Earthquake- and rainfall-induced landslides are common geologic hazard in many regions of the world. Traditional analyses performed using limit equilibrium or strength reduction methods can evaluate the triggering of landslides but are not able to model the associated deformations. Finite element or finite difference analyses can model deformation patterns in landslides, but numerical errors can arise as large deformations occur on discrete failure planes. This inability to model realistic deformations limits the ability of engineers and geologists to understand how factors like elevated groundwater conditions or retrogressive sliding affects the amount of mobilized material or potential impacts on infrastructure. Particle-based numerical methods like the material point method offer a promising alternative to model both triggering and mobilization of landslides, but there are still limited applications of MPM to landslide case histories. This study will present results from MPM simulations of two landslide case histories where elevated groundwater conditions were observed at the time of the failures. The first case history is a large rainfall-induced landslide that occurred along a major highway in Lacey’s Spring, Alabama in 2020. The second case history is a liquefaction-induced flow slide that occurred during the 2018 Palu earthquake in Indonesia. Both case histories have been well-documented through post-failure surveys, geotechnical explorations, and slope stability analyses. In both cases elevated groundwater conditions were believed to be a driver behind the size of the landslides, but previous analyses were not able to model the large deformations that occurred at these sites. This study expands on these previous analyses by developing MPM simulations for both case histories. The simulation results are compared with both the field observations and previous analyses and the effects of groundwater conditions on the size of the mobilized area are explored. The results of this study serve as both validation of the MPM simulation framework and provide a better understanding of how groundwater conditions impacted these case histories.