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Abstract We use the deterministic earthquake simulator RSQSim to generate complex sequences of ruptures on fault systems used for hazard assessment. We show that the source motions combined with a wave propagation code create surface ground motions that fall within the range of epistemic uncertainties for the Next Generation Attenuation-West2 set of empirical models. We show the model is well calibrated where there are good data constraints, and has good correspondence in regions with fewer data constraints. We show magnitude, distance, and mechanism dependence all arising naturally from the same underlying friction. The deterministic physics-based approach provides an opportunity for better understanding the physical origins of ground motions. For example, we find that reduced stress drops in shallow layers relative to constant stress drop with depth lead to peak ground velocities in the near field that better match empirical models. The simulators may also provide better extrapolations into regimes that are poorly empirically constrained by data because physics, rather than surface shaking data parameterizations, is underlying the extrapolations. Having shown the model is credible, we apply it to a problem where observations are lacking. We examine the case of crustal faults above a shallow subduction interface seen to break coseismically in simulations of the New Zealand fault system. These types of events were left out of consideration in the most recent New Zealand national seismic hazard model due to the modeling complexity and lack of observational data to constrain ground-motion models (GMMs). Here, we show that in the model, by breaking up the coseismic crustal and interface rupturing fault motions into two separate subevents, and then recombining the resulting ground-motion measures in a square-root-of-sum-of-squares incoherent manner, we reproduce well the ground-motion measures from the full event rupture. This provides a new method for extrapolating GMMs to more complex multifault ruptures. 

Abstract Surface rupture from the 2019 Ridgecrest earthquake sequence, initially associated with the Mw 6.4 foreshock, occurred on 4 July on a ∼17  km long, northeast–southwest-oriented, left-lateral zone of faulting. Following the Mw 7.1 mainshock on 5 July (local time), extensive northwest–southeast-oriented, right-lateral faulting was then also mapped along a ∼50  km long zone of faults, including subparallel splays in several areas. The largest slip was observed in the epicentral area and crossing the dry lakebed of China Lake to the southeast. Surface fault rupture mapping by a large team, reported elsewhere, was used to guide the airborne data acquisition reported here. Rapid rupture mapping allowed for accurate and efficient flight line planning for the high-resolution light detection and ranging (lidar) and aerial photography. Flight line planning trade-offs were considered to allocate the medium (25 pulses per square meter [ppsm]) and high-resolution (80 ppsm) lidar data collection polygons. The National Center for Airborne Laser Mapping acquired the airborne imagery with a Titan multispectral lidar system and Digital Modular Aerial Camera (DiMAC) aerial digital camera, and U.S. Geological Survey acquired Global Positioning System ground control data. This effort required extensive coordination with the Navy as much of the airborne data acquisition occurred within their restricted airspace at the China Lake ranges. 

Following the Ridgecrest Earthquake Sequence, consisting of a M6.4 foreshock and M7.1 mainshock along with many other foreshocks and aftershocks, the Geotechnical Extreme Events Reconnaissance (GEER) Association deployed a team to gather perishable data. The team focused their efforts on documenting ground deformations including surface fault rupture south of the Naval Air Weapons Station China Lake, and liquefaction features in Trona and Argus. The team published a report within two weeks of the M7.1 mainshock. This paper presents data products gathered by the team, which are now published and publicly accessible. The data products presented herein include ground-based observations using GPS trackers, digital cameras, and hand measuring devices, as well as UAV-based imaging products using Structure from Motion to create point clouds and digital surface models. The paper describes the data products, as well as tools available for interacting with the products.