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Ice speeds in Greenland are largely set by basal motion1, which is modulated by meltwater delivery to the ice base2–4. Evidence suggests that increasing melt rates enhance the subglacial drainage network’s capacity to evacuate basal water, increasing bed friction and causing the ice to slow5–10. This limits the potential of melt forcing to increase mass loss as temperatures increase11. Here we show that melt forcing has a pronounced influence on dynamics, but factors besides melt rates primarily control its impact. Using a method to examine friction variability across the entirety of western Greenland, we show that the main impact of melt forcing is an abrupt north-to-south change in bed strength that cannot be explained by changes in melt production. The southern ablation zone is weakened by 20–40 per cent compared with regions with no melt, whereas in northern Greenland the ablation zone is strengthened. We show that the weakening is consistent with persistent basal water storage and that the threshold is linked to differences in sliding and hydropotential gradients, which exert primary control on the pressures within drainage pathways that dewater the bed. These characteristics are mainly set by whether a margin is land or marine terminating, suggesting that dynamic changes that increase mass loss are likely to occur in northern Greenland as temperatures increase. Our results point to physical representations of these findings that will improve simulated ice-sheet evolution at centennial scales.

Basal shear stress on hard‐bedded glaciers results from normal stress against bed roughness, which depends on basal water pressure and cavity size. These quantities are related in a steady state but are expected to behave differently under rapid changes in water input, which may lead to a transient frictional response not captured by existing friction laws. Here, we investigate transient friction using Global Positioning System vertical displacement and horizontal velocity observations, basal water pressure measurements, and cavitation model predictions during rain‐induced speed‐up events at Glacier d'Argentière, French Alps. We observe up to a threefold increase in horizontal surface velocity, spatially migrating at rates consistent with subglacial flow drainage, and associated with surface uplift and increased water pressure. We show that frictional changes are mainly driven by changes in water pressure at nearly constant cavity size. We propose a generalized friction law capable of capturing observations in both the transient and steady‐state regimes. Changes in water input at the bed of glaciers greatly modify their sliding speed by changing subglacial water pressure. High water pressure, induced by extreme meltwater input, is thought to increase cavity size, a process known as cavitation, which reduces direct contact and increases basal sliding speed. Our Global Positioning System observations indicate that the existing cavitation law, which is based on multidecadal sliding velocities of an alpine glacier, fails at capturing short‐lived, rain‐induced speed‐ups. This is because cavities have insufficient time to adjust their size in response to water pressure changes. Here, we propose a generic friction law that satisfyingly captures observations by incorporating a direct dependency of basal friction on water pressure. With Global Positioning System we observe rain‐induced glacier speed‐up events associated with surface uplift and down‐glacier migrationObservations and modeling show that water pressure rather than cavity size mainly controls changes in basal friction during these eventsWe propose a generalized version of the "regularized” Coulomb friction law, adapted to transient friction under rapid water pressure variations With Global Positioning System we observe rain‐induced glacier speed‐up events associated with surface uplift and down‐glacier migration Observations and modeling show that water pressure rather than cavity size mainly controls changes in basal friction during these events We propose a generalized version of the "regularized” Coulomb friction law, adapted to transient friction under rapid water pressure variations

Understanding glaciers structural heterogeneity is crucial for assessing their fate. Yet, places where structure changes are strong, such as crevasses fields, are often inaccessible for direct instrumentation. To overcome this limitation, we introduce an innovative technique that transforms seismic sources, here generated by crevasses, into virtual receivers using source‐to‐receiver spatial reciprocity. We demonstrate that phase interference patterns between well‐localized seismic sources can be leveraged to retrieve phase velocity maps using Seismic Michelson Interferometry. The obtained phase velocity exhibits sensitivity to changes in glacier structure, offering insights into the origins of mechanical property changes, with spatial resolution surpassing traditional methods by a factor of five. In particular, we observe sharp variations in phase velocity related to strongly damaged subsurface areas indicating a complex 3‐D medium. Applying this method more systematically and in other contexts will enhance our understanding of the structure of glaciers and other seismogenic environments. We transform seismic sources from crevasses into virtual receivers using source‐to‐receiver spatial reciprocityWe derive phase velocity maps in previously inaccessible areas with a resolution five times larger than traditional approachesWe retrieve the influence of glacier geometry and structural heterogeneity on the glacier mechanical properties We transform seismic sources from crevasses into virtual receivers using source‐to‐receiver spatial reciprocity We derive phase velocity maps in previously inaccessible areas with a resolution five times larger than traditional approaches We retrieve the influence of glacier geometry and structural heterogeneity on the glacier mechanical properties

The deformation of a circular fault in a thin floating ice plate imposed by a slow rotational displacement is investigated. Temporal changes in shear strength, as a proxy for the resistance of the fault as a whole, are monitored by the torque required to impose a constant displacement rate. Micro‐seismic monitoring is used to study the relationship between fault average resistance (torque) and micro‐ruptures. The size distribution of ruptures follows a power‐law scaling characterized by an unusually high exponent (b≃3), characteristic of a deformation driven by small ruptures. In strong contrast to the typical brittle dynamics of crustal faults, an 'apparently aseismic' deformation regime is observed in which small undetected seismic ruptures, below the detection level of the monitoring system, control the slip budget. Most (≃71%) of the detected ruptures are organized in bursts with highly similar waveforms, suggesting that these ruptures are only a passive by‐product of apparently aseismic slip events. The seismic signature of this deformation regime has strong similarities with crustal faulting in settings characterized by high temperature and with non‐volcanic tremors. A micro‐seismic monitoring of a fault is setup to monitor its deformationSmall undetected fractures control the slip and energy budgets of the faultFractures are mostly a by‐product of the imposed slip, similarly to swarm‐seismicity

During the RESOLVE project (“High‐resolution imaging in subsurface geophysics: development of a multi‐instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass‐filtered copies of the continuous seismic waveforms, we compute energy‐based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on‐ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity. Alpine glaciers are a major component in the dynamic cryospheric environment. They are characterized by a multitude of processes occurring side by side, including but not limited to melt water flow, crevasse formation, and frictional basal sliding of the ice mass over the rigid and obstructive bedrock. Each of these processes generates distinctive acoustic signals that can be recorded by seismic instruments and the changing on‐ice motions are resolvable with Global Positioning System. Considering the rapidly changing glacial environment, there is an increasing need for reliable models to predict glacial dynamics to properly assess any associated hazard. Understanding basal sliding is of particular interest to this problem. Investigated here is how to overcome the challenge of describing glacier sliding using seismic signals since the records often contains multiple “loud” signals originating from associated surface processes within the glacier. To uncover specific processes occurring at the ice‐bedrock interface, we design a machine learning model to incorporate signals recorded on the glacier to predict the on‐ice surface motions. The results provide valuable insights into the spatiotemporal dynamics of an active Alpine glacier with the potential to contribute to a better understanding of the driving mechanisms of glacier sliding. Seismic and Global Positioning System (GPS) data are examined to study physical processes controlling glacial basal motionDecision tree model uses beamforming catalog and statistical features of time series to constrain correlations with GPS recorded motionsModel features indicate glacial on‐ice velocity is modulated by basal motions Seismic and Global Positioning System (GPS) data are examined to study physical processes controlling glacial basal motion Decision tree model uses beamforming catalog and statistical features of time series to constrain correlations with GPS recorded motions Model features indicate glacial on‐ice velocity is modulated by basal motions

Surges and glacier avalanches are expressions of glacier instability, and among the most dramatic phenomena in the mountain cryosphere. Until now, the catastrophic collapse of a glacier, combining the large volume of surges and mobility of ice avalanches, has been reported only for the 2002 130 × 106m3detachment of Kolka Glacier (Caucasus Mountains), which has been considered a globally singular event. Here, we report on the similar detachment of the entire lower parts of two adjacent glaciers in western Tibet in July and September 2016, leading to an unprecedented pair of giant low-angle ice avalanches with volumes of 68 ± 2 × 106m3and 83 ± 2 × 106m3. On the basis of satellite remote sensing, numerical modelling and field investigations, we find that the twin collapses were caused by climate- and weather-driven external forcing, acting on specific polythermal and soft-bed glacier properties. These factors converged to produce surge-like enhancement of driving stresses and massively reduced basal friction connected to subglacial water and fine-grained bed lithology, to eventually exceed collapse thresholds in resisting forces of the tongues frozen to their bed. Our findings show that large catastrophic instabilities of low-angle glaciers can happen under rare circumstances without historical precedent. Two catastrophic glacier collapse events in western Tibet in 2016 were caused by a convergence of weather and glacier-bed conditions, according to an analysis of observations and modelling.

Hysteresis in the relationship between bed load transport and river stage is a well‐documented phenomenon with multiple known causes. Consequently, numerous studies have interpreted hysteresis in the relationship between seismic ground motion near rivers and some measure of flow strength (i.e., discharge or stage) as the signature of bed load transport. Here we test this hypothesis in the Erlenbach stream (Swiss Prealps) using a metric to quantitatively compare hysteresis in seismic data with hysteresis recorded by geophones attached beneath steel plates within the streambed, a well‐calibrated proxy for direct sediment transport measurements. We find that while both the geophones and seismometers demonstrate hysteresis, the magnitude and direction of hysteresis are not significantly correlated between these data, indicating that the seismic signal at this site is primarily reflecting hysteresis in processes other than sediment transport. Seismic hysteresis also does not correlate significantly with the magnitude of sediment transport recorded by the geophones, contrary to previous studies' assumptions. We suggest that hydrologic sources and changes in water turbulence, for instance due to evolving boundary conditions at the bed, rather than changes in sediment transport rates, may sometimes contribute to or even dominate the hysteresis observed in seismic amplitudes near steep mountain rivers. An increasing number of studies have recently observed changes in the amount of seismic shaking (hysteresis) recorded near a river at a given discharge during floods. Most studies have assumed that this hysteresis was caused by changes in the amount of sediment being transported in the river and have therefore used the hysteresis to assess sediment transport rates and patterns. We examine concurrent seismic and sediment transport data from a steep mountain stream in the Swiss Prealps and find that changes in seismic shaking are unrelated and even opposed (increasing versus decreasing) to changes in sediment transport rates for four out of five transport events. Water turbulence, rather than sediment transport, appears to be the strongest source of seismic shaking, and changes in seismic shaking are most likely caused by changes in turbulence or how turbulence transmits energy through the river bed. These effects may be due to rearrangement of sediment around large boulders on the bed or slight shifting of the boulders themselves. Our results have significant implications for the growing field of fluvial seismology and the evaluation of seismic data near rivers, as previous interpretations of seismic hysteresis as evidence for sediment transport may not always be accurate. Hysteresis in seismic signals near rivers may not always indicate hysteresis in bed load sediment transport rates, as previously assumedThe seismic signal generated by water turbulence, rather than sediment transport, can dominate seismic observations near riversShifting of grains on the river bed may change the seismic response to fluid flow between rising and falling water levels (hysteresis)

Surface melt forces summertime ice‐flow accelerations on glaciers and ice sheets. Here, we show that large meltwater‐forced accelerations also occur during wintertime in Greenland. We document supraglacial lakes (SGLs) draining in cascades at unusually high elevation, causing an expansive flow acceleration over a ∼5,200 km2region during winter. The three‐component interferometric surface velocity field and decomposition modeling reveal the underlying flood propagation with unprecedented detail as it traveled over 160 km from the drainage site to the margin, providing novel constraints on subglacial water pathways, drainage morphology, and links with basal sliding. The triggering SGLs continuously grew over 40 years and suddenly released decades of stored meltwater, demonstrating surface melting can impact dynamics well beyond melt production. We show these events are likely common and thus their cumulative impact on dynamics should be further evaluated. Understanding factors that influence flow speeds on ice sheets are linked to our ability to predict changes in sea level and prepare coastal communities for the future. On the Greenland Ice Sheet, ice flow‐speed changes have long been linked to surface melting in summer. Meltwater can make it to the bed of the ice sheet via surface cracks causing changes in ice motion. Here, we show that melt that is produced during summer, but stored within lakes on the ice surface, can drain to the bed and cause large flow accelerations during winter. This demonstrates the influence of meltwater on flow speeds needs to be considered beyond when it is produced. A cascade of supraglacial lake drainages and an associated ice‐flow acceleration are observed during winter in GreenlandDecomposition of motion into vertical and horizontal components allows for subglacial water pathways and links with sliding to be inferredTracking the history of the supraglacial lakes shows some of the meltwater released was produced decades earlier A cascade of supraglacial lake drainages and an associated ice‐flow acceleration are observed during winter in Greenland Decomposition of motion into vertical and horizontal components allows for subglacial water pathways and links with sliding to be inferred Tracking the history of the supraglacial lakes shows some of the meltwater released was produced decades earlier

Water that pressurizes the base of glaciers and ice sheets enhances glacier velocities and modulates glacial erosion. Predicting ice flow and erosion therefore requires knowledge of subglacial channel evolution, which remains observationally limited. Here we demonstrate that detailed analysis of seismic ground motion caused by subglacial water flow at Mendenhall Glacier (Alaska) allows for continuous measurement of daily to subseasonal changes in basal water pressure gradient, channel size, and sediment transport. We observe intermittent subglacial water pressure gradient changes during the melt season, at odds with common assumptions of slowly varying, low‐pressure channels. These observations indicate that changes in channel size do not keep pace with changes in discharge. This behavior strongly affects glacier dynamics and subglacial channel erosion at Mendenhall Glacier, where episodic periods of high water pressure gradients enhance glacier surface velocity and channel sediment transport by up to 30% and 50%, respectively. We expect the application of this framework to future seismic observations acquired at glaciers worldwide to improve our understanding of subglacial processes. We measure key subglacial channel physical parameters from the analysis of seismic ground motionWater input changes are accommodated by pressure gradient changes at short time scales and by channel size changes at longer time scalesIncreases in subglacial channel pressure gradient correlate with increases in glacier velocity and sediment transport

Below hard‐bedded glaciers, both basal friction and distributed subglacial drainage are thought to be controlled by a network of cavities. Previous coupled hydro‐mechanical models, however, describe cavity‐driven friction and hydraulic transmissivity independently, resulting in a physically inconsistent cavity evolution between the two components of the models. Here, we overcome this issue by describing the hydro‐mechanical system using a common cavity‐evolution description, that governs both transient friction and hydraulic transmissivity. We show that our coupling approach is superior to previous formulations in explaining a unique observation record of glacier sliding speed from the French Alps. We find that, at multi‐day to multi‐decadal timescales, sliding speed can be expressed as a direct function of basal shear stress and water discharge, without accounting for water pressure, which simply adjusts to maintain the cavitation ratio needed to accommodate the water supply. Predicting the sliding speed of glaciers and ice sheets is challenged by the difficulties of assessing the water pressure at the glacier base. Here, we improve the coupling between existing theories about basal friction and subglacial hydrology by introducing a consistent description of roughness and hydraulic transmissivity. Our work breaks with the common view on the subglacial environment that water pressure drives the sliding speed by modulating friction at the glacier base. Instead, our findings show that at multi‐day and longer timescales sliding speed and water pressure are imposed by the water discharge along the glacier base that needs to be accommodated. Our results open new perspectives for understanding contemporary glacier and ice sheet sliding and predicting its future behavior under changing climate. We introduce a consistent framework to describe the effect of cavitation on both friction and hydraulic transmissivityThis approach reduces the number of parameters of the coupled hydro‐mechanical problem and shows better performance in explaining our dataWe find that seasonal sliding variations are well captured assuming cavities in equilibrium with their average discharge We introduce a consistent framework to describe the effect of cavitation on both friction and hydraulic transmissivity This approach reduces the number of parameters of the coupled hydro‐mechanical problem and shows better performance in explaining our data We find that seasonal sliding variations are well captured assuming cavities in equilibrium with their average discharge

The hydromechanical processes by which basal water controls sliding at the glacier bed are poorly known, despite glacier basal motion being responsible for a large part of ice flux in temperate alpine glaciers. Previous studies suggest that sliding strongly relates to the quantity of water being stored at the ice‐bedrock interface. However, this water storage is difficult to quantify accurately on the basis of surface‐motion observations, given that uplift can also be affected by changes in vertical‐strain rates and sliding velocity change. Here, we use a comprehensive data set of in situmeasurements performed over 2 years on the Argentière Glacier in the French Alps to investigate the relationships between horizontal and vertical velocities, basal sliding, subglacial runoff and bed separation. We observe strikingly large uplifts varying spatially between 0.20 and 0.90 m over the winter/spring seasons between January and June and with a consistent spatial pattern from 1 year to another. We show, based on observations and three dimensional ice‐flow modeling, that these large uplifts cannot be explained solely by changes in strain rates or in sliding up an inclined bed. Our results reveal that more than 80% of the observed uplift is related to enhanced bed separation through cavitation, allowing us to estimate the volume occupied by water‐filled subglacial cavities. Our interpretation of uplift being mainly caused by increased cavitation is also consistent with an associated increase in the observed surface horizontal velocity. These findings provide important observational constraints for testing subglacial hydrological models. Glacier basal motion is responsible for a large part of ice flux in temperate alpine glaciers and outlet glaciers of ice sheets. However, the hydromechanical processes by which basal water controls sliding at the glacier bed are poorly known in large part because observations are very scarce. Consequently, the impact of surface melting and meltwater input on the future of mountain glaciers and outlet glaciers of ice sheets remains unclear. Here, we use a comprehensive data set of in situmeasurements performed over 2 years on the Argentière Glacier in the French Alps, complemented by state‐of‐the‐art ice flow and hydrology modeling, to investigate changes in water storage at the ice‐bedrock interface. We find strikingly large uplifts ranging between 0.20 and 0.90 m over the winter/spring seasons in the ablation zone. We show that this uplift is mostly related to enhanced bed separation as a result of increased basal water storage. We expect this study to be helpful to the glaciological community studying basal sliding and its modulation by sub‐glacial hydrology with a view of improving predictions of the future behavior of mountain glaciers and outlet glaciers of ice sheets. We investigate horizontal, vertical velocities, basal sliding and subglacial runoff on the Argentière glaciers (French Alps)We find large uplifts ranging between 20 and 90 cm over the winter/spring seasons over a large part of ablation zoneWe show that the observed uplift is very likely related to enhanced bed separation as a result of increased storage of basal water We investigate horizontal, vertical velocities, basal sliding and subglacial runoff on the Argentière glaciers (French Alps) We find large uplifts ranging between 20 and 90 cm over the winter/spring seasons over a large part of ablation zone We show that the observed uplift is very likely related to enhanced bed separation as a result of increased storage of basal water

Previous studies suggest that the seismic noise induced by rivers may be used to infer river transport properties, and previous theoretical work showed that bedload sediment flux can be inverted from seismic data. However, the lack of a theoretical framework relating water flow to seismic noise prevents these studies from providing accurate bedload fluxes and quantitative information on flow processes. Here we propose a forward model of seismic noise caused by turbulent flow. In agreement with previous observations, modeled turbulent flow‐induced noise operates at lower frequencies than bedload‐induced noise. Moreover, the differences in the spectral signatures of turbulent flow‐induced and bedload‐induced forces at the riverbed are significant enough that these two processes can be characterized independently using seismic records acquired at various distances from the river. In cases with isolated turbulent flow noise, we suggest that riverbed stress can be inverted. Finally, we validate our model by comparing predictions to previously reported observations. We show that our model captures the spectral peak located around 6–7 Hz and previously attributed to water flow at Hance Rapids in the Colorado River (United States); we also show that turbulent flow causes a significant part of the seismic noise recorded at the Trisuli River in Nepal, which reveals that the hysteresis curve previously reported there does not solely include bedload, but is also largely influenced by turbulent flow‐induced noise. We expect the framework presented here to be useful to invert realistic bedload fluxes by enabling the removal of the turbulent flow contribution from seismic data. Seismic records near rivers are sensitive to turbulent flow velocitiesOur model allows separating bedload from turbulent flow induced noiseFor an identified turbulent flow signal, riverbed stress can be inverted

Dense seismic array monitoring combined with advanced processing can help retrieve and locate a variety of seismic sources with unprecedented resolution and spatial coverage. We present a methodology that goes beyond classical localization algorithms through gathering various types of sources (impulsive or continuous) using a single scheme based on a gradient‐descent optimization and evaluating different levels of phase coherence. We apply our methodology on an Alpine glacier and demonstrate that we can retrieve the dynamics of active crevasses with a metric resolution using sources associated with high phase coherence; the presence of diffracting materials (e.g., rocks) trapped in transverse crevasses using sources with moderate phase coherence; and the two‐dimensional time evolution of the subglacial hydrology system using sources with low phase coherence. Our study highlights the strength of using an appropriate and systematic seismological approach to image a wide range of subsurface structures and phenomena in settings with complex wavefields. Over the past two decades, the growing use of dense seismic arrays has often overcome limitations of traditional observations methods and yielded new insights on the physics of subsurface process and properties. Yet scientific and computational challenges remain to be addressed for using the appropriate array‐processing approaches and automating the techniques on large volume of data and for complex wavefields. In this paper we address such challenges in the particular case of monitoring glaciers, which host numerous and diverse sets of seismic sources that produce signals ranging from impulsive to tremor‐like. We combine a physics‐based and a statistical approach to explore with a dense seismic array the spatial coherence of the seismic wavefield generated by such a diversity of sources. We show that even a small coherence in the phase signal remains rich in statistical information on concomitant and/or low amplitudes micro‐seismic sources. This allows us to localize seismic sources with a super‐resolution (meter to decameter) and identify emerging patterns associated with a wide range of glacier features and their dynamics, ranging from active crevasses, debris in transverse passive crevasses and subglacial water flow. Such methodological and conceptual advance may enable a more efficient and complete imaging of geophysical objects. We present an innovative array‐processing approach to image glaciers structures at high resolution by locating seismic sourcesWe investigate a large range of spatial phase coherences, from very low up to very high, over narrow frequency bands and short time windowsWe image the spatial and temporal dynamics of sources originating from active and passive crevasses as well as from subglacial hydrology We present an innovative array‐processing approach to image glaciers structures at high resolution by locating seismic sources We investigate a large range of spatial phase coherences, from very low up to very high, over narrow frequency bands and short time windows We image the spatial and temporal dynamics of sources originating from active and passive crevasses as well as from subglacial hydrology

Understanding the dynamic response of glaciers to climate change is vital for assessing water resources and hazards, and subglacial hydrology is a key player in glacier systems. Traditional observations of subglacial hydrology are spatially and temporally limited, but recent seismic deployments on and around glaciers show the potential for comprehensive observation of glacial hydrologic systems. We present results from a high‐density seismic deployment spanning the surface of Lemon Creek Glacier, Alaska. Our study coincided with a marginal lake drainage event, which served as a natural experiment for seismic detection of changes in subglacial hydrology. We observed glaciohydraulic tremor across the surface of the glacier that was generated by the subglacial hydrologic system. During the lake drainage, the relative changes in seismic tremor power and water flux are consistent with pressurization of the subglacial system of only the upper part of the glacier. This event was not accompanied by a significant increase in glacier velocity; either some threshold necessary for rapid basal motion was not attained, or, plausibly, the geometry of Lemon Creek Glacier inhibited speedup. This pressurization event would have likely gone undetected without seismic observations, demonstrating the power of cryoseismology in testing assumptions about and mapping the spatial extent of subglacial pressurization. It is important to understand how glaciers are affected by climate change because glaciers contribute to fresh water resources, flood hazards, and sea levels. We want to understand how liquid water moves underneath solid glacier ice, because that water affects how glaciers move, melt, and crack. We put seismometers (the same sensors that detect earthquakes) on an Alaska glacier to detect tiny vibrations from the flowing water below. By observing the changing strength of the vibrations over time and comparing them to the amount of water that goes into and out of the glacier, we mapped where and when the water below the ice was under pressure. When a lake on top of the glacier drained into the water channels below the glacier, we used the seismic data to see that the water became pressurized under half of the glacier. We did not see other obvious signs of pressurization, such as the glacier speeding up dramatically, so we likely would not have known about the pressurization without the seismometers. To get the best understanding of glaciers, scientists need to combine different methods of observation, and this case is an example of why including seismic observations can be very helpful. Subglacial water flow generates continuous seismic tremor observable in the power spectra recorded by on‐ice seismometersUsing a dense array of seismometers to detect glaciohydraulic tremor allows us to map subglacial pressurization in space and timeSeismic data indicate pressurization in the upper glacier, particularly near the margins, that was not perceptible in glacier velocity data Subglacial water flow generates continuous seismic tremor observable in the power spectra recorded by on‐ice seismometers Using a dense array of seismometers to detect glaciohydraulic tremor allows us to map subglacial pressurization in space and time Seismic data indicate pressurization in the upper glacier, particularly near the margins, that was not perceptible in glacier velocity data

Bedload transport is a key process in fluvial morphodynamics, but difficult to measure. The advent of seismic monitoring techniques has provided an alternative to in‐stream monitoring, which is often costly and cannot be utilized during large floods. Seismic monitoring is a method requiring several steps to convert seismic data into bedload flux data. State‐of‐the‐art conversion approaches exploit physical models predicting the seismic signal generated by bedload transport. However, due to a lack of well‐constrained validation data, the accuracy of the resulting inversions is unknown. We use field experiments to constrain a seismic bedload model and compare the results to high‐quality independent bedload measurements. Constraining the Green's function (i.e., seismic ground properties) with an active seismic survey resulted in an average absolute difference between modeled and empirically measured seismic bedload power of 11 dB in the relevant frequency band. Using generically estimated Green's function parameters resulted in a difference of 20 dB, thus highlighting the importance of using actual field parameters. Water turbulence and grain hiding are unlikely to be the cause of differences between field observations and our analysis. Rather, they may be either due to the inverted model being particularly sensitive to the coarse tail of the grain‐size distribution, which is least well constrained from field observations, or due to the seismic model underestimating effects of the largest grains. Constrained seismic model inversion reveals dominant control of largest grain size on bedload flux estimatesMeasuring ground properties from a seismic experiment allows improving spectrogram fit by an order of magnitude in seismic powerConsidering all field‐constrained parameters results in bedload flux overestimation by two orders of magnitude Constrained seismic model inversion reveals dominant control of largest grain size on bedload flux estimates Measuring ground properties from a seismic experiment allows improving spectrogram fit by an order of magnitude in seismic power Considering all field‐constrained parameters results in bedload flux overestimation by two orders of magnitude

Bedload transport drives morphological changes in gravel‐bed streams and sediment transfer in catchments. The large impact forces associated with bedload motion and its highly dynamic spatiotemporal nature make it difficult to monitor bedload transport in the field. In this study, we revise a physically‐based model of bedload‐induced seismic ground motion proposed by Tsai et al. (2012, htpps://doi.org/10.1029/2011GL050255) and apply it to invert bedload flux from seismic measurements alongside an Alpine stream. First, we constrain the seismic response of a braided river reach with a simple active experiment using a series of large‐rock impacts. This allows the characterization of surface wave propagation and attenuation with distance from the impact source. Second, we distinguish bedload‐generated ground vibrations from those caused by turbulent flow using frequency‐based scaling relationships between seismic power and discharge. Finally, absolute bedload transport rates are quantified from seismic measurements using inverse modeling based on a simplified formulation of bedload particle motion. The results are verified with a large data set of bedload samples, demonstrating that seismic measurements can provide an indirect measure for bedload flux with uncertainties within a factor of 5±1for instantaneous measurements (between 0.01 and 1 kg/m/s). Larger deviations may be caused by uncertainties in the contribution of turbulent flow effects, particle impact velocity, and especially particle size that may vary with sediment supply and flow conditions. When constraining these uncertainties, instream sediment transport measurements are no longer necessarily required and seismic monitoring may provide an accurate and continuous means to investigate bedload dynamics in gravel‐bed streams. Bedload fluxes are derived independently from bank‐side seismic measurements with an uncertainty factor of 5±1for instantaneous valuesSimple experiments with large‐rock impacts are used to calibrate seismic response and provide an alternative to instream bedload samplingScaling seismic power with discharge allows bedload‐generated vibrations to be isolated and gives insight into bedload temporal dynamics