The strength parameters of geotechnical bodies in strata formed under natural conditions often exhibit spatial variability. Predicting the run-out distance of potential large-scale landslides using limited strength data is challenging as it may not comprehensively reflect the range of changes in sliding distance. Therefore

it is necessary to conduct stochastic analyses of landslide sliding distance by combining statistical characteristics and distribution laws of strength parameters

providing a reference for the prevention and control of landslide disasters. This study presents a smooth particle hydrodynamics (SPH) method for modeling the large-deformation sliding process of landslides

based on the Bingham model

equivalent viscosity

and Mohr-Coulomb failure criterion. The mid-point method is used to generate random field samples of the internal friction angle. Monte Carlo simulations were conducted for stochastic analysis of the sliding distance

thereby obtaining the distribution characteristics of the run-out distance for large-scale landslides. The Yangbaodi landslide was chosen as a study case to verify the feasibility of the SPH method. The accuracy of the discretization of the internal friction angle random field was verified by establishing and analyzing geological models with different random field parameters

and the simulation parameters were calibrated. On this basis

the range and distribution pattern of landslide sliding distance under different conditions were analyzed by varying the coefficient of variation of the internal friction angle

as well as the vertical and horizontal scales of fluctuation. The results show that an increase in the coefficient of variation leads to an increase in the range of the landslide distance

with the sliding distance showing stronger discreteness; an increase in the vertical fluctuation range increases the size of the intensity parameter distribution clusters

which in turn increases the range of the landslide distance; both the horizontal and vertical fluctuation ranges

as well as the coefficient of variation

show a positive correlation with the standard deviation of the sliding distance

with the horizontal fluctuation range having the least impact.