Dr. Mauro Werder

A quantitative understanding of how sediment discharge from subglacial fluvial systems varies in response to glaciohydrological conditions is essential for understanding marine systems around Greenland and Antarctica and for interpreting sedimentary records of cryosphere evolution. Here we develop a graph-based approach, Graphical Subglacial Sediment Transport (GraphSSeT), to model subglacial fluvial sedimentary transport using subglacial hydrology model outputs as forcing. GraphSSeT includes glacial erosion of bedrock and a dynamic sediment model with exchange between the active transport system and a basal sediment layer. Sediment transport considers transport-limited and supply-limited regimes and includes stochastically evolving grain size, network-scale flow management, and tracking of detrital provenance. GraphSSeT satisfies volume balance and sediment velocity and transport capacity constraints on flow. GraphSSeT is demonstrated for synthetic scenarios that probe the impact of variations in hydrological, geological, and glaciological characteristics on sediment transport over multi-diurnal to seasonal time frames. For steady-state hydrology scenarios on seasonal timescales, we find a primary control from the scale and organisation of the channelised hydrological flow network. The development of grain-size-dependent selective transport is identified as the major secondary control. Non-steady-state hydrology is tested on multi-diurnal timescales for which sediment discharge scales with peak water input, leading to increased sediment discharge compared to the steady state. Subglacial hydrology models are being applied more broadly, and GraphSSeT extends this capacity to quantitatively define the volume, grain-size distribution, and detrital characteristics of sediment discharge that through comparison with the sediment record may enable improved knowledge of the glaciohydrological system and its impact on marine systems.

As climate warms, hydrology and geomorphology in glacierized catchments are evolving, changing sediment export from these catchments, thus impacting downstream ecosystems and communities. Currently, much uncertainty persists regarding interactions among geomorphic processes that evacuate sediment from glacierized catchments. Here, we present a catchment-scale numerical model of subglacial and proglacial sediment transport with debris meltout processes. We apply the model in a Monte Carlo framework to suspended sediment data collected over 2014–2020 from the Fieschertal catchment in the Swiss Alps, assessing possible combinations of geomorphic processes responsible for suspended sediment discharge. The ensemble of model outputs quantifies the interaction of different geomorphic processes, including the trade-off between bedrock erosion and sediment previously stored in the catchment. Model runs suggest that, at some periods, up to 20% of the sediment leaving the glacier is deposited in the proglacial area relative to the catchment's total sediment discharge. This shows that the model captures the proglacial area change from sediment source to sediment sink in different hydrological and glaciological conditions. Furthermore, the findings highlight the impact of glacier retreat on the catchment's sediment dynamics, which both reduces the proglacial area's slope and introduces additional sediment to the proglacial area through debris meltout. The model outputs and the parameters quantify the interaction among geomorphic processes, yielding key insights into the drivers of sediment transport in alpine regions. The implications of these interactions are discussed in the context of interpreting processes responsible for controlling erosion rates from glacierized regions and modeling sediment transport in glacierized catchments.

Subglacial hydrology models struggle to reproduce seasonal drainage patterns that are consistent with observed subglacial water pressures and surface velocities. We modify the standard sheet-flow parameterization within a coupled sheet–channel subglacial drainage model to smoothly transition between laminar and turbulent flow based on the locally computed Reynolds number in a physically consistent way (the "transition" model). We compare the transition model to standard laminar and turbulent models to assess the role of the sheet-flow parameterization in reconciling observed and modelled water pressures under idealized and realistic forcing. Relative to the turbulent model, the laminar and transition models improve seasonal simulations by increasing winter water pressure and producing a more prominent late-summer water pressure minimum. In contrast to the laminar model, the transition model remains consistent with its own internal assumptions across all flow regimes. Based on the internal consistency of the transition model and its improved performance relative to the standard turbulent model, we recommend its use for transient simulations of subglacial drainage.

Global climate warming leads to ever-increasing glacier mass loss. Pine Island Glacier in Antarctica is one of the largest contributors to global sea level rise (SLR). One of the biggest uncertainties in the assessment of glacier contribution to SLR at present are subglacial hydrology processes which are less well known than other ice dynamical processes. We use the Glacier Drainage System (GlaDS) model which couples both distributed and channelized components to simulate the basal hydrology of Pine Island Glacier with basal sliding and meltwater production taken from a full-Stokes Elmer/Ice model fitting observed surface velocities. We find ≈100 km long Rothlisberger channels up to 26 m in diameter extending up glacier from the grounding line along the main trunk of Pine Island Glacier delivering 51 m³ s⁻¹ of fresh water to the grounding line. Channelization occurs at high water pressure because of high basal melt rates (maximum of 1 m a⁻¹) caused by high rates of shear heating in regions with fast ice flow (>1000 m a⁻¹). We simulate a shallow “swamp” of 0.8 m water depth where flow transitions from a distributed system into the channels. We performed a set of 38 sensitivity experiments varying sheet and channel conductivity over 4 orders of magnitude. We find a threshold behavior in distributed sheet conductivity above which basal water pressures are unaffected by changing channel conductivities. Our findings suggest a strong need to better understand controls on basal water conductivity through the distributed system. This issue is critical to improve model-based predictive capability for the Pine Island Glacier and, more generally, the Antarctic Ice Sheet.

Active subglacial lakes provide a rare glimpse of the subglacial environment and hydrological processes at play. Several studies contributed to establishing active subglacial lake inventories and document lake drainage and connection, but few focused on the period between lake drainage when the melt production and transport contribute to the refilling of these lakes. In this study, we employ high-resolution CryoSat-2 altimetry data from 2010 to 2021 to compile an inventory of recharging lakes across Antarctica. We extract recharge rates from these lakes, which serve as a lower limit on subglacial melt production. These recharge rates are compared against predictions obtained by routing modelled subglacial meltwater at the ice-sheet's base. Our findings indicate that modelled recharge rates are consistent with observations in all but one of the investigated lakes, providing a lower bound on geothermal heat fluxes. Lake Cook E2 displays recharge rates far exceeding predictions, indicating that processes are taking place that are currently unaccounted for. Considering recharge in hydrologically connected lake networks instead of individually provides a stricter constraint on melt production. Recharge rates extracted from the Thwaites Lake system suggest that subglacial melt production has been underestimated.

The englacial and subglacial drainage systems exert key controls on glacier dynamics. However, due to their inaccessibility, they are still only poorly understood and more detailed observations are important, particularly to validate and tune physical models describing their dynamics. By creating artificial glacier moulins - boreholes connected to the subglacial drainage system and supplied with water from surface streams - we present a novel method to monitor the evolution of an englacial hydrological system with high temporal resolution. Here, we use artificial moulins as representations for vertical, pressurised, englacial R-channels. From tracer and pressure measurements, we derive time series of the hydraulic gradient, discharge, flow speed and channel cross-sectional area. Using these, we compute the Darcy-Weisbach friction factor, obtaining values which increase from 0.1 to 13 within five days of channel evolution. Furthermore, we simulate the growth of the cross-sectional area using different temperature gradients. The comparison to our measurements largely supports the common assumption that the temperature follows the pressure melting point. The deviations from this behaviour are analysed using various heat transfer parameterisations to assess their applicability. Finally, we discuss how artificial moulins could be combined with glacier-wide tracer experiments to constrain parameters of subglacial drainage more precisely.

Knowing the ice thickness distribution of a glacier is of fundamental importance for a number of applications, ranging from the planning of glaciological fieldwork to the assessments of future sea-level change. Across spatial scales, however, this knowledge is limited by the paucity and discrete character of available thickness observations. To obtain a spatially coherent distribution of the glacier ice thickness, interpolation or numerical models have to be used. Whilst the first phase of the Ice Thickness Models Intercomparison eXperiment (ITMIX) focused on approaches that estimate such spatial information from characteristics of the glacier surface alone, ITMIX2 sought insights for the capability of the models to extract information from a limited number of thickness observations. The analyses were designed around 23 test cases comprising both real-world and synthetic glaciers, with each test case comprising a set of 16 different experiments mimicking possible scenarios of data availability. A total of 13 models participated in the experiments. The results show that the inter-model variability in the calculated local thickness is high, and that for unmeasured locations, deviations of 16% of the mean glacier thickness are typical (median estimate, three-quarters of the deviations within 37% of the mean glacier thickness). This notwithstanding, limited sets of ice thickness observations are shown to be effective in constraining the mean glacier thickness, demonstrating the value of even partial surveys. Whilst the results are only weakly affected by the spatial distribution of the observations, surveys that preferentially sample the lowest glacier elevations are found to cause a systematic underestimation of the thickness in several models. Conversely, a preferential sampling of the thickest glacier parts proves effective in reducing the deviations. The response to the availability of ice thickness observations is characteristic to each approach and varies across models. On average across models, the deviation between modeled and observed thickness increase by 8.5% of the mean ice thickness every time the distance to the closest observation increases by a factor of 10. No single best model emerges from the analyses, confirming the added value of using model ensembles.

Our understanding of the subglacial drainage system has improved markedly over the last decades due to field observations and numerical modelling. However, integrating data into increasingly complex numerical models remain challenging. Here we infer two-dimensional subglacial channel networks and hydraulic parameters for Gorner Glacier, Switzerland, based on available field data at five specific times (snapshots) across the melt season of 2005. The field dataset is one of the most complete available, including borehole water pressure, tracer experiments and meteorological variables. Yet, these observations are still too sparse to fully characterize the drainage system and thus, a unique solution is neither expected nor desirable. We use a geostatistical generator and a steady-state water flow model to produce a set of subglacial channel networks that are consistent with measured water pressure and tracer-transit times. Field data are used to infer hydraulic and morphological parameters of the channels under the assumption that the location of channels persists during the melt season. Results indicate that it is possible to identify locations where subglacial channels are more likely. In addition, we show that different network structures can equally satisfy the field data, which support the use of a stochastic approach to infer unobserved subglacial features.

The glacier-dammed Lac des Faverges, located on Glacier de la Plaine Morte (Swiss Alps), has drained annually as a glacier lake outburst flood since 2011. In 2018, the lake volume reached more than 2 × 10⁶ m³, and the resulting flood caused damage to the infrastructure downstream. In 2019, a supraglacial channel was dug to artificially initiate a surface lake drainage, thus limiting the lake water volume and the corresponding hazard. The peak in lake discharge was successfully reduced by over 90 % compared to 2018. We conducted extensive field measurements of the lake-channel system during the 48 d drainage event of 2019 to characterize its hydraulics and thermodynamics. The derived Darcy–Weisbach friction factor, which characterizes the water flow resistance in the channel, ranges from 0.17 to 0.48. This broad range emphasizes the factor's variability and questions the choice of a constant friction factor in glacio-hydrological models. For the Nusselt number, which relates the channel-wall melt to the water temperature, we show that the classic, empirical Dittus–Boelter equation with the standard coefficients does not adequately represent our measurements, and we propose a suitable pair of coefficients to fit our observations. This hints at the need to continue research into how heat transfer at the ice–water interface is described in the context of glacial hydraulics.

Subglacial hydrological systems require innovative technological solutions to access and observe. Wireless sensor platforms can be used to collect and return data, but their performance in deep and fast-moving ice requires quantification. We report experimental results from Cryoegg: a spherical probe that can be deployed into a borehole or moulin and transit through the subglacial hydrological system. The probe measures temperature, pressure and electrical conductivity in situ and returns all data wirelessly via a radio link. We demonstrate Cryoegg's utility in studying englacial channels and moulins, including in situ salt dilution gauging. Cryoegg uses VHF radio to transmit data to a surface receiving array. We demonstrate transmission through up to 1.3 km of cold ice-a significant improvement on the previous design. The wireless transmission uses Wireless M-Bus on 169 MHz; we present a simple radio link budget model for its performance in cold ice and experimentally confirm its validity. Cryoegg has also been tested successfully in temperate ice. The battery capacity should allow measurements to be made every 2 h for more than a year. Future iterations of the radio system will enable Cryoegg to transmit data through up to 2.5 km of ice.

Accurate estimations of ice thickness and volume are indispensable for ice flow modelling, hydrological forecasts and sea-level rise projections. We present a new ice thickness estimation model based on a mass-conserving forward model and a Bayesian inversion scheme. The forward model calculates flux in an elevation-band flow-line model, and translates this into ice thickness and surface ice speed using a shallow ice formulation. Both ice thickness and speed are then extrapolated to the map plane. The model assimilates observations of ice thickness and speed using a Bayesian scheme implemented with a Markov chain Monte Carlo method, which calculates estimates of ice thickness and their error. We illustrate the model's capabilities by applying it to a mountain glacier, validate the model using 733 glaciers from four regions with ice thickness measurements, and demonstrate that the model can be used for large-scale studies by fitting it to over 30 000 glaciers from five regions. The results show that the model performs best when a few thickness observations are available; that the proposed scheme by which parameter-knowledge from a set of glaciers is transferred to others works but has room for improvements; and that the inferred regional ice volumes are consistent with recent estimates.