State of the glaciers in the Hindu Kush- Himalyan region

Transcription

HighNoon
Technical Report No 1.9
Report on the current distribution of glaciers in the
Hindu Kush - Himalayan Region
S P E C I M EN
Please insert your images
Authors: University of Geneva, Marlene Scheel with contributions from Holger Frey
and Tobias Bolch
Date: (11-11-11)
HighNoon
Project No 227087
HighNoon is an Integrated Project funded by the European Commission under the 7th
Framework Programme, Theme 6: Environment, including Climate Change.
Contract number: 227087
The HighNoon project started on 1 May 2009 and will continue for three years.
Title
Author(s)
Organization
Deliverable
Number
Submission date
Report on the current distribution of glaciers in the
Hindu Kush - Himalayan Region
Marlene Scheel
Holger Frey
Tobias Bolch
University of Geneva, Switzerland
1.9
11-11-11
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1. INTRODUCTION
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THE HINDU KUSH-HIMALAYA: REGIONAL SETTING
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2. METHODOLOGY
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GLACIER AREAS OF THE ENTIRE HKH REGION - THE HKH COMPILED GLACIER INVENTORY
INVENTORY SOURCES AND ITS ADVANTAGES AND DISADVANTAGES
Remotely sensed glacier outlines
Glacier mapping from topographic maps
Topographic glacier features
GLACIER VOLUMES
Area Volume scalings
MEASUREMENTS OF CHANGE
Mass balance
Volume
Area
Length and terminus position change
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3. GLACIERS IN THE HINDU KUSH HIMALAYAN ARC - CURRENT DISTRIBUTION IN AREA
AND VOLUME
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HINDU KUSH AND KARAKORAM
Hindu Kush
Karakoram Range
KARAKORAM AND HIMALAYA
HIMALAYAN RANGE
Western and Central Himalaya
Western Himalaya
Central and Eastern Himalaya
Central Himalaya
Eastern Himalaya
3. 1 CONCLUSIONS ON THE CURRENT DISTRIBUTION OF GLACIERS IN THE HKH
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4. OBSERVED CHANGES OF HINDU KUSH - HIMALAYAN GLACIERS
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4.1 AREA CHANGE
Hindu Kush & Karakoram
Himalaya
Conclusion Area Changes
4.2 VOLUME CHANGES
Himalaya
Conclusions Volume changes
4.3 MASS BALANCE
Hindu Kush
Karakoram
Himalaya
Conclusions mass balance
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4.4 ADDITIONAL INFORMATION
Hindu Kush
Karakoram
Surges in the Karakoram
Langtang Himal
Kachenjunga Himal
Khumbu Himal
Bhutan Himal
Debris Cover
4.1 CONCLUSIONS GLACIER CHANGES
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GENERAL CONCLUSIONS
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REFERENCES
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ANNEX 1
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Figures
Figure 1: The Hindu Kush-Himalayan Arc
Figure 2: Atmospheric circulation over Central Asia and HKH modeled precipitation estimate maps
Figure 3: HKH glacier sub-regions
Figure 4: Map of the HKH presenting the regionally integrated inventory sources of the HKH inventory
Figure 5: Glacier area in the Hindu Kush based on the HKH inventory
Figure 6: Glacier area in the Karakoram based on the HKH inventory.
Figure 7: Inventory coverage of Cogley (2011) indicated by thin black line.
Figure 8: Glacier map of Bhagirati basin, Garhwal Himal from the Inventory of Himalayan Glaciers
Figure 9: Inventory coverage of the new GlobGlacier inventory part in Western and central Himalaya
Figure 10: Glacier area in the Western Himalaya based on the HKH inventory
Figure 11: North India with the location of basins used to monitor snow cover and to estimate glacier retreat
Figure 12: Glacier area in the Central Himalaya based on the HKH inventory
Figure 13: Glacier area mapped in the Upper Bhagirati and Saraswati/ Alakanda basins
Figure 14: Glacier area in the Eastern Himalaya based on the HKH inventory
Figure 15: Mean glacier sizes in the HKH sub regions
Figure 16: Mean elevation of glaciers in the HKH sub regions
Figure 17: Minimum elevation of glaciers in the HKH sub regions
Figure 18: Locations of area change assessments in the Western Himalaya.
Figure 19: Locations of area change assessments in the Central Himalaya.
Figure 20: Locations of area change assessments in the Eastern Himalaya.
Figure 21: Area change studies for glacier areas across the HKH region.
Figure 21: The longest glacier of the HKH Region: Siachen glacier
Figure 22: Annual mass balance distribution with altitude
Figure 23: Available mass balance data for glaciers across the HKH region
Figure 24: Terminus changes from 2000 to 2008 across the HKH determined with remote sensing.
Figure 25: Central Karakoram range with glacier change indication by Hewitt, 2005.
Figure 26: Flow velocities of selected glaciers in the Bhutan Himalayas.
Figure A1: Ranking scheme for quality assessment of the identified investigations in the HKH region
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Tables
Table 1: Estimates of glacier extent in the Hindu Kush- Himalayan region
Table 2: Estimates of glacier extent in the Hindu Kush
Table 3: Estimates of glacier extent in the Karakoram
Table 4: Estimates of glacier extent in the Karakoram and Himalaya
Table 5: Estimates of glacier extent in the Himalaya
Table 6: Glacierized areas of the Map of Glacier Resources in the Himalayas
Table 7: Glacier inventory data of The Inventory of Himalayan Glaciers
Table 8: Glacierized area and number of glaciers in selected basins of the Western Himalaya
Table 9: Topographic glacier parameters in the HKH sub-regions
Table 10: Ice volume estimates for the HKH based on the HKH inventory areas
Table 11: Area change studies and results in the HKH region
Table 13: Mass balance data for the HKH region
Table 14: Specific mass balances of glacier areas of the Himalayan range
Table 15: Observed characteristics and changes of Karakoram glaciers
Table 16: Glacierized areas in the Hindu Kush - Himalayan region
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1. Introduction
The mountains of southern Central Asia, arching over 2400 km (Qin, 1999) from Afghanistan to
eastern India and China built the origin for massive ice masses, flowing downstream from these
highest elevations on Earth. Glacierized basins form the headwaters of almost all the major rivers in
the central, south, and south-east Asia mainland (Armstrong, 2010). The ice extension and volume of
this so called third pole is of high interest at present stage and under future climate conditions.
Glaciers are considered as the best natural indicators of climatic change (IPCC, 2007). The
understanding of their reaction to past and current climate conditions gives important insights in the
actual manifestation of climate change in this region which is characterized by little gauge network
coverage. Glacier work as water storages and their meltwater provide an additional fresh water source
to downstream living populations, not only in the dry seasons of the year. The amount of future run
off from these glacierized basins is important in terms of power production and food security of large
populations.
The aim of this report is to resume the current state of knowledge about the Hindu Kush Himalayan glacier distribution and to identify possible patterns of glacier change. This goal needs to
be approached very carefully and precisely. Firstly, because the recent propagation of an error related
to this topic (Cogley et al., 2010a) and the following public polemic lead to a certain damage of the
scientific credibility. And secondly, because the quality of the investigations in terms of methodology
and its documentation varies very strongly and uncertainty is generally high.
The overall assessment of the state of HKH glaciers is a challenging task due to the relatively little
information and investigations carried out for such a large area, and studies cover different time spans
and locations of this very wide region. The studies often provide ´snapshot´ insights to the Asian
cryosphere, captured with different parameters so that results are difficult to link to each other and to
draw general conclusions from. Deriving general regional patterns of these point insights can be
incautious and misleading in this heterogeneous terrain.
The progress in remote sensing and geographic information system (GIS) science are very
promising for the compilation and completion of inventories and assessments of large glacier areas.
Furthermore, the broader spatial coverage increases the regional representativeness of results and
allows the identification of changes and their regional patterns and trends.
In the following chapters the current state of knowledge of the Hindu Kush - Himalayan glacier
distribution will be presented. Where overall assessments exist, they will be presented first. Then the
degree of detail increases with further regional or sub basin wide inventories. At the end of the
regional chapters, conclusions are drawn and in the overall conclusion of this chapter, parallels and
differences to the other regions are identified and discussed in terms of glacier distribution and
topographic parameters among regions.
In a second part, changes and trends in glacier behavior in the HKH region will be presented,
where reported and an attempt to identify patterns in glacier change will be presented. The regional
characterization of glacier changes should give an indication on how the current distribution will be
modified in the future. Possible explications of differences in glacier change will be presented and
discussed.
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The Hindu Kush-Himalaya: Regional Setting
This report concentrates on the glaciers of the Hindu Kush Himalayan (HKH) region, including the
Himalayan range, the Karakoram and the Hindu Kush. Mountain chains of northern Central Asia as
for instance Pamir and Tien Shan are excluded, as well as glaciers distributed over the Tibetean
Plateau because of the strongly differing settings in this continental climate. The macro-scale arcshape of the HKH mountains results in higher latitudes in the western parts, e.g. the Karakoram and
Hindu Kush, than the central and eastern Himalaya, resulting in lower temperatures and generally
lower radiation. Figure 1 shows the location of the investigation area.
Figure 1: The Hindu Kush-Himalayan Arc
The ice masses of the Hindu Kush, Karakoram and Himalaya are mainly concentrated in and
around marked peaks and outstanding massifs like the Nanga Parbat, the Nanda Devi group, the
Dhaulagiri massif, the Everest-Makalu group, the Kanchenjunga, the Kula Kangri area, and the
Namche Barwa and for instance the K-2 region of the Karakoram with its very large glaciers
(Hasnain, 2000).
The Central Himalaya of Nepal and the Karakoram built two regional centers, which concentrate
the highest elevations on Earth, separated by the Indus, Gilgit, and Shyok Rivers with approximately
150 km of lower elevation terrain in between them. Both massifs have a general southeast-northwest
direction of the main ranges. The topographic and climatic characteristics of these two regions are
very different, however, resulting in different glacier characteristics. While the Karakoram glaciers
are often interconnected to large glacier systems, the Himalayan glaciers often appear individual
(Higuchi et al., 2010).
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Across the HKH mountains, a large climate variability exists. Due to its height, the mountain
ranges act as obstacles in the atmospheric circulation (Eriksson et al., 2009). In the summer months
the monsoon brings large precipitation amounts from the Gulf of Bengal, reaching first the Himalayas
in its easternmost fringes (see Figure 2a and c). Its progression towards northwest is drawn by a
precipitation gradient with decreasing intensities and amounts from southeast to northwest (Mool et
al., 2001b). In the eastern Himalayas the monsoon season lasts from March to October (8 months)
while in the Western Himalayas it is concentrated on 2 month, July to August (Chalise and Khanal,
2001 in Eriksson et al., 2009).
During the winter months, atmospherical
circulation brings moisture through the
westerlies, this time with dominance in the
western HKH region, in the Hindu Kush and
Karakoram, as Figure 2a and b illustrate.
Considering the total amount though,
monsoonal summer precipitation makes the
largest part of annual precipitation. The
portion generally decreases towards the west,
but local influence is strong and often
superimposed on the general atmospheric
circulation.
Figure 2: a) Atmospheric circulation over Central
Asia with the Karakoram and Himalaya outlined in
green and HKH modeled precipitation estimate
maps of b) January and c) July.
Precipitation data courtesy of J. Böhner;
Böhner et al., 2008
Highest precipitation intensities can be
found on the southern slopes of the east-west
stretching Himalayan main range due to
orographically forced ascension of moisturecharged air (Bookhagen and Burbank, 2006)
This phenomena results in a second
precipitation
gradient
with
decreasing
precipitation northwards towards the more arid
Tibetan plateau. The northern slopes of the
Himalaya are dominated by an arid-cold
regime, where permafrost and thus permafrost
glacier interactions are common (Frey et al.,
submitted).
2b)
2c)
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On the basis of precipitation patterns, different glacier regions can be distinguished. There are the
monsoon dominated regions in the east as for instance the Bhutan Himal, Sikkim and the Khumbu
Himal including Mt. Everest (also Qomolangma or Sagarmatha). In the Western Himalaya, dominant
winter precipitation regime under the westerlies influence can be found (Vohra, 2010). Here, twothirds of high-altitude snow accumulation occurs in winter (Hewitt et al., 1989 for Central
Karakoram). In between a broad transition zone is situated, thus alternately influenced by the
monsoon in summer and the westerlies in the winter. The rate of influence vary within this type and
the exact extension of the transition zone is not defined as changes are rather gradual than sudden. In
contrast to Vohra (2010), the Western Himalaya is considered as a transition zone in between
westerlies and monsoon dominated regions by Wagnon et al. (2007) and Mayewski & Jeschke (1979).
The Karakoram is seldom reached by the monsoon (Rees and Collins, 2006) and can be classified as
westerly dominated. The transition zone thus means gradual change of climatic influence in between
the Central Himalaya and the Karakoram range.
The precipitation distribution in combination with radiation characteristics also led to a glacier
classification by accumulation season. Ageta and Higuchi (1984) first characterized the summer
accumulation type of glaciers, which shows synchronous ablation and accumulation through the
summer monsoon season. On the other hand the respective type for the westerlies dominated regions
exists, where winter accumulation dominates and let some authors suggest similarities to the glaciers
of the mid-latitudes.
Additional to these glacier regions determined by the dominant atmospheric circulation, a rain
shadow type also exist (Vohra, 1981 cited in Vohra, 2010). Due to the strong topography, local
climate is often dominating the influence of the atmospheric circulation. Through orographic and
leeward effects, extremely dry inner valleys can co-exist to adjacent mountain slopes receiving much
more precipitation (Eriksson et al., 2009).
Precipitation often increases with elevation (Vohra, 2010). Usually a zone of maximum
precipitation can be observed (Hewitt et al., 1989). In the west, arid conditions dominate at lower
elevations, especifically in the valleys (Rees and Collins, 2006). Here extreme vertical precipitation
gradients can exist, as for instance in the Karakoram. While the lower elevation zones below 3500 m
show arid characteristics (150-300 mm), precipitation increases strongly to ~1500 mm above 5000m
a.s.l. (Hewitt et al., 1989), resulting in an “atypical high zone of maximum precipitation” between
~5000 - 6000 m a.s.l (Hewitt, 2005).
The pronounced vertical precipitation gradients imply that gauges which are usually installed in
the valleys for logistical reasons and which are commonly scarce at higher altitudes cannot provide a
representative estimate of the precipitation actually occurring on the glaciers situated in the upper
parts (Eriksson et al., 2009). The situation is complicated by the often non-steady gradients which
make simple interpolation difficult. In other parts of the HKH region, as for instance the Khumbu
Himal, rather weak altitudinal precipitation gradients are observed (Benn and Lehmkuhl, 2000).
Some studies report that actual accumulation is occurring mainly through avalanches rather than
through direct precipitation on the glacier. For Khumbu glacier in Eastern Nepal for instance, the
amount from avalanches is about twice as high than from direct snowfall (Inoue, 1977 in Bolch et al.,
2008).
The study area has been divided in sub-regions to enable the distinction of regional patterns in
glacier distribution and behavior. Climatologic, hydrologic and geologic aspects define the HKH subregions presented in Figure 3.
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Figure 3: HKH glacier sub-regions
The particular settings of the HKH mountain region pose some difficulties to data acquisition for
any kind of method applied. The rough topography characterized by steep vertical gradients, the
highest elevations on Earth and political issues in some parts limit not only field accessibility but also
introduces some challenges to remotely sensed data. Cast shadow in this steep terrain and frequent
orographically induced clouds especially on the southward slopes of the Himalayan main range limit
the applicability of automated glacier delineation algorithms (Frey et al., submitted; Racovitenau et
al., 2008). Debris cover on glaciers furthermore shows different radiospectral characteristics than
clean ice and hence makes the accurate manual delineation of glacier borders even for the very
experienced eye difficult. Further complications are introduced by permafrost-glacier interactions,
especially important in the northwestern parts of the HKH region, where arid-cold conditions are
prevalent (Frey et al., submitted).
2. Methodology
The current distribution of glaciers in the HKH region will be assessed by the presentation of
glacier areas and ice volumes divided in sub regions, presented in Figure 3.
Until present, no consistent glacier inventory for the entire HKH region exists. Various regional
inventories have been compiled and will be presented below. The existing inventories show differing
data formats, regional extents, and varying time spans of observation. The levels of accuracy are of a
wide range. Furthermore, low transparency considering the data sources, data acquisition, and
processing, and often absent accuracy and error analysis hinder the quantification of their particular
uncertainty.
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Within this project a composition of glacier areas for the entire Hindu Kush, Karakoram and
Himalaya mountain ranges has been complied. This data set sums the best available glacier data for
each location, selected from a range of different sources. In some regions where no or very low
quality data exist, completely new inventories were created based on remote sensing techniques and
included in the compiled data set, for instance in the Western Himalaya (Frey et al., submitted) and
the Karakoram. The composition represents the best overarching spatially consistent data set of the
HKH glaciers and hence builds the core of the assessment of the current distribution. Volume
estimates based on the inventory will be provided. As no ground measurements can validate the large
area samples and provide an error indication, different approaches of area-volume scaling have been
applied to decrease the uncertainty. The comparison of results achieved by different approaches
increases the representativeness and reliability of the results and shows through the differing results
the high uncertainty which has to be taken into account .
Glacier areas of the entire HKH region - the HKH compiled glacier inventory
The new HKH glacier inventory (in the following named HKH inventory and cited as Frey, 2011)
provides glacier outlines covering the entire investigation area from the Hindu Kush over the
Karakoram and the Himalayas. It is composed of different input data sets, namely the GlobGlacier
inventory of northwestern India (see also detailed description under the Western and Central
Himalaya section in Chapter 3), the Global Land Ice Measurements from Space initiative (GLIMS)
database (Raup et al., 2007), and several regional inventories of the International Centre for Integrated
Mountain Development (ICIMOD) of different ages (ICIMOD, 2007; Bajracharya et al., 2011). In
these regions, the GLIMS data base consists mostly of data from the first Chinese glacier inventory
(Shi et al., 2010) and is of heterogeneous and generally slightly lower quality than the other glacier
data used. The GLIMS data base provides digital single glacier outlines with information about the
altitudinal extension, length along the center line and other parameters. In many cases additional meta
data of the method used to derive the presented data is offered (Frey, 2011). Some minor parts in the
northwestern Hindu Kush have been filled with data of the Digital Chart of the World (DCW) which
is of rather low quality as it provides no individual glacier outlines. The most of the Hindu Kush part
of the inventory is composed by GLIMS data with additional own mapping performed within the
High Noon project (Holger Frey, personal communication, 2011).
Accuracy and quality of the different input data sets were assessed based on satellite imagery and
by overlay in GoogleEarthTM (Frey, 2011). Where available the best ranked data source, the
GlobGlacier inventory, builds the inventory. Outside of its reach, mainly outside the Western
Himalaya, the ICIMOD data fills the gap. GLIMS data was used in cases where no other source was
available, mainly on the northern slopes of the Himalayas and the northeastern part of Karakoram.
The majority of the glacier outlines in the Karakoram origin from ICIMOD data, which was also used
in the Central and Eastern Himalayas (ICIMOD, 2007). Newer ICIMOD inventories of 2008 and
2009 are available for Nepal (Bajracharya et al., 2011).
The map in Figure 4 illustrates the distribution of input sources merging to the spatially consistent
inventory over the entire HKH region. The map can also be interpreted as an overview of regional
data quality distribution
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Figure 4: Map of the HKH presenting the regionally integrated inventory sources of the HKH
inventory
Inventory sources and its advantages and disadvantages
Remotely sensed glacier outlines
The use of remote sensing for glacier mapping is widely recognized (Paul, 2010, Racovintenau et
al., 2010) and can provide very good results, if limitations are well taken into account.
The quality of the base image is directly influencing the accuracy of the mapped glacier outlines.
Resolution hence plays an important role but also the time of image acquisition. In the HKH region,
best period for glaciological purposes is September. This is the end of the ablation period and
commonly before the first snowfall. Also the daytime plays a role. Higuchi et al. (2010) state that for
Nepal, image acquisition by LANDSAT takes place in the morning hours due to orbital parameters.
The mapping of detailed features on western slopes of these images is complicated by the strong
shadow at this time of the day. Orographic clouds also hinder the mapping in the investigation area,
especially on the southern slopes of the main range (Frey et al., submitted).
The delineation of individual glaciers out of glacier ensembles is a challenging task as well and at
the same time indispensable for a range of applications, such as area volume scaling (see below) or
the calculation of topographical parameters. The determination of the ice divide is indispensable for
this task but represents a challenge even to experienced glaciologists and is somehow submitted to
subjectivity. This difficulty and subjectivity may partly explain inconsistencies in the total amount of
glaciers identified in the different inventories and data bases.
A special issue in the HKH region are debris covered glaciers. These are very common throughout
the region, but especially concentrated in the Karakoram and Central Himalaya south of the main
ridge (Scherler et al., 2011). While on one hand they react differently to climate signals than their
clean-ice equivalents, they show also differing radio spectral characteristics. The optical sensors do
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not detect ice under a thick debris cover and therefore automate mapping is not possible or leads to
large errors. Manual delineation of large sample sizes as in the investigation area is very time
consuming and thus a set of semi-automated methods has been developed (Paul, 2010). Difficulties
still persist though and reduce the accuracy of mapped glacier areas (Racovitenau, 2008; Bhrambi et
al., 2011).
Even manual delineation can be impossible when bad conditions such as high solar elevation exist
(Paul, 2010). This topic is of special concern as debris-covered glaciers exhibit different
characteristics and behavior than clean ice glaciers. The categorical miss-mapping of their features
would lead to lacking or erroneous process comprehension and estimates.
In combination with permafrost, the delineation of debris-covered glaciers is further complicated
because of the similarity in debris covered glacier features in the lateral and front parts with
permafrost influenced shapes as e.g. push moraines. For this reason, the uncertainty assigned to
glacier outlines in the cold-arid regions in the northern and northwestern parts of the investigation
areas is higher (Frey et al., submitted).
Glacier mapping from topographic maps
When inventories provide glacier outlines which are not derived through remote sensing, they
consist commonly in analogue topographic maps based on field surveys or aerial photographs. The
accuracy of the delineated glacier outlines can only be as good as the map, therefore the knowledge of
the scale and source of the base map is important for quality assessment of the resulting glacier areas.
When this information is not given for a certain inventory, the reliability has to be classified as lowest.
Unfortunately high discrepancies in map quality and in the representation of glacier features in the
maps exist in the HKH region. Vohra states in 1980 that “the Survey of India (SOI) has produced
accurate maps of topography from the aerial photographs but the same, unfortunately, cannot be said
of the ice cover”. Unfortunately, these maps are still in use (e.g. Kulkarni et al., 2007; Mool et al.,
2001) as they provide a long-term comparison and thus allow the assessment of glacier change. Most
of glacier change studies in the Indian Himalaya are based on the comparison of such maps (SOI)
from the 1960s with satellite data (Bhrambi et al, 2011), and commonly do not provide an assessment
on the accuracy of the basemap. Bhrambi and Bolch (2009) revealed large inaccuracies in the maps of
SOI and Geological Survey of India (GSI) and give a comprehensive overview on glacier mapping in
the Himalayas since ~1850 and related accuracy problems. Cogley (2011b) describes inaccuracies in
regional glacier inventories for the HKH region based on topographic maps and finds dislocations of
glaciers by up to 3 to 10 km. In India, the situation is especially bad in Himachal Pradesh (Bhrambi
and Bolch, 2009; Cogley, 2011b). For other countries such accuracy investigations of glacier maps are
not available, but similar inaccuracies may be likely.
Topographic glacier features
To derive the topographic characteristics of each glacier and subsequent regional analysis, the
glacier outlines are overlaid to a digital elevation model (DEM) and analyzed within a GIS
environment. For this analysis the hole-filled SRTM (Shuttle Radar Topography Mission) DEM
version 4.1 from February 2000 with about 90 m spatial resolution between 60°N and 60°S (Jarvis et
al. 2008) is used for the calculation of geometric glacier features. A global mean vertical error of
±16m is assigned to the SRTM DEM (Rabus et al., 2003). Paul (2010) compared three DEMs of
differing sources and levels of detail including SRTM for the Swiss Alps and concludes that all three
are suitable for deriving topographic glacier parameters. DEMs generated from radar measurements as
SRTM show data voids due to radar shadow in terrain with strong topography. However, Paul and
Haeberli (2008) state that applications concerning glaciers are not much affected by this problem, due
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to the relatively gentle sloped terrain which usually accommodate glaciers and therefore are less
laying outside the radar shadow.
For each glacier and glacier sub-region (see Figure 3), maximum, minimum and average
elevations are determined. The fraction of glacier area situated above and below the mean elevation
canb e taken as a proxy for the accumulation area ratio (AAR) and hence is included in the analysis.
The AAR is the fraction of the accumulation area above the equilibrium line altitude (ELA) to the
ablation area below the ELA. When the AAR for steady-state conditions of a glacier (or glacier
region; mass balance = 0) is established, its actual estimate can be taken as an indicator for a glacier’s
mass balance for its current state.
Furthermore elevation range and mean slope are calculated. The mean slope is calculated once by
the altitude difference of the highest and lowest glacier point divided by the length (aerial distance). A
second time mean slope is calculated through an ARC GIS algorithm (mean slope), which calculates
the mean slope of each pixel and builds the mean of all these values. The differences between these
two ways to calculate the apparently same parameter are large for larger glaciers. A threshold can be
identified at about 3 km2 size, below which the difference is neglectable. Above this size the results
can be corrected with a regression equation (Bolch et al., in preparation).
The DEM has been quality checked in the investigation area via hillshade views and artifacts like
holes and bumps were revealed. Such errors can have a strong influence on the topographic
parameters minimum and maximum elevation as these values are obtained from a single DEM cell.
For the other parameters the DEM values are averaged over the entire glacier area, and they are thus
less influenced by such artifacts (Frey et al., submitted).
Glacier volumes
Area Volume scalings
Based on the knowledge of the glacier area the volume can be derived making a set of
assumptions. Glacier thickness is inversely related to the slope. That means, more inclined glaciers are
thinner and vice versa. The relationship is expressed by the following equation:
τ = f ρgh sin α
or
h = f( ρg/ τ)(sin α)
where τ is the basal shear stress, ρ is the ice density and g is acceleration due to gravity. f is a
forming factor accounting for the friction on the bed of valley glaciers. For extensive beds, f is equal
to 1. h is the ice thickness and sin α the mean slope.
Under basal shear stress assumptions and the knowledge of the mean slope, an approximated ice
thickness can be computed.
Haeberli and Hoelze (1995) developed an empirical relationship between glacier altitudinal extent
and basal sheer stress based on inventory data from the Alps. A maximum shear stress of τ = 1.5 bar
is assumed for glaciers exceeding 1.6 km in altitudinal extent and has been used for the area-volume
scaling of which the results will be presented in this report.
The area-volume scaling will be applied to all inventoried glaciers for which individual outlines exist.
Two versions of the volume estimates are computed and will be presented. They are based on the
equation presented here above, using once the mean slope calculated over maximum and minimum
glacier height (ΔH) and the total length (approach 1), and once using the GIS environment to plot the
mean slope of all single pixels (approach 2; see also section on Topographic Parameters).
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As explained above, results of the two different approaches are used to account for the lacking ground
truth validation.
Measurements of change
Besides the current distribution of glaciers in the HKH region, observed changes of glaciers and
regional trends in glacier change (growing or shrinking), will be assessed by this report.
There are several parameters which can be used to detect glacier changes. Changes in the glacier
can be reflected by terminus position or length changes, changes in area or volume and the mass
balance, which integrates accumulation and ablation over the glacier; to name the main ones. All these
parameters differ in their ability to adequately measure if a glacier is growing or shrinking.
Furthermore the way a parameter is determined, e.g. the methodology used to estimate the parameter,
influences this ability due to the differing uncertainties assigned to the estimates.
Mass balance
A glacier’s mass balance is the direct and undelayed response to atmospheric conditions (Zemp et
al., 2009). Unlike, for instance, length changes which are governed by a glacier’s response time to the
climate signal, mass balance reproduces the reaction of a glacier to current conditions. Mass balance
is therefore the most representative measure to determine if a glacier is growing or shrinking (Kaser et
al, 2006). To determine a clear trend, the mass balance measurement series needs to be sufficiently
long.
When mass balance is directly measured in the field with glaciological methods, the uncertainty is
lowest in comparison to indirect estimates. The other methods are shortly outlined in the chapter on
mass balance. A disadvantage in the use of mass balance data is the necessity for data extrapolation
when larger glacier systems should be assessed. No completely reliable approach to mass balance data
extrapolation has yet been found (Dyugerov and Meier, 2005). This limits the use of mass balance for
the assessment of larger areas (when not measured for each glacier) and generalizations are incautious
considering the high variability inherent in the region.
Volume
A glacier volume change over time is the second most representative measure to assess if a glacier
is growing or shrinking (Miller et al, 2010). It is difficult though to adequately determine a glacier’s
volume and the possible methodologies often imply high uncertainties. The most common methods to
determine glacier volume in the Himalaya are presented in the section on volume change.
Area
The evolution of area over time is a limited parameter to indicate glacier shrinkage or growth as it
gives no information about potential simultaneous volume changes. An advantage of area changes is
that the estimate accuracy can be very high when employing sound methods and error assessment.
The methods to estimate glacier area are presented in the Area Changes section. The difficulties to
accurately delineate glacier outlines with remote sensing are additionally presented in the
methodology section.
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Length and terminus position change
The change in terminus position is the least representative measure to characterize if a glacier is
shrinking or growing. It indicates if this lowest part of the glacier is advancing or receding, but this
part is not representative for the entire glacier. Bolch et al. (2008) for instance report increasing
accumulation areas time-synchronous to glacier snout retreat in the Khumbu Himal. If only the
terminus position would have been observed, a not reflected result of a study could have been that this
glacier is shrinking. The increase in accumulation area though is a better indicator of the trend in
glacier change. The increase in area in the accumulation area will be translated into an advancing
snout with a delay according to the glacier´s response time.
Furthermore, in the Himalayas glacier shrinkage is often happening as downwasting. This is
especially common for debris covered glaciers (Kargel et al., 2005). Downwasting means that the
lowest glacier part, e.g. the tongue, becomes decoupled from the rest of the glacier and then consists
of stagnant or passive ice. This part then slowly melts, indicated by surface lowering. The snout
position though remains at about the same position. Even if the glacier is significantly shrinking, the
snout position often does not give any indication of this change and would suggest a glacier in its
equilibrium. Furthermore a lot of glaciers in the HKH region are debris covered. Schmidt and Nuesser
(2009) suggest that almost half (>42%) of the glaciers in the Himalayan range are debris covered, and
thus the usefulness of terminus fluctuations as indicators of change for these glaciers is greatly
reduced. Furthermore, in many cases length changes are only measured at the terminus and no
indication of the entire glacier length is reported along with the terminus change. The provided
absolute numbers do not allow comparisons of change rates or classification if the change is rather
large or not relative to the glacier size.
Terminus positions can be measured relatively easily and accurately in the field or with remote
sensing techniques. The mapping problems arising from debris cover are the same as in the
delineation of glacier outlines, described in the section on “Remotely sensed glacier outlines” section.
Being on one hand a relatively limited parameter to describe glacier change, it is relatively simple
to measure and hence a lot of investigations describe terminus positions. More than the half of the
studies included in the review of Miller et al. (2010) about the evidence of glacier growth or shrinkage
across the HKH region consists in terminus position changes.
For the presented reasons, glacier length changes will only included in this report, when a) there
are no studies providing other indicators of change in a certain region and the length measurement
series is considerably long; or b), when anomalous behavior of terminus position has been reported.
This means, when extreme lengths changes are observed over a short period indicating a surge type
movement. Surging glaciers have been reported especially for the Karakoram range (Hewitt, 2005).
Language limitations
This report includes mainly literature in English language. An important contribution in Russian
language has been included for special importance (Dolgushin & Osipova, 1989) as well as the
pioneer work of Von Wissmann (1959) in German. Some studies are reported in other languages and
unfortunately their findings could not be integrated. This includes: the complete description of the
Chinese glacier inventories (summarized by Shi et al., 2010), a publication of the Russian Academy
of science on a Russian inventory (Kotliakov, V.M., 1997, Atlas snezhno – ledovykh resursov mira
[World atlas of snow and ice resources]: Moscow, Rossiiskaya Akademiya Nauk, 3 v., 392 p.) and a
Nepalese Inventory described in Asahi (2001) of which only the abstract could be assessed as the
remaining work is published in Japanese.
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3. Glaciers in the Hindu Kush Himalayan Arc - current distribution in area
and volume
The areal extent of the HKH ice mass has been estimated by different scientists. As general
comprehension on the geographic extent of the HKH region varies itself, the borders are often
somehow submitted to subjectivity. It depends on every investigator to include or exclude smaller
mountain ranges or parts on the range’s periphery, as for instance the Hindu Raj range in the
Northwest or Hengduan Shan in the easternmost branches. The varying spatial extent hinders the
direct comparison of estimates and the often imprecise terminology describing the area under
investigation often complicates the inter-comparison of estimates furthermore.
A number of differing values for the HKH regions glacier extent exists. Besides the geographic
extent, completeness and age of the data on which the inventories are based vary strongly, not only
between inventories, but also within inventories. The Chinese glacier inventory, for instance, took 23
years for its compilation (Shi et al., 2010), and so vary the documented glacier stages.
Von Wissman (1959) presented the first quantitative description of the entire HKH region’s
glaciers and climatic snowline. He estimated the ice extend of Hindu Kush, Karakoram (including
Hindu Raj) and the Himalaya, stretching until the eastern end of the Assam Himalaya to 52 875 km2.
For the High Asian cryosphere south of the Alai Valley, he gives an estimate of 101 808 km2.
First internationally published detailed glacier inventories of single basins or massifs were done by
Müller (1980) for the Mt. Everest (Qomolangma; Sagarmatha) region and Vohra (1980) for the Baspa
basin, reporting on the large difficulties encountered during the compilation of the inventory.
The values of glacier coverage for the entire HKH region range from 101 808 km2 by Von
Wissman and 112 000 km2 (Eriksson et al., 2009) over 114 800 km2 (Dyurgerov and Meier, 1997;
WGMS, Zemp et al., 2008) for the “greater Himalayan region”, to 116 180 km2 for “High Mountain
Asia” (Dyugerov and Meier, 2005). Armstong (2010) estimates the total glacier coverage for the
glaciers of “High Asia” to at least 110 000 km², stating a “general agreement” on this number, but
giving no indication how it is build up. Values are summarized in Table 1.
Based on the new HKK Inventory, a total ice extent of 49 380 km2 has been estimated. As
estimates are twice as high, most of the other studies include apparently a larger area. A surprisingly
good agreement can be noticed with the first estimates of Von Wissmann (1959).
Table 1: Estimates of glacier extent in the Hindu Kush- Himalayan region
Reference
Von Wissmann, 1959
Von Wissmann, 1959
Eriksson et al., 2009
Dyurgerov & Meier, 1997
Dyurgerov & Meier, 2005
Frey, 2011
Specified region
Hindu Kush, Karakoram and Himalaya
High Mountain Asia South of Alai Valley
Greater Himalayan region
Greater Himalayan region
High Mountain Asia
Hindu Kush, Karakoram and Himalaya
Area [km2]
52 875
101 808
112 000
114 800
116 180
49 380
Hindu Kush and Karakoram
The Hindu Kush and Karakoram ranges are situated in the western part of Central Asia. The exact
extent is shown in Figure 3. The glaciers of these mountain ranges are some of the longest and largest
mid-latitude glaciers of the world (Sarikaya et al., 2012, Mayewski and Jeschke, 1979). In Pakistan
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alone the extent of glaciers of the Hindu Kush, the Swat/Kohistan region, the Nanga Parbat Himalaya,
and the Karakoram Himalaya is estimated to be over 15 000 km2 (Shroder and Bishop, 2010b).
Despite their exceptional sizes and extent, glaciers in the Karakoram and the Hindu Kush have
been scarcely studied, in comparison to their Himalayan neighbours (Mool et al., 2001a and 2001b;
Shroder and Bishop, 2010b). Besides difficult access due to the rough topography and remoteness,
studies get complicated due to political issues in the region.
A new inventory on Pakistan´s glaciers based on LANDSAT ETM+ (Roohi et al., 2005 in Shroder
and Bishop, 2010p) has been compiled, but it has not been published yet.
Hindu Kush
The Hindu Kush mountain range hosts the highest peaks of Afghanistan, the Noshaq (7492 m
a.s.l.), and Pakistan, the Tirich Mir (7708 m a.s.l.). Its longest glacier is the Tirach with ~30 km in
1959, followed by the ~28 km long Atrak (Von Wissmann, 1959). Glaciers are typically located along
the political border of Afghanistan and Pakistan which is formed by the highest peaks of the region
(Sarikaya et al., 2012). In general the glaciers are of the winter accumulation type (Shroder, 2011).
Considering only the Afghanistan part of the Hindu Kush, there are approximately 3000 glaciers,
rather short of a few kilometers length with very few exceptions. On the southern slopes of the range
in Pakistan, longer valley glaciers up to ~24 km (2011) length are situated. Here the high elevations of
about 7690m a.s.l. (Tirich Mir) may act as precipitation fences and can occasionally catch some of the
summer monsoon precipitation to nourish the larger glaciers on this side (Shroder, 2011).
The glacier coverage of the Hindu Kush has been estimated to 3 200 km2 (Dyurgerov and Meier,
1997; following the calculations of Dyugerov and Lebedeva, technical report for the U.S. department
of state 1994, not available to the authors) and to 3 900 km2 by Von Wissmann (1959).
Based on the HKH inventory, an area of 2969 km2 has been estimated for the Hindu Kush. The
glacier area estimate in this region consists in the majority of GLIMS data and own mapping
performed within the High Noon project. In the northwestern corner, a little fraction is composed by
DCW data (H. Frey, personal communication, 2011; the part is too small to be displayed in the map
resolution).
The volume estimates based on the inventoried areas are 105 (approach 1) and 140 km3 (approach
2). This estimate is the first quantitative assessment of the Hindu Kush ice resources.
Table 2: Estimates of glacier extent in the Hindu Kush
Reference
Von Wissmann, 1959
Specified
region
Hindu Kush
Area [km2]
3900
Dyurgerov & Meier, 1997 based on Dyugerov &
Lebedeva, 1994
Frey, 2011
Hindu Kush
Hindu Kush
3200
2969
Numbers of
glaciers
-
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Figure 5: Glacier area in the Hindu Kush based on the HKH inventory
The glaciers of the Hindu Kush range have an average size of 1.37 km2 and show a mean elevation
of 4755 m a.s.l.. Their mean altitudinal range is considerably large with about 520 m, and can reach
maximum values of 3864 m of height difference. Minimum elevation has been found at 3038 m a.s.l.,
while the highest glacierized point of the range is at 7578 m a.s.l., almost as high as the highest peak.
The ratio of areas above and below the mean elevation is 0.51.
Karakoram Range
The second highest peak on Earth is situated in the Karakoram; the Chogori/K2 has 8611 m a.s.l..
From its slopes, the huge Baltoro glacier, fed by about 30 tributaries extends to a total ice coverage of
about 1 300 km2. Siachen and Biafo are further examples of some of the largest glacier of Asia.
Siachen glacier measures ~78 km length (Bhutiyani, 1999), Baifo ~68 km (Hewitt et al., 1989), and
Hispar ~61 km (Mayewski and Jeschke, 1979). Raikot and Baltoro (~60km) are further examples
(Hewitt, 2005).
Extreme topographical vertical gradients of 300 m/km can be found in this region, which are
exceptional even in comparison to the Himalaya (Mayewski and Jeschke, 1979). The steep walls
provide a lot of material, resulting in a thick debris cover on most of the glaciers (Hewitt et al., 1989).
37% of the Karakoram mountain range is covered by glaciers (Shroder and Bishop, 2010b).
Extreme vertical precipitation gradients can be observed as well: While the zone of maximum
precipitation is situated at heights of ~5000 - 6000 m a.s.l (Hewitt, 2005), the glacier generally end in
the semi-arid and arid elevation zones below 4000 m a.s.l. (Hewitt et al., 1989). Shroder and Bishop
(2010) even report low elevations of 3000 to 3800 m a.s.l. and Mayeswki and Jeschke stated 2800 m
a.s.l. in 1979. The Karakoram glaciers are dominated by winter accumulation brought by the
westerlies, which provide about two thirds of the snow accumulation in Central Karakoram (Hewitt et
al. 1989; see Figure 2).
Despite their large dimensions, information about these glaciers is relatively scarce. Hewitt (2005)
states a “comparative neglect of Karakoram glaciers in the recent literature”. Early works of Von
Wissmann (1959) estimate the total ice extent of this area to 15 145 km2 of which 13775 is assigned
to the eastern Karakoram. Dolgushin and Osipova (1989) mention slightly more, 15 400 km2. Hewitt
et al. (1989) states 15 000 km2. Newer estimates increase the Karakoram ice coverage to 16 000 km2
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(Dyugerov and Meier, 1997; following the calculations of Dyugerov and Lebedeva, published in a
technical report 1994, but not available to authors) and 16 500 km2 (Hewitt, 2010).
The new HKH inventory counts 8901 glaciers in the region covering an area of ~22 120 km2,
exceeding all former estimates by at least a third as Table 3 shows. The HKH inventory in the
Karakoram is mainly based on new mapping performed within the High Noon project as Figure 4
shows. GLIMS and older ICIMOD data further merge to achieve the complete coverage.
Table 3: Estimates of glacier extent in the Karakoram
Reference
Von Wissmann, 1959
Von Wissmann, 1959
Dolgushin and Osipova, 1989
Dyurgerov & Meier, 1997 based on Dyugerov & Lebedeva, 1994
Hewitt, 2010*
Frey, 2011
Specified
region
Karakoram
Ostkarakoram
Karakoram
Karakoram
Karakoram
Karakoram
Area [km2]
15 145
13 665
15 400
16 000
16 500
22 123
*without indication of source
The applied area volume scalings assign 729 km3 (approach 1) and 1235.7 km3 (approach 2) to
these areas. The strongly differing estimates show the influence of the applied methods on the results
and the high uncertainty. The concentration of long glaciers in this region may especially cause a
difference in the results, as the difference in two approaches is also length dependent.
The results of the analysis of topographic parameters based on the HKH inventory are confirming
the superlatives reported from this region: The mean glacier size is with 2.49 very large, according to
the concentration of very large glaciers in this region. The mean elevation of glaciers is with 5483
considerably high and extreme altitudinal ranges of maximum 5100 m can be observed. The average
height extension is 561 m. Glaciers reach as low as 2299 m a.s.l., but mean minimum elevation is at
about 5201 m a.s.l..
Figure 6: Glacier area in the Karakoram based on the HKH inventory. Note that for every glacier,
here in white, individual outlines exist. As the entire area is displayed, the resolution of the map does
not allow the visual distinction in single glaciers.
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Karakoram and Himalaya
A merged inventory for the Himalaya and Karakoram has been recently published. It is compiled
of various sources (Chinese Glacier Inventory, CGI, several regional inventories of ICIMOD and
partial inventories of the GSI; Information about which inventory parts are taken from which source is
not given). Additionally new glacier outlines for the part of Kashmir claimed by India, based on
analog maps of the Sovjet military (reference date : late 1970s; 1:200 000 scale) have been created.
The inventory counts 20 812 glaciers covering a total area of 43 178 km2 of the Karakoram –
Himalayan region. As inventory data varies and from 1968-2003 the author suggests that currently up
to 20% of the glaciers may already have disappeared (Cogley, 2011b).
Figure 7 shows the areas included in the estimates. The chosen limits are almost identical to the
ones in this report, as comparison with Figure 3 suggests. Table 4 compares the values to the HKH
inventory by Frey (2011). The HKH inventory estimates the ice coverage in the region a lot higher
than the compiled inventory by Cogley (2011b).
Figure 7: Inventory coverage of Cogley (2011b) indicated by thin black line. Taken from Cogley (2011b)
Table 4: Estimates of glacier extent in the Karakoram and Himalaya
Reference
Specified region
Area
[km2]
Numbers of
glaciers
Von Wissmann, 1959
Himalaya & Karakoram
48 975
Cogley, 2011b
43 178
20 812
Frey, 2011
57 357
32 565
The HKH inventory data in the Karakoram is based on newly mapped glacier outlines in the
eastern part and GLIMS data in the north, which is here based on the CGI. The central western part is
composed by older ICIMOD data. In the Himalayas mostly ICIMOD data has been used (see Figure
4). The employed data sources of both inventories are apparently similar considering the older
ICIMOD inventories and the GLIMS (mostly CGI data) data base. Differences are more obvious in
the newer ICIMOD inventories in the Central and Eastern Himalaya, but here, the HKH inventory
suggests rather lower estimates as will be shown further on and hence the a lot larger value for the
Himalaya and Karakoram total ice extent has to be build by the glaciers in the Karakoram. The
difference in the Karakoram ice extent in both inventories must be made by the respective own
mappings as the other sources are identical. Whereas the inventory presented by Cogley (2011b) used
older Sovjet maps as a base for the inventory, the own mapping is based on remote sensing and shows
very high quality. As a consequence, the confidence assigned to the HKH inventory estimate is ranked
superior as compared to the much lower estimates of Cogley (2011b).
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Himalayan Range
The Himalayan range stretches generally east-west, tending northwards in its western parts. With
the Mt. Everest (Qomolangma, Sagarmatha) it is the highest mountain range on Earth. Its waters
mainly drain towards the Ganges, some also towards Bhramaputra and Indus, who separates the
Himalaya from the Karakoram in the west.
First quantitative estimates of the Himalayan ice coverage have been provided by the work of Von
Wissmann (1959) with 31 530 km2. The longest glacier of the Hinalayan range is Gangotri glacier
which builds the uppermost source of the Ganges river. It measures ~32 km in length (1959, Von
Wissmann).
By far the most cited value for glacier extent in the Himalayan range is 33 050 km2 of Dolgushin
and Osipova (1989) in their publication on glaciers in Russian language. It is doubtable that the
following list of authors has actually consulted this work. The value given is not a proper estimate by
Dolgushin and Osipova (1989), but goes itself back to older publications in Russian language.
Unfortunately these sources could not be consulted and consequently, the origin of this most cited
value maintains unknown to the wider public.
The value of 33 050 km2 keeps to be cited (Dyurgerov and Meier, 1997 and 2005; Zemp et al.,
2008, Armstrong 2010; Eriksson et al. 2009; Berthier et al., 2007; Cogley, 2011b) with uncertainty of
its accuracy and origin in most of the cases. The actuality of the citation list of this value which goes
back to at least the late 1980s is characterizing the current situation of HKH glacier knowledge. At
least 50 000 individual glaciers are assigned to this ice mass by Dyurgerov and Meier (2005).
The new HKH inventory counts 23 664 glaciers in the Himalayas. They cover a total area of 25
234 km2. Maps of the inventoried glacier outlines are provided in the sub-sections of Western, Central
and Eastern Himalaya The inventory in the Himalaya is in its majority composed by new ICIMOD
data in its central part, together with older ICIMOD inventories and GLIMS data. The Western
Himalayan part is build up by a new high quality inventory, named GlobGlacier, presented under the
Western and Central Himalaya Section. The confidence assigned to the data is relatively high.
The HKH inventory value is the smallest of all collected estimates presented in Table 5. In the
following paragraphs, the origins and assigned uncertainties or qualities of the other estimates will be
presented. The volume estimate for the entire Himalayan range amounts to 842 (approach 1) and
1167 km3 (approach 2). Again the large difference between the estimates shows the high uncertainties
persistent in current estimates of the ice resources.
Table 5: Estimates of glacier extent in the Himalaya
Reference
Specified region
Area [km2]
Von Wissmann, 1959
Himalaya*
31 530
Dolgushin & Osipova, 1989
Himalaya
33 050
Qin, 1999
Himalaya
35 109
Kaul, 1999
Himalaya**
38 000
ISRO, 2011
Himalaya***
71 182
Frey, 2011
Himalaya
25 233
* including Assam Himalaya
** only glaciers on territory claimed by India
*** glaciers on territory claimed by India or outside but draining towards India
The Map of Glacier Resources in the Himalayas of Qin (1999) on a 1:500 000 scale provides an
estimate of overall HKH glacier coverage east of the Indus river. The total ice coverage is estimated
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to 35 110 km2 including 18 020 glaciers. The map is based on LANDSAT 7 images from 1975-1978
and some not specified aerial photographs. The contour line interval is 1000m. The authors state that
they “have tried their best to reduce errors to the least degree” and give an error estimate of 5% for the
satellite image interpretation (Qin, 1999). Visual inspection of the map let suggest a rather rough
glacier estimate, especially for small glaciers which show rather undifferentiated shapes (triangles)
and no separation into individual glaciers. With regard to the degree of detail of the HKH inventory,
the estimates based on the map of Qin (1999) are largely overestimated. This seems especially true
for the Central Himalaya, where a total area of 20 214 km2 has been estimated, in comparison to 8386
km2 by the HKH inventory (see also subsections on central Himalaya).
Despite of the high uncertainty, the map provides one of the few estimates for the entire region and
has been fairly cited thus results are presented here nevertheless for comparisons.
Table 6: Glacierized areas of the Map of Glacier Resources in the Himalayas (Qin,1999)
Basins
Mapam Yumco
Ganges (partly)
Yarlung Zangbo
Ganges
Indus (partly)
Sutlej River
Indus
Total
Count of glaciers
Area [km2]
48
6649
4366
Regions
Count of
glaciers
Area
[km2]
5648
10284.75
9449
2968
20214.54
4610.33
18065
35109.62
66.51
16677
6580
11015
5057
23257
8926
1900
2860.82
6957
11786.82
18020
35110.33
Western
Himalaya
Central Himalaya
Eastern Himalaya
Notice that Yarlung Zangbo River basin is draining towards the Ganges and Sutlej River basin is draining towards Indus.
Eriksson et al. (2009) state an area of 32 182 km² based on Qin (1999) and estimates the fraction
of glacierized area based on this number to 17%. Vohra (2010) cites the same source with 35 110
km2. The differences may arise from the varying definition of the investigated area. Investigation
shows that while Vohra (2010) considered the entire mapped region, Eriksson et al. (2009) excluded
Mapam Yunco basin in Tibet and Sutlej river basin in Western Himalaya. Citations of values in
important publications as these ones without indication of the exact spatial extent of the estimates and
their further citation deteriorate the quality and increment uncertainty about HKH glacier resources,
especially when cited sources are not digitally and hence widely available. Therefore, this rather long
section is included in this report to enhance transparency and clearness.
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Indian glacier inventories
Glaciers of some selected basins across
the Himalayas on Indian territory have been
presented in The Inventory of Himalayan
Glaciers by GSI in 1999 (Kaul, 1999). The
inventories are based on SOI topographic
maps on 1:50 000 scale with 40m contour
intervals (or degree sheets on 1:250 000
scale following availability). Problems of
SOI maps have been presented in the
Methodology Section. Additional air or
space borne photography has been
consulted but absence of further information
where and which images have been used
hinders the accuracy assessment. An error
estimate based on the given information is
impossible.
Figure 8: Glacier map of Bhagirati basin, Garhwal
Himal from the Inventory of Himalayan Glaciers by
Kaul (ed.), 1999
The inventoried basins are presented in
Table 7. The selective character of the
inventory limits the comparability with
other estimates and in combination with
lacking error assessment limits furthermore
the use of the inventory for a range of
applications, as for instance the estimation
of fresh water resource stored as ice in the
basins. The estimated areas may be of an
approximate character as the map in Figure
8 suggests.
On the other hand, glaciological parameters provided in tabular format such as AAR or range of
lowest elevation of glaciers allow further glaciological interpretations on glacier distribution and
regional differences as other inventories in this data format. A summary of the inventory data is
presented in Table 7.
Table 7: Glacier inventory data of The Inventory of Himalayan Glaciers, Kaul (ed.), 1999.
Inventoried
subbasin
Basin
Jhelum basin
Bhagirathi basin
Tista basin
Indus
Ganges
Bhramaputra
Numbers of
Inventoried
Mountain region
glaciers
Glacierized Area
[km2]
133
238
449
94.18
755.43
705.54
HKH Subregion
Kashmir Himalaya Western Himalaya
Garhwal Himalya Central Himalaya
Sikkim Himalaya Eastern Himalaya
Data for Satluy basin and parts of Arunachal Pradesh is not provided here because the inventory work has not
been carried out for the entire basin or is still in or progress
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A glacier inventory has been recently compiled by the Indian Space Applications Center (ISRO)
for the Indus, Ganges and Brahmaputra basins on a 1: 50 000 scale using IRS LISS III satellite data of
the period from 2004 to 2007 and ancillary material. In total, 32 392 glaciers were identified, covering
an area of 71 182.08 km2 (ISRO, 2011). These numbers refer to glaciers located within India or
outside the Indian territory but within a basin draining into India. The glacierized area within the
Indian territory alone is 40 563 km2, hosting 16 627 glaciers (Sarkar, 2011, about the same inventory).
The spatial extension of the inventory data following administrative borders in combination with
hydrological catchments limits its use for comparisons, for example of watershed-wide estimates of
glacier coverage. Therefore numbers for the Brahmaputra basin for instance, should not be taken as
absolute, as only parts of the basin draining to India are considered. Divided by watersheds, the
inventory map shows a considered glacierized area of the Indus basin of 32 246.43 km2 (16049
glaciers), 18 392.90 km2 (6 237 glaciers) in the Ganges basin and 20 542.75 km2 (10 106 glaciers) in
the Brahmaputra basin (ISRO, 2011).
In general the reported values seem in comparison to other estimates presented in Table 5 largely
overestimated, even if parts of the Karakoram range may be included.
In the “Satellite atlas of glaciers of the world – Glaciers of Asia”, the glacier coverage for the
Indian Himalaya is estimated to be 8 500 km2 based on Kaul (ed. 1999) (Vohra, 2010). This number
is, especially considering the new ISRO and the HKH inventory results certainly too low.
Consultation of the original work of Kaul (ed., 1999) reveals (as presented above) that only glaciers of
selected basins have been inventoried and thus the estimate does not refer to the total glacier coverage
on Indian territory.
Indian Part of Kashmir
Based on digitized analogue maps of the Soviet military in 1: 200 000 resolution from the late
1970s, an inventory counting 3526 glaciers with an area extent of 9 584 km2 has been compiled. A
publication on this inventory, which is merged to a larger compilation (see section “Karakoram –
Himalaya”) is in progress (Cogley, 2011b).
Please consult the Western Himalaya and the Central Himalaya sections for information about
regional settings.
A new inventory with glacier outlines for the western and central Himalayas of India based on
Landsat ETM+ scenes from 2000 to 2002 has been recently compiled (Frey et al., submitted). The
inventory called GlobGlacier includes parts of the Ladakh Range, the Zanskar Range and parts of the
Garhwal Himalaya, and some glaciers in the autonomous region Tibet (China) NW of the Himalayan
main range), including Samudra Tapu, Chhota Shigri and Gangotri glaciers is presented in Figure 9.
The inventory counts 11 550 glaciers (exceeding 0.2 km2) covering an area of 9 370 km2. Glacier
outlines below this area extent were excluded from the data set for being likely to be seasonal snow
accumulations. Additionally, 938 of these glacier polygons were excluded due to partial cloud cover,
thus 10 845 glaciers (8 872 km2) were included in the analysis of glacier parameters. The accuracy
assigned to the glacier outlines are ± 30 m for debris free ice, ± 60 m for debris covered ice and ± 150
m for debris covered glaciers in the northern arid-cold part of the investigation area (Autonomous
region of Tibet), where glacier permafrost interactions are common (Frey et al., submitted).
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The GlobGlacier inventory forms part of the compiled HKH inventory on which the main glacier
area distribution assessment of this report is based.
Figure 9: Inventory coverage of the new GlobGlacier inventory part in Western and central
Himalaya
Frey et al., submitted
The glaciers in Western and Central Himalaya show similar patterns as mid-latitude glaciers
considering the number and area per size class with the majority of glaciers being rather small (86%
under 1 km2) covering in total a small area of about one fifth of the total glacierized area. Only 13
glaciers exceed 50 km2. The largest completely debris-free glacier is 7.4 km2 (Frey et al., submitted).
64.5% of the glacierized area is found on North facing slopes (NW, N, NE) while only 21.7% is
found on southern slopes (SW, S, SE). The mean elevation shows large differences between the arid
cold glaciers towards the Tibetean Plateau (5700 m a.s.l.) and the monsoon fed glaciers southwards
the Himalayan main range (Frey et al., submitted).
Debris cover is 14.9% of the total inventoried glacier surface. A southeast to northwest gradient in
debris cover has been revealed (SE: 22% to NW:6% of the area debris covered), assigned to the larger
supply of steep rock faces in the south (Frey et al., submitted).
Western Himalaya
The Western Himalaya is located in the monsoon–arid transition zone (Mayewski and Jeschke,
1979). Here, the most of the annual precipitation falls during the summer month of July to September.
In winter from January to April, the westerlies supply the glaciers with additional precipitation. The
region is thus alternately influenced by the Asian monsoon system and the mid latitude westerlies as
Figure 2 illustrates (Wagnon et al., 2007). Local conditions are often superimposed to the large
atmospheric circulation. For example for a valley in the Baspa basin (please see Figure 23 for
localization of Naradu glacier: Available mass balance data for glaciers across the HKH region for
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exact location), the opposite climate and accumulation regime is observed, with an alpine to subMediterranean climate, receiving nearly 70% of annual precipitation in winter and spring (Koul and
Ganjoo, 2010). Due to the orientation of the main ridge (east-west), precipitation is often reduced on
the leeward (northern) slopes and valleys (Bookhagen and Burbank, 2006; Wagnon et al., 2007).
The glacier coverage in the Western Himalaya is 8927 km2, split in remarkably many, 11 679
glaciers. This results in a relatively small medium glacier size of 0.76 km2.
The volume estimated based on this area shown in Figure 10 is 316 (approach 1) to 415 km3
(approach 2).
Figure 10: Glacier area in the Western Himalaya based on the HKH inventory
The analysis of topographic parameters based on the HKH inventory reveals, that the glaciers in
the Western Himalayas show a relatively low mean elevation situated at about 5136 m a.s.l., ranging
on average over only 355 m. The lowest glacier ends at 2367 m a.s.l., the highest accumulation area
reaches above 8000 m a.s.l. showing the diversity of glacier distribution. The ratio of glacier areas
above the mean elevation to the ones below is 48.2.
Other glacier inventories in the Western Himalaya
The Indian state Himachal Pradesh shows a relatively high number of studies performed about its
glaciers. On the other hand serious accuracy issues of SOI topographic maps of the region have been
revealed (see “Methodology section”, Cogley, 2011b; Bhrambi and Bolch,2009; Vohra, 1980) and
need to be taken into account when glacier areas are estimated based on these maps (e.g. Kaul, 1999).
The largest glacier of Himachal Pradesh is Bara Shigri with a length of ~28 km (Berthier et al.,
2007). The name of the over 131 km2 extending glacier means ‘debris covered’ in the Spiti dialect
(Dutt, 1961 cited in Mayewski and Jeschke, 1979) and is characteristic for this region’s glaciers,
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where debris cover are very common (Mayewski and Jeschke, 1979). Another large glacier is Chhota
Shigri, situated west of Bara Shigri. It covers an area of ~15.7 km2, including its four tributaries
(Wagnon et al., 2007).
The section about Indian glaciers in the promising Satellite Atlas of Glacier of the World is
unfortunately mainly from 1982 due to a publishing delay (Vohra, 2010). Therefore, only very limited
findings from this source can be included in this report.
In the Chenab, Parbati and the Baspa basins, a glacierized area of 1 628 km2 consisting of 466
glaciers has been mapped based on Indian LISS III and IV Sensor images from 2000 (Baspa) to 2004
(Parbati). Images for Chenab are dated 2000 and 2001. The average glacier area is 0.32 km2 (Kulkarni
et al., 2007). The authors leave open if the mapped area is supposed to be the total glacierized area of
the basins or if only parts were considered.
The Parbati basin counts 88 glaciers with a total extent of 379 km2 in 2004. For the Chenab basin,
359 glaciers with a total extent of 1 110 km2 (2001) have been mapped. 19 glaciers were mapped in
the Baspa basin, covering a total area of 140 km2 in 2001. The results must be considered with care
taking into account the methodologies used. The delineation of the recent glacier outlines from
satellite imagery has been performed automatically with the bands ratio method, accounting for the
mapping of debris covered parts only through geomorphologic features. The authors state that
numerous geomorphologic features can be utilized to identify terminus (Kulkarni et al., 2011). But not
only the terminus but also lateral glacier parts can be heavily debris covered.
In 2011, Kulkarni et al. expanded the 2007 study to further basins in the Western Himalaya, based
on the same methodology. Tista, Gori Ganges, Bhagrithi, Baspa, Parbati, Chandra, Bhaga, Miyar,
Bhut, Warwan and Zanskar basin (see Figure 11) show a mapped glacierized area of 5 329 km2. The
aim of the presented study is detection of area changes (and volume and mass balance estimation).
Therefore, the authors do not claim completeness or inventory status of the mapped glacierized area.
The use of the estimates for comparisons is limited for this reason, but presented anyway in Table 8.
Figure 11: Northern India with the location of basins used to monitor snow cover and to
estimate glacier retreat by Kulkarni et al, 2011. 1: Tista (excluded from quantitative analysis);
2: Gori Ganges; 3: Bhagrithi; 4: Baspa; 5: Parbati; 6: Chandra; 7: Bhaga; 8: Miyar; 9: Bhut;
10: Warwan; 11: Zanskar. Black line: North Indian country border, Indian definition.
Kulkarni et al., 2011
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Table 8: Glacierized area and number of glaciers in
selected basins of the Western Himalaya identified by
Kulkarni et al., 2011. Glacier outlines estimated
satellite imagery (LISS III and IV), reference years
are 2000 to 2004. Notice that the basin glacier
estimates do not claim completeness but can be
interpreted as minimum values.
Basin
Total
GoriGanges
Bhagirathi
Baspa
Parbati
Chandra
Bhaga
Miyar
Bhut
Warwan
Zanskar
Tista
Glacierized
Area
km2
5329
269
1178
140
390
554
254
523
420
672
929
392
Number of
Glaciers
1868
41
212
19
90
116
111
166
189
253
671
57
Following The Inventory of Himalayan Glaciers, Bhagirati basin counts 238 glaciers covering a
surface of ~755 km2 (Kaul, 1999). The significantly smaller area value in comparison to the data of
Kulkarni et al. (2011) reveals that further investigation is needed to assess the glacierized area in this
basin or even region.
Central and Eastern Himalaya
The Central and Eastern Himalaya are situated in southern Central Asia, and are mainly situated on
Indian, Nepalese and Bhutanese territory (See Figure 3). Large glacier areas are found around the
highest elevations as for instance the Badrinath group, Nanda Devi group, Kamet group,
Kanchenjunga group, Rangtö group and the peaks around Mt. Everest (Von Wissmann, 1959). The
region is dominated by summer monsoon resulting in a strong north-south gradient of precipitation.
The east-west stretching main range works on one as a barrier for the moisture rich air masses which
are pushed northwards by the monsoon circulation and forced to orographic ascension reaching the
mountain chain. Exceptional precipitation rates are thus found on the southern slopes (see also Figure
2). On the other side the high elevations of the main range built a rain shadow to valleys located on
the northern side of this divide resulting in semi-arid to arid conditions on the northern slopes.
Additional to the north-south humidity pattern, an east-west gradient is superimposed due to earliest
and highest monsoon precipitation in the southeast which looses intensity on its way to the northwest
(Mool et al., 2001b).
The Nepalese country is partly situated within the Central and partly within the Eastern Himalaya.
A countrywide inventory is presented here, while an inventory on Eastern Nepal is presented under
the Eastern Himalaya section.
Inventories of the Nepalese Himalayas
The Nepalese Himalaya shows the highest elevations on Earth. The Himalayas in Nepal perceive
the monsoon onset first in the southeastern part of the country, then slowly spreading northwest with
decreasing intensities resulting in lower annual totals in regions located in the northwest relatively to
the southeast (Mool et al., 2001).
In the Satellite Atlas of Glaciers of the World (2010) the section on glaciers of Nepal is mainly
from the early 1980s. A preliminary application of LANDSAT images to the Nepal Himalaya in these
times resulted in a glacier inventory in tabular form with 706 glaciers (Higuchi et al.,2010, Ageta,
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2010). The glaciers were mapped without apparent distinction to the snow cover. As no glacier area
estimates are provided, the influence of the late image acquisition dates in winter (Nov, Dec, even
including January) maybe acceptable for the estimation of the numbers of glacier. Ground truth has
been provided by studies in the Dudh Kosi region (Higuchi et al., 2010)
A Nepalese glacier inventory in tabular form (WGI format) is provided by ICIMOD and is based
on large-scale topographic maps and aerial photographs (1:125 000; reference date 1992 for West and
1996 for East Nepal) and auxiliary material in form of satellite images of LANDSAT TM, LISS III
and Spot. The topographic maps used were published by the SOI from 1950 to 1970 on 1:63 360 scale
and by the Survey Department of His Majesty’s Government of Nepal (HMGN) in 1996 on a scale of
1:50 000. The inventory documenting glacier areas is entirely based on the SOI topographic maps
(1:63,360 scale) published in the 1950s–1970s (Mool et al., 2001b). Serious inaccuracies are found in
glacier areas in SOI maps (see Methodology section). The tabular form of the inventory does
furthermore not allow the reconstruction of the glacier outlines and makes afterwards quality control
and accuracy assessment almost impossible (Frey et al., submitted). As there exist sustained doubts
but for the presented reasons and the quality cannot be assessed, the inventory data of Nepal should
not be considered in further assessments and is here presented for reasons of completeness: It counts
3252 glacier covering an area of 5323 km2. Ageta (2010) states in the “Supplement to Glaciers of
Nepal” that this inventory is the actual and updated version of the Nepalese inventory.
A new glacier inventory for Nepal based on 2008 and 2009 LANDSAT images counts 3808
glaciers covering 4212 km2. Glacier outlines were derived semi-automatically, taking into account the
differences of clean ice and debris covered glaciers (Bajracharya et al., 2011). This inventory has been
integrated in the HKH inventory.
Central Himalaya
The Central Himalaya contains some of the longest glaciers in the Himalayas including the longest
one, the Gangotri glacier with approximately 30 km length (Von Wissmann, 1959). The climatic
settings are described in the section on Central and Eastern Himalaya here above. The mean glacier
size in the Central Himalaya is 1.27 km2. The total glacier area has been estimated to amount 8386
km2, compound by 6613 glaciers.
The estimated volume varies from 274 with approach 1 to 390 km3 applying approach 2.
Figure 12: Glacier area in the Central Himalaya based on the HKH inventory
The mean glacier elevation in the Central Himalaya is 5485 m a.s.l. with an average range of
533m. Glaciers reach on average low as 5225 m a.s.l., the lowest glacier tongue can be found at 3124
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m a.s.l.. The glaciers show almost equal area distributions above and below the mean elevation, with a
ratio of 0.505.
Inventories of the Garhwal Himal
The Garhwal Himalaya is part of Uttarakhand in northern India in the Central Himalayas. It hosts
the largest glacier of the Himalayas, the Gangotri. Based on the Glacier Atlas of India, 968 glaciers
exist in the Garhwal Himalaya, covering 2 885 km2 (Srivastava, 2008 cited in Bhrambi et al., 2011).
Early estimates of the ice extent state 3825 km2 of which 19 exceed each 40 km2 (Von Wissmann,
1959).
Bhrambi et al. (2011) mapped glaciers of the Upper Bhagirathi and Saraswati/Alaknanda basins in
the Garhwal Himalaya based on ASTER images of 2006 and report a glacierized area of 572.5 ± 18
km2. The investigation area is shown in Figure 13. The individual basins have glacierized areas of 274
±8.6 km2 (Upper Bhagirathi Basin 20 glaciers) and 311.4 ± 9.8 km2 (Saraswati/Alaknanda basin, 83
glaciers) and show similar debris covered fractions of glacier ice of about one quarter. The assigned
total error is ±4%. They found that larger glaciers reach to lower elevations and have higher
altitudinal ranges (the opposite is true for small glaciers).
Figure 13: Glacier area mapped in the Upper Bhagirati and Saraswati/ Alakanda basins by Bhrambi
et al. (2011)
Bhrambi et al. (2011)
Following the glacier atlas of India, the Alaknanda basin has in total 407 glaciers covering 1 229
km2, whereas the Bhagirathi basin contains 238 glaciers covering 755 km2 (Raina and Srivastava,
2008 cited in Bhrambi et al., 2011).
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Inventories of Nepal
Please consult the Nepalese Himalayas section in the Central and Eastern Himalaya chapter.
Inventory of Langtang Valley
The Langtang Valley, also named Langtang Khola, is located in the Central Himalayas in the
border region between Nepal and China, approximately 60 km north from Kathmandu, Nepal. A
glacier inventory has been compiled based on aerial photos from 1981 and 1991, ground survey data
and topographic maps published by the Austrian Alpine Club on a 1: 50 000 scale. The inventory
counts 72 glaciers covering an area of 137.50 km2 (Shiraiwa and Yamada, 2001). The inventory is in
tabular form (WGMS format) and quality and accuracy control problems and lacking error estimation
as mentioned above are related to this inventory type and hence limit the reliability and utility of the
data set.
Eastern Himalaya
The Eastern Himalaya extends from east of Kathmandu, Nepal over Sikkim (India) to the Bhutan
Himalaya (see Figure 3). It includes the well studied glacier AX010 and the Khumbu Himal where
Mt. Everest (Qomolangma, Sagarmatha) is situated. The longest glacier is Zemu with ~20 km
originating from the eastern slopes of Mt. Kanchenjunga (Raina et al., 2008). The climate in the
Eastern Himalaya is dominated by the Asian monsoon and generally resulting in high annual
precipitation amounts, of which 70–80% occur during the summer months (Ueno et al., 2001 in Bolch
et al., 2008). Glaciers in this region are the typical example of the summer accumulation type after
Ageta and Higuchi (1984).
Figure 14: Glacier area in the Eastern Himalaya based on the HKH inventory
In the Eastern Himalaya, a glacier area of 7921 km2 has been estimated. The 5372 glaciers show a
mean size of 1.47 km2 and mean elevation of 5417 m a.s.l. The altitudinal extent of the glaciers is on
average 516 m, and can reach considerably large until 4699 m of height difference between the
highest glacier point and the tongue. Highest glacier elevations can be found here until 8806 m a.s.l.,
and extremely low reaching glacier tongues can be found until 1924 m a.s.l..
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The glacier ice volumes amount to 252 to 361 km3, for approaches 1 and 2, respectively.
Inventory of Eastern Nepal
Asahi (2001) presents a glacier inventory for eastern Nepal based on new topographic maps
produced of aerial photography from 1992. For language restrictions, only the abstract of the
publication in Japanese language could be included. Therefore the values given should be considered
with care and be used for comparisons or order of magnitude estimation. The inventory counts 1024
glaciers covering an area of 1 597 km2 in eastern Nepal, which compromises the Kanchenjunga,
Khumbu, Rolwaling and Langtang Himalayas. 153 of these glaciers (15%) are debris-covered.
Inventories of the Khumbu and Kanchenjunga Himal
The glaciers of the Kanchenjunga-Everest region are commonly characterized by steep gradients
and do not reach lower than 4000 m a.s.l. (Mayewski and Jeschke, 1979). Besides accumulation by
direct precipitation on the glacier, avalanches build an important accumulation source. For Khumbu
glacier for instance, accumulation from avalanches is about twice as high than from direct snowfall
(Inoue, 1977 in Bolch et al., 2008). Heavy debris covers are common and increase toward the
terminus to several meters in thickness (Mayewski and Jeschke, 1979, Bolch et al., 2008).
Inventories of the Sikkim Himal
The Tista river basin is situated within the Indian state Sikkim and covers its area almost entirely.
It shows an extreme altitudinal extent for the Himalayas from 300 to 8598 m a.s.l. on relatively small
territory which drains towards the Bhramaputra basin (Krishna, 2005). In the Tista basin 449 glaciers
are situated covering an approximated area of 705 km2 (Kaul, 1999). One of the longest glaciers of
India is situated in the Sikkim Himalaya, the ~28 km long Zemu (Vohra, 2010). Krishna (2005)
estimated its length to ~20.5 km including the Tent Peak and Nepal Gap glaciers The Glacier Atlas of
India states ~20 km (Raina et al., 2008). More confidence to actuality is assigned to the work of
Krishna (2005), because large parts of the Glacier Atlas of India by Vohra (2010) date from the early
1980s. The glacier shows a large altitudinal range of 1330 m. In general, glaciers of Sikkim can reach
as low as 3700 m a.s.l. Based on LISS II and LISS III data (image acquisition in 1992 and 1997) a
glacier area of 89.41 km2 has been estimated (Krishna, 2005).
Inventories of the Bhutan Himal
The glaciers in Bhutan are situated in their majority along the main ridge of the Bhutan Himalaya,
and on plateaus and ridges that stretch downwards of it. While the valley glaciers on the southern side
show narrow upper basins surrounded by steep rock faces, the glaciers north of the main crest have
larger and less steep accumulation areas. Their glacier tongues reach here not very low; from the high
elevation accumulation areas at 7000 m a.s.l. to ~5000 m a.s.l (Kääb, 2005). On the other hand, large
valley glaciers on the southern side have usually debris cover, not only limited to the ablation areas
(Iwata, 2010). The glaciers can descend until 4 000 m a.s.l. on the southern side depending if debris
covered or clean ice type. From south to north, the monsoon influence decreases, while continentality
increases (Kääb, 2005). The glaciers are of the summer accumulation type classification by Ageta
and Higuchi (1984). Wachey Glacier is with 20.1 km (reference date ~1950-1970) the longest glacier
(Mool et al., 2001a).
The knowledge of the glacier extent in Bhutan is relatively limited (Iwata, 2010; Mool et al.,
2001a, Karma et al., 2003).
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The first inventory for Bhutan’s glaciers was published in 1999 by the Geological Survey of
Bhutan (Revised version of 1996). ICIMOD published in 2001 a more complete inventory (Iwata,
2010). It is based on topographic maps of the SOI of the 1950s to 1970s (1:50 000) and auxiliary
satellite data of LANDSAT TM (Mool et al., 2001a). The accuracy problems related to SOI maps
have been presented in the Methodology section. Glacier areas have been mapped with GIS software.
No specifications on the procedure are given, but at least the maps with glacier coverage are provided,
unlike the inventory of Nepal. Another important difference is that snow cover is not mapped together
with glaciers and hence the glacier inventory quality is supposed to be superior. The inventory counts
667 glaciers covering 1 316.71 km2. A volume area scaling based on empirical data for the Tien Shan
is applied, but no error and uncertainty discussion is provided. Using empirical area volume equations
in different regions of where they were developed without any ground validation is very critical. The
presented volume is 127.25 km3 (Mool et al., 2001a).
3. 1 Conclusions on the current distribution of glaciers in the HKH
The presented works show that even now regional inventories exist with patchy information for the
HKH region’s glaciers. The HKH inventory presented here overcomes the problems arising from
differing inventory coverages, time spans and resolutions and provides a sound basis for an overall
HKH-wide assessment on glacier distribution.
Based on the research made and presented above, the highest confidence is assigned to the
estimates of Himalayan glacier extent based on the HKH inventory, stating a total glacierized area of
25 234 km2 . Besides that the estimates based on Kaul (1999) and ISRO (2001) cannot be directly
compared due to the administratively determined inventory limits, the first is based on topographic
maps of the SOI and the latter made use of remote sensing, but error assessments are lacking. While
here high uncertainty needs to be stated, the estimates of Qin (199) need to be ranked as low accuracy.
The quality of the often cited values of Dolgushin and Osipova (1989) cannot be assessed as it is a
citation itself and goes back to further studies in Russian language and hence, uncertainty is high.
Surprisingly near to the HKH inventory value for the Himalayan glacier area is the first quantitative
estimate of 1959 of Von Wissmann, including the Assam Himalaya with 31 530 km2. As a
consequence, a general overestimation with regard to the Himalayan glacier extent can be stated. The
newly compiled HKH inventory suggests that the Himalayan glacier area is lower than assumed until
today.
For the Karakoram, 22 132 km2 of glacier area has been estimated based on the HKH inventory,
the by far most high value. The quality of the other estimates cannot be assessed, as original works are
not publically available (in English; Dolgushin and Osipova, 1989; Dyugerov & Lebedeva, 1994), or
not mentioned (Hewitt, 2010). The work of Von Wissmann (1959) provides certainly a good estimate
as other values based on this work show relatively good agreement, but also the limited possibilities
of the time in that the estimates were made, have to be considered and hence the confidence assigned
is ranked as lower than to the HKH inventory.
For the glacier extent in the Hindu Kush, only three estimates exist. The HKH inventory counts
2969 km2, based on relatively good GLIMS data. The other estimates origin from Dyugerov &
Lebedeva (1994), of which the original is not available, but who’s estimate shows good agreement;
And of Von Wissmann (1959) stating with 3900 km2 a relatively high value. The HKH inventory can
be considered as the best available estimate.
Through the analysis of topographic parameter some interesting regional differences were
revealed. Considering the sizes of glaciers, the Karakoram shows with a mean glacier size of 2.49
very large glaciers (see Figure 15).
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The Hindu Kush, Central and the
Eastern Himalayas show similar
average sizes, but in the Western
Himalaya a concentration of much
smaller glaciers is apparent.
Figure 15: Mean glacier sizes in the HKH sub regions
Figure 16 shows the mean
elevation of the glaciers of each sub
region. Again, the Western Himalaya
differs from its Central and Eastern
equivalents as it is characterized by a
relatively low mean elevation. Notice
also the very low mean elevation of
glaciers in the Hindu Kush with 4755 m a.s.l. The exact values are presented in Table 9. It is
interesting that, while the glaciers in the Eastern Himalaya show a relatively high mean elevation,
deviation is high and their tongues can reach below 2000 m a.s.l. as Figure 17 illustrates. This is a
difference to the Central Himalayan glaciers, situated at a similar mean elevation, but they do not
reach very low. The intensity and onset of the monsoon in the easternmost fringes of the Himalayas
gives a possible explanation providing the east with higher accumulation amounts. The Western
Himalayan glaciers are characterized by a very small altitudinal range in comparison to its neighbors.
The Karakoram is characterized by relatively low reaching glaciers as well, consistent with the
extraordinary elevation ranges found for the glaciers of this mountain range. The mean altitudinal
extent of glaciers here is with 561 m considerably large, but appears small in relation to the maximum
range of a glacier extending over 5000 height meters (5138 m, see Table 10 for details).
Figure 16: Mean elevation of glaciers
in the HKH sub regions
Figure 17: Minimum elevation of glaciers in the HKH sub
regions
The analysis of the ratio of glacier areas situated above the mean elevation and below the mean
elevation revealed similar distribution along the HKH area, ranging from 48.8 to 51.6, suggesting
AAR of about 0.50 for the HKH. This is consistent with the AAR established at two glaciers in Baspa
basin, Himachal Pradesh with 0.5 (Kulkarni et al., 2004) and 0.46 to 0.5 (Koul and Ganjoo, 2010).
For Tipra and Rataban glaciers in the Garwhal Himal, AARs of 0.47 and 0.49, respectively, have
been estimated (Mehta et al., 2011) while Dobhal et al. (2008) calculate values of 0.67 to 0.70 for
Dokriani glacier.In other regions of the world as for instance the European Alps, a glacier needs an
accumulation area of about 2/3 (AAR=0.66) to maintain its equilibrium. Debris cover may play here
an important role, as AARs of glaciers with debris covered terminus parts are lower than the ones of
clean ice glaciers (Benn and Lehmkuhl, 2000). Dokriani glacier though is heavily covered as well.
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Further investigation needs to be conducted to assess, if the difference arises from regional
particularities or if the determined AAR does maybe not describe a glacier in its equilibrium, but in
recession. The reported glacier expansion in the high Central Karakoram though does not support this
hypothesis as AARs here are similar.
Table 9: Topographic glacier parameters in the HKH sub-regions.
The volume estimates based on the HKH Inventory are summarized in Table 11. As the volumes
are based on the areas, a correlation can be observed. Noticeable is the difference in volumes
estimated with the different approaches. The large difference between the values shows the high
uncertainty inherent in the results and reveals how sensitive the estimates are towards mean slope. It is
interesting that volumes for the Karakoram and the Himalaya estimated with approach 2 (taking into
account the more detailed mean slope calculation) are inverse to the area distribution. While the
Karakoram shows slightly lower ice coverage, it hosts a larger ice volume. This may be partly due to
the larger glaciers and larger altitudinal ranges. Cogley (2011b) states that Karakoram glaciers are
about twice as thick as Himalayan glaciers. Even if this estimate is rather rough, it is consistent with
the larger ice volume in relation to the area found in the Karakoram.
The total ice volume in the HKH can be estimated in between 1676 and 2543 km3. The uncertainty
is high and hence, the estimated values should be taken as an order-of-magnitude assessment.
Table 10: Ice volume estimates for the HKH based on the HKH inventory areas. Area volume scaling Approach
1 and Approach 2 are explained in the methodology section.
Total area
Volume Approach 1 Volume Approach 2
[km2]
[km3]
[km3]
Hindu Kush
Karakoram
Himalaya
Western Himalaya
Central Himalaya
Eastern Himalaya
Total
2969
22123
25234
8927
8386
7921
50326
105
729
842.1
316
274
252
1676
37
140
1235.7
1167.6
415.8
390
361.8
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The knowledge about the distribution of HKH glaciers in terms of area is relatively good, now that
a complete inventory has been compiled. Even if uncertainties persist and inventory quality varies, it
can be considered the best estimate of the current HKH ice extent for reasons of consistency and
performed quality control. The studies conducted in the field and resulting knowledge of the HKH
glaciers and related processes though still remain very limited.
In the following chapters, the current knowledge on glacier changes across the region is presented
and discussed.
4. Observed changes of Hindu Kush - Himalayan Glaciers
The observed changes of glaciers in the HKH region are presented here according to the glacier
parameter for which a change has been detected (see Methodology section for details on parameters).
The reason for this separation is that changes in glacier area for instance cannot be directly compared
to mass balance or volume data and vice versa and thus do not allow a comparison and quantitative
assessment of the trend in glacier change in the HKH region. On the other hand, of course, not for
every region studies exist and even less for all different parameters.
The integration of data of different studies is not only complicated by the differing measures of
change, but also investigation periods or times vary naturally and longer time series are rare.
Furthermore most studies represent point measurements of single glaciers with inherent low
representativity for larger areas or even entire mountain ranges and thus their use is limited for
regional assessments. This data type makes the identification of regional patterns in glacier behavior,
its change and their interpretation very critical. On the other hand information in this large region is
rather small and thus single glacier studies need to be considered nevertheless, particularly when they
provide mass balance data, as this is the best measure to adequately characterize if a glacier is
shrinking or growing (see section on Methodology).
Some studies investigated several glaciers, and the growing amount of studies using high coverage
remotely sensed data allow assessments of glacier change with a wider scope.
Recently an extensive and systematic review on the evidence of change in glacier melt in the
Hindu Kush Himalayan region has been concluded for the Collaboration of Environmental Evidence
funded by the British Department for International Development (Miller et al., 2010). The review
provides a transparent assessment on the scientific investigations and the resulting findings on the
Hindu Kush-Himalayan glaciers until 2009. Sophisticated and traceable quality assessments were
conducted by the author team resulting in an expert ranking of the studies. Information about the
research, ranking methods and criteria applied are presented in annex 1. Studies which have been
excluded from the report of Miller et al. (2010) for not meeting at least moderate quality criteria will
not be included in this report neither.
4.1 Area change
There are different methods to estimate the area change of glaciers. In the HKH region area change
assessments are usually based on air and space borne imagery due to the remoteness and difficult
access to the study area. An advantage of remote sensing is the time-synchronous compilation of
larger areas. Some difficulties for satellite image interpretation arise from the investigation area (see
Methodology section). Considering the methods applied to derive the area changes, the smallest
potential errors are found in the comparison of two images, taken with the same sensor at different
times. Here, result quality is only influenced by the image quality (resolution, clouds, acquisition
time, snow cover, see Methodology section), through debris-cover on glaciers and the expertise of the
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mapping team. The estimation of glacier changes from the comparison of two or more topographic
maps is ranked less accurate than the comparison of outlines from satellite images. Often the scales of
the two maps differ (Vohra, 1980; Bhrambi and Bolch, 2009) and resulting errors are very difficult to
avoid. Very few studies question the accuracy of the base maps, even though serious accuracy issues
have been reported (Bhrambi and Bolch, 2009; Cogley, 2011b) so that the error in the base map
propagate through the analysis and add to further errors.
Often studies compare satellite images with older maps based on field work. The advantage is that
longer time spans of change can be assessed, where satellite imagery just emerged or was simply not
available. The accuracy and confidence ascribed to the results depends directly on the accuracy of the
baseline map. The existing studies though commonly present no specific estimates of the error in the
topographic maps or of the error arising from the comparison of these two different data sources
(Miller et al., 2010). Bhrambi and Bolch (2009) show inaccuracies and dislocation for several glaciers
mapped in SOI and GSI maps (Please see Methodology section for details). Their study shows that
errors of this magnitude are common in the glacier outlines of the presented topographic maps and
leads to the assumption that large errors have to be expected for other regions. Unfortunately reported
errors cannot be simply translated to other studies using the same methods and thus systematical and
comparative error assessments are not possible. If no consideration on this topic is presented by the
investigators using this method, the results have limited validity.
The presented difficulties in the delineation of the glacier outlines from satellite images
(Methodology section) build a further source of errors and inaccuracies, as well as the process of
digitalization of analogue maps. On the other hand, errors arising from the mapping of glaciers from
aerial images and field measurements are almost impossible to assess, as it is subjected to the
cartographers skills, and the often absent reporting on the method hinders a sound quality estimate
(Salerno et al., 2008, Miller et al., 2010).
Often area changes are reported for single glaciers. Area wide assessments provide a more
representative image of the dominant glacier behavior in a certain region than single glacier area
changes. While lacking of accurate details for each glacier, an advantage of area wide assessments is
the assumption, that errors are somehow equalized over a larger sample size. Considering for example
Salerno’s et al. (2008) work about over 29 glaciers in the Khumbu Himal, the area change rate varies
very strongly from glacier to glacier, ranging from –1.57 %/a to +0.75 %/a. The authors themselves
identified interpretation errors in the 1990s official Nepal topographic map, leading to an exceptional
rate of +74.6% area increase for Tingbo glacier (Salerno et al., 2008) and the expert may find some
further delineation inaccuracies at glacier parts typically difficult to assess with remote sensing
techniques (Personal communication T. Bolch, 2011) as for instance debris covered lateral parts and
snouts. If assessing the behavior of an individual glacier, these errors would very likely exceed the
magnitude of the observed change and therefore invalidate the significance of the findings. In the
overall regional look however, these errors are acceptable as assumed to decrease over a larger sample
size.
Therefore studies covering multiple glaciers or glacier areas are preferred to single glacier studies,
to assess area changes and their regional patterns. Single glacier studies will provide additional
information and maintain the heterogeneity of the whole picture.
Hindu Kush & Karakoram
Reliable assessments of area change are lacking so far.
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Himalaya
Western Himalaya
For 34 glaciers of the Greater Himalayan range in Jammu and Kashmir, a recent study revealed
heterogeneous area changes. While in the first two analyzed periods, all glaciers showed diminishing
areas, in the recent period from 2001 to 2007, 11 of the 34 glaciers expanded their areas, 16 were
approximately stable and the rest showed small to extreme (2 glaciers) mass losses (Pandey et al.,
2011). Unfortunately no numbers of the glacier areas are indicated. The location of the study area is
shown in Figure 218, number 4 “Zanskar”.
Generally, the largest losses were found in the period 1989/1992–2001, this is especially
pronounced on the Northern slopes, where rates were more fluctuating in the past 3 decades. Glaciers
on southern slopes showed more constant rates for the entire period (Pandey et al., 2011).
Figure 18: Locations of area change assessments in the Western Himalaya. Area change rates are
given in the text but not integrated here given the very high uncertainty of the results
The results are based on satellite images of LANDSAT MSS (October 1975), LANDSAT TM
(October 1989, September 1992) and LISS III (August 2001 and 2007) processed with the band ratio
method for automated glacier outline delineation. A not very clear description of method lets suggest
that manual correction for certain debris-covered glacier parts has been applied. An accuracy
assessment for the mapped areas is presented depending on image resolution and uncertainty in the
terminus positions, resulting in ± 0.0023 km2 for the areas derived from Landsat TM image, ± 0.0136
km2 for the LANDSAT MSS image and ±0.0017 km2 for the LISS III images (Pandey et al., 2011).
In the Chenab, Parbati and the Baspa basins, a glacierized area of 2 077 km2 (1962) consisting of
466 glaciers has been estimated based on a topographic map of the Survey of India (SOI) from 1962.
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The area reduced by 21% to 1 628 km2 in the early 2000s (Indian LISS III and IV Sensor images from
2000 (Baspa) to 2004 (Parbati)), an average retreat rate of ~-0.53 %/a (Kulkarni et al., 2007). The
map in Figure 18 shows the approximate location of the studied basins.
The Parbati basin counts 88 glaciers with a total extent of 379 km2 in 2004. The glacier area
experienced an average loss of -0.52 %/a since 1962 (Kulkarni et al., 2007). For the Chenab basin, the
area change for 359 glaciers with a total extent of 1 110 km2 (2001) was estimated to be 22% since
1962, resulting in an average change rate of -0.52 %/a. 19 glaciers were mapped in the Baspa basin,
covering a total area of 140 km2 in 2001. The glaciers experienced an average area loss of 0.475 %/a
and lost almost one fifths since the 1960s (Kulkarni et al., 2007).
The total number of glaciers has increased due to fragmentation, resulting in a reduction of the
average glacier area from 1.4 to 0.32 km2 (Kulkarni et al., 2007). The results must be considered with
care taking into account the methodologies used. The detection of glacier changes from the
comparison of analog topographic maps and satellite images is challenging. The authors give no error
indication or uncertainty assessment for the area estimation. The SOI maps show partly large
inaccuracies (Bhrambi and Bolch, 2009). The delineation of the recent glacier outlines from satellite
imagery has been done automatically with the bands ratio method, accounting for the mapping of
debris covered parts only through geomorphologic features. The authors state that numerous
geomorphologic features can be utilized to identify terminus (Kulkarni et al., 2011, extension of the
2007 study). This only true when permafrost is not interacting with the glacier and the
geomorphologic features. Furthermore not only the terminus but also lateral glacier parts can be
debris covered and accurate terminus mapping alone does not mean accurate area estimation.
In 2011, Kulkarni et al. expanded the 2007 study to further basins in the Western and Central
Himalaya, based again on a 1962 topographic map and 2000-2004 satellite imagery. The approximate
location of the basins is presented in Figures 18, 19 , 20 and 21. This time, retreat has been estimated
only for selected glaciers with clear geomorphologic features. An error estimation has been performed
through comparisons of 261 glaciers to outlines of the Geological Survey of India, finding an error
less than 0.5 %. The small size of the error is unusual and let suspect that both, Kulkarni et al. (2011)
and GSI outlines are based on the same topographic map and therefore validate themselves.
The selected glaciers, covering an area of 72.41 km2 in 1976 lost about 0.58 km2 until 2006. That
equals to less than 1% of the total area in 30 years.
Considering the basin wide assessments, an average area loss of -16% has been observed for 1962
to 2001/2002. Glacier occupying an area of 6 332 km2 in 1962 retreated at an average rate of -0.4 %/a
to 5 329 km2. That is less than found in the 2007 study. Retreat rates range between -0.2 %/a (Miyar)
and -0.75 %/a (Bhaga) depending on the basins. It is noteworthy that the two basins showing the
minimum and maximum rates are situated in direct neighborhood, as Figures 11 and 18 illustrate.
Inconsistencies as for instance the very differing rate of the detailed single glacier (change < 1%)
and the basin wide assessment (-16%) call the attention in the study presented above and need further
investigation. Bhrambi and Bolch (2009) report serious inconsistencies in the work of Kulkarni et al.,
2005 on Parbati glacier.
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Central Himalaya
Garhwal Himal
The glaciers of the Upper Bhagirathi and Saraswati/Alaknanda basins in the Garhwal Himalaya
experienced an area loss of -4.56 ± 2.8% in 38 years. Glacier disintegration led to increasing number
of glaciers with time (88 in 2006). The location of the basins is shown in Figure 19. These results are
based on ASTER images of which a total glacierized area of 572.5 ± 18 km2 was found in 2006. In
comparison to the 1968 extent based on Corona images, the area has decreased from 5 999 ± 16.5 km2
at a rate of -0.12 ± 0.07%/a (Bhrambi et al., 2011).
Basin wise, in the upper Bhagirathi basin, the glacierized area decreased from 275.1 ± 7.5 km2 in
1968 to 266.1 ± 8.3 km2 in 2006. The average change rate is -0.09 %/a, but the error margin of ±
0.07%/a exceeds 75% of the detected change (3.26 ± 2.8% in total). The Saraswati/Alaknanda basin
changed from 324.77 ± 8.4 km2 in 1968 to 306.35 ± 9.5 km2 in 2006, showing a retreat rate of -0.15
%/a ± 0.07%/a (5.76 ± 2.7%). Due to glacier disintegration the total number of mapped glaciers
increased from 69 to 75 (Bhrambi et al., 2011).
The loss in glacier area of individual glaciers shows strong differences from -0.9% to -42.5%
(Saraswati/Alaknanda basin; -2% to -28% for the Upper Bhagirathi Basin) indicating very
heterogeneous glacier behavior within a spatially limited area. Smaller glaciers below 1 km2 lost in
average -0.51 ± 0.07 %/a in area, while the largest glaciers exceeding 50 km2 in area lost -0.074 ±
0.071 %/a (Bhrambi et al., 2011). Notice that the uncertainty for the larger glacier´s rate is as high as
the change.
Strong differences of change rates could be identified depending on the exposition. While south
facing glaciers lost about one fifth (19.4 %) of their area in 38 years, north-facing glaciers lost on
average only 4.7 %. Both investigation areas showed similar debris covered fractions of glacier ice of
about one quarter. An increase in debris covered glacier ice was found for both basins of +17.8 ±
3.1% (Saraswati/Alaknanda) and +11.8 ± 3% (Upper Bhagirathi), respectively (Bhrambi et al., 2011).
Figure 19: Locations of area change assessments in the Central Himalaya. Area change rates are
given in the text but not integrated here given the very high uncertainty of the results.
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Nepal
Based on the new inventory of Nepalese glaciers (Bajracharya et al., 2011) and the older version of
ICIMOD (Mool et al., 2001) an area change assessment has been made. The comparison of inventory
data compiled with different methods and sources shows high uncertainties and with regard to the
very high uncertainties of the older inventories presented in Chapter 3 results of this study are only
presented here in a qualitative manner: Glacier area decreased and the number of glaciers increased
(Bajracharya et al., 2011). Even the authors discuss that the increase of glaciers can be cause by a)
fragmentation, b) reduced snow cover in the recent study and c) more detailed mapping of the recent
study.
Eastern Himalaya
Eastern Nepal
An inventory counting 1024 glaciers in Eastern Nepal covering an area of 1597 km2, which
compromises the Kanchenjunga, Khumbu, Rolwaling and Langtang Himalayas has been presented by
Asahi (2001). Changes in glacier area were estimated based on topographic maps based on aerial
photography from 1992 and 1958 topographic maps. The topographic maps the inventory is based on
have a resolution of 1:50000 (Ageta et al., 2001). 153 of observed glaciers (15 %) are debris-covered.
The author excluded 54 % of the glaciers of the assessment for being not reliable data. Of the
resulting 456 glaciers, 56.8% were found retreating, 34.6 % of the glaciers showed stationary
conditions and 8.6 % were advancing (Asahi, 2001). For language restrictions, only the abstract of
the publication in Japanese could be included plus citations (Ageta et al., 2001) and no quality
assessment of methods and reporting of methods could be performed. Therefore the values given
should be considered with care and be used only for order of magnitude or trend assessments even if
the exclusion of uncertain data lifts the confidence assigned.
Shorong Himal / AX010
The area of glacier AX010 has decreased from 0.57 in 1978 to 0.42 km2 in 1999. The total loss of
26% equals to an average rate of -1.24 %/a. No error quantification is provided (Fujita et al, 2001).
Khumbu Himal
Investigation of glacier area changes in the Khumbu Himal based on satellite imagery (Corona,
Landsat, ASTER) revealed retreat rates of -0.12 %/a ± 0.00047% from 1962 to 2005 (-5.3% ± 2%).
The investigation area is shown in Figure 20, number 13. The four point times series (1962, 1992,
2001, 2005) showed highest rates between 1992 and 2001 of 0.25 %/a. The clean-ice area diminished
by >10% in the investigation period (Bolch et al., 2008).
For glaciers located within the same region (Sagarmatha national park), a slight overall decrease of
glacier area from 403.9 to 384.6 km2 (-4.9%) within an approximately 34 years covering time span
has been observed, resulting in an average area change rate of -0.14 %/a for the hole area. The map
in Figure 20 shows the study site location with number 14. The results are based on the comparison of
topographic maps from the late 1950s and early 1990s. The authors assign an error associated with the
cartographic interpretation which is equal to the size of the detected change, 4.9% (Salerno et al.,
2008).
The average retreat rate is composed by receding but also increasing glacier areas, varying
strongly within the sample counting 29 glaciers. Maximum area change rate is found for Nuptse
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glacier, increasing its surface by 25.4%, while maximum retreat is found of Kdu_gr 38 loosing over
the half of its area (53.5 %) (Salerno et al., 2008).
Differences in glacier change were identified according to glacier size and elevation: Larger
glaciers situated at higher altitudes increased in size during the study period, while the smaller
glaciers at lower elevations decreased. The increase was mainly found on south facing slopes in the
accumulation areas while the same glaciers show receding tongues. Glaciers whose area decreased are
orientated to other than southward direction and show steeper slopes and lack of debris cover. Larger
glaciers in the area face commonly southwards, from where the main moisture transport occurs. For
the smaller glaciers, the sections most affected by change were the accumulation zones, and these
glaciers showed a tendency for the front to advance (Salerno et al., 2008).
Uncertainties in the deduced area change rates of this study are high (see Tingbo glacier; Salerno
et al., 2008). Some misinterpretations in glacier outlines as for instance in the delineation of Cholo
glacier tongue catch the experts eye (Personal communication T. Bolch, 2011). Over the large sample
size, these errors may be equalized to a certain degree. The single glacier rates though should be
considered with care.
Bhutan Himalaya
Glacier variations in terms of area changes have been studied for 66 clean ice glaciers the Bhutan
Himalayas. The estimated surface of 147 km2 has decreased at an average rate of -0.18 %/a within
the 30 year period until 1993. The change estimate is based on SOI toposheets of the 1960s and a
SPOT image of 1993 (Karma et al., 2003). Even though debris covered glaciers have been excluded to
enhance the accuracy, no error discussion is provided and the quality of the results is uncertain.
Additionally length changes have been investigated, revealing a north south gradient with increasing
retreat rates southwards.
Figure 20: Locations of area change assessments in the Eastern Himalaya. Area change rates are
given in the text but not integrated here given the very high uncertainty of the results.
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Conclusion Area Changes
The overall image of area changes in the Himalaya is clearly glacier decrease. All of the
investigations report area losses in the past three to four decades, as Table 11 indicates. The
investigations are limited to the Himalayas though. For the Hindu Kush and Karakoram ranges, no
quantitative area change assessments exist so far.
Good agreement on average retreat rates in the past 40 years of -0.14 to -0.12 ± 0.05%/a is
reported from two independent studies employing different data sources for Khumbu Himal (Salerno
et al., 2008; Bolch et al., 2008) in the Eastern Himalaya. A study from the Central Himalaya, Garhwal
Himal report similar rates of -0.12 ±0.07 %/a (Bhrambi et al., 2011).
The individual glaciers show very heterogeneous behavior within the larger investigation areas,
including increasing areas. This is reported by Asahi (2001) for a larger investigation area in Eastern
Himalaya including also the Khumbu Himal and by Pandey et al (2011) who report 11 of 34 glaciers
with increasing areas in the Western Himalaya in the recent period of 2001-2007 (Results are not
integrated in the table, as not quantitatively comparable). The dominant pattern though is area loss,
which is especially pronounced on smaller glaciers as AX010.
Figure 21: Area change studies for glacier areas across the HKH region. Note that sites of all
numbers besides 11,13,14,16 are investigated by the studies of Kulkarni et al. (2007 and 2011)
A lot of the area changes estimates across the Himalaya are based on one source (see Figure 21
and Table 11). It is catching the eye that all the reported values of this study are a lot higher than the
other estimates, on average in the magnitude of factor 3 and this phenomenon is not limited to one
region. This lets suggest an overestimation of the shrinking rate by Kulkarni et al. (2011). This is not
unlikely considering the information on which the estimates are based and the accuracy issues
reported on them (Bhrambi and Bolch, 2009).
Interesting are findings for the Garhwal Himal (Number 10 and 11 in Figure 19) and Khumbu
(Number 13 in Figures 20 and 21) about the influence of exposition on glacier area change. While
south facing glaciers in the Garwhal Himal are reported to experience high area loss rates (north
facing smaller area loss rates, respectively), the south facing large glaciers of the Khumbu HImal
show even increasing areas, mainly concentrated in the accumulations areas (receding snouts are
reported from the same glaciers).
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Table 11: Area change studies and results in the HKH region
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4.2 Volume changes
Estimating a glaciers volume by field measurements is very difficult due to the large area to assess
and the difficult terrain and consequently difficult access. In any case, it is impossible to directly
measure the volume of all glaciers and thus a combination of measurements and interpolation
techniques needs to be chosen. Ice volume can also be determined with the means of remote sensing
and GIS applications. When accuracy and error estimation is provided this method delivers the best
estimates of glacier volume (Miller et al., 2010).
Geodetically estimated volume based on satellite images can be compared to field mapping
estimates, as for instance done by Kulkarni et al. (2007).
Another possibility is a combination of thickness profiling with glacier area mapping. The volume
is estimated based on measured or assumed thickness profile and resulting averaged thickness maps.
Observed area changes are then translated to volume changes. An assumption commonly adopted for
the thickness maps is a uniform slope of the glacier bed (Miller et al., 2010), thus the resulting
estimates of the base volume are generally of rough nature themselves. Often validation of thickness
estimates is lacking and thus uncertainty is very high.
The investigations performed in the HKH region to accurately estimate volume change are very
limited and this parameter is the least studied, if considering the number of publications on glacier
changes in the HKH. Furthermore, there is a concentration of studies on Himachal Pradesh and no
quantitative investigation on Hindu Kush or Karakoram glacier volume changes has been performed
yet. A lack of knowledge on volume and volume changes of glaciers in the HKH has to be stated so
far, which shows its most extreme form in the absolute lack of reliable volume (change) studies for
the entire Karakoram and Hindu Kush mountain ranges. The volume estimates based on the new
compiled inventory (Frey, 2011) therefore help in closing an important knowledge gap on current ice
resources in the region.
The investigations on volume changes concentrate on single glaciers with limited
representativeness for larger change assessments. An exception is Himachal Pradesh, where volume
changes of larger glaciers samples are reported by Kulkarni et al. (2004, 2007, 2011) and Berthier et
al. (2007) but the uncertainty in the results is generally very high and the area changes reported by the
first study are found to be likely to be overestimated (see Conclusion Area Changes).
Himalaya
Western Himalaya
Himachal Pradesh
Elevation changes have been calculated through comparison of two DEMs (SRTM and SPOT5)
from 2000 and 2004 and allowed the estimation of the respective volume loss. The volume loss
estimates under the constant density assumption (constant density of ice over the hole glacier ρ=0.9
kg/m3) is – 3.87 km3, that equals a rate of -0.774 km3 per year over the entire glacierized area of 608.5
km2 (of the 915 km2, 66.5% have been assessed because of artifacts in the remaining areas, see
paragraph above). Unfortunately no reference volume is given and thus comparability is limited,
maybe because of the consideration of only parts of the glaciers (the loss equals to -0.85 m/a/km2
glacier). Even if standard deviation in between the two DEMs on the ice free terrain is high with 16m,
the authors suggest that errors reduce over the large investigation area of 915 km2. Furthermore
artifacts in the DEMs were detected and consequently these glacier parts were excluded from the
calculation (Berthier et al., 2007). This procedure increases the accuracy of the results for the
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remaining glacier parts, but lowers the representativeness of the detected change for the entire glacier,
as 21 to 42% of the glacier’s area has not been considered.
Strongest lowering of glacier surfaces has been observed at low elevations (8 to 10 m below 4400
m), independent of the amount of debris cover. Higher elevations experience a reduced thinning of
about -2m. Most low elevation glacier tongues are heavily debris covered and show high thinning
rates (Berthier et al., 2007). This is unexpected following the assumption that debris cover above a
certain thickness threshold prevents from enhanced melting because of the protection of solar
radiation (Benn and Lehmkuhl, 2000).
Volume changes for 466 glaciers of Baspa, Parbati and Chenab basins are estimated based on
remotely sensed outlines and subsequent area volume scaling. A volume reduction of one third has
been estimated for all three basins since 1962, equaling to an average loss rate of ~-0.77%/a for the
region. The 359 glaciers in the Chenab basin showed the highest volume loss of -0.83 %/a. In Parbati
basin loss rate was estimated to -0.66 %/a. The 19 glaciers of Baspa basin lost on average -0.57 %/a
(Kulkarni et al., 2007).
The error assigned to the volume estimation method is 10 to 20% based on literature, the total loss
is 30.8 % (Kulkarni et al., 2007), thus the volume decrease can vary within the range of -10 and 50%. The areal extents on which the scaling is applied were derived from a SOI topographic map
from 1962 and Indian LISS III and IV images for 2000 to 2004. The determination of change rates
based on the comparison of analog topographic maps and satellites imagery is critical itself.
Furthermore strong inaccuracies were found in topographic maps of the region (see section on
Methodology). Therefore change rates estimated here should be considered very carefully.
Central Himalaya
Nepal
The volume change of Rikha Samba in the Hidden Valley in Western Nepal has been estimated to
amount 12.6 m ice equivalent between 1974 and 1994 (Fujita et al. 1997) what equals to ~13.74 m
w.e., a rate of -0.68 m/a w.e. or -0.65 %/a . Unfortunately the study could only be assessed at abstract
level and no quality assessment can be provided.
Eastern Himalaya
Shorong Himal / Glacier AX010
Glacier AX010 is a small glacier of 0.57 km2 in the Shorong Himal extending between 4950 and
5300 m a.s.l. (reference date 1978, Kadota et al., 1997) and has no debris accumulations (Bolch et al.,
2008). The glacier lost -4.8 x 106m3 from 1978 to 1991 (Kadota et al., 1997). No reference volume is
provided; per km2 this equals to a loss rate of -0.65 m/a. The estimates are based on surface changes
derived from own topographic mapping and a density assumption of ρ=0.85 kg/m3 (Kadota et al.,
1997).
Khumbu Himal
Volume changes based on Corona (1962) and ASTER (2002) DTMs of Khumbu, Nuptse, Lhotse
Nup and Lhotse glaciers were investigated. For the image limits, only about 50% of the ablation zone
of Khumbu Glacier is included and no reference volume is provided. Thus the results are limited in
representativeness for the entire glacier and not comparable. Down wasting has been observed for all
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glaciers, with minimum lowering rates of -0.275 m/a for Lhotse Glacier, but the estimated error is
hardly smaller than the detected change. Therefore the findings should be used qualitatively for trend
and order of magnitude assessments. The down wasting is clearly pronounced in the middle part of
the glaciers, where the authors suppose the location of the transition zone between the active and
inactive glacier parts (Bolch et al., 2008).
Conclusions Volume changes
The overall pattern in the Himalayas is volume loss of glaciers in the past decades. There exist no
knowledge about glacier volume evolution in the Karakoram or Hindu Kush mountains.
Unfortunately, the data base on volume changes in the HKH region is too sparse to make any
quantitative statements. Very few studies have been conducted on volume changes in the HKH region
and of the ones available, none provides sound and comparable results at the same time. Even if the
employed method is adequate and error assessment is provided, the glacier volume change is only
assessed for a part of the glacier (Bolch et al., 2008 for Khumbu; Berthier et al., 2007, Himachal
Pradesh) or only the total volume loss without reference volume is given (Kulkarni et al., 2004;
Berthier et al., 2007, Himachal Pradesh, Bolch et al., 2008). Other estimates are based on the SOI
maps without reflection on its accuracy and roughly estimated errors exceed 50% of the detected
change already without taking the basemap quality into account (Kulkarni et al., 2007). Relative
reliable single glaciers studies exist for Rikkha Samba (Fujita et al., 1997) and Glacier AX010
(Kadota et al., 1997), both situated on Nepalese territory. Table 12 on the next page summarizes
available quantitative results.
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Table 12: Volume change estimates for the Himalayas. No reliable studies quantifying volume change exist for Hindu Kush and Karakoram
glaciers.
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4.3 Mass Balance
There are different methods available to estimate a glacier´s mass balance. The glaciological
method measuring the ablation and the accumulation directly on the glacier provides the most detailed
information on the spatial variation of mass balance over the entire glacier.
The overall or specific mass balance of a glacier can also be determined with the geodetic method.
Surface elevation difference for two different dates is calculated. Assuming an ice or firn density, the
volume change can be calculated. The use of high resolution remote sensing for this task is helpful for
regions as the Himalaya. With this method, no mass balance gradient, the change of mass balance
over the glacier length, can be determined, which is a good indicator for a glacier’s sensitivity. Also,
usually mass balances over longer time scales are assessed with this method.
The hydrological approach is an indirect method based on the water balance and requires a lot of
data on precipitation, run off and evaporation, seldom available directly at the glacier and spatial
representativeness of the existing stations, usually at a certain distance of the glacier, is limited. This
is particularly true for the investigation area, exhibiting strong not always linear vertical precipitation
gradients and extreme local precipitation variability due to narrow valleys and resulting luv-lee effects
(see also the section The Hindu Kush-Himalaya: Regional Setting).
A disadvantage in the use of mass balance data is the necessity for data extrapolation when larger
glacier systems should be assessed. No completely reliable approach to mass balance data
extrapolation has yet been found (Dyugerov and Meier, 2005). This limits the use of mass balance
data for larger areas (when not measured for each glacier) and generalizations are critical considering
the high variability. The mass balance data is presented here to amplify the generalized pattern of
larger area changes with pointed detail insights.
In one of the most recent and comprehensive global inventories (Wagnon et al., 2007) of mass
balance measurements (>1 year), data from the HKH is very underrepresented considering the
relative amount of glaciers gathered in this mountain range in comparison to other regions (Kaser et
al., 2006). Only 11 glaciers from the Himalaya and none of the Karakoram nor Hindu Kush are
presented (Dyugerov and Meier, 2005).
Hindu Kush
No mass balance measurements have been reported in the international literature.
Karakoram
Mass balance data for the Karakoram is scarce, consisting in exactly one reliable study providing
mass balance data for Siachen glacier by Bhutiyani (1999).
The Siachen glacier is situated in the Eastern Karakoram in the Nubra valley and represents with
~78 km length the largest glaciers in the HKH region (see Figure 21). Its location is shown in Figure
23. The specific mass balance has been on average –0.51 m w.e./a during 1986-1991. The most
negative value has been estimated for 1990-1991 with -1.08 m w.e.. Positive values were found for
the hydrological year 1988-1989 with +0.35 m w.e. The authors suggest an overall error of ~15%
based on literature, accounting for errors in accumulation, ablation and evaporation measurements
(Bhutiyani, 1999).
Siachen glacier’s mass balance has been estimated with the hydrological method, representing the
only mass balance series for the Karakoram. Even if the hydrological method is ranked as lower
accuracy in estimating the specific mass balance than other methods, the methodology applied by
Bhutiyani (1999) with five gauges distributed over the glacier for precipitation and evaporation
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measurements increases the confidence assigned in the results. Commonly one rain gauge
“somewhere near” the glacier is used.
Figure 21: The longest glacier of the HKH Region: Siachen glacier in the eastern Karakoram
(Number 155;) Landsat 3 scene of 18th of August 1979.(See also Figure 23 for its location in the
HKH)
Shroder and Bishop, 2010b
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Himalaya
Western Himalaya
Himachal Pradesh
Specific mass balance for a glacierized area of 608.5 km2 (2002) in the Lahaul and Spiti region has
been estimated for the period 2000 to 2004. Values between −0.7 and −0.85 m/a w.e. depending on
the assumed density (ρ=0.6 kg/m3 and ρ=0.9 kg/m3 respectively) were determined (Berthier et al.,
2007).
Making use of remote sensing techniques, Berthier et al. (2007) presented the only mass balance
estimates for a large sample of glaciers in the HKH region. The investigation area is situated in
Himachal Pradesh. Digital elevation models (DEM) derived from satellite imagery (SPOT5 images
and SRTM DEM, additional visual source ASTER) were used to estimate the mass balance from the
detected elevation change between 2000 and 2004. The DEMs were corrected and empirically
adjusted to each other to minimize the vertical difference off glacier resulting in ±0.43 m as mean
error and ±16 m standard deviation. The overall specific mass balance was modeled assuming an ELA
of 5100 m for the whole region, constant glacier area and the density in the accumulation area to be in
between ice and firn. Uncertainty and error sources are discussed but cannot be quantified due to
lacking ground data. Although verification with field measurements showed good agreement for
Chhota Shigri glacier (Berthier et al., 2007; Wagnon et al., 2007), large errors and uncertainty advert
from the use of individual glacier mass balance. Between 20 and 48% of each glacier area has been
excluded from the analysis due to DEM artifacts (total glacier area is 915 km2, of which 608.5 km2 are
included in the assessment). This procedure decreases the overall error but also the representativeness
of the estimate for the entire glacier.
Considering the sizes of glaciers, all size classes show ice loss. The specific mass balance was
most negative for larger glaciers (> 30 km2, spec. mass balance = -1.04 and -0.86 m w.e./a
respectively, depending on the density assumptions). Even if the category consists only in three
glaciers, the summed area is similar to the ones of the other size classes, which show both less
negative mass balances (<10km2: -0.63 to -0.46 m w.e./a and 10- 30 km2: -0.6 to -0.51 m w.e./a,
respectively; Berthier et al., 2007).
On Chhota Shigri Glacier situated as well in the Lahaul and Spiti valley (See Figure 23), a long
term mass balance series has been initiated in 2002. Wagnon et al. (2007) present results of the first
four years of monitoring, with mass balances estimated with the direct glaciological method and
velocity measurements. The 9 km long glacier (15.7 km2) has an average negative specific mass
balance of -0.97 m w.e., altering between –1.4 m w.e. (2002/03, 2005/06) and +0.1 m w.e. (2004/05;
-1.2m w.e. in 2003/04). The respective ELAs are 5180 m a.s.l. and 4855 m a.s.l.. Chhota Shigri mass
balances are strongly dependent on debris cover, exposure and the shading effect of surrounding steep
slopes. Debris cover significantly protects the lowest part of the glacier from melting. An error
estimate of ±0.2 m/a w.e. is given.
The mean vertical mass balance gradient in the clean-ice parts of the ablation zone was found to be
+0.7 m w.e./100 m. The diagram in Figure 22 shows the mass balance gradients for clean-ice and
debris-covered glacier parts. Ablation is limited to the summer month. In these terms of gradient and
ablation season Chhota Shigri is similar to the European mid-latitude glaciers (Wagnon et al., 2007).
Further work needs to be performed to corrobate the similarity and to derive possible analogies for
glacier sensitivity.
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Figure 22: Annual mass balance distribution with altitude. The dashed and plain curves
represent mean gradients of specific mass balance as a function of altitude the clean ice part
of the glacier for 2003/04 and 2004/05, respectively. A: Debris-free glacier part, B: debriscovered glacier parts, C: tributary. Below 4400 m a.s.l., stakes were inserted in the debris
covered area of the glacier and experienced reduced ablation compared to their respective
gradients (Wagnon et al., 2007).
Wagnon et al. (2007)
The relationship of accumulation area ratio to the specific mass balance has been determined for
Shaune Garang and Gor Garang glaciers of Baspa basin in Himachal Pradesh (see Figure 23) based on
reported mass balances measured in the field by the GSI from 1982 to 1988 (Shaune Garang) and
1976 to 1984 (Gor Garang), respectively (report on GSI data: Sangewar and Siddique, 2006 cited in
Kulkarni et al., 2011). The established empirical relationship shows with r2=0.80 (Kulkarni et al.,
2004) a good correlation and suggest that these glaciers are in steady state conditions (specific mass
balance = 0) when accumulation and ablation area have about equal extent (AAR = 0.5).
The relationship has been applied to 19 glaciers of Baspa Basin to estimate specific mass balances
for 2001 and 2002. The glacier areas have been derived from LISS III sensor images and snow lines
with a sample of WiFS sensor images, both Indian remote sensing satellites (Kulkarni et al., 2004).
The overall specific mass balance for glaciers of Baspa Basin for the year 2000/01 was -0.90 m
w.e., ranging from -0.25 to -1.20 m w.e. for individual glaciers. In 2001/02 a slightly less average of –
0.78 m w.e. has been estimated, ranging from -0.19 to -1.20 m w.e..
Differences of specific mass balances for individual glaciers according to exposition and the midaltitude have been observed: as mid-altitude rises from 5000 to 5400 m a.s.l., specific mass balance
rises from –1.11 to –0.49 m w.e. (Kulkarni et al., 2004). This is consistent with the assumption that
mid altitude is a good indicator for the ELA.
The study has been extended to the years 2003/04 and 2005/06, and less negative overall specific
mass balances of -0.57 and -0.50 m w.e. were measured (Kulkarni et al., 2011).
The glaciological method has been used to estimate Naradu glacier’s mass balance for the years
2000 to 2003. Naradu is also situated in the Baspa basin, Himachal Pradesh (see Figure 23). The
specific mass balance is constantly negative with very similar values of -0.35 (2001-2002) to -0.44
(2000-2001) m w.e. per year, averaging to a mean specific mass balance of -0.4 m w.e./a. To assess
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glacier-climate interaction processes, two meteorological stations were installed at the glacier snout
and at approximated firn line altitude. The glacier receives over two thirds of the precipitation in
winter and spring and thus is similar in these terms to mid-latitude glaciers. It is partly debris covered
and surrounded by a cirque with steep walls. Additionally AAR are provided and range from 0.46 to
0.5 (Koul and Ganjoo, 2010) confirming the values obtained by Kulkarni et al. (2004) in the same
basin.
Central Himalaya
Garhwal Himal
Dokriani glacier is situated south west of Gangotri glacier in the Garhwal Himal (see Figure 23).
The 5.5 km long glacier occupies an area of 7.0 km2. The mean mass balance for the investigation
period of 1992/93 to 1999/2000, estimated with the glaciological method, has been on average -0.32
m w.e./a., with 1998-99 being the most negative year (-0.46 mm w.e./a). During the investigation
period Dokriani´s mass balance has never been positive. AAR for steady state conditions has been
determined as 0.73. GPR measurements revealed maximum thickness of 120 m. Altitudinal extent is
from 3880 to 6000 m a.s.l., with an ELA fluctuating between 3030 and 3095 m a.s.l. during the
investigation period (Dobhal et al., 2007 and 2008).
Nepal
The annual mass balance of Rikha Samba in the Mukut Himal (see Figure 23) has been on average
-0.55 m w.e. between 1974 and 1994 (Fujita et al. 1997). Unfortunately the study could only be
assessed at abstract level and thus no quality indication can be provided for this rate.
Eastern Himalaya
Shorong Himal – Glacier AX010
Glacier AX010 is a relatively small glacier in the Shorong Himal. It has been observed in field
campaigns in 1978, 1979, 1989, 1991 and from 1995 to 2001 every year. Averaged annual mass
balances rates from 1978 to 1996 and from 1996 to 1999 are estimated to -0.70 and -0.74 m w.e./ a
respectively (Ageta et al., 2001; Original source is Ageta et al., 1983, but the publication is not
available in English language). The estimates from 1978 to 1991 are based on surface changes derived
from own topographic mapping and a density assumption of 0.85 kg/m3. In 1995 a more detailed
monitoring program has been initiated providing additional ground surveys, stake measurements and
further mapping (Kadota et al., 1997). In 1996/97 and 1997 /98 the glacier showed negative mass
balances over its entire extension, lacking literally of an accumulation area in these years (Fujita et al.,
2001a in Ageta et al 2001).
Khumbu Himal
The specific mass balance of glaciers in the Khumbu Himal covering an approximate area of ~50
km2 has been estimated to be in average -0.32 ± 0.08 m/a w.e. for the period 1970 to 2007. The
estimations are based on satellite imagery of CORONA and Cartosat-1 of the years 1970 and 2007
(plus 1962 for additional information) and aerial photographs of 1984 in combination with an ASTER
derived DTM. Positional corrections with non-differential GPS and control points from topographic
maps have been applied and a sophisticated error assessment is provided (Bolch et al., 2011)
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Khumbu glacier’s specific mass balance has been estimated to −0.27 ±0.08 m/a w.e. for the period
1970-2007 derived with remote sensing techniques (details for the method see above, Bolch et al.,
2011).
Conclusions mass balance
Even though only a limited number of studies on mass balances in the HKH region exist, they
provide a clear picture of negative mass balances. Positive values have been reported only isolated for
single years within a series of mainly negative balances, for instance Chhota Shigri in 2004/05 with
+0.1 m w.e. and Siachen with +0.35 m w.e. in 1988/89 (Wagnon et al., 2007; Bhutiyani, 1999).
In the Karakoram, only one glacier, the longest of the HKH region, has been studied: Siachen
shows negative mass balance of -0.55 m/a w.e. during 1986 to 1991.
In the Western Himalaya, characterized by the highest score of investigations on this parameter,
average specific mass balance values of -0.4 to -1.35 m/a w.e. are reportet. The latter, comparatively
extreme value, is a very short term average of only two years in the end of the 1980s. Nevertheless an
independent study found similar values of -1.4 m/a w.e. for 2002-2003 on the same glacier (Wagnon
et al., 2007). In the Central Himalaya, values range from -0.32 to -0.55 m/a w.e., but the sample
consists of only 2 glaciers.
In the Eastern Himalaya, two studies report on mass balance: The small glacier AX010 in Shorong
Himal shows a stronger loss with -0.71 m/a w.e. than the assessed larger area in the Khumbu Himal,
northeast of Shorong. Here mass balance has been estimated to -0.32 m/a w.e. in the past three
decades. Even considering the high error margin of one quarter, values are significantly lower, and
indicate a possible dependency of loss rate on glacier size.
Figure 23: Available mass balance data for glaciers across the HKH region
In comparison to area and volume change studies, the time spans covered by mass balance studies
are rather short as Table 13 indicates. Even within the short series, very high inter-annual variability
can be stated.
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Again a lack of studies for the Hindu Kush and Karakoram (one single study available) has to be
stated, but also the easternmost parts of the Himalayan range draining towards the Bhramaputra lack
of reliable mass balance studies so far.
Table 13: Mass balance data for the HKH region.
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Considering only large area assessments, an average of -0.59 m/a w.e. can be estimated for the
glaciers of the Himalayan range and for recent years (2000-2004) as presented in Table 14. Even if
three averaged values cannot be representative, the similarity of the values for Himachal Pradesh in
the order of ~-0.73 m w.e./a can be stated and a significantly lower rate for the Khumbu area in
Eastern Himalaya.
Table 14: Specific mass balances of glacier areas of the Himalayan range
These values are in good agreement to other recent overall estimates as -0.57 m w.e. for 19872006 (Miller et al., 2010) and – 0.41 m w.e. for 1961 – 1999 (Dyugerov and Meier, 2005). Including
the Karakoram, Cogley (2011b) states -0.364 (±0.055) m w.e.. The less negative value when
including Karakoram glaciers is in accordance to observations of glacier growth in this region and
consequent less negative mass balances. Further information on the “Karakoram Anomaly” (Hewitt,
2005) will be presented in the following section.
4.4 Additional information
Remotely-sensed investigations on terminus positions and velocities between 2000 and 2008
across the HKH revealed that the most of the glaciers in the monsoon driven Eastern Himalaya are
receding. Debris-covered glaciers though show commonly stable fronts. In all study sites from the
Hindu Kush to Bhutan Himalaya, advancing, stable and retreating glacier tongues have been
observed, showing the heterogeneous behavior within each subregion. In the Karakoram, over the half
of the observed terminus positions remained stable or slowly advancing. The highest fraction of
retreating glaciers has been found for the Western Himalaya and the northern slopes of central
Himalaya, where the authors suggest a lower fraction of debris covered glaciers (Scherler et al.,
2011). The error ranges often exceed the detected change and thus limits the reliability and utility of
results, not only quantitatively. Figure 24 shows the detected terminus changes for the different sub
regions.
Figure 24: Terminus changes from 2000 to 2008
across the HKH determined with remote sensing.
Note that errors bars often exceed the detected
change. HK: Hindu Kush; K: Karakoram; WH:
Western Himalaya; CHS: Central Himalaya
South; CHN: Central Himalaya North;(Areas
delineations are as shown in Figure 3: sub
regions) WKS: West Kunlun Shan (outside the
focus of this study)
Scherler et al., 2011
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Hindu Kush
The investigations on the glaciers of the Hindu Kush range are extremely scarce considering actual
coverage, distribution and knowledge of most simple glacier parameters. Glacier change parameter as
mass balance, area and volume estimates are completely absent as well as reliable and comparable
reports on length changes (Miller et al., 2010), therefore, additional available information will be
consulted here.
Investigating pro- and supra-glacial lake evolution in the HKH region with remote sensing
imagery, a recent publication found diminishing lake coverage in the Hindu Kush and Karakoram
from 1990 to 2009. Growing glacier lakes are associated with growing glacier wastage. Glacial lake
coverage has decreased by half in the past two decades in the Hindu Kush, where relatively small
supra-glacial lakes dominate. In the Karakoram, lake coverage diminished by a third. In the Himalaya,
especially in the Central and Eastern parts, glacier lakes increased their coverage in the same period
(Gardelle et al., 2011). These results indicate firstly a glacier change pattern differing from the one
dominating the Himalayas and secondly a potentially stable or even advancing glacier behavior.
Karakoram
As shown in the preceding chapters, the reliable information on Karakoram glaciers is extremely
scarce, especially quantitatively, and in consequence, the region lacks of estimates of fundamental
glacier parameters (Shroder and Bishop, 2010p). Some information though exists mainly reported by
Hewitt (2005), allowing an insight to this large glacier region which shows recently very differing
glacier behavior to the most of glacier areas in the world. Therefore this additional information is
presented here, even if comparable estimates as area changes or mass balance data cannot be
provided.
Glacier expansion has been reported at the highest altitudes of the Central Karakoram Range since
the late 1990s, characterized of an unusual sudden onset after decades of decline (since the 1920s with
some short term exceptions in the 1970s). The map in Figure 25 gives an overview of observed
changes and data is summarized in Table 15.
Figure 25: Central Karakoram range with glacier change indication by Hewitt, 2005.
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The glaciers increasing their thickness are rather large, mainly extent over a wide altitudinal range
and most of them have accumulation areas starting above 7000 m a.s.l., some reaching down to 2300
m a.s.l. as the analysis of glacier parameter per sub region revealed (see Chapter 3). This is much
lower than the most of the glaciers in the Western and Central Himalayas (see Table 9). The
information on glacier change has been collected in field surveys between 1985 and 2002 and is
mainly based on observations of ice margin geometries and related processes which are clearly
associated with expanding glaciers. Some changes could be detected with LANDSAT imagery,
mainly sudden length changes (surges) but the author states that the use of satellite images is limited
for the monitoring because observed ice-margin features and the purely vertical shifts identified are
too localized for remote sensing methods or hidden by debris cover (Hewitt, 2005).
Table 15: Observed characteristics and changes of Karakoram glaciers
Hewitt, 2005.
The lack of historic and on-going climatological and glaciological measurements at these high
elevations makes the analysis and scientific understanding of this phenomena, coined as “ the
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Karakoram anomaly”, very difficult. A possible explication is proposed in an atypical high zone of
maximum precipitation at about 5000 to 6000m a.s.l. in combination with steep and high walls acting
as snow catchers nourishing the accumulation zones of the glaciers with high precipitations amounts
(as Biafo Glacier without avalanche accumulation) and avalanches respectively (Hewitt, 2005).
Comparing glacier length evolution from 2000 to 2008 over the HKH region, Scherler et al. (2011)
found that the Karakoram sample poses an exception to the overall retreating glaciers from the Hindu
Kush to Bhutan. Here, terminus positions are in their majority (>58%) stable or slowly advancing.
The estimated rate of 8 m/a however, is smaller than the error margin of ± 12 m/a.
While expansion is reported for the high situated and large glaciers in the Central Karakoram,
retreat has been observed for glaciers located north and westwards, namely in the Upper Chapursan,
Chalt, Naltar, Karambar, and Darkot valleys (Hewitt, 2005). Hence, as well in the Karakoram
spatially very heterogeneous glacier changes have to be stated.
Considering the ice thickness, Cogley (2009) states 86 m of average glacier thickness for the
Himalayas and 172 m for Karakoram glaciers. These numbers should be taken as qualitative
measures, as Cogley (2011b) states the incompleteness of the used inventories. Surges are a particular
observation in this region.
Surges in the Karakoram
In the Karakoram, surge behavior has been observed for Bultura (1987) and Chiring (1994)
glaciers. Khurdopin Maedan, a tributary to Panmah glacier, has been advancing ~2.5 km since the mid
1990s. For Sherpigang the glacier terminus had advanced 1 and 4 m within one single week in July
2001 (Hewitt, 2005).
The terminus position of Liligo glacier, a rather small glacier of about 17 km2 (~10km length)
situated in the Karakoram as well, south of Baltoro glacier, has been investigated based on various
sources from the dating as far as from the late 19th century. Even if a surge-type behavior has been
stated beforehand, the picture from the early 1990s differs strongly from its behavior until then. The
partially debris-free terminus shows bulging appearance and is heavily crevassed. It had advanced far
beyond the reference spots of the former analysis and was situated at only 50m (± 5m) distance of
Baltoro in 1997. Only a decade earlier (1986), its snout position has been 1400 m (±75m) far behind.
The lack of continuous information does not allow the determination of the onset of Liligo’s advance:
After a period of recession, it started advancing between 1954 and 1986. Even if the estimated
averaged pace of advance is rather slow, the authors suggest a surging glacier type (Diolauti et al.,
2003).
Based on MSS and Landsat imagery, Shroder and Bishop (2010b) investigated unusual or
irregular glacier response of 161 selected glaciers in Pakistan based on surge-typical features. They
found clear signs of surge behavior on a lot of glaciers, unfortunately information is of rather
qualitative nature.
Langtang Himal
The Lirung glacier has been measured in the late 1990s through a research team of Ageta et al.
(2001) and the University of Washington (Geophysics Program) with a radio echo-sounding system.
Lirung’s thickness was measured 160 m below its thick supraglacial debris cover. The averaged
surface lowering rate in the ablation area of Lirung Glacier was about - 1 - 1.5 m/a 1996 to 1999.
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Kachenjunga Himal
The Ktr_gr 193 glacier in Nepal has been classified as largest glacier of Nepal in 2001. Nowadays
it broke into two pieces as a result of shrinkage and hence is not anymore the country’s largest glacier
(Bajracharja et al., 2011).
Khumbu Himal
The Kumbu glacier thickness was measured in the late 1990s through a research team of Ageta et
al. (2001) and the University of Washington (Geophysics Program) with a radio echo-sounding
system. They found Khumbu glacier’s ice depth is up to 450 m. Khumbu’s surface elevation was
measured in 1978, 1995 and 1999 finding a surface lowering rate of approximately 1m/a in the upper
ablation area between 1978 to 1995 and a doubled rate in the years 1995-1999 (Ageta et al., 2001).
Volume changes based on Corona (1962) and ASTER (2002) DTMs of Khumbu, Nuptse, Lhotse
Nup and Lhotse glaciers have been investigated. Down wasting has been observed for all glaciers,
with minimum lowering rates of -0.275 m/a for Lhotse Glacier, but the estimated error is hardly
smaller than the detected change. The down wasting is clearly pronounced in the middle part of the
glaciers, where the authors suppose the location of the transition zone between the active and inactive
glacier parts (Bolch et al., 2008).
Bolch et al. (2011) report sustained surface lowering in the period 1970 to 2003 for all observed 10
glaciers in the Khumbu Himal, derived from air and space borne imagery and digital terrain models.
Despite potential elevation errors in the compared DEMs, downwasting of debris covered glacier
tongues can be observed. This is due to the less inclined slopes of the tongues showing less elevation
errors. They state the maximum surface lowering rates in the middle of the ablation areas near the
transition zone between the active and the stagnant glacier parts of the debris-covered glacier tongues,
with one exception. Average surface lowering is -0.36 ± 0.07 m/a, considering only the debris covered
parts (~72% of the glacierized area) increases the rate to -0.39 ±0.07 m/a. The estimated overall ice
loss exceeds 0.6 km3.
Bhutan Himal
The velocities of glaciers of the Lulana region in northern Bhutan have been investigated using
ASTER and SRTM 3 DEMs and further satellite imagery (Kääb, 2005). According to the different
settings north and south of the main range, differing velocities have been estimated: On the northern
side, horizontal surface velocities of the glacier tongues of several tens of meters have been detected
for 2001 on the almost debris free glaciers. Maximum velocities of up to 220 m/a have been observed
on some steep glacier parts. On the southern side, where steeper valleys, south exposition and debris
cover are dominating, lower flow velocities at the glacier tongues near the error range (noise level) of
10-20 m/a have been observed. Figure 26 shows the respective flow profiles. A north-south gradient
in glacier length changes has been detected by Karma et al. (2003) for the same region, being
consistent with the above reported findings. Bhutan glaciers on the southern slopes of the main range
hence experience larger terminus retreat in combination with low ice velocities, while on the
continental northern slopes high velocities and less retreat is observed.
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Figure 26: Flow velocities of selected glaciers in the Bhutan Himalayas. Left side shows glaciers on
slopes north of the main ridge, right side profiles are of southwards glaciers.
The surface and terminus changes of the Jichu Dramo Glacier in Lunana, Northern Bhutan have
been estimated based on field surveys in 1998, 1999 and 2003. The debris free glacier measures ~3.2
km2 and showed average surface lowering of 2-3 m/a. The terminus retreated -11 m in the first year
and consequently slowed down to 7 m/a, resulting in average retreat of - 8 m/a for 1998-2003 (Naito
et al., 2006).
Debris Cover
A glacier´s ablation is strongly reduced by debris cover on its surface, if it exceeds a threshold
thickness of about 2 cm. For instance on Khumbu glacier, ablation increases when descending from
the ELA down-glacier, but then decreases depending on the varying supra-glacial debris thickness.
Thin debris cover (~<2 cm) can on the other hand strongly enhance the ablation process due to the
decreased surface albedo and subsequent enhanced energy absorption. On Khumbu, ablation is at a
maximum in the upper part of the ablation area, where thin and patchy debris cover is common (Benn
& Lehmkuhl, 2000). Debris covered glaciers are often characterized by down wasting processes,
rather than terminus retreat (Kargel et al. 2005).
Following the significant effect of debris cover on glacier’s ablation and consequently its mass
balance, clean ice glaciers and debris-covered glaciers must react with differing sensitivity to a
climate signal.
Across the HKH, especially glaciers in the Central Himalaya (Raina et al., 2008) south of the main
ridge are heavily debris covered. On the Tibetean Plateau north of the main ridge where less
pronounced topography is prevalent, rather clean-ice glaciers can be observed, as well as in the
Western Himalaya (Scherler et al., 2011). A southeast to northwest gradient in debris cover from the
Central to Western Himalaya has been identified by Frey et al. (submitted) with decreasing covered
glacier surface towards the northwest (22% to 6%).
In the Central Karakoram, a zone of enhanced melting through dust and thin debris cover is
located between 3500 and 4600 m a.s.l., whereas protection by debris cover occurs mainly below
3500 m (Hewitt, 2005). That ablation-reducing thick debris covers is generally situated at the lower
ends of Karakoram glaciers is also stated by Schmidt and Nuesser (2009). Thus it protects the lower
penetration of glaciers but greatly limits the usefulness of terminus fluctuations and down-wasting as
indicators of change in these areas.
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The Hindu Kush shows a relatively high concentration of debris-covered glaciers (Scherler et al.,
2011).
In Eastern Nepal, the inventory of Asai (2001) counts 1024 glacier, of which only 15% (153) are
debris covered. In a large investigation area in the Western and Central Himalaya (exact extent is
shown in Figure 11), 14.9% of the total glacier surface is debris covered. Here, altitudinal bands of
debris concentration on the glaciers have been observed. Between 3 500 and 4 100 m a.s.l 75% of the
glacier ice is debris covered (Frey et al., submitted). Schmidt and Nuesser (2009) estimate the fraction
of debris covered glaciers in the Himalayan range to over 42%, a rather high estimate.
Generally the northern slopes of the Himalayan range towards the Tibetean plateau show more
gently sloped glaciers, often large plateau like accumulation areas and valleys than on the south side.
Here where steeper vertical gradients can be found, narrow valleys and steep rock faces are more
common and deliver the material which accumulates as supraglacial debris (Scherler et al., 2011,
Kääb, 2005).
Remotely-sensed investigations on terminus positions and velocities between 2000 and 2008
across the Himalaya revealed that the most of the glaciers in the monsoon driven east are receding.
Debris-covered glaciers though show commonly stable fronts (Scherler et al., 2011, Bolch et al.,
2008).
From the Eastern Himalaya though, higher retreat rates and reduced flow velocities have been
reported from the glaciers on the southern slopes with higher debris cover (Kääb, 2005; Karma et al.,
2003). Here the climate or other signal is apparently stronger than the debris cover influence and
hence, debris cover cannot be assumed to prevent general melt. Also for heavily debris covered
tongue strong surface lowering rates have been reported for instance for Khumbu glacier (Bolch et al.,
2008) and glaciers in Himachal Pradesh (Berthier et al., 2007). Also strong retreat for large debris
covered glaciers as Gangotri (Kumar et al., 2008) and Samadratapu Glacier (Shukla et al., 2009) has
been stated.
Debris free glaciers are commonly smaller than debris covered glaciers in the HKH. The
GlobGlacier inventory (coverage Figure 4 and 11) shows that the largest debris free glacier in the
investigation area in the western and central Himalaya is 7.4 km2, while the 13 glaciers exceeding
50km2 are all debris covered.
Negative mass balance resulting of increased melt or decreased accumulation leads to higher
debris cover. This may be due to the melt out of intra-glacial debris or the diminished re-covering of
the supra-glacial debris with snow. Increase in debris cover on Himalayan glaciers in the last decades
has been reported by various authors (e.g. Bolch et al., 2008; Shukla et al., 2009; Bhrambi et al.,
2011). Although it is likely that melting leads to the appearance of intra-glacial debris at the glacier
surface, and hence increases the area covered with supra-glacial debris, this relationship needs further
investigations to be sustained and to derive consequences for future glacier shrinkage under increasing
debris cover.
Summarizing it can be stated that across the HKH, the Central Himalaya (south of the main ridge)
and the Hindu Kush build regional centers of debris cover (Scherler et al., 2011). North of the main
ridge the glaciers show lower fractions of debris cover than in the south due to the topography (Karma
et al., 2003, Scherler et al., 2011). Even if a thick debris cover protects from increased melting and
can alter a glacier’s mass balance significantly, it is not always the crucial process governing the
glacier’s response to a climate signal.
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4.1 Conclusions glacier changes
The glacier changes of the Hindu Kush Himalayan region need to be considered region wise, as no
general conclusion for the glaciers of this wide range can be drawn. This is on one hand the result of
differing change patterns but primarily due to the differing availability of studies conducted in these
mountain ranges. A scarcity of studies with sound and quantitatively comparable results has to be
stated for the Hindu Kush and the Karakoram and hence, general conclusions for the HKH region
would mean to interpolate glacier behavior over hundreds of kilometers of mountain ranges and
climates.
Himalaya
Within the Himalayan range the observed change pattern is clearly glacier shrinkage. The average
shrinking pattern includes very strong variability of glacier evolution within small areas as reported
by a majority of investigators. In the Western Himalaya, higher area shrinking rates go along with
more negative mass balances. Even if the detected rates are likely to be overestimated, and very few
studies exist, a higher glacier retreat for the Western Himalaya may be suggested.
Considering changes in volume, a concluding statement cannot be given due to the very limited
data availability and very high uncertainty.
The overall specific mass balance of glaciers in the Himalaya is clearly negative. More negative
balances are found the Western Himalaya, while the Khumbu region in the East show less negative
balances. The studies on which these conclusions are based though are very few and require the
maintenance and implementation of further mass balance series to enable sound and valid
conclusions.
Studies from the Bhutan (Kääb, 2005, Karma et al., 2003), and the Central Himalaya (Scherler et
al., 2011) show a north south pattern of glacier change. In Bhutan, the more maritime glaciers south of
the main range experience higher terminus retreat and reduced velocities, even though their debris
cover is higher. In the Central Himalaya though, south facing glaciers show lower terminus retreat
(Scherler et a., 2011) than their neighbors on the northern slopes on the main ridge, a fact that the
authors assign to the protecting debris cover on southern glaciers. Stagnant fronts in the south though
do not mean that glaciers are in equilibrium stage, as they are heavily debris covered and may shrink
via down wasting.
The area and volume change assessments provide the picture of an overall decrease consistent with
the overall negative mass balance data, but high inter annual variability needs to be stated. The
combination with the spatially strongly heterogeneous glacier evolution revealed by the area change
assessments results in a picture of glacier shrinkage in the Himalaya, build up by very differing single
glacier evolutions in space and time, where deviation from the average is the norm.
Karakoram
The Karakoram Range shows a similar ice coverage as the Himalayas, its glaciers though are
almost ignored in comparison to its neighbors. The one mass balance series for the largest glacier of
the HKH, the Siachen, is negative, but it only covers 5 years and ends in 1991. Quantitative area
change assessments as well as volume change estimates are absent and thus, only qualitative
conclusions can be made. For the last decade, glacier expansion has been reported from the highest
altitudes of the Central Karakoram Range after decades of decline. In the northern and western
regions of the Central range though, retreat is the dominating behavior.
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Hindu Kush
The few existing studies indicate a differing evolution of the glaciers in the Hindu Kush than in the
Himalayas. Taking supraglacial lake evolution as indicators for glacier wastage, recently receding
lakes in size and amount could suggest stabilization or even growth of certain glaciers in this range
(Gardelle et al., 2011). The investigated glacier length changes though do show average retreat of
glacier tongues, but the error margins are very high (Scherler et al., 2011).
General Conclusions
The newly compiled HKH inventory provides the best available estimate of the HKH glacier
distribution and area extent. As Table 16 indicates, the Karakoram and the Himalaya host similar
areas of glaciers, with a slightly smaller coverage in the Karakoram. The Hindu Kush shows a glacier
extent which is about one order of magnitude lower as compared to the other mountain ranges.
Table 16: Glacierized areas in the Hindu Kush - Himalayan region
Hindu Kush
Karakoram
Himalaya
Number of glaciers
Total area [km2]
2173
8901
23664
2969
22123
25233
The estimated volumes show a very high uncertainty and range from 842 to 1167 km3 for the
Himalayas, from 729 to 1235 km3 for the Karakoram and from 105 to 140 km3 for the Hindu Kush,
respectively.
The HKH region is characterized by a lack of reliable and quantitative studies on its glaciers, with
decreasing investigation coverage from the Eastern and Central Himalaya (relatively good coverage)
over Western Himalaya the Karakoram to the Hindu Kush (no quantitative assessments available).
Himachal Pradesh in the Western Himalaya builds a regional exception with a considerable number of
studies. Even if they could not be sufficiently assessed with this report, it should be mentioned that
north-south gradients in glacier change within the sub regions exist as some studies suggest for the
Central and Eastern Himalaya.
An important finding is that the spatial and temporal variability is very high in all regions and no
regions of homogeneous glacier change exist. Considering the large mountain ranges however, overall
regional differences can be observed. The almost complete lack of quantitative studies for the Hindu
Kush and the Karakoram though does inhibit any quantitative comparison.
The analysis of regional topographic parameters revealed some interesting findings: The Western
Himalaya shows particular glacier features in comparison to the other regions. Its glaciers are on
average a lot smaller than in other regions (and more numerous) and their mean elevation is rather
low. In addition their altitudinal range is very small in comparison to all other sub regions and here
the lowest values for the ratio of areas above and below the mean elevation (AAR proxy) can be
observed.
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For the Western Himalaya the glacier change assessment revealed more negative mass balances
than in the Central Himalaya (large glacier area mass balances), but uncertainties are very high. Also
higher area retreat rates have been reported, but this result is strongly biased as all results origin of
one single study (Kulkarni et al., 2007 and extension in 2011), as well reporting higher than other
rates for other regions, where further investigations exist (and generally lower rates dominate).
The small mean glacier size in combination with the high number of individual glaciers, the
smallest AAR proxy values of all regions and the more negative mass balances let suggest that a) the
number of glaciers has increased due to fragmentation leading to a smaller mean size and b) that
glaciers are shrinking at a higher pace than in the other Himalayan regions or Karakoram. The glaciers
in the Western Himalaya show low debris cover in comparison to its neighbors in the Central
Himalaya or Karakoram.
For glaciers in the Karakoram exceptional altitudinal ranges of over 5100 height meter have been
observed. The glaciers are very large and reach to relatively low elevations, where debris cover often
decreases ablation. For some glaciers in the highest parts of the Central Karakoram range, glacier
expansion has been reported but quantitative estimates are lacking and hence further investigation is
needed to assess the region’s dominant glacier change pattern. The same has to be stated for the
glaciers of the Hindu Kush.
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83
HighNoon
Project No 227087
Annex 1
An extensive and transparent review around the central question of the existing evidence on
changes in glacier melt in the Hindu Kush Himalayan region has been perfomed by Miller et al.
(2010). Secondary questions are, if glaciers are shrinking or growing in mass, if there are regional
differences and if the rate of glacial shrinkage is increasing across the region.
In order to answer these
questions,
Miller
et
al.
performed
a
systematic
research including data bases,
organizational
and
web
searches
and
expert
questionnaires and applied
exclusion and inclusion criteria
to their finds. They found 52
works which were included in
the review as full text
assessments and 143 at abstract
level after applying inclusion
and exclusion criteria to their
about 2000 search results. The
reviewers subjected the so
identified documents to an
expert ranking based on i) how
adequate and representative the
chosen
methodological
approach can determine glacier
change, and ii) how much
confidence is assigned to the
measurement depending on the
method and its reporting (e.g.
including a uncertainty analysis
or not) as strong differences
can exist even using the same
method to perform the same
measurement. The ranking
scheme is presented in Figure
A1. Studies which were not
ranked as at least moderate
quality with the presented
approach are not included in
this report.
Figure A1: Ranking scheme for quality assessment of the identified
investigations carried out in the HKH region
84

State of the glaciers in the Hindu Kush- Himalyan region

Transcription

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