Ablation on debris covered glaciers

Transcrição

Ablation on debris covered
glaciers:
Basic research on the impact of debris
cover on melt processes and their
modelling
Doctoral Thesis
in Meteorology
Submitted to the
Faculty of Geo- and Atmospheric Sciences
of the
University of Innsbruck
in Partial Fulfillment of the Requirements for the Degree of
Doctor rerum naturalium
by
Mag. rer. nat. Martin Juen
Advisors
Dr. Christoph Mayer
Dr. Michael Kuhn
München, November 2013
To Florian
”. . . to be a doer you have to be a dreamer in the first place.”
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Abstract
This thesis focuses on the impacts of debris cover on ablation. To find out how
lithology and grain size influence subdebris ice ablation, it appeared reasonable to
establish test plots with different debris grain sizes and debris thicknesses consisting
of different natural material. The observations on a test site on the Vernagtferner
revealed a clear dependence of the subdebris ice melt on the layer thickness, grain
size, porosity and moisture content. Ablation, debris internal temperature and meteorological parameters were monitored. Highly porous volcanic material protected
the ice much more effectively from melting than similar layer thicknesses of the local mica schist. However, the analysis of thermal diffusivities demonstrated that a
vertical moisture gradient is present during ablation conditions especially close to
the layer interfaces. The potential of remote sensing-based surface classification on
debris covered glaciers using thermal infrared images was investigated at the same
location utilizing a numerical surface energy balance model. A thermal infrared
camera allowed us to capture the surface temperature of the individual plots and
enables us to draw conclusions about the effects of different grain sizes on the surface temperature. It turns out that the distinction between debris covered ice and
periglacial moraine material is restricted with current remote sensing applications.
To quantify the ablation processes on a debris covered glacier, a simple distributed
ablation model has been developed and applied to the Koxkar glacier in the Central
Tien Shan. Extensive field work was carried out during the ablation season 2010 to
collect the required data. To map and classify melt-relevant surface types, remote
sensing techniques using high resolution satellite imagery, were applied to capture
the areal distribution of topographic features, that influence debris thickness and
consequently ablation. The model allows the estimation of ablation on a debris covered glacier by combining field data and remote sensing information. The subdebris
ice ablation accounts for about 19% of the entire ice ablation, while the percentage
of the moraine covered area accounts for approximately 32% of the entire glacerized
area. Although the ice cliffs occupy less than 2% of the debris covered area, the melt
on them accounts for approximately 15% of the total subdebris ablation and 2.7%
of the total ablation respectively. The comparison of total ablation amount from
an imaginary debris free and a debris covered glacier highlights the importance to
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include debris cover into discharge modelling. The results demonstrate that debris
cover has a major impact on the response of the glacier terminus to climate warming
and it must be taken into account for predictions of fresh water availability and sea
level rise.
Zusammenfassung
In der vorliegenden Arbeit werden die Auswirkungen einer supraglazialen Schuttbedeckung auf die Ablation von Gletschern untersucht. Um herauszufinden wie
Lithologie und Korngröße die Schmelze beeinflussen, wurden Testflächen mit verschiedenen Schuttdicken auf der Zunge des Vernagtferners eingerichtet. Die verwendeten Testflächen bestanden aus natürlichem Material. Die Beobachtungen
auf dem Testgelände zeigten eine deutliche Abhängigkeit der Schmelze von den
Schuttdicken, der Korngröße, der Porosität und dem Feuchtigkeitsgehalt. Die Ablation, schuttinterne Temperaturen und meteorologische Parameter wurden gemessen.
Die Analyse der Wärmeleitfähigkeiten zeigt, dass hochporöse vulkanische Materialien das Eis besser vor dem Schmelzen schützen, als vergleichbare Schichtdicken des
lokalen Glimmerschiefers. Die Untersuchung der Temperaturleitfähigkeiten zeigt,
dass besonders an der Grenzfläche von Schutt zu Eis ein vertikaler Feuchtigkeitsgradient vorherrscht. Die fernerkundungsbasierte Oberflächenklassifizierung von
schuttbedeckten Gletschern mittels thermischen Infrarotbildern wurde an derselben Testfläche unter Verwendung eines numerischen Energiebilanzmodells untersucht. Eine thermische Infrarot-Kamera registrierte die Oberflächentemperaturen
der einzelnen Schuttparzellen. Die Auswertung erlaubt Rückschlüsse auf die
Auswirkungen der verschiedenen Korngrößen auf die Oberflächentemperatur. Es
stellte sich heraus, dass die Unterscheidung zwischen schuttbedecktem Eis und
periglazialem Moränenmaterial mit aktuellen Methoden der Fernerkundung begrenzt ist. Um die Ablationsprozesse auf einem schuttbedeckten Gletscher zu quantifizieren, wurde ein einfaches, räumlich verteiltes Ablationsmodell entwickelt und
auf dem Koxkar Gletscher im zentralen Tien Shan angewandt. Es wurden umfangreiche Feldarbeiten während der Ablationssaison 2010 durchgeführt, um die
für das Modell erforderlichen Daten zu sammeln. Zudem wurden hochaufgelöste
Satellitenbilder verwendet, um die räumliche Verteilung der schmelzrelevanten
Oberflächenklassen zu kartieren. Das Modell erlaubt die Berechnung der Schmelze
auf einem schuttbedeckten Gletscher durch die Kombination von vor Ort gemessenen Ablationsdaten und Fernerkundungsinformationen. Auf die bedeckte Ablation entfallen rund 19% der gesamten Schmelze, während der Anteil der schuttbedeckten Fläche etwa 32% der gesamten Gletscherfläche ausmacht. Obwohl die
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Eisklippen weniger als 2% der schuttbedeckten Fläche einnehmen, sind sie für etwa
15% der bedeckten Ablation und 2,7% der Gesamtablation verantwortlich. Der
starke Einfluss der Schuttbedeckung wird klar, sobald die Ablation mit einem imaginären schuttfreien Gletscher verglichen wird. Diese Ergebnisse unterstreichen die
Notwendigkeit, die bedeckte Ablation in Abflussmodellierungen und somit die Prognosen von Frischwasserverfügbarkeit und Meeresspiegelanstieg zu integrieren.
Contents
Abstract
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Zusammenfassung
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Contents
ix
1 Introduction
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 State of Research . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1 The influence of debris cover on the ablation of glaciers . . .
1.2.2 Assessing debris covered glaciers by means of thermal remote
sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.3 The role of ice cliffs and supraglacial lakes on debris covered
glaciers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.4 Modelling runoff from debris covered glaciers . . . . . . . . .
1.3 Goals and Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3.1 Framework of the thesis . . . . . . . . . . . . . . . . . . . .
1.3.2 Research questions . . . . . . . . . . . . . . . . . . . . . . .
1.3.3 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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2 Paper I
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3 Paper II
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4 Poster I
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5 Paper III
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6 Conclusions and Outlook
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A Visual fieldwork impressions
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Bibliography
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CONTENTS
Acknowledgments
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Curriculum Vitae
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List of presentations
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Chapter 1
Introduction
1.1
Motivation
Numerous glaciers in the world’s largest mountain regions are characterized by
layers of debris-like material (dust, sand, rocks, volcanic ash) on their surface.
Debris covered glaciers are defined by the presence of a supraglacial debris mantle
in the ablation zones that can originate from various sources, such as thrusting of
subglacial material, melt-out of englacial debris bands, channel fill material, rockfall
from mountain sides and meltwater bursts through the crevasse and conduit system
or aeolian deposition directly on the glacier surface (Schomacker 2008). Retreating
mountain glaciers are one of the most compelling examples of recent climate change
(Dyurgerov and Meier 2005). The associated retreat of the ice masses and the
increased thawing of permafrost ensure that the surrounding mountain slopes
can become increasingly instable and an increasing area of glacier surfaces are
covered with debris and sediments. Furthermore, decreasing ice flow velocities
combined with increasing ablation rates result in an increase in supraglacial debris
from englacial melt out (Kellerer-Pirklbauer 2008). In remote areas like the
Karakorum, the Himalaya, the Tien Shan or the Andes, melt water is an important
component of the water cycle and especially if a river flows into an arid area the
fresh water supply from glaciers is essential for agricultural planning and food
security (e.g. Kaser et al. 2010). As a result, debris-covered glaciers represent a
current challenge for the assessment of water resources from glacial melt (Shukla
et al. 2010). Oerlemans (2005) investigated changes in glacier lengths for different
parts of the world and showed that moderate global warming started in the middle
of the 19th century. Retreating glaciers fronts are good visible indicators for
rising temperatures, but the response of debris covered glaciers to climate change
differs from the behavior of bare ice glaciers. Several authors state that instead
of retreating in length during years of negative massbalance, the position of the
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2
Introduction
terminus of debris covered glaciers remains stable while the moraine covered parts
of the glacier react by downwasting (Bolch et al. 2008; Scherler et al. 2011; Sorg
et al. 2012; Benn et al. 2012).
Debris covered glaciers are a prominent feature in high relief mountain ranges
around the world and the number of debris-covered areas is increasing (Fig. 1.1).
Figure 1.1: Diagram explaining the causes of the increasing number of debris covered
areas.
Therefore the influence of debris cover on subdebris melt rates represents a challenge when future fresh water availability and global sea level change are predicted
by models. This can only be achieved by more massbalance studies from heavily
debris covered glaciers and the inclusion of debris cover in glacier inventories, which
are currently all missing (Scherler et al. 2011).
1.2 State of Research
1.2
1.2.1
3
State of Research
The influence of debris cover on the ablation of
glaciers
Østrem (1959) provided the fundamental contribution to the understanding of
the effects of moraine cover on melting ice underneath. He observed that some
of the moraine ridges in the Tarfala valley apparently were ice-cored. As the ice
melted in the upper part, the debris material started to slide down, protecting the
lower part of the ice core from further melting. Therefore he decided to conduct a
melt experiment. He placed sand and gravel on the bare ice surface and measured
the ablation by means of bamboo stakes. It became evident, that the melt rates
decreased when the cover had a certain thickness compared to the clean ice case.
Østrem (1959) also showed that under thin layers the melting speed accelerated
(Fig. 1.2).
Figure 1.2: Relationship between debris cover thickness and melt rates. (a) Fundamental
results of the experiment from Østrem (1959). (b) Examples of empirical measurements
from various authors summarized from Mattson et al. (1993) and redrawn from Nicholson
and Benn (2006). (1) Thickness where maximum subdebris melt occurs. (2) Critical
thickness where bare ice ablation is equal to subdebris ablation.
Because of their different albedo, debris layers or single grains absorb more heat
than bare ice. The heat energy is transfered into the underlying ice causing enhanced
melt rates. Although the albedo effect is also present for thicker moraine covers,
the shielding impact of debris cover dominates when exceeding a critical thickness,
where melt rates are equal to bare ice. Mattson et al. (1993) conducted ablation
experiments on the Rakhiot Glacier (Punjab, Himalaya) and compared their results
with previous research in other regions (see Fig. 1.2). He pointed out that the pro-
4
Introduction
cesses responsible for ablation on debris covered glaciers remain the same no matter
where the glacier is located. But also the radiation cycle variability has an impact on
the critical thickness, where values decrease with increasing latitude and increasing
elevation (Reznichenko et al. 2010).
Kraus (1966) highlighted the physical processes involved and presented a comprehensive energy balance model to estimate melt rates from debris free and debris
covered ice surfaces. He investigated the dependence of ablation on individual meteorological factors as well as the heat transmission coefficient of the moraine material.
Consequently he provided diagrams that document the relationship of ablation to
global radiation, downward terrestrial radiation, air temperature, relative humidity
and wind speed.
Nakawo and Young (1981) carried out field experiments at Peyto Glacier (Rocky
Mountains, Alberta, Canada - 51.67◦ N, 116.54◦ W) and developed a more simple
but practical method by which ablation under a layer of debris could be estimated
from meteorological variables even if the thermal conductivity of the material was
unknown. They distinguished between wet and dry debris surfaces and proposed to
determine the surface temperature of a debris layer over a wide area by means of
remote sensing. Hence the thermal resistance and the ablation rate under a debris
layer could be estimated from external variables only.
A number of studies concentrated on the energy balance at the debris cover surface
(e.g. Nicholson and Benn 2006). The numerically reconstructed surface temperature
from daily mean meteorological variables is used to determine the heat conduction
through the debris cover in dependence of its thermal properties and thickness. Melt
rates beneath debris layers of arbitrary thickness can be calculated based on the assumptions that (1) daily mean temperature gradients within the debris are linear
and (2) there is negligible net change in heat storage on diurnal timescales.
Brock et al. (2010) investigated the various meteorological factors and quantified
surface energy fluxes on the debris covered Miage Glacier (Mont Blanc Massif, Italian Alps - 45.78◦ N,6.86◦ E) over three ablation seasons. The analysis of the results
showed that subdebris ice melt rates are fairly insensitive to atmospheric temperature variations in contrast to debris free glaciers and that improved knowledge of
spatial patterns of debris thickness distribution and air temperature are needed for
distributed, physically based melt modeling of debris covered glaciers.
Reid and Brock (2010) presented an improved model that considers the atmospheric
stability of the surface layer and the heat flux due to precipitation, validated with
data collected at Miage Glacier and the tephra-covered glacier on Villarrica volcano,
Chile (39.42◦ S,71.94◦ W). Their model allowed a thorough statistical analysis of different aspects of energy balance at a debris surface and was able to reproduce the
Østrem-curve (Fig. 1.2). For example, it indicated that the heat flux from precipi-
5
tation is negligible for alpine glaciers, and that latent heat can be omitted without
large losses in model performance. A lot of effort has been put into finding the most
important processes for good model performance. They identified air temperature
and incoming shortwave radiation as the key input variables and proposed to develop simpler, empirical models for practical applications (e.g. as a component in
large scale hydrological catchment models) based around those variables.
Nicholson and Benn (2013) measured temperature profiles in debris of different
grain size on the Ngozumpa glacier in Nepal over an annual cycle. They analyzed
the thermal properties of the debris layer and the processes involved with respect to
seasonal variability. Water content has a pronounced effect on the thermal conductivity, which is generally 30% higher during summer than in winter. Furthermore
they showed that using a probability density function represents the debris thickness
distribution better than a down-glacier trend of increasing thickness.
Admittedly a large number of debris covered glaciers are located in remote areas,
where data sets of meteorological variables are rare, because these measurements are
time-consuming and cost-intensive. A very simple, but for many applications sufficiently accurate technique to estimate melt rates is the temperature-index method.
It bases on an empirical relation between the sum of daily mean temperatures above
melting point and ablation, so it can be seen as a simplification of the energy balance approach (Braithwaite 1995). This method has been used for research on alpine
glaciers since the 19th century (Finsterwalder and Schunk 1887). Since then, this
technique has been further improved and represents one of the most widely used
approaches for calculating snow and ice melt (Hock 2003).
1.2.2
Assessing debris covered glaciers by means of thermal
remote sensing
Because the fluctuation of mountain glaciers is recognized as a high-confidence indicator of air-temperature trends, the exact mapping, monitoring and inventorying of
glaciers at a global scale is essential for documenting climate change (Haeberli et al.
2000). Especially in remote and inaccessible regions, extensive and cost-effective
studies can be carried out by means of remote sensing. Furthermore, the detection
of the areal distribution of debris thickness is a crucial parameter in the runoff calculation and prediction of glacier response to climatic changes (Bozhinskiy et al. 1986).
Due to the visual similarity of supraglacial debris and the surrounding moraine material, fluvioglacial deposits and bedrock, automated glacier mapping from satellite
multispectral image data is particularly difficult (Paul et al. 2004; Shukla et al.
2010).
Lougeay (1974) stated that thermal remote sensing systems should be capable at
6
Introduction
detecting buried glacial ice and distinguishing between various ice-cored geomorphic
features. Ground level observations have shown that surface temperature, and thus
the emitted terrestrial radiation, is closely correlated to the thickness of the debris
mantle which covers an ice core. His theory is based on the fact, that a debris covered ice surface will have a lower surface temperatures than a non-ice-cored surface
if the lithology and therefore the emissivity are the same.
Nakawo et al. (1993) utilized satellite data (MESSR data of MOS-1 and Thematic
Mapper data of LANDSAT) to identify areas of either snow, bare ice or debris on
Khumbu Glacier (Himalaya, Nepal). In addition the areas of granitic debris and
schistose debris could be differentiated. The paper described briefly an outline for
estimating ablation under supraglacial debris with the aid of satellite data. Although he asserted that for obtaining thermal properties of the debris additional
information on meteorological variables would be required.
Paul et al. (2004) presented a semi-automatic method for delineation of debris covered glaciers, which combines multispectral image classification (glacier ice, vegetation) with digital elevation model (DEM) data (slope), neighbourhood analysis
(connection to glacier ice), and change detection. For creating glacier inventories
this method is much faster than manual delineation alone, even if the final manual
editing is considered.
Mihalcea et al. (2008a) showed that maps representing the spatial distribution and
thickness of the debris cover can be derived from Advanced Spaceborne Thermal
Emission and Reflection Radiometer (ASTER) surface temperature data on the
Miage Glacier. This was achieved utilizing empirical surface temperature – thickness relationships with respect to 100 m elevation bands. The study of Mihalcea
et al. (2008b) aimed primarily at analyzing the influence of debris thickness on the
melt distribution, at Baltoro glacier (Karakoram, Pakistan). Remote sensing, field
measurements and meteorological data recorded at a station near the glacier were
combined to determine subdebris ablation using a distributed surface energy balance
model.
Foster et al. (2012) developed a physically based model to calculate debris thickness
from thermal bands of ASTER satellite thermal band imagery in combination with
reanalysis meteorological input data. This method is based on the solution of the
energy balance equation at the debris surface to determine moraine thickness as a
residual parameter at each pixel of the underlying image.
1.2.3
7
The role of ice cliffs and supraglacial lakes on debris
covered glaciers
Ice cliffs and supraglacial lakes are common features of debris covered glaciers all
over the world. The exposed areas of steeply inclined ice are normally covered with
a very thin layer of dust or sand, leading to higher absorption of shortwave radiation
due to the low albedo compared to clean ice.
Supraglacial ponds are features that are a result of the differential ablation that
occurs on debris covered glaciers. They tend to form in depressions and can
drain in various kinds. Meltwater lakes on the surface or at the end of a glacier
(proglacial lakes) are particularly important because they represent a potential risk
for glacial lake outburst floods (GLOFs). The threat of downstream damage and
life-endangering effects on the population living there, encouraged numerous scientists to conduct research in those areas (Ives et al. 2010).
Inoue and Yoshida (1980) studied the role of supraglacial debris on the ablation of
the Khumbu Glacier based on observational data. They measured melting rates of
ice cliffs and pointed out that these surface features play an important role for the
total ablation. Ice cliffs are widely recognized as spots of enhanced melting (Sakai
et al. 2002, 2000).
Sakai et al. (2000) examined the heat balance at the water surface of a supraglacial
pond, the pond heat balance, and the consequent effect on ice ablation. They stated
that supraglacial lakes produce internal ablation in the conduit system that lead to
a positive feedback process, accelerating the ablation rate of debris covered glaciers.
Caused by the collapse of water channels, new ice cliffs and ponds can be created.
Sakai et al. (2002) described the orientation and distribution of ice cliffs on the
Lirung Glacier in Langtang Valley (Nepal, Himalaya). Field observation showed
that south-facing cliffs were small in area because they had low slope angles and
tended to be covered with debris, while north-facing cliffs were large in area and
maintain a slope angle larger than the angle of repose of the debris. The difference
in slope at alternatively oriented ice cliffs can be explained by the variation in local
radiation between the upper and lower portion of the ice cliff.
Reynolds (2000) showed that the surface gradient of a debris mantled glacier is the
controlling factor on the formation and abidance of supraglacial ponds. He proposed
that identifying areas with a surface gradient of less than 2◦ on glaciers with a negative massbalance should make it possible to forecast the formation of large volumes
of water, that may later prove to be potentially dangerous.
Benn et al. (2001) presented a qualitative model of supraglacial lake evolution based
on field observations on the Ngozumpa Glacier (Himalaya, Nepal). They identified
subaerial melting, water-line melting (also called thermo-erosional notching) and
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Introduction
calving as mechanisms that contribute to ice ablation and therefore lake growth.
Röhl (2008) investigated the characteristics and development of supraglacial ponds
on Tasman Glacier (New Zealand) with regard to terminus disintegration. She distinguished three types of supraglacial ponds: (1) Perched ponds that lie above the
level of the englacial drainage system and have a limited contribution to ice loss and
may disappear, (2) ponds that are hydraulically connected to the main drainage
system and (3) ponds which constitute an active part of the drainage system and
feature noticeable currents with flow velocities. Pond development in the earlier
stages occurs predominantly in the horizontal dimension by subaerial melt. Thereafter subaqueous calving plays a central role in the evolution by exposing bare ice.
The transition from melting to calving may be initiated by enhanced water temperatures and currents in deeper and larger ponds.
Sakai et al. (2009) found that calving at supraglacial lakes occurs at ponds exceeding a certain size by thermal undercutting when the water temperature is within a
given range. This happens due to the fact that the annual subaqueous ice cliff melt
becomes larger than the supraaqueous ice cliff melt due to development of valley
wind driven water current. The authors suggested, that also small supraglacial lakes
should be examined in the future, since they have the potential to expand rapidly.
Benn et al. (2012) used observations of glaciers in the Mount Everest region to
present an integrated view of debris covered glacier response to climate change.
They monitored the evolution of debris covered glaciers, and lakes in particular,
during periods of negative mass balance. A general conceptual model is introduced
which describes the development of a dynamically active moraine covered glacier to a
glacier with a potentially unstable moraine dammed lake. The transitional period is
characterized by high rates of downwasting in the mid-ablation zone. Consequently
the glacier surface gradient is reduced, introducing favourable conditions for the
formation of supraglacial lakes. When a continuous moraine-dam is present in the
terminus region, large base-level lakes can develop, entailing the risk of GLOFs.
Xin et al. (2012) surveyed the thermal regime of a supraglacial lake on the Koxkar
glacier in the Central Tien Shan (Fig. A.4). Their analysis revealed that changing
daily weather conditions affected the surface water temperature but had little effect
on the temperature of the supraglacial lake at a depth of 5 m. Additionally it was
found that meltwater from the glacier surface at temperatures of around 0◦ C feeds
the lake and mixes with the relatively high-temperature surface water during the
course of a day. As a consequence the water temperature rises to approximately
4◦ C, sinks to the bottom of the pond and forms a low-temperature trough in the
middle of the day.
1.2.4
9
Modelling runoff from debris covered glaciers
The spatial distribution of debris thickness has a huge impact on ablation and
therefore should be integrated into calculating melt water production in runoff
models.
Braun et al. (1993) applied the HBV3-ETH conceptual precipitation – runoff model
in the glacierized basin of Langtang Khola (Himalaya, Nepal). They accounted for
the debris covered parts of the glaciers (over 7% of the total area) by introducing
a single reduction factor of glacier melt to the temperature driven model. After
model tests with no reduction and total suppression of melt, the new parameter
was set to 0.5, meaning that ablation over debris covered parts would be reduced
by half compared to the bare ice melt.
Rana et al. (1996, 1997) utilized a similar runoff model (HYCYMODEL) to
calculate daily runoff from basins located in the Langtang Valley (Himalaya,
Nepal). Surface temperature of the debris layer was estimated using Landsat 5 TM
data. The obtained average thermal properties of the debris material were applied
to the model. Again daily discharges for different basin conditions were compared:
(1) assuming the whole drainage basin is debris free, (2) assuming no melt from
the debris covered areas, and (3) with melt under the debris layer calculated with
the constant thermal resistance derived from the satellite data. The latter improved the modelled results and showed the best correlation with observed discharge.
10
Introduction
1.3
1.3.1
Goals and Outline
Framework of the thesis
This thesis is written in the framework of a project bundle supported by the Deutsche
Forschungsgemeinschaft. The bundle is titled: Climate Change and water resources
in western China. The main goal of the AKSU TARIM project bundle is the integrative assessment of the local to regional hydrological cycle including the atmospheric
components, the processes related to glaciers, snow cover and permafrost as well as
the river runoff at the southern slopes of the Tian Shan mountains. It consists of
four individual projects:
• AKSU TARIM-CLIM: The atmospheric component of the hydrological cycle
and the issue of anthropogenic climate change is addressed by a chain of global,
regional and local climate models, validated with post-processed observational
data.
• AKSU TARIM-MELT: Field and modelling studies at the scale of individual
glaciers are conducted to improve our knowledge of ablation and melt water
runoff by an extended ablation model.
• AKSU TARIM-CRYO: Detailed field studies with respect to permafrost and
active layer distribution and characteristics, and perennial snow fields as permafrost indicators are dedicated to assess the relevance of these important
components of the cryosphere to the overall hydrological cycle in the region.
• AKSU TARIM-RS: Based on remote sensing data the variability and changes
of the glacier extent in the entire Aksu catchment are studied. This includes
the period of direct satellite measurements since the 1960s and indirect witnesses of the glacier extent in former times by the detection of moraines from
space, describing the long-term behaviour of glaciers in the Tian Shan mountains since the Little Ice Age.
Although all four projects are strictly alone-standing, they are closely linked to each
other by harmonizing input and output data, regional and local focuses as well
as models and measurements. For example, the climate model data produced in
AKSU TARIM-CLIM are used as input parameters in the hydrological model in
AKSU TARIM-MELT.
In the following paragraph the project AKSU TARIM-MELT: Modelling of melt
and runoff in a basin with debris covered glacier parts in the upper Aksu catchment, northwest China, will be introduced in detail.
1.3 Goals and Outline
11
The aim is to improve our knowledge of ablation as a function of surface structures
on glaciers with and without debris cover by an extended ablation model. In addition, the resulting runoff for present-day and future conditions will be simulated
by a hydrological model. Therefore two PhD candidates, where one focuses on the
application and further development of a conceptual runoff model (Elisabeth Mayr)
and the other one is mainly responsible for the design of a distributed ablation model
(Martin Juen), were employed. By implementing the ablation model into the runoff
model, an improved version of the HBV-ETH model, capable to reproduce runoff
from moraine covered glaciers will be created.
1.3.2
Research questions
(1) How does lithology and grain size influence subdebris ice ablation? For this
question it appeared reasonable to establish test plots with different debris
grain sizes and debris thicknesses consisting of different natural material on a
test site at the Vernagtferner.
(2) What is the potential of remote sensing-based surface classification on debris covered glaciers using thermal infrared (TIR) images? The goal of the
investigation thus became trying to determine the amount of available heat
for subdebris ablation as a function of the complex meteorological boundary
conditions.
(3) Taking into account the multiple ablation processes on a debris covered glacier
(enhanced or reduced melt, ice cliffs, supraglacial lakes), can one quantify the
ablation on a debris covered glacier with the aid of a simple distributed ablation
model?
1.3.3
Outline
This doctoral thesis consists of three peer-reviewed papers and one poster presented
at an international conference.
Chapter 2 contains the paper: Thermal properties of a supraglacial debris
layer with respect to lithology and grain size. Different methods to estimate
the thermal properties of the debris matter are introduced. Thermal conductivity
and thermal diffusivity are investigated with the aid of a bundle of field measurements. Meteorological parameters, subdebris ablation and debris internal temperature were monitored on test plots consisting of natural sieved material. Three
different rock types were used: mica schist, which typifies the local metamorphic
type of rock; black, basaltic tephra of the Etna volcano (Italy); and grey, trachytic
pumice of the Sete Cidades volcano (Azores, Portugal). The various lithologies and
12
Introduction
grain sizes can be compared under identical meteorological conditions.
This is followed by chapter 3, where the paper: Surface debris classification
at Vernagtferner using temperature observations from a thermal camera
and radiation sensors, is presented. This study examines the applicability of remote sensing-based surface classification on glaciers using thermal infrared images.
For this purpose the surface temperatures and the heat flux of supraglacial debris
and periglacial moraine were determined using radiation sensors and a thermal infrared camera. A numerical surface energy balance model is introduced, to find out
if a thermal difference between ice cored and non ice cored surfaces exists.
In chapter 4 the following poster is introduced: Ablation and runoff generation
on debris covered Keqikar glacier in the upper Aksu catchment, China.
The poster was on display at the EGU General Assembly, April 2011, Vienna. The
field work during the ablation season 2010 conducted at the Koxkar glacier is presented. Several methods and results of the survey are illustrated.
Chapter 5 contains the paper: Impact of varying debris cover thickness on
catchment scale ablation: A case study for Koxkar glacier in the Tien
Shan. This study focuses on the effects of moraine cover on the ablation of an entire
glacier. Field measurements and remote sensing information provide the necessary
input data for a practically applicable method to quantify the ablation processes on
a debris covered glacier.
The conclusions are drawn in chapter 6.
Chapter 2
Paper I
Thermal properties of a supraglacial debris layer with respect to lithology and grain
size.
Juen, M., Mayer, C., Lambrecht, A., Wirbel, A. and Kueppers,U., 2013. Published
in: Geografiska Annaler: Series A, Physical Geography, 95, 197-209.
13
14
THERMAL PROPERTIES OF A SUPRAGLACIAL DEBRIS
LAYER WITH RESPECT TO LITHOLOGY AND
GRAIN SIZE
MARTIN JUEN1, CHRISTOPH MAYER1, ASTRID LAMBRECHT1,2, ANNA WIRBEL2 and
ULRICH KUEPPERS3
1
Commission for Geodesy and Glaciology, Bavarian Academy of Sciences, Munich, Germany
2
Institute of Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
3
Earth and Environmental Sciences, Ludwig-Maximilians-University Munich, Munich, Germany
Juen, M., Mayer, C., Lambrecht, A., Wirbel, A. and Kueppers, U., 2013. Thermal properties of a supraglacial debris
layer with respect to lithology and grain size. Geografiska
Annaler: Series A, Physical Geography, ••, ••–••.
doi:10.1111/geoa.12011
ABSTRACT. This paper focuses on the impacts of debris
cover on ice melt with regards to lithology and grain size.
Ten test plots were established with different debris grain
sizes and debris thicknesses consisting of different natural
material. For each plot, values of thermal conductivity were
determined. The observations revealed a clear dependence of
the sub-debris ice melt on the layer thickness, grain size,
porosity and moisture content. For the sand fraction the
moisture content played a dominant role. These test fields
were water saturated most of the time, resulting in an
increased thermal conductivity. Highly porous volcanic
material protected the ice much more effectively from
melting than similar layer thicknesses of the local mica
schist. However, the analysis of thermal diffusivities demonstrated that the vertical moisture distribution of the debris
cover must be taken into consideration, with the diffusivity
values being significantly lower in deeper layers.
Key words: supraglacial debris, ablation, debris-covered glaciers, thermal conductivity, thermal diffusivity, Vernagtferner, Austria
Introduction
Analysing the thermal properties of supraglacial
debris layers is important to understand the effects
of grain size and rock type on the sub-debris melt
rates. Supraglacial debris covers can originate from
various sources, such as thrusting of subglacial
material, melt-out of englacial debris bands,
channel fill material, rockfall from mountain sides
and meltwater bursts through the crevasse and
conduit system or Aeolian deposition directly on
the glacier surface (Schomacker 2008). Currently
many glaciers all over the world show negative
mass balances, due to global climate change
(Dyurgerov and Meier 2005). In combination with
increased thawing of permafrost, the deglaciated
slopes can become unstable and account for an
additional supply of the subaerial sediment onto
the glacier. Furthermore, decreasing ice flow
velocities combined with increasing ablation rates
result in an increase in supraglacial debris from
englacial melt out (Kellerer-Pirklbauer 2008).
Numerous studies concentrated on the empirical
relationship between debris cover thickness and
sub-debris ice melt rates since the fundamental
contribution of Østrem (1959). When solar radiation is present, very thin layers of debris or small
single grains absorb more heat than ice due to their
different albedo and specific heat capacity. The
transfer of this energy into the underlying ice
increases ablation rates. Thicker supraglacial
debris covers act as a protecting shield, which insulates the underlying ice and strongly reduces melt
rates (Østrem 1959). Even though the dependence
of melt rates on debris cover thickness has been
observed on various glaciers, the value for critical
thickness varies for each glacier and seems to be
controlled by the thermal properties of the debris
(Rana et al. 1998). Reznichenko et al. (2010)
showed that the critical thickness also decreases
with increasing latitude and increasing elevation
due to the radiation cycle variability. However, the
influence of rock type and grain size on the main
physical characteristics of a debris layer has not
been investigated in detail so far. Detailed knowledge about their role in the heat conduction
through the debris layer will improve the prediction of melt rates. Natural debris mantles usually
feature a mixture of grain sizes. Also different rock
© 2013 Swedish Society for Anthropology and Geography
DOI:10.1111/geoa.12011
1
15
16
Paper I
MARTIN JUEN ET AL.
types can be present on a single glacier. Commonly
coarser material can be found on the surface and
finer particles are present towards the debris–ice
interface. The sorting of melt-out debris occurs
through a variety of mechanisms due to rain, melt
water or redistribution while developing supraglacial channels, lakes or ice cliffs. Melt water percolation, where small grains migrate downwards
through channels between coarser grains, causes
segregation. Furthermore, supraglacial debris
undergoes in situ mechanical and chemical weathering which generates a large portion of fine material. Supraglacial rock avalanche deposits differ
from melt-out subglacial or englacial material
because the grain size composition is determined
by the fragmentation during deposition, leaving a
high proportion of very fine material and often a
boulder carapace (Reznichenko et al. 2011).
The aim of this paper is to contribute new
insights into the influence of different debris cover
parameters on the ice melt rate underneath. While
most previous studies concentrated on debris thickness vs. melt rates, this study focuses on the interactions between lithology and debris thermal
properties. In order to reduce the number of free
parameters, the experiments have been constricted
to grain size, layer thickness and rock type, providing specific information for otherwise identical
environmental conditions. We present experimental data and the quantitative results for ice ablation,
characterizing the thermal properties for different
combinations of the above mentioned parameters.
Debris thermal properties
The melt rate experienced at a sub-debris ice interface is determined by external or atmospheric and
debris internal factors. The total energy balance
determines how much energy is received by a
surface. The intensity of solar radiation is controlled by latitude, altitude, solar elevation angle,
orientation and inclination of the surface, while the
turbulent fluxes are dependent on wind speed,
atmospheric stability, surface roughness, as well as
temperature and water vapour pressure of the
ambient air. The specific debris properties, such as
thermal conductivity, thermal diffusivity, specific
heat capacity and albedo determine the actual heat
transport into and within the debris layer. The
albedo controls the fraction of solar radiation
absorbed at the surface and therefore how much of
the available energy is used to heat up the debris
surface. Not only does the surface type specify the
2
ratio of reflected to incident short-wave radiation,
but also the humidity of the debris surface (causing
a change of colour) and shadow effects. A higher
moisture content within the debris cover leads to
increased heat transfer by conduction, because the
pore spaces formerly occupied with air are then
filled with water, which has a higher thermal
conductivity.
Thermal conductivity
Ice only melts if the heat flux through the debris
cover is positive towards the ice surface and the ice
is at its melting point. The transport of heat can
occur by conduction, radiation or convection, with
or without latent heat transport. Heat conduction is
assumed to be the major physical process between
the near-surface and the deeper debris layers
(Conway and Rasmussen 2000). The conductive
heat flux Qc is proportional to the temperature gradient within the debris layer:
Qc = k
∂T
( W m −2 )
∂z
(1)
where the proportionality factor k (W m–1 K–1) is
the thermal conductivity, which is a measure of the
ability to transport heat through the medium (Oke
1987). If it is high, heat will be conducted easily
from the surface to the debris–ice interface, consequently causing higher melt rates.
Thermal diffusivity
The thermal diffusivity is a material property used
to describe the progressive change in the spatial
distribution of temperature by heat conduction. It
determines the temporal evolution of the temperature at a point inside the material when a temperature change occurs at the surface. Debris layers
with low diffusivities respond slower to a surface
temperature change than materials with high
thermal diffusivities. Assuming an isotropic debris
cover, the conductive heat transfer is described by
the one-dimensional heat diffusion equation:
∂T
∂ 2T
=κ 2
∂t
∂z
(2)
where T represents debris temperature, t is the
time, z is the depth in the debris profile and κ
(m2 s–1) is the thermal diffusivity of the layer. The
thermal diffusivity is directly proportional to the
thermal conductivity k:
17
THERMAL PROPERTIES OF A SUPRAGLACIAL DEBRIS LAYER WITH RESPECT TO LITHOLOGY AND GRAIN SIZE
Fig. 1. (a) Location of the test site on the middle tongue of the Vernagtferner and the location of the Vernagtferner in the Ötztal Alps,
Austria (b).
κ=
k
cd ρ d
(3)
where cd (J kg–1 K–1) is the specific heat capacity of
the debris cover and ρd (kg m–3) is the bulk density.
The thermal diffusivity is inversely proportional to
the amount of heat that is necessary to cause a
temperature change in the material.
Study area
The ablation experiments with artificial debris
cover were performed on the middle tongue of
Vernagtferner (10° 49' E, 46° 52' N), a temperate
glacier in the Ötztal Alps, Austria (Fig. 1). Situated
in the Central Alps, an inner-Alpine dry region, the
climatic conditions can be described as continental.
It is one of the most studied glaciers in the European Alps with a continuous mass balance series
from 1964 until now. The mean annual precipitation is about 1560 mm, the mean discharge
amounts to 1800 mm. Consequently, the glacier
has continuously been losing mass since the early
1980s (Escher-Vetter et al. 2005). The glacier
mostly shows a clean ice surface. Apart from some
very minor medial moraines and a rockfall that
occurred in 2012 no debris-covered areas are
present. The melt season is primarily from June to
September and a typical bare ice melt rate on the
tongue of Vernagtferner is roughly 0.06 m per day.
The location where the ablation experiment took
place is relatively flat but oriented towards South,
at an elevation of 2910 m a.s.l. close to the glacier
terminus.
Materials and methods
Field setup
The test field was established on 24 June 2010. To
enable the analysis of the influence of the specific
parameters grain size and rock type on ablation,
controlled conditions were established by using
sieved debris. Ten plots with varying debris thicknesses were prepared on the glacier surface, also
representing different grain sizes, all in the sand
and gravel fraction. Sub-debris melt rates and temperatures within the debris layer were monitored at
different depths. Furthermore stakes were placed in
bare ice and in a natural debris cover close by for
monitoring natural conditions. Three different rock
types were used: mica schist (MS), which typifies
the local metamorphic type of rock; black, basaltic
tephra (EB) of the Etna volcano (Italy); and grey,
trachytic pumice (SC) of the Sete Cidades volcano
(Azores, Portugal). The layer thicknesses ranged
between 0.025 and 0.18 m (±0.01 m). Using volcanic material next to local schist on the Vernagtferner enabled us to compare melt rates in identical
meteorological conditions and allows a direct comparison of supraglacial debris for varying material
properties (e.g. albedo, conductivity or porosity).
Table 1 and Fig. 2 provide a schematic overview of
the entire test site.
Ablation measurements
Each specific test field was equipped with a
wooden ablation stake, where the melt rates were
measured during the entire observation period. Ice
melt over a certain period was determined by meas3
18
Paper I
MARTIN JUEN ET AL.
Fig. 2. Experimental layout of the different debris plots on the tongue of the Vernagtferner. The large fields (plots 1–6) with local
material (MS) had a size of 1 × 1 m each. The fields with volcanic material (7–10) were about 50 × 50 cm in dimension.
4
19
Table 1. Experimental layout of the testfield.
Material
Mica schist (MS)
Basaltic tephra (EB)
Trachytic pumice (SC)
Basaltic tephra (EB)
a
Plot no.
Grain type
Grain size
(m)
Debris cover thickness
(m)
Thermistor depth
(m)
1
2
3
4
5
6
7
8
9
10
Fine sand MS
Coarse sand MS
Coarse gravel MS
Gravel MS
Coarse gravel MS
Gravel MS
Volcanic coarse EB
Volcanic coarse SC
Volcanic fine SC
Volcanic fine EB
0.001–0.002
0.002–0.003
0.03–0,05
0.02–0.03
0.03–0.05
0.02–0.03
0.0056–0.008
0.0056–0.008
0.001–0.002
0.001–0.002
0.04
0.055
0.045
0.030
0.18
0.08
0.04
0.025
0.025
0.02
0.01 and 0.03a
0.015 and 0.045a
0.035a
0.015a
0.07, 0.11a and 0.15
0.04, 0.06a and 0.08
0.015 and 0.03a
0.01 and 0.02a
0.01a
0.01a
Thermistors used for derivation of mean thermal conductivities.
Table 2. Sensor specifications thermistors.
Sensor
Debris temperature (°C)
Manufacturer and type
Accuracy according to the manufacturer
Gemini Tinytag TGP-4020 temperature logger
PB 5001 – standard thermistor probe
± 0.35°C at 0–70°C
uring the distance from the melting bare ice surface
or the debris cover surface to the top of the protruding stake using a standard measuring tape. The
error in the measured surface lowering (±0.01 m) is
included in the figures. Ablation monitoring took
place during the summer season 2010 with daily
observations from 25 June to 1 July (ablation
measured twice daily, in the morning as well as in
the afternoon) and 5–10 July 2010. Over these time
periods debris was controlled and repositioned
daily to maintain a constant thickness. During the
rest of the ablation season the field observations
were carried out on a less frequent basis. Ice ablation was measured at the plots with local material
(1–6) from the end of June until the middle of
September, whereas the volcanic test fields (7–10)
were only measured for one month (end of June to
end of July). In the course of the ablation season,
however, differential ablation led to considerable
geometrical distortions of the individual test fields.
At the end of July the test site geometries of the
volcanic fields were already strongly disturbed
with steep ice cones in the centre of each field. It
was therefore decided to abandon further observations of these fields. Due to the bigger plot size the
test fields with local material showed a less pronounced redistribution. Therefore the data up to 10
July 2010 could be used for determination of the
thermal properties.
Thermistor measurements
To obtain information about the debris internal
temperature distribution, thermistors were installed
at varying depths in the debris cover. Depending on
the thickness of the debris layer, one to three thermistors per plot were set up. In addition three thermistor probes have been installed in a vertical
profile in the glacier foreland close to the test site
to enable comparison with natural debris layer
conditions, not influenced by underlying ice. Temperatures were recorded by Gemini TinyTag,
battery-driven data loggers with external sensors
(Tables 1 and 2). The data were stored as 5 min
mean values. Constant inspection of thermistor
depths, carried out contemporaneously to the
debris thickness checks, was essential to obtain
robust temperature data. To determine the thermal
diffusivity of the debris layers by evaluating the
downward propagation characteristics of a temperature wave, the analysis of debris internal temperatures is focused on times with controlled
temperature probe depths during the periods
described in the previous section.
Meteorological measurements
An automatic weather station (AWS) was installed
to record meteorological data as 10 min mean
values. The AWS was situated close by on the bare
5
20
Paper I
MARTIN JUEN ET AL.
ice. Air temperature, relative humidity, precipitation, wind speed and wind direction were
monitored.
Determination of thermal conductivity
The bulk thermal conductivity of the debris layer
was estimated using a method described by
Mihalcea et al. (2006). It is based on the balance
between the flux of available energy for melt Qm
and the conductive heat flux Qc. This approach has
the big advantage that only measurements of melt
rates and surface temperatures are needed. Qm is
described by:
Qm = m L f ρi ( W m −2 )
(4)
where m is the melt rate (m s–1), Lf is the latent heat
of fusion (J kg–1) and ρi is the density of ice
(kg m–3). According to Kraus (1966), Qc can be
written as:
Qc = k
Ts − Ti
( W m −2 )
Δz
(5)
where Ts is the layer surface temperature, Ti is ice
temperature and Δz is the debris cover thickness. A
main assumption is that the temperature gradient
within the debris cover is linear for the period of
melt determination. Nicholson and Benn (2006)
have shown that the temperature gradient is linear
for a daily time scale. Instead of surface temperatures, the debris internal temperatures from the
uppermost thermistor have been used and the ice
temperature was assumed to be at the melting
point. Near surface internal debris temperatures
show much lower fluctuations and are therefore a
better indicator for determining the temperature
gradient than surface temperatures which are
directly influenced by air movement and convection. In addition, this method assumes that conduction is the only mechanism by which heat is
transported through the debris layer.
Determination of thermal diffusivity
Conway and Rasmussen (2000) proposed a method
to estimate the depth averaged thermal diffusivity κ
by using ∂T/∂t and ∂2T/∂z2 (Eqn 2). If both derivatives are plotted against each other, the gradient of
the best-fit line returns κ. The disadvantage of this
method is that a minimum of three temperature
measurements in regular depth intervals are needed
6
in order to determine the second derivative. Due to
the ideal positioning of the thermistors at plot 5 and
in the glacier foreland, these two locations have
been chosen for a comparison of thermal diffusivities. At plot 2 only two thermistors with irregular
spacing were installed, so the boundary value for
the temperature at the debris–ice interface has been
set to 273.16 K (melting conditions) and the measurements of one thermistor were interpolated in
order to meet the depth interval requirements. The
time period of observations for these calculations
has to be selected carefully because precipitation
for example would impede the use of this method
due to an additional heat source being introduced
to the system. As soon as the energy flux differs
from purely conductive conditions, the technique is
not valid anymore.
Another method to determine the thermal diffusivity was introduced by Ingersoll et al. (1948).
They addressed the problem of heat flow in one
dimension that takes place in a medium when the
boundary plane, normal to the direction of flow,
experiences simple periodic variations in temperature. The findings can be utilized to determine the
apparent thermal diffusivity. The method is based
on the assumption that soil temperatures oscillate
as a sinusoidal function of time around an average
value. Therefore the ground temperature TG can be
represented by a function of time by:
TG ( z0, t ) = T + T0 sin ω t
(6)
where T is the average soil temperature, T0 is the
amplitude of temperature fluctuation at the soil
surface and ω is the frequency defined as 2π/P with
P equal to the period of the fundamental cycle (e.g.
86 400 s for a diurnal period). An expression for
temperature variations as a function of time and
depth is given as a solution of the one-dimensional
heat diffusion equation:
T ( z, t ) = T + T0 e − z
ω 2κ
(
sin ω t − z ω 2κ
)
(7)
Due to the fact that the temperature amplitude
decreases exponentially, the ratio between two
temperature amplitudes measured at different
depths can then be used to infer the apparent
thermal diffusivity:
κ=
ω
[( z2 − z1 ) ln ( A1 A2 )]2
2
(8)
where A1 is the amplitude of the temperature fluctuation in Kelvin at depth z1 and A2 is the amplitude
21
at depth z2. The advantage of this method is that
only two thermistor measurements at different
depths are needed to obtain an estimate of the
apparent thermal diffusivity. Due to temporal variations of the boundary conditions (e.g. inhomogeneity of debris, wind and cloud effects), the
diffusivities derived by Eqn (8) can only be compared for defined points in time. It is not possible to
relate these diffusivities to the bulk diffusivities
derived by the method of Conway and Rasmussen
(2000). However, this method is suitable for the
comparison of different layers at various depths in
the debris mantle, as long as the observation period
is identical. The value of κ is obviously affected by
the conductivity of the debris particles, the porosity
and especially the moisture content. Oke (1987)
found that adding moisture to a dry soil initially
produces a sharp increase in κ by increasing
thermal contact and expelling air from the voids.
However, in most soils κ begins to decline beyond
about 20% moisture content by volume.
Results and analysis
Conditions during the experiment
The mean daily air temperature ranged from 1.8 to
8.6°C, the mean daily relative humidity ranged
from 50% to 82% during the periods considered
(25 June–10 July 2010). Precipitation events took
place on 5 and 6 July 2010 (<2 mm) and on 7 July
2010 (6 mm).
Ablation
For the first two weeks the effect of changing plot
topography is very limited and differential melt is
clearly visible. The ablation experiments show a
clear dependence of the sub-debris ice melt on the
layer thickness, as can be expected (Fig. 3).
For all the debris plots a reduction of ice melt
was observed compared with the clean ice case.
This implies that on the Vernagtferner the critical
thickness is smaller than 0.03 m. During the time
period of detailed investigations (25 June–10 July
2010) the mean daily ablation at the bare ice stake
was 0.06 m per day. In comparison, the ice melt
underneath the 0.18 m thick coarse gravel revealed
a mean melt rate of about 0.02 m per day during the
same time period. For the sand fraction (plots 1 and
2) higher melt rates have been observed than for
the gravel fraction (plots 3 and 4) with a comparable layer thickness (Fig. 3).
A comparison of the different material with
similar layer thicknesses showed that the highly
Fig. 3. Mean daily melt rates of individual metamorphic local
material plotted against debris cover thickness for the time
period from 25 June to 10 July 2010. The grey shaded area
represents the estimated critical thickness on Vernagtferner. The
error bars depict the uncertainties of ablation and debris thickness measurements.
porous volcanic material protects the ice much
more effectively from melting than the compact
local mica schist. Porous debris layers have
more air trapped inside the material than compact
layers. Due to the very low conductivity of air
(0.025 W m–1 K–1), the amount of ablation was
reduced significantly.
Albedo has a striking influence on ablation
because darker debris layers will absorb solar
radiation more efficiently than bright materials,
leading to higher surface temperatures and thus
more energy available for sub-debris ice melt. Over
the observed two-week period the bright pumice
with its high albedo and porosity was most effective in reducing ice melt compared with all other
materials. A very thin layer of only 0.025 m led to
a mean daily ablation of about 0.02 m for the
coarse and nearly 0.04 m for the fine trachytic
pumice. Although their grain sizes are slightly different, the mean ablation rate underneath the fine
black tephra was about 1.75 times higher than
underneath the coarser white pumice (Fig. 4).
Because the finer grain size offers a higher porosity, which should reduce melt rates, this differential
ablation can be attributed to albedo.
For the trachytic pumice the influence of grain
size on ablation can be observed in Fig. 5. The
coarser volcanic material appeared to have a more
shielding effect on the underlying ice than the fine7
22
Paper I
MARTIN JUEN ET AL.
Fig. 4. Ice melt measured at stakes. Due to the higher albedo the
bright pumice (plot 8) is more effective in reducing ablation than
the black tephra (plot 10) and the local mica schist (plot 4). The
grey areas depict the uncertainties of ablation measurements.
Fig. 5. Ice melt underneath volcanic material. During the first
observation period until 1 July, the ablation rates were measured
usually twice a day, which results in the apparent step function. The grey areas depict the uncertainties of ablation
measurements.
grained debris with the same thickness. Within a
six-day period the fine trachytic pumice experiences a higher sub-debris ice melt (0.03 m) than
the coarse material (Fig. 5).
After the time period of manually repositioning
the debris (grey shaded area in Fig. 6) the flat test
8
Fig. 6. Ice melt measured at stakes over the entire observation
period for three examples: bare ice, gravel cover of 3 cm and
8 cm respectively (plots 4 and 6). The differential ablation is
clearly recognizable for the first two weeks of the experiment
(grey shaded area). The grey arrows display an extrapolation of
the trend line from the first two weeks, indicating large differences in total ablation for stable debris cover conditions.
site turned into several steep debris-covered cones
and sub-debris ice melt was additionally influenced
by slope development and debris redistribution.
The amount of solar radiation received by a surface
is controlled by aspect and slope, which consequently change the ablation conditions. The effects
can be observed in particular in the changes of the
melt function gradients of debris-covered ice compared with bare ice, which are almost identical in
the time period 4–16 August 2010 (Fig. 6).
If the controlled conditions would have continued, the total melt over the entire observation
period would show strong differences for the individual plots. To demonstrate the effect of the slope
formation and debris redistribution, a linear fit of
the first two weeks is extrapolated and indicated by
the grey arrows in Fig. 6. Consequently, the analysis of debris-influenced melt is focused on the first
period (grey shaded area in Fig. 6) with controlled
debris conditions and undisturbed surfaces. Furthermore the two gravel plots (plots 4 and 6) show
the same amount of ablation due to rearrangement
and unification in debris thickness at the end of the
observation period (Fig. 6).
23
Table 3. Thermal diffusivity at described distance from surface
(depth) for various grain sizes.
Fig. 7. Mean thermal conductivities of the different debris layers
for the period from 25 June to 1 July 2010. The error bars depict
the uncertainties of ablation and thermistor measurements.
Thermal conductivity
The thermal conductivity was derived for the first
week of the experiment using the method described
by Mihalcea et al. (2006). During this period (25
June–1 July 2010) no precipitation events took
place and the rearrangement in geometry of the
plots remained limited. Melt rates and debris temperatures from the thermistor sensors (Table 1)
were used as input parameters. The results presented in Fig. 7 represent the mean thermal conductivity for each plot.
The highly porous volcanic rocks (plots 7–10)
featured the lowest thermal conductivities, with
mean values below 0.6 W m–1 K–1. The numerous
pore spaces were filled with air and therefore
lowered the bulk thermal conductivity of the material. Because of the high specific surface area, the
fine-grained sand fraction has the highest water
retention capacity and small void space. The water
film on the grain surface and the saturated vapour
Plot no.
Grain size
Depth
(m)
Thermal diffusivity
(m2 s−1)
2
5
5 – day
5 – night
Coarse sand
Coarse gravel
Coarse gravel
Coarse gravel
Glacier foreland
0.045
0.11
0.11
0.11
0.15
1.6 × 10−7
3.93 × 10−7
3.64 × 10−7
3.04 × 10−7
8.22 × 10−7
in the voids lead to a higher thermal conductivity
compared with the dry material and therefore
increased melt rates. This became particularly
apparent for the sand fraction plots, which turned
out to be much darker when the meltwater made its
way up to the surface. The moisture transport
mechanism in capillary porous sediments depends
on the size of the pores and the porosity of the
material. Generally the particle surface area per
unit volume increases with decreasing grain size,
therefore the smallest grain sizes offer the highest
water retention capacity. As grain size increases,
the porosity can still be high, but the retention
capacity of the material is very low. This will affect
the moisture transport from the ice–debris interface
towards the debris surface and cause differential
saturation of the bottom layer. For the gravel fraction (plots 3–6), no significant differences or consistent tendencies in thermal conductivity have
been found between coarse gravel and gravel.
Thermal diffusivity
The depth averaged thermal diffusivity κ was estimated for two plots on the testfield, as well as for
the glacier foreland (within the existing sediments)
and is summarized in Table 3. Fig. 8 illustrates the
process of how the depth-averaged values for κ
were obtained.
The higher dispersion of the values of plot 5
indicates that other processes apart from pure conduction were involved. In Fig. 9 the daytime
(07:00–19:00) and night time (19:00–07:00)
derivatives are considered separately.
It became clear that higher dispersion prevails
during the daytime compared with the night time.
Especially for the coarse gravel, this might be
attributed to convective conditions at the surface
and latent heat exchange at the bottom of the debris
layer that developed in the course of the day due to
solar heating of the debris. Therefore the assump9
24
Paper I
MARTIN JUEN ET AL.
Fig. 8. Distribution of ∂T/∂t vs. ∂2T/∂z2 at selected depths within the supraglacial debris. Time period for the assessment of the
derivatives: 25–26 June 2010 for plot 2, 25–28 June 2010 for plot 5 and 26 June–19 August 2011 for the glacier foreland. The slope
of the best fitting line gives an approximation of the thermal diffusivity (Eqn 2).
Fig. 9. Distribution of ∂T/∂t vs. ∂2T/∂z2 at selected depths within the supraglacial debris (total debris cover thickness 0.18 m). Time
period for the assessment of the derivatives: 25–28 June 2010. (a) Night: 19:00–07:00; (b) day: 07:00–19:00.
tion that the heat flux is purely conductive (Eqn 2)
was not fulfilled anymore, because of the presence
of local heat sources or sinks. The high dispersion
of the derivatives during the day in plot 5 can be
explained by these conditions.
Using the amplitude method (Eqn 8) the thermal
diffusivity for various depths can be obtained.
Fig. 10 shows thermal diffusivities in varying
depths for plots 5 and 6, and the glacier foreland.
Although the results are not comparable with the
depth-averaged thermal diffusivity, they give an
indication that the moisture content plays an
important role towards the debris–ice interface. For
plots 5 and 2, lower values of κ were found in
10
deeper layers in proximity to the debris–ice interface. Due to the melting ice, these layers contained
more water which has a decreasing effect on κ.
Owing to the high specific heat capacity of water
(4180 J kg–1 K–1) the thermal diffusivities are lower
towards the melting ice (see Eqn 3). In consequence, more heat is stored within the layer instead
of being conducted through it. The discrepancies
of thermal diffusivities in different depths can be
interpreted as a measure of this non-homogeneity
within the debris mantle. Also the temporal change
of κ can be attributed to the presence of moisture.
In the coarse gravel (plot 5) both levels show temporal fluctuations. This is not the case for the gravel
25
Fig. 10. Thermal diffusivity obtained from the amplitude equation (Ingersoll et al. 1948). Time period: (a, b) 25 June–3 July 2010
(plots 5 and 6) and (c) 18–26 August 2011 (glacier foreland). Due to the melting ice, more water is present towards the debris ice
interface. Hence values of thermal diffusivities are significantly lower in deeper layers.
(plot 6), where the variability in the lower layer is
very small, due to the saturated conditions. The
fluctuations in κ could be explained by a phase
change happening in the corresponding layers
during this time. Looking at the non-ice cored
material from the glacier foreland, no depth
dependence of κ values was determined.
Discussion
Glacier ice melt depends on the meteorological
conditions and the properties of the supraglacial
debris cover. Global radiation heats the uppermost
debris layer in dependence of the albedo. Considering the characteristic heat transport through the
debris cover, the thermal conductivity is most suitable to estimate sub-debris ablation, especially for
distributed models. This bulk parameter summarizes the lithology of the material itself, but also the
porosity of the layer and the filling of the pore
volume. Debris covers usually offer a mixture of
grain sizes on a single glacier. Supraglacial tephra
can be an exception, because the fallout pattern
will correlate with the grain size (smaller particles
will stay in the atmosphere longer) and tephra
thickness (Kirkbride and Dugmore 2003).
The field experiments during the ablation season
affirm the dependence of the sub-debris ice melt on
the layer thickness. For the local metamorphic
material, a continuous debris cover surface of
0.03 m already had a shielding effect on the underlying ice. Therefore, the critical thickness, where
sub-debris melt rates are equal to bare ice melt
rates, is smaller than 0.03 m on the Vernagtferner.
This is in line with values found for the Glacier de
Tsidjiore Nouve, Valais, Switzerland (Small and
Gomez 1981) and the Miage Glacier, Italy
(Mihalcea et al. 2008).
Highly porous volcanic material protects the ice
much more effectively from melting than similar
layer thicknesses of the local metamorphic mica
schist. Tephra covers provide more insulation from
solar radiation and heat that is advected by the
atmosphere. A porous medium contains more air,
trapped within the material, and therefore transfers
less heat than a more dense material. For example,
the trachytic pumice with a layer thickness of
0.025 m reduced ablation by 70% compared with
bare ice and by 50% compared with the local mica
schist gravel (Fig. 4). It can be concluded that
metamorphic rock debris has a less insulating
impact on melt rates than similar layer thicknesses
of volcanic material and even thin layers of volcanic ash will act as an effective protection for ice
ablation in glacierized volcanic areas. The results
regarding the impact on glacier melt rates agree
with earlier studies of tephra mantles on the icecapped Volcán Villarrica in southern Chile (Brock
et al. 2007) and the Eyjafjallajøkull ice cap in
southern Iceland (Kirkbride and Dugmore 2003).
Also the albedo plays an important role. A lower
albedo means less energy is reflected and the debris
surface absorbs more energy. The volcanic material
represents a particularly good example: Melt rates
underneath the black tephra were about 1.75 times
higher than underneath the bright pumice, with a
similar layer thickness (Fig. 4). The mean thermal
conductivity for all mica schist debris layers (plots
11
26
Paper I
MARTIN JUEN ET AL.
1–6) in the experiment is 1.53 W m–1 K–1 (Fig. 7).
A comparable value for pure rock mica schist is
about 2.9 W m–1 K–1 (Busby et al. 2009). The presence of voids reduces k almost by half. No significant differences or consistent tendencies in thermal
conductivity have been found between coarse
gravel and gravel, leading to the conclusion that in
this grain size range the effect of particle size is
rather small.
The analysis of thermal diffusivities indicates
deviations from pure conductivity and a layering
with lower values towards the debris–ice interface
(Figs 9 and 10). This is attributed to air movement
in the upper parts and the presence of melt water in
the lower parts of the debris cover. A higher porosity in these layers leads to a higher potential saturation. This effect will have a bigger impact on fine
materials with a high porosity. Generally, higher
moisture contents in the debris lead to higher
thermal conductivity and larger heat capacity.
More heat can be transported to the debris–ice
interface, owing to the displacement of the air
inclusions by water (Fig. 7). These results confirm
the findings from previous studies. Harris and
Pedersen (1998) showed that the dominant process
of heat transport in the upper layers of coarse
blocky material is by rapid air movement through
the voids. Conway and Rasmussen (2000) found
that latent heat exchange might dominate near the
debris–ice interface.
This study demonstrates that the effects of rock
type and grain size on melt rates underneath
supraglacial debris mantles are significant for the
ablation on debris-covered glaciers. The effects are
complex and interactive, but the analysis of the
thermal diffusivities indicates the need to account
for this depth dependency in future sub-debris ice
ablation models. The effect of air convection in the
upper parts and the phase change in the saturated
layers of the lower parts of the debris cover lead to
the conclusion that the use of a multi-layered
energy transfer model would improve the prediction of sub-debris melt rates. With our setup it was
not possible to observe water movement in the
debris. While the surface of the sand fraction was
almost always wet, this was not the case for all the
other plots. The volcanic plots showed a high fluctuation of dry and wet surfaces. Our observations
indicate that the coarser the grain size of the sediment, the lower the probability of a wet surface.
Improvements can be made by using probes that
measure debris moisture at multiple depths in addition to temperature sensors.
12
Acknowledgements
The authors would like to thank Ursula Blumthaler
and Lina Seybold for assisting with the fieldwork.
They also thank Maria Shahgedanova from the
Walker Institute for Climate System Research,
University of Reading, UK for providing two meteorological stations. The funding of the experiments
by the Austrian Academy of Science, the Deutsche
Forschungsgemeinschaft (MA 3347/4-1) and the
Bavarian Ministry of Environment is gratefully
acknowledged.
Martin Juen, Christoph Mayer and Astrid Lambrecht Commission for Geodesy and Glaciology, Bavarian Academy of
Sciences, Alfons-Goppel-Strasse 11, D-80539 Munich,
Germany
Email: [email protected]
Anna Wirbel, Institute of Meteorology and Geophysics, University of Innsbruck, Innrain 52, A-6020 Innsbruck, Austria
Ulrich Kueppers, Earth and Environmental Sciences,
Ludwig-Maximilians-University Munich, Theresienstrasse
41, D-80333 Munich, Germany
References
Brock, B., Rivera, A., Casassa, G., Bown, F. and Acunn, C.,
2007. The surface energy balance of an active icecovered volcano: Villarrica Volcano, southern Chile.
Annals of Glaciology, 45, 104–114.
Busby, J., Lewis, M., Reeves, H. and Lawley, R., 2009.
Initial geological considerations before installing ground
source heat pump systems. Quarterly Journal of Engineering Geology and Hydrogeology, 42, 295–306.
Conway, H. and Rasmussen, L.A., 2000. Summer temperature profiles within supraglacial debris on Khumbu
Glacier Nepal. In: Nakawo, M., Raymond, C.F. and
Fountain, A. (eds), Debris-covered Glaciers. Proceedings of a workshop held at Seattle, September 2000.
IAHS Publ., 264, 89–97.
Dyurgerov, M.B. and Meier, M.F., 2005. Glaciers and the
Changing Earth System: A 2004 Snapshot. Institute of
Arctic and Alpine Research, University of Colorado.
Escher-Vetter, H., Braun, L.N., Siebers, M. and Weber, M.,
2005. Water balance of the Vernagtferner high alpine
basin bassed on long-term measurements and modelling.
Landschaftsökologie und Umweltforschung, TU Braunschweig, 45, 19–32.
Harris, S.A. and Pedersen, D.E., 1998. Thermal regimes
beneath coarse blocky materials. Permafrost and Periglacial Processes, 9, 107–120.
Ingersoll, L.R., Zobel, O.J. and Ingersoll, A.C., 1948. Heat
Conduction – With Engineering and Geological Application. McGraw-Hill, New York.
Kellerer-Pirklbauer, A., 2008. The supraglacial debris
system at the Pasterze Glacier, Austria: spatial distribution, characteristics and transport of debris. Zeitschrift
für Geomorphologie Supplement, 52, 3–25.
Kirkbride, M.P. and Dugmore, A.J., 2003. Glaciological
response to distal tephra fallout from the 1947 eruption
Chapter 3
Paper II
Einsatz
einer
Thermalkamera
und
von
Strahlungssensoren
zur
Oberflächenklassifizierung am Vernagtferner.
Surface debris classification at
Vernagtferner using temperature observations from a thermal camera and radiation
sensors.
Juen, M., Mayer, C., Lambrecht, A., Eder, K., Stilla, U. and Wirbel, A., 2013.
Accepted in: Zeitschrift für Gletscherkunde und Glazialgeologie, 45/46, 185-201.
27
28
Band 45/46 (2011/12), S. 185–201
Z eits c hri f t
f ü r
Gletscherkunde
u n d G l azia l geo l ogie
© 2013 by Universitätsverlag Wagner, Innsbruck
Einsatz einer Thermalkamera und von
Strahlungssensoren zur Oberflächenklassifizierung
am Vernagtferner
Martin Juen, Christoph Mayer, Astrid Lambrecht, Konrad Eder,
Uwe Stilla, München, und Anna Wirbel, Wien
Mit 6 Abbildungen und 4 Tabellen
Zusammenfassung
Die vorliegende Arbeit untersucht die Anwendbarkeit der fernerkundungsbasierten
Oberflächenklassifizierung auf Gletschern mit Hilfe von thermischen Infrarot (TIR)
Bildern. Auf einem Testgelände an der Gletscherzunge des Vernagtferners wurden
die Oberflächentemperaturen einer supraglazialen Schuttdecke und zusätzlich von
periglazialem Moränenmaterial mit Strahlungssensoren und einer TIR Kamera ermittelt. Außerdem wurde die schuttinterne Temperaturentwicklung während der Mess
perioden mit Thermistoren aufgezeichnet. Aus den Thermistorenmessungen geht
hervor, dass Richtung und Intensität des Wärmestroms im Schutt und somit auch die
Oberflächentemperatur von der mittleren Temperatur des Untergrundes in einer kritischen Tiefe abhängt. Die Auswertung der Strahlungsdaten dokumentiert die Existenz
eines thermischen Unterschiedes zwischen supraglazialer Schuttdecke und Schutt
ohne Eisunterlage und somit auch die prinzipielle Detektierbarkeit von Eis unter einer
Schuttschicht geringer Mächtigkeit. Die Daten der TIR Kamera erlauben eine räumlich differenzierte Analyse der einzelnen Schuttparzellen und somit Rückschlüsse
auf die Effekte der verschiedenen Korngrößen. Es zeigt sich allerdings auch, dass
die Unterscheidung von schuttbedecktem Eis und periglazialem Moränenmaterial
mit den derzeitigen fernerkundlichen Beobachtungsmöglichkeiten Einschränkungen
unterliegt.
29
30
186
Paper II
M. Juen, C. Mayer, A. Lambrecht, K. Eder, U. Stilla und A. Wirbel
Surface debris classification at Vernagtferner using temperature
observations from a thermal camera and radiation sensors
Abstract
The present study examines the applicability of remote sensing-based surface classification on glaciers using thermal infrared (TIR) images. At a test site located at
the glacier tongue of Vernagtferner surface temperatures of supraglacial debris and
periglacial moraine were determined using radiation sensors and a TIR camera. In
addition, the debris internal temperature was monitored with thermistors. The analysis
of the thermistor measurements shows that the direction and intensity of the heat flux
in the debris and thus the surface temperature depends on the average daily temperature of the substrate at a critical depth. The evaluation of the radiation data reveals
the existence of a thermal difference between debris and ice cored debris and thus the
principal detectability of ice below a shallow debris layer. The data of the TIR camera
allow a spatially differentiated analysis of the individual debris plots and enable us to
draw conclusions about the effects of different grain sizes on the surface temperature.
It turns out that the distinction between debris covered ice and periglacial moraine
material is restricted with current remote sensing applications.
1. Einleitung
Aufgrund des globalen Klimawandels weisen weltweit zahlreiche Gletscher derzeit
negative Massenbilanzen auf (Dyurgerov and Meier, 2005). Der damit einher gehende
Rückzug der Eismassen und das verstärkte Auftauen von Permafrostgebieten sorgen
dafür, dass immer mehr Gletscheroberflächen von Schutt und Sedimenten bedeckt
werden. Infolgedessen stellen schuttbedeckte Gletscher eine aktuelle Herausforderung
für die Abschätzung der Wasserressourcen aus der Gletscherschmelze dar (Shukla et
al., 2010). Speziell in abgelegenen Gebieten wie im Karakorum, dem Himalaya oder
dem Tien Schan ist Schmelzwasser eine wichtige Komponente des Wasserkreislaufs
(z. B. Kaser et al., 2010). Darüber hinaus sind die genaue Kartierung und die Über
wachung von Gletschern und das Erstellen von Gletscherinventaren für die Bewertung der Auswirkungen des Klimawandels auf die globalen Eisressourcen wichtig
(Paul et al., 2004; Bolch et al., 2008; Shukla et al., 2010). Besonders in entlegenen
und schwer zugänglichen Regionen lassen sich durch Fernerkundung umfangreiche
und kosteneffektive Studien durchführen. So ist die Erfassung der flächenhaften Verteilung der Schuttdicke ein entscheidender Parameter bei der Abflussberechnung und
der Vorhersage der Gletscherreaktion auf klimatische Veränderungen in einem größeren Zeitraum (Bozhinskiy et al., 1986). Einige Studien konzentrieren sich auf die
Verwendung von Satellitendaten (Sensoren von Landsat-7 ETM+ und ASTER), um
aus der langwelligen Ausstrahlung der Oberfläche, Karten der Schuttdickenverteilung
31
Oberflächenklassifizierung mittels Thermalkamera und Strahlungssensoren
187
zu erstellen. Das Prinzip beruht darauf, dass schuttbedeckte Eisflächen im Vergleich
zu reinem Schuttmaterial derselben Lithologie, eine geringere Oberflächentemperatur
aufweisen (Lougeay, 1974). Die Auswertung der langwelligen Ausstrahlung, welche
in direktem Zusammenhang mit der Oberflächentemperatur steht, erlaubt es, diese
Oberflächen voneinander zu unterscheiden. In Kombination mit empirischen Beziehungen zwischen Schuttdicke und Oberflächentemperatur bei gegebener Einstrahlung
können Karten mit räumlich verteilter Schuttdicke erstellt werden (Mihalcea et al.,
2008a und 2008b). Foster et al. (2012) entwickelten ein physikalisch basiertes Modell
um die supraglaziale Schuttdicke aus den thermischen Kanälen von Satellitenbildern
zu berechnen. Diese Methode basiert auf der Lösung der Energiebilanzgleichung an
der Schuttoberfläche, um die Schuttdicke als Restglied jedes Pixels zu ermitteln. Ziel
der vorliegenden Arbeit ist es, den Energiefluss durch die Schuttdecke in Abhängigkeit der natürlichen Randbedingungen zu bestimmen und daraus die Temperatur
verteilung zu rekonstruieren. Diese Erkenntnisse werden genutzt um das Potential
von fernerkundungsbasierter Schuttkartierung auf Gletschern, mithilfe von Thermalkameras und langwelligen Strahlungssensoren, zu evaluieren und die Randbedingungen zu erörtern.
2. Hintergrund
Die von Fernerkundungssatelliten wie LANDSAT-ETM und TERRA-ASTER ermittelten Oberflächentemperaturen können genutzt werden um Oberflächentypen voneinander zu unterscheiden. Unter der Annahme, dass die Emissivität und die thermischen
Eigenschaften des Schutts auf und um den Gletscher in etwa gleich sind, emittiert eine
schuttbedeckte Eisfläche und eine nahegelegene periglaziale Schuttoberfläche thermische Infrarotstrahlung in verschiedener Intensität. Da der supraglaziale Schutt aus
Material von eisfreien Hängen um den Gletscher oder subglazialem Gesteinsmaterial besteht, welches durch die Eisbewegung Richtung Gletschervorfeld transportiert
und dort abgelagert wird, erscheint diese Annahme gerechtfertigt. Zwischen den zwei
Flächen auf und außerhalb des Gletschers ist ein thermischer Kontrast zu erwarten.
Im Vergleich zum Moränen- oder Schuttmaterial ohne Eisunterlage wird der Wärmestrom in die Schuttschicht verstärkt und als Konsequenz die Emission langwelliger
Strahlung an der Oberfläche vermindert. Der Einsatz von thermischen Satellitendaten
zur Klassifizierung von supraglazialen Schuttbedeckungen aufgrund dieser Eigenschaften ist allerdings nur eingeschränkt möglich. Das größte Problem bei der thermischen Klassifizierung von Gletscheroberflächen mit Satellitendaten liegt im fehlenden
zeitlichen Verlauf der Oberflächentemperatur, welche mit lokalen Strahlungssensoren
und terrestrischen TIR Kameras einfach registriert werden kann. Die Gleichung der
Energiebilanz einer supraglazialen Schuttoberfläche lautet nach Kraus (1966):
QO – BO – HO – EO = 0,
(1)
32
Paper II
188
wobei QO die Strahlungsbilanz an der Oberfläche, BO der Bodenwärmestrom, HO die
turbulente Flussdichte fühlbarer Wärme und EO die turbulente Flussdichte latenter
Wärme des Wasserdampfes sind. In dieser Betrachtung wird die Wärmeflussdichte aufgrund von Regen vernachlässigt, welche je nach Temperatur des Niederschlags bzw.
der Schuttoberfläche die Oberflächentemperatur mindern kann. Die Komponenten der
Strahlungsbilanz Q0 sind die kurzwellige Einstrahlung KW↓, die reflektierte kurzwellige Strahlung KW↑, die langwellige Einstrahlung LW↓ und die langwellige Ausstrahlung LW↑. Es gilt QO = (KW↓ – KW↑) + (LW↓ – LW↑). Die Existenz einer Eisschicht
unter der Schuttbedeckung bedeutet eine zusätzliche Wärmesenke, welche den Bodenwärmestrom beeinflusst. Der Bodenwärmestrom BO [W/m²] ist definiert durch:
BO = – λ
∂T
.
∂z
(2)
BO ist proportional zum Temperaturgradienten im Schutt mit der Wärmeleitfähigkeit λ
[W/m K] als Proportionalitätsfaktor. Die Flussdichte BO wird als positiv definiert wenn
sie von der Oberfläche in den Untergrund gerichtet ist. Das negative Vorzeichen von λ
besagt, dass die Wärme entgegengesetzt zum Temperaturgradienten, also in Richtung
der geringeren Temperatur fließt. Der mit der Schuttdicke exponentiell abnehmende
Bodenwärmestrom verschwindet in verschiedenen Materialien ab einer Tiefe von ca.
0,5 m bis 1,0 m (Häckel, 2005). Die Temperatur weist dort praktisch keinen Tagesgang
mehr auf, diese Schicht wird als thermisch aktive Schicht definiert. Bei schuttbedecktem
Eis stellt die Übergangsfläche vom Schutt zum Eis die untere Randbedingung (meist
0°C während der Ablationsperiode) dar. Dieser Umstand bedingt die niedrigeren Oberflächentemperaturen im Falle von supraglazialem Schutt, da der stärkere Temperaturgradient im Gegensatz zu einer generellen Temperaturschichtung über dem Gefrierpunkt für einen höheren Wärmestrom in der Schuttschicht sorgt. Es wird mehr Wärme
von der Oberfläche in tiefere Schichten geleitet und die Oberfläche kühlt sich ab.
3. Messstandort und experimentelle Anordnung
Im Sommer 2010 wurde eine Reihe von Ablationsexperimenten auf der Zunge des
Vernagtferners (Ötztaler Alpen, Österreich) durchgeführt. Zehn Parzellen mit unterschiedlichen Schuttdicken wurden auf der relativ flachen Gletscheroberfläche auf
einer Seehöhe von 2910m installiert. Der lokale metamorphe Glimmerschiefer wurde
gesiebt und in vier verschiedenen Korngrößen auf dem Eis aufgebracht (Abb. 1).
Meteorologische Daten wurden mit zwei automatischen Wetterstationen (AWS) im
Bereich des Testgeländes aufgezeichnet. Die erste AWS (AWS 1) wurde direkt über
den Schutttestflächen eingerichtet, eine weitere Station (AWS 2) befand sich im
Gletschervorfeld ca. 20 Meter tiefer über Moränenmaterial. Am 15. September 2010
wurde zusätzlich zur normalen Instrumentierung, die zeitliche Entwicklung der Oberflächentemperatur mit Hilfe einer TIR Kamera aufgezeichnet.
33
DEF+*+)
Abb. 1:>$?)2@AB C!,Fig. 1:
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4. Daten und Methoden
!"#
" $ % &! '
(%% !
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34
190
Paper II
4.2 Messung der Oberflächentemperatur
Die von der Oberfläche emittierte langwellige Strahlung wurde mithilfe von drei
Strahlungssensoren (Typ CNR1 und CNR4, siehe Tab. 2) im Zeitraum von Juni bis
September 2010 durchgehend aufgezeichnet.
Tab. 2: Technische Spezifikationen der Strahlungssensoren – Table 2: Technical specifications of
the radiation sensors
Genauigkeit nach
Herstellerangaben
Sensor
Hersteller und Typ
emittierte Strahlung im
langwelligen Spektralbereich
[W/m²]
Kipp & Zonen Spektralbereich:
± 10 % der Tagessumme
5 bis 50 μma
Kipp & Zonen Spektralbereich:
± 10 % der Tagessumme
4,5 bis 42 μmb
a
CNR1, b CNR4
Für eine räumliche Analyse der Oberflächentemperatur am Testfeld wurde die TIRKamera (Tab. 3) an der Spitze der automatischen Wetterstation befestigt um alle
Schuttparzellen zu beobachten. TIR-Bilder wurden in 30-minütigen Zeitschritten von
9.00 bis 14.00 Uhr manuell von dieser festen Position aufgezeichnet.
Tab. 3: Technische Spezifikationen der TIR-Kamera – Table 3: Technical specifications of the TIR
camera
Kamera Model
InfraTec, VarioCAM hr
Detektor Typ und Format
Microbolometer Focal Plane Array
320 x 240 Pixel
7,5 μm – 14 μm
besser als 0,08 K
± 1,5 K, ± 2 %
12.5mm
(57 x 44)°
Spektralbereich
Temperaturauflösung bei 30°C
Messgenauigkeit
Brennweite
Sichtfeld
35
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36
Paper II
M. JUEN, C. MAYER, A. LAMBRECHT, K. EDER, U. STILLA und A. WIRBEL
5. Ergebnisse der Messungen
5.1 Thermistoren
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37
193
tur mit zunehmender Tiefe geringer werden. Allerdings ist die Temperatur auf dem
Gletscher in 18 cm Tiefe durch die schmelzende Eisoberfläche auf 0° C begrenzt,
während im periglazialen Schutt in dieser Tiefe die Tagesschwankung noch etwa 6°C
beträgt. Auffallend sind die verschieden stark ausgeprägten Temperaturgradienten,
speziell in den Stunden um den Sonnenhöchststand (ca. 13:00 Uhr). Aus Abb. 3 ist
auch ersichtlich, dass Richtung und Größe des Bodenwärmestroms und somit auch
die Oberflächentemperatur des periglazialen Schutts von der mittleren Temperatur an
der Unterseite der thermisch aktiven Schicht, bzw. der Eisoberfläche abhängen.
5.2 Strahlungssensoren
Der thermische Unterschied an der Oberfläche zwischen schuttbedecktem Gletschereis
und einer reinen Schuttablagerung kann durch die Strahlungssensoren beurteilt werden. Dazu werden die abgeleiteten Oberflächentemperaturen von AWS 1 und AWS 2
miteinander verglichen. In Abbildung 4 ist zusätzlich zu den Temperaturen auch deren
Unterschied ΔTO für mehrere Tage dargestellt. Generell ist festzustellen, dass zwischen
den zwei Standorten eine Differenz besteht, diese jedoch je nach Witterungsbedingungen verschieden stark ausgeprägt ist. Während einer Folge von Strahlungstagen vom
12. bis 16. Juli 2010 erwärmt sich der Schutt ohne Eisunterlage jeden Tag ein wenig
mehr, während der supraglaziale Schutt jede Nacht wieder auf dieselbe Ausgangstemperatur auskühlt. Auch die Auswirkungen von Bewölkung und Niederschlag sind in
Abb. 4 gut zu erkennen. In der Schönwetterperiode mit geringer Bewölkung am 16. und
17. Juli 2010 sind Differenzen der Oberflächentemperaturen von bis zu 16°C messbar.
Am Abend des 17. Juli ziehen Wolken auf und es fallen ca. 20 mm Niederschlag. Auch
am darauffolgenden Tag herrscht eine geschlossene Wolkendecke und es kann sich
nur ein sehr geringer Tagesgang der Oberflächentemperaturen entwickeln. Die Temperaturdifferenz der beiden Oberflächen beträgt am 18. Juli nur maximal 4 K. In den
Morgenstunden des 19. Juli klart der Himmel auf und durch die verstärkte langwellige
Ausstrahlung kühlen die Oberflächen weiter aus. Zum Zeitpunkt des Sonnenaufgangs
kommt es zu einer raschen Temperaturerhöhung an beiden Schuttoberflächen. Weisen
der supraglaziale und der periglaziale Schutt ähnliche Werte von thermischer Diffusivität auf, wird sich die Temperaturänderung in beiden Schuttmaterialien bei gleicher
Ausgangssituation gleich schnell ausbreiten. Im Falle des supraglazialen Schutts sorgt
der stärkere Temperaturgradient dafür, dass mehr Wärme Richtung Eis fließt und somit
die Oberflächentemperatur im Vergleich zum benachbarten Moränenmaterial ohne Eisunterlage kleiner ist. Das größere Schuttvolumen und der geringere Temperaturgradient
der thermisch aktiven Schicht sorgen für ein schwächeres Auskühlen der Oberfläche in
den Nachtstunden. Anhand dieser Ergebnisse lässt sich feststellen, dass für eine Oberflächenklassifizierung oder Schuttdickenbestimmung mit Fernerkundungsdaten der
Zeitraum nach dem Sonnenhöchststand der ideale Aufnahmezeitpunkt ist. Dann ist der
Temperaturunterschied der Oberflächen am stärksten ausgeprägt.
38
Paper II
Abb 4: ! " !# !$"%
&
%'&
()*!
+%+&
,
ΔTO"- . Fig. 4: , + + ! " !$"+/%
+
+0&/+%&()*
++%
+++ΔTO"-
39
195
5.3 Thermalkamera
Während die Strahlungssensoren die langwellige Ausstrahlung des gesamten Testfelds
wiedergeben, ermöglicht die TIR-Kamera die Analyse einzelner Schuttparzellen und
somit Rückschlüsse auf die Effekte der verschiedenen Korngrößen. Daher wurden
am 15. September 2010 Temperaturmessungen mit einer TIR-Kamera am Testfeld
durchgeführt. Die von der Kamera registrierten Oberflächentemperaturen zeigen eine
klare Abhängigkeit von der Schuttdicke (Tab. 4, Abb. 5). Die Sandfraktion (Parzelle 1
und 2) resultiert in den niedrigsten Temperaturen, während Parzelle 5 mit der größten
Schuttdicke von 5,5 cm den höchsten Mittelwert von 14.2°C (Tabelle 4) aufweist.
Tab. 4: Oberflächentemperaturen der einzelnen Parzellen aus TIR Kamera Daten – Table 4: Surface
temperatures for the different plots monitored with the TIR camera
Zeit
Parzelle 1 Parzelle 2 Parzelle 3
3 cm
2.5 cm
4.5 cm
feiner Sand grober Sand grober Kies
Parzelle 4
3.5 cm
Kies
Parzelle 5
5.5 cm
grober Kies
Parzelle 6
4.5 cm
Kies
CNR4 CNR1
9:14
8,0
5,5
9,4
9,3
10,8
9,8
7,1
5,9
9:43
9,8
5,7
11,8
11,8
13,9
12,0
10,1
9,2
10:11
10,2
6,3
12,8
13,0
15,6
12,6
11,6
10,7
10:42
11,8
6,8
15,0
15,1
18,2
15,0
13,1
11,7
11:10
11,4
6,3
14,3
14,8
17,1
14,5
14,2
12,7
11:41
9,3
5,7
11,6
12,3
14,0
11,2
13,4
12,3
12:11
8,3
5,3
10,4
10,6
12,2
9,5
12,0
10,4
13:09
9,7
6,0
12,2
12,2
14,1
11,4
11,5
10,0
13:37
9,8
6,2
11,6
12,4
13,4
12,1
12,0
10,8
14:09
8,7
6,1
10,8
11,4
12,5
10,3
12,0
10,7
Mittelwert
9,7
6,0
12,0
12,3
14,2
11,9
11,7
10,4
Neben der Schuttdicke beeinflussen noch andere Faktoren die Oberflächentemperatur
der einzelnen Schuttparzellen. Dazu zählen die Korngröße, der Feuchtigkeitsgehalt
im Schutt und auch die Oberflächenfarbe (Albedo). Der Einfluss der Korngröße ist an
den Messwerten um 13:09 Uhr und um 13:37 Uhr gut zu erkennen. Die Parzellen mit
dem groben Kiesmaterial (Parzelle 3 und 5) zeigen einen sinkenden Trend, während
die kleinkörnigen Parzellen steigende Oberflächentemperaturen aufweisen. Je größer
die einzelnen Steine im Schutt sind, desto langsamer reagieren sie auf eine Veränderung der Lufttemperatur oder der Sonneneinstrahlung. Zusätzlich spielt der Feuchtigkeitsgehalt, insbesondere für kleine Korngrößen, eine wichtige Rolle. Durch die hohe
spezifische Oberfläche des Sandes können Parzelle 1 und 2 leichter Wasser binden
als das grobe Material der Nachbarfelder. Daher sind diese Testflächen tagsüber oft
40
Paper II
196
gesättigt. Aufgrund der hohen thermischen Leitfähigkeit von Wasser und der niedrigen Albedo des gesättigten Materials, kann mehr Energie zum darunter liegenden
Eis übertragen werden, was zu einer niedrigen Oberflächentemperatur führt. Darüber
hinaus trägt auch die Verdunstungskälte, die von der Lufttemperatur, der relativen
Feuchte und der Windgeschwindigkeit abhängt, ihren Teil zu den geringen Ober
flächentemperaturen der Sandparzellen bei. In den grobkörnigen Schuttparzellen (Parzellen 3 bis 6) führt der größere Hohlraumanteil zu einem geringeren Energietransport
und somit zu höheren Oberflächentemperaturen im Vergleich zu den Sandtestflächen.
Die mit Luft gefüllten Hohlräume, welche eine niedrigere thermische Leitfähigkeit
als das Gesteinsmaterial oder Wasser aufweisen, sorgen für eine bessere Isolation des
darunter liegenden Eises, während das Schuttmaterial mit höherer Leitfähigkeit nur an
den Kontaktstellen Wärme effektiv übertragen kann.
6. Modellierung der Oberflächentemperatur
auf Grundlage der Energiebilanz
Es deutet sich an, dass mit zunehmender Schuttdicke der thermische Unterschied ΔTO
der Oberfläche zwischen supra- und periglazialem Schutt geringer wird. Um die Frage
zu klären, ab welchen Schuttdicken keine Temperaturdifferenz mehr vorhanden ist,
wurde ein Energiebilanzmodell (EBM) angewandt. Dieses numerische Modell – entwickelt, um die Eisschmelze unter einer supraglazialen Schuttschicht zu berechnen –
wurde mit der Datenreihe des Testfeldes kalibriert (Wirbel, 2011). Als Eingangsdaten
werden die meteorologischen Messungen der AWS1 verwendet, deren zeitliche Auflösung 10 Minuten beträgt. Die Oberflächentemperatur der Schuttdecke wird durch die iterative Lösung der Energiebilanzgleichung (Gleichung 1) zu jedem Zeitschritt (10 Minuten) ermittelt. Für die Berechnungen wurde eine Wärmeleitfähigkeit von 1,29 W/m K
angenommen, die Albedo wurde über den gesamten Messzeitraum bestimmt, das
arithmetische Mittel beträgt 0,125. Die turbulente Flussdichte latenter Wärme wurde
ignoriert, da die Schuttoberfläche während der Ablationsperiode tagsüber trocken anzunehmen ist, solange kein Niederschlag auftritt. Das ursprüngliche EBM wurde für die
aktuelle Fragestellung um den Speicherterm ΔS, welcher die Änderung der gespeicherten Wärme im Schutt parametrisiert, erweitert (Mattson and Gardner, 1989):
ΔS = ρscs
–
∂T
∂t
Δz,
(4)
–
wobei ρs die Dichte, cs die spezifische Wärmekapazität und ∂T /∂t die mittlere Rate der
Temperaturänderung des Schutts darstellt.
Die Oberflächentemperatur wurde für mehrere Schuttdicken berechnet. Die Ergebnisse für eine Schuttmächtigkeit von 0,04 m zeigen tagsüber eine recht gute Übereinstimmung mit den Messwerten der Testflächen während nachts die modellierten
Oberflächentemperaturen stets zu niedrig ausfallen (Abb. 6). In den Nachmittags-
41
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42
Paper II
Abb. 6:7
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7. Diskussion
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43
199
Ein entscheidender Punkt im Hinblick auf unterscheidbare Oberflächentemperaturen
ist die vorherrschende mittlere Temperatur an der Unterseite der thermisch aktiven
Schicht im periglazialen Schutt. Diese bestimmt die Größe des Temperaturgradienten
und somit den Bodenwärmestrom und dadurch auch die Oberflächentemperatur.
Diese mittlere Untergrundtemperatur, welche in erster Näherung der Jahresmitteltemperatur entspricht, weist jedoch eine starke Höhenabhängigkeit auf, welche bei der
Auswertung der thermischen Differenz berücksichtigt werden muss. Speziell für die
Ableitung einer Schuttdickenverteilung aus Fernerkundungsdaten werden Feldmessungen benötigt um eine empirische Beziehung zwischen Oberflächentemperatur und
Schuttmächtigkeit herzustellen (Mihalcea et al., 2008a). Die Auswertung von thermalen Satellitenbildern zur Unterscheidung von supraglazialem Schutt und angrenzendem Moränenmaterial scheint durch mehrere Faktoren recht beschränkt zu sein. Zum
einen ist durch die vertikale Sortierung des Materials, die Annahme einer homogenen
Schuttdecke nicht erfüllt, zum anderen kann die, aufgrund der verschieden starken
Schuttdicke, räumlich hoch variable Oberflächentemperatur von den Satellitensensoren aufgrund der Pixelgröße nur unzureichend erfasst werden. Ein vielversprechender
neuer Ansatz wurde von Piatek (2009) vorgestellt. Hier wird die thermophysikalische
Signatur verschiedener Oberflächenklassen aufgrund der thermischen Trägheit ermittelt. Zur Berechnung der thermischen Trägheit werden Informationen über die Albedo
und den Unterschied zwischen Tages- und Nachttemperaturen der Oberfläche benötigt. Idealerweise sind dazu jedoch zwei Satellitenbilder desselben Tages notwendig,
was sich in der Praxis mit LANDSAT-TM und TERRA-ASTER Daten allerdings
nicht bewerkstelligen lässt. Die in der vorliegenden Studie erzielten Modellergebnisse
sowie die aus den Messungen abgeleiteten Oberflächentemperaturen zeigen jedoch,
dass die Differenz zwischen Nacht- und Mittagstemperaturen von der Existenz von
Eis im Untergrund beeinflusst wird. Eine quantitative Analyse dazu steht noch aus.
Der Einsatz einer TIR-Kamera zur räumlich verteilten Ermittlung der Temperaturdifferenzen erscheint vielversprechend und sollte bei einem Folgeexperiment auf
seine Anwendbarkeit untersucht werden.
8. Danksagung
Die Autoren bedanken sich für die zur Verfügung gestellten automatischen Wetterstationen bei Maria Shahgedanova (Walker Institute for Climate System Research, University of Reading, UK). Die Arbeiten wurden von der Österreichischen Akademie
der Wissenschaften, der Deutschen Forschungsgemeinschaft (MA 3347/4–1) und dem
Bayerischen Staatsministerium für Umwelt und Gesundheit gefördert.
44
200
Paper II
9. Literatur
Bolch, T., M. F. Buchroithner, A. Kunert and U. Kamp, 2007: Automated delineation of debriscovered glaciers based on ASTER data. Proceedings of the 27th EARSeL-Symposium „GeoInformation in Europe“, 4.–7.6.07, Bozen, Italy (Gomarasca, M. A., Ed.), Millpress, Rotterdam
(2008): 403–410.
Bozhinskiy, A. N., M. S. Krass and V. V. Popovnin, 1986: Role of debris cover in the thermal physics
of glaciers, Journal of Glaciology 32: 255–266.
Brock, B. W., C. Mihalcea, M. P. Kirkbride, G. Diolaiuti, M. E. J. Cutler and C. Smiraglia, 2010: Meteorology and surface energy fluxes in the 2005–2007 ablation seasons at the Miage debris-covered
glacier, Mont Blanc Massif, Italian Alps, Journal of Geophysical Research 115 (D9): 1–16.
Dyurgerov, M. B. and M. F. Meier, 2005: Glaciers and the changing Earth system: A 2004 snapshot.
Technical representative, University of Colorado, Institute of Arctic and Alpine Research: 117 p.
Foster, L. A., B. W. Brock, M. E. J. Cutler and F. Diotri, 2012: A physically based method for
estimating supraglacial debris thickness from thermal band remote-sensing data, Journal of Glaciology 58 (210): 677–691.
Häckel, H., 2005: In: Meteorologie. 5. Auflage, Ulmer, Stuttgart: 233.
Kaser, G., M. Großhauser and B. Marzeion, 2010: Contribution potential of glaciers to water availability in different climate regimes. Proceedings of the National Academy of Science of the
U. S. A, 107 (47): 20223–20227. doi:10.1073/pnas.1008162107.
Kraus, H., 1966: Freie und bedeckte Ablation. Ergebnisse des Forschungsunternehmens Nepal
Himalaya, Band 1, Lieferung 3, Springer Verlag, Berlin: 203–235.
Lougeay, R., 1974: Detection of buried glacial and ground ice with thermal infrared remote sensing.
Advanced concepts and techniques in the study of snow and ice resources (Santeford, H. S. and
J. L. Smith, Ed.), National Academy of Sciences, Washington, DC: 487–494.
Mattson, L. E. and J. S. Gardner, 1989: Energy exchange and ablation rates on the debris-covered
Rakhiot Glacier, Pakistan, Zeitschrift für Gletscherkunde und Glazialgeologie 25 (1): 17–32.
Mihalcea, C., B. W. Brock, G. Diolaiuti, C. D’Agata, M. Citterio, M. P. Kirkbride, M. E. J. Cutler,
and C. Smiraglia, 2008a: Using ASTER satellite and ground based surface temperature measurements to derive supraglacial debris cover and thickness patterns on Miage Glacier (Mont
Blanc Massif, Italy), Cold Regions Science and Technology 52 (3): 341–354.
Mihalcea, C., C. Mayer, G. Diolaiuti, C. D’Agata, C. Smiraglia, A. Lambrecht, E. Vuillermoz,
E. and G. Tartari, 2008b: Spatial distribution of debris thickness and melting from remote-sensing and meteorological data, at debris-covered Baltoro Glacier, Karakoram, Pakistan, Annals
of Glaciology 48: 49–57.
Paul, F., C. Huggel and A. Kääb, 2004: Combining satellite multispectral image data and a digital elevation model for mapping debris-covered glaciers, Remote Sensing of Environment 89: 510–518.
Piatek, J. L., 2009: Thermophysical properties of terrestrial rock and debris-covered glaciers as
analogs for Martian lobate debris aprons. 40th Lunar and Planetary Science Conference, 23–27
march 2009, The Woodlands, Texas.
Shukla, A., R. P. Gupta and M. K. Arora, 2010: Delineation of debris-covered glacier bounda
ries using optical and thermal remote sensing data, Remote Sensing Letters 1 (1): 11–17.
doi:10.1080/01431160903159316.
Wirbel, A., 2011: Physically based ice melt beneath supraglacial debris, driven by a reduced set of
input parameters. Diploma Thesis, University of Innsbruck, Faculty of Geo- and Atmospheric
Sciences: 126 S.
45
Manuskript erhalten am 7.12.2012, angenommen am 10.3.2013
Anschrift der Verfasser: Mag. Martin Juen, Dr. Christoph Mayer und Dr. Astrid Lambrecht
Kommission für Erdmessung und Glaziologie, Bayerische Akademie
der Wissenschaften, Alfons-Goppel-Str. 11, D–80539 München
[email protected] / [email protected] /
[email protected]
Dipl.-Ing. (FH) Konrad Eder, Prof. Dr. -Ing Uwe Stilla
Technische Universität München, Fachgebiet Photogrammetrie
und Fernerkundung, Arcisstr. 21, D–80290 München
[email protected] / [email protected]
Mag. Anna Wirbel
BOKU Wien, Peter-Jordan-Straße 82, A–1190 Wien
[email protected]
201
46
Chapter 4
Poster I
Ablation and runoff generation on debris covered Keqikar glacier in the upper Aksu
catchment, China.
Juen, M., Mayer, C., Mayr, E., Lambrecht, A., Hagg, W., Haidong, H. and Shiyin,
L. Presented at the European Geoscience’s General Assembly 2011, Vienna, Austria.
47
48
Martin Juen1, Christoph Mayer1, Elisabeth Mayr², Astrid Lambrecht³ , Wilfried Hagg², Han Haidong4, Liu Shiyin4
Fig. 1: Schematic map of Keqikar glacier (Han, H. et al. 2010). The red and orange circles indicate the position
Stake farm 3
Stake farm 2
Stake farm 1
Fig. 8: Cumulative ablation at 13 stakes starting on four consecutive days. The stakes were placed in
the upper and lower areas of the ice cliffs perpendicular to the surface. Backwasting rates show a
clear dependence on the exposition of the ice cliff. The comparison to bare ice melt rates reflects the
influence of the lower albedo, caused by the thin dust layer that is permanently present on these
locations (as can be seen in Fig. 6). Degree day factors for each orientation have been calculated.
ICE CLIFF MELT RATES MEASURED AT STAKES
Bare ice – 3.5 cm/d
North – 4.1 cm/d
West – 4.6 cm/d
East – 5.2 cm/d
South – 5.6 cm/d
Melt rates
per day
Debris/ice interface
26 cm
16 cm
1 cm
∗
∗
∗
+ C
∗ln (DCT) + C
Empirical equations
Deutsche
Forschungsgemeinschaft
Fig. 9: Degree day factors of individual stakes plotted against
debris cover thickness. An enhanced DDF is clearly visible for
very thin films of debris, whereas decreased values are
observed for thicker layers. The equations used for the curve
fittings are illustrated besides the Figure.
∑
Fig 2: Example of an ablation stake before
renaturation of the surface.
IMGI
CAREERI
Fig. 10: Correlation between measured and simulated ice
melt. Ablation was calculated using the degree day
approach. The power law equation gives no results for
debris cover thickness values of zero, therefore this value is
not taken into account.
To estimate the amount of ablation after a
projected climate change, the results from the
climate modelling group (AKSU TARIM‐CLIM) will be
used as input data.
The findings of the second field trip will supply a
data set that is needed for the ablation model to
work over a whole year and not only during the
main ablation seasons. This is essential for making
statements or predictions on a longer time scale.
The results of these measurements form the
experimental basis for the development of a sub‐
debris ice melt model. A conceptual runoff model
including this ablation routine for debris covered
glaciers will be applied to simulate current
conditions and forthcoming changes in the
hydrological cycle.
4. OUTLOOK
Fig. 6: Ablation was also measured at several ice cliffs with varying
expositions. Three cliffs have been investigated by terrestrial
photogrammetry (see poster XL 113)
ICE CLIFF INVESTIGATION
Fig 3: Relationship between debris thickness and mean ice
ablation.
SET UP AND OBERVATION OF A STAKE NETWORK
Fig. 5: The layer temperatures show a strong diurnal signal. The temperature from the sensor 1 cm
beneath the surface shows a strong correlation with the global radiation signal.
DEGREE DAY FACTOR (DDF) VS. DEBRIS COVER THICKNESS (DCT)
Fig 4: Postition of the thermistor sensors
within the debris cover.
T3
T2
T1
THERMISTOR MEASUREMENTS WITHIN THE DEBRIS LAYER
Debris surface
To calculate temperature gradients and energy available for ice melt,
temperatures in varying depths in the debris layer were recorded, using
digital data loggers. Figure 4 and Figure 5 show the setup of the thermistor
measurements and a four day time series of the temperatures. Figure 6
demonstrates the measurement process on an ice cliff. The observed
ablation was much higher at these locations, which leads to the conclusion
that they are an important source of meltwater on debris covered glaciers.
During the ablation season 2010 a series of ablation measurements were
performed on the Keqikar glacier. 43 ablation stakes (Fig. 2) with varying
debris thicknesses were installed and observed to collect a dataset of
ablation rates with a high temporal resolution. Fig. 3 illustrates the results of
the survey. The largest mean ablation rate was measured under a thin debris
layer of less than 0.5 cm, due to a lower albedo compared to bare ice,
resulting in higher absorption of shortwave radiation. In comparison to bare
ice, ablation rates decreased for debris thicknesses of more than 2 cm. The
insulating and shielding effect of the debris cover is getting stronger with
increasing debris thickness.
2. FIELD MEASUREMENTS
Braithwaite, R. J. 1995. Positive degree‐day factors for ablation on the Greenland ice sheet studied by energy‐balance modelling. J. Glaciol. 41, 153‐160. Han, H. et al. 2010. Backwasting rate on debris‐covered Koxkar glacier, Tuomuer mountain, China. J. Glaciol. 56(196), 287‐296.
REFERENCES
Fig. 7: Tautochrones (lines that show the relationship of
temperature to depth at a given time) were drawn for the 14.08.10
(Beijing time), using the thermistor temperature record. At 09:00
sunrays had not struck the ground yet, afterwards the surface
temperature increased rapidly, reaching the maximum at 15:00.
THERMISTOR MEASUREMENTS
Using the air temperature record, the sum of positive degree days is calculated for each stake. Consequently degree day factors have been
computed, which are shown in Fig. 9 (Braithwaite, 1995). To obtain an empirical equation that represents the connection from debris cover
thickness to degree day factor different curve fittings have been tested. Fig. 10 shows how well the empirical equations perform in simulating ice
melt, using the temperature‐index approach. Considering the simplicity of the equations, there is good agreement between measured and
modelled ablation values. Coefficient of determination ranges from 0.8 to 0.92. The exponential equation is giving the best results.
Thermistor measurements show a strong diurnal signal that diffuses downward with decreasing amplitude and increasing lag (Fig. 5). The mean
daily temperature gradient was found to be linear with depth (Fig. 7). Ice Cliff measurements indicate that the ablation and the resulting melt
water runoff are strongly influenced by the presence of ice cliffs (Fig. 8).
3. RESULTS
Keqikar glacier contributes to the Tarim river, the most
important water resource of Chinas largest inland
watershed, the Tarim basin. With annual precipitation sums
of less than 100 mm, large parts of this basin are desert.
Irrigation is essential for agriculture and food production.
To assess future changes in the water resources it is
necessary to better understand the climate‐glacier
interaction that controls ablation and as a consequence,
the formation of runoff from glaciers. A conceptual runoff
model, including an ablation routine for debris covered
glacier parts will be applied to simulate current conditions
and future changes in the hydrological cycle.
The investigation area is Keqikar glacier which is located in China’s western Tien
Shan, in the Xingjiang Uigur Autonomous Region. The glacier reaches from
6432 to 3060 m a.s.l. with a length of 25 km and area of 84 km². Almost 16 km²
of the glacier area is debris covered , accounting for 83% of the total ablation
area (Han et al. 2010).
The AKSU TARIM‐MELT project is part of a DFG project bundle about climate
change and water resources in western China (AKSU‐TARIM). The long term aim
of the project is the modeling of melt and runoff in a catchment with debris
covered glacier parts.
1. INTRODUCTION
Commission for Geodesy and Glaciology, Bavarian Academy of Sciences and Humanities, Munich, Germany ([email protected]), 2 Geography Department, Ludwig‐Maximilians‐University, Munich, Germany,
3 Institute of Meteorology and Geophysics, University of Innsbruck, Austria, 4 State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions, Environmental and Engineering Research Institute, Lanzhou, China.
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Ablation and runoff generation on debris covered Keqikar glacier in the upper Aksu catchment, China.
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Chapter 5
Paper III
Impact of varying debris cover thickness on catchment scale ablation: A case study
for Koxkar glacier in the Tien Shan.
Juen, M., Mayer, C., Lambrecht, A., Haidong, H. and Shiyin, L., 2013. The
Cryosphere Discuss., 7, 5307-5332, doi:10.5194/tcd-7-5307-2013, 2013.
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Discussions
This discussion paper is/has been under review for the journal The Cryosphere (TC).
Please refer to the corresponding final paper in TC if available.
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The Cryosphere
Open Access
The Cryosphere Discuss., 7, 5307–5332, 2013
www.the-cryosphere-discuss.net/7/5307/2013/
doi:10.5194/tcd-7-5307-2013
© Author(s) 2013. CC Attribution 3.0 License.
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Commission for Geodesy and Glaciology, Bavarian Academy of Sciences, Munich, Germany
State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and
Engineering Research Institute, Chinese Academy of Sciences, China
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Received: 11 September 2013 – Accepted: 11 October 2013 – Published: 5 November 2013
Correspondence to: M. Juen ([email protected]) and C. Mayer
([email protected])
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M. Juen , C. Mayer , A. Lambrecht , H. Haidong , and L. Shiyin
Discussion Paper
Impact of varying debris cover thickness
on catchment scale ablation: a case study
for Koxkar glacier in the Tien Shan
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Published by Copernicus Publications on behalf of the European Geosciences Union.
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Introduction
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Debris covered glaciers are a prominent feature in high relief mountain ranges like the
Tien Shan, the Himalaya or the Karakoram. These glaciers are characterized by the
presence of supraglacial debris mantles in the ablation zones that can originate from
various sources, such as thrusting of subglacial material, melt-out of englacial debris
bands, channel fill material, rockfall from mountain sides and meltwater bursts through
the crevasse and conduit system or aeolian deposition directly on the glacier surface
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To quantify the ablation processes on a debris covered glacier, a simple distributed ablation model has been developed and applied to a selected glacier. For this purpose,
a bundle of field measurements was carried out to collect empirical data. A morphometric analysis of the glacier surface enables us to statistically capture the areal distribution of topographic features that influence debris thickness and consequently ablation.
Remote sensing techniques, using high resolution satellite imagery, were used to extrapolate the ground truth results to the whole ablation area and to map and classify
melt-relevant surface types. As a result, a practically applicable method is presented,
that allows the estimation of ablation on a debris covered glacier by combining field data
and remote sensing information. The sub-debris ice ablation accounts for about 19 %
of the entire ice ablation, while the percentage of the moraine covered area accounts
for approximately 32 % of the entire glacerized area. Although the ice cliffs occupy only
1.7 % of the debris covered area the melt amount accounts for approximately 15 %
of the total sub-debris ablation and 2.7 % of the total ablation respectively. Our study
highlights the influence of debris cover on the response of the glacier terminus to climate warming. Due to the fact that melt rates beyond 0.1 m of moraine cover are highly
restricted the shielding effect of the debris cover dominates over the temperature- and
elevation dependence of the ablation in the bare ice case.
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Abstract
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(Schomacker, 2008). Several studies concentrated on the relationship between debris cover thickness and sub-debris ice melt rates since the fundamental contribution
of Østrem (1959). When solar radiation is present, very thin layers of debris or small
single grains absorb more heat than ice, due to their lower albedo. The transfer of this
energy into the underlying ice increases ablation rates. Thicker supraglacial debris covers act as a protecting carapace, which insulates the underlying ice and significantly
reduces ablation (Østrem, 1959). The response of debris covered glaciers to climate
change and therefore the prediction of future water availability are the subject of current research (e.g. Scherler et al., 2011; Benn et al., 2012; Bolch et al., 2012). Several
physically based models that calculate sub-debris melt rates based on meteorological variables and debris thermal properties have been developed during the recent
past (Nicholson and Benn, 2006; Reid and Brock, 2010). However, these physically
based models require a wide range of input data whose determination is difficult, time
consuming and expensive, especially for larger areas. They are important for process
studies at point locations, but the application for large glaciers or even basin wide calculations remains difficult. To determine the ablation of a whole debris covered glacier,
robust conceptual approaches with empirically derived functions have been proven to
produce realistic results.
Apart from the natural debris coverage also ice cliffs and supraglacial lakes are important features of debris covered glaciers: they are widely recognized as spots of
enhanced melting (Sakai et al., 2002, 2000). The exposed areas of steeply inclined ice
are normally covered with a very thin layer of dust or sand, leading to higher absorption of shortwave radiation due to the low albedo compared to clean ice. Sakai et al.
(2000) also states that supraglacial lakes produce internal ablation in the conduit system that leads to a positive feedback process, accelerating the ablation rate of debris
covered glaciers. Caused by the collapse of water channels new ice cliffs and ponds
are created.
To quantify these complex physical melt processes on a debris covered glacier, this
study applies a distributed ablation model to a selected glacier.
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3 Data compilation
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Field observations have been carried out on the moraine covered ablation area of the
Koxkar glacier, located in the Xinjiang Uyghur Autonomous Region of northwestern
China (41.76◦ N, 80.11◦ E; Fig. 1).
The glacier is situated in the Central Tien Shan, one of the largest mountain ranges
in Central Asia. Melt water, originating from the glaciers in this region feeds the Tarim
river and is required in the surrounding lowlands for agriculture and drinking water
(Hagg et al., 2007). The prevailing climate can be described as continental and is characterized by low winter precipitation and convective rainfall events in summer (Aizen
et al., 1997). The glacier reaches from 3060 to 6432 m a.s.l. with a length of 25 km
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and an area of 84 km (Haidong et al., 2010). Debris thickness ranges from less than
0.01 m on the upper reach of the ablation area and on ice-cliff slopes to more than
3 m near the glacier terminus (Haidong et al., 2006; Wu and Liu, 2012). According to
Yong et al. (2006) the glacier has an ablation zone of about 30.6 km2 , with 60 % of the
area covered by debris. The Equilibrium Line Altitude is 4300 m a.s.l. and the maximum
glacier area is situated at the elevation band between 4600 and 4800 m a.s.l. (Haidong
et al., 2010).
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2 Study area
Ablation measurements
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From 10 August to 29 August 2010 a series of ablation measurements were performed
on the Koxkar glacier. Ablation stakes were installed at locations with varying debris
thicknesses and preferably horizontal surfaces. Ablation was also measured at several
ice cliffs of different expositions. To find out how the slope angles of the cliffs evolve,
stakes have been placed orthogonal to the ice surface in the upper and the lower part
of the ice cliffs. Debris cover thickness was measured at each stake during installation.
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3.3 Remote sensing
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High resolution images from the Ikonos satellite have been used to generate a digital elevation model (DEM) from the entire Koxkar glacier catchment. Ikonos provides
panchromatic images with 1 m resolution and multispectral imagery with 4 m resolution
(Table 1). A cloud-free Ikonos image was acquired on 30 April 2009, 13:32 LT. The solar
elevation was 60.1◦ and the solar azimuth was 149.6◦ .
An ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer)
Level 1B granule was processed to obtain land surface temperature (LST) following
the approach by Pu et al. (2006). The observation date is 10 April 2007, the local
observation time is 13:39 and the spatial resolution of the thermal infrared channel,
which is used to obtain LST, is 90 m. The ASTER scene was selected, because no
snow or clouds are present over the debris covered area in the acquired image.
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An automatic weather station (AWS) operated by CAREERI provides the required temperature record for the model. The AWS is located near the glacier terminus at an
elevation of 3009 m a.s.l. (Fig. 1). The respective air temperature sensor is a HMP45C,
Campbell Scientific Inc., mounted 2 m above ground surface. It is connected to a datalogger (CR1000, Campbell Scientific Inc.) which provides hourly records (Haidong
et al., 2010).
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Meteorological measurements
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Additionally moraine thickness along a longitudinal profile was measured in summer
2011 by scientists from the Cold and Arid Regions Environmental and Engineering
Research Institute (CAREERI).
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To compare ablation rates of several locations and time spans, mean degree day
factors for each stake were calculated from the air temperature record (Braithwaite,
1995). The temperature data was extrapolated to higher elevations using a lapse rate
◦
−1
◦
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of −0.008 C km (from 3000 to 3700 m a.s.l.) and −0.004 C km (from 3700 m a.s.l.
and above) respectively. These lapse rates have been determined by Haidong et al.
(2008) on the basis of measured air temperature at two different AWS located on the
glacier (short term observation in 2003 and 2004) and the AWS in vicinity to the glacier
described above (long term observation). Haidong et al. (2008) state that the drastic
change in temperature laps rate at an elevation of 3700 m a.s.l. is because of the transition from a broad supraglacial debris cover in the lower parts to a debris free ice
surface in the middle and upper parts of the glacier. Ablation rates and their relation to
debris thickness are determined empirically, to obtain an equation that represents the
connection from debris cover thickness to degree day factor (Hagg et al., 2008).
Different curve fittings were tested, but a power law regression provides the most reliable equation because of the asymptotic approximation to the x-axis. To take account
of the fact that the degree day factor for very thin layers of debris cover is enhanced
compared to bare ice, a linear equation is used for moraine thicknesses smaller than
0.014 m. Considering the simplicity of the equation, there is good agreement between
the measurements and the regression equation with a coefficient of determination of
0.92 (Fig. 2). In the case of the ice cliffs, degree day factors for north facing, south
facing and east/west facing cliffs were calculated and applied within the model. Because the ice cliff area is measured in the horizontal projection from an orthophoto,
the actual area of the cliffs was determined using a standard slope angle of 45◦ according to Haidong et al. (2010) which represents a reasonable mean value for the
observed cliff slopes. During the observation period in the ablation season 2010 no
change in inclination was determined. The slope angle of the observed cliffs was in
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Ablation model design
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between 40 and 50 and fits well with the determined mean value. For supraglacial
lakes the melt rates at the lake bottom are estimated using the same degree day factor – debris cover thickness regression. But instead of calculating the sum of positive
degree days based on the air temperature record, the overlying water is assumed to
have a constant temperature of 4 ◦ C. This assumption is supported by the work of Xin
et al. (2012), who monitored the thermal regime of a supraglacial lake during ablation
season at the Koxkar glacier in 2008. One drawback of the present model is that the
lateral melting in the ponds is not included, because the dynamic evolution of the debris
mantle is not incorporated.
The mapping and area calculation of supraglacial lakes and steep ice cliffs were
carried out with the stereo image data provided by the Ikonos product (Fig. 3).
For this purpose a digital elevation model (DEM) with a spatial resolution of 6 m was
generated utilizing stereo satellite image data. The orthorectified multispectral images
in combination with the derived elevation model were used to detect surfaces like ice,
water or ice cliffs semi-automatically. For the lake detection the normalized difference
water index (NDWI) developed by Huggel et al. (2002) was used. Two spectral channels
with maximum reflectance difference for water (blue- and near infrared-channel) were
utilized. In the case of the ice cliffs a combination of the slope, derived from the DEM,
and a grayscale filter applied on the panchromatic image yields to the best result.
Unfortunately a large number of ice cliffs are not recognized by this approach because
of their small size. The method is limited to features that are larger than the pixel size
of the fundamental DEM. Therefore these features were picked manually with the aid
of the semi-automatic method.
To estimate debris cover thickness from thermal satellite imagery an empirical approach was used. Mihalcea et al. (2008) showed the strong correlation between
ASTER-derived LST and debris thickness. To obtain a map of moraine thickness distribution we investigated the relation between those two parameters (Fig. 4).
For 22 pixels of the ASTER image one or more debris thickness measurements
were available. For pixels with more than one measurement the mean value of moraine
Results and discussion
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thickness was used for the regression. Three different regressions were tested: (a) an
exponential regression (b) a linear regression through the origin and (c) a power law
regression. The exponential regression is leading to very thick debris covers for high
temperatures, but when compared to debris cover thickness from Wu and Liu (2012) it
seems to be the most realistic and therefore is used as the default choice in the following figures. The linear regression through the origin is based on the assumption that
the surface temperature of melting ice is 0 ◦ C and if there would be debris present the
LST would be higher. The power law regression represents a compromise of the previous regressions. This empirical relationship can now be used to derive debris cover
thickness from ASTER LST. To find out how sensitive the model responds to different moraine patterns the three different regressions shown in Fig. 4 were tested. The
ASTER image was resampled to a pixel size of 10 m × 10 m so that the ablation model
is able to resolve small features like ice cliffs. The resulting debris cover thickness
distribution maps are shown in Fig. 5.
The total debris cover volume can now be calculated by accumulating the pixel values of the entire debris covered area of the corresponding map. The resulting mean
debris thicknesses are shown in Fig. 5. The patterns of the three debris cover thickness
distributions are very similar, although the resulting thicknesses differ, especially in the
tongue area where the highest values can be assumed.
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The analysis of the satellite data reveals the areal distribution of features that are relevant for the ablation model (Table 2).
The statistic shows that more than 32 % of the entire glacierized area is covered with
debris. The areas of ice cliffs occupy 1.70 %, the area of the supraglacial lakes 0.36 %
of the debris covered area.
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Areal distribution of features
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It is stated by several authors that debris covered glaciers respond differently to climate change than bare ice glaciers (Bolch et al., 2008; Sorg et al., 2012; Scherler
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5.3 Influence of debris cover on the response of the glacier terminus
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In Fig. 6 the modelled ice ablation for the time span of 1 May 2010 to 31 October 2010 is
shown. This period covers the entire ablation season, before and after this time period
no temperatures above 0 ◦ C were measured at the AWS.
To compare the total ice melt of the different regressions for the debris thickness
inversion the calculated ablation is presented in Fig. 7.
The bare ice ablation, the ice cliff ablation and the sub debris ice ablation beneath
supraglacial debris is the same for all of the three regressions due to the model structure. The features are all on the same location and their degree day factors are constant. Therefore the only difference in total ice ablation arises from debris cover thickness that has an effect on the sub debris ice ablation. The sub-debris ice ablation
accounts for 16.9 % in the case of the exponential regression, for 17.4 % in the case
of the linear regression and for 19.9 % in the case of the power law regression of the
entire ice ablation. Although the ice cliffs are relatively small in area (1.7 % of the debris
covered area) the melt amount accounts for 13–16 % of the total sub-debris ablation
and 2.6–2.7 % of the total ablation respectively (Table 3).
These results are not in line with the findings of Sakai et al. (1998), who states that
the ice cliff melt amount reaches 69 % of the total ablation at the debris covered area,
although the area of ice cliffs occupies less than 2 % of the debris covered area on
Lirung glacier in Nepal. Despite the analogy in the fraction of ice cliffs of the debris
covered area the ice cliff melt amount differs significantly. The discrepancy can be
explained by the fact that Sakai et al. (1998) used an average melt rate for the entire
debris covered area and therefore did not account for the spatial distribution of debris
thickness.
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et al., 2011). During years of negative mass balance the position of the terminus region remains stable while the debris covered parts react by surface lowering. This
downwasting behaviour is also reported for the Koxkar glacier (Pieczonka et al., 2013).
The significant difference in the terminus evolution is related to the facts that moraine
cover is present and the decreasing ice flow velocity due to reduction of ice thickness
and surface gradient (Benn et al., 2012). The ablation model allows us to compare
melt rates of the debris covered Koxkar glacier with an imaginary debris free glacier.
Figure 8 shows the direct comparison of melt rates including a zoomed section of the
glacier terminus. It becomes quite clear why debris covered glaciers respond differently on climate warming and negative mass balances. While the melt amount on the
bare ice glacier reaches values of approximately 8 m in one ablation season, the ablation on the debris covered glacier almost comes to a standstill. The ice cliffs are the
exception and can easily be spotted as melt hotspots with values up to 9 m melt on
the debris covered tongue. For the supraglacial lakes a slightly inferior ablation can
be observed. Another important point is the melt gradient: the modelled ablation on
the bare ice tongue exhibits the temperature- and elevation dependence of the melt
rates. In the case of the debris covered glacier this effect is not present. Due to the fact
that the curve in Fig. 2 beyond 0.1 m levels out, no significant changes in ablation are
observable along the tongue profile (Fig. 9). The shielding effect of the debris cover
dominates over the vertical temperature gradient.
In Fig. 9 the longitudinal section A–A (Fig. 1) of the tongue of the Koxkar glacier is
presented. The DEM is shown as a solid grey line, the ablation of the bare ice glacier
and the debris covered glacier are displayed as blue line and black line respectively. In
the higher parts, where debris cover thickness is rather small, the differences are not
as manifest as in the lower parts, where subdebris ablation almost ceases. Figure 9
also exhibits the influence of the ice cliffs, where the ablation reaches values beyond
the bare ice case.
The substantial differences between a debris covered and a debris free glacier becomes evident when looking at the total ablation amount. Whereas for the moraine
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The exponential regression of debris cover thickness appears to be the most realistic
when compared to the multi-frequency ground penetrating radar measurements from
Wu and Liu (2012), who have been able to derive a map of debris cover thickness in
the lowest part of the glacier terminus.
The results regarding ablation indicate that melt on ice cliffs plays a significant role
but not as substantial as stated by Sakai et al. (1998).
Our study highlights the influence of debris cover on the response of the glacier terminus to negative mass balance. Due to the fact that melt rates are highly restricted
the shielding effect of the debris cover dominates over the temperature and elevation
dependence of the ablation in the bare ice case. In addition the reduced melt rates
highlight the serious implications with regard to runoff modelling from debris covered
glaciers. The comparison of total ablation amount from a debris free and a debris covered glacier underlines the importance to include debris cover into discharge modelling.
The representation of debris covered glacier parts in hydrological models is still an
unsolved problem. By implementing the presented ablation model into a conceptual
runoff model, an improved version of the HBV-ETH-model (Mayr et al., 2014), capable
to reproduce runoff from moraine covered glaciers will be created. Moreover, runoff
scenarios for changing climate and glaciation conditions can be realised after the cali5317
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Conclusions and outlook
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covered glacier the total ice ablation is in the range of 67–70 × 106 m3 (67 × 106 m3 for
the exponential regression, 68× 106 m3 for the linear regression through the origin and
6 3
70 × 10 m for the power law regression), the ice melt at the debris free glacier would
6 3
be 150 × 10 m . Thus, it becomes clear how important the consideration of debris
cover in predictions of future melt water availability really is. Our presented results do
not support the statement of Kaab et al. (2012), that the insulating effect of debris layers with thicknesses exceeding a critical thickness acts on local scales of intact covers,
but not in general on the spatial scale of entire glacier tongues.
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Aizen, V. B., Aizen, E. M., Melack, J. M., and Dozier, J.: Climatic and hydrologic changes in the
Tien Shan, Central Asia, J. Climate, 10, 1393–1404, 1997. 5310
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Bolch, T., Buchroithner, M. F., Peters, J., Baessler, M., and Bajracharya, S.: Identification of
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Acknowledgements. The authors would like to thank Elisabeth Mayr and Liu Qiao for assisting
with the fieldwork. The funding of the study by the Deutsche Forschungsgemeinschaft (MA
3347/4-1) in the context of the AKSU-TARIM project bundle (Water Resources in Western
China) is gratefully acknowledged.
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Wu, Z. and Liu, S.: Imaging the debris internal structure and estimating the effect of debris layer
on ablation of Glacier ice, J. Geol. Soc. London, 80, 825–835, 2012. 5310, 5314, 5317
Xin, W., Shiyin, L., Haidong, H., Jian, W., and Qiao, L.: Thermal regime of a supraglacial lake
on the debris-covered Koxkar Glacier, southwest Tianshan, China, Environ. Earth Sci., 67,
175–183, 2012. 5313
Yong, Z., Shi-Yin, L., Yong-jian, D., Jing, L., and Donghui, S.: Preliminary study of mass balance
on the Keqicar Baxi Glacier on the south slopes of Tianshan Mountains, J. Glaciol. Geocryol.,
28, 477–484, 2006. 5310
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66
|
5320
Discussion Paper
|
Satellite
Spectral range
Multi-spectral
1 = Blue
2 = Green
3 = Red
4 = NIR
Pan
445–516 nm
506–595 nm
632–698 nm
757–853 nm
526–929 nm
Panchromatic
Pixel resolution
4m
1m
Discussion Paper
Band number
|
Ikonos-2
Sensor
Discussion Paper
Table 1. Ikonos satellite sensor specifications.
|
Discussion Paper
67
|
5321
Discussion Paper
|
Discussion Paper
Table 2. Horizontally projected area of the melt relevant surface types on the Koxkar glacier
derived from satellite imagery mapping.
Feature area
|
2
65.60 km
21.17 km2
0.36 km2
0.08 km2
Discussion Paper
Entire glacierized area
Debris covered area
Cliffs
Supraglacial lakes
|
Discussion Paper
68
|
5322
Discussion Paper
|
power law
regression
2.71 %
2.72 %
2.62 %
15.6 %
16.06 %
13.17 %
Discussion Paper
ice cliff ablation
of the total ablation
ice cliff ablation of
total sub debris ice ablation
exponential
regression
|
linear regression
through the origin
Discussion Paper
Table 3. Percentage of ice cliff melt off total ablation and sub-debris ablation respectively.
|
Discussion Paper
69
|
5323
Discussion Paper
|
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|
Discussion Paper
|
70
|
5324
Discussion Paper
Fig. 1. (a) The location of the Koxkar glacier in western China. (b) An orthoimage in black and
white of the debris covered glacier, including the position of the AWS and the profile A–A .
Discussion Paper
|
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|
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|
71
|
5325
Discussion Paper
Fig. 2. Degree day factors of individual stakes plotted against debris cover thickness. The
2
black line represents the empirical equations used in the ablation model. R – coefficient of
determination and S – standard error of the regression.
Discussion Paper
|
Discussion Paper
|
Discussion Paper
|
5326
|
72
Discussion Paper
Fig. 3. (a) Overview of the study area with glacier outlines. (b) Detail of the glacier tongue. Ice
cliffs and supraglacial lakes have been mapped manually.
Discussion Paper
|
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|
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|
73
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5327
Discussion Paper
Fig. 4. Debris cover thickness (DCT) vs. ASTER LST with three different regression methods.
2
R – coefficient of determination and S – standard error of the regression.
Discussion Paper
|
Discussion Paper
|
Discussion Paper
|
Fig. 5. (a) Debris cover thickness distribution derived from LST for the exponential regression
(coefficients as in Fig. 4). (b) Difference in DCT for the linear regression through the origin
relative to the exponential regression. (c) Difference in DCT for the power law regression relative
to the exponential regression.
Discussion Paper
74
|
5328
Discussion Paper
|
Discussion Paper
|
Discussion Paper
|
Fig. 6. (a) Distribution of total ice ablation for the exponential regression during the time span
of 1 May 2010 to 31 October 2010. (b) Difference in ablation for the linear regression through
the origin relative to the exponential regression. (c) Difference in ablation for the power law
regression relative to the exponential regression.
Discussion Paper
75
|
5329
Discussion Paper
|
Discussion Paper
|
Discussion Paper
|
Fig. 7. Sum of ablation for the time span of 1 May 2010 to 31 October 2010 for different debris
cover thickness regressions.
Discussion Paper
76
|
5330
Discussion Paper
|
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|
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|
Fig. 8. Distribution of ice ablation for the time span of 1 May 2010 to 31 October 2010. (a)
debris covered Koxkar glacier using the exponential regression (b) imaginary bare ice glacier.
Discussion Paper
5331
|
77
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|
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|
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|
5332
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78
Discussion Paper
Fig. 9. DEM (grey line), ice ablation (blue line) and subdebris ablation (black line) along the
profile A–A (Fig. 1) for the exponential regression of debris cover thickness.
Chapter 6
Conclusions and Outlook
The current chapter refers to the publications included in the presented thesis. It
consolidates the discrete conclusions of the individual academic papers and contains
consequences that derive from the results. Hence, it provides an outlook and suggestions for future studies.
The ablation of debris covered glacier ice depends on the meteorological conditions
and the properties of the supraglacial debris cover. The effects of lithology and grain
size on melt rates underneath supraglacial debris mantles are significant for the ablation on debris covered glaciers. The thermal conductivity is the most suitable
parameter to represent the thermal properties of the debris. This bulk parameter
summarizes the rock type itself, but also the porosity of the layer and the filling
of the pore volume. The field experiments on the Vernagtferner affirm the dependence of the subdebris ice melt on the layer thickness. Highly porous Tephra covers
provide more insulation due to more air inclusions and therefore less heat transfer
than a more dense material. Higher porosity also leads to a higher potential saturation. Due to the displacement of the air inclusions by water, thermal conductivity
increases and more heat can be transported to the debris/ice interface. Higher melt
rates are the consequence.
Debris covered glaciers are a prominent feature in remote regions like the Tien Shan,
the Himalaya or the Karakoram. Often these glaciers are difficult to access and field
work is time consuming and expensive. Therefore remote sensing is a suitable tool
for monitoring debris covered glaciers, but the determination of the extent of these
glaciers introduces new challenges. The surface of debris covered glacier tongues and
the surrounding rock material are difficult to discriminate from each other. Thermal
infrared images can be utilized for surface classification, but are restricted with current remote sensing applications. Depending on the acquisition time of the image
and the prevailing meteorological conditions, the thermal difference between the a
79
80
Conclusions and Outlook
supraglacial and a periglacial surface can be well pronounced or barely discernible.
For the estimation of debris cover thickness distribution from remote sensing data
field measurements are needed to derive an empirical relationship between surface
temperature and debris thickness. To answer the question at which depth of moraine
cover no thermal difference between ice cored and non ice cored surfaces exist, a numerical surface energy balance model was tested on the Vernagtferner. Utilizing the
difference of day and night surface temperatures to investigate the thermo-physical
signature of different surface classes seems promising. However, two satellite images
of the same day are required for this, which in practice can not be accomplished
with satellite systems currently available.
To quantify the ablation processes on a debris covered glacier, a distributed ablation
model has been developed and applied to the Koxkar glacier in the Aksu catchment.
Ice cliffs play a significant role but not as substantial as stated by other authors.
The downwasting behaviour of the debris covered glacier terminus due to negative
mass balance and climate warming can be explained by the fact, that melt rates
are highly restricted beneath debris of more than approximately 10 cm in thickness.
The shielding effect of the moraine cover dominates over the temperature and elevation dependence of the ablation in comparison to a bare ice glacier. Reduced
melt rates highlight the serious implications with regard to runoff modelling from
debris covered glaciers. The comparison of total ablation amount from a debris free
and a debris covered glacier underlines the importance to include debris cover into
discharge modelling. Taking into account that debris cover has a major impact on
predictions of fresh water availability and sea level rise much research remains to
be done. The representation of debris covered glacier parts in hydrological models is still an unsolved problem. By implementing the presented ablation model
(Chapter 5) into a conceptual runoff model, an improved version of the HBV-ETH
model (Mayr et al. in preparation), capable to reproduce runoff from moraine covered glaciers will be created. Moreover, runoff scenarios for changing climate and
glaciation conditions can be realized. Results from regional and local climate modelling with the models REMO and FOOT3DK (AKSU TARIM-CLIM) will serve as
input for the improved HBV-ETH model version, allowing to run the model with
the output of sophisticated climate modelling.
Appendix A
Visual fieldwork impressions
Fieldwork Vernagtferner (Ötztal Alps, Austria):
Figure A.1: (a) Ursula Blumthaler and Anna Wirbel sieving debris material (17 June
2010). (b) Entire test site at the tongue of the Vernagtferner (30 June 2010).
Figure A.2: (a) Test site four weeks after installation (20 July 2010). In comparison to
the bare ice the differential ablation is clearly visible. (b) Setup of the test site for the
thermal infrared camera experiment (15 September 2010).
81
82
Visual fieldwork impressions
Fieldwork Koxkar Glacier (Xinjiang Uyghur Autonomous Region,
China):
Figure A.3: Heavily debris covered terminus of the Koxkar Glacier. Photos: Han
Haidong, 12 August 2010.
Figure A.4: Supraglacial lake and adjacent ice cliffs before (10 August 2010) and after
the outburst (19 August 2010) of the pond.
83
Figure A.5: (a) Installing ablation stakes in the upper part of an ice cliff (12 August
2010). (b) Ablation stakes on ice cliffs surrounding a former supraglacial lake (18 August
2010).
84
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Acknowledgments
I am genuinely thankful to my supervisor, Christoph Mayer, whose encouragement,
guidance and support from the initial to the final level enabled me to develop an
understanding of the subject. I feel privileged to have had the opportunity to learn
from him, not only concerning science but also on a personal level. Thank you for
giving me the liberty to work in my own way, for your valuable time, and for always
lending me an ear when I needed help.
I am grateful to the staff of the Commission for Geodesy and Glaciology at the
Bavarian Academy of Sciences and Humanities for the support and their helping
hand. Thanks for providing me the working environment and the fruitful and often
funny discussions during tea breaks.
Thanks also to my colleagues from the Department of Geography at the LudwigMaximilians-University in Munich, who lent a helping hand when it came to
fieldwork and always provided stimulating discussions. The debriefing session with
you after meetings always cheered me up and encouraged me to stick with it.
I also would like to thank Dr. Michael Kuhn, who is a passionate scientist and
an outstanding professor. He promoted my enthusiasm for natural science since I
started my studies. Furthermore I would like to thank the staff and my colleagues
at the Institute of Meteorology and Geophysics at the University of Innsbruck. I
always felt very welcome and I enjoyed the beneficial discussions that helped me to
progress with my work.
I would like to express my sincere thanks to Dr. Uli Wetzel who offered me the
great opportunity to work at the Inylchek glacier in Kyrgyzstan. It has been
a pleasure to collaborate with the people from the German Research Centre
for Geosciences (GFZ) in Potsdam and the Central-Asian Institute for Applied
Geosciences (CAIAG). I also acknowledge Maria Shahgedanova from the Walker
Institute for Climate System Research, University of Reading, UK. She provided
two meteorological stations for the experiments at the Vernagtferner.
I owe my deepest gratitude to my family for all their love and encouragement.
91
92
Marita, you are one of a kind, thanks for your support and for your love.
Lastly, I offer my regards to the Deutsche Forschungsgemeinschaft (MA 3347/4-1),
the Austrian Academy of Science and the Bavarian Ministry of Environment for
the funding of my work.
Curriculum Vitae
Martin Juen
Josephsburgstr. 94a
D-81673 Munich
Born on 23rd of March 1980 in Zams,
Austria
[email protected]
Education:
2010–2013
Research assistant and Ph.D. student in the group of Dr. C. Mayer
at the Commission for Geodesy and Glaciology. Bavarian Academy of
Sciences and Humanities. Munich (Germany).
2008–2010
Diploma thesis under the guidance of Dr. A. Fischer, Institute of
Meteorology and Geophysics, University of Innsbruck: Laserscanmessungen zur Bestimmung der Ablation im schuttbedeckten Teil des
Hintereisferner.
2004–2010
Diploma study at the University of Innsbruck (Austria). Master of
Natural Science (Magister rerum naturalium) in Meteorology.
1994–1999
Hoehere Technische Lehranstalt für Tiefbau. Innsbruck (Austria).
Matura.
1990–1994
High School – Bundesrealgymnasium. Landeck (Austria).
1986–1990
Elementary School – Volksschule. Flirsch (Austria).
93
94
Vocational Experience:
2002–2004
Compilation of specification, call for tenders and construction supervision. Architekturbüro Falch. Landeck (Austria).
2001–2002
Basic and detailed planning of cellular phone network transmitting
stations. ProCad. Innsbruck (Austria).
2000–2001
Basic and detailed planning of cellular phone network transmitting
stations. Abel Kommunikationstechnik. Zirl (Austria).
1999–2000
Alternative civilian service. Rotes Kreuz Bezirksstelle Landeck (Austria).
technical skills:
Languages
German: native speaker. English: fluently written and spoken. Spanish: basic knowledge.
Computer
skills
Windows and Linux OS, Microsoft Office and Open Office, CAD software, GIS software, Matlab, Polyworks.
since 1998
Member of the mountain rescue team – Flirsch.
Training courses:
Regular Student at the Summer School Karthaus 2011. Ice Sheets and Glaciers in
the Climate System, organised by Hans Oerlemans, IMAU, Utrecht.
List of presentations
Posters:
Juen, M. and A. Fischer, 2010: Laserscan measurements to determine the ablation
at the debriscovered part of the Hintereisferner. Alpine Glaciology Meeting 2010,
February 2010, Milan, Italy.
Juen, M., C. Mayer, E. Mayr, A. Lambrecht, W. Hagg, H. Haidong and L. Shiyin,
2011: Ablation and runoff generation on debris covered Keqikar glacier in the upper
Aksu catchment, China. European Geosciences Union Vienna, April 2011, Vienna,
Germany.
Mayer, C., A. Lambrecht, K. Eder, M. Juen and L. Qiao, 2012: Ice cliff ablation
derived from high resolution surface models, based on close-range photogrammetry.
European Geosciences Union Vienna, April 2011, Vienna, Germany.
Juen, M., E. Mayr, W. Hagg and C. Mayer, 2011: Present and future runoff
generation on debris covered glaciers in the upper Aksu catchment, China. 21.
Jahrestagung des Arbeitskreises Hochgebirge – Interaktionsraum Hochgebirge.
Herausforderung für die Wissenschaft, February 2012, Munich, Germany.
Juen, M., C. Mayer and K. Eder, 2012: Determination of debris cover surface
temperature using infrared thermography. Alpine Glaciology Meeting Zürich,
February 2012, Zürich, Switzerland.
Lambrecht, A., M. Juen, A. Wirbel, C. Mayer, U. Küppers, L. Seybold and M.
Shahgedanova, 2012: Ice melt underneath a supra-glacial debris cover: interactions
between meteorology and debris properties based on field experiments. European
Geosciences Union Vienna, April 2012, Vienna, Germany.
95
96
Oral presentations:
Juen, M. and E. Mayr, 2010: Modellierung von Schmelze und Abfluss in einem
Einzugsgebiet mit schuttbedeckten Gletscherteilen. Seminar Meteorologisches
Institut München, December 2010, Munich, Germany.
Juen, M., C. Mayer, E. Mayr, A. Lambrecht, W. Hagg, H.Haidong and L. Shiyin,
2011: Ablation model design on debris covered Keqikar glacier in the upper Aksu
catchment, China. Alpine Glaciology Meeting Munich, February 2011, Munich,
Germany.
Juen, M., C. Mayer, A. Lambrecht, A. Wirbel and U. Küppers, 2012: Field
experiments to assess the effect of lithology and grain size on the ablation of debris
covered glaciers. European Geosciences Union Vienna, April 2012, Vienna,
Austria.
Leopold‐Franzens‐Universität In
nnsbruck klärung
Eidessttattliche Erk
Ich erklläre hiermitt an Eides statt durch
h meine eigenhändige
e Unterschriift, dass ich die
vorliegende Arbeit selbständig
s
verfasst un d keine and
deren als die
e angegebeenen Quellen und
Hilfsmitttel verwende
et habe. Alle
e Stellen, di e wörtlich oder inhaltlich den angeggebenen Qu
uellen
entnomm
men wurden
n, sind als so
olche kenntl ich gemacht.
Die vorliegende Arb
beit wurde bisher
b
in gle
eicher oder ähnlicher Fo
orm noch niicht als Mag
gister/Master--/Diplomarbe
eit/Dissertattion eingereiicht.
D
Datum
Unterschririft
97

Ablation on debris covered glaciers

Transcrição

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