The direct glaciological method provides in situ observations of annual or seasonal surface mass balance, but can only be implemented through a succession of intensive in situ measurements of field networks of stakes and snow pits. This has contributed to glacier surface mass-balance measurements being sparse and often discontinuous in the Tien Shan. Nevertheless, long-term glacier mass-balance measurements are the basis for understanding climate–glacier interactions and projecting future water availability for glacierized catchments in the Tien Shan. Riegl VZ®-6000 long-range terrestrial laser scanner (TLS), typically using class 3B laser beams, is exceptionally well suited for repeated glacier mapping, and thus determination of annual and seasonal geodetic mass balance. This paper introduces the applied TLS for monitoring summer and annual surface elevation and geodetic mass changes of Urumqi Glacier No. 1 as well as delineating accurate glacier boundaries for 2 consecutive mass-balance years (2015–2017), and discusses the potential of such technology in glaciological applications. Three-dimensional changes of ice and firn–snow bodies and the corresponding densities were considered for the volume-to-mass conversion. The glacier showed pronounced thinning and mass loss for the four investigated periods; glacier-wide geodetic mass balance in the mass-balance year 2015–2016 was slightly more negative than in 2016–2017. Statistical comparison shows that agreement between the glaciological and geodetic mass balances can be considered satisfactory, indicating that the TLS system yields accurate results and has the potential to monitor remote and inaccessible glacier areas where no glaciological measurements are available as the vertical velocity component of the glacier is negligible. For wide applications of the TLS in glaciology, we should use stable scan positions and in-situ-measured densities of snow–firn to establish volume-to-mass conversion.
Glacier meltwater is a crucial freshwater resource for populations and hydro-economies in arid and semiarid regions (e.g., Sorg et al., 2012; Chen et al., 2016). The concept of “solid reservoirs” is well represented in the Tien Shan, where most glaciers have experienced substantial mass loss over recent decades (Farinotti et al., 2015; Pieczonka et al., 2015; Liu and Liu, 2016; Sakai and Fujita, 2017; Li et al., 2018). Hence, a better understanding of the relationship between Tien Shan glacier wastage and changing climate is important for projecting water availability in the near future. Glacier mass balance provides important information on the gain or loss in glacier mass and is a direct and immediate indicator of climate evolution (Kaser et al., 2006; Haeberli et al., 2007).
Continuous mass-balance observations are fundamental to understand climate–glacier interactions (Zemp et al., 2015). Annual and sometimes seasonal surface mass balance of individual glaciers can be measured using the direct glaciological method. Stakes are drilled into the ice, allowing the monitoring of ablation, and snow pits are dug in the area where snow has accumulated to provide net accumulation (Østrem and Brugman, 1991; Xie and Liu, 1991; Cogley et al., 2011). However, the shortage of long-term financial and human resources and the inaccessibility of remote regions and natural hazards means that ongoing in situ glacier mass-balance measurements are sparse and discontinuous in the Tien Shan; only Tuyuksu glacier (northern Tien Shan, Kazakhstan) and Urumqi Glacier No. 1 (eastern Tien Shan, China) have long glaciological mass-balance series (Hoelzle et al., 2017). In contrast to the extensive in situ measurement networks required for glaciological observations, the geodetic method provides mass balance by repeated surveys of the glacier surface terrain, in which two digital elevation models (DEMs) are subtracted to calculate the volume changes and then convert them to mass balance using a density conversion (Zemp et al., 2013; Huss, 2013; Andreassen et al., 2016). The method includes all processes that affect the surface, internal, and basal mass balances (Cuffey and Paterson, 2010; Sold et al., 2016), but the geodetic mass balances are assumed to be accurate since the topographic surveys are of high quality (Thibert et al., 2008; Huss et al., 2009; Joerg et al., 2012). The available DEMs, derived from aerial photography and traditional remote sensing imagery, usually limit the accuracy and time resolution of geodetic mass-balance measurements (e.g., Cox and March, 2004; Cogley, 2009; Fischer, 2011).
In recent years, emerging earth observation technologies (e.g., airborne,
ALS, and terrestrial laser scanning, TLS) allow the derivation of
high-resolution DEMs with vertical and horizontal errors on the order of a
few centimeters, and increasingly they have been used to calculate geodetic mass
balance and changes in glacier volume (e.g., Geist et al., 2005; Pellikka and
Rees, 2009; Joerg et al., 2012; Gabbud et al., 2015; Fischer et al., 2016;
Klug et al., 2018). ALS is effective for rapidly mapping extensive areas,
but studying glacial changing processes with high temporal
resolution is different since the high costs of ALS and the presence of great topographic
relief and high-altitude rock outcrops around glaciers reduce the capacity
of observations by aircraft as most ALS instruments have limited operating
flight altitude, so we need ground-based surveys (Piermattei et al., 2015).
The TLS system is usually simpler, more economical, and more flexible than
ALS, and has become a well-established tool for monitoring annual and
sometimes seasonal changes in individual glaciers (e.g., Gabbud et al., 2015;
Fischer et al., 2016; López-Moreno et al., 2016). The new high-speed and
high-resolution Riegl VZ®-6000 terrestrial laser
scanner offers a long measurement range of more than 6 km and a wide field
of 60
Urumqi Glacier No. 1 has the most detailed annual and seasonal surface mass-balance measurements in China. It is also one of the reference glaciers in the World Glacier Monitoring Service (WGMS) network due to its long data series, important location, and significant local water supply (Li et al., 2011; Zemp et al., 2009). TLS surveys of Urumqi Glacier No. 1 were initiated on 25 April 2015 for four scan positions (Fig. 1a), and the subsequent surveys correspond to measurement dates for glaciological mass-balance measurements. Multi-temporal high-resolution and high-precision TLS-derived DEMs are therefore available. To date, comparison of glaciological and geodetic mass balances of the glacier was reported for the period 1981–2009 at intervals of several years (Wang et al., 2014) and for the period 1981–2015 (Xu et al., 2018), but these studies used a series of low-quality topographic maps to calculate sub-decadal and decadal geodetic results. An accurate reanalysis of seasonal and annual glaciological mass balance of Urumqi Glacier No. 1 using high-resolution and high-precision DEMs has not been performed. Our previous study used the TLS to implement two measurements 1 month apart (25 April–28 May 2015) to get monthly net mass balance of Urumqi Glacier No. 1, whereas we simply compared glaciological and TLS-derived geodetic elevation changes of individual stakes. Regardless of whether agreement between the glaciological and TLS-derived glacier-wide mass balance was pending, potential and shortcomings of such technology applied in seasonal and annual glacier mass-balance measurements in western China had not been discussed. In addition we only considered snow–firn densities in the determination of a density conversion, which was used to convert monthly volume change to geodetic mass changes, as an abundance of fresh snow covered the entire glacier surface at the time of the TLS surveys (Xu et al., 2017). In fact, the volume-to-mass conversion becomes more challenging over short time periods as meteorological factors change mass-balance gradients (Huss, 2013). Several recent studies have used an area-weighting method to calculate the annual density conversion by classifying a glacier surface into bare ice and firn (Fischer et al., 2016; Klug et al., 2018). But the volume changes in ice and firn–snow usually take place at the same vertical layer for summer-accumulation-type glaciers (accumulation and ablation take part simultaneously in summer months) from our field observations, it is therefore inappropriate for this study to adopt the area-weighting method. In addition, compaction and metamorphosis imply a shift in the vertical firn profile as well as changes in firn thickness and density (Cuffey and Paterson, 2010; Ligtenberg et al., 2011), so assuming no change occurs in the vertical firn density profile over time in the accumulation area is unrealistic (Bader, 1954).
Overview of the study area.
This study takes Urumqi Glacier No. 1 as an example and describes the use of the TLS to monitor annual and seasonal geodetic mass balances for 2 consecutive mass-balance years (2015–2017). The aim of this study is thus to established an optimization scheme of volume-to-mass conversion to realize the calculation of TLS-derived geodetic mass changes, to investigate the possible causes of the differences between glaciological and geodetic mass balance. The potential of such long-range TLS to measure mass balance of glaciers in western China is evaluated and several main considerations for a wide application of the TLS in glaciology are suggested.
Urumqi Glacier No. 1 is a northeast-oriented small valley glacier, situated
on the northern slope of Tianger Summit II (4848 m a.s.l.) in the eastern
Tien Shan (
Urumqi Glacier No. 1 is a typical summer-accumulation-type glacier in a
continental climate setting (Liu and Han, 1992; Li et al., 2011). The
westerly circulation is influenced by the dynamic action of the Tibetan
Plateau in the winter months, causing a cold climate with little
precipitation at the study site (Han et al., 2006; Huintjes et al., 2010).
During the summer months, the Tibetan Plateau becomes a thermal depression
and forms a plateau monsoon, which carries warm and humid air from the Indian
Ocean, producing abundant precipitation surrounding the plateau (Huintjes et
al., 2010). These climatic conditions were confirmed by the annual climate
records (1959–2015) of Daxigou Meteorological Station, located about 3 km
southeast of Urumqi Glacier No. 1 at 3539 m a.s.l.; the annual average air
temperature was about
Riegl VZ®-6000 TLS is an active laser imaging
technique that calculates the distance between the object and the laser
transmitter based on time-of-flight measurement with echo digitization and
online waveform processing and consequently the position of the point of
interest to be computed (RIEGL Laser Measurement Systems, 2013).
The scan mechanism includes a fast-rotating (60–120
The high-accuracy and high-precision ranging is based on its unique V-line technology of echo digitization and online waveform processing, which allows Riegl VZ®-6000 TLS to operate even in poor visibility and in demanding multi-target situations caused by dust, haze, rain, snow, etc.
Multi-temporal terrestrial laser scanning data of Urumqi Glacier No. 1 were
collected from four scan positions to achieve maximum coverage, and each
scan location was selected from the directions where most glacier surface
point clouds would be achieved (i.e., the best possible visibility to glacier
surface terrain) (Fig. 1c, d). To avoid ground motion and to obtain accurate
coordinates of point clouds, each scan position was fixed using reinforced
concrete with a standard GNSS leveling point. The four scan positions were
surveyed using the real-time kinematic (RTK) global navigation satellite
system (GNSS, Unistrong E650 instrument) to give the most accurate direct
georeferencing and registration. The 3-D coordinates were acquired in the
UTM 45N coordinate system in the WGS84 datum. The accuracy of this type of
survey has been reported to be within
After the measurements of 3-D coordinates, the Riegl
VZ®-6000 was mounted on a tripod placed in the
scan position to survey the glacier surface terrain. The scan parameters and
atmospheric conditions are of crucial importance, which directly determined
point cloud data quality (point density and coverage) and acquisition time.
The laser pulse repetition rate was first set to 50 kHz, then line
resolution and frame angle measurement resolution were set to 0.2
Riegl VZ®-6000 TLS surveying parameters of Urumqi Glacier No. 1.
* Scanning range is the total areas of four scan positions and does not include overlapped areas. The overlap percentage of the four scans on 25 April 2015 is smaller than other scan campaigns so that the average point density is relatively low.
Raw data were post-processed with RiSCAN PRO® v
1.81; this includes direct georeferencing, data registration, compression
and filtering (RIEGL Laser Measurement Systems, 2014b). For all five scan
campaigns, four scan positions were used (Table 1). At first (i.e., direct
georeferencing), the TLS data from the different scan positions had to be
transformed from the scanner's own coordinate system (SOCS) into a global
coordinate system (GLCS). The transformation of a point from SOCS into the
GLCS was described by Lichti et al. (2005) and can be expressed by the
following vector equation:
The location of each scan was fixed in the GLCS after direct georeferencing; but the point clouds of the overlapped areas cannot coincide completely due to the influence of orientation. In the second step, multi-station adjustment (MSA) was used for the data registration of each scan position according to the iterative closest point algorithm (Besl and McKay, 1992; Zhang, 1992). When we used MSA, the location of each scan was locked and the orientation of each scan was constantly adjusted in several iterations to compute the best overall fit for it based on least-squares minimization of residuals.
Afterwards we combined the overlapped scans in one layer. An octree algorithm was used to the merged layer to produce points with equal spacing to realize point cloud data compression (Schnabel and Klein, 2006; Perroy et al., 2010). A terrain filter was then applied to filter out noise and non-ground data due to atmospheric reflections such as dust or moisture, which still occurred despite scanning on fine days (RIEGL Laser Measurement Systems, 2014b). Finally, visual interpretation was performed to check the data and remove clear visual outliers, and then glacier surface point clouds with one layer were produced.
As the orientation of each scan is continually adjusted to compute the best fit, the attitude angles of each scan campaign are different. Multi-temporal registration, also called relative registration, set the processed layer of 2 September 2015 as a reference; alignment of other scan campaigns onto the reference layer was finished with iterative closest point algorithms to determine the spatial bias of the multi-temporal scans and extract accurate elevation changes (Revuelto et al., 2014; Gabbud et al., 2015). The relative registered layers were then exported into LAS data format for further processing. Multi-temporal registration of two consecutive campaigns is a crucial step and determines the reliability of TLS-derived surface elevation changes (Revuelto et al., 2014; López-Moreno et al., 2016; Fey and Wichmann, 2017).
After the relative registration procedure, interpolation of the processed
point cloud data calculated high-resolution DEMs of the study site. The
surface elevation change
The calculated volume change is converted to geodetic mass balance (m water
equivalent, w.e.) following
As described above, the geodetic mass balance is calculated based on volume
changes, which require a density conversion. However, the density is
difficult to determine; in most studies, it is estimated and not measured.
Some researchers assumed that no change occurs in the vertical firn density
profile over time in the accumulation area and use glacier ice density for
the conversion based on Sorge's law (Bader, 1954). Actually, the firn line,
firn thickness and firn density all vary, and using the ice density causes
an overestimate of mass balance. Huss (2013) recommended a density
conversion of
It is generally true that the density conversion relies on measurements of
changes in the firn body, thickness, and density of each firn layer being
continuous from the top to the bottom of the snow pit, and a stratigraphic
description of the firn layers is completed by experienced investigators.
Major change processes in the snowpack (e.g., from crystals to grains,
descriptive free water content, and ice layers) can be considered in
this case (Kaser et al., 2003), and firn compaction is assumed to be
negligible. We use the volume-weighting method (the weights are the
thickness changes of each firn layer and glacier ice) to calculate the firn
density (
The mass balance of Urumqi Glacier No. 1 has been observed using stakes or snow pits since 1959 (Xie and Liu, 2010). Glaciological measurements broke off during the period 1967–1979 and the glaciological data series during this period were reconstructed from correlations with climatic data observed at Daxigou Meteorological Station (Li et al., 2011). The program was re-established using glaciological methods in 1980. No fewer than 40 ablation stakes were drilled into the glacier and evenly distributed at different elevation bands using a stream drill, despite the fact that the number and location of stakes has varied from year to year, and snow pits were dug in the accumulation area (Fig. 1a). The mass-balance year of Urumqi Glacier No. 1 is defined from the previous 1 September to the next 31 August (Liu et al., 1997). Usually, from the beginning of May to early September each year, a spatial distribution of single-point ablation (mass loss) or accumulation (mass gain) and snow density (if there is snow cover) were measured by stakes and snow pits at monthly intervals. The net accumulation is measured by digging snow pits at each of the stakes in the area of the glacier where snow has accumulated during the period of investigation; stakes are drilled into the glacier and change in an exposed stake height plus change in snow depth (if snow exists) at two successive dates give the net ice ablation at this point (Kaser et al., 2003; Xie and Liu, 2010). Hence the measured items include the stake vertical height over the glacier surface, thickness of superimposed ice, and the thickness and density of each snow–firn layer at individual snow pits. Note that fresh snow covered the whole glacier surface at the beginning of the ablation season, so snow pits must also be dug at each of the stakes.
Glaciological mass balance includes point and glacier-wide mass balances.
The rate of mass gain and loss per unit time is accumulation rate
An accurate and updated glacier area was important for both geodetic and
glaciological mass-balance calculations (Zemp et al., 2013). Fresh snow
cover probably led to an overestimate of glacier extent at the beginning of
the ablation season. To reduce the influence of snow cover and to extract
accurate glacier outlines, we mainly considered glacier extents at the end
of the ablation season. Glacier boundary delineation was performed following
Abermann et al. (2010). First three shade reliefs at the end of
hydrological years 2015, 2016, and 2017 with an azimuth angle for
illumination (300
Statistics on annual surface elevation changes over stable terrain
extracted by differencing of TLS-derived DEMs from 2 consecutive years.
Spatial and corresponding frequency distributions of these changes for mass-balance year 2015–2016
After multi-temporal registration, errors related to the spatial bias of the multi-temporal DEMs may be negligible. In addition to density conversion for converting TLS-derived glacier surface elevation changes to mass balance, uncertainties in the geodetic mass balances derived from the TLS may be related to (1) errors in point cloud data acquisition, including surface terrain and atmospheric conditions (moisture and wind) (Revuelto et al., 2014; Fischer et al., 2016) and (2) errors in data processing and DEM generation, e.g., registration (multi-station adjustment), point cloud compression, and filtering (smoothing terrain information) (Wheaton et al., 2010; Gabbud et al., 2015; Hartzell et al., 2015).
Spatial distribution of TLS-derived glacier surface elevation
changes
As mentioned in Sect. 3.1.2, dry and windless days were selected to perform
the five scan campaigns. Instability of the TLS influences the registration
of single scan positions from each data acquisition campaign, which includes
small displacements of scan positions and the vibration of TLS. Each scan
position was established on stable rock surfaces using reinforced concrete
(the average drilling depth was greater than 80 cm) with a standardized
GNSS-leveling point to avoid ground motion. In fieldwork, TLS is mounted
using a tribrach on a tripod to level the instrument (Xu et al., 2017).
Revuelto et al. (2014) found that the vibration of TLS can introduce
considerable errors in measurements performed over large scales. In our
experience, this issue is mainly relevant to wind, so windless weather
conditions are important. Because the registration error cannot be
distinguished from the positional uncertainties and the surface, it is
difficult to assess registration-induced uncertainty; the error statistics
are usually used to evaluate the registration error (Fey and Wichmann,
2017). RiSCAN PRO® v 1.81 software reports error
statistics of the MSA results (RIEGL Laser Measurement Systems, 2014b). The
standard deviation of errors (
Error or SD (
Despite four scan positions placed at the terminus of Urumqi Glacier No. 1, two undetected areas of the west branch exist (two green polygons in Fig. 5) due to flat terrain ranges from 4050 to 4100 m a.s.l. (Fig. 1a), where the emission laser cannot be received by the laser receiver. We filled these regions using the spatial interpolation method, which can induce potential errors in DEM creations. The lack of dense measured 3-D coordinates of the terrain limits us to assessing terrain-induced errors qualitatively. For precision, the undetected areas were not taken into account in calculating the geodetic mass balance; in fact, related errors were small as the relative proportions of the two areas over the entire glacier surface were minor (3.1 % for summer 2015, 3.2 % for 2015–2016, 3.6 % for summer 2016, and 4.6 % for 2016–2017, Fig. 5). Furthermore, a supraglacial river exists in the strong ablation season (June to September) due to glacier melting (Fig. 1c, d), which was detected by the TLS surveys. In order to preserve terrain information as much as possible, the octree algorithm built the topological relationship of scattered points to realize the compression of the point cloud. Point cloud filtering is also a significant post-processing step because of the dense ablation stake network, which is actually scanned by the device. Fortunately, a fine scan generates high-density points of the glacier surface terrain.
Distributed density conversions
No better ways can be used to evaluate the uncertainty of DEMs without
precise and well-distributed stable points (Bolch et al., 2017). The
standard error (
Uncertainty related to the density conversion for a single point (
Glacier-wide mean of density conversion (
There are additional sources of error in the glaciological measurements that lead to uncertainties in glaciological mass balance that are not easy to quantify (Dyurgerov, 2002). These uncertainties were classified into three groups: (i) errors in field observations, (ii) errors related to spatial extrapolation over the entire glacier, and (iii) errors due to non-updated glacier area. Note that the class (iii) uncertainties appeared to be negligible due to the short time intervals (2 consecutive years) in our study.
Point measurement uncertainties are prone to errors in stake readings and
snow–firn density measurements (Jansson and Pettersson, 2007; Thibert et
al., 2008; Huss et al., 2009), sinking or melting-out of stakes, and
misidentification of the firn layer surface at the end of the last
hydrological year (Zemp et al., 2010). Huss et al. (2009) demonstrated
errors of
The class (ii) errors originate from extrapolating observed values to
unmeasured areas, insufficient spatial distribution of measured sites, and
the interpolation method. Hock and Jensen (1999) evaluated the error of the
interpolation method at about
Taking into account the abovementioned factors, the uncertainty of the
glaciological mass balance
The high-accuracy and high-resolution DEMs allowed a detailed insight into the glacier surface elevation changes. Distributed elevation change patterns are generally similar for the four periods; i.e., both branches are characterized by a lower-elevation thinning of 1–3.5 m. Elevation changes are more positive and show smaller lowering to pronounced thickening in the upper-elevation parts except for the west branch in the mass-balance year 2016–2017 (Fig. 4a, c, e). These altitudinal change patterns are in good agreement with the long-term glaciological measurements.
Compared to the mass-balance year 2015–2016, areas of clearer increase were observed in the upper eastern parts of the east branch in the mass-balance year 2016–2017, but ice losses in the lower-elevation parts and glacier thickening in the upper reaches of the west branch were greater in the previous mass-balance year (Fig. 4c, g). Surface lowering in summer 2015 mainly occurred in the ablation areas of the east branch (Fig. 4a), and glacier surface ablation was significantly greater in summer 2016 than in the first summer (Fig. 4e). For a completed mass-balance year 2015–2016, glacier thinning areas and values in summer were obviously bigger than the whole year, which may be related to fresh snow covering the glacier at the beginning of ablation season. In addition, there were some curves of pronounced glacier surface lowering in the ablation areas during summer periods, which were related to supraglacial river (Fig. 1c, d). An area of minor thinning is detected at the lower lift (northerly) edge of the east branch, which may be associated with debris cover (Fig. 1c).
TLS-derived glacier-wide mass balances (Table 3) and their spatial
distributions (Fig. 5b, d, f, h) were calculated by multiplying the
spatially distributed glacier surface elevation changes (Fig. 4a, c, e, g)
with the corresponding distributed density conversion (Fig. 5a, c, e, g).
The thicker snow and firn covered the whole glacier surface at the beginning
of May each year and the ablation area was bare ice or covered by a thin
snow layer at the end of the ablation season according to field observations
(Liu et al., 1997; Xie and Liu, 2010), so the changes in ice and firn–snow
thickness are observed during the summer months. However, firn and snow
densities are far smaller than glacier ice density. These result in annual
single-point density conversion
Urumqi Glacier No. 1 experienced negative surface elevation changes and mass
balances for all of the four investigated periods (Table 3). Summer
elevation lowering and mass loss were slightly greater than annual
decreases, which may be related to the climatic conditions observed at
Daxigou Meteorological Station (see Sect. 2). In the mass-balance year
2015–2016, calculated glacier-wide geodetic mass balance was
TLS-derived geodetic elevation changes at individual stakes closely matched
the glaciological elevation change (changes in stake height) of individual
stakes from in situ measurements, and the difference (
Glaciological versus TLS-derived geodetic mass balances for Urumqi Glacier No. 1, the west branch and the east branch, with error bars of the two independent methods.
Spatially distributed differences between glacier-wide glaciological and geodetic mass balances were calculated to give the spatial deviations. Over most parts of the glacier surface, especially for the areas near the best-monitored points, deviations were small, indicating both methods showed very close spatial results. Pronounced differences mainly occurred on the steep slopes where in situ measurements were missing (Fig. 7a, d, g, j). The mass-balance elevation distribution derived from the two methods remained similar despite the presence of differences in magnitude, i.e., mass balance increased with rising altitude (Fig. 7b, c, e, f, h, i, k, m). The geodetic results were more positive in lower-elevation regions and more negative in the higher glacier parts in general compared with the glaciological mass balance, which was probably related to glacier dynamic processes (discussed in Sect. 6.4). The dotted (glaciological) and solid (geodetic) lines met where the glacier mass balances were close to zero; this meant that the equilibrium-line altitudes (ELAs) derived from the two methods matched closely, especially in mass-balance year 2015–2016 and summer 2016 (Fig. 7e, f, h, i), but the biggest shift between the two methods was detected in summer 2015 for the east branch, which may be related to survey data differences between the glaciological and geodetic observations (see details in Sect. 6.5). This reflects that the TLS can therefore be considered an effective tool to calculate ELA.
Spatially distributed difference derived from TLS-derived geodetic
mass balance minus glaciological mass balance
The important factors for scanning high-quality point cloud data are visual
angles of the scan positions and atmospheric conditions. A dry and windless
atmosphere is a prerequisite for high-quality data acquisition. Good visual
angles can easily be achieved for very small cirque glaciers. Generally, the
area and length of reference glaciers are greater, with a huge variation in
altitude. The maximum working distance (6 km) of Riegl
VZ®-6000 is specified for flat targets with size
in excess of the laser beam diameter, perpendicular angle of incidence, and
atmospheric visibility in excess of 23 km. In bright sunlight the
operational range may be considerably shorter than under an overcast sky
(RIEGL Laser Measurement Systems, 2014a). However, glaciers generally have
complicated surface terrain and the requirement of perpendicular angle of
incidence is not always met, so the unscanned regions usually have flat
terrain (Fig. 1d). It is very difficult for us to get a dry and windless
atmosphere under an overcast sky around a glacier. In these situations, more
than one scan position must be set in order to scan as much of the glacier
surface area as possible. However, this, in turn, can create errors in data
registration. The average error originating in MSA (
Systematic shifts of DEMs in the horizontal and vertical directions can also
increase the uncertainty of DEM differencing (Nuth and Kääb, 2011),
so multi-temporal registration of two consecutive scan campaigns is
predicted for the TLS-derived geodetic elevation changes to be accurate. The
mean uncertainty of elevation changes was
It is obvious that the quality of TLS-derived geodetic mass balances relies
on the accuracy of glacier surface elevation changes and density conversion
of volume-to-mass changes. With regard to density conversion, our approaches
account for the changes in ice and firn–snow thickness as well as the
corresponding densities to calculate more accurate values of density (Table 3). The annual values for
Dense spatially measured sites cover the glacier surface (the average
density is about 28 stakes km
The glaciological method cannot measure internal and basal mass balances, but these processes are implicitly captured by the repeated geodetic surveys. We need to provide a rough estimate of internal and basal mass balances of Urumqi Glacier No. 1 to detect their contributions to the differences between glaciological and geodetic mass balances.
Urumqi Glacier No. 1 is a small and cold glacier. Basal sliding and bed
deformation of the glacier are negligible since the temperature at the
glacier bed is below the melting point of ice, so the glacier has low ice
velocity and dynamics and hardly any subglacial water systems (Huang, 1999;
Xie and Liu, 2010; Wang et al., 2017). Previous studies have suggested that
internal ablation of polythermal glaciers is negligible as the ice motion
is small (e.g., Albrecht et al., 2000; Zemp et al., 2010). In addition,
internal melt caused by changes in potential energy due to glacier dynamics
is negligible as the glacier dynamics themselves are insignificant. Thus,
internal ablation of Urumqi Glacier No. 1 is weak, and mainly comes from the
released potential energy of descending water:
Basal ablation is generally attributed to frictional heat of basal sliding
and geothermal heating for mountain glaciers (Thibert et al., 2008; Thomson
et al., 2017; Galos et al., 2017). Basal ablation caused by frictional heat
is very small since there is hardly any basal sliding of Urumqi Glacier
No. 1. Here we mainly consider the contribution of basal ablation from
geothermal heat (
Finally the total value of internal and basal mass balances was close to
zero, which is far less than the difference (
Geodetic measurements of glacier surface elevation changes include glacier
surface mass balance and vertical velocity components (Kaser et al., 2003;
Geist et al., 2005). Vertical velocity (
Applying a reciprocal density conversion to the mass-balance differences provides estimates of the submergence and emergence velocities. Here we defined the term submergence as negative vertical velocity and emergence as positive vertical velocity. Variation tendency of the estimated velocities at ablation stakes were found to match the in-situ-measured ones, especially for the east branch (Fig. 8). Relatively bigger differences in the west branch were detected in the mass-balance year 2016–2017 (Fig. 8b, d), which may be due to an avalanche in the upper part during the summer 2017. The firn basin terrain of the west branch is very steep and is adverse to mass accumulation, which can also be validated in terms of TLS-derived glacier surface elevation changes (Fig. 4g). Thus pronounced misalignment of mass-balance elevation distribution curves between the two methods occurred. Considering the errors of estimate and in situ measurements, submergence and emergence velocities can be estimated using the TLS-derived DEMs and glaciological mass balance. The difference in mass-balance elevation distribution can be largely explained by glacier dynamic thinning at higher elevations and dynamic thickening at lower elevations.
Comparison between estimated and in situ measured vertical velocity for the mass-balance year 2015–2016 and 2016–2017; the letters represent ablation stakes (Fig. 1). Note that the summer periods and stakes in the higher elevations were not selected for comparison due to snow cover reduced the quality of in situ measured vertical velocity.
In fact, the vertical velocity of Urumqi Glacier No. 1 is small (Fig. 8). We now discuss the errors of glacier surface elevation changes versus dynamic thinning and thickening. Differences in glacier surface elevation changes derived from the TLS and glaciological measurements were close to zero for the vast majority of the ablation stakes, and corresponding errors in the differences were mostly larger than the difference themselves (Fig. 9). Compared with the errors of measurements, dynamic thinning and thickening of the glacier were minor and negligible. So Riegl VZ®-6000 TLS can be considered an effective tool to measure the mass balance of Urumqi Glacier No. 1.
Although glacier thinning and thickening were negligible, other factors such
as meteorological conditions and glacier surface terrain may cause mass-balance differences between the two methods. Figure 9 shows daily
meteorological records provided by Daxigou Meteorological Station from 25 April 2015 to 28 August 2017. Positive temperature and more than 75 % of
the annual total precipitation amount occurred during the summer months;
this probably resulted in summer mass balances that were slightly more
negative than annual ones (Table 3). Although the reduced discrepancies
between TLS-derived geodetic and glaciological mass balances fall within the
95 %, a bigger difference (
Changing differences between TLS-derived (
The differences in mass balance between the two methods were possibly related to the effect of glacier surface terrain. The presence of two minimal unscanned areas in TLS surveys is due to the flat terrain of the west branch surface (two green polygons in Fig. 5). The geodetic mass-balance calculations did not include these unscanned areas; this cloud potentially increased the difference between the two methods. Furthermore, these undetected regions located in the ablation area and higher wastage than the surroundings were observed according to glaciological measurements. This may imply that the geodetic mass balances of the west branch were more positive than the glaciological ones (Table 3), and a discrepancy in mass-balance elevation distributions of the west branch was observed at 4000–4150 m a.s.l. Nevertheless, the geodetic method is able to cover the majority of the glacier surface and take the terrain characteristics into account, whereas the glaciological measurements cannot capture all the topographic features despite a dense spatial coverage of in situ observations being applied. Furthermore, in situ observations are missing in the firn basin and glacier tongue terrain of the west branch and eastern elevations of the east branch because of the presence of precipitous terrains in these inaccessible regions (green color in Fig. 11a). The eastern elevations of the east branch are dominated by the northwest aspect, and the firn basin has aspects from north to northwest (Fig. 11b). Aspects are likely to influence the glacier surface albedo and thereby control the surface change patterns (see Yue et al., 2017).
Daily precipitation and mean air temperature observed at Daxigou Meteorological Station during 25 April 2015–28 August 2017.
Spatially distributed slope
This study presents the application of multi-temporal Riegl VZ®-6000 TLS point clouds in mass-balance monitoring of Urumqi Glacier No. 1. The long-range TLS can provide DEMs of high temporal spatial resolution and accuracy to allow more detailed insight into glacier evolution (e.g., Gabbud et al., 2015). To take advantage of this and provide more-precise glacier surface elevation changes, it is worth remembering that fixed scan positions are highly important between consecutive scans when using our approach. We should also note that not all glaciers in China are as easily accessible as Urumqi Glacier No. 1. For many large glaciers, it is not always easy to fix scan positions using reinforced concrete with a standard GNSS-leveling point, but we can mark stable bedrock outcrop as a scan site. Another advantage of this type of TLS is the long scanning range, and such an instrument could allow most of the glacier surface to be scanned from one or several scan positions, especially for remote and inaccessible glacier areas (e.g., crevasses, steep ice, debris cover). Therefore the instrument provides a quantitative evolution in spatial coverage compared to glaciological in situ measurements, which can be seen as a beneficial complement to glaciological mass balance, particularly for calibrating inaccessible areas. TLS surveys can also provide updated glacier boundary and surface DEMs. In addition, we can paste several retro-reflective targets (e.g., reflective foils, corner cube reflectors, and retro-reflective paintings) to the surface of each stake and the targets can be easily surveyed and identified since each of them has a high directivity of the reflected laser radiation; then the location of stakes can be determined. All of these parameters are favorable for glaciological mass-balance calculations. A combination of glaciological and TLS observations may yield optimum results. TLS-derived geodetic results can validate the distributed glacier mass-balance models as the TLS can provide measurements of high spatial and temporal resolution, especially in the strong ablation season. The instrument can be used to investigate daily or sub-daily ablation (e.g., Haut Glacier d'Arolla, Switzerland; Gabbud et al., 2015), which can completely meet the requirements of time resolution for glacier mass-balance models.
One drawback of the TLS surveys is the presence of data voids (unscanned areas), even for very small glaciers (e.g., Fischer et al., 2016). This is due to limited scanning angle and complex glacial terrain. An emerging low-cost unmanned aerial vehicle (UAV) has the potential to avoid data voids in glaciological monitoring with the good surveying angle of UAV. Immerzeel et al. (2014) showed that UAV combined with a structure from motion (SFM) workflow provide a powerful tool for monitoring mass balance and surface velocity of a Himalayan glacier with high spatial accuracy. From our field experiment at Urumqi Glacier No. 1, rarefied air and frequent blustery wind around glaciers usually reduce the power of UAV, and rock outcrops result in difficult operations of such instruments. Hence we mainly consider using UAV to survey unscanned area. Integration of UAV- and TLS-acquired data can provide the whole glacier surface terrain of interest. Other technology such as terrestrial photogrammetry also has the ability to estimate mass balance, and the quality of photogrammetric estimation is similar to the quality of TLS (e.g., Piermattei et al., 2015; Fugazza et al., 2018). However, the reliability of UAV and terrestrial photogrammetry in glacial environments is more dependent on the natural features (i.e., characteristic image objects) of the surveyed surfaces compared with TLS. The cost of TLS is higher than UAV and ground-based photogrammetric surveys.
From our experience, the monitoring tool is potentially applicable to other
glaciers provided that these glaciers have a small to medium size and relatively
steep terrain. According to the second Chinese glacier inventory (Guo et
al., 2015),
Spatial distribution of suitable glaciers: in theory those
glaciers with an area of
Nevertheless, TLS measurements and point cloud data post-processing are
challenges for a broader application. One disadvantage of the TLS is that it
requires specific knowledge, skills, and experience for its use and data
processing. Other limitations of the TLS are related to suitable scan
positions for obtaining good visual angles of the glacier surface and stable
scan positions for multi-temporal registration of repeated scans for change
detection. In addition, the uncertainties of density conversion still remain
at seasonal and annual scales as in-situ-measured densities of all benchmark
sites are difficult to obtain (very few glaciers in China have as
detailed of observations as Urumqi Glacier No. 1). A day with little snow in the
accumulation area and no snow in the ablation area (i.e., snow line is
clearly distinguished) should be chosen to perform TLS measurements. We may
use a built-in camera of the TLS to create high-resolution panorama images
of a glacier (RIEGL Laser Measurement Systems, 2014a). Then firn–snow and
bare ice areas (i.e., snow line) can be determined (e.g., Barandun et al.,
2018). An area-weighting approach can be used to estimate density because the
lack of in-situ-measured densities makes the volume-weighting approach difficult
to extensively use. A density assumption over time intervals (
Urumqi Glacier No. 1 is one of the reference glaciers in the WGMS network, a representative glacier in central Asia and the best-monitored glacier in China. Here, for the first time, we have presented the potential of a novel long-range TLS to monitor annual and intra-annual geodetic mass balances of the glacier. The Riegl VZ®-6000 TLS has a long scan range up to 6 km and is exceptionally well suited for measuring snowy and icy terrain in glacier mapping. We use TLS-derived DEMs to calculate summer and annual surface elevation changes and geodetic mass balances of the glacier for 2 consecutive years (2015–2017) and to delineate accurate glacier boundaries.
Our analysis suggests that Urumqi Glacier No. 1 has experienced pronounced
thinning and mass loss for the four investigated periods. Glacier surface
elevation lowering and mass loss during the summer were slightly greater
than annual values. Glacier-wide geodetic mass balance in the mass-balance
year 2015–2016 was
Despite uncertainties inherent in TLS-derived geodetic mass balances, our
results show that the TLS device yields reliable results and is therefore
well suited to the study of Urumqi Glacier No. 1 since the observed vertical
velocity component is small. Furthermore, the TLS can provide accurate and
detailed information on glacier area and mass-balance changes, and its
temporal–spatial resolution allows more detailed insight into the glacier's
evolution. The greatest strength of the TLS is the long-range scanning, which
allows most of the glacier surface to be measured, including areas that are
inaccessible for in situ measurements. Use of the TLS-based geodetic method
will be an important development since it is clearly a beneficial complement
to direct glaciological mass balance, particularly for calibrating the
unmeasured areas and validating the distributed glacier mass-balance models.
A combination of glaciological and TLS observations may yield the optimum
results. Moreover, the TLS has application potential for glacier
mass-balance monitoring in western China as most glaciers (
Glaciological mass balance data related to this study are submitted to the WGMS and be available at the following website:
CX and ZL designed this study. HL and FW assisted with the analysis and calculated glaciological mass balance. PZ led the field work. CX conducted the TLS processing and analysis and wrote the paper with contributions from all co-authors.
The authors declare that they have no conflict of interest.
The authors are very grateful to the staff from Tien Shan Glaciological Station, Chinese Academy of Sciences, for the continuous field observations. Additionally, the authors would like to thank the editor Tobias Bolch and referees for their numerous invaluable comments in improving the paper.
This research has been supported by the Strategic Priority Research Program of Chinese Academy of Sciences (grant nos. XDA20020102 and XDA20060201), the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (grant no. 2019QZKK0201), National Natural Science Foundation of China (International cooperation and exchange projects) (grant no. 41761134093), State Key Laboratory of Cryospheric Science (grant no. SKLCS-ZZ-2019), and National Natural Science Foundation of China (grant nos. 41471058 and 41771081). Huilin Li also acknowledges the funding received from Key Research Program of Frontier Sciences of Chinese Academy of Sciences (grant no. QYZDB-SSW-SYS024).
This paper was edited by Tobias Bolch and reviewed by Miriam Jackson and two anonymous referees.