Search for: All records

ABSTRACT The recorded seismic waveform is a convolution of event source term, path term, and station term. Removing high-frequency attenuation due to path effect is a challenging problem. Empirical Green’s function (EGF) method uses nearly collocated small earthquakes to correct the path and station terms for larger events recorded at the same station. However, this method is subject to variability due to many factors. We focus on three events that were well recorded by the seismic network and a rapid response distributed acoustic sensing (DAS) array. Using a suite of high-quality EGF events, we assess the influence of time window, spectral measurement options, and types of data on the spectral ratio and relative source time function (RSTF) results. Increased number of tapers (from 2 to 16) tends to increase the measured corner frequency and reduce the source complexity. Extended long time window (e.g., 30 s) tends to produce larger variability of corner frequency. The multitaper algorithm that simultaneously optimizes both target and EGF spectra produces the most stable corner-frequency measurements. The stacked spectral ratio and RSTF from the DAS array are more stable than two nearby seismic stations, and are comparable to stacked results from the seismic network, suggesting that DAS array has strong potential in source characterization. 

Moho topography yields insights into the evolution of the lithosphere and the strength of the lower crust. The Moho reflected phase (PmP) samples this key boundary and may be used in concert with the first arriving P phase to infer crustal thickness. The densely sampled station coverage of distributed acoustic sensing arrays allows for the observation of PmP at fine-scale intervals over many kilometers with individual events. We use PmP recorded by a 100-km-long fiber that traverses a path between Ridgecrest, CA and Barstow, CA to explore Moho variability in Southern California. With hundreds of well-recorded events, we verify that PmP is observable and develop a technique to identify and pick P-PmP differential times with high confidence. We use these observations to constrain Moho depth throughout Southern California, and we find that short-wavelength variability in crustal thickness is abundant, with sharp changes across the Garlock Fault and Coso Volcanic Field. 

Continuous geodetic measurements near volcanic systems can image magma transport dynamics, yet resolving dike intrusions with high spatiotemporal resolution remains challenging. We introduce fiber-optic geodesy, leveraging low-frequency distributed acoustic sensing (LFDAS) recordings along a telecommunication fiber-optic cable, to track dike intrusions near Grindavík, Iceland, on a minute timescale. LFDAS reveals distinct strain responses from nine intrusive events, six resulting in fissure eruptions. Geodetic inversion of LFDAS strain reveals detailed magmatic intrusions, with inferred dike volume rate peaking systematically 15 to 22 min before the onset of each eruption. Our results demonstrate DAS’s potential for a dense strainmeter array, enabling high-resolution, nearly real-time imaging of subsurface quasi-static deformations. In active volcanic regions, LFDAS recordings can offer critical insights into magmatic evolution, eruption forecasting, and hazard assessment. 

Abstract Vadose zone soil moisture is often considered a pivotal intermediary water reservoir between surface and groundwater in semi-arid regions. Understanding its dynamics in response to changes in meteorologic forcing patterns is essential to enhance the climate resiliency of our ecological and agricultural system. However, the inability to observe high-resolution vadose zone soil moisture dynamics over large spatiotemporal scales hinders quantitative characterization. Here, utilizing pre-existing fiber-optic cables as seismic sensors, we demonstrate a fiber-optic seismic sensing principle to robustly capture vadose zone soil moisture dynamics. Our observations in Ridgecrest, California reveal sub-seasonal precipitation replenishments and a prolonged drought in the vadose zone, consistent with a zero-dimensional hydrological model. Our results suggest a significant water loss of 0.25 m/year through evapotranspiration at our field side, validated by nearby eddy-covariance based measurements. Yet, detailed discrepancies between our observations and modeling highlight the necessity for complementary in-situ validations. Given the escalated regional drought risk under climate change, our findings underscore the promise of fiber-optic seismic sensing to facilitate water resource management in semi-arid regions. 

Abstract The use of fiber-optic sensing systems in seismology has exploded in the past decade. Despite an ever-growing library of ground-breaking studies, questions remain about the potential of fiber-optic sensing technologies as tools for advancing if not revolutionizing earthquake-hazards-related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber-optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber-optic sensing to impact monitoring efforts by documenting the data completeness in a number of long-term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber-optic sensing and unlock its potential application to a broad range of earthquake hazard problems. 

Abstract The structure of fault zones and the ruptures they host are inextricably linked. Fault zones are narrow, which has made imaging their structure at seismogenic depths a persistent problem. Fiber‐optic seismology allows for low‐maintenance, long‐term deployments of dense seismic arrays, which present new opportunities to address this problem. We use a fiber array that crosses the Garlock Fault to explore its structure. With a multifaceted imaging approach, we peel back the shallow structure around the fault to see how the fault changes with depth in the crust. We first generate a shallow velocity model across the fault with a joint inversion of active source and ambient noise data. Subsequently, we investigate the fault at deeper depths using travel‐time observations from local earthquakes. By comparing the shallow velocity model and the earthquake travel‐time observations, we find that the fault's low‐velocity zone below the top few hundred meters is at most unexpectedly narrow, potentially indicating fault zone healing. Using differential travel‐time measurements from earthquake pairs, we resolve a sharp bimaterial contrast at depth that suggests preferred westward rupture directivity. 

Abstract Distributed acoustic sensing (DAS) offers a cost effective, nonintrusive method for high-resolution near-surface characterization in urban environments where conventional geophysical surveys are limited or nonexistent. However, passive imaging with DAS in urban settings presents challenges such as strong diurnal traffic noise, nonlinear array geometry, and poor fiber coupling to the ground. We repurposed a dark fiber in Melbourne, Australia, into a 25 km DAS array that traces busy arterial roads, tram routes, and orthogonal sections. By employing noise cross correlation and array beamforming, we calculated dispersion curves and successfully inverted for a near-surface shear-wave velocity model down to 100 meters. Stationary seismic sources are maximized by selecting daytime traffic signals, thereby recovering surface waves and reducing interference from acoustic waves from man-made structures in the subsurface. Poorly coupled channels, which are linked to fiber maintenance pits, are identified through cross-correlation amplitudes. The dispersion curve calculation further considers the channel orientation to avoid mixing Rayleigh and Love waves. Using a trans-dimensional Markov chain Monte Carlo sampling approach, we achieved effective model inversion without a prior reference model. The resulting near-surface profile aligns with mapped lithology and reveals previously undocumented lithological variation. 

Abstract The firn layer covers 98% of Antarctica's ice sheets, protecting underlying glacial ice from the external environment. Accurate measurement of firn properties is essential for assessing cryosphere mass balance and climate change impacts. Characterizing firn structure through core sampling is expensive and logistically challenging. Seismic surveys, which translate seismic velocities into firn densities, offer an efficient alternative. This study employs Distributed Acoustic Sensing technology to transform an existing fiber‐optic cable near the South Pole into a multichannel, low‐maintenance, continuously interrogated seismic array. The data resolve 16 seismic wave propagation modes at frequencies up to 100 Hz that constrain P and S wave velocities as functions of depth. Using co‐located geophones for ambient noise interferometry, we resolve very weak radial anisotropy. Leveraging nearby SPICEcore firn density data, we find prior empirical density‐velocity relationships underestimate firn air content by over 15%. We present a new empirical relationship for the South Pole region. 

Abstract Large earthquakes can trigger smaller seismic events, even at significant distances. The process of earthquake triggering offers valuable insights into the evolution of local stress states, deepening our understanding of the mechanisms of earthquake nucleation. However, our ability to detect these triggered events is limited by the quality and spatial density of local seismometers, posing significant challenges if the triggered event is hidden in the signal of a nearby larger earthquake. Distributed acoustic sensing (DAS) has the potential to enhance the monitoring capability of triggered earthquakes through its high spatial sampling and large spatial coverage. Here, we report on an uncatalogued magnitude (M) 5.1 event in northeast Turkey, which was likely dynamically and instantaneously triggered by the 2023 M7.8 earthquake in southeast Turkey, located 400 km away. This event was initially discovered on ∼1,100 km of active DAS recordings that are part of an 1,850‐km linear array. Subsequent validation using local seismometers confirmed the event's precise time, location, and magnitude. Interestingly, this dynamically triggered event exhibited precursory signals preceding its P arrivals on the nearby seismometers. It can be interpreted as the signal from other nearby, uncatalogued, smaller triggered events. Our results highlight the potential of high‐spatial‐density DAS in enhancing the local‐scale detection and the detailed analysis of earthquake triggering.