Distributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Due to some instrumental limitations, current DAS studies primarily focus on the phase information but less on the amplitude information. In this study, we compile earthquake data from two DAS arrays in California, USA, and one submarine array in Sanriku, Japan. We develop a data-driven method to obtain the first scaling relation between DAS amplitude and earthquake magnitude. Our results reveal that the DAS amplitude in different regions follows a similar scaling relation. The scaling relation can provide a rapid magnitude estimation and effectively avoid uncertainties caused by the conversion to ground motions. We finally show that the scaling relation is transferable from one to another new region. The scaling relation highlights the great potential of DAS in earthquake source characterization and early warning.

The mixing of ocean waters on continental shelves, which is mainly driven by waves, tides, and currents, plays a key role in the physics, biogeochemistry, and ecology of coastal regions. This study focuses on four months of continuous data recorded along a telecommunication cable offshore Oregon, USA, with Distributed Acoustic Sensing (DAS). We apply a cross-correlation approach to the continuous DAS data to infer the propagation of ocean surface gravity waves in the 3 to 100 s period range and estimate near-surface ocean flows. We observe strong spatio-temporal variations of ocean flows along the cable over four months, with strong impacts from a series of storms in late October 2021. We find that our measurements capture oceanic surface motions as those measured by nearby traditional oceanographic instruments. This study demonstrates that ocean-bottom DAS can be used to infer the dynamic properties of near-shore oceans with an unprecedented spatio-temporal resolution.

Distributed Acoustic Sensing (DAS) offers a transformative solution for dense, high-resolution seismic monitoring to address the challenges of traditional seismometers in urban seismic surveys. Here, we employ seismic interferometry of the ambient noise field and the trace stretching method to monitor seismic velocity variations in Mexico City. We present spatiotemporal variations in relative Rayleigh wave group velocity (dU/U) calculated over two frequency bands (0.4-1.2 Hz and 1.2-3.6 Hz) using DAS data collected over a year. To investigate these variations, we model the impacts resulting from the 2022 Mw7.6 earthquake, along with the effects of precipitation and temperature on the dU/U calculated in the 0.4-1.2 Hz frequency band, which is primarily dominated by the fundamental mode of the Rayleigh waves. Our results indicate that the earthquake-induced velocity drop differs in certain fiber sections, likely due to their non-linear soil behaviors and co-seismic stress changes but without relation to the maximum local deformation registered during the earthquake. Additionally, our modeling indicates that the velocity changes are influenced by seasonal temperature variations, and the impact of precipitation is relatively minor, at least for the depth range (<~50 m) examined in this study. This study highlights the capability of DAS to enhance spatiotemporal monitoring in urban environments, providing valuable insights into both seismic and environmental responses.

Volcanic eruptions progress by co-evolving fluid and solid systems. The fluid mechanics can be observed through the plumes and ejecta produced, but how does the solid system evolve? When does the conduit open? When does it close? Seismology can potentially tell us about these processes by measuring the failure of the solid rock. Such inferences require the detection of earthquakes during an explosive eruption. Standard earthquake detection methods often fail during this time as the eruption itself produces seismic waves that obscures the earthquake signals. We address this problem by applying supervised and unsupervised search techniques to the existing catalog of the 2008 Okmok eruption to find brittle failure signals during the continuous eruptive sequence. The interaction between fluid pathways and seismicity is reinforced by high precision earthquake relocations that highlight a ring-fault structure, which may be acting as a conduit for fluids to the surface. The timing of the earthquakes during the eruption reveal that the seismicity gradually increases during the vent-opening stage (July 12-July 24), peaks during the vent-widening stage (July 24-August 1) which culminates in a large burst of earthquakes, and then gradually decrease until the end of the eruptive period. Seismic bursts during the eruption are not synchronized with the exhalation of large ash and steam plumes. In other words, when the system is closed, the rock breaks. We call this scenario clog and crack.

Seismic waves can be significantly amplified by soft sediment layers. Large dynamic strains can trigger a nonlinear response of shallow soils having low strength, which is characterized by a shift of the resonance frequencies, ground motion deamplification, and in some cases, soil liquefaction. We investigate the response of marine sediments during earthquake ground motions recorded along a fiber-optic cable offshore the Tohoku region, Japan, with Distributed Acoustic Sensing (DAS). We compute AutoCorrelation Functions (ACFs) of the ground motions from 103 earthquakes in different frequency bands. We detect time delays in the ACF waveforms that are converted to relative velocity changes (dv/v). dv/v drops, which are characteristic of soil nonlinearity, are observed during the strongest ground motions. Moreover, the dv/v values show a strong variability along the cable. This study demonstrates that DAS can be used to infer the dynamic properties of the shallow Earth with an unprecedented spatial resolution.