It is acknowledged that various sources of uncertainties play a vital role in the seismic vulnerability of slope systems, while many studies ignore these sources in seismic assessments. This is because seismic performance and fragility evaluation of large soil-structure systems is challenging and computationally intensive by conventional nonlinear dynamic analysis methods, especially when the modeling uncertainties are considered. To address this challenge, this paper proposes a new framework for addressing uncertainties in the seismic evaluation of earth slopes using the Endurance Time Analysis (ETA) method. The ETA method is a dynamic pushover procedure in which the slope is subjected to a limited number of artificial intensifying records, and seismic responses are obtained over a continuous range of seismic intensities. For the purpose of this study, probabilistic two-dimensional numerical simulations of earth slopes are created using the FLAC software by considering the soil parameters uncertainty. Latine Hypercube Sampling is employed to generate random simulations. The models are then subjected to the intensifying prefabricated excitations based on the ETA method, and the fragility curves of the slope are obtained in three damage states by considering and not considering uncertainties. The results indicate that as the endurance time, which is a kind of intensity measure, increases, the uncertainties of seismic responses also increase. This shows that the effects of uncertainties become more significant when the slope is subjected to strong ground motions. Additionally, the influence of modeling uncertainty is negligible in the slight damage state, but significant in the extensive damage state. The proposed framework provides an effective and rapid way for performing the fragility and associated risk analysis of earth slopes considering uncertainties.

This paper compares the probabilistic analysis results of earth slopes using Random Variable (RV) and Random Field (RF) approaches, with a focus on potential differences in the mobilized sliding mass. The Finite Element Method (FEM) with Shear Strength Reduction (SSR) is utilized to determine Pore Water Pressure (PWP) and the Factor of Safety (FoS). In the RF approach, random FEM is conducted using crude Monte Carlo Simulation (MCS) and the Karhunen-Lo & egrave;ve expansion, while the RV approach employs the First-Order Reliability method (FORM) and Importance Sampling Monte Carlo Simulation (IMCS). Sensitivity analysis was performed to reveal the most important parameters. The RV results may either underestimate or overestimate the probability of failure (Pf) compared to those obtained by the RF approach. Smaller Pf values are observed in RF with smaller correlation lengths (L) of soil properties. The mean value of the factor of safety (mu FoS) closely matches the deterministic FoS when L is largest, while the coefficient of variation of FoS (COVFoS) increases. Finally, in the RF analysis, it was found that intermediate sliding volumes carry higher risks, with smaller volumes having higher occurrence probabilities and larger volumes having much lower probabilities.