The dynamics of supraglacial ponds in the Everest region, central Himalaya
The dynamics of supraglacial pond development in the Everest region are not well constrained at a glacier scale, despite their known importance for meltwater storage, promoting ablation, and transmitting thermal energy englacially during drainage events. Here, we use fine-resolution (~0.5–2m) satell...
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Veröffentlicht in: | Global and planetary change 2016-07, Vol.142, p.14-27 |
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Sprache: | eng |
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Zusammenfassung: | The dynamics of supraglacial pond development in the Everest region are not well constrained at a glacier scale, despite their known importance for meltwater storage, promoting ablation, and transmitting thermal energy englacially during drainage events. Here, we use fine-resolution (~0.5–2m) satellite imagery to reveal the spatiotemporal dynamics of 9340 supraglacial ponds across nine glaciers in the Everest region, ~2000–2015. Six of our nine study glaciers displayed a net increase in ponded area over their observation periods. However, large inter- and intra-annual changes in ponded area were observed of up to 17% (Khumbu Glacier), and 52% (Ama Dablam) respectively. Additionally, two of the fastest expanding lakes (Spillway and Rongbuk) partially drained over our study period. The Khumbu Glacier is developing a chain of connected ponds in the lower ablation area, which is indicative of a trajectory towards large lake development. We show that use of medium-resolution imagery (e.g. 30m Landsat) is likely to lead to large classification omissions of supraglacial ponds, on the order of 15–88% of ponded area, and 77–99% of the total number of ponds. Fine-resolution imagery is therefore required if the full spectrum of ponds that exist on the surface of debris-covered glaciers are to be analysed.
•Inter- and intra-annual pond area changes were up to 17% and 52% respectively.•Spillway and Rongbuk lakes declined in area, attributed to drainage reorganisation.•Khumbu Glacier is developing a series of connected ponds on the lower ablation area.•9340 ponds were classified using fine-resolution satellite imagery.•Coarser-resolution imagery cannot capture the pond size distributions encountered. |
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ISSN: | 0921-8181 1872-6364 |
DOI: | 10.1016/j.gloplacha.2016.04.008 |