Probabilistic assessment of liquefiable soil thickness considering spatial variability and model and parameter uncertainties

This paper develops a probabilistic approach for identifying liquefiable soil layers and assessing the liquefiable soil thickness using cone penetration tests (CPTs). The inherent spatial variability of liquefaction resistance (i.e. cyclic resistance ratio (CRR)), the model uncertainty associated with the CPT-based Robertson and Wride model and input parameter uncertainty in cyclic stress ratio (CSR) are taken into consideration explicitly in the proposed approach. The probability distribution of the CRR and the thicknesses of soil layers with statistically homogeneous CRR are first identified. Then, for a given nominal seismic loading, the thicknesses of liquefiable soil layers are estimated. A ratio of the liquefiable soil thickness over the total thickness of all soil layers considered is quantified for assessment of liquefaction consequences, and it is determined probabilistically using Monte Carlo simulations. The proposed approach is illustrated using a set of CPT data collected from New Zealand. Case histories of the 2010–2011 Canterbury earthquake sequence in New Zealand are used to systematically validate the proposed approach. The proposed approach is shown to identify properly the liquefiable soil layers, quantify their liquefiable soil thicknesses and associated uncertainty and provide results that are consistent with earthquake field observations. It is also shown that deterministic analysis not only cannot quantify the uncertainty in the assessment results, but also fails to provide consistent results for the assessment of liquefaction consequences. It is therefore necessary to perform probabilistic analysis using the proposed approach. In addition, a sensitivity study is performed to explore the effect of spatial variability on soil liquefaction.