Relative seismic velocity changes (dv/v) are being increasingly used to monitor changes in groundwater. However, it remains challenging to verify its implementation in watersheds without direct groundwater well measurements. In this study, we conduct a twelve year dv/v observation in a watershed of the Yellowstone National Park. We find that the seasonal fluctuations and long-term trend of the measured dv/v are highly correlated with the estimated baseflow, which serves as a constraint for groundwater changes. We integrate the estimated baseflow into a poroelastic mechanism and conduct two dv/v simulations based on pressure diffusion. These two simulations closely match with our observed dv/v variations. In addition, our analysis suggest that the measured dv/v is primarily influenced by hydrologic pressure diffusion rather than surface air temperature. We conclude that the baseflow analysis can further enhance the seismic monitoring of groundwater changes.

Ambient seismic noise (ASN) recorded by ocean bottom seismometers allows us to perform coda wave interferometry without using active sources. We analyzed two-year ASN recordings from five ocean bottom stations in the northwestern Pacific Ocean basin (depth > 5,500 m), and measured the relative velocity variation (\(\delta\)v/v) near the seafloor. The most important finding is an extremely low variation in \(\delta\)v/v (around -0.05\%), which likely responds to a significant pressure drop at sea level and subsequently affects an anomaly at the ocean bottom (over -400 Pa) in December 2013. Furthermore, several major phases of the velocity change show delayed-correlation with the sea level pressure variations. A poroelastic simulation with adjusted ocean bottom variables supports the pressure factor mainly drives the variation in \(\delta\)v/v. Our study suggests the potential use of seismic signals to monitor oceanic and atmospheric processes by tracking variations in the oceanic pressure field.

We utilize twelve-year ambient seismic noise (ASN) recordings to measure near-surface seismic velocity variations (dv/v) within the YNP flooding watersheds. We have observed that the annual peaks of dv/v variations have two to three months lead-time in comparison to anomalous water discharges. Our analysis indicates that the annual cycle of dv/v is highly correlated with the effective precipitation, which takes into account the snowpack loading and melting water infiltration processes. The annual peaks of dv/v are likely caused by abnormal melt water, which exceed the water storage capacity of the land. Furthermore, the best-fit poroelastic model provides further evidence that precipitation factors primarily influence the variations of the seismic field. Our analysis successfully explains the indicative changes in dv/v prior to the 2014 and 2022 YNP floods. This study demonstrates the potential of using seismic observables to monitor and assess the risk of devastating floods in the YNP.