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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. Key Points: 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 [ABSTRACT FROM AUTHOR] more...

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. Plain Language Summary: 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. Key Points: 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 [ABSTRACT FROM AUTHOR] more...

Recent advances in fluvial seismology have provided solid observational and theoretical evidence that near‐river seismic ground motion may be used to monitor and quantify coarse sediment transport. However, inversions of sediment transport rates from seismic observations have not been fully tested against independent measurements, and thus have unknown but potentially large uncertainties. In the present study, we provide the first robust test of existing theory by conducting dedicated sediment transport experiments in a flume laboratory under fully turbulent and rough flow conditions. We monitor grain‐scale physics with the use of 'smart rocks' that consist of accelerometers embedded into manufactured rocks, and we quantitatively link bedload mechanics and seismic observations under various prescribed flow and sediment transport conditions. From our grain‐scale observations, we find that bedload grain hop times are widely distributed, with impacts being on average much more frequent than predicted by existing saltation models. Impact velocities are observed to be a linear function of average downstream cobble velocities, and both velocities show a bed‐slope dependency that is not represented in existing saltation models. Incorporating these effects in an improved bedload‐induced seismic noise model allows sediment flux to be inverted from seismic noise within a factor of two uncertainty. This result holds over nearly two orders of magnitude of prescribed sediment fluxes with different sediment sizes and channel‐bed slopes, and particle–particle collisions observed at the highest investigated rates are found to have negligible effect on the generated seismic power. These results support the applicability of the seismic‐inversion framework to mountain rivers, although further experiments remain to be conducted at sediment transport near transport capacity. © 2018 John Wiley & Sons, Ltd. We use a large‐scale flume (see a) to conduct sediment transport experiments with dedicated monitoring of both seismic noise and grain scale physics (using accelerometer embedded tracers, see b). Our analysis of grain‐scale acceleration timeseries (see c) allows new insights on bedload transport physics. Incorporating these effects into an enriched bedload‐induced noise model, we demonstrate that sediment flux can successfully be inverted from seismic noise (see d), which supports the applicability of the framework to mountain rivers. [ABSTRACT FROM AUTHOR] more...

Substantial effort has recently been made to predict seismic energy caused by ocean waves in the 4–10 s period range. However, little work has been devoted to predict shorter period seismic waves recorded in coastal regions. Here we present an analytical framework that relates the signature of seismic noise recorded at 0.6–2 s periods (0.5–1.5 Hz frequencies) in coastal regions with deep-ocean wave properties. Constraints on key model parameters such as seismic attenuation and ocean wave directionality are provided by jointly analyzing ocean-floor acoustic noise and seismic noise measurements. We show that 0.6–2 s seismic noise can be consistently predicted over the entire year. The seismic noise recorded in this period range is mostly caused by local wind-waves, i.e. by wind-waves occurring within about 2000 km of the seismic station. Our analysis also shows that the fraction of ocean waves traveling in nearly opposite directions is orders of magnitude smaller than previously suggested for wind-waves, does not depend strongly on wind speed as previously proposed, and instead may depend weakly on the heterogeneity of the wind field. This study suggests that wind-wave conditions can be studied in detail from seismic observations, including under specific conditions such as in the presence of sea ice. [ABSTRACT FROM AUTHOR] more...

Braided river reaches show large temporal and spatial variability in morphological change and bedload transport. Whereas the functioning of these reaches is crucial for the storage and transfer of sediment in Alpine catchments, field-based measurements are scarce and typically non-continuous in both time and space. Here, we demonstrate how a rudimentary seismic approach can be used to investigate the magnitude and location of bedload transport during high flow events.We installed geophones on the banks of a c. 60 m wide, braided reach of the Séveraisse River in the French Alps. Active experiments, consisting of dropping rocks with a known weight and from specified heights, were performed on the (dry) river bed at set distances along a cross section between seismometers located on opposite banks. Based on these, we quantify local (sub)surface wave propagation and attenuation. We retrieve impact locations with a precision of c. 10 m, and determine a Green's function from which the energy associated with the impacts, and thus the size and mass of the stone, can be inverted with an uncertainty of a factor 2. These derivations provide a physical basis for field characterization of seismic response, yielding constraints on the source and spatial extent of response, and on the calibration of bedload fluxes. Based on these insights we explore changes in seismic noise from bedload transport (large individual boulders and total sediment flux) over the course of a flood event and longer-term (seasonal) channel migration, and relate these changes to the morphodynamic evolution of the river bed. In general, we demonstrate that with limited means, in terms of equipment and field effort, detailed information may be acquired covering the temporal and spatial signatures of bedload transport in a braided river. [ABSTRACT FROM AUTHOR] more...

A number of studies over the past years have established that seismic data can be used to observe fluvial activity, and that the amplitude of high frequency (>1 Hz) seismic noise in near-river stations can be related to river discharge and bedload transport. Recent theoretical models of seismic noise generation by flow turbulence and bedload impacts provide a framework for understanding how fluvial processes combine to produce observed seismic signals. We use data from a network of seismometers installed in the Bhote Koshi River valley from spring 2015 through fall 2018 to test these models and explore the seismic signals generated by a monsoon-dominated mountain river with typical discharges ranging from approximately 30 to 300 m3/s. We first use a series of event case studies to explore the relationships between fluvial processes and the seismic noise generated in different frequency ranges. These events include temporary damming of the river by an upstream landslide, a local tributary debris flow causing channel constriction, and the aftermath of a glacial lake outburst flood. We find that a reduction in discharge leads to reduced seismic noise over a wide range of frequencies (1-80 Hz), but in near-river (<100 m) stations, the most affected parts of the spectra are a sharp peak at 2-5 Hz and a broad peak at 10-15 Hz. Both of these frequency ranges are sensitive to discharge, but appear to reflect different processes in the river, as they respond in different ways to changes in channel geometry. At even higher frequencies, seismic noise is sensitive to both bedload transport and water discharge. Events that caused an increase in sediment supply in the river are associated with a change in the shape of the frequency spectra and the development of a broad hump at 30-50 Hz, supporting model predictions that this frequency range is sensitive to bedload transport. However, throughout much of the observation period, this 30-50 Hz hump is not visible and noise in this frequency range appears to be dominated by turbulent flow, even in stations 20-50 m from the river, possibly reflecting limited bedload transport at rates well below the river's transport capacity. We then use the existing theoretical models to do a Monte Carlo inversion of the seismic data for water depth and bedload flux over the 2015 monsoon season. The inverted water depth is consistent with pressure gauge data, but we have lower confidence in the bedload flux inversion. Our observations from the Bhote Koshi illustrate the viability of seismic monitoring of discharge, but highlight the difficulty of seismic detection of bedload transport in rivers that are well below transport capacity. [ABSTRACT FROM AUTHOR] more...