Surging Dynamics of Glaciers in the Hunza Valley under an Equilibrium Mass State since 1990

Wu, Kunpeng; Liu, Shiyin; Jiang, Zongli; Zhu, Yanzi; Xie, Fuming; Gao, Yongpeng; Yi, Ying; Tahir, Adnan Ahmad; Saifullah, Muhammad

doi:10.3390/rs12182922

Cited by 26 publications

(13 citation statements)

References 57 publications

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“…where GSD is the displacement measured between each image pair, T i is the interval between the image pair in days, and T y is a constant of 365. Due to the limitations of the clear surface features of optical satellite images, the detection of mountain glacier motion inevitably has the problem of decorrelation, e.g., variable snow-cover [26]. To reduce these impacts, we smoothed the displacement map using a Gaussian low pass filter with a kernel size of 3 × 3.…”

Section: Velocity Mappingmentioning

confidence: 99%

“…It is difficult to evaluate DEM data errors through field measurements because of harsh glacier environments and poor accessibility [56]. Assuming that the heights in non-glacier areas remain essentially unchanged for long periods, the mean elevation differences (MED) and standard deviation (SD) in non-glacier areas can be used to estimate the glacier height change errors [26]. In order to reduce the autocorrelation error, a distance value of 600 m was chosen for the difference map derived from TOPO DEM, SRTM DEM, and ASTER DEM [57].…”

Section: Glacier Surface Elevation Changesmentioning

confidence: 99%

“…Some studies have also suggested that both thermal and hydrological controls are significant in the Pamir [25]. Surging has been widely studied at either a regional scale or the glacier scale across the Karakoram, e.g., the Hunza Basin [26], Khurdopin glacier [27], and Kyagar glacier [28]. Recently, Bhambri and others [8] produced an inventory of surging in the Karakoram, identifying 221 STGs using a wide variety of observations spanning the period 1840-2017.…”

Section: Introductionmentioning

confidence: 99%

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The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

Gao

Liu

et al. 2022

Remote Sensing

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Glacier surges (GSs) are a manifestation of glacier instability and one of the most striking phenomena in the mountain cryosphere. Here, we utilize optical images acquired between 1973 and 2021 to map changes in glacier surface velocity and morphology and characterize differences in surface elevation using multi-source DEMs in the Tuanjie Peak (TJP), located in the Qilian Mountains (QLMs). These data provide valuable insights into the recent dynamic evolution of glaciers and hint at how they might evolve in the next few years. We identified a confirmed surge-type glacier (STG), three likely STGs, and three possible STGs. Our observations show that TJP GSs are generally long-term, although they are shorter in some cases. During the active phase, all glaciers exhibit thickened reservoir areas and thinned receiving areas, or vice-versa. The ice volume transfer was between 0.11 ± 0.13 × 107 m3 to 5.71 ± 0.69 × 107 m3. Although it was impossible to obtain integrated velocity profiles throughout the glacier surge process due to the limitations of available satellite imagery, our recent observations show that winter velocities were much higher than summer velocities, suggesting an obvious correlation between surge dynamics and glacial hydrology. However, the initiation and termination phase of GSs in this region was slow, which is similar to Svalbard-type STGs. We hypothesize that both thermal and hydrological controls are crucial. Moreover, we suggest that the regional warming trend may potentially increase glacier instability and the possibility of surge occurrence in this region.

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Section: Velocity Mappingmentioning

confidence: 99%

Section: Glacier Surface Elevation Changesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

Gao

Liu

et al. 2022

Remote Sensing

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“…The ELA is signi cantly affected by the local topography and climate change. Thus, the changes in the climate past and present-day can be monitored and understood from ELA (Donghui et al, 2017;Wu et al, 2020). The studies of the palaeo-glacier reconstructions conclude that the ELA of the glacier is in equilibrium the with climate.…”

Section: Introductionmentioning

confidence: 99%

Estimation of glacier mass balance using remote sensing and GIS technology in the Hindu Kush region of northern Pakistan

et al. 2023

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The Hindu Kush range of northern Pakistan has a large variety of Alpine and valley glaciers. These glaciers are subjected to volumetric changes owing to a host of factors (i.e., altitude, slope, glacier types, and aspect). The geodetic survey and eld-based data are not available for assessment of glacier's ELA for the Hindu Kush due to rough topography and rigorous climate. However, the mass balance of the alpine and valley glaciers can be obtained through Equilibrium Line Altitude (ELA) and Accumulation Area Ratio (AAR). Therefore, this study deals with the estimation of ELA, the hypsometrically controlled methods based on AAR and Accumulation Area Balance Ratio (AABR). The various ratio of AAR and AABR is applied to obtain the glacier ELAs of valley glaciers. AAR-ELAs are estimated based on ratios between 0.4-0.8 with 0.05 interval a d 0.67-4.4 with 0.01 for AABR-ELAs Moreover, the glacier contours with the interval of 50 m ± 5 m are employed for these estimations. This technique adjusted glacier hypsometry and area with the constant AAR ratio (rather than constant glacier area) to calculate the ELA variations. The results show that for AAR (0.5), 50m ELA declined from 5409 to 5359 m and reducing 4% the geometric area. The maximum decrease of 150 m ELA for these glaciers is reported for the AAR-AABR ratio 0.1-4.4, showing a signi cant decrease. The estimated decrease in the glacier area of Hindu-Kush glaciers is extremely variable speci cally in Phargam, Khorabohr and Gordoghan.

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“…Due to global warming in recent decades, changes in glacier-related resources and hazards present threats to the safety of critical infrastructure and the sustainable livelihoods of local 65 communities living within the basin (Immerzeel et al, 2020;Bazai et al, 2021;Gao et al, 2021). In the past few decades, remote sensing-based mass balance, glacier flow, and surge or advance characteristics indicate that the glaciers in Karakoram are exhibiting anomalous behaviour (Hewitt, 2005;Kaab et al, 2012;Bolch et al, 2017;Dehecq et al, 2018;Farinotti et al, 2020;Wu et al, 2020;Wu et al, 2021). 70…”

Section: Introductionmentioning

confidence: 99%

Interdecadal glacier inventories in the Karakoram since the 1990s

Xie

Liu

Gao

et al. 2022

Preprint

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Abstract. Multi-temporal glacier inventories provide key information about the glaciers, their characteristics and changes and are inevitable for glacier modelling and investigating geodetic mass changes. However, to date, no consistent multi-tempo glacier inventory for the whole of the Karakoram exists, negatively affecting the monitoring of spatiotemporal variations of glaciers’ geometric parameters and their related applications. We used a semi-automatic method combining automatic segmentation and manual correction and produced multi-temporal Karakoram glacier inventories (KGI) compiled from Landsat TM/ETM+/OLI images for the 1990s, 2000s, 2010s, and 2020s. Our assessments using independent multiple digitization of 37 glaciers show that the KGI is sufficiently accurate, with an overall uncertainty of ±3.68 %. We also performed uncertainty evaluation for the contiguous glacier polygons using a buffer of half a pixel, which resulted in an average mapping uncertainty of ±3.68 %. We calculated more than 20 attributes for each glacier, including coordinates, area, supraglacial debris area, date information, and topographic parameters derived from the ASTER GDEM. According to the KGI-2020, approximately 10500 alpine glaciers (> 0.01 km2 each) cover an area of 22510 ± 828 km2 of which 10.18 ± 0.38 % (2290 ± 84 km2) are covered by supraglacial debris. Over the past three decades, the glaciers experienced a loss of clean ice/snow area but a gain in supraglacial debris. Supraglacial debris cover has increased by 17.63 ± 1.44 % (343.30 ± 27.95 km2) while non-debris-covered glaciers decreased by 1.56 ± 0.0.24 % (319.85 ± 49.92 km2). The total glacier area was relatively stable and showed only a slight insignificant increase of 23.45 ± 28.85 km2 (0.10 ± 0.13 %). The glacier area has declined by 3.27 ± 0.24 % in the eastern Karakoram while the glacier area slightly increased in central (0.65 ± 0.10 %) and western Karakoram (1.26 ± 0.11 %). Supraglacial debris has increased over whole Karakoram, especially in areas above 4200 m a.s.l., showing an upward shift. The glacier area changes were characterized by strong spatial heterogeneity, influenced by surging and advancing glaciers. However, due to global warming, the glaciers are on average retreating. This is in particular true for small and debris-free glaciers. The multi-temporal KGI data are available at the National Cryosphere Desert Data Center of China: https://doi.org/10.12072/ncdc.glacier.db2386.2022 (Xie et al., 2022a).

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Surging Dynamics of Glaciers in the Hunza Valley under an Equilibrium Mass State since 1990

Cited by 26 publications

References 57 publications

The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains

Estimation of glacier mass balance using remote sensing and GIS technology in the Hindu Kush region of northern Pakistan

Interdecadal glacier inventories in the Karakoram since the 1990s

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