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Abstract The Rock Valley fault zone in southern Nevada has a notable history of seismic activity and is the site of a future direct comparison experiment of explosion and earthquake sources. This study aims to gain insight into regional tectonic processes by leveraging recent advances in seismic monitoring capabilities to elucidate the local stress regime. A crucial step in this investigation is the accurate determination of P-wave first-motion polarities, which play a vital role in resolving earthquake focal mechanisms of small earthquakes. We deploy a deep learning-based method for automatic determination of first-motion polarities to vastly expand the polarity dataset beyond what has been reviewed by human analysts. By the integrating P-wave polarities with new measurements of S/P amplitude ratios, we obtain robust focal mechanism estimates for 1306 earthquakes with a local magnitude of 1 and above occurring between 2010 and 2023 in southern Nevada. We then use the focal mechanism catalog to examine the regional stress orientation, confirming an overall trans-tensional stress regime with smaller scale complexities illuminated by individual earthquake sequences. These findings demonstrate how detailed analyses of small earthquakes can provide fundamental information for understanding earthquake processes in the region and inform future experiments at the Nevada National Security Site. 

Abstract Tectonic and seismogenic variations in subduction forearcs can be linked through various processes associated with subduction. Along the Cascadia forearc, significant variations between different geologic expressions of subduction appear to correlate, such as episodic tremor-and-slip (ETS) recurrence interval, intraslab seismicity, slab dip, uplift and exhumation rates, and topography, which allows for the systematic study of the plausible controlling mechanisms behind these variations. Even though the southern Cascadia forearc has the broadest topographic expression and shortest ETS recurrence intervals along the margin, it has been relatively underinstrumented with modern seismic equipment. Therefore, better seismic images are needed before robust comparisons with other portions of the forearc can be made. In March 2020, we deployed the Southern Cascadia Earthquake and Tectonics Array throughout the southern Cascadia forearc. This array consisted of 60 continuously recording three-component nodal seismometers with an average station spacing of ∼15 km, and stations recorded ∼38 days of data on average. We will analyze this newly collected nodal dataset to better image the structural characteristics and constrain the seismogenic behavior of the southern Cascadia forearc. The main goals of this project are to (1) constrain the precise location of the plate interface through seismic imaging and the analysis of seismicity, (2) characterize the lower crustal architecture of the overriding forearc crust to understand the role that this plays in enabling the high nonvolcanic tremor density and short episodic slow-slip recurrence intervals in the region, and (3) attempt to decouple the contributions of subduction versus San Andreas–related deformation to uplift along this particularly elevated portion of the Cascadia forearc. The results of this project will shed light on the controlling mechanisms behind heterogeneous ETS behavior and variable forearc surficial responses to subduction in Cascadia, with implications for other analogous subduction margins. 

Abstract Understanding the generation of damaging, high‐frequency ground motions during earthquakes is essential both for fundamental science and for effective hazard preparation. Various theories exist regarding the origin of high‐frequency ground motions, including the standard paradigm linked to slip heterogeneity on the rupture plane, and alternative perspectives associated with fault complexity. To assess these competing hypotheses, we measure ground motion amplitudes in different frequency bands for 3 ≤ M ≤ 5.8 earthquakes in Southern California and compare them to empirical ground motion models. We utilize a Bayesian inference technique called the Integrated Nested Laplace Approximation (INLA) to identify earthquake source regions that produce higher or lower ground motions than expected. Our analysis reveals a strong correlation between fault complexity measurements and the high‐frequency ground motion event terms identified by INLA. These findings suggest that earthquakes on complex faults (or fault networks) lead to stronger‐than‐expected ground motions at high frequencies.