A Framework for Modeling Liquefaction-Induced Road Disruptions After Earthquakes: Implications for Emergency Response and Access in the Cascadia Region of North America

arXiv cs.LG / 3/19/2026

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Key Points

It introduces a mechanics-informed, data-driven framework to estimate liquefaction-induced road closures and service reductions after earthquakes.
The framework is applied to a magnitude-9 Cascadia Subduction Zone earthquake, converting liquefaction severity into segment-level closure probabilities via empirically derived fragility relationships and mapping at 90 m resolution.
A spatially correlated Monte Carlo simulation propagates disruptions through the National Highway System to estimate link-level disruption patterns, identifying concentration in coastal zones and along critical routes such as US Route 101.
The analysis highlights elevated isolation risk and potential loss of hospital access in Washington’s Pacific and Grays Harbor counties, with modest associations to socioeconomic indicators.
It stresses that the approach provides a regional planning baseline and can be adapted to other regions, though it is not a substitute for site-specific geotechnical analysis.

Abstract

Large earthquakes along the Cascadia Subduction Zone (CSZ) are expected to trigger widespread soil liquefaction that could disrupt transportation systems across the U.S. Pacific Northwest. However, past regional assessments have relied on simple geologic screening methods and binomial shaking thresholds that are only loosely informed by liquefaction science. This study introduces a mechanics-informed, data-driven framework for estimating liquefaction-induced road closures and service reductions, and the framework is applied to a magnitude-9 CSZ earthquake. Predicted liquefaction severity is translated into segment-level probabilities of closure and reduced service using empirically derived fragility relationships. These probabilities are mapped at 90-m resolution and propagated through the National Highway System using a spatially correlated Monte Carlo simulation to estimate link-level disruption. Results show that impacts are concentrated in low-lying coastal zones, river valleys, and urban waterfronts, with major disruptions expected along critical routes including U.S. Route 101. Local mobility is further examined in Pacific and Grays Harbor counties, Washington, where limited network redundancy, strong shaking, and high liquefaction susceptibility lead to elevated probabilities of isolation and loss of hospital access. Socioeconomic analysis reveals modest but statistically significant associations between road impacts and demographic indicators, suggesting that liquefaction impacts may compound with existing social vulnerabilities. While not a substitute for site-specific analysis, the results provide a regional baseline for emergency planning, risk communication, and prioritization of more advanced geotechnical sampling and analysis. Moreover, the methodology proposed here is not specific to the CSZ, but rather, could be applied to analogous studies of road impacts elsewhere.