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Appendix C
Glacier Measurement Methods
GLACIOLOGICAL MASS BALANCE GEODETIC MASS BALANCE
MEASUREMENT MEASUREMENT
In the glaciological method, a network of stakes The geodetic method measures elevation changes
and pits are placed on the glacier surface and used to of the glacial surface over time from various digital ele-
measure the change in surface level while taking into vation models (DEMs) constructed over the entire gla-
account snow/firn/ice density. Comparing measure- cial surface (Racoviteanu et al., 2008). This method can
ments between two fixed dates yields an annual mass be applied using topographic maps, DEMs obtained
balance, while comparing measurements at the end of by aircraft and satellite imagery, and by airborne laser
the ablation and accumulation seasons yields a seasonal scanning (Kaser et al., 2003). The accuracy of this
mass balance (Racoviteanu et al., 2008). The mass bal- method depends on (1) the interpolation method used
ance for the glacier is then estimated by multiplying to derive a DEM, (2) errors introduced by any change
the changes in mass balance at each sampling point in spatial resolution, (3) biases inherent in the remote
with the area that point represents, and summing the sensing--derived DEMs, and (4) density assumptions
product over the entire glacier. This method provides (Racoviteanu et al., 2008). Errors in the original DEMs
detailed information on the mass balance spatial varia- propagate with each calculation and may introduce
tion and is considered more accurate than other meth- large errors in the end result. Because of these issues,
ods (Kaser et al., 2003). it is recommended that the geodetic method only be
The glaciological method may achieve the great- used for mass balance measurements on decadal or
est accuracy and provides the investigator insight longer timescales (Kaser et al., 2003; Racoviteanu et
for the field conditions, it is based on repeated field al., 2008).
measurements, which have to be carried out under
sometimes rather challenging conditions. These chal- HYDROLOGICAL MASS BALANCE
lenges include logistical constraints in remote areas, MEASUREMENT
inclement weather conditions including cold tempera-
tures and high winds, crevasses, avalanches and icefalls, The hydrological mass balance can also be used
and rockfall from surrounding terrain. The rate of data to estimate the glacial mass balance. The hydrological
acquisition is slow and the process expensive (Kaser et method uses a water-balance approach to compute
al., 2003). Thus, only a few dozen such records in the glacial mass balance. The estimated net precipitation
world exist that cover significant periods of time (i.e., in the basin is subtracted from the net runoff to com-
decades; WGMS, 2008; Zemp et al., 2009), and there pute the water storage within the basin, which is then
are currently no such long-term records for the HKH interpreted as due to changes in glacial mass balance
region (Kaser et al., 2006). (Braithwaite, 2002). Although this approach is con-
127
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128 APPENDIX C
sidered to provide only a crude approximation and is Figure C.1. For example, Band 2 of Landsat1 7 records
not generally recommended (Barry, 2006), it was used the brightness temperature from 0.53 to 0.61 µm, often
for many years for the basin of the Grosse Aletsch in mapped as the blue band.
Switzerland (PSFG, 1967, 1973). The hydrological Snow and ice are characterized by (1) high reflec-
approach is difficult to use in the HKH area because tivity in the visible wavelengths, (2) medium reflectivity
of limited precipitation and discharge measurements. in the near-infrared, (3) low reflectivity and high emis-
However, the approach does hold promise as more sivity in the thermal infrared, and (4) low absorption
basins become instrumented with automatic weather and high scattering in the microwave (Racoviteanu et
stations and automated measurements of discharge al., 2008). Increasing amounts of black carbon quickly
height, as demonstrated for the Langtang Basin in reduce the albedo of snow and ice.
Nepal by the recent International Centre for Integrated The spatial resolution of a remote sensing image is
Mountain Development (ICIMOD) field class on gla- critical to obtaining glacial properties in mountainous
cial mass balance measurements. terrain, such as the ELA. A pixel size of 500 m on a
side (e.g., MODIS)2 means that, in general, the remote
REMOTE SENSING MEASUREMENTS sensing information can only detect changes that occur
in lengths greater than 500 m.
Remote sensing measurements are based on infor- Newer sensors can acquire data at medium spatial
mation gained by aerial sensing technologies installed resolutions (5 to 90 m in multispectral mode), with
on aircraft and satellites. Scientists are increasingly larger swath widths (185 km for Landsat and 60 km for
able to measure glacier properties over larger areas and ASTER)3 and short revisit times (16 days for ASTER).
longer time spans because of the increased availability These capabilities allow regular glacier mapping over
of imagery from remote sensing platforms. Remote extensive areas. The thermal band of Landsat Enhanced
sensing yields information about glacier properties Thermal Mapper Plus (EMT+)4 (10.4 to 12.5 µm, at
including glacier area, length, surface elevation, surface 60-m pixel size) and the multispectral thermal bands of
flow fields, accumulation/ablation rates, albedo, equi- ASTER (8.125 to 11.65 µm, at 90 m pixel size) could
librium line altitude (ELA), accumulation area ratio, potentially distinguish debris cover on glaciers. The
and the mass balance gradient. The ELA, accumulation ASTER, SPOT5,5 IRS-1C,6 and CORONA KH-4,
area ratio, and mass balance gradient respond to annual KH-4A and KH-4B7 can acquire stereoscopic images,
changes in temperature, precipitation, and humidity which in turn provide elevation data that can be used
and are therefore important for mass balance monitor- for geodetic mass balance estimates (Racoviteanu et al.,
ing. Changes in glacier area and terminus positions
over timescales of several decades, which are relatively 1 Landsat is a series of Earth-observing satellite missions jointly
easy to determine from remote sensing imagery, have managed by the National Aeronautics and Space Administration
been used as indicators of a glacier's response to climate and the U.S. Geological Survey. More information about the pro-
gram is available at http://landsat.gsfc.nasa.gov/.
forcing (Barry, 2006). 2 The Moderate Resolution Imaging Spectroradiometer is an
Remote sensing uses sensors that detect solar instrument aboard the Terra (EOS AM) and Aqua (EOS PM)
energy reflected by Earth's features as well as the emis- satellites. More information about the instrument is available at
http://modis.gsfc.nasa.gov/.
sion of the Earth's own thermal energy (Figure C.1). 3 The Advanced Spaceborne Thermal Emission and Reflection
Wavelength ranges (or bands) of interest to remote Radiometer is an instrument aboard the Terra (EOS AM) satel-
sensing of glaciers generally include visible light (VIS lite. More information about the instrument is available at http://
ranging from about 0.45 to 0.75 µm), near-infrared asterweb.jpl.nasa.gov/.
4 More information about this instrument is available at http://
(NIR ranging from 0.75 to 1.4 µm), short-wavelength landsat.gsfc.nasa.gov/about/etm+.html.
infrared (SWIR ranging from 1.4 to 3 µm), and ther- 5 A fifth-generation Earth observation satellite launched in 2002,
mal infrared (TIR ranging from about 8 to 15 µm). the series of SPOT satellites were initiated by the French space
Sensors record the brightness temperature within a agency and are run by Spot Image base in Toulouse, France.
6 India's second generation remote sensing satellite.
defined band that depends on the characteristics of the 7 A series of U.S. reconnaissance satellites launched between
specific sensor, as illustrated for two different sensors in 1959 and 1972.
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APPENDIX C 129
FIGURE C.1 Wavelength regions and bandwidths for two remote sensing satellites, Landsat 7 and ASTER. SOURCE: NASA Goddard
Space Flight Center and U.S. Geological Survey.
2008). Thus, newer sensors with pixel sizes on the order using band ratios include (1) the presence of proglacial
of 3 to 30 m provide more accurate representations and supraglacial lakes, (2) the presence of fresh snow on
(and changes over time) of such parameters as glacial surfaces other than a glacier, and (3) debris cover on gla-
area, location of the glacier terminus, and location of ciers (Racoviteanu et al., 2008). Lakes are misidentified
the ELA. as glacial ice because liquid water and ice have similar
Snow and ice are distinct from surrounding terrain bulk optical properties in the visible and near-infrared
in clear weather. Thick cloud cover can complicate such wavelength. Glaciers always have snow above the ELA.
distinction. However, measurements of the 1.6 to 1.7 However, surrounding bedrock, moraines, tundra, and
µm wavelengths (wavelength band 4 of ASTER) can other surfaces may also have snow. These snow-covered
overcome this issue. At these wavelengths, clouds are surfaces can easily be misclassified as part of a glacier.
reflective but snow and ice are absorbing (Racoviteanu Care must be taken to discriminate snow on surround-
et al., 2008). Techniques including single-band ratios ing areas from snow on glaciers. Often multiple years
and the normalized difference snow index (NDSI) use of imagery are needed to do so.
the high brightness values of snow and ice in the visible Debris cover is one of the greatest challenges in
wavelengths to distinguish them from darker rock, soil, remote sensing of glaciers. In the visible and near-
or vegetation (Racoviteanu et al., 2008).8 The single- infrared wavelengths, debris cover has optical proper-
band ratio and NDSI techniques are also fast and robust, ties very similar to the surrounding moraines. Auto-
making them relatively easy to automate over extensive mated methods of analyzing spectral information are
areas. Challenges to automatic mapping of glaciers ineffective in mapping ice covered by debris. However,
manual digitization is time-consuming and subject to
8 NDSI is calculated as (VIS - SWIR)/(VIS + SWIR), where
human error. Thus, debris on glaciers may result in
VIS is band 1 of ASTER (0.52-0.6 µm) at 15 m and SWIR is band underrepresenting glacial area and overcalculating rates
4 of ASTER (1.6-1.7 µm) at 30 m. of glacial retreat.
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