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New Perspectives on Hydrological Monitoring from Passive Seismic Interferometry

Figure 2. Seasonal variabilities of Δv/v and surface deformation [7,10]. a-c: Maps of the seasonal amplitude of Δv/v in three decreasing frequency bands, sensitive to changes at increasing depths. d: Map of the seasonal amplitude of vertical displacement

With climate change and population growth, securing freshwater supply is an imminent challenge faced by humanity worldwide [Figure 1]. An overarching component of freshwater resources is groundwater, which makes up 98% of liquid freshwater on Earth and contributes to over 60% of California’s water supply in dry years. Despite its critical importance to water security, groundwater is often poorly monitored and managed compared to more visible surface water (e.g., in rivers, lakes, and reservoirs) [1]. A fundamental obstruction to understanding groundwater systems is the lack of observations. In recent years, national or global networks of groundwater monitoring (e.g., the National Water Information System operated by USGS [2], and the Global Groundwater Monitoring Network [3]) have been established to facilitate the management of groundwater aquifers. Still, the availability of groundwater data remains insufficient. Geodetic tools (including GRACE, GNSS/GPS, and InSAR [4-7]) have provided invaluable information about the spatiotemporal variations of the Terrestrial Water Storage (i.e., the sum of all water on the land surface and in the subsurface). Yet, these vertically integrated measurements lack the depth resolution, which is key to isolating different hydrologic components and assessing their impact.

Figure 1. Continental U.S. percent area in U.S. Drought Monitor Categories. It shows that over 40% of the continental U.S. has suffered from different droughts in the past two decades.

Passive seismological techniques are emerging as powerful tools to bring novel perspectives to groundwater monitoring.  Seismic velocity (i.e., the propagation speed of seismic waves) is associated with the mechanical state of Earth’s medium, so the relative changes in seismic velocity (Δv/v) can serve to quantify the variations in groundwater content.  The spatiotemporal variations of Δv/v can be measured continuously, in near real-time, by employing the passive seismic interferometry techniques in two steps: Firstly, calculating the interferometry of the ambient seismic field recorded at two seismometers on different days provides estimates of the seismic Green’s functions for the corresponding days [8,9]. These Green’s functions allow the continuous measurement of Δv/v. Secondly, an advanced coda-wave interferometry protocol, leveraging the newly developed coda-wave sensitivity kernels, allows further imaging Δv/v in space. Combining these two steps, the passive seismic approach provides time-lapse imaging of Δv/v that can quantitatively inform the 4D (space-time) variations of groundwater volume.

Figure 2. Seasonal variabilities of Δv/v and surface deformation [7,10]. a-c: Maps of the seasonal amplitude of Δv/v measured in three decreasing frequency bands, sensitive to changes at increasing depths. d: A map of the seasonal amplitude of vertical displacement at the Earth’s surface inferred from InSAR [7].

The promise of this cost-effective passive seismic technique is highlighted by a pilot application [10] focusing on groundwater aquifers in the water-stressed Los Angeles (LA) metropolitan area. Using ~50 existing seismic stations in the Southern California Seismic Network [11], the measured Δv/v well recovered the records of groundwater table from 2000 to 2020, showing the potential of leveraging seismic data to improve substantially the spatiotemporal resolution of point-scale borehole measurements. The spatial patterns of Δv/v seasonality agree with surface deformation inferred from InSAR, but also further enable the of understanding aquifer behaviors at different depths [Figure 2]. The depth resolution from the seismic approach is crucial in distinguishing the hydrological processes occurring in different layers (e.g., changes in vadose zones, unconfined aquifers, or confined aquifers), which is not easy by using other techniques such as satellite-sensing (that only gives images at Earth surface) or electromagnetic methods (that usually provides local-scale static imaging at relatively shallow depth).

Furthermore, the seismic approach allows, for the first time, the direct imaging of aquifer storage changes over two decades at depth, without the need to drill hundreds of (nested) monitoring wells across metropolitan LA. Such images reveal distinct patterns of long-term groundwater changes in adjacent basins around LA due to the different pumping practices in different water districts. This analysis illustrates the significance of human activities in shaping the hydrologic systems, compounding the effect of climate change. The anthropogenic impact on shallow subsurface can now be verified and quantified by seismological analysis. This example also showcases the potential of using dv/v to assess the groundwater budget: The seismic approach is independent of the traditional groundwater modeling (based on precipitation, stream flow, and hydraulic head) that may be subject to considerable uncertainties without accurate aquifer models.

 

Figure 3. A comparison of the drought map and the coverage of seismic stations in California. Left: California drought intensity in July 2021 [National Drought Mitigation Center]. Right: Existing and proposed seismic stations in California as of 2018 [California Governor’s Office of Emergency Services; USGS; NCEDC; SCEDC].

Being cost-effective and non-invasive, the passive seismic interferometry technique is increasingly recognized as a potent tool to enhance the knowledge of groundwater aquifers. With the coverage of seismic stations improving rapidly in many water-challenged regions (e.g., the Central Valley in California) [Figure 3], the seismic network can also serve as a hydrological network to tackle the basin-wide aquifer structures and quantify storage changes. In response to extreme weather (e.g., the historic droughts over the past two decades and the acute storms in 2023 in California), seismic monitoring is instrumental in adjusting water management in a data-informed manner. Moreover, this passive seismic technique opens up the possibility of understanding a wide range of environmental processes and the anthropogenic interactions with the shallow subsurface.

 

 

 

 

About the Authors

Shujuan Mao is a Thompson Postdoctoral Fellow in the Department of Geophysics at Stanford University. Her research focuses on the monitoring and understanding of various processes in the Earth’s shallow subsurface, associated with groundwater resources, geothermal energy, carbon capture and storage, and human-environment interactions.
Michel Campillo  is a Professor of Geophysics at Université Grenoble Alpes in France. His recent research largely focuses on the use of continuous seismic records of ambient fields or diffuse waves, with numerous applications at different scales from the deep Earth to experiments in the laboratory.

References​

  1. Famiglietti, J. S. (2014). The global groundwater crisis. Nature Climate Change, 4(11), 945-948.
  2. U.S. Geological Survey (2016). National Water Information System data available on the World Wide Web (USGS Water Data for the Nation). http://doi.org/10.5066/F7P55KJN
  3. Struckmeier, W. et al. Groundwater Resources of the World (1:25,000,000) (BGR & UNESCO World-wide Hydrogeological Mapping and Assessment Programme, 2008).
  4. Rodell, M., Velicogna, I., & Famiglietti, J. S. (2009). Satellite-based estimates of groundwater depletion in India. Nature, 460(7258), 999-1002.
  5. Borsa, A. A., Agnew, D. C., & Cayan, D. R. (2014). Ongoing drought-induced uplift in the western United States. Science, 345(6204), 1587-1590.
  6. Schmidt, D. A., & Bürgmann, R. (2003). Time‐dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometric synthetic aperture radar data set. Journal of Geophysical Research: Solid Earth, 108(B9).
  7. Riel, B., Simons, M., Ponti, D., Agram, P., & Jolivet, R. Quantifying ground deformation in the Los Angeles and Santa Ana Coastal Basins due to groundwater withdrawal. Water Resources Research, 54(5), 3557-3582 (2018).
  8. Campillo, M. & Paul, A. Long-range correlations in the diffuse seismic coda. Science 299, 547–549 (2003).
  9. Brenguier, F. et al. Towards forecasting volcanic eruptions using seismic noise. Nature Geoscience 1, 126–130 (2008).
  10. Mao, S., Lecointre, A., van der Hilst, R. D., & Campillo, M. (2022). Space-time monitoring of groundwater fluctuations with passive seismic interferometry. Nature communications, 13(1), 4643.
  11. SCEDC, Southern California Earthquake Data Center, Dataset, 2013. http://scedc.caltech.edu