Annals of Glaciology 54(64) 2013 doi:10.3189/2013AoG64A111

157

Changes in ice thickness and flow velocity of Yala Glacier,Langtang Himal, Nepal, from 1982 to 2009
Shin SUGIYAMA,1 Kotaro FUKUI,2 Koji FUJITA,3 Kenta TONE,1,4 Satoru YAMAGUCHI5
1

Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
E-mail: sugishin@lowtem.hokudai.ac.jp
2
Tateyama Caldera Sabo Museum, Tateyama-cho, Toyama, Japan
3
Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
4
Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan
5
Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Prevention, Nagaoka, Japan
ABSTRACT. To investigate recent glacier changes in the Himalayan region, we carried out GPS andground-penetrating radar (GPR) measurements at Yala Glacier, a benchmark glacier in Nepal. Glaciersurface elevation and ice thickness were surveyed along a 1.5 km profile from the glacier top to theterminus. Ice flow velocity was measured at five locations by surveying stakes for either 1 year or 4 day
periods. Obtained surface elevation and ice velocity were compared with those measured in 1982 and1996. The mean ice thickness along the radar profile was 36 m in 2009 and the ice has been thinning at
rates of –0.69  0.25 and –0.75  0.24 m a–1 during the periods 1982–96 and 1996–2009, respectively.
The thinning rate increases down-glacier, reaching a magnitude up to –1.8 m a–1 near the terminus from1996 to 2009. The ice velocity has reduced by >70% from 1982 to 2009 in the lower half of the glacier.
By assuming a constant driving stress over the glacier, the total ice volume in 2009 was estimated as
0.061 km3. Our results indicate that Yala Glacier has lost 40% of its ice volume over the last 27 years
and that the rate of the mass loss has accelerated over the last decade.

INTRODUCTION
Lack of information regarding mass change in Himalayan
glaciers is one of the main causes of uncertainties in thecontribution of mountain glaciers to current and future sealevel rise. Ice mass loss in this region over past decades wasestimated by several studies on the basis of satellite and fielddata with the aid of mass-balance modelling (e.g. Dyurgerov,
2010; Radić and Hock, 2011), as well as satellite gravimetricmeasurements (Matsuo and Heki, 2010; Jacob and others,2012). However, these studies yielded significantly different
estimates with relatively large uncertainties. The primaryreason for the discrepancy and ambiguity is insufficient field
data, which hampers the understanding of processes
controlling glacier changes in the Himalaya. In situ data
are important for this region because of the uniqueness anddiversity of geographical conditions (e.g. monsoon climate,summer accumulation, high elevation and debris-covered
surface). Nevertheless, field observations of the Himalayan
glaciers are sparse in space and time.
The Nepal Himalaya form the central part of the Himalayan mountain system. High mountains with deeply incisedterrain accommodate a large number of glaciers, which arefrequently covered by debris. The glacier mass balance isdominated by Indian monsoon, and thus summer accumulation regime is a characteristic feature in this region (Ageta
and Higuchi, 1984; Fujita, 2008). Glacier changes are ofparticular importance for Nepal, not merely because glacierrunoff is an essential water resource in mountain areas, butalso because it influences the discharge in lowland rivers.
Studies based on satellite imagery showed that the glaciers
have been retreating and losing mass since the 1970s (Bolch
and others, 2011; Scherler and others, 2011; Nuimura andothers, 2012), but accurate estimation of glacier volume
change is still difficult because satellite-derived surface
elevation is often insufficiently accurate. Detailed analysisof the mechanisms that control changes in glaciers is alsodifficult because essential information (e.g. ice velocity, ice
thickness and mass balance) is usually unavailable.
In the Nepal Himalaya, reliable long-term ground-based
data are available from only a limited number of glaciers.
Yala Glacier has been the focus of several studies since the1980s (e.g. Ageta and others, 1984; Higuchi, 1984) and thus
is regarded as a benchmark glacier in the region. Together
with data from two other glaciers in Nepal, surface elevation
data from Yala Glacier were used to compute mass-balancevariations over the three decades since the 1970s (Fujita andNuimura, 2011). The results showed spatially non-uniform
distributions of mass balance over the Nepal Himalaya, andthe data from Yala Glacier represented the changes in theglaciers in a relatively humid environment at lower altitudes.
The aim of this paper is to report the observational data fromthe 2009 field campaign on Yala Glacier. We present theresults of a ground-penetrating radar (GPR) ice thickness
survey performed for the first time on this glacier. The GPR
data were used to estimate the total ice volume of the glacierby several methods. We also compared surface elevationand ice velocity with those measured in previous campaigns
to discuss their changes since 1982. Surface elevation
change over Yala Glacier was presented by Fujita andNuimura (2011), but we focus the study on our GPR survey
route to investigate the details of ice thickness change and its
influence on the ice dynamics.

METHOD
Study site
Yala Glacier is located in the Langtang valley in northcentral Nepal (Fig. 1). The glacier covers a southwest-facing
slope over an area of 1.82 km2 in 2006 and an elevation
range of 5000–5600 m a.s.l. It is one of the most frequently

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Sugiyama and others: Ice thickness and flow velocity of Yala GlacierFig. 2. Maps showing the GPR and GPS survey route in 2009 (boldblack curve): (a) surface elevation survey sites in 1996 (open circles)
and 1981 and 1982 borehole sites (crosses); (b) ice flow vectors in2009 (bold black arrows), 1996 (thin black arrows) and 1982 (boldgrey arrows). Ice surface elevation and thickness were interpolated
along the thin black curve to present the data in Figures 4 and 5.
Contours show surface elevation at intervals of 50 m. The velocitiesin (b) were measured at the origins of the vectors. The coordinates
are in Universal Transverse Mercator (UTM) zone 45N.

Fig. 1. (a) Map of Nepal showing the location of the study site. (b) A
satellite image of Yala Glacier taken on 3 January 2006 (datasource: Google Earth). The bold curve on the glacier indicates the
GPR and GPS survey route, and the triangle shows the location of
the GPS reference station. Contours show surface elevation withintervals of 50 m.

studied glaciers in the Himalaya. The research conductedhere includes an ice-core drilling project undertaken in
1981 and 1982 (Watanabe and others, 1984) and massbalance, ice flow and climatic observations in the 1980s and1990s (Steinegger and others, 1993; Nakawo and others,
1997; Fujita and others, 1998). The ice thickness is known to
be 30 and 60 m at two ice-core drilling sites (Fig. 2a)(Watanabe and others, 1984), but ice radar measurements
have never been carried out. Borehole observations showedthat ice was temperate at the upper drilling site and slightly
cold (–18C) at the lower site (Watanabe and others, 1984;
Ozawa, 1991). The glacier has been thinning since the1980s, and the rate of thinning has been increasing (Fujita
and others, 1998; Fujita and Nuimura, 2011).

Ice thickness
We employed GPR (Geophysical Survey Systems Inc.,
SIR3000) with a centre frequency of 270 MHz to measure
ice thickness. The field measurement was carried out on
1 November 2009. The instrument was mounted on asledge, which was towed along a survey route from the topof the glacier to the terminus (Figs 1 and 2). The route wasdiverted to the north at an elevation between 5300 and
5350 m because of crevasses. Antennas enclosed in a box
were aligned perpendicular to the survey route. Radar echo
signals were recorded with a scanning frequency of 24 Hz(2048 samples per scan) and processed using Radan 7

software for Windows (Geophysical Survey Systems Inc.).
We determined the two-way travel time of return waves fromthe bed by carefully inspecting a radargram. Ice thickness
was computed from the travel time by assuming a wave
velocity in a glacier as 170 m ms–1. An ice thickness profile
along the route was obtained using the GPS survey data
described in the following subsection. An error due touncertainty in the reflection peaks in the radargram wasevaluated as 0:9 m from repeated identification of the peaklocations. We also expect errors due to ambiguity in the
wave velocity, GPS positioning errors and vertical resolution
limited by the wavelength. As a sum of these, the maximum
error in the ice thickness measurement was estimated as
1.5 m plus 2% of ice thickness.

Surface elevation
Glacier surface elevation was measured along the GPR
survey route using paired GPS equipment. A GPS antenna
and receiver (Magellan, ProMark3) were mounted on a
backpack carried by a surveyor, and the continuously
recorded GPS satellite signals were post-processed withthose from a reference GPS station (GNSS Solutions, GEM-1)
installed southwest of the glacier (Fig. 1b). The positioning
error in the vertical direction, including uncertainty in theheight of the antenna carried by a surveyor, was estimated as
0.3 m (Fujita and Nuimura, 2011). Errors in the horizontal
direction were smaller than this value and negligible for ouranalyses described below. The surface elevation wascompared with that measured in 1982 and 1996 to computeice thickness changes over the periods. The surface elevationin 1982 was surveyed by ground photogrammetry (Yokoyama, 1984) and later digitized into a 10 m resolution digital
elevation model (DEM) (Fujita and Nuimura, 2011). The
accuracy of this DEM was reported as 10 m (Fujita andNuimura, 2011). The 1982 DEM was interpolated to the2009 GPR survey route to compute the elevation change
from 1982 to 2009. Because the 1996 survey sites are notexactly on our survey route (Fig. 2a) (Fujita and others,Sugiyama and others: Ice thickness and flow velocity of Yala Glacier159

Fig. 3. A GPR radargram along the survey route. The intensity of the reflection power is represented by an arbitrary greyscale.

1998), we compared the 1996 and 2009 data at the same
surface elevation according to an Advanced Spaceborne
Thermal Emission and Reflection Radiometer (ASTER) DEM
in 2003 (i.e. 1996 and 2009 survey sites that were compared
were at the same elevation in the 2003 DEM). This
procedure assumes an equal ice thickness change at thesame surface level. The ASTER DEM was generated bystereographic analysis of ASTER images and distributed by
the Earth Remote Sensing Data Analysis Center in Japan. The
root-mean-square error of the DEM is typically in the range
10–20 m (Fujita and others, 2008). The GPS data in 2009were also used to locate the GPR data.

the maximum ice thickness was 61  3 m at 530 m from the
top of the glacier. Bed elevation was obtained as shown in
Figure 4a by subtracting the thickness from the surface

Ice flow velocity
Ice flow velocity was measured by surveying stakes installedat five locations on the glacier (Fig. 2b). The upper threestakes were installed on 26 September 2008 and resurveyed
on 31 October 2009, with kinematic GPS measurements(Magellan, ProMark3). The lower two stakes were surveyed
for 4 days from 31 October to 4 November 2009, with dualfrequency static GPS measurements (Leica, System 1200).
The GPS measurements were performed using reference
GPS receivers located at 500 m from the glacier margin(Fig. 1b), and the baseline length of the relative positioning
was within 2 km. Positioning errors in the kinematic andstatic GPS measurements were 0.3 m and 2 mm in thehorizontal plane. Accordingly, errors in the computed
velocity were within 3% and 16% for the upper three andlower two measurement sites, respectively.

RESULTSIce thickness
Figure 3 shows the intensity of GPR return signals along thesurvey route. The glacier bed was clearly identified by atransition from low to high return power at a certain depth in
the lower half of the glacier. In contrast, the reflection fromthe bed was less clear and obscured by englacial return
signals in the upper portion. We identified the bed reflection
as much as possible in these regions by taking return power
maxima, which were observed continuously up- and downglacier. The GPR survey route followed a detour in the
middle of the glacier to bypass crevasses. Hereafter, thedetour was eliminated and the data blank near the terminus
was interpolated, i.e. the bed and surface profiles areanalyzed and depicted along the thin line in Figure 2. The
mean ice thickness along the corrected route was 36 m andFig. 4. (a) Surface elevation measured in 1982 (dashed curve), 1996
(solid curve with open circles) and 2009 (solid curve). The bold
curve indicates the bed elevation. (b) Change in surface elevationfrom 1982 to 1996 (open circles) and from 1982 to 2009 (dashedcurve). The grey lines are linear regressions of the data. (c) The
horizontal component of ice flow velocity in 2009 (solid circles),1996 (open circles) and 1982 (asterisks). The 1982 and 1996
velocities are only those measured within 50 m from the 2009
survey route.

160

Sugiyama and others: Ice thickness and flow velocity of Yala Glacierfrom 1982 to 2009 ranged from –10 to –12 m a–1 in thelower half of the glacier (x > 700 m). This is equivalent to a
60–90% velocity reduction. Most of the velocities were notmeasured for an annual interval (October–November at thelower two stakes in 2009, May–October in 1996 and
September–October in 1982), which leaves the possibility
that the velocities were influenced by seasonal variations.
Nevertheless, the influence of the short measurement periodon the velocity is probably insignificant since the bed isfrozen in the ablation area according to the drilling in the
1980s (Watanabe and others, 1984). Moreover, the observed
velocity changes are much greater than those explained bypossible seasonal variations.

DISCUSSION
Fig. 5. (a) Change in surface elevation from 1982 to 1996 (opencircles) and from 1996 to 2009 (solid circles); (b) the horizontal
component of ice flow velocity in 2009 (solid circles), 1996 (opencircles) and 1982 (asterisks); and (c) ice thickness along the survey
route measured with GPR (solid curve) and computed with aconstant driving-stress assumption (dashed curve). Surface elevation coordinates are in the years of the second measurements for (a)and (b) and in 2009 for (c).

elevation measured by GPS. Owing to a bed depression at
500–600 m from the top of the glacier, relatively thick ice ispresent in this region. The bed slopes upwards (to thedirection of ice flow) near the terminus at 1200–1300 m,
which accompanies a depression in the surface.

Surface elevation
Glacier surface elevation obtained in this study wascompared with the values measured in 1982 and 1996
(Fig. 4a). The results show that the surface has been
continuously lowering since 1982 and that the magnitudeof the change was greater down-glacier. The greatest change
is found near the terminus, which is –40 m over the
27 years from 1982 to 2009 (Fig. 4b). The magnitudedecreases up-glacier, approaching zero near the top of thesurvey route. The magnitude of elevation change within theupper 400 m of the glacier is less than –3.5 m for 1996–2009
and –7.5 m for 1982–2009. Mean rates of elevation changeover the survey route were computed by assuming a linear
relationship between the surface elevation change z andthe distance from the top x (Fig. 4b). Obtained relationships
are z ¼ 0:0195x þ 4:87 m for 1996–2009 and z ¼
0:0302x þ 2:66 m for 1982–2009. Assuming z ¼ 0 in theupper reaches, where the linear functions give positive
values, the mean rates along the survey route were0:75  0:24 m a–1 for 1996–2009 and –0.72  0.09 m a–1
for 1982–2009 (–0.69  0.25 m a–1 for 1982–96 as a residual). The uncertainties were estimated from the standard
deviation of the data from the linear regression in Figure 4b.

Ice flow velocity
Measured flow velocities are shown in Figures 2b and 4c,
together with those from 1982 and 1996 (Ageta and others,
1984; Fujita and others, 1998). The 1982 and 1996 data in
Figure 4c are only those measured within 50 m of the 2009
survey route. The glacier has slowed down significantly
since the previous measurements. The change in velocity

Our results showed that Yala Glacier has been losing ice
mass since 1982 and that the rate of mass loss is not uniform
over the glacier. The ice thinning rate is clearly dependent
on the glacier surface elevation (Fig. 5a). The relationships
between the thinning rate and elevation in 1982–96 and
1996–2009 are similar in the elevation range from 5200 to
5400 m. However, the magnitude of the thinning rate in
1996–2009 is greater than that in 1982–96 near the terminus
in the region below 5200 m a.s.l. Such variations in theelevation change, i.e. gradual increase from high to low
elevations and greater increase near the terminus, arecommonly observed on other debris-free Himalayan glaciers(Fujita and Nuimura, 2011). Considering that the ice wasrelatively thin and slow-moving at 5200 m a.s.l. in 2009
(Fig. 5b and c), only a little ice mass was advected into thelower elevation range. Thus, the reduction in down-glacierice flux might have caused a decrease in vertical strain rate
and a significant increase in thinning rate near the terminus,
as has been reported in a valley glacier in the European Alps
(Berthier and Vincent, 2012).
The mean ice velocity at 5120–5300 m a.s.l. reduced by
29% and 62% from 1982 to 1996 and from 1996 to 2009,
respectively (Fig. 5b). Presumably, the most important driverof this deceleration is glacier thinning. The mean ice
thickness in this elevation range was 60 m in 1982, which
decreased to 45 m in 1996 and 31 m in 2009. If we assume
ice flow was entirely due to viscous deformation andproportional to the fourth power of ice thickness (Cuffeyand Paterson, 2010), the velocity reduction expected fromthe ice thinning is 68% for 1982–96 and 93% for 1996–2009.
Apparently, the observed velocity change is smaller than thisestimation, probably because the ice surface has been
steepening because of greater elevation change in the lower
reaches of the glacier. The surface slope is another importantfactor in the ice deformation rate, and thus surface
steepening partly compensated the deceleration due to ice
thinning. In addition to the geometrical conditions, changes
in ice thermal structure since the 1980s have to be taken into
account. The borehole temperature measurements in 1981
and 1982 showed that ice was temperate in the accumulation zone while it was cold in the ablation zone (Watanabe
and others, 1984; Ozawa, 1991). Such polythermal structureis expected to be influenced by ice thinning as well as
warming climate conditions. For example, ice temperaturemight have decreased after the glacier thinning, which has
potentially reduced the ice velocity. On the other hand,meltwater increase due to warming might have enhanced
basal sliding over a temperate bed.

Sugiyama and others: Ice thickness and flow velocity of Yala Glacier

GPR bed reflection was not clearly observed in the upper
half of the glacier. Presumably, wave transmission andscattering within the ice were influenced by the thermal
structure of the glacier. The drilling in 1982 confirmed that
ice was temperate in the upper reach at 5405 m a.s.l.
(Fig. 2a) (Watanabe and others, 1984). Thus, we can expect
more significant attenuation and scattering by temperate ice
as well as snow meltwater percolated into firn and ice. In thelower reaches, cold ice was observed by the drilling in 1981
near the current terminus at 5180 m a.s.l. (Fig. 2a). This isconsistent with our GPR data, i.e. clear reflection from the
bed and less scattering within the ice. Our data suggest that
Yala Glacier is a polythermal glacier with temperate andcold ice in the upper and lower portions, which agrees withthe structure proposed in previous studies (Watanabe andothers, 1984; Ozawa, 1991).
The ice thickness measured along the GPR survey route(Fig. 5c) provides a clue to estimate the ice volume of Yala
Glacier. If we simply multiply the mean ice thickness(h ¼ 36 m) along the route to the surface area obtained fromthe satellite image in 2006 (A ¼ 1:82 km2), the ice volume is
V ¼ 0:066 km3. This value can be regarded as the upperbound because the survey route was taken in the central partof the glacier, where ice is relatively thick. Next, we assume
the driving stress (d ¼ gh sin , where  ¼ 910 kg m–3 is
ice density, g ¼ 9:8 m s–2 is the gravitational acceleration, his ice thickness and  is surface slope) is constant over theglacier and d is represented by the mean value along thesurvey route. By using surface slope from the ASTER DEM in
2003, the mean driving stress along the route was d =98 kPa and the total ice volume was computed as
A  h ¼ A  d =g sin  ¼ 0:061 km3 . This method overestimates actual values over a flat terrain and near glaciermargins. Nevertheless, thickness measured along the survey
route is reasonably well reproduced by the computation(Fig. 5c). The computed thickness distribution shows relatively thick ice in the lower middle part of the glacier(Fig. 6). A very similar total ice volume 0.062 km3 was
obtained from an equation of area–volume scaling analysis(V ¼ cA ) by using one of the proposed parameter sets(c ¼ 0:191,  ¼ 1:36) (Bahr and others, 1997; Radić and
Hock, 2010). This choice of parameter values gives a
relatively smaller volume estimate by this method among
the parameters proposed for mountain glaciers. Anotherparameter set proposed by Chen and Ohmura (1990)(c ¼ 0:2055,  ¼ 1:375) gives a volume of 0.083 km3 ,which is greater than that obtained above from the mean
thickness along the survey route. A likely reason why thearea–volume scaling analysis tends to overestimate thevolume of Yala Glacier is the relatively steep slopes of thisglacier. According to these analyses, we propose 0.061 km3
as a likely value and 0.066 km3 as the upper bound for the
total ice volume in 2009.
In addition to the elevation data along the GPR survey
route presented in this study, Fujita and Nuimura (2011)
measured surface elevation extensively in the lowermost
region of the glacier to compute the mean thinning rate of
Yala Glacier from 1982 to 2009. The area-averaged ice
thinning rates were shown as –0.746  0.202 and–0.879  0.088 m a–1 for the periods 1982–96 and 1996–
2009, respectively. If we assume these rates and the icevolume estimated in this study (0.061 km3 in 2009), the total
volume loss from 1982 to 2009 corresponds to 43  5% of
the 1982 volume.

161

Fig. 6. Ice thickness computed by assuming a constant driving
stress. The intervals of the contours are 10 m, and the coordinates
are in UTM zone 45N. The bold curve on the glacier indicates the
GPR and GPS survey route.

CONCLUSION
To contribute to the accurate understanding of recent
glacier changes in the Himalaya, surface elevation and ice
velocity of Yala Glacier were resurveyed in 2009. The
results were compared with those measured in 1982 and1996. The glacier has been thinning since 1982 at anincreasing rate: –0.69  0.25 m a–1 from 1982 to 1996 and–0.75 0.24 m a–1 from 1996 to 2009. The magnitude of
the thinning rate increased from the top to the lower
reaches of the glacier, for example from –0.3 m a–1 in theupper 400 m to –1.8 m a–1 near the terminus in 1996–2009.
Ice velocity has reduced by 60–90% from 1982 to 2009 in
the lower half of the glacier. The lower reaches of theglacier became steeper as a result of the greater thinning
rate down-glacier, suggesting that deceleration due to ice
thinning was partly compensated by the steepening surface
slope. We also measured ice thickness using GPR along asurvey route from the top to the terminus. Mean thickness
along the route was 36 m and the thickest ice (61  3 m)
was found on a bedrock depression at 530 m from the top.
Assuming a constant driving stress over the glacier, the total
ice thickness of the glacier was estimated as 0.061 km3 . By
assuming this value and the area-averaged thinning
rates reported by a previous study (Fujita and Nuimura,2011), Yala Glacier has lost 40% of ice volume from1982 to 2009.

ACKNOWLEDGEMENTS
We thank members of the 2009 field campaign for their help
in the measurements on Yala Glacier. T. Fukuda helped insatellite data analysis. The manuscript was handled by thescientific editor, A. Booth, and was improved by constructive comments from two anonymous reviewers. This research
was funded by the Japanese Ministry of Education, Science,Sports and Culture, Grant-in-Aid for Scientific Research A,
19253001, 2007–10.

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REFERENCES
Ageta Y and Higuchi K (1984) Estimation of mass balancecomponents of a summer-accumulation type glacier in the
Nepal Himalaya. Geogr. Ann. A, 66(3), 249–255
Ageta Y, Iida H and Watanabe O (1984) Glaciological studies on
Yala Glacier in Langtang Himal. Bull. Glacier Res., 2, 41–47
Bahr DB, Meier MF and Peckham SD (1997) The physical basis ofglacier volume–area scaling. J. Geophys. Res., 102(B9),20 355–20 362 (doi: 10.1029/97JB01696)
Berthier E and Vincent C (2012) Relative contribution of surface
mass-balance and ice-flux changes to the accelerated thinningof the Mer de Glace, French Alps, over 1979–2008. J. Glaciol.,58(209), 501–512 (doi: 10.3189/2012JoG11J083)
Bolch T, Pieczonka T and Benn DI (2011) Multi-decadal mass lossof glaciers in the Everest area (Nepal Himalaya) derived fromstereo imagery. Cryosphere, 5(2), 349–358 (doi: 10.5194/tc-5349-2011)
Chen J and Ohmura A (1990) Estimation of Alpine glacier water
resources and their change since the 1870s. IAHS Publ. 193(Symposium at Lausanne 1990 – Hydrology in Mountainous
Regions), 127–135
Cuffey KM and Paterson WSB (2010) The physics of glaciers, 4thedn. Butterworth-Heinemann, Oxford
Dyurgerov MB (2010) Reanalysis of glacier changes: from the IGY
to the IPY, 1960–2008. Mater. Glyatsiol. Issled./Data Glaciol.
Stud. 108, 1–116
Fujita K (2008) Effect of precipitation seasonality on climatic
sensitivity of glacier mass balance. Earth Planet. Sci. Lett.,
276(1–2), 14–19 (doi: 10.1016/j.epsl.2008.08.028)
Fujita K and Nuimura T (2011) Spatially heterogeneous wastage of
Himalayan glaciers. Proc. Natl Acad. Sci. USA (PNAS), 108(34),
14 011–14 014 (doi: 10.1073/pnas.1106242108)
Fujita K, Takeuchi N and Seko K (1998) Glaciological observationsof Yala Glacier in Langtang Valley, Nepal Himalayas, 1994 and1996. Bull. Glacier Res., 16, 75–81
Fujita K, Suzuki R, Nuimura T and Sakai A (2008) Performance of
ASTER and SRTM DEMs, and their potential for assessing glaciallakes in the Lunana region, Bhutan Himalaya. J. Glaciol.,54(185), 220–228 (doi: 10.3189/002214308784886162)
Higuchi K (1984) Outline of the glaciological expedition of Nepal:
boring project 1981 and 1982. Bull. Glacier Res., 2, 1–5

Sugiyama and others: Ice thickness and flow velocity of Yala Glacier

Jacob T, Wahr J, Pfeffer WT and Swenson S (2012) Recent
contributions of glaciers and ice caps to sea level rise. Nature,482(7386), 514–518 (doi: 10.1038/nature10847)
Matsuo K and Heki K (2010) Time-variable ice loss in Asian highmountains from satellite gravimetry. Earth Planet. Sci. Lett.,
290(1–2), 30–36 (doi: 10.1016/j.epsl.2009.11.053)
Nakawo M, Fujita K, Ageta Y, Shankar K, Pokhrel AP and Yao T(1997) Basic studies for assessing the impacts of the global
warming on the Himalayan cryosphere, 1994–1996. Bull.
Glacier Res., 15, 53–58
Nuimura T, Fujita K, Yamaguchi S and Sharma RR (2012) Elevation
changes of glaciers revealed by multitemporal digital elevation
models calibrated by GPS survey in the Khumbu region, Nepal
Himalaya, 1992–2008. J. Glaciol., 58(210), 648–656 (doi:10.3189/2012JoG11J061)
Ozawa H (1991) Thermal regime of a glacier in relation to glacierice formation. (PhD thesis, Hokkaido University)
Radić V and Hock R (2010) Regional and global volumes ofglaciers derived from statistical upscaling of glacier inventory data. J. Geophys. Res., 115(F1), F01010 (doi: 10.1029/
2009JF001373)
Radić V and Hock R (2011) Regionally differentiated contributionof mountain glaciers and ice caps to future sea-level rise. Nature
Geosci., 4(2), 91–94 (doi: 10.1038/ngeo1052)
Scherler D, Bookhagen B and Strecker MR (2011) Spatially variable
response of Himalayan glaciers to climate change affected bydebris cover. Nature Geosci., 4(3), 156–159 (doi: 10.1038/
ngeo1068)
Steinegger U, Braun LN, Kappenberger G and Tartari G (1993)
Assessment of annual snow accumulation over the past 10 years
at high elevations in the Langtang region. IAHS Publ. 218(Symposium at Kathmandu 1992 – Snow and Glacier Hydrology), 155–165
Watanabe O, Takenaka S, Iida H, Kamiyama K, Thapa KB and
Mulmi DD (1984) First results from Himalayan glacier boring
project in 1981–1982. Part I. Stratigraphic analyses of full-depth
cores from Yala Glacier, Langtang Himal, Nepal. Bull. GlacierRes., 2, 7–23
Yokoyama K (1984) Ground photogrammetry of Yala glacier,Langtang Himal, Nepal Himalaya. Bull. Glacier Res., 2,
99–105