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How did late first-century Christians learn about the person and character of Jesus and attempt to imitate him? In many ways, their situation is not so different from the vast majority of mid-first-century Christ-followers who had never met Jesus or had regular access to anyone who had, including the large number who were evangelized or pastored by Paul of Tarsus. Paul had a solution to their problem: convinced that Christ lived in him, he advised them that, by imitating him (or, sometimes, his coworkers), they would imitate Christ. I propose that one moment of reception of this counsel is revealed in 1 Peter. Building on prior work that identifies this text as a late first-century pseudepigraphical work that exhibits dependence on a Pauline corpus, I argue that its author constructs much of his christological diction from Paul’s self-description (and his description of his coworkers), a method of learning Christ that the author has learned from Paul himself.

Seismic surveys are widely used to characterise the properties of glaciers, their basal material and conditions, and ice dynamics. The emerging technology of Distributed Acoustic Sensing (DAS) uses fibre optic cables as seismic sensors, allowing observations to be made at higher spatial resolution than possible using traditional geophone deployments. Passive DAS surveys generate large data volumes from which the rate of occurrence and failure mechanism of ice quakes can be constrained, but such large datasets are computationally expensive and time consuming to analyse. Machine learning tools can provide an effective means of automatically identifying seismic events within the data set, avoiding a bottleneck in the data analysis process.Here, we present a novel approach to machine learning for a borehole-deployed DAS system on Store Glacier, West Greenland. Data were acquired in July 2019, as part of the RESPONDER project, using a Silixa iDAS interrogator and a BRUsens fibre optic cable installed in a 1043 m-deep borehole. The data set includes controlled-source vertical seismic profiles (VSPs) and a 3-day passive record of cryoseismicity. To identify seismic events in this record, we used a convolutional neural network (CNN). A CNN is a deep learning algorithm and a powerful classification tool, widely applied to the analysis of images and time series data, i.e. to recognise seismic phases for long-range earthquake detection.For the Store Glacier data set, a CNN was trained on hand-labelled, uniformly-sized time-windows of data, focusing initially on the high-signal-to-noise-ratio seismic arrivals in the VSPs. The trained CNN achieved an accuracy of 90% in recognising seismic energy in new windows. However, the computational time taken for training proved impractical. Training a CNN instead to identify events in the frequency-wavenumber (f-k) domain both reduced the size of each data sample by a factor of 340, yet still provided accurate classification. This decrease in input data volume yields a dramatic decrease in the time required for detection. The CNN required only 1.2 s, with an additional 5.6 s to implement the f-k transform, to process 30 s of data, compared with 129 s to process the same data in the time domain. This suggests that f-k approaches have potential for real-time DAS applications.Continuing analysis will assess the temporal distribution of passively recorded seismicity over the 3 days of data. Beyond this current phase of work, estimated source locations and focal mechanisms of detected events could be used to provide information on basal conditions, internal deformation and crevasse formation. These new seismic observations will help further constrain the ice dynamics and hydrological properties of Store Glacier that have been observed in previous studies of the area.The efficiency of training a CNN for event identification in the f-k domain allows detailed insight to be made into the origins and style of glacier seismicity, facilitating further development to passive DAS instrumentation and its applications.

Traditionally interpretations assume that as magma-rich rift settings mature, the magmatism accommodates greater amounts of extension at the expense of mechanical deformation. However, the importance of faulting in the final stages of magma-rich rifting remains poorly constrained, with the data (e.g. structural geological mapping, seismic reflection and borehole data) from rifts near to break-up a rarity. The Danakil Depression (Northern Afar), is undergoing the final stages of continental break-up, thus providing the ideal natural laboratory to conduct high resolution, quantitative analysis on the architecture, extension and subsidence facilitated by faulting in an active rift setting before seafloor spreading initiates. >500 rift axis faults were identified using remote sensing data (satellite imagery, DEMs), with quantitative analysis showing an increase in fault density, length and connectivity away from magmatic segments. Kinematic and earthquake focal mechanism data demonstrate a transition from transtensional opening in the northern and central sub-regions of the rift to oblique opening in the southern Giulietti Plain and Tat-Ali sub-regions of the Danakil Depression. The oblique opening is attributed to the along-axis step between the Erta-Ale and Harak sub-regions. Integration of seismic reflection and borehole data with the mapped faults shows that extension is primarily accommodated by magmatism within the rift center, with faulting more significant towards the ends of the rift. ~30% of crustal extension is accommodated by axial faulting in areas of low magmatism, highlighting the importance of faulting even in the final stages of magma-rich rifting. Comparing our findings with spreading ridge morphology and structure, which is relevant due to the rift maturity and extensive magmatism present, we conclude that the Danakil Depression is in a transitional stage between continental rifting and seafloor spreading. Spatial changes in the importance of faulting and magmatism in accommodating extension, alongside rift morphology, resemble the relationships observed along spreading ridges. From our observations we have shown that axial faulting still plays a vital role in the final stages of break-up despite the increased importance of magmatism.

When modelling ice sheet and glacier dynamics, a consideration of basal conditions is essential. Bed topography, hydrology and materials provide important controls on ice flow; however, the materials underlying large sections of the polar ice sheets are unknown. Seismic amplitude-versus-offset (AVO) analysis provides a means of inferring glacier bed properties, namely acoustic impedance and Poisson's ratio, by measuring bed reflectivity as a function of incidence angle.However, existing methods of applying AVO to glaciology only consider the compressional-wave component of the wavefield and solutions suffer from non-uniqueness. This can be addressed using multi-component seismic datasets, in which a strong converted-wave arrival (downgoing compressional-wave energy converted to shear-wave energy upon reflection at the glacier bed) is often present. We present a method of jointly inverting compressional (PP) and converted-wave (PS) seismic data to improve constraint of glacier bed properties.Using synthetic data, we demonstrate that for typical survey geometries, joint inversion of PP- and PS-wave AVO data delivers better-constrained bed acoustic impedance and Poisson’s ratio estimates compared with PP-only inversion. Furthermore, joint inversion can produce comparably constrained results to PP inversion when using input data with a smaller range of incidence angles/offsets (0-30 degree incidence for joint inversion, versus 0-60 degrees for PP- only). This could simplify future field acquisitions on very thick ice, where obtaining data at large incidence angles is difficult.Joint AVO inversion therefore has the potential to improve identification of glacier bed materials and simplify field acquisitions of glacial AVO data. We also present preliminary results from Korff Ice Rise, West Antarctica, where better constraints on bed conditions can help improve our knowledge of ice sheet history in the Weddell Sea sector. Routine measurements of this kind will help constrain ice-sheet model inputs and reduce uncertainty in predictions of sea-level rise.

We present seismic measurements of the firn column at Korff Ice Rise, West Antarctica, including measurements of compressional- and shear-wave velocity and attenuation. We describe a modified spectral-ratio method of measuring the seismic quality factor (Q) based on analysis of diving waves, which enables us to characterise the attenuative structure of firn in greater detail than has previously been possible. The compressional-wave quality factor, Qp, increases from 20 ± 10 in the uppermost firn to 423 ± 260 between 77 and 86 m depth, and the shear-wave quality factor, Qs, increases from 16 ± 9 in the uppermost firn to 100 ± 87 between 49 and 64 m depth. Our modified spectral-ratio method aids the understanding of the seismic structure of firn and benefits characterisation of deeper glaciological targets, being particularly impactful for correcting reflection amplitudes in wide-angle seismic data.

The recognition of Distributed Acoustic Sensing (DAS) as a valuable tool for glaciological seismic applications is growing. However, besides the logistical challenges of installing fibre-optic cable, the volume of DAS data that can be collected in a field campaign poses computational challenges. In this paper, we show the potential of active-source DAS to image and characterise subglacial sediment, 20-30 m thick, beneath a fast-flowing Greenlandic outlet glacier, but highlight the difficulty of analysing a counterpart 3-day (9 TB) record of cryoseismicity. We describe experiments with data compression using the frequency-wavenumber (f-k) transform, that provides ~300-times improvement in the computational efficiency of the detection of cryoseismic events via a convolutional neural network. In combining active and passive-source and the machine learning framework, the potential of large DAS datasets can be unlocked for a range of future applications.

The density structure of firn has implications for hydrological and climate modelling, and ice shelf stability. The structure of firn 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 strictly 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) may yield more success than HWI. FWI extends HWI capabilities by considering the full seismic waveform and incorporates reflected arrivals. Using synthetic firn density profiles, assuming both steady- and non-steady-state accumulation, we show that FWI outperforms HWI for detecting ice slab boundaries (5-80 m thick, 5-80 m deep) and velocity anomalies within firn. FWI can detect slabs thicker than one wavelength (here, 20 m, assuming a maximum frequency of 60 Hz) but requires the starting velocity model to be accurate to ±2.5%. We recommend for field practice that the shallowest layers of velocity models are constrained with ground-truth data. Nonetheless, FWI shows advantages over established methods, and should be considered when the characterisation of firn ice slabs is the goal of the seismic survey.

IntroductionMobile health applications are increasingly being used in health and clinical research. SARS-CoV-2 has proven to have high infectivity, making outbreaks difficult to contain. Early detection can help prevent spread, but there is a need to develop easy-to-use screening tools that can help identify potential infection as early as possible. Here, we describe the development of a machine learning classifier that can predict SARS-CoV-2 PCR positivity using smartphone-submitted vital sign measurements.MethodsThe Fenland App study followed 2,199 UK participants using a smartphone application from August 2020 and for a minimum of six months. Participants completed a baseline questionnaire and then monthly questionnaires about SARS-CoV-2 status and vaccinations. Three times a week, participants provided measurements of their blood oxygen saturation, body temperature, and resting heart rate via a pulse oximeter, digital thermometer, and their smartphone. The participants participated in self initiated SARS-CoV-2 testing as per concurrent public health guidelines.We built predictive models SARS-CoV-2 PCR positivity status as obtained from national surveillance PCR test results.ResultsA total of 77 positive and 6,339 negative SARS-CoV-2 tests were recorded during the study. The final model achieved an ROC AUC of 0.695 ± 0.045. There was no difference in model performance when using 4, 8 or 12 weeks of baseline data before a SARS-CoV-2 test (F(2) = 0.80, p = 0.472). Addition of demographic or symptom information had no impact on model performance.ConclusionsUsing only three smartphone collected vital sign measurements, it is possible to predict SARS-CoV-2 PCR positivity, using a four week baseline period. Smartphone based remote monitoring of patient vital signs could allow for earlier screening for potential infections. This method could be applicable to any infectious disease that causes physiological changes in vital signs.

Recent studies highlight the potential of the drone platform forground-penetrating radar (GPR) surveying. Most guidance foroptimizing drone flight heights is based on maximizing the imagequality of target responses, but no study yet considers the impacton diffraction traveltimes. Strong GPR velocity contrasts acrossthe air-ground interface introduce significant refraction effectsthat distort diffraction hyperbolas and introduce errors into diffraction-based velocity analysis. The severity of these errors isexplored with synthetic GPR responses, using ray- and finite-difference approaches, and a field GPR data set acquired overa sequence of diffracting features buried up to 1 m depth.Throughout, GPR antennas with 1000 MHz center frequency areraised from the ground to heights

BACKGROUND The COVID-19 pandemic accelerated the interest in implementing mobile health (mHealth) in population-based health studies, but evidence is lacking on engagement and adherence in studies. We conducted a fully remote study for ≥6 months tracking COVID-19 digital biomarkers and symptoms using a smartphone app nested within an existing cohort of adults. OBJECTIVE We aimed to investigate participant characteristics associated with initial and sustained engagement in digital biomarker collection from a bespoke smartphone app and if engagement changed over time or because of COVID-19 factors and explore participants’ reasons for consenting to the smartphone substudy and experiences related to initial and continued engagement. METHODS Participants in the Fenland COVID-19 study were invited to the app substudy from August 2020 to October 2020 until study closure (April 30, 2021). Participants were asked to complete digital biomarker modules (oxygen saturation, body temperature, and resting heart rate [RHR]) and possible COVID-19 symptoms in the app 3 times per week. Participants manually entered the measurements, except RHR that was measured using the smartphone camera. Engagement was categorized by median weekly frequency of completing the 3 digital biomarker modules (categories: 0, 1-2, and ≥3 times per week). Sociodemographic and health characteristics of those who did or did not consent to the substudy and by engagement category were explored. Semistructured interviews were conducted with 35 participants who were purposively sampled by sex, age, educational attainment, and engagement category, and data were analyzed thematically; 63% (22/35) of the participants consented to the app substudy, and 37% (13/35) of the participants did not consent. RESULTS A total of 62.61% (2524/4031) of Fenland COVID-19 study participants consented to the app substudy. Of those, 90.21% (2277/2524) completed the app onboarding process. Median time in the app substudy was 34.5 weeks (IQR 34-37) with no change in engagement from 0 to 3 months or 3 to 6 months. Completion rates (≥1 per week) across the study between digital biomarkers were similar (RHR: 56,517/77,664, 72.77%; temperature: 56,742/77,664, 73.06%; oxygen saturation: 57,088/77,664, 73.51%). Older age groups and lower managerial and intermediate occupations were associated with higher engagement, whereas working, being a current smoker, being overweight or obese, and high perceived stress were associated with lower engagement. Continued engagement was facilitated through routine and personal motivation, and poor engagement was caused by user error and app or equipment malfunctions preventing data input. From these results, we developed key recommendations to improve engagement in population-based mHealth studies. CONCLUSIONS This mixed methods study demonstrated both high initial and sustained engagement in a large mHealth COVID-19 study over a ≥6-month period. Being nested in a known cohort study enabled the identification of participant characteristics and factors associated with engagement to inform future applications in population-based health research.

Subglacial bedforms such as mega-scale glacial lineations and drumlins are commonly thought to form during active ice flow. They are often present in deglaciated areas with various elongation ratios, consisting of different materials , information which led to the development of different formation theories. However, these exposed examples were formed not only by subglacial processes during glaciation but also altered by processes during and after deglaciation. Here, we analyse in-situ properties and topography beneath Rutford Ice Steam, a fast flowing ice stream in West Antarctica to evaluate current theoretical models of bedform formation. We present a combination of seismic and radar data, including high-resolution 3D radar topography covering the upstream end of a bedform. Data acquisition and processing of the high-resolution 3D radar dataset result in a horizontal resolution of 24 m along- and across-track and a vertical resolution of 12 m. Using seismic acoustic impedance and calibrated radar reflectivity subglacial properties of the bedforms as well as the surrounding area are identified.A depression around the upstream end of a 360 m wide, 50 m high and more than 13 km long bedform was observed for the first time analysing the high-resolution 3D radar topography. The depression consists of a deepening up to 45 m deep and 360 m wide and is seen to extend around 10.5 km downstream. Radar reflectivity reveals that the material the depression is excavated into at least partly consists of low porosity material. Radar reflectivity and seismic acoustic impedance along the bedform imply a stiffer upstream end which softens along flow. The subglacial topography and properties give evidence that the bedform and the depression are formed by a combination of erosional and depositional processes. Both processes are likely interlinked, as implied by the comparable volume of the moat and the bedform at the upstream end of the bedform. Based on these observations we support or reject common bedform formation theories beneath Rutford Ice Stream.

Basal properties beneath ice streams and glaciers are known to be a control for ice flow dynamics, hence knowledge of them is crucial for predicting sea level due to changes in glacial dynamics. Ba...

Climate change poses an imminent physical risk to cultural heritage sites and their surrounding landscape through intensifying environmental processes such as damaging wetting and drying cycles that disrupt archaeological preservation conditions, and soil erosion which threatens to expose deposits and alter the archaeological context of sites. In the face of such threats, geospatial techniques such as GIS, remote sensing, and spatial modelling have proved invaluable tools for archaeological research and cultural heritage monitoring. This paper presents the application of secondary multi-source and multi-temporal geospatial data within a processing framework to provide a comprehensive assessment of geophysical risk to the Roman fort of Magna, Carvoran, UK. An investigation into the ancient hydraulic system at Magna was carried out with analysis of vegetation change over time, and spatio-temporal analysis of soil erosion risk at the site. Due to COVID-19 restrictions in place at the time of this study, these analyses were conducted using only secondary data with the aim to guide further archaeological research, and management and monitoring strategies for the stakeholders involved. Results guided inferences about the ancient hydraulic system, providing insights regarding how to better manage the site at Magna in the future. Analysis of soil erosion allowed the identification of hot spot areas, indicating a future increase in rates of erosion at Magna and suggesting a seasonal period of higher risk of degradation to the site. Results have proven that freely available multi-purpose national-scale datasets are sufficient to create meaningful insights into archaeological sites where physical access to the site is inhibited. This infers the potential to carry out preliminary risk assessment to inform future site management practices.

The development of glacier karst at the margins of melting ice sheets produces\ud complex glaciofluvial sediment-landform assemblages that provide information on ice\ud sheet downwasting processes. We present the first combined geomorphological,\ud sedimentological and geophysical investigation of the Brampton Kame Belt, an\ud important glaciofluvial depositional zone at the centre of the last British-Irish Ice Sheet.\ud Ground-penetrating radar (GPR) data allow the broad scale internal architecture of\ud ridges (eskers) and flat-topped hills (ice-walled lake plains) to be determined at four\ud sites. In combination with sediment exposures, these provide information on lateral\ud and vertical variations in accretion styles, depositional boundaries, and grain size\ud changes. Building on existing work on the subject, we propose a refined model for the\ud formation of ice-walled lake plains resulting from the evolution and collapse of major\ud drainage axes into lakes as stable glacier karst develops during deglaciation. The\ud internal structure of esker ridges demonstrates variations in sedimentation that can be\ud linked to differences in ridge morphologies across the kame belt. This includes low\ud energy flow conditions and multiple accretion phases identified within large S-N \ud oriented esker ridges; and fluctuating water pressures, hyperconcentrated flows, and\ud significant deformation within a fragmented SW-NE oriented esker ridge. In\ud combination with updated geomorphological mapping, this work allows us to identify\ud two main styles of drainage within the kame belt: (1) major drainage axes aligned\ud broadly S-N that extend through the entire kame belt and collapsed into a chain of icewalled lakes; and (2) a series of smaller, fragmented SW-NE aligned esker ridges that\ud represent ice-marginal drainage as the ice sheet receded south-eastwards up the Vale\ud of Eden. Our study demonstrates the importance of integrated geomorphological,\ud sedimentological and geophysical investigations in order to understand complex and\ud polyphase glaciofluvial sediment-landform assemblages.

Ground-penetrating radar is widely used to provide highly resolved images of subsurface sedimentary structures, with implications for processes active in the vadose zone. Frequently overlooked among these structures are tunnels excavated by fossorial animals (e.g., moles). We present two repeated ground-penetrating radar surveys performed a year apart in 2016 and 2017. Careful three-dimensional data processing reveals, in each data set, a pattern of elongated structures that are interpreted as a subsurface mole tunnel network. Our data demonstrate the ability of three-dimensional ground-penetrating radar imaging to non-invasively delineate the small animal tunnels (similar to 5 cm diameter) at a higher spatial and geolocation resolution than has previously been achieved. In turn, this makes repeated surveys and, therefore, long-term monitoring possible. Our results offer valuable insight into the understanding of the near-surface and showcase a potential new application for a geophysical method as well as a non-invasive method of ecological surveying.

This chapter focuses on those characters in the work of Silas House who are both queer and in the Appalachian sense “quare”—this is, characters who are cast as different, gay, or “other.” Storyteller Adam Booth specifically deals with the characters like Serena and Paul in House’s fiction trilogy, character in his dramatic writing who are gay, and characters like Brennan in short stories like “Recruiters.” House’s gay, lesbian and queer characters reveal the range of Appalchian diversity and the range of acceptance of that diversity. Booth’s reading of House is whimsical, pointed, and refreshing as he looks at gender issues in the work of Silas House.

High-resolution observations from a 1043-m-deep borehole show highly variable ice properties and heterogeneous deformation., Measurements of ice temperature provide crucial constraints on ice viscosity and the thermodynamic processes occurring within a glacier. However, such measurements are presently limited by a small number of relatively coarse-spatial-resolution borehole records, especially for ice sheets. Here, we advance our understanding of glacier thermodynamics with an exceptionally high-vertical-resolution (~0.65 m), distributed-fiber-optic temperature-sensing profile from a 1043-m borehole drilled to the base of Sermeq Kujalleq (Store Glacier), Greenland. We report substantial but isolated strain heating within interglacial-phase ice at 208 to 242 m depth together with strongly heterogeneous ice deformation in glacial-phase ice below 889 m. We also observe a high-strain interface between glacial- and interglacial-phase ice and a 73-m-thick temperate basal layer, interpreted as locally formed and important for the glacier’s fast motion. These findings demonstrate notable spatial heterogeneity, both vertically and at the catchment scale, in the conditions facilitating the fast motion of marine-terminating glaciers in Greenland.

Across the UK, sandy beaches and dunes protect coastal infrastructure from waves and extreme water levels during large-scale storms, while providing important habitats and recreational opportunities. Understanding their long-term evolution is vital in managing their condition in a changing climate. Recently, ground-penetrating radar (GPR) methods have grown in popularity in geomorphological applications, yielding centimetre-scale resolution images of near-surface stratigraphy and structure, thus allowing landscape evolution to be reconstructed. Additionally, abrupt changes in palaeo-environments can be visualized in three dimensions. Although often complemented by core data, GPR allows interpretations to be extended into areas with minimal ground-truth control. Nonetheless, GPR data interpretation can be non-intuitive and ambiguous, and radargrams may not initially resemble the expected subsurface geometry. Interpretation can be made yet more onerous when handling the large 3D data volumes that are facilitated with modern GPR technology. Here we describe the development of novel semi-automated GPR feature-extraction tools, based on ‘edge detection’ and ‘thresholding’ methods, which detect regions of increased GPR reflectivity which can be applied to aid in the reconstruction of a range Quaternary landscapes. Since reflectivity can be related to lithological and/or pore fluid changes, the 3D architecture of the palaeo-landscape can be reconstructed from the features extracted from a geophysical dataset. We present 500 MHz GPR data collected over a buried Holocene coastal dune system in North Wales, UK, now reclaimed for use as an airfield. Core data from the site, reaching a maximum depth 2 m, suggest rapid vertical changes from sand to silty-organic units, and GPR profiles suggest similar lateral complexity. By applying thresholding methods to GPR depth slices, these lateral complexities are effectively and automatically mapped. Furthermore, automatic extraction of the local reflection power yields a strong correlation with the depth variation of organic content, suggesting it is a cause of reflectivity contrast. GPR-interpolated analyses away from core control thus offer a powerful proxy for parameters derived from invasive core logging. The GPR data collected at Llanbedr airfield highlight a complex dune system to a depth of 2.8 m, probably deposited in several phases over ~700 years, similar to elsewhere in North Wales.

Comprehensive descriptions of the seismic properties of glaciers and ice masses require that both compressional (P-) and shear (S-) wave components are considered. Among these properties is the seismic attenuation, expressed by the Quality Factor (Q). Q is valuable for two reasons: first, to correct measurements of seismic amplitude for wavelet propagation effects, as in reflection amplitude-versus-angle (AVA) studies. Second, Q is an indicator of ice properties such as temperature and impurity content, and laboratory/field studies of soils and geological materials suggests that the ratio of the compressional- and shear-wave quality factors, Qp/Qs, may indicate fluid saturation (particularly when considered jointly with the velocity ratio Vp/Vs). Thus, a measurement of Qp/Qs could usefully inform the hydrological structure of the firn and indicate variations in the density of the firn column. Despite its importance, few studies appear to have measured Qp in firn columns and none appear to have measured Qs in firn. Doing so for either compressional- or shear-wave arrivals is challenging, due to the ray paths followed by the diving wave first arrivals and their accurate representation in attenuation measurement methods. In preparation for an AVA study of bed properties at Korff Ice Rise, West Antarctica, we have used spectra of diving wave first arrivals and a modified spectral-ratio method to measure Qp and Qs as a function of depth in the firn column. Shot gathers with vertically oriented geophones at offsets of 2.5 - 1000m were used to measure Qp. For detecting the shear component, the geophones were oriented horizontally; in this configuration, diving and reflected shear phases were recorded with high signal-to-noise ratios. The variation of Q with depth is represented as discrete constant-Q layers with thicknesses between 6 and 27 m. Qp shows progressive increases in depth from 21 ± 3 in the uppermost 20 m (where Vp < 3000 m/s), to 246 ± 30 between 74 and 80 m depth (3750 m/s < Vp < 3770 m/s). Qs increases from 14 ± 4 in the uppermost 20m, to 80 ± 6 between 80 and 90m depth. The ratio Qp/Qs varies throughout the depths measured, from Qp/Qs ~ 1.5 at the surface, to Qp/Qs ~ 3 at 80 m. This is broadly consistent with previously quoted values, but the variation may imply that Qp/Qs is influenced by firn structure.Similar measurements at a variety of sites could help to inform a relationship between Qp, Qs and firn properties. In the immediate future, the measurement of Q in the firn will aid measurements of bed reflectivity, and help to determine the material properties of the ice-bed interface.

Peatlands have long been recognized as providing a wide range of ecosystem services valuable to humans. In recent decades their role in the global climate and particularly their importance in long-term carbon sequestration has come into focus. Peatlands and peat basins are an important carbon store globally, and are estimated to cover nearly 25% of the Scottish landscape: they constitute a significant carbon stock, but being able to accurately estimate the volume of peat stored in coastal basins, both locally and regionally, remains a time-consuming process. Traditional methods of investigating peat depth and volume involved the measurement of peat to depth of contact with a mineral horizon, such as sand. This process is conducted with a peat depth probe or corer, with the spatial density of measurements varying significantly with basin size. Volumetric assessments based on such measurements therefore require interpolation between control points, leading to unquantifiable errors particularly if the base of peat has significant and unrecorded topography. Geophysical methods, in particular the 3D application of ground-penetrating (GPR), offer a promising solution to improve the accuracy in basin volumetrics.In this paper, a 3D dataset of 100 MHz GPR data was acquired with a Mala Geosciences Rough Terrain system over a buried Holocene coastal environment near Arisaig, northwest Scotland. 3D surveying involves the acquisition of a suite of parallel GPR profiles, with a small profile separation to capture the full variability of subsurface structure. For this site, a profile was acquired every 0.5 m, over an area of 62 x 32 m. The site is also sampled by 39 boreholes, which record the base of peat between 1-3.2 m depth and indicate a peat volume of 3720 m3. By revealing the true topography of the base of the basin, the GPR data suggest that the borehole-derived volume is overestimated by almost 50%, and instead predict a basin volume of 2529 ± 200 m3. Of this, 2064 ± 200 m3 is classified as organic peat (81.6%) and the remaining 465 ± 200 m3 is marine clay (18.4%). The principal source of error in this estimate is in the constraint of the GPR velocity, required to convert the time-axis of the GPR dataset to depth. This was measured at 0.034 m/ns ± 8%.The acquisition of 3D GPR data is nonetheless time-consuming and requires precise positional control to locate the GPR antennas and avoid misinterpretation. Nonetheless, sufficient topographic information is captured even if the acquisition had recorded only every 5th GPR profile: for this downsampled dataset, the estimated basin volume is 2490 m3 ± 200 m3 (a difference of only 2.5% from the full 3D dataset). 3D survey methods, therefore, give confidence to a volumetric estimate, but the need for full-resolution 3D sampling can likely be relaxed. However, GPR surveys reveal subsurface variability that would be difficult to reconstruct from a sparse set of borehole observations. Nonetheless, some amount of borehole control is invaluable for validating the GPR data and providing ground-truth control of subsurface structure.

Glacier forelands contain valuable information on past glacier dynamics and associated climatic conditions, particularly at small mountain glaciers where responses to climate change are rapid. To maximize the potential of glacial landforms as palaeoclimate indicators, a thorough understanding of the controls on landform genesis and subsequent evolution is required. Traditionally, such landforms have been studied using glacial geological techniques such as sedimentary logging. While these provide valuable in situ information they have numerous limitations, namely poor availability and spatial extent of exposures. Near-surface geophysics provides an efficient and non-invasive means of studying subsurface conditions in numerous sedimentary settings, offering spatially extensive information on substrate material properties and architecture. However, the logistically challenging terrain, remote location and complex structure of proglacial environments has limited the development of geophysical techniques for studying the internal architecture of glacial landforms.Here, we explore the application of three geophysical methods to investigate proglacial substrates: ground penetrating radar (GPR), seismic refraction and multi-channel analysis of surface waves (MASW). Three sites with contrasting sediment properties were surveyed at the foreland of Midtdalsbreen glacier in southern Norway; (a) a 100 m2 area of glaciotectonised sandy sediments, (b) a ~2 m high lateral moraine ridge containing stratified silts, sands, and gravel and (c) a terminal moraine ridge with a peak crest height of ~5 m and an open blockwork of cobbles and boulders at its surface. At all sites, we deployed 25 MHz and 100 MHz GPR antennas and undertook seismic surveys with 50−75 m long geophone spreads and a sledge-hammer source to sample to target depths of around 10−15 m. Through comparing the results from sites (a) to (c), we assess the capabilities and limitations of each of the aforementioned techniques for proglacial substrate imaging and characterisation, we analyse how their performances vary across these settings and outline factors that contribute to a successful geophysical investigation. The ease of analysis and achievable investigation depths of the geophysical data and the applicability of seismic interpretation methods varied considerably depending on the surface terrain and structural complexity of the site. Our results show how the combination of GPR and seismic data can assist with the internal characterisation of glacial moraines when a relatively simple subsurface structure is present. However, basic seismic inversions likely lack the sophistication to resolve seismic structure in all but the simplest of layered models. We offer suggestions on how to optimise field time in more complex settings, where more sophisticated seismic inversion algorithms (e.g. tomography) or 3-D GPR surveys could be better-suited.Our experience should help advance the use of geophysics in proglacial studies. It should serve as a guide for future survey planning, and help avoid typical pitfalls such that field time can be optimised. It is hoped that geophysical survey methods will play an increasing role in the understanding of proglacial sedimentary landforms and their associated palaeoenvironments.

Distributed acoustic sensing (DAS) involves detecting seismic energy from the deformation of a length of optical fibre cable, offers considerable potential in the high-resolution monitoring of glacier systems. Subglacial conditions and sediment properties exert a strong control on the basal sliding rate of glaciers, but identifying the connectivity of drainage pathways and their hydraulic conductivity remains poorly understood. This is due in part to the limitations of instrumental methods to monitor these processes accurately, whether by locating cryoseismic emissions in passive seismic records or actively imaging the subglacial environment in seismic reflection surveys. Here, we explore the application of a borehole survey geometry for constraining the thickness and distribution of subglacial sediment deposits around a DAS installation on Greenland’s Store Glacier.Store Glacier is a fast-moving outlet of the Greenland Ice Sheet. The instrumented borehole is drilled near the centre of a drained supraglacial meltwater lake, 28 km upstream of the Store Glacier terminus, and within 100 m of an active moulin, representing a continuous supply of water to the glacier bed. The borehole, which terminates at the glacier bed at a depth of 1043 m depth, is instrumented throughout its length with Solifos BruSENS fibre-optic cable, and monitored with a Silixa iDASTM interrogator. A suite of ~30 vertical seismic profiles (VSPs) was recorded at various azimuths and offsets (up to 500 m) from the borehole, using a 7 kg sledgehammer source. Initial analyses of VSP data implied a 20 [+17, -2] m thickness of sediment immediately beneath the borehole. These analyses are refined by considering the full suite of VSP data, to map spatial variations in the thickness of subglacial sediment layers. This is undertaken using an iterative ray-tracing scheme, which seeks to minimise the differences in the arrival-time of direct seismic energy and subglacial reflections received at various depths in the borehole. Englacial compressional (P-) wave velocities are measured from cross-correlating direct arrivals (= 3700 ± 75 m/s in the upper 800 m of the glacier, 4000 ± 75 m/s between 880-950 m, 3730 ± 75 m/s through basal ice). For the subglacial sediment, we use a P-wave velocity of 1839 m/s, consistent with a value constrained in nearby surface seismic reflection data. To improve the definition of subglacial reflections and the constraint of their arrival times, data are first enhanced using frequency-wavenumber filtering.Our approach suggests that sediment thickness is ~30 m directly beneath the borehole, potentially thinning by 10 m approximately 75 m further south. In reality, the seismic velocity through the sediment layer is unconstrained, but travel-time variations are themselves indicative of changes in either P-wave velocity and/or sediment thickness. Our work further highlights the interpretative potential of borehole DAS approaches, in support of conventional surface-based seismic analysis.