Monitoring the stability of tailings storage facilities (TSFs) is extremely important due to the catastrophic consequences of instability, which pose a threat to both the environment and human life. For this reason, numerous laboratory and field tests are carried out around dams.

An extensive database is collected as part of monitoring and field research. The in-depth analysis of available data can help monitor stability and predict disaster hazards. One of the important factors is displacement, including surface displacements—recorded by benchmarks as well as underground displacements—recorded by inclinometers.

In this work, methods were developed to help assess the stability of the TSF in terms of surface and underground displacement based on the simulated data from geodetic benchmarks. The context of spatial correlation was investigated using hot spot analysis, which shows areas of greater risk, indicating the places of correlation of large and small displacements. The analysis of displacements versus time allowed us to indicate the growing exponential trend, thanks to which it is possible to forecast the trend of future displacements, as well as their velocity and acceleration, with the coefficient of determination of the trend matching reaching even 0.97. Additionally, the use of a geographically weighted regression model was proposed to predict the risk of shear relative to surface displacements.