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Communication

The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985

by
Xuanru Zhao
1,
Jinquan Cheng
1,
Weijin Guan
1,
Yuxuan Zhang
1 and
Bo Cao
1,2,3,*
1
Key Laboratory of Western China’s Environmental Systems (MOE), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
2
Department of Geosciences, University of Oslo, 0313 Oslo, Norway
3
Shiyang River Basin Scientific Observing Station, Lanzhou University, Lanzhou 730000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(5), 762; https://doi.org/10.3390/rs16050762
Submission received: 8 January 2024 / Revised: 6 February 2024 / Accepted: 17 February 2024 / Published: 22 February 2024
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Abstract

:
In High Mountain Asia, most glaciers and glacial lakes have undergone rapid variations throughout changes in the climate. Unlike land-terminating glaciers, lake-terminating glaciers show rapid shrinkage due to dynamic interactions between proglacial lakes and glacier dynamics. In this study, we conducted a detailed analysis of the changes in the surface elevation, velocity, and especially frontal ablation on Jiongpu Co lake-terminating glacier. The results show that the Jiongpu Co glacier has twice as much negative mass balance compared to other glaciers, and the annual surface velocity has anomalously increased (3.6 m a−1 per decade) while other glaciers show a decreased trend. The frontal ablation fraction in the net mass loss of the Jiongpu Co glacier increased from 26% to 52% with the accelerated expansion of the proglacial lake. All available evidence indicates the presence of positive feedback between the proglacial lake and its host glacier. Our findings highlight the existence of proglacial lake affects the spatial change patterns of the lake-terminating glacier. Furthermore, the ongoing enlargement of the lake area amplifies the changes associated with the evolution of the lake-terminating glacier.

Graphical Abstract

1. Introduction

Outside the polar regions, High Mountain Asia (HMA) is the largest glacierized area (RGI 7.0) [1]. Owing to the rapid rate of climate change, the majority of glaciers have exhibited retreat and negative mass balance over the past several decades in this region [2,3,4,5]. With the continuous shrinkage of glaciers, there is a significant increase in the expansion of glacial lakes across HMA [4,6,7,8]. The number and area of glacial lakes on HMA increased by approximately 10.7% and 15.2% from 1990 to 2020, respectively [9]. Increasing evidence confirms the existence of an interactive feedback mechanism between glaciers and glacial lakes, which accelerates the glacier mass loss [10,11,12,13,14], and therefore, future ice mass loss may surpass previous estimates [12].
Among all types of glacial lakes, the proglacial lakes are more intimately related to the glacier changes as they are directly connected to glacier termini. Recent research on the relationship between proglacial lakes and their host glaciers is primarily concentrated on the development of lake-terminating glaciers and proglacial lakes, as well as the effect of proglacial lakes on glacier dynamic process, such as surface velocity and ice thickness changes [11,12,13,15,16]. Nie et al. noted that the total area of glacial lakes increased by 14% between 1990 and 2015, while proglacial lakes’ area increased by 51.6%, contributing to 83.1% of the total glacial lake expansion in the Himalayas [17]. King et al. reported a 32% higher mass loss in lake-terminating glaciers than in land-terminating glaciers in the Everest region of the Himalayas among 2000–2015 [18]. Additionally, lake-terminating glaciers displayed a more negative mass balance (ranging from −0.13 to −0.29 m w.e. a−1) compared to land-terminating glaciers from the 1970s to 2015 [12]. Furthermore, the Thorthormi Glacier in northern Bhutan has transitioned from land- to lake-terminating glacier since 2011. Following this transformation, the glacier has shown notable accelerated thinning (twice the rate compared to before 2011) and a considerable flow velocity (>150 m a−1) at the terminus [19].
The lake-terminating/tidewater glaciers lose more mass through mechanical calving and subaqueous melt at the termini, which is known as frontal ablation [12,20]. The frontal ablation constitutes 20% of the net mass loss in 27 tidewater glaciers in Alaska and around 21% of the overall mass loss from Svalbard glaciers [21,22]. However, the knowledge of frontal ablation in lake-terminating glaciers in HMA is extremely lacking. Therefore, gaining insights into the proglacial lake dynamics, their feedback to host glaciers, and the proportion of frontal ablation to the total mass change in lake-terminating glaciers is crucial for comprehending the intricate interaction of glaciers and glacial lakes in HMA.
The Yigong Zangbo Basin, situated in the eastern part of the Tibetan Plateau, stands out as one of the highly concentrated areas featuring large mountain glaciers on the Tibetan Plateau. Glaciers in this region have retreated significantly, which has led to the rapid expansion of glacial lakes [23,24,25]. The Jiongpu Co glacial lake is the largest proglacial lake, which is fed by a large temperate glacier in this region. Therefore, a comprehensive and detailed assessment of changes in the Jiongpu Co glacier and lake would enhance our comprehending of the interactions between the proglacial lakes and their host glaciers and provide a reference for future numerical simulations. Thus, the primary aim of our study was to investigate the evolution of the Jiongpu Co glacier and its proglacial lake during 1967–2020, utilizing multi-source remote sensing data. Additionally, we aimed to discuss the influence of this lake on the glacier’s dynamics by comparing the differences in the glacier’s change pattern with the land-terminating glaciers. Lastly, we estimated the total mass change and the proportion of frontal ablation to it with the lake expanding since 1985.

2. Study Area and Data Sources

2.1. Study Area

According to the Randolph Glacier Inventory (RGI 7.0), the Yigong Zangbo Basin contains 2185 glaciers (Figure 1) ranging from 2800–7000 m a.s.l. in elevation. This basin also contains 182 glacial lakes (>0.005 km2), 24 of which are proglacial lakes [9]. The Jiongpu Co lake is the biggest proglacial lake in this basin. In 2020, the Jiongpu Co glacier covered an area of approximately 56.0 km2, ranging from 4100–6500 m a.s.l. in altitude (Figure 1b,c). The glacier melted dramatically, providing both the space and material for the expansion of the proglacial lake with an area of 5.3 km2.

2.2. Data Sources

2.2.1. KH and Landsat Series

One Corona KH-4 image and two Hexagon KH-9 images were employed to obtain the boundaries of the Jiongpu Co glacier and lake in 1967, 1976, and 1982 in the study. Furthermore, 35 Landsat images were selected to identify the Jiongpu Co glacier and lake boundaries from 1986 to 2020 (Table S1). Most images were captured towards the end of the ablation season (from September to December), and the cloud coverage of all images was less than 10%.

2.2.2. Digital Elevation Models (DEMs) and Surface Elevation Change Dataset

Topographical DEM and SRTM DEM were used to calculate the mass change in the Jiongpu Co glacier. The topographical DEM was taken in 1985, based on a series of 1:50000 topographical maps. The vertical accuracy of this DEM was ±8 m for regions with slopes between 6−25° [26,27]. The C-band SRTM DEMs, with vertical errors ranging from 7.2 to 12.6 m, obtained from the USGS and served as a reference altitude in the process of monitoring glacial altitude changes [28]. In addition, the C-band radar penetration depth in glacial regions was estimated using the X-band SRTM DEMs acquired from the German Aerospace Center (DLR).
Hugonnet et al. (2021) derived the change rate of glacier surface elevation in 2000−2020 through the interpolation of a continuous elevation time series from multiple co-registered optical DEMs and related dataset [29]. This dataset has been widely employed in glacier mass change research [30,31,32,33]. In this paper, the dataset provided the surface elevation change from 2000 to 2020 of Jiongpu Co glacier and all land-terminating glaciers in the Yigong Zangbo Basin.

2.2.3. Glacier Surface Velocity Dataset

The NASA MEaSUREs ITS_LIVE project provides the annual glacier velocity data over the 1985–2018 period [34]. This dataset, featuring a resolution of 240 m, generated from Landsat series images (Landsat 4, 5, 7, and 8) using auto-RIFT [35]. In this paper, the surface velocities of all land-terminating glaciers and Jiongpu Co glacier between 1987 and 2018 were obtained from the ITS_LIVE dataset. And the average uncertainty of glacier surface velocities was 1.6 m a−1 (Figure S1), determined by analyzing the surface displacements in stable, non-glacier-covered area with slopes below 10° [36].

2.2.4. The Bed Elevation of Jiongpu Co Lake

The bed elevation of Jiongpu Co lake was measured in 2020 and 2021 using an uncrewed surface vessel (USV) equipped with a sonar system. In total, there were 2658 evenly distributed sampling points, which measured by the uniform time intervals approach. Bathymetry results showed that the Jiongpu Co lake features an average depth of 124 m, reaching a maximum depth at 245 m. The uncertainty of the bathymetry depths was evaluated at seven points on a measuring rope and was less than 4%.

3. Methods

3.1. Jiongpu Co Glacier and Jiongpu Co Lake Area Changes

The use of manual digitization in shadowed regions is still required, while automated methods can be employed for delineating glacier and glacial lake boundaries [37]. In this paper, the boundaries of Jiongpu Co glacier and lake were manually digitized in each image. In addition, the topographic characteristics of glacier and glacial lake formation, along with 3D view and images in Google Earth, served as references throughout this process.
Errors in the area measurement are intricately linked to the image spatial resolution, and the calculation formula is as follows:
u a = P λ σ λ 2 2 = P λ 2 σ
where λ represents the resolution of pixel spatial, P denotes the glacier/lake perimeter, and σ is the weight coefficient for random errors in vectorization, set at 0.7 [38].

3.2. Glacier Surface Elevation Changes

Surface elevation changes in the Jiongpu Co glacier from 1985 to 2000 were calculated using topographic maps and the SRTM DEM C-band. We corrected horizontal and vertical offsets in the DEMs based on a statistical relationship between elevation differences caused by spatial position deviation and slope and aspect [37,39]:
d h tan ⁡ α = a · cos ⁡ b − ψ + c
where d h denotes the elevation difference; α represent the terrain slope; a represents the magnitude of the elevation-difference bias; b is the angle of the elevation-difference bias; ψ represents the terrain aspect; and c is the mean deviance between the DEMs divided by the mean slope of the chosen terrain.
To eliminate the influence of the glacier’s own motion on the elevation difference, a non-glacierized region was chosen as the rectified sample. In addition, an error parameter within the slope range of 1–45° was chosen for the non-glacier-covered region to minimize the effects of severe terrain fluctuations on parameter estimations [39,40]. Subsequently, the 5% and 95% quantiles were employed as thresholds to exclude the most extreme outliers [41]. After co-registration, the absolute average elevation difference over the non-glacierized domain changed from −5.7 m to 0.2 m. We also took into account the penetration depth of the SRTM C-band in evaluating the glacier surface elevation changes [41,42]. Our calculations revealed an average penetration depth of approximately 6 m for SRTM-C, which was utilized to correct the elevations in the SRTM-C DEM.

3.3. Net Mass Loss of the Lake-Terminating Glacier

The net mass loss ( M t ) of a lake-terminating glacier is mainly manifested by its net surface mass loss ( M s ) driven by climate change and its frontal ablation ( A f ), owing to mechanical calving and subaqueous melt [12,43] (Figure 2). Negligible amounts of evaporation and percolation were not considered in the calculations [44,45,46].
This is expressed as follows:
M t = A f + M s
in which the frontal ablation ( A f ) is calculated from the ice discharge ( D i c e ) across a flux gate (the location of it is defined as approximately 1 km from the terminus in 2020 of Jiongpu Co glacier and it was drawn as close to perpendicular to the flow direction as possible). The mass change related to the terminus position change ( M t e r m ) [27,47] as follows:
A f = D i c e + M t e r m
where D i c e is given as follows:
D i c e = ρ i c e · v t R ∑ i = 1 N f h s i s i − ρ g l a · S · ∆ h ¯ s
in which ρ i c e , set as 900 kg m−3, represents the vertically averaged the ice column density [48]; ρ g l a is the glacier density, assigned a value of 850 kg m−3 [49]; t is the interval time; v is the average ice flow velocity at the flux gate in the interval time, the average ice velocity of 2010–2018 was used to approximate the velocity for 2010–2020; R represents the pixel spatial resolution; N f is the number of pixels within the flux gate; h s i denotes the ice thickness for a single pixel of the flux gate from the preceding year; s i is the pixel area; S and ∆ h ¯ s represent the area and average surface elevation change in the region enclosed by the glacier terminus at t2 and the flux gate profile, respectively.
The mass change lead by the terminus position change was calculated as follows:
M t e r m = ρ i c e · ∑ i = 1 N r h s i s i − ρ g l a · 0.5 · ∆ S · ∆ h ¯ ∆ S
where N r represents the pixel count across the terrain between the profiles of glacier terminus position in two years; ∆ S is the area of a retreating glacier replaced by the lake at the end year (this is then multiplied by 0.5, which is necessary to account for glacier frontal retreat combined with surface lowing); and ∆ h ¯ ∆ S is the average surface elevation change within the glacier retreat region from t1 to t2.
The surface mass change ( M s ) was calculated as follows:
M s = ρ g l a ∆ h ¯ · S g + 0.5 · ∆ S · ∆ h ¯ ∆ S
where S g represents the glacier area at t2 and ∆ h ¯ denotes the mean surface elevation change within the region above the glacier terminus at t2.
The uncertainties in calculating glacier mass change were mainly associated with errors in glacier surface velocity, glacier thinning, and ice thickness. The glacier ice thickness was determined by comparing surface and bed elevations near glacier tongue. Thus, the ice thickness uncertainty (approximately 10 m) was determined based on errors associated with the surface and bed elevations at glacier terminus. Finally, the uncertainty associated with mass change was calculated at approximately 0.34 Gt from 1985 to 2020.

4. Results

4.1. Expansion of Jiongpu Co Lake and Shrinkage of Jiongpu Co Glacier

Between 1967 and 2020, Jiongpu Co lake expanded by 820% (from 0.6 ± 0.1 km2 to 5.3 ± 0.3 km2, Figure 3), with a mean expansion rate of 15.5% a−1. The dramatic rate of expansion resulted in Jiongpu Co lake transitioning from a small lake into one of the largest proglacial lakes in HMA. In contrast, the area of the Jiongpu Co glacier was 61.6 ± 3.2 km2 in 1967 and then decreased by 0.17% a−1 to 56.0 ± 3.0 km2 in 2020 (Figure 3).

4.2. Surface Elevation Changes in Jiongpu Co Glacier

The surface elevation changes in the Jiongpu Co glacier were −9.5± 3.9 m, −8.2 ± 0.8 m, and −13.4± 0.9 m in 1985–2000, 2000–2010, and 2010–2020, respectively. This shows an evident more negative trend: from −0.64 m a−1 in 1985–2000 to −1.34 m a−1 in 2010–2020 (Figure 4). The thinning of the Jiongpu Co glacier at lower altitudes was more significant, especially in the most recent years of the study period (Figure 5). For example, the thinning rate at 4200–4400 m was approximately 2.9 m a−1, 3.6 m a−1, and 4.2 m a−1 in 1985–2000, 2000–2010, and 2010–2020, respectively. Above 4500 m, the glacier surface elevation change rate remained relatively stable across all periods. Thus, the rapid change rate of the Jiongpu Co glacier was mostly attributed to the larger amount of thinning occurring at the terminus (Figure 5).

4.3. Surface Velocity Changes in Jiongpu Co Glacier

The average surface velocity of Jiongpu Co glacier increased from 11.5 m a−1 in 1987 to 23.1 m a−1 in 2018, with a rate of 3.6 m a−1 dec−1 (Figure 6). As well as glacier thinning, the glacier surface velocity accelerated significate in recent years. The distribution of Jiongpu Co glacier surface velocity along the center line from the equilibrium-line altitude (ELA) to the terminus, which was statistics by the normalization, showed a slow decrease trend (Figure 7). Particularly, the glacier velocity exhibited another peak near the terminus.

4.4. The Net Mass Loss of the Jiongpu Co Glacier with the Lake Expanding

Since 1985, the net mass loss of the Jiongpu Co glacier was 2.25 ± 0.34 Gt, of which 0.97 ± 0.34 Gt (43%) was by frontal ablation and 1.28 ± 0.34 Gt (57%) was by net surface mass loss (Table 1). During 1985–2000, the frontal ablation was 0.15 Gt, constituting 26% of the net mass loss (0.57 ± 0.23 Gt). With the continuous expansion of the Jiongpu Co lake, the contribution of frontal ablation to the net mass loss increased to 52% in the period of 2010–2020.

5. Discussion

5.1. The Difference between Jiongpu Co Glacier and Other Glaciers

The Yigong Zangbo Basin contains 2185 glaciers, with an area retreating rate of −0.1% a−1 in 1990–2015 [50], and 99% (2161) of these are land-terminating glaciers. The change in the mean surface elevation of the land-terminating glaciers in this region was −0.7 m a−1 in 2000–2020, while the Jiongpu Co glacier displayed a more substantial negative mass balance (approximately −1 m a−1 in 1985–2020). In particular, a significant mass balance difference was observed at the glacier tongue (4200–4400 m), where the Jiongpu Co glacier’s thinning rate was approximately three times higher than land-terminating glaciers in 2010–2020 (Figure 5).
Ideally, for land-terminating glaciers, along the center flow line, the maximum velocity occurs near the ELA and gradually diminishes to 0 at the terminus [51]. However, the Jiongpu Co glacier velocities exhibit rapid surface velocity in the vicinity of its terminus along the center flow line (Figure 7).
This implies that the existence of the glacial lake causes the accelerated thinning rate and the surface velocity at the Jiongpu Co glacier tongue, aligning with findings from previous global studies. In the central Himalaya, lake-terminating glaciers experienced the fastest thinning at their termini [12]. Moreover, for the lake-terminating Lugge Glacier in this region, the mass balance (−4.67 ± 0.07 m a−1) was more negative compared with a neighboring land-terminating Glacier [11]. Furthermore, the average velocity of 70 lake-terminating glaciers (18.8 m a−1) was more than twice than that of the land-terminating glaciers in the Himalaya region, which display considerably more variability around the glacier termini [14].
The velocities of the land-terminating glaciers displayed a decreasing trend of −0.5 m a−1 per decade, while the Jiongpu Co glacier surface velocity presented an increasing trend of 3.6 m a−1 per decade (Figure 6). This increased feedback from the lake to its host glacier, which increases with the continued expansion of the Jiongpu Co lake. Previous research has identified an increase trend in the velocities of some lake-terminating glaciers, attributed to the rapid enlargement of proglacial lakes [52].
As faster sliding is encouraged by diminishing basal drag due to the lake’s existence, the ice velocities at the lake-terminating glacier terminus are much faster than those at the land-terminating glaciers [53]. The increase in velocity in the terminus accelerates the surface thinning and then reduces effective pressure (the difference between ice overburden pressure and water pressure), which results in further velocity acceleration, longitudinal stretching, and the ensuing calving rate increases [20]. Calving, velocity increase, and thinning therefore form a positive feedback loop in which initial surface lowering and acceleration are amplified and propagated by the dynamic processes of the host glacier.

5.2. Jiongpu Co Glacier Shrinkage and Lake Development

Song et al. have found that the 15 proglacial lakes observed in southeast Tibetan Plateau expanded by an average of 74.77% between 1988 and 2013 [54]. In addition, the proglacial lake at the terminus of Yanong Glacier expanded from 1.15 ± 0.07 km2 in 1986 to 3.15 ± 0.1 km2 in 2017 (174%) [55]. During the investigated period, the Jiongpu Co lake expanded rapidly by 820% and the rate of lake expansion showed an accelerating trend (Figure 3). Correspondingly, the frontal ablation from the Jiongpu Co glacier increased at a faster rate, with the value of constituents increasing from 26% in 1985–2000 to 52% in 2010–2020 (Table 1). Similarly, the constitute of the frontal ablation from the lake-terminating glacier Longbasaba in the Himalaya region also increased from 19% to 40% [28]. The evidence clearly highlights the importance of considering the contribution of the frontal ablation to the net mass loss of the lake-terminating glaciers. Moreover, it is crucial to acknowledge that the frontal ablation of these glaciers has increased substantially due to the expansion of proglacial lakes.
The Longbasaba Lake had a maximum depth of 102.3 m in 2018, and its expansion rate was 3.3% a−1 during 1988–2018, slower than that of the Jiongpu Co Lake [28]. Benn et al. have proven that calving rate increase with lake water depth [20]. Thus, the rapid expansion of the Jiongpu Co lake can also be attributed to the deeper water depth. Interestingly, we found that the area of Jiongpu Co lake stabilized from 2016 to 2020, with the change rate of 0.33% a−1 (Figure 3). The velocity at the glacier front also showed a slightly lower and relatively stable during the same period (Figure S2). This may be attributed to the dramatic decrease in the maximum lake depth along the glacier front from ~160 m in 2015 to ~40 m in 2016 (Figure S3), which might have slowed down the ice flow and stabilized the glacier front [56,57].

6. Conclusions

In this study, we undertook a detailed analysis of the impact of the Jiongpu Co proglacial lake on the dynamic processes of its host glacier, comparing it with the spatiotemporal variation characteristics of the land-terminating glaciers in the Yigong Zangbo Basin.
The dramatic expansion of the Jiongpu Co lake is accompanied by rapid glacier shrinkage. The lake expanded by 820% from 0.6 ± 0.1 km2 in 1967 to 5.3 ± 0.3 km2 in 2020, with a mean expansion rate of 15.5% a−1. Correspondingly, the Jiongpu Co glacier area decreasing from 61.6 ± 3.2 km2 in 1967 to 56.0 ± 3.0 km2 in 2020. Since 1985, the net mass loss of the Jiongpu Co glacier accelerated, with values of 0.57 ± 0.23 Gt, 0.62 ± 0.05 Gt, and 1.06 ± 0.06 Gt in 1985–2000, 2000–2010, and 2010–2020, respectively.
With the continued expansion of proglacial lakes, their impact on glacier evolution was noted to have become more significant. The retreating rate, thinning rate, and surface velocity of the Jiongpu Co glacier all accelerated in the past several decades. This led to an increase in the amount of mass loss associated with frontal ablation, with the constitute value increasing from 26% to 52%. The evidence shows that the existence of Jiongpu Co lake affects the spatial change patterns of its host glacier, and the lake’s expansion amplifies these evolutionary changes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/rs16050762/s1, Figure S1: Displacement on flat terrain observed in Landsat optical data set from 1987 to 2018; Figure S2: The velocity at glacier terminus (2 km to 6.5 km from the outlet of Jiongpu Co lake) from 1987 to 2018; Figure S3: The depth of Jiongpu Co lake and the position of the glacier terminus in 2015, 2016 and 2020; Table S1: Details regarding the dataset utilized in this paper.

Author Contributions

Conceptualization, B.C. and X.Z.; methodology, B.C. and X.Z.; formal analysis, X.Z., J.C. and W.G.; investigation, X.Z. and W.G.; writing—original draft preparation, X.Z.; writing—review and editing, B.C. and Y.Z.; funding acquisition, B.C. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by the Second Tibetan Plateau Scientific Expedition and Research Program [grant No. 2019QZKK0205], National Natural Science Foundation of China [grant No. 42071077], and Science and technology Project of Tibet Autonomous Region [grant No. XZ202101ZY0001G].

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors would like to thank the USGS and the German Aerospace Center (DLR) (https://download.geoservice.dlr.de/SRTM_XSAR/, (accessed on 2000)) for providing the data.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. RGI Consortium. Data Set. Randolph Glacier Inventory—A Dataset of Global Glacier Outlines, Version 7; National Snow and Ice Data Center: Boulder, CO, USA, 2023. [Google Scholar] [CrossRef]
  2. Yao, T.; Thompson, L.; Yang, W.; Yu, W.; Gao, Y.; Guo, X.; Yang, X.; Duan, K.; Zhao, H.; Xu, B.; et al. Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nat. Clim. Change 2012, 2, 663–667. [Google Scholar] [CrossRef]
  3. Zemp, M.; Frey, H.; Gärtner-Roer, I.; Nussbaumer, S.U.; Hoelzle, M.; Paul, F.; Haeberli, W.; Denzinger, F.; Ahlstrøm, A.P.; Anderson, B.; et al. Historically unprecedented global glacier decline in the early 21st century. J. Glaciol. 2015, 61, 745–762. [Google Scholar] [CrossRef]
  4. Miles, E.; McCarthy, M.; Dehecq, A.; Kneib, M.; Fugger, S.; Pellicciotti, F. Health and sustainability of glaciers in High Mountain Asia. Nat. Commun. 2021, 12, 2868. [Google Scholar] [CrossRef]
  5. Wang, T.; Zhao, Y.; Xu, C.; Ciais, P.; Liu, D.; Yang, H.; Piao, S.; Yao, T. Atmospheric dynamic constraints on Tibetan Plateau freshwater under Paris climate targets. Nat. Clim. Change 2021, 11, 219–225. [Google Scholar] [CrossRef]
  6. Zhang, G.; Yao, T.; Xie, H.; Wang, W.; Yang, W. An inventory of glacial lakes in the Third Pole region and their changes in response to global warming. Glob. Planet. Change 2015, 131, 148–157. [Google Scholar] [CrossRef]
  7. Wang, Q.; Yi, S.; Sun, W. Continuous estimates of glacier mass balance in High Mountain Asia based on ICESat-1,2 and GRACE/GRACE Follow-On data. Geophys. Res. Lett. 2020, 48, e2020GL090954. [Google Scholar] [CrossRef]
  8. Zheng, G.; Allen, S.K.; Bao, A.; Ballesteros-Cánovas, J.A.; Huss, M.; Zhang, G.; Li, J.; Yuan, Y.; Jiang, L.; Yu, T.; et al. Increasing risk of glacial lake outburst floods from future Third Pole deglaciation. Nat. Clim. Change 2021, 11, 411–417. [Google Scholar] [CrossRef]
  9. Wang, X.; Guo, X.; Yang, C.; Liu, Q.; Wei, J.; Zhang, Y.; Liu, S.; Zhang, Y.; Jiang, Z.; Tang, Z. Glacial lake inventory of high-mountain Asia in 1990 and 2018 derived from Landsat images. Earth Syst. Sci. Data. 2020, 12, 2169–2182. [Google Scholar] [CrossRef]
  10. Brun, F.; Wagnon, P.; Berthier, E.; Jomelli, V.; Maharjan, S.B.; Shrestha, F.; Kraaijenbrink, P.D.A. Heterogeneous Influence of Glacier Morphology on the Mass Balance Variability in High Mountain Asia. J. Geophys. Res. Earth Surf. 2019, 124, 1331–1345. [Google Scholar] [CrossRef]
  11. Tsutaki, S.; Fujita, K.; Nuimura, T.; Sakai, A.; Sugiyama, S.; Komori, J.; Tshering, P. Contrasting thinning patterns between lake- and land-terminating glaciers in the Bhutanese Himalaya. Cryosphere 2019, 13, 2733–2750. [Google Scholar] [CrossRef]
  12. King, O.; Bhattacharya, A.; Bhambri, R.; Bolch, T. Glacial lakes exacerbate Himalayan glacier mass loss. Sci. Rep. 2019, 9, 18145. [Google Scholar] [CrossRef]
  13. Kumar, V.; Mehta, M.; Shukla, T. Spatially resolved estimates of glacial retreat and lake changes from Gepang Gath Glacier, Chandra Basin, Western Himalaya, India. J. Geol. Soc. India 2021, 97, 520–526. [Google Scholar] [CrossRef]
  14. Pronk, J.B.; Bolch, T.; King, O.; Wouters, B.; Benn, D.I. Contrasting surface velocities between lake- and land-terminating glaciers in the Himalayan region. Cryosphere 2021, 15, 5577–5599. [Google Scholar] [CrossRef]
  15. Basnett, S.; Kulkarni, A.V.; Bolch, T. The influence of debris cover and glacial lakes on the recession of glaciers in Sikkim Himalaya, India. J. Glaciol. 2013, 59, 1035–1046. [Google Scholar] [CrossRef]
  16. Liu, Q.; Mayer, C.; Wang, X.; Nie, Y.; Wu, K.; Wei, J.; Liu, S.Y. Interannual flow dynamics driven by frontal retreat of a lake-terminating glacier in the Chinese Central Himalaya. Earth Planet. Sci. Lett. 2020, 546, 116450. [Google Scholar] [CrossRef]
  17. Nie, Y.; Sheng, Y.; Liu, Q.; Liu, L.; Liu, S.; Zhang, Y.; Song, C. A regional-scale assessment of Himalayan glacial lake changes using satellite observations from 1990 to 2015. Remote Sens. Environ. 2017, 189, 1–13. [Google Scholar] [CrossRef]
  18. King, O.; Quincey, D.J.; Carrivick, J.L.; Rowan, A.V. Spatial variability in mass loss of glaciers in the Everest region, central Himalayas, between 2000 and 2015. Cryosphere 2017, 11, 407–426. [Google Scholar] [CrossRef]
  19. Sato, Y.; Fujita, K.; Inoue, H.; Sakai, A. Land- to lake-terminating transition triggers dynamic thinning of a Bhutanese glacier. Cryosphere 2022, 16, 2643–2654. [Google Scholar] [CrossRef]
  20. Benn, D.I.; Warren, C.R.; Mottram, R.H. Calving processes and the dynamics of calving glaciers. Earth-Sci. Rev. 2007, 82, 143–179. [Google Scholar] [CrossRef]
  21. Mcnabb, R.W.; Hock, R.; Huss, M. Variations in Alaska tidewater glacier frontal ablation, 1985–2013. J. Geophys. Res. Earth Surf. 2015, 120, 120–136. [Google Scholar] [CrossRef]
  22. Błaszczyk, M.; Jania, J.; Hagen, J. Tidewater Glaciers of Svalbard: Recent changes and estimates of calving fluxes. Pol. Polar Res. 2009, 30, 85–142. [Google Scholar]
  23. Brun, F.; Buri, P.; Miles, E.S.; Wagnon, P.; Steiner, J.; Berthier, E.; Ragettli, S.; Kraaijenbrink, P.; Immerzeel, W.W.; Pellicciotti, F. Quantifying volume loss from ice cliffs on debris-covered glaciers using high-resolution terrestrial and aerial photogrammetry. J. Glaciol. 2016, 62, 684–695. [Google Scholar] [CrossRef]
  24. Pritchard, H.D. Asia’s shrinking glaciers protect large populations from drought stress. Nature 2019, 569, 649–654. [Google Scholar] [CrossRef] [PubMed]
  25. Yao, T.; Yu, W.; Wu, G.; Xu, B.; Yang, W.; Zhao, H.; Wang, W.; Li, S.; Wang, N.; Li, Z. Glacier anomalies and relevant disaster risks on the Tibetan Plateau and surroundings. Chin. Sci. Bull. 2019, 64, 2770–2782. (In Chinese) [Google Scholar] [CrossRef]
  26. GB/T 12343.1–2008; Chinese National Standard. Compilation Specifications for National Fundamental Scale Maps. Part 1: Compilation Specifications for 1:25 000/1:50 000/1:100 000 Topographic Maps. General Administration of Quality Supervision, Inspection and Quarantine: Beijing, China, 2008.
  27. Wei, J.; Liu, S.; Wang, X.; Zhang, Y.; Jiang, Z.; Wu, K.; Zhang, Z.; Zhang, T. Longbasaba Glacier recession and contribution to its proglacial lake volume between 1988 and 2018. J. Glaciol. 2020, 67, 473–484. [Google Scholar] [CrossRef]
  28. Rodríguez, E.; Morris, C.S.; Belz, J.E. A global assessment of the SRTM performance. Photogramm. Eng. Remote. Sens. 2006, 72, 249–260. [Google Scholar] [CrossRef]
  29. Hugonnet, R.; McNabb, R.; Berthier, E.; Menounos, B.; Nuth, C.; Girod, L.; Farinotti, D.; Huss, M.; Dussaillant, I.; Brun, F.; et al. Accelerated global glacier mass loss in the early twenty-first century. Nature 2021, 592, 726–731. [Google Scholar] [CrossRef]
  30. Pan, B.; Guan, W.; Shi, M.; Wu, G.; Cheng, J.; Shangguan, D.; Guo, W.; Cao, B. Different characteristics of two surges in Weigeledangxiong Glacier, northeastern Tibetan Plateau. Environ. Res. Lett. 2022, 17, 114009. [Google Scholar] [CrossRef]
  31. Van Tricht, L.; Huybrechts, P. Modelling the historical and future evolution of six ice masses in the Tien Shan, Central Asia, using a 3D ice-flow model. Cryosphere 2023, 17, 4463–4485. [Google Scholar] [CrossRef]
  32. Schuster, L.; Rounce, D.; Maussion, F. Glacier projections sensitivity to temperature-index model choices and calibration strategies. Ann. Glaciol. 2023, 1–16. [Google Scholar] [CrossRef]
  33. Li, J.; Sun, M.; Yao, X.; Duan, H.; Zhang, C.; Wang, S.; Niu, S.; Yan, X. A Review of Karakoram Glacier Anomalies in High Mountains Asia. Water 2023, 15, 3215. [Google Scholar] [CrossRef]
  34. Gardner, A.S.; Fahnestock, M.A.; Scambos, T.A. ITS_LIVE Regional Glacier and Ice Sheet Surface Velocities: Version 1; National Snow and Ice Data Center: Boulder, CO, USA, 2019. [Google Scholar] [CrossRef]
  35. Gardner, A.S.; Moholdt, G.; Scambos, T.; Fahnstock, M.; Ligtenberg, S.; van den Broeke, M.; Nilsson, J. Increased West Antarctic and unchanged East Antarctic ice discharge over the last 7 years. Cryosphere 2018, 12, 521–547. [Google Scholar] [CrossRef]
  36. Paul, F.; Bolch, T.; Briggs, K.; Kääb, A.; Mcmillan, M.; Mcnabb, R.; Nagler, T.; Nuth, C.; Rastner, P.; Strozzi, T. Error sources and guidelines for quality assessment of glacier area, elevation change, and velocity products derived from satellite data in the Glaciers_cci project. Remote Sens. Environ. 2017, 203, 256–275. [Google Scholar] [CrossRef]
  37. Paul, F.; Bolch, T.; Kääb, A.; Nagler, T.; Nuth, C.; Scharrer, K.; Shepherd, A.; Strozzi, T.; Ticconi, F.; Bhambri, R.; et al. The glaciers climate change initiative: Methods for creating glacier area, elevation change and velocity products. Remote Sens. Environ. 2015, 162, 408–426. [Google Scholar] [CrossRef]
  38. Hanshaw, M.N.; Bookhagen, B. Glacial areas, lake areas, and snow lines from 1975 to 2012: Status of the Cordillera Vilcanota, including the Quelccaya Ice Cap, northern central Andes, Peru. Cryosphere 2014, 8, 359–376. [Google Scholar] [CrossRef]
  39. Nuth, C.; Kääb, A. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere 2011, 5, 271–290. [Google Scholar] [CrossRef]
  40. Zhao, X.; Wang, X.; Wei, J.; Jiang, Z.; Zhang, Y.; Liu, S. Spatiotemporal variability of glacier changes and their controlling factors in the Kanchenjunga region, Himalaya based on multi-source remote sensing data from 1975 to 2015. Sci. Total Environ. 2020, 745, 140995. [Google Scholar] [CrossRef] [PubMed]
  41. Pieczonka, T.; Bolch, T.; Wei, J.F.; Liu, S.Y. Heterogeneous mass loss of glaciers in the Aksu-Tarim Catchment (Central Tien Shan) revealed by 1976 KH-9 Hexagon and 2009 SPOT-5 stereo imagery. Remote Sens. Environ. 2013, 130, 233–244. [Google Scholar] [CrossRef]
  42. Berthier, E.; Arnaud, Y.; Vincent, C.; Rémy, F. Biases of SRTM in high-mountain areas: Implications for the monitoring of glacier volume changes. Geophys. Res. Lett. 2006, 33, L08502. [Google Scholar] [CrossRef]
  43. Cogley, J.G.; Hock, R.; Rasmussen, L.A.; Arendt, A.A.; Zemp, M. Glossary of glacier mass balance and related terms. IHP-VII Technical Documents in Hydrology. Polar Record. 2012, 48, e15. [Google Scholar] [CrossRef]
  44. Brock, B.W.; Mihalcea, C.; Kirkbride, M.P.; Diolaiuti, G.; Cutler, M.E.J.; Smiraglia, C. Meteorology and surface energy fluxes in the 2005–2007 ablation seasons at the Miage debris-covered glacier, Mont Blanc Massif, Italian Alps. J. Geophys. Res. Atmos. 2010, 115, D09106. [Google Scholar] [CrossRef]
  45. Zhang, Y.; Hirabayashi, Y.; Liu, S. Catchment-scale reconstruction of glacier mass balance using observations and global climate data: Case study of the Hailuogou catchment, south-eastern Tibetan Plateau. J. Hydrol. 2012, 444–445, 146–160. [Google Scholar] [CrossRef]
  46. Treichler, D.; Kääb, A.; Salzmann, N.; Xu, C.Y. Recent glacier and lake changes in High Mountain Asia and their relation to precipitation changes. Cryosphere 2019, 13, 2977–3005. [Google Scholar] [CrossRef]
  47. Kochtitzky, W.; Copland, L.; Van Wychen, W.; Hugonnet, R.; Hock, R.; Dowdeswell, J.A.; Benham, T.; Strozzi, T.; Glazovsky, A.; Lavrentiev, I.; et al. unquantified mass loss of Northern Hemisphere marine-terminating glaciers from 2000–2020. Nat. Commun. 2022, 13, 5835. [Google Scholar] [CrossRef]
  48. Kääb, A.; Berthier, E.; Nuth, C.; Gardelle, J.; Arnaud, Y. Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas. Nature 2012, 488, 495–498. [Google Scholar] [CrossRef]
  49. Huss, M. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 2013, 7, 877–887. [Google Scholar] [CrossRef]
  50. Ke, C.Q.; Lee, H.; Han, Y.F. Glacier Change in the Yigong Zangbo Basin, Tibetan Plateau, China. Korean J. Remote Sens. 2019, 35, 491–502. [Google Scholar] [CrossRef]
  51. Cuffey, K.M.; Paterson, W.S.B. The Physics of Glaciers, 4th ed.; Butterworth-Heinemann/Elsevier: Burlington, MA, USA, 2010. [Google Scholar]
  52. King, O.; Dehecq, A.; Quincey, D.; Carrivick, J. Contrasting geometric and dynamic evolution of lake and land-terminating glaciers in the central Himalaya. Glob. Planet. Change 2018, 167, 46–60. [Google Scholar] [CrossRef]
  53. Benn, D.I.; Evans, D. Glaciers and Glaciation; British Library Cataloguing: London, UK, 2010; ISBN 978-0-340-905791. [Google Scholar]
  54. Song, C.; Sheng, Y.; Ke, L.; Nie, Y.; Wang, J. Glacial lake evolution in the southeastern Tibetan Plateau and the cause of rapid expansion of proglacial lakes linked to glacial-hydrogeomorphic processes. J. Hydrol. 2016, 540, 504–514. [Google Scholar] [CrossRef]
  55. Wu, K.; Liu, S.; Xu, J.; Zhu, Y.; Liu, Q.; Jiang, Z.; Wei, J. Spatiotemporal variability of surface velocities of monsoon temperate glaciers in the Kangri Karpo Mountains, southeastern Tibetan Plateau. J. Glaciol. 2021, 67, 186–191. [Google Scholar] [CrossRef]
  56. Kavan, J.; Luláková, P.; Małecki, J.; Strzelecki, M.C. Capturing the transition from marine to land-terminating glacier from the 126-year retreat history of Nordenskiöldbreen, Svalbard. J. Glaciol. 2023, 1–11. [Google Scholar] [CrossRef]
  57. Sutherland, J.L.; Carrivick, J.L.; Gandy, N.; Shulmeister, J.; Quincey, D.J.; Cornford, S.L. Proglacial lakes control glacier geometry and behavior during recession. Geophys. Res. Lett. 2020, 47, e2020GL088865. [Google Scholar] [CrossRef]
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Figure 1. (a) Location of the Yigong Zangbo Basin on the Tibetan Plateau (the base map in this subgraph was a Google Earth image downloaded from BIGMAP); (b) the distribution of the glaciers within the basin (The SRTM DEM obtained from the United States Geological Survey (USGS) was used in this subgraph); (c) terminus location of the Jiongpu Co glacier (the Landsat 8 OLI image on 11 November 2020 that downloaded from USGS was used as base map in subgraph); (d) ice calved from the glacier terminus currently floating on the lake, taken on 1 August 2021; (e) Jiongpu Co glacier terminus, taken on 3 August 2019.
Figure 1. (a) Location of the Yigong Zangbo Basin on the Tibetan Plateau (the base map in this subgraph was a Google Earth image downloaded from BIGMAP); (b) the distribution of the glaciers within the basin (The SRTM DEM obtained from the United States Geological Survey (USGS) was used in this subgraph); (c) terminus location of the Jiongpu Co glacier (the Landsat 8 OLI image on 11 November 2020 that downloaded from USGS was used as base map in subgraph); (d) ice calved from the glacier terminus currently floating on the lake, taken on 1 August 2021; (e) Jiongpu Co glacier terminus, taken on 3 August 2019.
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Figure 2. (a) Diagram of mass change within a lake-terminating glacier, solid and dash green lines represent the glacier surface and frontal position at t1, and the red lines represent the glacier surface and frontal position at t2; (b) the location of the flux gate and the region where glacier retreat was observed during the investigation period (the Landsat 8 OLI image on 22 December 2020 that downloaded from USGS was used as base map in this subgraph).
Figure 2. (a) Diagram of mass change within a lake-terminating glacier, solid and dash green lines represent the glacier surface and frontal position at t1, and the red lines represent the glacier surface and frontal position at t2; (b) the location of the flux gate and the region where glacier retreat was observed during the investigation period (the Landsat 8 OLI image on 22 December 2020 that downloaded from USGS was used as base map in this subgraph).
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Figure 3. The area changes in the Jiongpu Co glacier and lake from 1967 to 2020.
Figure 3. The area changes in the Jiongpu Co glacier and lake from 1967 to 2020.
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Figure 4. The change in the surface elevation of Jiongpu Co glacier in 1985–2020 and land-terminating glaciers in 2000–2020.
Figure 4. The change in the surface elevation of Jiongpu Co glacier in 1985–2020 and land-terminating glaciers in 2000–2020.
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Figure 5. Scatter diagram of the glacier surface elevation change rate versus the elevation of the land-terminating glaciers and Jiongpu Co glacier in Yigong Zangbo Basin. The different colored lines indicate the mean changes in all the land-terminating in 2000–2020, Jiongpu co glacier in 1985–2020, 2020–2010, and 2010–2020.
Figure 5. Scatter diagram of the glacier surface elevation change rate versus the elevation of the land-terminating glaciers and Jiongpu Co glacier in Yigong Zangbo Basin. The different colored lines indicate the mean changes in all the land-terminating in 2000–2020, Jiongpu co glacier in 1985–2020, 2020–2010, and 2010–2020.
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Figure 6. Box plots of the surface velocity of the Jiongpu Co glacier and land-terminating glaciers from 1987 to 2018. The red dash lines represent the trend of velocity change.
Figure 6. Box plots of the surface velocity of the Jiongpu Co glacier and land-terminating glaciers from 1987 to 2018. The red dash lines represent the trend of velocity change.
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Figure 7. Distribution of the velocity of land-terminating glaciers and the Jiongpu Co glacier in 1987–2018 along the center flow line from the equilibrium-line altitude (ELA) to glacier terminus (a total of 18 land-terminating glaciers, with an area greater than or equal to 10 km2, were included in the statistics. The ELA altitude of the Jiongpu Co glacier is 5050 m. The ELA altitude of the land-terminating glaciers calculated one by one, ranging from 4200 m to 5400 m).
Figure 7. Distribution of the velocity of land-terminating glaciers and the Jiongpu Co glacier in 1987–2018 along the center flow line from the equilibrium-line altitude (ELA) to glacier terminus (a total of 18 land-terminating glaciers, with an area greater than or equal to 10 km2, were included in the statistics. The ELA altitude of the Jiongpu Co glacier is 5050 m. The ELA altitude of the land-terminating glaciers calculated one by one, ranging from 4200 m to 5400 m).
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Table 1. Net mass loss and its two components (frontal ablation and net surface mass loss) of the Jiongpu Co glacier from 1985 to 2020.
Table 1. Net mass loss and its two components (frontal ablation and net surface mass loss) of the Jiongpu Co glacier from 1985 to 2020.
PeriodNet Mass Loss
M t (Gt)		Frontal AblationNet Surface Mass Loss
A f (Gt)Proportion (%) M s Proportion (%)
1985–20000.57 ± 0.230.15 ± 0.0126.30.42 ± 0.2273.7
2000–20100.62 ± 0.050.27 ± 0.0143.50.35 ± 0.0456.5
2010–20201.06 ± 0.060.55 ± 0.0251.90.51 ± 0.0448.1
Total2.25 ± 0.340.97 ± 0.0443.11.28 ± 0.356.9
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Zhao, X.; Cheng, J.; Guan, W.; Zhang, Y.; Cao, B. The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985. Remote Sens. 2024, 16, 762. https://doi.org/10.3390/rs16050762

AMA Style

Zhao X, Cheng J, Guan W, Zhang Y, Cao B. The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985. Remote Sensing. 2024; 16(5):762. https://doi.org/10.3390/rs16050762

Chicago/Turabian Style

Zhao, Xuanru, Jinquan Cheng, Weijin Guan, Yuxuan Zhang, and Bo Cao. 2024. "The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985" Remote Sensing 16, no. 5: 762. https://doi.org/10.3390/rs16050762

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