This paper presents a mechanics-informed, data-driven framework for modeling liquefaction-induced disruption of roadway networks following a magnitude-9 earthquake on the Cascadia Subduction Zone (CSZ). Liquefaction hazard is predicted using a geospatial liquefaction model trained on more than 37,000 cone penetration tests (CPTs) and conditioned on spatial data describing geomorphology, hydrology, climate, and surficial geology. Ground motions are derived from physics-based ensembles of CSZ rupture scenarios. Segment-level probabilities of closure and service degradation are estimated using empirically derived fragility relationships and propagated through the National Highway System using spatially correlated Monte Carlo simulation. Results indicate strong concentration of impacts in coastal lowlands, estuaries, and river valleys, with pronounced exposure along U.S. Route 101. Focused analysis in Pacific and Grays Harbor Counties, Washington, shows elevated probability of healthcare isolation. Compared with prior statewide assessments based on geologic screening, predicted bridge closures due solely to liquefaction are an order of magnitude lower, reflecting improved representation of subsurface conditions and damage mechanisms. Despite uncertainties, the framework provides a defensible tool for transportation resilience planning and asset prioritization in Cascadia.

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