ALBERT

Description: The rapid development and instability of moraine-dammed proglacial lakes is increasing the potential for the occurrence of catastrophic Glacial Lake Outburst Floods (GLOFs) in high-mountain regions. Advanced, physically-based numerical dam-breach models represent an improvement over existing methods for the derivation of breach outflow hydrographs. However, significant uncertainty surrounds the initial parameterisation of such models, and remains largely unexplored. We use a unique combination of numerical dam-breach and two-dimensional hydrodynamic modelling, employed with a Generalised Likelihood Uncertainty Estimation (GLUE) framework to quantify the degree of equifinality in dam-breach model output for the reconstruction of the failure of Dig Tsho, Nepal. Monte Carlo analysis was used to sample the model parameter space, and morphological descriptors of the moraine breach were used to evaluate model performance. Equifinal breach morphologies were produced by parameter ensembles associated with differing breach initiation mechanisms, including overtopping waves and mechanical failure of the dam face. The material roughness coefficient was discovered to exert a dominant influence over model performance. Percentile breach hydrographs derived from cumulative distribution function hydrograph data under- or overestimated total hydrograph volume and were deemed to be inappropriate for input to hydrodynamic modelling. Our results support the use of a Total Variation Diminishing solver for outburst flood modelling, which was found to be largely free of numerical instability and flow oscillation. Routing of scenario-specific optimal breach hydrographs revealed prominent differences in the timing and extent of inundation. A GLUE-based method for constructing likelihood-weighted maps of GLOF inundation extent, flow depth, and hazard is presented, and represents an effective tool for communicating uncertainty and equifinality in GLOF hazard assessment. However, future research should focus on the utility of the approach for predictive, as opposed to reconstructive GLOF modelling.

Description: Multi-temporal and fine resolution topographic data products are being increasingly used to quantify surface elevation change in glacial environments. In this study, we employ 3-D digital elevation model (DEM) differencing to quantify the topographic evolution of a blue-ice moraine complex in front of Patriot Hills, Heritage Range, Antarctica. Terrestrial laser scanning (TLS) was used to acquire multiple topographic datasets of the moraine surface at the beginning and end of the austral summer season in 2012/2013 and during a resurvey field campaign in 2014. A complementary topographic dataset was acquired at the end of season 1 through the application of Structure-from-Motion (SfM) photogrammetry to a set of aerial photographs taken from an unmanned aerial vehicle (UAV). Three-dimensional cloud-to-cloud differencing was undertaken using the Multiscale Model to Model Cloud Comparison (M3C2) algorithm. DEM differencing revealed net uplift and lateral movement of the moraine crests within season 1 (mean uplift ∼ 0.10 m), with lowering of a similar magnitude in some inter-moraine depressions and close to the current ice margin. Our results indicate net uplift across the site between seasons 1 and 2 (mean 0.07 m). This research demonstrates that it is possible to detect dynamic surface topographical change across glacial moraines over short (annual to intra-annual) timescales through the acquisition and differencing of fine-resolution topographic datasets. Such data offer new opportunities to understand the process linkages between surface ablation, ice flow, and debris supply within moraine ice.

Description: The instability of moraine-dammed proglacial lakes creates the potential for catastrophic glacial lake outburst floods (GLOFs) in high-mountain regions. In this research, we use a unique combination of numerical dam-breach and two-dimensional hydrodynamic modelling, employed within a generalised likelihood uncertainty estimation (GLUE) framework, to quantify predictive uncertainty in model outputs associated with a reconstruction of the Dig Tsho failure in Nepal. Monte Carlo analysis was used to sample the model parameter space, and morphological descriptors of the moraine breach were used to evaluate model performance. Multiple breach scenarios were produced by differing parameter ensembles associated with a range of breach initiation mechanisms, including overtopping waves and mechanical failure of the dam face. The material roughness coefficient was found to exert a dominant influence over model performance. The downstream routing of scenario-specific breach hydrographs revealed significant differences in the timing and extent of inundation. A GLUE-based methodology for constructing probabilistic maps of inundation extent, flow depth, and hazard is presented and provides a useful tool for communicating uncertainty in GLOF hazard assessment.