Tuna, Sahin Caglar2026-04-072026-04-0720261879-341X0267-726110.1016/j.soildyn.2025.1100622-s2.0-105027932097https://hdl.handle.net/123456789/14788https://doi.org/10.1016/j.soildyn.2025.110062This study develops a comprehensive probabilistic, performance-based framework for assessing earthquakeinduced soil liquefaction by explicitly incorporating spatial variability through semivariogram-calibrated three-dimensional Gaussian Random Fields (3D GRFs). A dataset of 52 Standard Penetration Test (SPT) boreholes from I(center dot)zmir, Türkiye was processed to generate Monte Carlo simulations that capture the stochastic nature of soil resistance. Liquefaction susceptibility was quantified using three complementary indicators: the Liquefaction Potential Index (LPI), reflecting potential surface deformation; the Damage Severity Index (DSI), linking severity to engineering performance thresholds; and the depth-averaged probability of liquefaction P(Liq), representing occurrence likelihood across different seismic intensities. Fragility functions were developed using both logistic regression and Monte Carlo-GRF simulations, and subsequently coupled with site-specific seismic hazard curves to derive annualized liquefaction risk metrics expressed in return-period format. Results highlight the nonlinear escalation of liquefaction severity with increasing seismic demand, accompanied by a systematic growth of epistemic uncertainty. Scenario-based probabilistic mapping revealed spatial hot spots of susceptibility and variance, underlining the value of incorporating correlation structures in liquefaction hazard assessment. Validation against field evidence from the 2020 Samos Earthquake confirmed the predictive reliability of the framework, with GRF-based simulations producing results consistent with reconnaissance observations in I(center dot)zmir Bay and surrounding coastal sites. Overall, the proposed framework advances methodological clarity and provides actionable contributions for seismic microzonation, regional hazard mapping, and performance-based geotechnical design, supporting the development of more resilient infrastructure in earthquake-prone urban environments.eninfo:eu-repo/semantics/closedAccessPerformance-Based Design (PBD)Fragility AnalysisMonte Carlo SimulationSpatial VariabilityLiquefactionDamage Severity Index (DSI)Gaussian Random Field (GRF)Article