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Abstract 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 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 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.
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Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone
Abstract The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high‐frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ∼1 m to tens of m can be detected. These changes are driven by variations at the land surface. The Moving‐Window Cross‐Spectral (MWCS) method was employed to measure seismic‐velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological‐event‐based signal. These signals were compared to time‐series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time‐series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high‐frequency ambient noise data may in some locations be used to detect changes in the critical zone from ∼1 to ∼100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.
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- PAR ID:
- 10449893
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Earth Surface
- Volume:
- 126
- Issue:
- 2
- ISSN:
- 2169-9003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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