TCDThe Cryosphere DiscussionsTCDThe Cryosphere Discuss.1994-0440Copernicus GmbHGöttingen, Germany10.5194/tcd-9-1555-2015Satellite monitoring of glaciers in the Karakoram from 1977 to 2013: an overall
almost stable population of dynamic glaciersBrahmbhattR. M.rupal.brahmbhatt@gmail.comBahugunaI. M.RathoreB. P.SinghS. K.RajawatA. S.ShahR. D.KargelJ. S.M.G. Science Institute, Ahmedabad, IndiaSpace Applications Centre, ISRO, Ahmedabad, IndiaDepartment of Hydrology & Water Resources, University of Arizona, Tucson, AZ, USAR. M. Brahmbhatt (rupal.brahmbhatt@gmail.com)10March201592155515924December20141February2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://tc.copernicus.org/preprints/9/1555/2015/tcd-9-1555-2015.htmlThe full text article is available as a PDF file from https://tc.copernicus.org/preprints/9/1555/2015/tcd-9-1555-2015.pdf
Six hundred and seven glaciers of the Shigar, Shashghan, Nubra and
part of Shyok sub-basins of the Karakoram region were monitored
using satellite data of years 1977, 1990, 2000, 2001, 2002, 2004,
2006, 2008, 2009, 2010, 2011 and 2013. Landsat MSS, TM, ETM+ and
IRS/Resourcesat-1 LISS III data were used. Glacier observations were
classified into 3 categories such as advance, retreat or stable with
reference to base data of 1977. Glaciers of the Karakoram have shown
inconsistency in advance, retreat and no change during this period,
and some examples of glacier surging have been caught in action.
Despite significant geographic and temporal variability betraying
the dynamic nature of many of the glaciers, in aggregate the
population is roughly stable with less propensity toward retreat
than most other glaciers in the nearby Himalaya and in the world.
341 glaciers exhibited no measured change throughout the
36 years of the study. Among other glaciers, no significant
and sustained pattern of retreat or advance was observed. The
overall changes in glacier area in the whole region are of small
magnitudes (positive and negative values) in the various measured
intervals. Moreover, it is mostly disconnected glaciers in
tributary valleys which have advanced, whereas the main former trunk
glaciers have primarily not changed. The dynamical differences
between disconnected former tributaries and trunks may be related to
response time differences, with the smaller, perhaps steeper
tributaries responding more rapidly than trunks to brief climatic
fluctuations. The advance/retreat fluctuations of many individual
glaciers suggest that their response times primarily may be of order
decades rather than some longer period, though some glaciers may
have longer response times that have limited their length and area
changes over the 36 year study period. The data from 2001 onwards
were also utilized for finding annual changes of glaciers. Among the
607 glaciers, 10 show considerable fluctuation in their area; in
several cases surge-waste cycles appear to be active. Glacier
thickness change measurements are needed to aid our understanding of
the regional glacier dynamics and relationships to climate change
and area-response dynamics.
Introduction
In most satellite-based and in situ studies of glaciers in the
Himalaya and most other parts of High Asia, it is reported that there
is a general glacier recession or thinning and mass loss (Berthier
et al., 2007; Kulkarni et al., 2007, 2014; Dobhal et al., 2008; Velicogna
et al., 2009; Cazenave and Chen, 2010; Matsuo and Heki, 2010; Bhambri
et al., 2011, 2012; Bolch, et. al., 2011, 2012; Fujita and Nuimura, 2011; Kargel
et al., 2011; Scherler et al., 2011; Brahmbhatt et al., 2012; Jacob et al., 2012; Schmidt and
Nusser, 2012; Venkatesh et al., 2012; Yuning and Freymueller, 2012;
Gardelle et al., 2013; Kulkarni and Karyakarte, 2014; Racoviteanu et al.,
2014a, b; Bahuguna et al., 2014). The assessed rates of retreat or
mass loss differ greatly between glaciers and among sub regions. It is
generally now agreed, contrary to widespread older speculations that
Hindu-Kush/Karakoram/Himalaya (HKH) glaciers were losing mass
unusually rapidly, that the rates of thinning and mass loss in the HKH
are typical of the rates around the world (Cogley et al., 2010), and
that some parts of this region, particularly the Karakoram, have
complex patterns of retreating/thinning, stable, and even growing
glaciers (Hewitt, 2005; Kargel et al., 2005; Bolch et al., 2012;
Gardelle et al., 2012, 2013; Kääb et al., 2012; Bhambri et al., 2013; Racoviteanu et al., 2014a, b). Our
present work reinforces this more nuanced emergent understanding of
glacier change in the HKH and adds news details on the temporal
evolution of the region's glaciers derived from a new methodological
approach to the matter.
Recently, the mass balance was determined gravimetrically for the last
decade for the various climatic zones of High Asia, which shows that
loss of mass was higher in western Himalaya in comparison to the
eastern and central Himalaya (Gardelle et al., 2013). Moreover,
glacier ice loss was estimated as a maximum in Jammu-Kashmir region
for the 21st century (Kaab et al., 2012). In addition, the Ganges,
Indus and Brahmaputra basins, the glacier contribution was estimated
to make up about 10 % of the current glacier contribution to
sea-level rise (Kaab et al., 2014). Contrary to the general world and
Himalayan trend of deglaciation, several studies of glaciers of the
Karakoram have shown the advances or surges of snouts. This was first
brought into notice by Hewitt, in his article “The Karakoram
anomaly” (Hewitt, 2005). Supporting this concept, slight mass gain
has occurred in the Karakoram in the 21st century, and this has been
attributed to glacier growth (Gardelle et al., 2012). Mayer has
carried out detailed field studies of the ablation zone of Baltoro
glacier in 2004 (Mayer et al., 2006). In addition, he has reported
a surge-like event of North Gasherbrum Glacier on the northeastern
slope of the Karakoram Mountains between 2003 and 2007 based on
Landsat ETM+ images from 2000 to 2009 (Mayer et al., 2011). Copland
determined surface velocities of major glaciers across the central
Karakoram using optical matching of ASTER (Advanced Spaceborne Thermal
Emission and Reflection Radiometer) image pairs (Copland et al.,
2011). Moreover, Minora measured area change of more than 700
glaciers for the period of 2001–2010 in the Central Karakoram
National Park (Minora et al., 2013). The inventory of glaciers and
velocity were measured using multi-mission satellite images. The
change in glaciers was estimated using two time frames (1976–2012),
in which they have shown that 80 % of glaciers have remained
stable during this monitoring period (Rankl et al., 2014). The
composite of studies has now made a complete inventory of glaciers
from the entire HKH, and these data are now in the GLIMS (Global Land
Ice Measurements from Space) glacier database. Taking cue from this
progress, we have determined the changes in Karakoram glaciers using
multi-temporal images acquired from 1977 to 2013. The analyzed
intervals are 1977 to 1990, 1990 to 2001, 2001 to 2010, and 2010 to
2013. Considering the seeming contradictory or ambiguous (or at least
confusing) collection of results obtained for Karakoram glaciers by
many previous studies (reviewed by Kääb et al., 2014), this
new temporal resolution of glacier changes is very needed. Image
resolution relative to changes remains a serious limitation for this
type of study, especially for the earlier periods, but we have done
the best we could with the available imagery.
Data and methodology
Multi-year Landsat MSS (Multispectral Scanner), Landsat TM (Thematic
Mapper)/ETM+ (Enhanced Thematic Mapper), and LISS III (Linear
Imaging Self-Scanner) images have been used for this study. The MSS
data have 68m×83m spatial resolution and
four spectral bands: Green (0.5–0.6 µm), Red
(0.6–0.7 µm), Near Infrared (0.7–0.8 µm),
and Near Infrared (0.8–1.1 µm). The dates of the various
satellite images have been given in Table 1. The Landsat data of the
TM sensor have seven bands, each with a spatial resolution of
30 m, except thermal infrared, which is 120 m. Landsat
ETM+ has 30 m spatial resolution, except the panchromatic
band with 15 m and thermal infrared band with 60 m
resolution. IRS LISS III images have four spectral bands: band 1
(0.52–0.59 µm), band 2 (0.62–0.68 µm), and
band 3 (0.77–0.86 µm) at 23.5 m resolution and
band 4 (1.55–1.70 µm) at 56 m (only for 2001)
resolution. The images were chosen to minimize snow and cloud cover
during the glaciers' ablation period. The false-color composites of
bands in VNIR of LISS-III data were georeferenced with the
corresponding ortho-rectified Landsat data. While executing
georeferencing, we applied the same datum and projection to the
images. The ERDAS IMAGINE version 9.1was used for the pre-processing
of digital images. Then vector layers of glacier extents were prepared
by on-screen digitization. The change detection of extents was carried
out using these vector layers.
Purely automated mapping is not yet technically feasible due to
obscuring effects of partial debris cover. Mapping from images
requires use of elements of visual interpretation, such as the unique
reflectance of snow and ice, the shape of the valley occupied by the
glacier (particularly changes in slope at the glacier edges), the flow
lines of ice movement inferred from medial moraines in single scenes
or feature displacement in multi-temporal images, the rough texture of
debris-covered parts of the ablation zone, and the presence of
vegetation on non-glacier areas. The SWIR band is also used to
discriminate snow and clouds. The advance, retreat, or stability of
the snout of a glacier is the most important feature for monitoring of
glaciers. However, the snouts of many glaciers are not distinct due to
debris cover and degradation of the tongue. In such cases various
other indicators helped in identification, such as location of the
origin of a stream from the glacier's terminus or presence of distinct
geomorphic features in the form of braided streams, lakes,
glacio-fluvio sands etc. In the periglacial area around snouts,
changes of slope or elevation near the snout may be discerned using
DEMs from SRTM. For detection of changes in area of glaciers, only the
change around the snout area (within the ablation zones) were
considered as the accumulation zone is very dynamic in terms of snow
cover, and net change in the glacier area is reflected most clearly
near the snout. Care was taken to see that changes in the extent do
not cross over former lateral moraines.
Estimation of uncertainties
Raup et al. (2014) conducted a set of Glacier Comparison Experiments
(GLACE) to assess the full combined set of errors when different
people map the same glaciers using either different or the same types
of remote sensing data. The uncertainties – assessed by divergence of
mapping results – were surprisingly large due mainly to human
subjective errors along debris-covered parts of glacier margins.
We have minimized errors by making use of a consistent measurement
approach applied to similar types of multispectral image data by
a single analyst (the first author). It is important to make very
clear our methodology. We computed uncertainties of glacier areas and
glacier area changes from the random error formulations adapted from
the treatment given by Krumwiede et al. (2014). It is important to
distinguish the problem of uncertainty of area change limited by
measurement precision of the snout area made by a consistent
methodology and a single analyst (which is what pertains here to
assessed changes) vs. the accuracy of total glacier area
measurements made by different methodologies and using different
analysts (which is mainly what the GLACE experiments investigated). It
is thus a problem similar to that of high-precision measurements used
to detect changes in quantities whose total magnitudes are
less reliably known to such high precision, for example, in mass
spectrometry, stellar luminosity measurements, or employment
statistics. Detection of extra solar planets and radiometric dating of
rocks would not have been possible without recognition of this
distinction between precision and accuracy; nor would the area changes
of Karakoram glaciers be measureable without this single-analyst
approach. The reproducibility of area-change results by another
analyst should, however, be possible, though the total glacier areas
measured by the two analysts would presumably be different, as the
GLACE experiments would indicate.
Clearly precision of change as defined here can be much
better than absolute accuracy of the whole. Furthermore, in
reference to glaciers, precision of glacier area-change measurements
made using a uniform approach can be much better than area-change
measurements assessed by using two independent measurements using
different methodologies, for example from two independent inventories
made from totally different data types, different approaches, and
different analysts. It should be clear that our fundamental
measurements were not of total glacier area, but of changed snout
area. This distinction explains the differences between the total
glacier area measurement uncertainties and the changed area
measurements reported below.
We have followed Krumwiede et al. (2014) and adapted their approach to
our analysis of the different uncertainties of measured snout area and
changes in area. The digitized glacier boundaries may be
systematically too wide or too narrow, thus the systematic error of
glacier area, Aer, may be assessed as a percentage of
digitized glacier area, Agl, as:
Aer=±100%⋅(fs⋅n⋅m)/Agl
where, Aer= error of glacier area, Agl is
digitized glacier area, n is the number of pixels defining the
perimeter of the glacier, m= spatial resolution of the image
expressed as area of a pixel (e.g., 900 m2 for
a 30m×30m TM image), fs is the
systematic fractional pixel error (e.g. fs=0.5 for half
a pixel error).
Glacier area change over a number of years may be computed from
digitizations of the same glacier in two images acquired in different
years. If the same human operator or same machine algorithm was used
and the datasets are similar, the systematic errors may be similar in
the two images, so random errors may dominate instead, and then the
error in the snout's area change computation, Ach, er is
calculated as:
Ach, er=±100%⋅(2/j)1/2⋅(fr⋅np⋅m)/Agl,
where j= the number of manual vertices of the vectorized polygon,
np is the modified perimeter of the snout area, and
fr now is the random pixel error, perhaps still around
0.5. Hence, the random error is far less than the possible systematic
error, meaning that we may know the area change much better than we
know the total area, as mentioned. This is a key in our measurement
and analysis approach and relies on an assumption that glacier area
change is concentrated mainly near the snout.
Findings
The results presented here account for 607 glaciers belonging to
Shashghan, Shigar, Nubra and part of Shyok sub-basins of Karakoram
region (Fig. 1). Summarized statistics of the study are shown in
Table 2. Uncertainties were calculated according to Eq. (1) (total
area) and Eq. (2) (change in area), as detailed in the Supplement.
Area-change results are summarized here.
1977–1990: the total area of glaciers was mapped as
7895 km2 (±8 %) in 1977 which reduced
insignificantly to 7885 km2 (±3 %) by 1990
(nominally -10 km2, i.e., within uncertainty of no change
or allowing either shrinkage or growth by 860 km2, i.e.,
roughly 11 % shrinkage to 11 % growth). However, taking the
approach described above where we assess the precision of
measurements for advancing glaciers and retreating glaciers (taken
separately), the total areas (and uncertainties) of deglaciation and
advancement of these classes of glaciers were 13.6 km2
(±6 %) and 3.6 km2 (± 10 %),
respectively. See the Supplement for further details on the calculations.
1990–2000: the total mapped area of glaciers had shrunk a little more
and became 7882 km2 (±3 %) up to year 2000
(nominally -3 km2). The total loss in area of retreating
glaciers was 23 km2 (± 1.5 %), whereas the
increased area of advancing glaciers was 20.2 km2
(±1.8 %) for the monitoring period of 1990–2000.
2000–2010: glacier area has increased to 7885.8 km2
(±3 %) and 7888.6 km2 (±3 %) by 2010 and
2013 respectively. In the period of 2000–2010, the total areas of
deglaciation and advancement nominally were 7.04 km2
(±2.8 %) and 10.6 km2 (± 2.1 %),
respectively.
2010–2013: surprisingly, some glaciers also have shown significant
change within a short span of three years (2010–2013): nominally
2.7 km2 (±4 %) and 5.5 km2 (±3.6 %)
of glacial loss and advancement, respectively.
The overall observations indicate that the trends are not of
continuous increase or decrease, and that for each period the net
change in total glacier area was always of small magnitude, even
though some individual glaciers had much larger percentage area
changes than the net percentage change of all glaciers combined. The
total change in glacier area was due to retreating glaciers during two
initial decades, whereas in the later period advancing glaciers caused
an increase in total area (Fig. 2). This change in total glacier area
was estimated for four time intervals as -9.9 km2
(1977–1990), -2.8 km2 (1990–2000), 3.6 km2
(2000–2010) and 2.8 km2 (2010–2013).
Discounting the 1977 measurement, which has a large uncertainty, the
measured net area change from 1990 to 2013 of all glaciers combined is
just about +4 km2, i.e., not much different from no
change at all. Hence, there could have been growth or shrinkage
amounting to an annual average rate of anywhere from
±0.0019 %year-1 for the 23 year span between these
measurements. During the briefer periods within this span there was
likewise no significant measureable change in total area. It does not
mean that in aggregate the glaciers were completely stable, but the
measurements rule out very large changes comparable to the percentage
area changes found in many other parts of the Himalaya and around the
world (Racoviteanu et al., 2014b; Kargel et al., 2014). Furthermore,
lack of measureable significant changes in the aggregate area is not
to say that there were no measureable changes amongst individual
glaciers, as we have documented many advancing and many shrinking
glaciers, as well as a larger number of stable glaciers.
These non-uniform changes during 1977 to 1990 were taken as the basis
for classifying them into three categories, i.e., advance, retreat and
no change (stable) on the basis of change in area in snout area
(within the ablation zone). Figures 3–5 show histograms of
change in glacier area for three categories during 1977–2013. Among
607 glaciers, only 23 glaciers experienced significant measureable
advance during the monitoring period of 1977–1990 (Fig. 6). The total
area of these glaciers was 402.5 km2 in 1977 and had shown
increase of about 4 km2 in 1990. After 1990, these have
remained nearly stable up to 2010. In 2013 there was a slight gain in
total area of the advancing glaciers up to
407.5 km2. However, 3 glaciers have continuously advanced
up to year 2010 and then became stable in 2013. Seventy nine glaciers
were observed retreating during 1977–1990 (Fig. 2). The total area of
these glaciers was 2356.3 km2 in 1977, which showed
a reduction of approximately 14 km2 up to 1990. These
shrinking glaciers have shown gradual increase from 1990 to
2013. Moreover, six glaciers out of 79 have experienced continuous
retreat up to 2010 and then have become stable.
505 glaciers experienced no measurable change during the period of
1977–1990 (Fig. 6). The total area covered by the 505 glaciers was
5136.2 km2 in 1977. During the period of 1990 to 2000, the
total area of glaciated region decreased to
5126.8 km2. Then it again increased up to year 2010 with an
area of 5129 km2 and became stable by 2013. 341 glaciers
(out of 505 glaciers) have continuously remained stable up to 2013
whereas remaining glaciers have not shown any significant or
continuous pattern of retreat, advance or stability.
These results prove that more glaciers (83 glaciers) have advanced
substantially in the earlier decade (1990–2000) than in 21st century
(41 glaciers). Similarly, the change in glacier area in context of
gain or loss or stability also shows the same results, although the
total change in area is very small. Interpreting the total results it
is observed that the largest fraction of glaciers have remained stable
since 1977, which is almost 44 % of total glaciers. The rest of
the glaciers have not shown continuous pattern of retreat or advance
since 1977. However, the aggregate glacier area, as mentioned before,
has not changed dramatically, because stable glaciers dominate in each
period and those glaciers that were advancing or retreating have
partly balanced each other, and these dynamic glaciers have tended to
fluctuate between advance, retreat, and stable conditions at various
intervals.
We have tried to show spatial distribution of advance retreat and
stability of glaciers. Spatial distribution of advance, retreat and no
change in the period of 1977–1990, 1990–2000 and 2000–2013 time
intervals in the study area has been shown in Figs. 7–9
respectively. For detailed information about spatial distribution of
advance, retreat and no change glaciers, the data have been displayed
at smaller scale (basin by basin) in Figs. 10–12. Basically,
Shashghan, Shigar, Nubra and part of Shyok basins have been isolated
for further study. Thus, the detailed distribution of change in
glaciers area of Shashghan basin has been represented in Fig. 10, for
Shigar it is in Fig. 11, and Nubra-Shyok basin is represented in
Fig. 12.
The spatial distribution of advance, retreat and stability of all
glaciers of the study area during three time intervals (1977–1990,
1990–2001, 2001–2013) is shown in Fig. 13. Each glacier is
identified with advance or retreat or no change in three time
intervals. Glaciers located at north-western and southeastern parts of
the study area show tremendous variation in the glaciation and
deglaciation for three time frames. Glaciers behaved very differently
in each time frame, thus, no significant generalized trend was
identified in changes of glaciers. In a few cases, glaciers have
experienced advancement and overrode on other glacier and then
gradually merged to form a main trunk glacier at a later stage
(Fig. 14). In other cases, glaciers were advancing slowly and then
stabilized (Fig. 15). In a few cases, the tributary glaciers advanced
and merged into main trunk glaciers, whereas the snout of main trunk
glacier did not show any considerable change (Fig. 16). The glaciers
were monitored annually for the period of 2001–2013 depending on the
availability of suitable data. Out of many glaciers, ten glaciers were
observed with extraordinary variations for 13 years. This
observation is significant in terms of identifying glaciers
characterized by a “surge-waste cycle” because of the abrupt
advances. Moreover, there are many glaciers showing rapid retreat as
well. The high level of variation was identified in these ten glaciers
(Fig. 17), e.g. glaciers which have remained stable for
8 years then experienced advancement of 0.4 km2
then again retreat and then again advancement of 0.8 km2.
Discussion
From the results presented above it emerges that we can classify
glaciers in two categories from these set of data: “normal” glaciers
and “surge-type” glaciers, as many other regions of temperate
glaciers in other parts of the world have. A third category of
glaciers undergoing speedy calving-induced retreat – common in the
central and eastern Himalaya – is not a major presence in the
Karakoram where there are few large lakes.
“Normal” glaciers show a normal (modest) advance or retreat or
stability in area, with advances or retreats commonly measured in
single digits of meters per year. These glaciers may be stable in mass
balance and maintain a constant condition of internal deformation and
basal sliding and thus maintain length and area; more commonly, small
variations in long-term mass balance, or changes in glacier dynamics
related to basal sliding or small rock falls onto the glacier may
result in small advances and retreats, with the average condition
commonly approaching stability. Other normal glaciers may have low
rates of sustained retreat or advance if they have sustained negative
or positive mass balance, but if local microclimate conditions or
other forcing such as from rockfalls or supraglacial landslides giving
rise to these negative or positive balances are themselves balanced
(no regional climate trend), then these imbalanced “normal” glaciers
may have their net area changes come close to a regional balanced
state.
In regions where mass balance has shifted to be negative, the
aggregate of glaciers may show a mean slow shrinkage, with individual
glaciers showing variable responses but more showing slow retreat than
slow growth. Or if regional mass balance shifts to positive, more
glaciers may show slow growth than slow retreat, but there will be
a distribution.
In the second category are those glaciers showing abnormal advance or
retreat of snouts. Anomalous advances (surges) are commonly identified
due to the presence of features such as looped medial moraines,
intense folding visible at the surface, rapid terminus advance, heavy
surface crevassing, and high surface velocities. Sharply increased
mass balance and episodes of accelerated basal sliding commonly due to
large amounts of melt water penetrating to the bed may be primary
causes of surging. Commonly, a glacier that has undergone a surge
episode will then stabilize briefly and then retreat rapidly over
a longer period of time than the surge phase. However, surge and waste
phases of a surge-type glacier are not symmetric in duration or rates
of advance and recession (advance phases being briefer and faster than
retreat phases of the cycle). For the surge-type subpopulation of
glaciers there will be an imbalance of fewer advancing glaciers
relative to more retreating glaciers (since the waste phase lasts
longer than the surge phase). To further complicate the dynamical
picture, surge glaciers that are at an early phase of wastage may thin
but not exhibit significant area shrinkage or terminus retreat; thus,
some fraction of surge-type glaciers may appear for a time to be
stable based on length and area measurements.
Individual glaciers will vary through time between advancing and
retreating, with their dynamics controlled both by slight oscillations
in climate and by intrinsic dynamics that cause length and area
oscillations even absent any climate forcing. Regardless of the
fraction of surge-type glaciers, the aggregate area of glaciers may
remain almost the same if there exists an overall stable state of the
population, despite the fact that a large proportion of glaciers are
in continual dynamic oscillation. Short-term departures from
a balanced state may appear if one or two very large glaciers suddenly
surge, but the bigger picture will show balance.
To a first order, this hypothetical situation seems to describe the
Karakoram glacier record. The Karakoram exhibits a roughly stable
population of dynamic glaciers, according to our analysis of glacier
area changes. An overall rough approach toward long-term stability of
the whole glacier population in the broader region we surveyed is in
sharp distinction with some other areas of the nearby Himalaya and
most parts of the glacierized world. Thus, we have added many new
details, particularly in the temporal domain, to the concept of the
Karakoram Anomaly first identified by Hewitt (2005).
An inventory carried out by Bhambri et al. (2013) in Shyok Valley is
significant in terms of dynamics of glaciers since 1973; a small
fraction of glaciers were identified as surging in the Upper Shyok
Valley, supporting our finding as well.
Do our new results imply that the climate in the Karakoram is in
a long-term stable condition? Not necessarily. If increases in snow
precipitation take place with an increase in temperature, there are
some situations that may cause a nearly balanced state of the
population of glaciers. Hence, a stable population of glaciers may
signify either long-term unchanging climate, or it may signify that
various dynamic climatic parameters are balancing each
other. Measurements of ice throughout (changes of which may be
indicated by surface velocity flow fields, or by direct field
measurements of seasonal accumulation and ablation) would discriminate
which of these climate scenarios applies.
Conclusion
The glaciers in our study area of the Karakoram include many advancing
glaciers and many retreating ones, but most of the glaciers have
remained nearly stable over several decades. A couple percent of the
glaciers are surge types. There have been temporal changes in
aggregate glacier behavior. Before 1990 the glaciers on average were
either stable or retreating. In the last two decades Karakoram
glaciers, on average, have experienced noticeable advances of their
snouts and areas. The aggregate changes, however, are small for every
period considered. There is a significant finding that it is mainly
tributary glaciers which show advancement or retreat; there are
exceptions of main trunk glaciers showing retreat or advance. It is
emphasized in this article that it is not only abnormal advancement
but sometimes abnormal retreat that is also observed. Although the
population of glaciers is dynamic in time and geographically, we find
that largely the population is almost stable but includes dynamics
disturbances due to surge-waste cycles of a minority of the glaciers
and smaller fluctuations of many other glaciers.
The Supplement related to this article is available online at doi:10.5194/tcd-9-1555-2015-supplement.
Acknowledgements
We sincerely acknowledge and express our gratitude to Shri
A. S. Kiran Kumar, Director, Space Applications Centre, ISRO,
Ahmedabad for giving opportunity and encouragement for carrying out
this activity. We sincerely express our thanks to P. K. Pal, Deputy
Director, Earth, Ocean Atmosphere, Planetary Sciences and
Applications Area, Space Applications Centre, ISRO, Ahmedabad for
collaborative project to our institution. We also thank USGS for
providing Landsat TM/ETM+ data at no cost. We are grateful to
Andreas Kaab for insightful comments and suggestions which
significantly improved this paper. This work has benefited greatly
from the discussions with lab mates Sandhya Rani Patnaik (JRF at
Space Applications Centre, ISRO) and Purnesh Jani (JRF at CEPT
University, Ahmedabad). One Author (Rupal) of M.G. Science Institute
is grateful to its Principal, B. K. Jain for providing all support
to carry out the project. We also thank the NASA/ISRO PESEP program
for funding collaborative travel by J. S. Kargel.
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The list of datasets.
YearTypeDate1977/78/79MSS9 Mar 1977 18 Jul 1978 2 Aug 19771989/90Landsat TM(147/36, 148/35) 9 Oct 1989 (148/35, 148/36) 29 Jun 19902000/01Landsat TM(147/36) 31 Oct 2000 (148/35) 18 May 2001 (148/36) 16 Jul 1999LISS III(94/45) 22 Jul 2001 (94/46) 26 Oct 20012000–2009Landsat ETM+(148/35) 14 Aug 2004; 7 Dec 2005; 7 Dec 2006; 8 Nov 2006; 23 Aug 2007; 12 Aug 2009; 31 Aug 2010; 27 Jul 2009; 21 May 2008; 26 Sep 2009; 26 Sep 2008 (147/36) 2 Aug 2002; 26 Jun 2006; 26 Aug 2005; 30 Sep 2006; 13 Jun 2007; 16 Aug 2007; 2 Aug 2008; 3 Sep 2008; 6 Sep 2009 (148/36) 2 Sep 2005; 23 Aug 2007; 12 Aug 2008; 28 Aug 2009; 12 Oct 2008; 29 Sep 20092010/11 Landsat ETM+(148/35) 5 Nov 2011 (147/36) 12 Sep 2011(94/45) 3 Oct 2010 (94/46) 3 Oct 20102013(147/36) 12 Feb 2013 (147/36) 25 Sep 2013 (147/36) 24 Aug 2013 (148/35) 3 Feb 2013
Overview results of glacier change for
607 glaciers.
YearTotal GlacierArea (km2)PeriodChange in totalglacier area (km2)Change of area ofadvancing glacier (km2)Change of area ofretreating glaciers (km2)19777895 (+8 %)––––19907885 (+3 %)1977–1990(-)10 (+8 %)3.62 (+10 %)13.6 (+6 %)20007882 (+3 %)1990–2000(-)3 (+1.7 %)20.2 (+1.8 %)23 (+1.5 %)20107885.8 (+3 %)2000–2010(+)4 (+2.5 %)10.6 (+2.1)7.04 (+2.8 %)20137888.6 (+3 %)2010–2013(+)3 (+3.8 %)5.5 (+3.6)2.7 (+4 %)
Locations of glaciers monitored in Karakoram region shown in
satellite data. (AWiFS image of year 2014 showing FCC of
SWIR-NIR-Red.)
Change in total area of glaciers from 1977 to 2013.
Change in total area of advanced (advancement for the period of 1977–1990) glaciers from 1977 to 2013.
Change in total area of retreated (retreat for the period of 1977–1990) glaciers from 1977 to 2013.
Change in total area of stable (no change for the period of 1977–1990) glaciers from 1977 to 2013.
Chart showing the statistics of stable advancing and
retreating glaciers from 1977–2013.
Image showing the glaciers which have experienced the
retreat, advance and no change for the period of 1977 to 1990.
Image showing the glaciers which have experienced the
retreat, advance and no change for the period of 1990 to 2000.
Image showing the glaciers which have experienced the
retreat, advance and no change for the period of 2000 to 2013.
Image showing the overview change of glaciers in Shashghan
sub-basin of Karakoram since 1977 to 2013. Note: R = Retreat,
A = Advance and S = Stable. R-A-S = Retreat (in
1977–1990) – Advance (in
1990–2000) – Stable (in
2000–2013).
Image showing the overview change of glaciers in Shigar
sub-basin of Karakoram since 1977 to 2013. Note: R = Retreat,
A = Advance and S = Stable. R-A-S = Retreat (in
1977–1990) – Advance (in 1990–2000) – Stable (in 2000–2013).
Image showing the overview change of glaciers in Nubra-Shyok
sub-basin of Karakoram since 1977 to 2013. Note: R = Retreat,
A = Advance and S = Stable. R-A-S = Retreat (in
1977–1990) – Advance (in 1990–2000) – Stable (in 2000–2013).
Spatial distribution of change in area of glaciers of
Karakoram since 1977. Note: R = Retreat, A = Advance and
S = Stable. E.g.: R-A-S = Retreat (in 1977–1990) –
Advance (in 1990–2000) – Stable (in 2000–2013).
Landsat images of TM (1990), ETM (2001), ETM+ (2004)
showing overriding and advancement of tributaries on main glacier
(Panmah Glacier) (FCC in SWIR-NIR-Red).
Landsat Images of MSS (1978), TM (1989), ETM (2001), ETM+
(2010) showing overriding and advancement of tributary glaciers
(Chong Kumdan) (FCC in SWIR-NIR-Red).
Images showing advancing of tributary glaciers upto bank of
main trunk (Baltoro) glaciers.
Graphs showing annual changes in area of individual glaciers
from 2001 to 2013 (Central Lat/Long of individual glacier is
given). The abrupt change in glacier area can be attributed to
surging of glaciers in a specific period.