow data were collected in each of these basins, below each rock glacier. Air temperature significantly influenced stream discharge below the rock glacier. Discharge and air temperature patterns indicate a possible air temperature threshold during late summer when rock glacier melt increases at a greater rate. The results also suggest that the aspect of rock glacier basins influences stream discharge, but that temperature and precipitation are likely larger components of melt regimes. [ABSTRACT FROM AUTHOR]

Abstract: The distribution of mountain permafrost along Trail Ridge Road (TRR) in Rocky Mountain National Park, Colorado, was modeled using ‘frost numbers’ and a ‘temperature of permafrost model’ (TTOP) in order to assess the accuracy of prediction models. The TTOP model is based on regional observations of air temperature and heat transfer functions involving vegetation, soil, and snow; whereas the frost number model is based on site-specific ratios of ground temperature measurements of frozen and thawed degree-days. Thirty HOBO© temperature data loggers were installed near the surface as well as at depth (30 to 85cm). From mid-July 2008 to 2010, the mean annual soil temperature (MAST) for all surface sites was −1.5°C. Frost numbers averaged 0.56; TTOP averaged −1.8°C. The MAST was colder on western-facing slopes at high elevations. Surface and deeper probes had similar MASTs; however, deeper probes had less daily and seasonal variation. Another model developed at the regional scale based on proxy indicators of permafrost (rock glaciers and land cover) classified 5.1km2 of permafrost within the study area, whereas co-kriging interpolations of frost numbers and TTOP data indicated 2.0km2 and 4.6km2 of permafrost, respectively. Only 0.8km2 were common among all three models. Three boreholes drilled within 2m of TRR indicate that permafrost does not exist at these locations despite each borehole being classified as containing permafrost by at least one model. Addressing model uncertainty is important because nutrients stored within frozen or frost-affected soils can be released and impact alpine water bodies. The uncertainty also exposes two fundamental problems: empirical models designed for high latitudes are not necessarily applicable to mountain permafrost, and the presence of mountain permafrost in the alpine tundra of the Colorado Front Range has not been validated. [Copyright &y& Elsevier]

Mountain terrestrial and aquatic ecosystems are responsive to external drivers of change, especially climate change and atmospheric deposition of nitrogen (N). We explored the consequences of a temperature-warming trend on stream nitrate in an alpine and subalpine watershed in the Colorado Front Range that has long been the recipient of elevated atmospheric N deposition. Mean annual stream nitrate concentrations since 2000 are higher by 50% than an earlier monitoring period of 1991–1999. Mean annual N export increased by 28% from 2.03 kg N ha−1 yr−1 before 2000 to 2.84 kg N ha−1 yr−1 in Loch Vale watershed since 2000. The substantial increase in N export comes as a surprise, since mean wet atmospheric N deposition from 1991 to 2006 (3.06 kg N ha−1 yr−1) did not increase. There has been a period of below average precipitation from 2000 to 2006 and a steady increase in summer and fall temperatures of 0.12 °C yr−1 in both seasons since 1991. Nitrate concentrations, as well as the weathering products calcium and sulfate, were higher for the period 2000–2006 in rock glacier meltwater at the top of the watershed above the influence of alpine and subalpine vegetation and soils. We conclude the observed recent N increases in Loch Vale are the result of warmer summer and fall mean temperatures that are melting ice in glaciers and rock glaciers. This, in turn, has exposed sediments from which N produced by nitrification can be flushed. We suggest a water quality threshold may have been crossed around 2000. The phenomenon observed in Loch Vale may be indicative of N release from ice features such as rock glaciers worldwide as mountain glaciers retreat. [ABSTRACT FROM AUTHOR]

Abstract: The performance improvements that can be achieved by classifier selection and by integrating terrain attributes into land cover classification are investigated in the context of rock glacier detection. While exposed glacier ice can easily be mapped from multispectral remote-sensing data, the detection of rock glaciers and debris-covered glaciers is a challenge for multispectral remote sensing. Motivated by the successful use of digital terrain analysis in rock glacier distribution models, the predictive performance of a combination of terrain attributes derived from SRTM (Shuttle Radar Topography Mission) digital elevation models and Landsat ETM+ data for detecting rock glaciers in the San Juan Mountains, Colorado, USA, is assessed. Eleven statistical and machine-learning techniques are compared in a benchmarking exercise, including logistic regression, generalized additive models (GAM), linear discriminant techniques, the support vector machine, and bootstrap-aggregated tree-based classifiers such as random forests. Penalized linear discriminant analysis (PLDA) yields mapping results that are significantly better than all other classifiers, achieving a median false-positive rate (mFPR, estimated by cross-validation) of 8.2% at a sensitivity of 70%, i.e. when 70% of all true rock glacier points are detected. The GAM and standard linear discriminant analysis were second best (mFPR: 8.8%), followed by polyclass. For comparison, the predictive performance of the best three techniques is also evaluated using (1) only terrain attributes as predictors (mFPR: 13.1–14.5% for best three techniques), and (2), only Landsat ETM+ data (mFPR: 19.4–22.7%), yielding significantly higher mFPR estimates at a 70% sensitivity. The mFPR of the worst three classifiers was by about one-quarter higher compared to the best three classifiers, and the combination of terrain attributes and multispectral data reduced the mFPR by more than one-half compared to remote sensing only. These results highlight the importance of combining remote-sensing and terrain data for mapping rock glaciers and other debris-covered ice and choosing the optimal classifier based on unbiased error estimators. The proposed benchmarking methodology is more generally suitable for comparing the utility of remote-sensing algorithms and sensors. [Copyright &y& Elsevier]

Here we characterize the nutrient content in the outflow of the Green Lake 5 rock glacier, located in the Green Lakes Valley of the Colorado Front Range. Dissolved organic carbon (DOC) was present in all samples with a mean concentration of 0·85 mg L-1. A one-way analysis of variance test shows no statistical difference in DOC amounts among surface waters (p = 0·42). Average nitrate concentrations were 69 μmoles L-1 in the outflow of the rock glacier, compared to 7 μmoles L-1 in snow and 25 μmoles L-1 in rain. Nitrate concentrations from the rock glacier generally increased with time, with maximum concentrations of 135 μmoles L-1 in October, among the highest nitrate concentrations reported for high-elevation surface waters. These high nitrate concentrations appear to be characteristic of rock glacier outflow in the Rocky Mountains, as a paired-difference t-test shows that nitrate concentrations from the outflow of 7 additional rock glaciers were significantly greater compared to their reference streams (p = 0003). End-member mixing analysis suggest that snow was the dominant source of nitrate in June, ‘soil’ solution was the dominant nitrate source in July, and base flow was the dominant source in September. Fluoresence index values and PARAFAC analyses of dissolved organic matter (DOM) are also consistent with a switch from terrestrial DOM in the summer time period to an increasing aquatic-like microbial source during the autumn months. [ABSTRACT FROM AUTHOR]

During the 1960s, several surveying networks were established on rock glaciers located in the Front Range of the Colorado Rocky Mountains. Most surveys were updated every 1 to 5 years until approximately 1966, providing a short-term record of flow velocities; however, since these initial studies, the measurements have not been updated. Short-term and long-term flow velocities are needed to examine the evolution of rock glaciers. During the summer of 2002, I re-established surveying networks, and obtained a 40-plus year record of flow. Average rates of 7.3, 6.3, and 9.5 cm/year were calculated for the Arapaho, Taylor, and Fair rock glaciers, respectively. Compared to other rock glaciers, the displacements are small because surveyed rocks are situated in a zone of compressive flow near the toes of the rock glaciers. Most displacements were within 10% of the projected estimates and were not significantly different from the earlier short-term measurements. Meteorological data do not show a clearly defined warming trend but indicate a slight increase in total precipitation. Rates of flow have remained consistent and suggest that rock glaciers in the Front Range are adjusted to the current climate, unlike some rock glaciers in the European Alps. The rock glaciers, however, are not in a permanent steady state and are still likely adjusting to neoglacial environmental processes (within 4000 years B.P.). [ABSTRACT FROM AUTHOR]

Rock glaciers, a feature associated with at least discontinuous permafrost, provide important topoclimatic information. Active and inactive rock glaciers can be used to model current permafrost distribution. Relict rock glacier locations provide paleoclimatic information to infer past conditions. Future warmer climates could cause permafrost zones to shrink and initiate slope instability hazards such as debris flows or rockslides, thus modeling change remains imperative. This research examines potential past and future permafrost distribution in the Colorado Front Range by calibrating an existing permafrost model using a standard adiabatic rate for mountains (0·5 °C per 100 m) for a 4 °C range of cooler and warmer temperatures. According to the model, permafrost currently covers about 12 per cent (326·1 km2) of the entire study area (2721·5 km2). In a 4 °C cooler climate 73·7 per cent (2004·4 km2) of the study area could be covered by permafrost, whereas in a 4°C warmer climate almost no permafrost would be found. Permafrost would be reduced severely by 93·9 per cent (a loss of 306·2 km2) in a 2·0 °C warmer climate; however, permafrost will likely respond slowly to change. Relict rock glacier distribution indicates that mean annual air temperature (MAAT) was once at least some 3·0 to 4·0 °C cooler during the Pleistocene, with permafrost extending some 600–700 m lower than today. The model is effective at identifying temperature sensitive areas for future monitoring; however, other feedback mechanisms such as precipitation are neglected. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]