Geology topics

Brent G. Delbridge

Publications and source records attributed to Brent G. Delbridge.

3 recordsLinked to original sources

USGS2024

Making phase-picking neural networks more consistent and interpretable

Improving the interpretability of phase‐picking neural networks remains an important task to facilitate their deployment to routine, real‐time seismic monitoring. The popular phase‐picking neural networks published in the literature lack interpretability because their output prediction scores do not necessarily correspond with the reliability of phase picks and can even be highly inconsistent depending on how we window the waveform data. Here, we show that systematically shifting the waveforms during training and using an antialiasing filter within the neural network architecture can substantially improve the consistency of the output prediction scores and can even make them scale with the signal‐to‐noise ratios of the waveforms. We demonstrate the improvements by applying these approaches to a commonly used phase‐picking neural network architecture and using waveform data from the 2019 Ridgecrest earthquake sequence.

The Seismic Record↗

USGS2020

Geodetic measurements of slow slip events southeast of Parkﬁeld, CA

Tremor and low-frequency earthquakes are presumed to be indicative of surrounding slow, aseismic slip that is often below geodetic detection thresholds. This study uses data from borehole seismometers and long-baseline laser strainmeters to observe both the seismic and geodetic signatures of episodic tremor and slip on the Parkfield region of the San Andreas Fault near Cholame, CA. The observed occurrence rates of both the tremors and co-located families of low-frequency earthquakes are not steady but instead exhibit quasiperiodic bursts of increased activity. We show that these periods of elevated seismic activity correlate with statistically significant stacked strain signals consisting of 44 slow-slip events. Modeled individual slow-slip events and their total summed moment, which are constrained by seismic signals and stacked strain, respectively, indicate that the individual moment magnitudes of these events range from 4.6–5.2. We find that the measured geodetic signal likely precedes the seismic signal by several hours, consistent with the aseismic slip preceding and driving the observed seismic tremor activity. We confirm that strike-slip faults, in addition to subduction zones, are capable of producing episodic tremor and slip.

California↗

USGS2016

Three-dimensional surface deformation derived from airborne interferometric UAVSAR: Application to the Slumgullion Landslide

In order to provide surface geodetic measurements with “landslide-wide” spatial coverage, we develop and validate a method for the characterization of 3-D surface deformation using the unique capabilities of the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne repeat-pass radar interferometry system. We apply our method at the well-studied Slumgullion Landslide, which is 3.9 km long and moves persistently at rates up to ∼2 cm/day. A comparison with concurrent GPS measurements validates this method and shows that it provides reliable and accurate 3-D surface deformation measurements. The UAVSAR-derived vector velocity field measurements accurately capture the sharp boundaries defining previously identified kinematic units and geomorphic domains within the landslide. We acquired data across the landslide during spring and summer and identify that the landslide moves more slowly during summer except at its head, presumably in response to spatiotemporal variations in snowmelt infiltration. In order to constrain the mechanics controlling landslide motion from surface velocity measurements, we present an inversion framework for the extraction of slide thickness and basal geometry from dense 3-D surface velocity fields. We find that the average depth of the Slumgullion Landslide is 7.5 m, several meters less than previous depth estimates. We show that by considering a viscoplastic rheology, we can derive tighter theoretical bounds on the rheological parameter relating mean horizontal flow rate to surface velocity. Using inclinometer data for slow-moving, clay-rich landslides across the globe, we find a consistent value for the rheological parameter of 0.85 ± 0.08.

Colorado↗