A LANDSLIDE PREDICTION MODEL BASED ON LOAD-UNLOAD RESPONSE RATIO THEORY AND ITS APPLICATION

Abstract

Landslide is one of the most common geological disasters that seriously threatens human production and life. Hence it is of great significance to accurately predict landslide disasters. However, the process of landslide is accompanied by a series of extremely complex mechanical reactions, which are determined by various factors, such as the strength of rock and soil, the attitude and structure of stratum, the external disturbances and so on, and these factors are difficult to accurately capture. To predict the landslide accurately, a comprehensive landslide forecast model was proposed based on the load-unload response ratio (LURR) theory. In this model, sliding force inside the slope and displacement of the slope surface as the key parameters were measured. The sliding force, as the load-unload parameter, was obtained by a sliding perturbation remote monitoring (SPRM) system. While the displacement, as the load-unload response parameter, was measured by total station. Besides, the velocity and acceleration of displacement were also used as parameters to improve the accuracy of landslide hazard prediction. The LURR landslide prediction model was applied in Antaibao and Pingzhuang west open-pit slopes. Results show that the proposed model is accurate and reliable for landslide prediction. The force-displacement coupling model is more efficient in landslide prediction and early-warning, which is helpful to track the causes of landslide. Keywords: Landslide prediction, Load-unload response ratio, Sliding force, Remote monitoring