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Liquid water can exist at temperatures well below freezing beneath glaciers and ice sheets, where subglacial water systems, fresh and saline, have been shown to host unique microbial ecosystems. Geophysical techniques sensitive to fluid-content contrasts, e.g. electromagnetics, can characterize subglacial water and its salinity. Here, we assess the ground-based transient electromagnetic (TEM) method for deriving the resistivity and salinity of subglacial water. We adapt an existing open-source Bayesian inversion algorithm, which uses independent depth constraints, to output posterior distributions of resistivity and pore fluid salinity with depth. A variety of synthetic models, including a thin (5 m), conductive (0.16 Ωm), hypersaline (147 psu) subglacial lake, are used to evaluate the TEM method for imaging under 800 m-thick ice. The study demonstrates that TEM methods can resolve conductive, saline bodies accurately using external depth constraints, for example, from radar or seismic data. The depth resolution of TEM can be limited beneath deep (>800 m), thick (>50 m) conductive, water bodies and additional constraints from passive electromagnetic (EM) methods could be used to reduce ambiguities in the TEM results. Subsequently, non-invasive active and passive EM methods could provide profound insights into remote aqueous systems under glaciers and ice sheets.

Fast ice flow is associated with the deformation of subglacial sediment. Seismic shear velocities, Vs, increase with the rigidity of material and hence can be used to distinguish soft sediment from hard bedrock substrates. Depth profiles of Vs can be obtained from inversions of Rayleigh wave dispersion curves, from passive or active-sources, but these can be highly ambiguous and lack depth sensitivity. Our novel Bayesian transdimensional algorithm, MuLTI, circumvents these issues by adding independent depth constraints to the inversion, also allowing comprehensive uncertainty analysis. We apply MuLTI to the inversion of a Rayleigh wave dataset, acquired using active-source (Multichannel Analysis of Surface Waves) techniques, to characterise sediment distribution beneath the frontal margin of Midtdalsbreen, an outlet of Norway's Hardangerjøkulen ice cap. Ice thickness (0–20 m) is constrained using co-located GPR data. Outputs from MuLTI suggest that partly-frozen sediment (Vs 500–1000 m s−1), overlying bedrock (Vs 2000–2500 m s−1), is present in patches with a thickness of ~4 m, although this approaches the resolvable limit of our Rayleigh wave frequencies (14–100 Hz). Uncertainties immediately beneath the glacier bed are <280 m s−1, implying that MuLTI cannot only distinguish bedrock and sediment substrates but does so with an accuracy sufficient for resolving variations in sediment properties.

The presence and nature of marine ice in ice shelves is important, yet difficult to determine. We present transient electromagnetic results spanning 10 km across a suture zone of Larsen C Ice Shelf (LCIS), Antarctica, supported by central borehole measurements. Our results indicate the presence of two ice‐shelf layers. The uppermost layer, ∼300 m thick, has resistivity 103−106 Ωm. We interpret this as meteoric ice, overlying a lower shelf layer 25–56 m thick with resistivity 3–20 Ωm, consistent with permeable basal marine ice. This reconstruction closely matches modeled marine‐ice thicknesses in the area. The porosity of this layer is 0.18–0.40, higher than measured farther down‐flow, suggesting the layer consolidates once formed. Within the upper layer at 78.5 m depth, we identify a 2.5 m thick layer, likely linked to brine infiltration. These heterogeneities in ice shelf properties should be accounted for in future LCIS stability assessments.

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 × 106 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.

Subglacial water modulates glacier-bed friction and therefore is of fundamental importance when characterising 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 transient (time-domain) electromagnetic (TEM) soundings, but these are often non-unique. Here, we adapt an existing Bayesian transdimensional algorithm (Multimodal Layered Transdimensional Inversion – MuLTI) to the inversion of TEM data using 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 ± 1000 %, with thickness 5–40 m, in turn underlain by a highly conductive basement (100 Ωm ± 15 %). High-resistivity material, 5×104 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 those from co-located seismic shear-wave velocity inversions to further reduce ambiguity in the hydrogeological interpretation of the subsurface, we propose a new 3-D interpretation in which the Midtdalsbreen subglacial material is partitioned into partially frozen sediment, frozen sediment/permafrost and weathered/fractured bedrock with saline water.