Keywords

Soil liquefaction, Lateral Displacement Index (LDI), Spatial analysis, Earthquake engineering, Christchurch earthquake, Cone Penetration Test (CPT)

Abstract

Liquefaction-induced lateral spreading is a major type of earthquake-induced ground failure hazard and poses a significant threat to infrastructure systems. While semi-empirical methods, such as Lateral Displacement Index (LDI), have been developed to estimate lateral spreading displacement (LSD), their efficacy for regional-scale liquefaction hazard assessment remains unknown. This study evaluates and improves the LDI method for urban-scale seismic hazard assessments using a comprehensive dataset consisting of 1,713 Cone Penetration Test (CPT) case histories from the 2011 Christchurch, New Zealand earthquake, and high-resolution topographic data. Comparing the predicted LSDs and ground-truth observations from both field investigations and remote-sensing surveys reveals that the LDI method only achieves a success rate of 54.5 %. These prediction failures stem from stratigraphic shielding by cohesive soil interlayers and a lack of geomorphic constraints, such as free-face proximity. To address this, this study explores alternative liquefaction triggering components, specially incorporating advancements after the LDI development and found that an optimal procedure incorporating procedures (Idriss & Boulanger, 2008; Youd et al., 2001) could improve success rate to 68.4%. In addition, a novel depth-weighting function for strain integration was proposed according to the centroid analysis of strain-depth distributions of under and good prediction samples, improving the success rate to 81.4%. Overall, these optimization procedures reduced under-predictions by 69.4% and increased good displacement estimates by 49.4%. Dependable urban-scale LSD assessment requires coupling depth-weighted kinematic drivers with specific geomorphic and stratigraphic boundary conditions.

Completion Date

2026

Semester

Spring

Committee Chair

Dr. Weiwei Zhan

Degree

Master of Science in Civil Engineering (M.S.C.E.)

College

College of Engineering and Computer Science

Department

Civil, Environmental and Construction Engineering

Document Type

Dissertation/Thesis

Identifier

DP0053174

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