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Debris-covered glaciers in the Himalaya play an important role in the high-altitude water cycle. The thickness of the debris layer is a key control of the melt rate of those glaciers, yet little is known about the relative importance of the three potential sources of debris supply: the rockwalls, the glacier bed and the lateral moraines. In this study, we hypothesize that mass movement from the lateral moraines is a significant debris supply to debris-covered glaciers, in particular when the glacier is disconnected from the rockwall due to downwasting. To test this hypothesis, eight high-resolution and accurate digital elevation models from the lateral moraines of the debris-covered Lirung Glacier in Nepal are used. These are created using structure from motion (SfM), based on images captured using an unmanned aerial vehicle between May 2013 and April 2018. The analysis shows that mass transport results in an elevation change on the lateral moraines with an average rate of −0.31±0.26 m year−1 during this period, partly related to sub-moraine ice melt. There is a higher elevation change rate observed in the monsoon (−0.39±0.74 m year−1) than in the dry season (−0.23±0.68 m year−1). The lower debris aprons of the lateral moraines decrease in elevation at a faster rate during both seasons, probably due to the melt of ice below. The surface lowering rates of the upper gullied moraine, with no ice core below, translate into an annual increase in debris thickness of 0.08 m year−1 along a narrow margin of the glacier surface, with an observed absolute thickness of approximately 1 m, reducing melt rates of underlying glacier ice. Further research should focus on how large this negative feedback is in controlling melt and how debris is redistributed on the glacier surface.

This study aims at developing and applying a spatially-distributed coupled glacier mass balance and ice-flow model to attribute the response of glaciers to natural and anthropogenic climate change. We focus on two glaciers with contrasting surface characteristics: a debris-covered glacier (Langtang Glacier in Nepal) and a clean-ice glacier (Hintereisferner in Austria). The model is applied from the end of the Little Ice Age (1850) to the present-day (2016) and is forced with four bias-corrected General Circulation Models (GCMs) from the historical experiment of the CMIP5 archive. The selected GCMs represent region-specific warm-dry, warm-wet, cold-dry, and cold-wet climate conditions. To isolate the effects of anthropogenic climate change on glacier mass balance and flow runs from these GCMs with and without further anthropogenic forcing after 1970 until 2016 are selected. The outcomes indicate that both glaciers experience the largest reduction in area and volume under warm climate conditions, whereas area and volume reductions are smaller under cold climate conditions. Simultaneously with changes in glacier area and volume, surface velocities generally decrease over time. Without further anthropogenic forcing the results reveal a 3% (9%) smaller decline in glacier area (volume) for the debris-covered glacier and a 18% (39%) smaller decline in glacier area (volume) for the clean-ice glacier. The difference in the magnitude between the two glaciers can mainly be attributed to differences in the response time of the glaciers, where the clean-ice glacier shows a much faster response to climate change. We conclude that the response of the two glaciers can mainly be attributed to anthropogenic climate change and that the impact is larger on the clean-ice glacier. The outcomes show that the model performs well under different climate conditions and that the developed approach can be used for regional-scale glacio-hydrological modeling.

Glaciers in the high mountains of Asia (HMA) make a substantial contribution to the water supply of millions of people1, 2, and they are retreating and losing mass as a result of anthropogenic climate change3 at similar rates to those seen elsewhere4, 5. In the Paris Agreement of 2015, 195 nations agreed on the aspiration to limit the level of global temperature rise to 1.5 degrees Celsius ( °C) above pre-industrial levels. However, it is not known what an increase of 1.5 °C would mean for the glaciers in HMA. Here we show that a global temperature rise of 1.5 °C will lead to a warming of 2.1 ± 0.1 °C in HMA, and that 64 ± 7 per cent of the present-day ice mass stored in the HMA glaciers will remain by the end of the century. The 1.5 °C goal is extremely ambitious and is projected by only a small number of climate models of the conservative IPCC’s Representative Concentration Pathway (RCP)2.6 ensemble. Projections for RCP4.5, RCP6.0 and RCP8.5 reveal that much of the glacier ice is likely to disappear, with projected mass losses of 49 ± 7 per cent, 51 ± 6 per cent and 64 ± 5 per cent, respectively, by the end of the century; these projections have potentially serious consequences for regional water management and mountain communities.

Many glaciers throughout the Himalayas are debris covered, which substantially alters the melt processes. Though the extent of these glaciers is well studied, there is less information available of the debris thickness. This debris thickness is spatially variable, and partly caused by sediment transport processes from the slopes adjacent to the glacier. To quantify and understand these processes field data was analyzed and based on these insights a simple erosion-transport model was developed. Using UAV images and DEMs from April 2013 to May 2017, the amount of erosion and the causing processes could be distinguished. Erosion rates on the moraine are 0.25 m yr-1, which almost completely happens during the wet season. Debris flows and sediment entrainment by water flow are the processes here. The lower loose part of the moraine moves downslope with a velocity of 0.5- 1.5 m yr-1. This may be caused by solifluction or large slumping processes. Furthermore, smaller slumps and small rockfalls also contribute to the sediment transport down the moraine. The model calculates that the average debris extent outward from the moraine is approximately 30 m, covering in total 22% of the glacier surface with an average thickness of 2.2 m. This is in sharp contrast with the fact that the glacier is currently entirely covered in debris. Not all the debris is thus derived from the lateral moraines.

Ice cliffs potentially contribute considerably to the glacier mass balance, as melt enhancement on ice cliffs was observed by multiple recent studies. However, quantification of ice cliff melt is still in its infancy. Distributed models are still very computationally intensive and no methodology exists that allows for the direct measurement of ice cliff backwasting. This study therefore developed a new methodology to directly measure ice cliff backwasting on high-resolution UAV imagery with the Multiscale Model to Model Cloud Comparison (M3C2) algorithm. Two sets of experiments showed that a normal scale of 20 m in combination with a horizontal constraint of the normals in average backwasting direction resulted in accurate cliff backwasting values. The technique allowed cliff-to-cliff measurements with a RMSE of only 0.4 m. Backwasting patterns were generated for five cliffs on the Nepalese Langtang glacier for the period May 2014 - October 2015, which revealed an average backwasting rate of 10.5 m a-1. The rate is 13 times higher than the average ablation of 0.8 m a-1 on this part of the glacier tongue and could be an important explanation for the observed debris-cover anomaly. The backwasting rate varied considerably among different parts of the cliffs and between different cliffs, which could be well explained by the influence of aspect and supraglacial ponds. Supraglacial ponds caused a consistent positive melt gradient from cliff top to base, indicating a large role of thermal erosion in the ablation and development of ice cliffs. The M3C2 algorithm was applied to an additional cliff on Lirung glacier, which showed similar backwasting values as found by previous studies on that cliff. The methodology developed in this study is faster and probably less complex than other studies measuring or modelling ice cliff backwasting. The temporal and spatial scalability of the methodology will improve accurate assessment of a glacier’s mass balance: the melt contribution

Debris-covered glaciers in the Himalayas are relatively unstudied due to the difficulties in fieldwork caused by the inaccessible terrain and the presence of debris layers, which complicate in situ measurements. To overcome these difficulties an unmanned aerial vehicle (UAV) has been deployed multiple times over two debris covered glaciers in the Langtang catchment, located in the Nepalese Himalayas. Using differential GPS measurements and the Structure for Motion algorithm the UAV imagery was processed into accurate high-resolution digital elevation models and orthomosaics for both pre- and post-monsoon periods. These data were successfully used to estimate seasonal surface flow and mass wasting by using cross-correlation feature tracking and DEM differencing techniques. The results reveal large heterogeneity in mass loss and surface flow over the glacier surfaces, which are primarily caused by the presence of surface features such as ice cliffs and supra-glacial lakes. Accordingly, we systematically analyze those features using an object-based approach and relate their characteristics to the observed dynamics. We show that ice cliffs and supra-glacial lakes are contributing to a significant portion of the melt water of debris covered glaciers and we conclude that UAVs have great potential in understanding the key surface processes that remain largely undetected by using satellite remote sensing.

Recent studies have shown that the application of unmanned aerial vehicles (UAVs) has great potential to investigate the dynamic behavior of glaciers. The studies have successfully deployed UAVs over generally contrast-rich surfaces of debris-covered glaciers and highly crevassed bare ice glaciers. In this study, the potential of UAVs in glaciology is further exploited, as we use a fixed-wing UAV over the largely snow-covered Storbreen glacier in Norway in September 2015. The acquired UAV-imagery was processed into accurate digital elevation models and image mosaics using a Structure from Motion workflow. Georeferencing of the data was obtained by ingesting ground control points into the workflow that were accurately measured with a differential global navigation satellite system (DGNSS). Geodetic accuracy was determined by comparison with DGNSS surface profiles and stake positions that were measured on the same day. The processed data were compared with a LIDAR survey and airborne imagery acquisition from September and October 2009 to examine mass loss patterns and glacier retreat. Results show that the UAV is capable of producing high-quality elevation models and image mosaics for the low-contrast snow-covered Storbreen at unprecedented detail. The accuracy of the output product is lower when compared to contrast-rich debris-covered glaciers, but still considerably more accurate than spaceborne data products. Comparison with LIDAR data shows a spatially heterogeneous downwasting pattern of about 0.75 m a−1 over 2009–2015 for the upper part of Storbreen. The lower part exhibits considerably more downwasting in the range of 0.9–2.1 m a −1 . We conclude that UAVs can be valuable for surveys of snow-covered glaciers to provide sufficient accurate elevation models and image mosaics, and we recommend the use of UAVs for the routine monitoring of benchmark glaciers such as Storbreen.

Mass losses originating from supraglacial ice cliffs at the lower tongues of debris-covered glaciers are a potentially large component of the mass balance, but have rarely been quantified. In this study, we develop a method to estimate ice cliff volume losses based on high-resolution topographic data derived from terrestrial and aerial photogrammetry. We apply our method to six cliffs monitored in May and October 2013 and 2014 using four different topographic datasets collected over the debris-covered Lirung Glacier of the Nepalese Himalayas. During the monsoon, the cliff mean backwasting rate was relatively consistent in 2013 (3.8 ± 0.3 cm w.e. d−1) and more heterogeneous among cliffs in 2014 (3.1 ± 0.7 cm w.e. d−1), and the geometric variations between cliffs are larger. Their mean backwasting rate is significantly lower in winter (October 2013–May 2014), at 1.0 ± 0.3 cm w.e. d−1. These results are consistent with estimates of cliff ablation from an energy-balance model developed in a previous study. The ice cliffs lose mass at rates six times higher than estimates of glacier-wide melt under debris, which seems to confirm that ice cliffs provide a large contribution to total glacier melt.

The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin's water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members.

In this thesis, insight is gained in the discharge distribution and channel evolution of meandering distributaries in the Ganges Delta by the development of a method that extracts channels from satellite imagery and that analyses the channel geometry. This focus is part of a project of the Utrecht University Physical Geography Department about the Ganges-Brahmaputra delta and is aimed at unravelling a small part of the delta to gain knowledge about the larger scale. To support the methodology and to compare and interpret the results of this study a comprehensive literature overview is presented additionally. The image analysis is performed with eCognition Developer 8 software and comprises segmenting a Landsat 5 TM image using six different segmentation scales. Meander objects are delineated by classifying the objects based on shape characteristics. The small meander objects from the different segmentation scales are merged into one dataset containing objects that represent large parts of the channel network. The skeletons of the objects are processed to obtain channel centerlines. The geometry of the centerlines is analysed in MATLAB to obtain inflection points that are used to approximate meander wavelength. This is used to determine discharges and sinuosities of the channels. Larger scale meandering present in the general course of numerous rivers in the area is analysed by fitting a cubic spline through the inflection points and determining the inflections of the spline. The methods that are developed in the study are successfully able to nearly automatically delineate meander objects, merge objects into large channel representations and obtain channel centerlines. Furthermore, it is proven that the used extraction methods yield the possibility to obtain river and discharge dynamics by analysing the centerline geometry. The discharge data that results from the analysis seems relatively accurate, taking into account the many potential sources of error of the meth