Liquefaction probability curves for surficial geologic deposits

Environmental & Engineering Geoscience
By: , and 



Liquefaction probability curves that predict the probability of surface manifestations of earthquake-induced liquefaction are developed for 14 different types of surficial geologic units. The units consist of alluvial fan, beach ridge, river delta topset and foreset beds, eolian dune, point bar, flood basin, natural river and alluvial fan levees, abandoned river channel, deep-water lake, lagoonal, sandy artificial fill, and valley train deposits. Probability is conditioned on earthquake magnitude and peak ground acceleration. Curves are developed for water table depths of 1.5 and 5.0 m. Probabilities are derived from complementary cumulative frequency distributions of the liquefaction potential index (LPI) that were computed from 927 cone penetration tests. For natural deposits with a water table at 1.5 m and subjected to a M7.5 earthquake with peak ground acceleration (PGA)  =  0.25g, probabilities range from <0.03 for alluvial fan and lacustrine deposits to >0.5 for beach ridge, point bar, and deltaic deposits. The curves also were used to assign ranges of liquefaction probabilities to the susceptibility categories proposed previously for different geologic deposits. For the earthquake described here, probabilities for susceptibility categories have ranges of 0–0.08 for low, 0.09–0.30 for moderate, 0.31–0.62 for high, and 0.63–1.00 for very high. Retrospective predictions of liquefaction during historical earthquakes based on the curves compare favorably to observations.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Liquefaction probability curves for surficial geologic deposits
Series title Environmental & Engineering Geoscience
DOI 10.2113/gseegeosci.17.1.1
Volume 17
Issue 1
Year Published 2011
Language English
Publisher Association of Environmental & Engineering Geologists
Contributing office(s) Earthquake Science Center
Description 21 p.
First page 1
Last page 21
Country United States
Google Analytic Metrics Metrics page
Additional publication details