Ground‐motion studies are a key component of seismic hazard analyses and often rely on information of the source, path, and site. Extensive research has been done on each of these parameters; however, site‐specific studies are of particular interest to seismic hazard studies, especially in the field of earthquake engineering, as near‐site conditions can have a significant impact on the resulting ground motion at a site. There has been much focus on the constraint of site parameters and their application to seismic hazard studies, especially in the development of ground‐motion models (GMMs). Kappa is an observational parameter describing the high‐frequency attenuation of spectra, and its site contribution (⁠κ0⁠) has shown to be a good predictor of high‐frequency ground motions; however, measurements are often limited. In this study, we develop a κ0 dataset for the San Francisco Bay area (SFBA) by estimating κ0 for 228 stations, and we produce a continuous regional map of κ0⁠. We find κ0 to range between 0.003 and 0.072 s, with larger values concentrating on the east, north, and south sides of the bay, and lower values concentrating on the west side. We also evaluate the robustness of κ0 as a site parameter and find it to correlate with peak ground acceleration. These estimates of κ0 can add predictive power to GMMs, thus increasing the accuracy of predicted ground motion and improving the robustness of ground‐motion studies in the SFBA.

In the tectonically complex Imperial Valley, California (USA), the Imperial fault (IF) is often considered to be the primary fault at the U.S.-Mexico border; however, its strain partitioning and interactions with other faults are not well understood. Despite inferred evidence of other major faults (e.g., seismicity), it is difficult to obtain a holistic view of this system due to anthropogenic surface modifications. To better define the structural configuration of the plate-boundary strain in this region, we collected high-resolution shallow seismic imaging data in the All American Canal, crossing the Imperial, Dixieland, and Michoacán faults. These data image shallow (<25 m) structures on and near the mapped trace of the Imperial fault, as well as the Michoacán fault and adjacent stepover. Integration of our data with nearby terrestrial cores provides age constraints on Imperial fault deformation. These data suggest that the Michoacán fault, unmapped in the United States, is active and likely produces dynamic or off-fault deformation within its stepover to the Dixieland fault. Together, these data support more strain partitioning than previously documented in this region.

Subduction zone earthquakes result in some of the most devastating natural hazards on Earth. Knowledge of where great (moment magnitude M ≥ 8) subduction zone earthquakes can occur and how they rupture is critical to constraining future seismic and tsunami hazards. Since the occurrence of well-instrumented great earthquakes, such as the 2004 M9.1 Sumatra–Andaman and 2011 M9.1 Tohoku earthquakes, the hypotheses that plate age and convergence rate influence the ability of subduction zones to host large earthquakes have been dispelled. In this Review, we highlight how certain subduction zone properties might influence the location and characteristics of great earthquake rupture and impact seismic and tsunami hazard. The rupture characteristics of great earthquakes that most heavily impact earthquake hazards include the rupture extent (seaward and landward), location of strong motion-generating areas and earthquake recurrence. By contrast, large slip or displacement at the seafloor is one of the major controls of tsunami hazard. Future improvements in addressing hazards posed by subduction zones depend heavily on sustained geophysical monitoring in subduction zone systems (both onshore and offshore), expanded development of palaeoseismic data sets and improved integration of observations and models across disciplines and timescales.

In this presentation, we discuss our methodology for estimating the site parameter, k0, for 296 broadband and accelerometer stations in the San Francisco Bay area. We deviate from our initial methods outlined in the SSA 2021 conference presentation and instead use the k_AS (acceleration spectrum) method (Anderson and Hough, 1984; Anderson 1991; Ktenidou et al., 2014). Preliminary results show k0 to vary strongly, but overall estimates are moderate. Larger k0 estimates (i.e. greatest attenuation) are observed to the east and north of the Bay, whereas smaller k0 estimates (i.e. least attenuation) are observed to the west of the Bay.

We present an updated ground-motion model (GMM) for Mw 6–9 earthquakes using Global Navigation Satellite Systems (GNSS) observations of the peak ground displacement (PGD). Earthquake GMMs inform a range of Earth science and engineering applications, including source characterization, seismic hazard evaluations, loss estimates, and seismic design standards. A typical GMM is characterized by simplified metrics describing the earthquake source (magnitude), observation distance, and site terms. Most often, GMMs are derived from broadband seismometer and accelerometer observations, yet during strong shaking, these traditional seismic instruments are affected by baseline offsets, leading to inaccurate recordings of low-frequency ground motions such as displacement. The incorporation of geodetic data sources, particularly for characterizing the unsaturated ground displacement of large-magnitude events, has proven valuable as a complement to traditional seismic approaches and led to the development of an initial point-source GMM based on PGD estimated from high-rate GNSS data. Here, we improve the existing GMM to more effectively account for fault finiteness, slip heterogeneity, and observation distance. We evaluate the limitations of the currently available GNSS earthquake data set to calibrate the GMM. In particular, the observed earthquake data set is lacking in observations within 100 km of large-magnitude events (Mw>8), inhibiting evaluation of fault dimensions for earthquakes too large to be represented as point sources in the near field. To that end, we separately consider previously validated synthetic GNSS waveforms within 10–1000 km of Mw 7.8–9.3 Cascadia subduction zone scenario ruptures. The synthetic data highlight the importance of fault distance rather than point-source metrics and improve our preparedness for large-magnitude earthquakes with spatiotemporal qualities unlike those in our existing data set.