Liquefaction can be a significant contributor to loss due to earthquakes as observed during the Canterbury earthquake sequence or the 1995 Kobe earthquake. Geospatial liquefaction models can be used to estimate liquefaction extent after an earthquake but do not estimate liquefaction damage or impact. This article presents a liquefaction loss database for the United States and event-level fragility functions (EFFs) using aggregate liquefaction hazard measures (LHMs) derived from geospatial liquefaction models. The liquefaction loss database for the United States is developed by sampling earthquakes with Magnitude > 5.0 between the years of 1964 and 2019 in the continental United States and Alaska. Within this sample of 42 earthquakes, 11 resulted in liquefaction loss. Estimates were characterized by the type of infrastructure (e.g. transportation, utilities, and buildings) and the subcategory (e.g. for buildings: residential, commercial, and public), and then loss was estimated using the 2018-equivalent US dollar amount. When possible, loss estimates were obtained directly from the literature. Within this sample of 42 earthquakes, 6 events resulted in estimated monetary losses from liquefaction damage greater than 1% of the total event loss, including one with liquefaction damage greater than 10%. Using estimates for aggregate liquefaction hazard and population exposure derived from geospatial liquefaction models as LHMs, EFFs are presented using cost-based damage state (DS) thresholds in the United States. The fragility functions also include confidence intervals representing the uncertainty in probabilities of exceeding DS thresholds. Aggregate liquefaction hazard was found to be a preferred LHM for liquefaction loss, especially when evaluating transportation and building loss. Aggregate population exposure was found to be a better LHM for utilities. In addition, a second set of EFFs is presented using an expanded international dataset and DSs which are assigned relative to overall earthquake damage rather than cost-based DSs.
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