|dc.description.abstract||Mountain glaciers play a crucial role in the global provision of water resources. The majority of these glaciers are retreating rapidly in response to anthropogenic climate change, posing serious risks to downstream communities, many of which are located in some of the most socio-economically vulnerable regions on Earth. Consequently, accurate simulations of the future behaviour of mountain glaciers are critical in facilitating effective planning and water resource management over the 21st century.
One fifth of the Earth’s largest glaciers (> 2 km2) are substantially covered by a layer of rocky material, known as supraglacial debris. This material alters the melt rates of the ice beneath, making the behaviour of debris-covered glaciers significantly harder to predict and limiting the ability of models to forecast effectively the impacts on downstream water resources.
This thesis aims to contribute towards an improved understanding of debris-covered glacier behaviour through the development and application of novel remote sensing techniques which utilise data collected by satellites and uncrewed aerial vehicles (UAVs). The major findings that stem from this thesis are presented as three results chapters.
The first results chapter (presented as Chapter 3) utilises recently-acquired satellite-derived datasets to estimate the surface-mass-balance gradients of the largest glaciers within five regions of High Mountain Asia. A key finding is that, on the ablation zones of debris-covered glaciers, there are distinctive reversed surface-mass-balance gradients which were previously concealed from geodetic studies of ice-surface lowering. More generally, this work emphasises the importance of quantifying the
distinctive contributions of ice-flow dynamics and surface mass balance towards the distributed mass changes of debris-covered glaciers, in order to better constrain their melt rates in glaciological models.
The second results chapter (Chapter 4) tests the application of high-resolution thermal UAV imagery to simulate spatially-distributed debris thicknesses and sub-debris melt rates on Llaca Glacier, a debris-covered glacier in the Peruvian Andes. The results demonstrate that appropriately-calibrated thermal UAV imagery can be used, in conjunction with meteorological data and thermal measurements within the debris layer, to provide more precise estimates of supraglacial debris thickness. Additionally, this work indicates large differences between the sub-debris melt rates simulated using UAV-derived and satellite-derived debris thicknesses, demonstrating the importance of further high-resolution data acquisition on debris-covered glaciers in order to parameterise better their complex melt patterns.
The final results chapter (Chapter 5) utilises high-resolution visible and thermal UAV imagery to explore the behaviour of supraglacial ice cliffs on Llaca Glacier. Surface energy balance modelling is used to quantify the contribution of ice-cliff backwasting towards overall melt rates on a portion of the glacier tongue. The findings show that aspect plays a crucial role in controlling the development of ice cliffs, with southwest-facing ice cliffs surviving preferentially over others. The results also show that ice-cliff backwasting contributes disproportionately towards the overall ablation of Llaca Glacier, demonstrating the importance of further high-resolution studies of tropical debris-covered glaciers in order to calibrate glacio-hydrological models effectively.
Overall, this thesis provides proofs-of-concepts for emerging methods that can be used to monitor debris-covered glaciers based on recently-available remote sensing datasets and UAV data-collection techniques. Future research to develop these techniques further, and apply them to multiple glaciers within different regions, will facilitate improved model calibration and better estimates of future runoff from debris-covered glaciers in mountain regions.||en