Future glacial lakes in High Mountain Asia: an inventory and assessment of hazard potential from surrounding slopes
TL;DR: In this article, the authors present the first complete inventory for future glacial lakes in High Mountain Asia by computing the subglacial bedrock for ~100 000 glaciers and estimating overdeepening area, volume and impact hazard for the larger potential lakes.
Abstract: Bedrock overdeepenings exposed by continued glacial retreat can store precipitation and meltwater, potentially leading to the formation of new proglacial lakes. These lakes may pose threats of glacial lake outburst floods (GLOFs) in high mountain areas, particularly if new lakes form in geomorphological setups prone to triggering events such as landslides or moraine collapses. We present the first complete inventory for future glacial lakes in High Mountain Asia by computing the subglacial bedrock for ~100 000 glaciers and estimating overdeepening area, volume and impact hazard for the larger potential lakes. We detect 25 285 overdeepenings larger than 104 m2 with a volume of 99.1 ± 28.6 km3 covering an area of 2683 ± 773.8 km2. For the 2700 overdeepenings larger than 105 m2, we assess the lake predisposition for mass-movement impacts that could trigger a GLOF by estimating the hazard of material detaching from surrounding slopes. Our findings indicate a shift in lake area, volume and GLOF hazard from the southwestern Himalayan region toward the Karakoram. The results of this study can be used for anticipating emerging threats and potentials connected to glacial lakes and as a basis for further studies at suspected GLOF hazard hotspots.
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01 Dec 2011
TL;DR: In this article, the authors presented a first regional assessment of glacial lake distribution and evolution in the Himalaya (HKH) and selected seven sites between Bhutan and Afghanistan, to capture the climatic variability along the 2000 km long mountain range.
Abstract: In this study, we present a first regional assessment of glacial lake distribution and evolution in the Hindu Kush Himalaya (HKH). Seven sites have been selected between Bhutan and Afghanistan, to capture the climatic variability along the 2000-km long mountain range. For each site, glacial lakes have been mapped with LANDSAT satellite imagery acquired in 1990, 2000 and 2009, using an automatic classification. In the East (India, Nepal and Bhutan), glacial lakes are bigger and more numerous than in the West (Pakistan, Afghanistan), and have grown continuously between 1990 and 2009 by 20% to 65%. On the other hand, during the same period, the glacial lake coverage has shrunk in the Hindu Kush (−50%) and the Karakorum (−30%). This east/west pattern of lake changes seems in agreement with sparse glaciological measurements that suggest less (or even no) ice loss in the western part of the HKH.
13 citations
TL;DR: In this paper , the authors examined the performance of six widely used and mainly global-scale DEMs: AW3D30 (ALOS), SRTM-GL1 (Shuttle Radar Topography Mission Global 1-arcsecond; 30 m), NASADEM (NASA Digital Elevation Model; 30
Abstract: Abstract. Accurate estimates of regional ice thickness, which are generally produced by ice-thickness inversion models, are crucial for assessments of available freshwater resources and sea level rise. A digital elevation model (DEM) derived from surface topography of glaciers is a primary data source for such models. However, the scarce in situ measurements of glacier surface elevation limit the evaluation of DEM uncertainty. Hence the influence of DEM uncertainty on ice-thickness modeling remains unclear over the glacierized area of the Tibetan Plateau (TP). Here, we examine the performance of six widely used and mainly global-scale DEMs: AW3D30 (ALOS – Advanced Land Observing Satellite – World 3D – 30 m; 30 m), SRTM-GL1 (Shuttle Radar Topography Mission Global 1 arc second; 30 m), NASADEM (NASA Digital Elevation Model; 30 m), TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement, synthetic-aperture radar; 90 m), SRTM v4.1 (Shuttle Radar Topography Mission; 90 m), and MERIT (Multi-Error-Removed Improved-Terrain; 90 m) over the glacierized TP by comparison with ICESat-2 (Ice, Cloud and land Elevation Satellite) laser altimetry data while considering the effects of glacier dynamics, terrain factors, and DEM misregistration. The results reveal NASADEM to be the best performer in vertical accuracy, with a small mean error (ME) of 0.9 m and a root mean squared error (RMSE) of 12.6 m, followed by AW3D30 (2.6 m ME and 11.3 m RMSE). TanDEM-X also performs well (0.1 m ME and 15.1 m RMSE) but suffers from serious errors and outliers on steep slopes. SRTM-based DEMs (SRTM-GL1, SRTM v4.1, and MERIT) (13.5–17.0 m RMSE) had an inferior performance to NASADEM. Errors in the six DEMs increase from the south-facing to the north-facing aspect and become larger with increasing slope. Misregistration of the six DEMs relative to the ICESat-2 footprint in most glacier areas is small (less than one grid spacing). In a next step, the influence of six DEMs on four ice-thickness inversion models – GlabTop2 (Glacier bed Topography), Open Global Glacier Model (OGGM), Huss–Farinotti (HF), and Ice Thickness Inversion Based on Velocity (ITIBOV) – is intercompared. The results show that GlabTop2 is sensitive to the accuracy of both elevation and slope, while OGGM and HF are less sensitive to DEM quality and resolution, and ITIBOV is the most sensitive to slope accuracy. NASADEM is the best choice for ice-thickness estimates over the whole TP.
11 citations
TL;DR: A comprehensive overview of GLOF research can be found in this article , where the authors analyze 594 peer-reviewed GLOF studies published between 2017 and 2021 (Web of Science and Scopus databases).
Abstract: Abstract. Glacial lake outburst floods (GLOFs) are among the most
concerning consequences of retreating glaciers in mountain ranges worldwide.
GLOFs have attracted significant attention amongst scientists and
practitioners in the past 2 decades, with particular interest in the
physical drivers and mechanisms of GLOF hazard and in socioeconomic and other
human-related developments that affect vulnerabilities to GLOF events. This
increased research focus on GLOFs is reflected in the gradually increasing
number of papers published annually. This study offers an overview of recent
GLOF research by analysing 594 peer-reviewed GLOF studies published between
2017 and 2021 (Web of Science and Scopus databases), reviewing the content and
geographical focus as well as other characteristics of GLOF studies. This
review is complemented with perspectives from the first GLOF conference (7–9
July 2021, online) where a global GLOF research community of major
mountain regions gathered to discuss the current state of the art of
integrated GLOF research. Therefore, representatives from 17 countries
identified and elaborated trends and challenges and proposed possible ways
forward to navigate future GLOF research, in four thematic areas: (i) understanding GLOFs – timing and processes; (ii) modelling GLOFs and GLOF
process chains; (iii) GLOF risk management, prevention and warning; and (iv) human dimensions of GLOFs and GLOF attribution to climate change.
11 citations
TL;DR: Wang et al. as discussed by the authors developed a per-pixel composited method named the "multitemporal mean NDWI composite" to automatically extract the glacial lake area in HMA from 1990 to 2020 using time-series Landsat data.
Abstract: Changes in a large-scale glacial lake area directly reflect the regional glacier status and climate changes. However, long time series of glacial lake dataset and comprehensive investigation of the spatiotemporal changes in the glacial lake area in the whole High Mountain Asia (HMA) region remained elusive. Satellite remote sensing provides an indispensable way for dynamic monitoring of glacial lakes over large regions. But glacial lakes are quite small and discretely distributed, and the extraction of glacial lakes is usually influenced by clouds, snow/ice cover, and terrain shadows; thus, there is a lack of an automatic method to continuously monitor the dynamic changes of glacial lakes in a large scale. In this paper, we developed a per-pixel composited method named the “multitemporal mean NDWI composite” to automatically extract the glacial lake area in HMA from 1990 to 2020 using time-series Landsat data. There were 19,294 glacial lakes covering a total area of 1471.85 ± 366.42 km2 in 1990, and 22,646 glacial lakes with an area of 1729.08 ± 461.31 km2 in 2020. It is noted that the glacial lake area in the whole HMA region expanded by 0.58 ± 0.21%/a over the past three decades, with high spatiotemporal heterogeneity. The glacial lake area increased at a consistent speed over time. The fastest expansion was in East Kun Lun at an average rate of 2.01 ± 0.54%/a, while in the Pamir and Hengduan Shan, they show slow increases with rates of 0.33 ± 0.08%/a and 0.39 ± 0.01%/a, respectively, during 1990–2020. The greatest increase in lake area occurred at 5000-5200 m a.s.l., which increased by about 45 km2 (~25%). We conclude that the temperature rise and glacier thinning are the leading factors of glacial lake expansion in HMA, and precipitation is the main source of lake water increase in West Kun Lun. Using the proposed method, a large amount of Landsat images from successive years of melting seasons can be fully utilized to obtain a pixel-level composited cloud-free and solid snow/ice-free glacial lake map. The uncertainties from supraglacial ponds and glacial meltwater were also estimated to improve the reliability and comparability of glacial lake area changes among different regions. This study provides important technical and data support for regional climate changes, glacier hydrology, and disaster analysis.
11 citations
References
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TL;DR: The contemporary evolution of glaciers in the Himalayan region is reviewed, including those of the less well sampled region of the Karakoram to the Northwest, in order to provide a current, comprehensive picture of how they are changing.
Abstract: Himalayan glaciers are a focus of public and scientific debate. Prevailing uncertainties are of major concern because some projections of their future have serious implications for water resources. Most Himalayan glaciers are losing mass at rates similar to glaciers elsewhere, except for emerging indications of stability or mass gain in the Karakoram. A poor understanding of the processes affecting them, combined with the diversity of climatic conditions and the extremes of topographical relief within the region, makes projections speculative. Nevertheless, it is unlikely that dramatic changes in total runoff will occur soon, although continuing shrinkage outside the Karakoram will increase the seasonality of runoff, affect irrigation and hydropower, and alter hazards.
1,561 citations
TL;DR: Satellite laser altimetry and a global elevation model are used to show widespread glacier wastage in the eastern, central and south-western parts of the HKKH during 2003–08 and show indirect evidence of a complex pattern of glacial responses in reaction to heterogeneous climate change signals.
Abstract: Glaciers are among the best terrestrial climate indicators, an important water resource in mountains1,2 and a major contributor to global sea level rise3,4. In the Hindu Kush - Karakoram - Himalaya region (HKKH), a paucity of appropriate glacier data has prevented a comprehensive assessment of current regional mass balance5. However, there are indirect evidences of a complex pattern of glacial responses5-8 in reaction to heterogeneous climate change signals9. Here, we provide the first coherent data set of detailed glacier thickness changes over the HKKH during 2003-2009 by combining satellite laser altimetry and a global elevation model. In the eastern, central and south-western parts of the HKKH, glacier wastage is widespread with regional thinning rates up to 0.66 ± 0.09 m a-1 in the Jammu-Kashmir region. Conversely, in the Karakoram, glaciers are close to balance with only a slight thinning of 0.07 ± 0.04 m a-1. Regionally averaged thinning rates under debris-mantled ice are similar to those of clean ice despite insulation by debris covers. The 2003-2008 specific mass balance for our HKKH study region is -0.21 ± 0.05 m a-1 water equivalent (WE), significantly less negative than the global average of ~ -0.7 m a-1 WE for glaciers and ice caps4,10. This difference is mainly an effect of the balanced glacier mass budget in the Karakoram. The corresponding HKKH sea level contribution is +0.035 ± 0.009 mm a-1 amounting to 1% of the present-day sea level rise11. Our 2003-2008 mass budget of -12.8 ± 3.5 Gt a-1 is more negative than recent satellite gravimetry based estimates of -5 ± 6 Gt a-1 over 2003-2010 (ref. 12). For the mountain catchments of the Indus and Ganges basins13, the glacier imbalance contributes ~3.5% and ~2.0%, respectively, to the annual average river discharge13, and up to ~10% for the Upper Indus basin14.
961 citations
University of Colorado Boulder1, University of Alaska Fairbanks2, Dresden University of Technology3, University of Zurich4, Trent University5, Clark University6, Uppsala University7, University of Innsbruck8, Scott Polar Research Institute9, University of California, Los Angeles10, University of British Columbia11, University of Alberta12
TL;DR: The Randolph Glacier Inventory (RGI) as discussed by the authors is a collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance.
Abstract: The Randolph Glacier Inventory (RGI) is a globally complete collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance. The RGI was created with limited resources in a short period. Priority was given to completeness of coverage, but a limited, uniform set of attributes is attached to each of the � 198 000 glaciers in its latest version, 3.2. Satellite imagery from 1999-2010 provided most of the outlines. Their total extent is estimated as 726 800 � 34 000 km 2 . The uncertainty, about � 5%, is derived from careful single-glacier and basin-scale uncertainty estimates and comparisons with inventories that were not sources for the RGI. The main contributors to uncertainty are probably misinterpretation of seasonal snow cover and debris cover. These errors appear not to be normally distributed, and quantifying them reliably is an unsolved problem. Combined with digital elevation models, the RGI glacier outlines yield hypsometries that can be com- bined with atmospheric data or model outputs for analysis of the impacts of climatic change on glaciers. The RGI has already proved its value in the generation of significantly improved aggregate estimates of glacier mass changes and total volume, and thus actual and potential contributions to sea-level rise.
884 citations
TL;DR: The results shed light on the Nyainqentanglha and Pamir glacier mass changes, for which contradictory estimates exist in the literature, and provide crucial information for the calibration of the models used for projections of future glacier response to climatic changes.
Abstract: Glacier mass balances in High Mountain Asia are uncertain. Satellite stereo-imagery allows a spatially resolved estimate for about 92% of the glacierized area and yields a region-wide average of about 16 Gt yr−1 for 2000 to 2016.
614 citations
TL;DR: In this paper, the characteristics and basic features of precipitation on the Tibetan Plateau during an 11-yr period (2001-11) are described on monthly-to-annual time scales.
Abstract: Because of the scarcity of meteorological observations, the precipitation climate on the Tibetan Plateau and surrounding regions (TP) has been insufficiently documented so far. In this study, the characteristics and basic features of precipitation on the TP during an 11-yr period (2001–11) are described on monthly-to-annual time scales. For this purpose, a new high-resolution atmospheric dataset is analyzed, the High Asia Reanalysis (HAR), generated by dynamical downscaling of global analysis data using the Weather Research and Forecasting (WRF) model. The HAR precipitation data at 30- and 10-km resolutions are compared with both rain gauge observations and satellite-based precipitation estimates from the Tropical Rainfall Measurement Mission (TRMM). It is found that the HAR reproduces previously reported spatial patterns and seasonality of precipitation and that the high-resolution data add value regarding snowfall retrieval, precipitation frequency, and orographic precipitation. It is demonstrat...
561 citations