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Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber
Author(s) -
Rodríguez Tribaldos Verónica,
AjoFranklin Jonathan B.
Publication year - 2021
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1029/2020jb021004
Subject(s) - ambient noise level , aquifer , water table , geology , groundwater , seismic noise , water well , noise (video) , remote sensing , seismology , hydrology (agriculture) , soil science , geomorphology , geotechnical engineering , sound (geography) , artificial intelligence , computer science , image (mathematics)
Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.