scholarly journals Pluri‐decadal evolution of rock glaciers surface velocity and its impact on sediment export rates towards high alpine torrents

2021 ◽  
Author(s):  
Mario Kummert ◽  
Xavier Bodin ◽  
Luc Braillard ◽  
Reynald Delaloye
Keyword(s):  
Surface Velocity ◽  
Rock Glaciers ◽  
Sediment Export

Schmidt-hammer exposure-age dating (SHD) of rock glaciers in the Schöderkogel-Eisenhut area, Schladminger Tauern Range, Austria

The Holocene ◽  
2011 ◽  
Vol 22 (7) ◽  
pp. 761-771 ◽  
Author(s):  
Matthias Rode ◽  
Andreas Kellerer-Pirklbauer
Keyword(s):  
Root Zone ◽  
Age Dating ◽  
Surface Velocity ◽  
Schmidt Hammer ◽  
Rock Glacier ◽  
Relative Age ◽  
Exposure Age ◽  
Rock Glaciers ◽  
Glacier Length ◽  
Eastern Austria

Schmidt-hammer rebound values ( R-values) enable relative-age dating of landforms, with R-values relating to degree of weathering and therefore length of exposure. This method – recently termed as Schmidt-hammer exposure-age dating (SHD) – was applied to date five rock glaciers (size range, 0.01–0.12 km2) and one recent rockfall deposit at the study area Schöderkogel-Eisenhut, in the Schladminger Tauern Range (14°03′E, 47°15′N), Austria. The rock glaciers consist of gneiss or high metamorphic series of mica-schist that are comparable in their R-values. Four of them are relict (permafrost absent) and one is intact (containing patches of permafrost). On each of the five rock glaciers, SHD was carried out at 4–6 sites (50 measurements per site) along a longitudinal transect from the frontal ridge to the root zone. Results at all five rock glaciers are generally consistent with each other sharing statistically significant R-values along transects. The range between the highest and the lowest mean R-value at each of the five rock glaciers is 9.9–5.2. Using rock glacier length and surface velocity data from nearby sites, the rock glacier development must have lasted for several thousand years. Furthermore, by using SHD results from rock glaciers of known age from other sites in the region with comparable geology, approximate surface ages of 6.7–11.4 ka were estimated. This indicates long formation periods for all five rock glaciers. Our results suggest that many of the 1300 relict rock glaciers in central and eastern Austria were formed over a long period during the Lateglacial and Holocene period.

Reconstruction of the dynamics and origin of rock glaciers in an Alpine environment

2021 ◽  
Author(s):  
Benjamin Lehmann ◽  
Robert S. Anderson ◽  
Xavier Bodin ◽  
Pierre G. Valla ◽  
Julien Carcaillet
Keyword(s):  
Remote Sensing ◽  
Time Scales ◽  
Surface Velocity ◽  
Rock Glacier ◽  
Alpine Environment ◽  
Mountain Ranges ◽  
Long Time ◽  
Rock Glaciers ◽  
Alpine Environments ◽  
Alpine Valleys

<p>Rock glaciers are one of the most frequent cryospheric landform in mid-latitude mountain ranges. They influence the evolution of alpine environments on short (years to decades) and long (centuries to millennia) time scales. As a visible expression of mountain permafrost [1] as well as an important water reserve in the form of ground ice [2], rock glaciers are seen as increasingly important in the evolution of geomorphology and hydrology of mountain systems in the context of climate change and deglaciation [3, 4]. On longer time scales, rock glaciers transport boulders produced by the erosion of the headwall upstream and downstream and therefore participate in shaping mountain slopes [5]. Despite their importance, the dynamics and origin of rock glaciers are poorly understood.</p><p>In this study, we propose to address two questions:</p><p>1) How does the dynamics of rock glaciers change over time?</p><p>2) What is the origin of rock glaciers and what is their influence on the evolution of alpine environments?</p><p>These two questions require an evaluation of the surface velocity field of rock glaciers by relating short and long time scales. To solve this problem, we combine complementary methods including remote sensing, geochronology with a mechanical model of rock glacier dynamics. We apply this approach to the rock glacier complex of the Vallon de la Route in the Massif du Combeynot (French alps).</p><p>In order to reconstruct the displacement field of the rock glacier on modern time scales, we used remote sensing methods (i.e., image correlation and InSAR). Over longer periods (10<sup>3</sup> to 10<sup>4</sup> years), we used cosmogenic terrestrial nuclides (TCN) dating. By applying this methodology to boulder surfaces at different positions along the central flow line of the rock glacier, from the headwall to its terminus, we will be able to convert the exposure ages into surface displacement. The use of dynamic modelling of rock glaciers [6] will allow us to relate the surface kinematics to short to long time scales. It will then be possible to discuss the age, origin of rock glaciers and how topo-climatic and geomorphological processes control their evolution in Alpine environment.</p><p> </p><p>[1] Barsch, D.: Rockglaciers. Indicators for the Present and Former Geoecology in High Mountain Environments, Springer series in physical environment vol. 16, Springer, Berlin, Heidelberg, 1996.</p><p>[2] Jones, D. B., Harrison, S., Anderson, K., and Whalley, W. B.: Rock glaciers and mountain hydrology: A review, Earth-Sci Rev, 193, 66–90, 2019.</p><p>[3] Haeberli, W., Schaub, Y., and Huggel, C.: Increasing risks related to landslides from degrading permafrost into new lakes in deglaciating mountain ranges, Geomorphology, 293, 405–417, 2017.</p><p>[4] Knight, J., Harrison, S., and Jones, D. B.: Rock glaciers and the geomorphological evolution of deglacierizing mountains, Geomorphology, 324, 14–24, 2019.</p><p>[5] MacGregor, K.R., Anderson, R.S., Waddington, E.D.: Numerical modeling of glacial erosion and headwall processes in alpine valleys. Geomorphology 103 (2):189–204, 2009.</p><p>[6] Anderson, R. S., Anderson, L. S., Armstrong, W. H., Rossi, M. W., & Crump, S. E.: Glaciation of alpine valleys: The glacier–debris-covered glacier–rock glacier continuum. Geomorphology, 311, 127-142, 2018.</p>

Inventory of active rock glaciers in the western Nyainqêntanglha Range, Tibetan Plateau

2021 ◽  
Author(s):  
Eike Reinosch ◽  
Markus Gerke ◽  
Björn Riedel ◽  
Antje Schwalb ◽  
Qinghua Ye ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
High Reliability ◽  
Surface Velocity ◽  
Windward Side ◽  
Mountain Range ◽  
The Tibetan Plateau ◽  
Automated Classification ◽  
Rock Glacier ◽  
North West ◽  
Rock Glaciers

<p>The western Nyainqêntanglha Range on the Tibetan Plateau (TP) reaches an elevation of 7162 m and is characterized by an extensive periglacial environment. Here, we present the first rock glacier inventory of the central TP containing 1433 rock glaciers over an area of 4622 km². The rock glaciers are identified based on their surface velocity. The surface velocity is derived from Sentinel-1 satellite data of 2016 to 2019 via InSAR time series analysis. 16.4 % of the inventoried rock glaciers are classified as active with a surface velocity above 10 cmyr<sup>-1</sup> and 80.0 % are classified as transitional with 1 to 10 cmyr<sup>-1</sup>. The western Nyainqêntanglha Range forms a climate divide between the dry continental climate brought by the Westerlies from the north-west and the Indian Summer Monsoon to the south. 89.7 % of all active rock glaciers and 74 % of the free ice glacial area are located on the southern side. The higher moisture availability on the southern (windward) side of the mountain range is likely the cause of a higher rock glacier occurrence and the greater activity.</p><p>Manually identifying and outlining rock glaciers is time consuming and subjective. To ensure a high reliability and comparability of our inventory, we therefore combined a manual approach with an automated classification. Three analysts worked in tandem to generate the manual outlines according to the guidelines of the IPA action group on ‘Rock glacier inventories and kinematics’. A subset of these outlines acted as training areas for a pixel-based maximum likelihood classification. Both the manual and the automated classification were performed based on DEM parameters (elevation, slope etc.), optical datasets (Sentinel-2 and NDVI) and surface velocity (generated with InSAR). 87.8 % of all manually outlined rock glaciers were identified successfully at a true positive rate of 69.5 %. 18 additional rock glaciers were added to the inventory based on the automated classification. This combined approach is therefore beneficial to generate a complete inventory. The automated classification can, however, not replace the expertise of an analyst as it greatly overestimates the actual rock glacier area.</p>

scholarly journals Surface velocity fields of active rock glaciers and ice‐debris complexes in the Central Andes of Argentina

2020 ◽  
Author(s):  
Jan Henrik Blöthe ◽  
Christian Halla ◽  
Ellen Schwalbe ◽  
Estefania Bottegal ◽  
Dario Trombotto Liaudat ◽  
...  
Keyword(s):  
Central Andes ◽  
Velocity Fields ◽  
Surface Velocity ◽  
Rock Glaciers

An Estimation of Past and Present Air Temperature Conditions, Water Equivalent, and Surface Velocity of Rock Glaciers in Cordillera Volcanica, Peru

2021 ◽  
Author(s):  
Edwin Badillo-Rivera ◽  
Edwin Loarte ◽  
Katy Medina ◽  
Xavier Bodin ◽  
Guillermo Azócar ◽  
...  
Keyword(s):  
Air Temperature ◽  
Surface Velocity ◽  
Temperature Conditions ◽  
Rock Glaciers

Modeling Vibration-Induced Tire-Pavement Interaction Noise in the Mid-frequency Range

2020 ◽  
Author(s):  
Sterling McBride ◽  
Ricardo Burdisso ◽  
Corina Sandu
Keyword(s):  
Sound Intensity ◽  
Element Model ◽  
Dominant Frequency ◽  
Contact Forces ◽  
Surface Velocity ◽  
New Wave ◽  
Normal Surface ◽  
Radiated Noise ◽  
Physical Effects ◽  
Effects Of Rotation

ABSTRACT Tire-pavement interaction noise (TPIN) is one of the main sources of exterior noise produced by vehicles traveling at greater than 50 kph. The dominant frequency content is typically within 500–1500 Hz. Structural tire vibrations are among the principal TPIN mechanisms. In this work, the structure of the tire is modeled and a new wave propagation solution to find its response is proposed. Multiple physical effects are accounted for in the formulation. In an effort to analyze the effects of curvature, a flat plate and a cylindrical shell model are presented. Orthotropic and nonuniform structural properties along the tire's transversal direction are included to account for differences between its sidewalls and belt. Finally, the effects of rotation and inflation pressure are also included in the formulation. Modeled frequency response functions are analyzed and validated. In addition, a new frequency-domain formulation is presented for the computation of input tread pattern contact forces. Finally, the rolling tire's normal surface velocity response is coupled with a boundary element model to demonstrate the radiated noise at the leading and trailing edge locations. These results are then compared with experimental data measured with an on-board sound intensity system.

Combining SAR interferometry and the equation of continuity to estimate the three-dimensional glacier surface-velocity vector

1999 ◽  
Vol 45 (151) ◽  
pp. 533-538 ◽  
Author(s):  
Niels Reeh ◽  
Søren Nørvang Madsen ◽  
Johan Jakob Mohr
Keyword(s):  
Steady State ◽  
Mass Balance ◽  
Vertical Velocity ◽  
Velocity Vector ◽  
Thickness Distribution ◽  
Vertical Surface ◽  
Horizontal Velocity ◽  
Sar Interferometry ◽  
Surface Velocity ◽  
Ice Thickness

AbstractUntil now, an assumption of surface-parallel glacier flow has been used to express the vertical velocity component in terms of the horizontal velocity vector, permitting all three velocity components to be determined from synthetic aperture radar interferometry. We discuss this assumption, which neglects the influence of the local mass balance and a possible contribution to the vertical velocity arising if the glacier is not in steady state. We find that the mass-balance contribution to the vertical surface velocity is not always negligible as compared to the surface-slope contribution. Moreover, the vertical velocity contribution arising if the ice sheet is not in steady state can be significant. We apply the principle of mass conservation to derive an equation relating the vertical surface velocity to the horizontal velocity vector. This equation, valid for both steady-state and non-steady-state conditions, depends on the ice-thickness distribution. Replacing the surface-parallel-flow assumption with a correct relationship between the surface velocity components requires knowledge of additional quantities such as surface mass balance or ice thickness.

Sign in / Sign up

Export Citation Format

Share Document