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Subglacial seismicity presents the opportunity to monitor inaccessible glacial beds at the epicentral location and time. Glaciers can be underlain by rock or till, a first order control on bed mechanics. Velocity-weakening, necessary for unstable slip, has been shown for each bed type, but is much stronger and evolves over more than an order of magnitude longer distances for till beds. Utilizing a de-stiffened double direct shear apparatus, we found conditions for instability at freezing temperatures and high slip rates for both bed types. During stick–slip stress-drops, we recorded acoustic emissions with piezoelectric transducers frozen into the ice. The two populations of event waveforms appear visually similar and overlap in their statistical features. We implemented a suite of supervised machine learning algorithms to classify the bed type of recorded waveforms and spectra, with prediction accuracy between 65–80%. The Random Forest Classifier is interpretable, showing the importance of initial oscillation peaks and higher frequency energy. Till beds have generally higher friction and resulting stress-drops, with more impulsive first arrivals and more high frequency content compared to rock emissions, but rock beds can produce many till-like events. Seismic signatures could enhance interpretation of bed conditions and mechanics from subglacial seismicity.

 

Distributed acoustic sensing (DAS) technology is an emerging field of seismic sensing that enables recording ambient noise seismic data along the entire length of a fiber-optic cable at meter-scale resolution. Such a dense spatial resolution of recordings over long distances has not been possible using traditional methods because of limited hardware resources and logistical concerns in an urban environment. The low spatial resolution of traditional passive seismic acquisition techniques has limited the accuracy of the previously generated velocity profiles in many important urban regions, including the Reno-area basin, to the top 100 m of the underlying subsurface. Applying the method of seismic interferometry to ambient noise strain rate data obtained from a dark-fiber cable allows for generating noise cross correlations, which can be used to infer shallow and deep subsurface properties and basin geometry. We gathered DAS ambient noise seismic data for this study using a 12 km portion of a dark-fiber line in Reno, Nevada. We used gathered data to generate and invert dispersion curves to estimate the near-surface shear-wave velocity structure. Comparing the generated velocity profiles with previous regional studies shows good agreement in determining the average depth to bedrock and velocity variations in the analyzed domain. A synthetic experiment is also performed to verify the proposed framework further and better understand the effect of the infrastructural cover along the cable. The results obtained from this research provide insight into the application of DAS using dark-fiber lines in subsurface characterization in urban environments. It also discusses the potential effects of the conduit that covers such permanent fiber installations on the produced inversion results.

 

Abstract Observations of glacier slip over till beds, across a range of spatial and temporal scales, show abundant seismicity ranging from Mw∼−2 microearthquakes and tremor (submeter asperities and millisecond duration) to Mw∼7 slow-slip events (∼50  km rupture lengths and ∼30  min durations). A complete understanding of the mechanisms capable of producing seismic signals in these environments represents a strong constraint on bed conditions. In particular, there is a lack of experimental confirmation of velocity-weakening behavior of ice slipping on till, where friction decreases with increasing velocity—a necessity for nucleating seismic slip. To measure the frictional strength and stability of ice sliding against till, we performed a series of double-direct-shear experiments at controlled temperatures slightly above and below the ice melting point. Our results confirm velocity-strengthening ice–till slip at melting temperatures, as has been found in the few previous studies. We provide best-fit rate-and-state friction parameters and their standard deviations from averaging 13 experiments at equivalent conditions. We find evidence of similar velocity-strengthening behavior with 50% by volume debris-laden ice slid against till under the same conditions. In contrast, velocity-weakening and linear time-dependent healing of ice–till slip is present at temperatures slightly below the melting point, providing an experimentally supported mechanism for subglacial seismicity on soft-beds. The stability parameter (a−b) decreases with slip velocity, and evolution occurs over large (mm scale) displacements, suggesting that shear heating and melt buildup is responsible for the weakening. These measurements provide insight into subglacial stiffness in which seismicity of this type might be expected. We discuss glaciological circumstances pointing to potential field targets in which to test this frozen seismic asperity hypothesis.