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Qiu, Hongrui

Publications and source records attributed to Qiu, Hongrui.

Internal Structure of the Central Garlock Fault Zone From Ridgecrest Aftershocks Recorded by Dense Linear Seismic Arrays

Abstract We provide high‐resolution seismic imaging of the central Garlock fault using data recorded by two dense seismic arrays that cross the Ridgecrest rupture zone (B4) and the Garlock fault (A5). Analyses of fault zone head waves and P ‐wave delay times at array A5 show that the Garlock fault is a sharp bimaterial interface with P waves traveling ∼5% faster in the northern crustal block. The across‐fault velocity contrast agrees with regional tomography models and generates clear P ‐wave reflections in waveforms recorded by array B4. Kirchhoff migration of the reflected waves indicates a near‐vertical fault between 2 and 6 km depth. The P ‐wave delay times imply a ∼300‐m‐wide transition zone near the Garlock fault surface trace beneath array A5, offset to the side with faster velocities. The results provide important constraints for derivations of earthquake properties, simulations of ruptures and ground motion, and future imaging studies associated with the Garlock fault.

58 GEOSCIENCES↗

Monitoring Seasonal Shear Wave Velocity Changes in the Top 6 m at Garner Valley in Southern California With Borehole Data

Abstract Subsurface structures play important roles in seismic ground motion, crustal hydrology, stability of the built environment, and more. Constraining temporal changes of subsurface shear wave velocity ( V S ) can provide useful information to all these topics and the growing field of hydrological monitoring with seismic velocity. Using borehole records at Garner Valley, CA, we estimate seasonal subsurface V S variations from impulse response functions (IRFs) of earthquake data (2005–2018) along with IRFs and cross‐correlation of cross‐hole experiment data (2015–2018). The inferred V S variations are up to ∼25% in the top 6 m and ∼10% at 2–5 m in depth. The V S variations correlate strongly with the water table depth changes, suggesting that the changes are mostly due to fluctuations of pore pressure in the shallow material. The shallow velocity changes alter the near‐surface conditions, can affect seismic hazard estimation, and may be improperly attributed to deeper processes without careful analysis.

58 GEOSCIENCES↗

Data–Driven Velocity Model Evaluation Using K–Means Clustering

In this work, we develop a data-driven clustering method to evaluate a velocity model using surface wave velocity dispersion. This is done by first computing theoretical dispersion curves for 1-D velocity profiles of all the grid locations and then splitting the resulting dispersion curves into a certain number of groups via the K-means clustering. The observed dispersion curves are also clustered following the same procedure and the velocity model is assessed by comparing the spatial patterns obtained for the observed and synthetic data sets. The method is applied to evaluate two community velocity models in southern California, CVM-S4.26 and CVM-H15.1, using phase velocity maps derived for 3–16 s Rayleigh waves. We found a good correlation in the spatial distribution of clusters between the result of CVM-S4.26 and that of the observed data, suggesting that the CVM-S4.26 fits the observed dispersion maps better than the CVM-H15.1 in terms of features extracted from the clustering analysis.

58 GEOSCIENCES↗

Seismic Imaging of the Mw 7.1 Ridgecrest Earthquake Rupture Zone From Data Recorded by Dense Linear Arrays

Abstract We analyze seismograms recorded by four arrays (B1–B4) with 100 m station spacing and apertures of 4–8 km that cross the surface rupture of the 2019 Mw 7.1 Ridgecrest earthquake. The arrays extend from B1 in the northwest to B4 in the southeast of the surface rupture. Delay times between P wave arrivals associated with ∼1,200 local earthquakes and four teleseismic events are used to estimate local velocity variations beneath the arrays. Both teleseismic and local P waves travel faster on the northeast than the southwest side of the fault beneath arrays B1 and B4, but the velocity contrast is less reliably resolved at arrays B2 and B3. We identify several 1–2 km wide low‐velocity zones with much slower inner cores that amplify S waveforms, inferred as damage zones, beneath each array. The damage zones at arrays B2 and B4 also generate fault‐zone head and trapped waves. An automated detector, based on peak ground velocities and durations of high‐amplitude waves, identifies candidate fault‐zone trapped waves (FZTWs) in a localized zone for ∼600 earthquakes at array B4. Synthetic waveform modeling of averaged FZTWs, generated by ∼30 events with high‐quality signals, indicates that the trapping structure at array B4 has a width of ∼300 m, depth of 3–5 km, S wave velocity reduction of ∼20% with respect to the surrounding rock, Q ‐value of ∼30, and S wave velocity contrast of ∼4% across the fault (faster on the northeast side). The results show complex fault‐zone internal structures (velocity contrasts and low‐velocity zones) that vary along fault strike.

Qiu, Hongrui↗