Using a 20‐year continuous broadband record and two independent single‐station techniques—ambient noise autocorrelation and receiver functions—we document a relationship between subsurface seismic response and groundwater levels (GWLs) in the Gulf Coast Aquifer System of southern Texas. We find that a surge of GWL following three consecutive hurricanes and documented at an adjacent monitoring well is accompanied with changes in receiver function power spectra and ambient noise autocorrelations. Using a simple physical model, we show that GWL changes should affect P‐ (VP) more strongly than S‐wave (VS) velocities, consistent with our observations and previous ones based on inter‐station correlations. Agreement between receiver function and ambient noise analyses shows that both can be used to reliably estimate temporal changes in subsurface properties on long timescales. Due to their sensitivity to VP, single‐station techniques respond more strongly to GWL changes, making them useful for characterizing and monitoring aquifer systems.

Receiver functions are sensitive to sharp seismic velocity variations with depth and are commonly used to constrain crustal thickness. The H–κ stacking method of Zhu & Kanamori is often used to constrain both the crustal thickness (H) and ${V_P}$/${V_S}$ ratio ($\kappa $) beneath a seismic station using P-to-s converted waves (Ps). However, traditional H–κ stacks require an assumption of average crustal velocity (usually ${V_P}$). Additionally, large amplitude reverberations from low velocity shallow layers, such as sedimentary basins, can overprint sought-after crustal signals, rendering traditional H–$\ \kappa $ stacking uninterpretable. We overcome these difficulties in two ways. When S-wave reverberations from sediment are present, they are removed by applying a resonance removal filter allowing crustal signals to be clarified and interpreted. We also combine complementary Ps receiver functions, Sp receiver functions, and the post-critical P-wave reflection from the Moho (SPmp) to remove the dependence on an assumed average crustal ${V_P}$. By correcting for sediment and combining multiple data sets, the crustal thickness, average crustal P-wave velocity and crustal ${V_P}$/${V_S}$ ratio is constrained in geological regions where traditional H–$\ \kappa $ stacking fails, without making an initial P-wave velocity assumption or suffering from contamination by sedimentary reverberations.

Temperature distribution at depth is of key importance for characterizing the crust, defining its mechanical behavior and deformation. Temperature can be retrieved by heat flow measurements in boreholes that are sparse, shallow, and have limited reliability, especially in active and recently active areas. Laboratory data and thermodynamic modeling demonstrate that temperature exerts a strong control on the seismic properties of rocks, supporting the hypothesis that seismic data can be used to constrain the crustal thermal structure. We use Rayleigh wave dispersion curves and receiver functions, jointly inverted with a transdimensional Monte Carlo Markov Chain algorithm, to retrieve the VS and VP/VS within the crust in the Italian peninsula. The high values (>1.9) of VP/VS suggest the presence of filled‐fluid cracks in the middle and lower crust. Intracrustal discontinuities associated with large values of VP/VS are interpreted as the α−β quartz transition and used to estimate geothermal gradients. These are in agreement with the temperatures inferred from shear wave velocities and exhibit a behavior consistent with the known tectonic and geodynamic setting of the Italian peninsula. We argue that such methods, based on seismological observables, provide a viable alternative to heat flow measurements for inferring crustal thermal structure.

(1) Max-Planck Institute for Solar System Science, Planets and Comets, Göttingen, Germany (joshir@mps.mpg.de), (2) Institute of Geology and Mineralogy, University of Cologne, Cologne, Germany (brigitte.knapmeyer-endrun@uni-koeln.de), (3) Institute of Geophysics, ETH Zürich, Switzerland (vandriel@erdw.ethz.ch), (4) Institute of Geophysics, ETH Zürich, Switzerland (savas.ceylan@erdw.ethz.ch), (5) Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA (mark.p.panning@jpl.nasa.gov)