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In 2018 the first subglacial lake in the Canadian Arctic was proposed to exist beneath the Devon Ice Cap, based on the analysis of airborne radar data. Here, we report a new interpretation of the subglacial material beneath the Devon Ice Cap, supported by data acquired from multiple surface-based geophysical methods in 2022. The geophysical data recorded included 9 km of active-source seismic-reflection profiles, seven transient electromagnetic (TEM) soundings, and 17 magnetotellurics (MT) stations. These surface-based geophysical datasets were collected above the inferred locations of the subglacial lakes and show no evidence for the presence of subglacial water. The acoustic impedance of the subglacial material, estimated from the seismic data, is 9.49 ± 1.92 × 10 6 kg m -2 s -1 , comparable to consolidated or frozen sediment. The resistivity models obtained by inversion of both the TEM and MT measurements show the presence of highly resistive rock layers (1000–100 000 Ω m) directly beneath the ice. Re-evaluation of the airborne reflectivity data shows that the radar attenuation rates were likely overestimated, leading to an overestimation of the basal reflectivity in the original radar studies. Here, we derive new radar attenuation rates using the temperature- and chemistry-dependent Arrhenius equation, and when applied to correct the returned bed power, the bed power does not meet the basal reflectivity threshold expected over subglacial water. Thus, the radar interpretation is now consistent with the seismic and electromagnetic observations of dry or frozen, non-conductive basal material. [ABSTRACT FROM AUTHOR]

In 2018 the first subglacial lake in the Canadian Artic was proposed to exist beneath Devon Ice cap, based on the analysis of airborne radar data. Here, we report a new interpretation of the subglacial material beneath Devon Ice Cap, supported by data acquired from multiple surface-based geophysical methods in 2022. The geophysical data recorded included 9 km of active source seismic reflection profiles, 7 transient electromagnetic soundings and 17 magnetotellurics stations. These surface-based geophysical datasets were collected above the inferred locations of the subglacial lakes and show no evidence for the presence of subglacial water. The acoustic impedance of the subglacial material, estimated from the seismic data, is 9.49 ± 1.92 x 106 kg m-2 s-1, comparable to consolidated or frozen sediment. The resistivity models obtained by inversion of both the transient electromagnetic and magnetotelluric measurements show the presence of highly resistive rock layers (1000 – 100000 Ω.m) directly beneath the ice. Re-evaluation of the airborne reflectivity data show that the radar attenuation rates were likely overestimated, leading to an overestimation of the basal reflectivity in the original radar studies. Here, we derive new radar attenuation rates using the temperature- and chemistry-dependent Arrhenius equation, and when applied to correct the returned bed power, the bed power does not meet the basal reflectivity threshold expected over subglacial water. Thus, the radar interpretation is now consistent with the seismic and electromagnetic observations of dry or frozen, non-conductive basal material. [ABSTRACT FROM AUTHOR]

Distributed Acoustic Sensing (DAS) is increasingly recognised as a valuable tool for glaciological seismic applications, although analysing the large data volumes generated in acquisitions poses computational challenges. We show the potential of active-source DAS to image and characterise subglacial sediment beneath a fast-flowing Greenlandic outlet glacier, estimating the thickness of sediment layers to be 20–30 m. However, the lack of subglacial velocity constraint limits the accuracy of this estimate. Constraint could be provided by analysing cryoseismic events in a counterpart 3-day record of passive seismicity through, for example, seismic tomography, but locating them within the 9 TB data volume is computationally inefficient. We describe experiments with data compression using the frequency-wavenumber (f-k) transform ahead of training a convolutional neural network, that provides a ~300-fold improvement in efficiency. In combining active and passive-source and our machine learning framework, the potential of large DAS datasets could be unlocked for a range of future applications. [ABSTRACT FROM AUTHOR]

The density structure of firn has implications for hydrological and climate modelling and for ice shelf stability. The firn structure can be evaluated from depth models of seismic velocity, widely obtained with Herglotz-Wiechert inversion (HWI), an approach that considers the slowness of refracted seismic arrivals. However, HWI is appropriate only for steady-state firn profiles and the inversion accuracy can be compromised where firn contains ice layers. In these cases, Full Waveform Inversion (FWI) can be more successful than HWI. FWI extends HWI capabilities by considering the full seismic waveform and incorporates reflected arrivals, thus offering a more accurate estimate of a velocity profile. We show the FWI characterisation of the velocity model has an error of only 1.7% for regions (vs. 4.2% with HWI) with an ice slab (20 m thick, 40 m deep) in an otherwise steady-state firn profile. [ABSTRACT FROM AUTHOR]

Subglacial water influences the dynamics of ice masses. The state of subglacial pore water, whether liquid or frozen, is associated with differences in electrical resistivity that span several orders of magnitude, hence liquid water can be inferred from electrical resistivity depth profiles. Such profiles can be obtained from inversions of time domain electromagnetics (TEM) soundings, but these are often non-unique. Here, we adapt an existing Bayesian transdimensional algorithm ("MuLTI") to the inversion of TEM data constrained by independent depth constraints, to provide statistical properties and uncertainty analysis of the resistivity profile with depth. The method was applied to ground-based TEM data acquired on the terminus of the Norwegian glacier Midtdalsbreen, with depth constraints provided by co-located ground penetrating radar data. Our inversion shows that the glacier bed is directly underlain by material of resistivity 10² Ωm ± 100 %, with thickness 5-40 m, in turn underlain by a highly conductive basement (100 Ωm ± 15 %). High resistivity material, 5 x 104 Ωm ± 25 %, exists at the front of the glacier. All uncertainties are defined by the interquartile range of the posterior resistivity distribution. Combining these resistivity profiles with co-located seismic shear-wave velocity inversions to further reduce ambiguity in the hydro-geological interpretation of the subsurface, we propose a new 3D interpretation of the Midtdalsbreen subglacial material partitioned into partially frozen sediment, frozen sediment/permafrost and weathered/fractured bedrock with saline water. [ABSTRACT FROM AUTHOR]

Supra-glacial lakes and ponds can create hotspots of mass loss on debris-covered glaciers. While much research has been directed at understanding lateral lake expansion, little is known about the rates or processes governing lake deepening. To a large degree, this knowledge gap persists due to sparse observations of lake beds. Here we report on the novel use of ground penetrating radar (GPR) surveys to simultaneously collect supra-glacial lake bathymetry and bottom composition data from Spillway Lake (surface area of 2.4 × 105 m2; volume of 9.5 × 104 m3), which is located in the terminus region of the Ngozumpa Glacier in the Khumbu region of the Nepal Himalaya. We identified two GPR bottom signals corresponding to two sedimentary facies of (1) sub-horizontal layered fine sediment drape and (2) coarse blocky diamict. We provide an understanding of the changes in subaqueous debris distribution that occur through stages of lake expansion by combining the GPR results with in situ observations of shoreline deposits matching the interpreted facies. From this, we present an updated conceptual model of supra-glacial lake evolution, with the addition of data on the evolving debris environment, showing how dominant depositional processes can change as lakes evolve from perched lakes to multi-basin base-level lakes and finally onto large moraine-dammed lakes. Throughout lake evolution, processes such as shoreline steepening, lakebed collapse into voids and conduit interception, subaerial and subaqueous calving and rapid areal expansion alter the spatial distribution and makeup of lakebed debris and sediments forcing a number of positive and negative feedbacks on lake expansion. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]