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Article

Characteristics of Glaciers Surging in the Western Pamirs

by
Zhenfeng Wang
1,
Zongli Jiang
1,*,
Kunpeng Wu
2,
Shiyin Liu
2,
Yong Zhang
3,
Xin Wang
1,
Zhen Zhang
4 and
Junfeng Wei
1
1
School of Earth Sciences and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
2
Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650091, China
3
School of Resource Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
4
School of Spatial Information and Mapping Engineering, Anhui University of Science and Technology, Huainan 232001, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(5), 1319; https://doi.org/10.3390/rs15051319
Submission received: 14 December 2022 / Revised: 14 February 2023 / Accepted: 24 February 2023 / Published: 27 February 2023
(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)
Browse Figures
Versions Notes

Abstract

:
The regional surge patterns and control mechanisms for glaciers in the western Pamirs are unclear. Using remote sensing, more surge-type glaciers have been discovered in the western Pamirs. This provides an opportunity to obtain the integral characteristics of glacier surging. Using Sentinel-1A, TSX/TDX and Landsat remote sensing data, the changes in surface velocity, surface elevation and surface features of five glaciers that have recently surged in the western Pamirs are obtained. The results show that (1) all glacier surges initiate gradually for several years and most form a surge front in the upper region of the glacier. (2) For most glaciers, the active phase of the surge is more than 2 years, except for one that is within several months. (3) The peak velocity mostly occurs in summer and autumn, and the maximum velocity is less than 8 m d−1. (4) There is sharp deceleration, such as the hydrologic controlled surge at the end of the surge. However, the surface flow of the transverse profiles shows no features of base sliding. Based on the comparison of surge patterns with other regions in High Mountain Asia, we conclude that the surging glaciers in the western Pamirs are triggered by thermal mechanisms under the control of sub-hydrological modulation.

1. Introduction

Glacier surges are a periodic movement alternating between short rapid flow (months to years) and long-term slow flow or stagnation (decades to hundreds of years) [1,2]. During the active phase of a typical glacial surge, a large number of glacier masses migrate rapidly from the upstream reservoir area to the downstream receiving area, resulting in dramatic changes in the glacial surface elevation, and sometimes leading to the advance of glacier terminus [3,4,5,6]. Due to the rapid transmission of a significant volume of ice masses downstream during the surge period, the glacial surge may cause a series of natural disasters such as glacial debris flow, glacier lake outburst flood (GLOF) and glacier blocked lake, which pose a major threat to the downstream area [7,8,9,10,11]. In this context, understanding the process and mechanisms of glacial surge is of great significance to predict and reduce the disasters caused by glacier surge.
Although surge-type glaciers account for only 1% of glaciers worldwide, there are reports of surge phenomena in major glacial regions around the world [12], such as Alaska, Canada, Svalbard, Iceland, the Andes, Greenland and High Mountain Asia (HMA) [13,14,15,16,17,18]. HMA is the largest concentration of glaciers on earth outside of the polar regions. Under the background of global warming, HMA glaciers have experienced negative material balance [19]. However, the Pamirs and the Karakoram have attracted much attention due to their abnormal slightly positive mass balance and large number of surge-type glaciers [20,21,22,23]. Compared with the glaciers in the Pamirs, the study of glacier surge in the Karakoram region is more extensive. These studies show that the glacial surge in the Karakoram region is triggered by thermal or subglacial hydrological conditions [5,24]. Due to their different thermal, hydrological conditions and morphological characteristics, the control mechanisms of glacier surges are heterogeneous [11]. In addition, topographic factors may also play an important role [24].
Due to the harsh environment and the suddenness of glacier surge, field measurements are very challenging tasks to perform. However, the wide application of remote sensing technology makes the identification and research of surge-type glaciers more convenient. The changes in surface elevation and velocity can be obtained by using time-series remote sensing images [3], so as to better understand the transportation of glacier mass during the process of surging. Glacier velocity is derived using cross-correlation feature tracking of either optical images or synthetic aperture radar (SAR) images, or radar differential interferometry. Since SAR image pairs are easy to be incoherent in complex terrain, it is difficult to obtain glacier velocity effectively using differential interferometry. Optical imagery, although a large archive of historical images, is susceptible to clouds and snow, especially in winter, making it difficult to obtain time-series glacier velocity data. Therefore, The SAR offset tracking method is more suitable as it is not affected by clouds and snow.
The current research of Pamir surge-type glaciers is limited to local areas or specific glaciers. For example, the Karayaylak Glacier in the eastern Pamirs surged in May 2015 [25] and destroyed a large number of pastures and herdsmen’s houses, which has attracted extensive attention of the media and scholars. This event led researchers to focusing on other surge-type glaciers in the eastern Pamirs [26]. To date, only the Medvezhiy and Bivachny glaciers in the western Pamirs have been studied in details [27,28]. These researches showed that these two glaciers underwent a surge for more than ten years and are considered to be sub-glacier hydrologically controlled. In addition, there are few other English literatures on the study of single glacial surge in the western Pamirs [11]. The study of the western Pamirs surging glacier is mostly limited to the inventory and report of surge-type glaciers, and surge control mechanisms still need to be well-understood for glacier catastrophic events prediction.
In this paper, relatively detailed surface velocities derived from Sentinel-1A imagery for five Pamir glaciers during recent surge were analyzed. Combined with the elevation change data during the surge, the characteristics of these glaciers surging were summarized, and the possible surge control mechanisms were concluded. Overall, the work has important implications for understanding the mechanisms controlling glacier surges in the region and will provide data support for us to better clarify the heterogeneity of glacier surge in HMA.

2. Study Area

The Pamir Plateau covers southeast Tajikistan, northeast Afghanistan and southwest Xinjiang. The Pamir Plateau can be divided into two parts, the eastern and western, with the Sarekool ridge as the boundary. A series of parallel mountains in the southeast–northwest are developed in the western Pamirs, so that the humid westerly can bring rich precipitation, and a number of mountain glaciers are developed in this region. Most glaciers in the western Pamirs are accumulated in winter due to the winter and spring precipitation because of the impact of the westerly. The Vanchdara Glacier and Shocalscogo Glacier are the two tributaries of the Garmo Glacier; the Koman Glacier is a small glacier with large accumulation areas, while the Gando Glacier and Sugran Glacier are large compound valley glaciers (Figure 1). The Gando Glacier has experienced several repeated surges revealed by the distorted moraine in the glacier trunk. Table 1 and Figure 2 show the recent surge glaciers and the timeline of surge events.

3. Data and Methods

3.1. Data Sources

Sentinel-1A was launched by ESA in April 2014 and with a C-band SAR sensor onboard. It has the characteristics of global acquisition, relatively short revisit cycle (12 days) and middle spatial resolution (https://search.asf.alaska.edu, accessed on 10 November 2022). Sentinel-1A images from 2014 to 2022 were used to estimate the surface velocity variation of the glacier in the western Pamirs.
TerraSAR-X/TanDEM-X (TSX/TDX) is a single-orbit, single-antenna, dual-satellite distributed system, consisting of two X-band SAR satellites launched by the Deutsches Zentrum für Luft- und Raumfahrt (DLR). In this bistatic imaging mode, the system can simultaneously collect the master-slave images of the interference pair, which has the characteristics of “0-time baseline”. In addition, SRTM DEM 30 m were also used for geo-code SAR imagery.
Landsat 8 OLI images were used to analyze the changes of the glacier medial moraines and the terminus. All of the Landsat images are freely distributed by the United States Geological Survey (USGS) Earth Explorer (http://earthexplorer.usgs.gov, accessed on 10 November 2022). The details of datasets used is given in Table 2.
[ICESat-2/ATLAS 06 elevations were also used to evaluate the surface elevation changes for Garmo Glacier and Koman Glacier due to the lack of DEM data during the active phase of the surging].

3.2. Estimation of Glacier Surface Velocity

Offset tracking technique using normalized cross-correlation as an alternative to D-InSAR was introduced to overcome the limitations of rapid and incoherent flow [32]. Offset tracking is divided into intensity tracking and coherence tracking, with lower accuracy than interferometry, but can provide the range and azimuth offsets between two SAR images. In this study, we applied intensity offset tracking of SAR image pairs to derive offset fields. The offset tracking procedure within GAMMA interferometry software is robust and used to estimate the offset of the Sentinel-1A image pair [33]. The processing steps included (Figure 3): The first step is to organize the images in pairs, where the previously acquired image is used as the reference image and the other as the secondary image. The master and slave images are track-corrected using precise track parameters to eliminate the initial offset errors between the images. After applying the orbital data to the acquired images, the master and slave images are co-registered with the help of SRTM-C DEM. Then, executing the offset tracking module, a patch window of 256 × 128 single-look pixels is applied in the range and orientation directions, a step size of 40 × 8 pixels is used during the offset tracking procedure and pixels with unreliable offset values by a signal-to-noise ratio threshold of 4.0 are discarded. After that, the SRTM-C DEM is employed for geocoding and calculating the velocity maps of glaciers. Finally, a median low-pass filter (5 × 5 pixels) is used to eliminate individual outliers [34].
The uncertainty of glacier velocity obtained by SAR offset tracking technology mainly comes from image registration error, uncertainty of image offset estimation and ionospheric error [3,34]. In order to evaluate the uncertainty of glacier surface velocity, it is usually assumed that the non-glacier flat area is a stable area, and the stable area contains all the above error sources, so the residual displacement of non-glacier area is used to evaluate the error of glacier velocity results [35]. The mean velocity and standard deviation of the non-glacier flat area were collected and used to calculate the uncertainty of the Sentinel-1A image pair, and the results are shown in Figure 4. The uncertainty is much smaller than the flow velocity during the surge phase.

3.3. Surface Elevation Changes

Based on Differential Synthetic Aperture Radar Interferometry (D-InSAR), the glacier elevation changes during 2000–2014, 2000–2017 and 2000–2020 were obtained by using TerraSAR-X/TanDEM-X (TSX/TDX) image pairs and SRTM DEM. Firstly, the topographical phase was simulated by SRTM DEM, and then the residual phase of glacier elevation change was obtained by removing the flat land and terrain phase from the TSX/TDX bistatic interferogram [36]. Finally, the glacier surface elevation change was obtained by generating the interferogram by using the residual phase [37]. The TSX/TDX DEM can be obtained by superimposing the elevation difference on the co-registered SRTM DEM. The flowchart of this approach is outlined in Figure 5.
The changes of glacier surface elevation were estimated by calculating the DEM difference acquired at different times. Since different DEMs were obtained from different sensors and orientation procedures, their geolocation accuracy may not be consistent, and, in addition, on steep slopes in high mountain areas, small horizontal offsets can lead to significant elevation deviations [38]. Therefore, the DEMs must be co-registered before the calculation. The co-registration method proposed by Nuth et al. [39] can correct relative horizontal and vertical shifts between two DEMs based on the cosinusoidal relationship between elevation difference, slope and aspect in non-glacier regions.
Since the images were acquired in similar seasons, the effects of seasonal penetration change can be negligible. However, the penetration depth of radar signal into snow and ice should be considered. The difference between X-band and C-band SRTM DEM obtained at the same time in this area should be carried out, and the average penetration depth of SRTM-C was calculated to be about 2 m [40].
The uncertainty in elevation changes between DEMs was estimated using the normalized median absolute deviation (NMAD) of the non-glacial stable areas, which is an indicator insensitive to outliers. The NMAD was computed through the following formula:
N M A D = 1.4826 × m e d i a n x i − x ˜
where x i is the elevation difference observation and x ˜ is the median of the elevational difference observation. The results are shown in Table 3.

4. Results

In this section, we describe the main changes in glacier surface elevation, velocity and ice-surface morphology through each surge event (Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10).

4.1. Sugran Glacier

Before 2014, surface elevation of the Sugran Glacier increased slightly at 6.8 km from the terminus, and decreased significantly in the rest of the centerlines (Figure 7a and Figure 9a). Mini surges were observed in the upstream of the Sugran Glacier between 2014 and 2017 (Figure 6a′), and they contributed to the surface elevation increasing in most low reservoir areas (Figure 7b and Figure 9a). The peak velocity of the surge emerged in May 2020, and the flow velocity was relatively high in the autumn of 2020 and the beginning of the summer of 2021. This coincided with the surface elevation, which increased in glacier tongue between 2017 and 2020 (Figure 7c and Figure 9a). There was a sharp slowdown in surface velocity in the mid-summer of 2021, and then acceleration emerged again from October 2021. Another peak velocity occurred in the July of 2022, and then sharply decreased again, flowing in a gradually slowing-down flow for a couple of months. Finally, it returned to a normal state. The rapid movement in active phase lasted for about two and a half years (Figure 6a,a′). The surging front advanced several kilometers and distorted the west tributary (Figure 10a).

4.2. Gando Glacier

It can be observed that relatively high surface velocity existed in the reservoir area of the south tributary of the Gando Glacier from October of 2014 to October of 2018. In this slow acceleration stage, the flow velocity was relatively high in summer and autumn, but low in winter and spring. The acceleration phase lasted for about 4 years, and the flow velocity began to increase significantly in the winter of 2018. The peak velocity during the surge mostly appeared in November of 2018, 2019 and 2020, and then slowed down in winter and spring. This active phase lasted until May of 2021, and then the flow velocity began to decline dramatically and gradually, returning to the normal (Figure 6b,b′). The elevation changing pattern of the main trunk of the Gando Glacier from 2000 to 2014 indicates that the trunk surged (Figure 7a and Figure 9b). Between 2014 and 2017, the main trunk of the glacier entered the quiescent stage, the surface elevation of the receiving area continued to decrease, and the surface elevation of the reservoir area of the south tributary was increasing.
The surge front of the southern tributary of the Gando Glacier advanced about 7 km during the surging, but its morphological front only advanced 3 km (Figure 10b). The distance of the morphological front advance was much lower than that of the surging front.

4.3. Garmo Glacier

The trunk of the Garmo Glacier surged before March of 2014 as the glacier tongue increased apparently and decreased in upper stream (Figure 7a). Between 2014 and 2017, the surface elevation of the tongue in the Garmo Glacier trunk decreased, and that of the upper stream clearly increased (Figure 7b and Figure 9c). From 2017 to 2020, a bulge formed in most low reservoir areas (Figure 7c and Figure 9c). Due to the limited data of ICESat-2/ATLAS, only four tracks covered the glacier trunk during the surge, indicating that the bulge flowed downward between 2020 and 2022 (Figure 7d and Figure 9c). Meanwhile, from May of 2022, surface velocity increased dramatically to the peak (8 m d−1) in the summer of 2022, and then rapidly decreased to about 3 m d−1. Finally, the surface velocity dropped to a lower level (<1 m d−1) by the end of November 2022 (Figure 6c′). The active phase of the surging lasted for about half a year after many years of acceleration in the up-stream. The dramatic drop in surface velocities was probably controlled by sub-glacier hydrological conditions.

4.4. Shocalscogo Glacier

The Shocalscogo Glacier is a tributary of the Garmo Glacier, which is still connected to the trunk (Figure 1). The thickened surface in the reservoir area and the thinned surface in the receiving area (Figure 7a and Figure 9d) were clearly seen between 2000 and 2014, while the contrastive phenomenon was found between 2014 and 2017 (Figure 7b). This indicates that the Shocalscogo Glacier surged, accompanying the glacier mass transferred downstream (Figure 7b and Figure 9d). The terminus of the tributary still thickened between 2017 and 2020 (Figure 7b and Figure 9d), suggesting that the bulge still slid downward. Figure 6d shows that the surface velocity time series dramatically dropped in the summer of 2017, which indicates that the release of sub-glacier water caused this sharp slowdown.

4.5. Vanchdara Glacier

The Vanchdara Glacier was probably a tributary of the Garmo Glacier, and now is disconnected from the Garmo Glacier. However, melt water from the Vanchdara Glacier may pour into the glacier bed. For the present, it is hard to evaluate the impact of the melting water on the Garmo Glacier trunk.
Between 2000 and 2014, the surface elevations of the Vanchdara Glacier in mid-part increased significantly, indicating the glacier mass transferred from the upper stream. Additionally, the surface elevation of the lowest tributary increased (Figure 7a and Figure 9e). Between 2014 and 2017, the surface elevation of the mid-part decreased by about 48 m on average, and that of the glacier tongue increased significantly, with a maximum increase of up to 143 m (Figure 7b and Figure 9e). Between 2017 and 2020, the tongue of the Vanchdara Glacier thinned while the up-region increased (Figure 7c and Figure 9e). The surface velocity time series indicates that the velocity accelerated gradually from up-stream, which is consistent with the glacier mass transferred from the reservoir area to receiving area (Figure 6e).

4.6. Koman Glacier

The surge of the Koman Glacier began in the summer of 2019 (Figure 6f,f′). After a year of slow acceleration, the flow velocity reached its maximum in July 2020, and the peak velocity was eight times more than that in quiescent. Subsequently, the flow rate slowed down, but this deceleration lasted for only one month. The flow rate gradually recovered the peak in September, and then maintained a high flow rate until December of 2021. The speed increased slightly in July 2021, but it has not been maintained for a long time. It took 13 years for the Koman Glacier to form a bulge in the lower reservoir area and 5 years to transfer glacier mass to the glacier tongue (Figure 8a–c and Figure 9f). The surge of the Koman Glacier has also caused significant changes in the surface of the main trunk, but the main trunk is still covered by a large amount of debris (Figure 10f).
The surge front is clearly observed in the flow velocity figures of the Vanchdara Glacier, Shocalscogo Glacier, Koman Glacier and Gando Glacier, while a distinct front is not observed at the Sugran Glacier. The surge front of the Vanchdara Glacier and Shocalscogo Glacier advanced from upstream to the terminus of the glacier, the morphological front of the two glaciers also advanced to some degree (Figure 7) and the terminus of the Shocalscogo Glacier advanced into the main trunk of Garmo Glacier. During 3 years of slow surging the significant mass transfer from upstream to downstream was completed (Figure 7d).

5. Discussion

Although the five surging glaciers are different in sizes and shapes, they are found to be similar in surface flow velocity variations. The peak velocities of these glaciers are not bigger than 8 m d−1 during the active phase of the surging, with most of the peak velocity in summer and autumn. There are no obvious seasonal variations in the initiation and termination of these glaciers surging, and the active phases of the glacier surge are more than 2 years, except for the trunk of the Garmo Glacier, whose active phase lasted about half a year. These features suggest that these glaciers surging in the western Pamirs may be under thermal control rather than hydrological control. Previous studies have shown that hydrologically controlled surges lead to ice instability, which is mainly due to the changes in subglacial pore water pressure, usually accompanied by a reorganization of subglacial drainage channels [16].The sub-hydrological control surge usually starts in winter when meltwater is scarce and the subglacial hydrological system is inefficient, and ends in summer when drainage efficiency is high [41] and the flow velocity changes sharply [26], especially in the termination phase. However, thermal-controlled surges can start or end in any season [35]. Such surges are mainly caused by the continuous accumulation of glacial mass that causes rising temperatures at the bottom of the glacier to reach the pressure melting point, and the increase in hydrostatic pressure at the bottom of the glacier causes the bottom to slip rapidly [23]. As the transition from cold base to warm base is relatively slow, the duration of thermal controlled surges may last from several years to more than ten years, and the acceleration stage at the beginning and deceleration stage at the end of the surge may be as long as several years [42].
The results of elevation changes show that during the quiescence stage, the surface elevation of these glacier reservoir areas increases significantly, while the surface elevation of the receiving area decreases dramatically; this is considered to be the key prerequisite for glacier movement by the theory of rate and state of friction [3,43]. Before the active phase, a dramatic increasing of the surface elevation leads to the formation of a bulge in most low reservoir areas. The glacier started to surge after the excess of longitudinal stress threshold. During the active stage, a large number of glacier masses were transferred from the reservoir area to the receiving area to maintain high surface velocities. Figure 7 shows the Gando Glacier and the Sugran Glacier at the ”interim phase” in 2014, with the upper part of the reservoir area gradually thinning and the lower part thickening. Combining the flow velocity of the Gando Glacier and the Sugran Glacier, it can be found that the mass was transferred from the glacier upstream to downstream, which is consistent with the acceleration of the glacier surface velocity. This redistribution of ice mass and the corresponding increase in flow velocity led to an increase in ice strain rate. The increase in strain rate makes the bottom of the glacier gradually reach the melting point, and as the accumulation mass in the reservoir area increases to the critical point, finally triggering glacier surge [32]. This suggests that these glaciers’ surging are triggered by sub-glacier thermal conditions.
Due to the redistribution of glacier mass, glacier surge may cause terminus advance, but most terminus advance occurs on shorter glaciers. For some large glaciers, the surge is mostly confined to the inside of them and does not cause terminus advance [28]. In this study, the surge of the Vanchdara Glacier and the Shocalscogo Glacier showed a substantial advance of terminus, and the terminus of the Shocalscogo Glacier advanced into the main trunk of the Garmo Glacier (Figure 10d,e). The terminus of the southern tributary of the Gando Glacier also advanced to the main trunk and squeezed the main trunk downstream during the surging (Figure 10b). The surging of the Koman Glacier was limited to the middle and upper reaches of the glacier, and it could be observed from Landsat OLI images that the moraine advanced a little to the downstream (Figure 10f). Moraines in the tongue of the Sugran and Garmo Glaciers were also advancing downstream. Combined with the profile velocity data of these glaciers (Figure 6a″–f″), it is believed that the basal part of the tongues may be frozen and the advancement distance may be inhibited. Reference [24] found that the surging of the Braldu Glacier and the Kunyang Glacier was also akin to this phenomenon.
Previous studies have shown that a downward-propagating surge front can be found in many surging processes [24], such as that of the Kunyang Glacier [41] and the Gasherbrum Glacier [44]. It is believed that the surge front is the result of changes in hydrologic and thermal conditions within the glaciers. The hydrologically controlled surge front represents the boundary between the inefficiently conjoined cavity system in the upper part of the glacier and the efficient drainage system in the lower part of the glacier [45], while the thermally controlled surge front represents the boundary between the upper warm ice and the lower cold ice [46]. In our study, only the Sugran Glacier did not show the occurrence of the surge front, which may be due to the fact that the thermal activation wave was faster than the ice flow, so the speed was suppressed by thermal control and no surge front was generated [47,48]. The surge front of the south tributary of the Gando Glacier advanced about 7 km during the surging, but its morphological front only advanced about 3 km, far below the advancing distance of the leaping front. This situation has been observed in the Medvezhiy Glacier [49].
Glacier surge is a quasi-periodic movement. If the interval of two or more active phases of glacier surge can be obtained, the surge cycle can be estimated [50], which can provide certain help for predicting glacier surge in the future [42]. However, the time spent for our data set is limited and cannot provide the recurrence period of these glaciers. Combined with previously published data sets and current research results, we conclude that the recurrence period of the Sugran Glacier is about 18–26 years, the recurrence period of the Gando Glacier is about 33 years, and the recurrence period of the other three glaciers cannot be determined for now (Table 1). Previous studies have shown that the Pamir and Karakoram surge-type glaciers have a repeat period of 11~40 a. The Sugran Glacier and the Gando Glacier are consistent with this conclusion.

6. Conclusions

Sentinel-1A, TSX/TDX, Landsat and multi-source remote sensing data were employed to obtain the changes of glacier surface elevation, surface velocity and surface morphology of five glaciers in the western Pamirs that have recently experienced surging, and finally to investigate the evolution and mechanism of glacier surging processes. The results indicate that: (1) the active phases of most of these glaciers are more than 2 years, except for the trunk of the Garmo Glacier, whose active phase lasted about a few months, and there is no obvious seasonality in the starting and ending stages. (2) Most of the peak velocity during the surge occurs in summer and autumn, and the peak velocity is less than 5 m d−1, except for the Garmo Glacier, which has a maximum speed of about 8 m d−1. The surging occurs after many years of acceleration, and the slowdowns are relatively shorter. (3) For the surging of small glaciers, the glacier surging front may have impact on the whole glacier, resulting in the advance of the terminus to some degree. This evidence suggests that the recent glacial surging in the western Pamirs is mainly controlled by sub-glacier thermal conditions and is regulated by sub-glacier hydrology conditions. Additionally, it is interesting that the aspects of the recent surging glaciers are mostly northwestern, except for the trunk of the Garmo Glacier.

Author Contributions

Conceptualization, Z.W. and Z.J.; methodology, Z.J.; software, K.W.; validation, Z.W. and Z.J.; formal analysis, Z.W.; data curation, Z.J.; writing—original draft preparation, Z.W.; writing—review and editing, Z.J., Y.Z., X.W., Z.Z., J.W. and K.W.; visualization, Z.W. and K.W.; supervision, S.L.; project administration, Z.J., Y.Z., Z.Z. and X.W.; funding acquisition, Z.J., Y.Z., Z.Z. and X.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Science and Technology (Grant No. 2018YFE0100100) and the National Natural Science Foundation of China (Grant No.41471067, 42071085, 42171134 and 42171137) and The Natural Science Foundation of Hunan Province (Grant No. 2022JJ30243 and 2021JJ30247).

Data Availability Statement

Not applicable.

Acknowledgments

The authors thank the following institutions for providing materials for this study: USGS for Landsat series images and SRTM DEM; the European Space Agency (ESA) for Sentinel-1 images; TerraSAR-X/TanDEM AO (DLR AO (syl_cas_XTI_LAND6642).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The location and extent of the five surging glaciers, Sugran Gl., Gando Gl., Garmo Gl. and its tributary Shocalscogo Gl., Vanchdara Gl. and Koman Gl. (a) Location of the study area in the Pamirs. (b) Boundaries and glacial centerlines of four surging glaciers (the background is Landsat OLI images, 654 composite, 27 September 2021). (c) Boundaries and glacial centerlines of Koman Gl. (the background is Landsat OLI images, 543 composite, 14 September 2022). Black and white lines (glacial centerlines) mark the distance from the terminus position in kilometers, plotted at 2 km intervals.
Figure 1. The location and extent of the five surging glaciers, Sugran Gl., Gando Gl., Garmo Gl. and its tributary Shocalscogo Gl., Vanchdara Gl. and Koman Gl. (a) Location of the study area in the Pamirs. (b) Boundaries and glacial centerlines of four surging glaciers (the background is Landsat OLI images, 654 composite, 27 September 2021). (c) Boundaries and glacial centerlines of Koman Gl. (the background is Landsat OLI images, 543 composite, 14 September 2022). Black and white lines (glacial centerlines) mark the distance from the terminus position in kilometers, plotted at 2 km intervals.
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Figure 2. Duration of the surges of the surging glaciers documented in this study.
Figure 2. Duration of the surges of the surging glaciers documented in this study.
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Figure 3. The flowchart of glacier velocity measurement.
Figure 3. The flowchart of glacier velocity measurement.
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Figure 4. Velocity in non-glacier flat area.
Figure 4. Velocity in non-glacier flat area.
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Figure 5. The flowchart of generating TSX/TDX DEM.
Figure 5. The flowchart of generating TSX/TDX DEM.
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Figure 6. Spatial-temporal changes of surface velocities along the centerlines (see Figure 1). Annual and time series of surface velocity of these glaciers are labeled with letters, (a,a′) Sugran Gl.; (b,b′) Gando Gl., (c,c′) Garmo Gl. trunk, (d,d′) Shocalscogo Gl. (tributary), (e,e′) Vanchdara Gl., (f,f′) Koman Gl., respectively. Figures of temporal changes of surface velocities along transverse profiles are labeled with (a″–f″) (for transverse profiles see red lines in Figure 1).
Figure 6. Spatial-temporal changes of surface velocities along the centerlines (see Figure 1). Annual and time series of surface velocity of these glaciers are labeled with letters, (a,a′) Sugran Gl.; (b,b′) Gando Gl., (c,c′) Garmo Gl. trunk, (d,d′) Shocalscogo Gl. (tributary), (e,e′) Vanchdara Gl., (f,f′) Koman Gl., respectively. Figures of temporal changes of surface velocities along transverse profiles are labeled with (a″–f″) (for transverse profiles see red lines in Figure 1).
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Figure 7. Surface elevation changes of four surging glaciers (Sugran Gl., Gando Gl., Garmo Gl. and its tributary Shocalscogo, Vanchdara Gl.). (a) 2000/02−2014/03, (b) 2014/03−2017/02, (c) 2017/02−2020/04, ICESat-2/ATLAS track GT1 (GT2) and GT3 (GT4) were obtained on 25 April 2022 and24 May 2022, respectively. (d) Elevation difference between ICESat-2/ATLAS and TSX/TDX (2020/04).
Figure 7. Surface elevation changes of four surging glaciers (Sugran Gl., Gando Gl., Garmo Gl. and its tributary Shocalscogo, Vanchdara Gl.). (a) 2000/02−2014/03, (b) 2014/03−2017/02, (c) 2017/02−2020/04, ICESat-2/ATLAS track GT1 (GT2) and GT3 (GT4) were obtained on 25 April 2022 and24 May 2022, respectively. (d) Elevation difference between ICESat-2/ATLAS and TSX/TDX (2020/04).
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Figure 8. Surface elevation changes of Koman Gl., (a) 2000/02−2013/01, (b) 2013/01−2020/01, ICESat-2/ATLAS track GT1 and GT2 were obtained on 17 December 2021 and19 February 2022, respectively. (c) Elevation difference between ICESat-2/ATLAS and TSX/TDX (2020/01).
Figure 8. Surface elevation changes of Koman Gl., (a) 2000/02−2013/01, (b) 2013/01−2020/01, ICESat-2/ATLAS track GT1 and GT2 were obtained on 17 December 2021 and19 February 2022, respectively. (c) Elevation difference between ICESat-2/ATLAS and TSX/TDX (2020/01).
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Figure 9. Surface elevation change along the centerlines (see Figure 1) for five surging glaciers. (a) Sugran Gl., (b) Gando Gl., (c) Garmo Gl. and its tributary (d) Shocalscogo Gl., (e) Vanchdara Gl. and (f) Koman Gl.
Figure 9. Surface elevation change along the centerlines (see Figure 1) for five surging glaciers. (a) Sugran Gl., (b) Gando Gl., (c) Garmo Gl. and its tributary (d) Shocalscogo Gl., (e) Vanchdara Gl. and (f) Koman Gl.
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Figure 10. Terminus and debris-cover change before and after the surge of, (a) Sugran Gl., (b) Gando Gl., (c) Garmo Gl. and its tributary (d) Shocalscogo Gl., (e) Vanchdara Gl. and (f) Koman Gl. The results are derived from Landsat OLI.
Figure 10. Terminus and debris-cover change before and after the surge of, (a) Sugran Gl., (b) Gando Gl., (c) Garmo Gl. and its tributary (d) Shocalscogo Gl., (e) Vanchdara Gl. and (f) Koman Gl. The results are derived from Landsat OLI.
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Table
Table 1. Surging glaciers in the western Pamirs during 2014–2022.
Table 1. Surging glaciers in the western Pamirs during 2014–2022.
Glacier NameLatitudeLongitudeZmin/Zmax (m)Area (km2)Asp_mean [29]Years of Surges [30,31]
Sugran38.93871.7433146/671741.072971976–1980
2002–2005
Gando38.87671.8293465/671452.922931985–1991
Garmo38.75771.9402976/6712104.32308Unknown
Shocalscogo 138.76971.9823637/596925.06304Unknown
Vanchdara38.75671.9573708/557916.233181977–1980
Koman39.36172.7923679/672519.930Unknown
1 Shocalscogo Glacier is a tributary of Garmo Glacier.
Table
Table 2. Remote sensing datasets used in this study.
Table 2. Remote sensing datasets used in this study.
SourceTime RangePixel Size (m)Use
TSX/TDX2013/01
2014/03
2017/02
2020/01
2020/04		10Estimation of glacier elevation change
SRTM2000/0230Estimation of glacier elevation change
Sentinel-1A2014/11–2022/105 × 20Estimation of glacier surface velocity
Landsat 8/OLI2014–202215Visualization of glacier surface morphology
Table
Table 3. Remote sensing datasets used in this study.
Table 3. Remote sensing datasets used in this study.
PeriodMeanSTDNMAD
2000–20130.690.880.74
2000–2014−0.021.311.40
2013–20200.030.921.01
2014–2017−0.770.80.77
2017–2020−0.230.650.72
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Wang, Z.; Jiang, Z.; Wu, K.; Liu, S.; Zhang, Y.; Wang, X.; Zhang, Z.; Wei, J. Characteristics of Glaciers Surging in the Western Pamirs. Remote Sens. 2023, 15, 1319. https://doi.org/10.3390/rs15051319

AMA Style

Wang Z, Jiang Z, Wu K, Liu S, Zhang Y, Wang X, Zhang Z, Wei J. Characteristics of Glaciers Surging in the Western Pamirs. Remote Sensing. 2023; 15(5):1319. https://doi.org/10.3390/rs15051319

Chicago/Turabian Style

Wang, Zhenfeng, Zongli Jiang, Kunpeng Wu, Shiyin Liu, Yong Zhang, Xin Wang, Zhen Zhang, and Junfeng Wei. 2023. "Characteristics of Glaciers Surging in the Western Pamirs" Remote Sensing 15, no. 5: 1319. https://doi.org/10.3390/rs15051319

APA Style

Wang, Z., Jiang, Z., Wu, K., Liu, S., Zhang, Y., Wang, X., Zhang, Z., & Wei, J. (2023). Characteristics of Glaciers Surging in the Western Pamirs. Remote Sensing, 15(5), 1319. https://doi.org/10.3390/rs15051319

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