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Physics-based ground motion simulations are a valuable tool for studying seismic sources with missing historical records, such as Cascadia Subduction Zone (CSZ) interface earthquakes. The last such event occurred in 1700 CE and is believed to be an M8-M9 rupture. The United States Geological Survey recently developed 30 physics-based simulations of a CSZ rupture to predict ground motions across the Pacific Northwest. Consideration of key modeling uncertainties across these simulations leads to estimates of ground motion intensity that vary by ~100% in some areas (e.g., Seattle). Paleoliquefaction, or soil liquefaction from past earthquakes, provides the best geologic evidence for constraining or "ground truthing" the intensity of past shaking, yet while paleoliquefaction has been documented throughout Cascadia, limited analyses have been performed to exploit this evidence. This study focuses on Kellogg Island, 2 mi south of Seattle, where liquefaction has been documented from several earthquakes, but not from the 1700 CE event. Therefore, using the CSZ simulations and in situ cone penetration test data, this study predicts the probability of surficial liquefaction manifestation at Kellogg Island during an M9 CSZ event. As part of this effort, velocity profiles are developed from multichannel analysis of surface waves, and non-linear site response analyses are used to propagate simulated motions to the surface. Results show a high probability of liquefaction near Kellogg Island for most simulations, whereas to date no evidence of 1700 CE liquefaction has been discovered at Kellogg Island, nor at any other location in the Puget Sound. The discrepancy between predictions and observations might indicate that the 1700 CE ground motions were less intense in Seattle than most predictions of M9 earthquakes indicate. Toward the goal of elucidating the expected impacts of future CSZ earthquakes, similar analyses are ongoing at additional sites across the region. 

While soil liquefaction is common in earthquakes, the case-history data required to train and test state-of-practice prediction models remains comparatively scarce, owing to the breadth and expense of data that comprise a single case history. The 2001 Nisqually, Washington, earthquake, for example, occurred in a metropolitan region and induced damaging liquefaction in the urban cores of Seattle and Olympia, yet case-history data have not previously been published. Accordingly, this article compiles 24 cone-penetration-test (CPT) case histories from free-field locations. The many methods used to obtain and process the data are detailed herein, as is the structure of the digital data set. The case histories are then analyzed by 18 existing liquefaction response models to determine whether any is better, and to compare model performance in Nisqually against global observations. While differences are measured, both between models and against prior global case histories, these differences are often statistically insignificant considering finite-sample uncertainty. This alludes to the general inappropriateness of championing models based on individual earthquakes or otherwise small data sets, and to the ongoing needs for additional case-history data and more rigorous adherence to best practices in model training and testing. 

In regions of infrequent moderate-to-large earthquakes, historic earthquake catalogs are often insufficient to provide inputs to seismic-hazard analyses (i.e. fault locations and magnitude–frequency relations) or to inform ground-motion predictions for certain seismic sources. In these regions, analysis of relic coseismic evidence, such as paleoliquefaction, is commonly used to infer information about the seismic hazard. However, while paleoliquefaction studies have been performed widely, all existing analysis techniques require a priori assumptions about the causative earthquake’s location (i.e. rupture magnitude and ground motions can otherwise not be estimated). This may lead to inaccurate assumptions in some settings, and by corollary, erroneous results. Accordingly, this article proposes an inversion framework to probabilistically constrain seismic-source parameters from paleoliquefaction. Analyzing evidence at regional scale leads to (a) a geospatial likelihood surface that constrains the rupture location and (b) a probability distribution of the rupture magnitude, wherein source-location uncertainty is explicitly considered. Simulated paleoliquefaction studies are performed on earthquakes with known parameters. These examples demonstrate the framework’s potential, even in cases of limited field evidence, as well as important caveats and lessons for forward use. The proposed framework has the potential to provide new insights in enigmatic seismic zones worldwide.