Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Abstract

Supra-glacial debris cover is key to glacier ablation through increasing (thin debris layer) or decreasing (thick debris layer) melt rates, thereby regulating the mass balance of a glacier and its meltwater runoff. The thickening or lateral expansion of supra-glacial debris cover correlates with a reduction of glacier ablation and, consequently, runoff generation, which is also considered to be an influential factor on the rheology and dynamics of a glacierized system. Studies on supra-glacial debris cover have recently attracted wide attention especially for glaciers in the Himalayas and Karakoram, where the glaciers have heterogeneously responded to climate change. In this study, we used 32 images from the Landsat Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager archive, going back to 1990, which are available on the Google Earth Engine cloud-computing platform, to map the supra-glacial debris cover in the Hunza Valley, Karakoram, Pakistan, based on a band ratio segmentation method (normalized difference snow index [NDSI] < 0.4), Otsu thresholding, and machine learning algorithms. Compared with manual digitization, the random forest (RF) model was found to have the greatest accuracy in identifying supra-glacial debris, with a Kappa coefficient of 0.94 ± 0.01 and an overall accuracy of 95.5 ± 0.9%. Overall, the supraglacial debris cover in the study area showed an increasing trend, and the total area expanded by 8.1-21.3% for various glaciers from 1990 to 2019. The other two methods (Otsu thresholding and NDSI < 0.4) generally overestimated the supra-glacial debris covered area, by 36.3 and 18.8%, respectively, compared to that of the RF model. The supra-glacial debris cover has migrated upward on the glaciers, with intensive variation near the equilibrium-line altitude zone (4,500-5,500 m a.s.l.). The increase in ice or snow avalanche activity at high altitudes may be responsible for this upward expansion of supra-glacial debris cover in the Hunza Valley, which is attributed to the combined effect of temperature decrease and precipitation increase in the study area.

Surface composition of debris-covered glaciers across the Himalaya using spectral unmixing and multi-sensor imagery

“…While slope thresholds are region-dependent, the minimum slope obtained when filtering the debris covered glaciers by area is consistent with other areas, for ex. 6.7º in the Hunza (Xie et al, 2020a). Both the area and surface slope have a skewed distribution (Fig.…”

“…Glacier tongues here descend to lower elevations (~3,700 m to 4,400 m compared to ~ 4,700 to 4.900 m in the western part) which, in conjunction with the more humid, monsoon-influenced climate might favour vegetation growth. Development of vegetation (mostly shrubs) has been noted on stagnant, thick debris-covered tongues in other areas of the world (Xie et al, 2020a;Tampucci et al, 2016), and was found to be increasing in certain glacierized areas such as the Alps as a consequence to climatic change and declining glaciation (Vezzola et al, 2016). As vegetation typically will only develop on stagnant surfaces that are no longer undergoing substantial gravitational reworking, its presence is also an indication of glacier inactivity and later stages of decay.…”

“…Recent studies (i.e. Xie et al, 2020a;Xie et al, 2020b;Wangchuk and Bolch, 2020) demonstrated the potential of innovative machine learning techniques combined with freely available data such as Landsat to quantify the surface features of debris-covered glaciers. Applying such methods at large scales allow gaining a better understanding of the response of debris-covered glaciers to climate variability in terms of water resources and hazards.…”

Evolution of Surface Characteristics of Three Debris-Covered Glaciers in the Patagonian Andes From 1958 to 2020

“…r 0.64, r 2 0.41, adjusted r 2 0.37, F(1,17) 11.72 N 19 p-value March temp 0.003 Dependent variable: mean-SLA, independent variable December-January precipitation r 0.68, r 2 0.47, adjusted r 2 0.44, F(1,17) 14.95 N 19 p-value December-January precipitation 0.001 Dependent variable: mean-SLA, Independent variables: December-January precipitation, March temperature multiple r 0.77, r 2 0.6, adjusted r 2 0.55, F(2,16) 12.03 N 19 p-value December-January precipitation 0.01 March temp 0.03 Icefields, but also in the smaller mountain glaciers in their periphery. In recent decades, expansion of debris-covered ice areas has also been observed in the Himalayas, Karakorum (Bolch et al, 2008;Bhambri et al, 2011;Kirkbride and Deline, 2013;Xie et al, 2020), Caucasus (Tielidze et al, 2020) and the European Alps (Mölg et al, 2019), mostly at decadal to subdecadal scale.…”

Novel Machine Learning Method Integrating Ensemble Learning and Deep Learning for Mapping Debris-Covered Glaciers

“…Debris-covered glaciers are a special type of glacier [21,22]. The surfaces of mountain glaciers are frequently covered in supraglacial debris, whose spectral characteristics are similar to those of rocks and soil at the foot of the mountain [21,23], making them hard to distinguish from rock glaciers and periglacial areas [24]. Particularly in the Tibetan Plateau, owing to the influence of the monsoon climate, frequent cloud activity occurs during the glacier melting period.…”