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Earthquake-induced landslides are associated with significant risks to human lives and infrastructure. Spatially distributed infrastructure systems, such as pipelines, power lines, and transportation networks, are at particular risk to seismic landslides due to their large spatial extent. To conduct a comprehensive seismic landslide risk assessment for these systems, there is the need to evaluate the seismic landslide characteristics (i.e., location, size, displacement, direction) on a broad, regional scale. This paper presents a framework for seismic landslide analysis that provides this information for subsequent risk assessments. The approach computes seismic landslide displacements using a sliding block approach while accounting for the uncertainties in the input variables and displacement models using a logic tree. The computed displacements are then aggregated based on geomorphic landforms to define landslide zones. For each landslide zone, the statistical distributions of landslide features, such as landslide size, displacement level, and direction of movement, are defined. These attributes are presented in a format that can be integrated with fragility models for distributed infrastructure systems to quantify risk on a regional scale. The application of the approach is demonstrated through assessments for gas pipeline networks across the state of California in the United States. • A framework for regional seismic landslide risk assessment is described. • A sliding block approach with a logic tree accounts for uncertainties. • Geomorphic landforms (slope units) are integrated to define landslide zones. • Distributions of landslide attributes are defined for input into fragility models. • Results are shown for a region of southern California. [ABSTRACT FROM AUTHOR]

Various predictive models for the seismically-induced displacement (D) of flexible slopes during shallow crustal earthquakes are available in the literature, but the model-to-model difference of predictions remains unclear. This paper conducts a comprehensive comparative study of ten representative D models based on scenario- and probabilistic-based displacement analyses. Explicit expressions are provided to implement the probabilistic displacement hazard approach, in which copula theory is utilized for deriving the joint occurrence probability of ground-motion parameters. A total of 6048 displacement hazard analyses are performed considering different earthquake and slope scenarios. It is found that the model-to-model difference generally becomes larger with increasing the natural period (T s) of a sliding mass, whereas the within-type difference among different coupled models is notably smaller than that of the decoupled models. The coupled-type models generally result in smaller total variability of D as compared to the decoupled-type models. Meanwhile, the coupled models tend to, on average, yield larger (or smaller) hazard-consistent D than the decoupled models for T s larger (or smaller) than an intersection period T s,inter , though the difference between the two model types diminishes as T s approaches zero. The effects of ground-motion model selection and ground-motion parameter correlation are also discussed. This study could hopefully provide insights into the displacement model selection for the seismic slope performance assessment and regional landslide hazard mapping. • Comparative studies of ten slope displacement models are conducted. • Copula-assisted probabilistic displacement hazard procedures are presented. • Models yielding lower- and upper-bound displacement hazards are identified. • Relative difference between decoupled and coupled predictions is closely related to T s. • Within-type difference among coupled models is smaller compared to decoupled models. [ABSTRACT FROM AUTHOR]

Seismic fragility analysis is one probabilistic method that represents the conditional probabilities of exceeding different predetermined damage states for various given earthquake hazard levels, which is the essential part of probabilistic seismic risk assessment. It has gained much popularity recently because much more comprehensive and richer results than traditional probabilistic methods can be provided. The classical seismic fragility analysis of slopes is always performed through analytical approaches. In the present study, a novel seismic fragility analysis framework combined with shaking table model test results is proposed for probabilistic seismic performance and risk assessment of slopes. The shaking table model tests of a rock slope reinforced by pile-anchor structures were firstly performed subjected to a suite of real earthquake records with different intensity levels. Subsequently, the seismic responses from shaking table model tests were then gathered for the optimal analysis to determine the optimal engineering demand parameter (EDP) and earthquake intensity measure (IM) for seismic fragility analysis of slopes. At last, the identified most appropriate IM and EDP were selected to construct the scalar-valued fragility curves, vector-valued fragility surfaces and fragility surfaces considering acceleration elevation amplification effect by the proposed framework. The results indicate that using single IM to construct scalar-valued fragility functions may result in different failure probabilities depending on the chosen earthquake IM. The vector-valued fragility surfaces provide more information than ordinary fragility curves, and lead to more proper and realistic evaluations of seismic hazard of slopes. The methods and results presented in this paper also provide the basis for the probabilistic seismic risk and loss assessment of earthquake-induced slope geological disaster. • A novel seismic fragility analysis framework of slopes combined with the data from shaking table model tests is proposed. • The optimal EDP and earthquake IM for scalar- and vector-valued fragility analysis of slopes are identified. • The fragility surfaces of a slope considering acceleration elevation amplification effect are constructed. [ABSTRACT FROM AUTHOR]