The probabilistic methods are receiving increasing recognition in assessing the hazards due to landslides, owing to the ability of these methods to consider the estimation uncertainties and geographical heterogeneity of geomorphological, geotechnical, geological, and seismological components. Therefore, the present study developed a probabilistic method to model the parametric uncertainties of modified Newmark's method using the Monte Carlo simulation technique. The proposed methodology was applied to evaluate the hazard potential for co-seismic landslides in the Uttarakhand state, located in the Indian Himalayan region. The modified Newmark model considered in the study incorporates the rock joint shear strength properties instead of soil shear strength parameters in the permanent displacement computation of slopes. The simulations were done pixel-by-pixel by seamlessly integrating into the current GIS computational settings. When analyzing these data, statistical distributions were used to account for uncertainties and variations in the input parameters. Monte Carlo simulations were employed to generate various probability density functions for each individual pixel within the study area. These simulated distributions were then maintained consistently across the entire computational workflow, ensuring that the generated samples were preserved throughout the analysis. With no limitations on the symmetry or complexity of the underlying distributions, the resultant numbers were then turned into probabilistic hazard maps. In the final step, a hazard map was produced, where each pixel indicates the probability that slope displacement will surpass the 5 cm threshold. Values of probability are distributed between 0.1 and 1, with elevated values primarily observed in the upper Himalayan region, emphasizing the greater likelihood of co-seismic landslides in this zone. This seismic landslide hazard map serves as a valuable tool for local planners and authorities, enabling them to assess regions vulnerable to seismic landslide hazards and implement measures to mitigate potential losses.

The seismic landslide-pipe problem was investigated numerically using finite-difference code and a bounding surface soil constitutive model [Simple ANIsotropic SAND constitutive model (SANISAND)]. The SANISAND model was calibrated using triaxial monotonic and cyclic tests at the element level and shaking-table test results at the boundary value level. The results show that the calibrated parameters of the SANISAND model can predict monotonic and cyclic triaxial test results and slope displacement response properly. After the verification process, the dynamic response of a slope with the presence of buried pipes under sinusoidal input acceleration was evaluated in terms of slope displacement and the pipe axial strain. The results show that the presence of buried pipes in the slope can reduce slope surface displacement by 50%, especially for shallower burial depths of pipe (i.e., 1-1.5 m). The results of the axial strain of the pipe for changes in the burial depth and location indicate that for pipes buried in the downslope and upslope sections, deeper and shallower burial depths, respectively, lead to less axial strain being imposed on the pipe under landslide actions. The variations of slope geometric parameters (slope width and inclination angle) on slope displacement response and pipe strain patterns show that with increasing slope width and inclination angle, the displacement of sliding mass increases, and the depth of the slope failure wedge decreases. Moreover, the maximum strain of the pipe increases by 150% as the width-to-height ratio (W/H) of the slope increases from 1 to 4. With the increase in soil density, the pipe axial strain increases. The results of dynamic analysis under earthquake records showed that the axial strain of the pipe has a high correlation with the cumulative absolute velocity of seismic input.

The Loess Plateau is marked by intense neotectonic activity and frequent earthquakes. Its unique physico-mechanical properties, combined with the granular overhead pore structure of loess, render it prone to seismic landslides triggered by strong earthquakes. Different types of loess seismic landslides have distinct formation mechanisms, disaster-causing characteristics, and risk assessment programs. In this study, the risk of seismic-collapsed loess landslides as one of the types of loess seismic landslides was evaluated on the Loess Plateau. A risk zoning map for seismic-collapsed loess landslides on the Loess Plateau, considering various exceedance probabilities, was compiled by assessing eight factors. These factors include peak ground acceleration, microstructure of loess, and were evaluated using both the minimum disaster-causing seismic peak ground acceleration zoning method and the analytic hierarchy process. The following conclusions were obtained: (1) Earthquakes are the primary inducing factor for seismic-collapsed loess landslides, with other factors serving as influencers, among which the microstructure of loess carries the highest weight; (2) Across various exceedance probabilities, the likelihood of seismic-collapsed loess landslides occurring at 63% of the 50-year exceedance probability is low. Moreover, as the minimum hazard-causing seismic peak ground acceleration increases, the risk of occurrence of seismic-collapsed loess landslides rises, leading to a gradual expansion of the area share in moderate and high-risk zones; (3) Hazard evaluation results align well with existing data on seismic-collapsed loess landslides and findings from field investigations. The case of seismic-collapsed loess landslides induced by the M6.2 magnitude earthquake in Jishishan County, China, is presented as an illustration. The combined use of the minimum hazard-causing seismic peak ground acceleration zoning method and the analytic hierarchy process method offers a reference for geohazard hazard assessment, with earthquakes as the primary inducing factor and other factors as influencers.

In seismic regions both in Iran and around the world, subterranean gas pipelines inevitably extend through highrisk areas prone to seismic landslides. The seismic landslide-pipe failure mechanism constitutes a continuum geomechanical challenge influenced by factors such as sliding mass configuration, pipe positioning relative to potential slope failure surfaces, and seismic input characteristics. In this study, response of steel pipeline buried in sand under seismic landslide action is analyzed by finite difference models using an advanced soil constitutive model. The numerical model is first validated based on the shaking table test results and then several dynamic analyses are performed using the selected records of the Iranian ground motions database. The outcomes of the dynamic analysis demonstrate that Arias Intensity (Ia) can be identified as an optimal intensity measure (IM) for predicting the seismic response of a slope-pipe system in terms of maximum pipe deflection, axial strain, and shear stress. Predictive models are then developed based on the optimal IM for estimating the pipe deflection, axial strain, and shear stress subjected to a seismic landslide. These proposed predictive models offer valuable insights for assessing the response of buried pipelines to seismic landslides in Iran within the framework of performance-based earthquake engineering.