Statistical models for slope instability classification

Abstract

Statistical models for reliable hazard assessment of landslides in a given area are presented. The models are based on information theory and regression analysis. Information theory is a branch of probability in which the most significant feature is unpredictability and regression analysis is based on simple statistical theory. Both methods of statistical prediction have been applied to slope instability to provide cross validation of the results. A FORTRAN 77 program for computer-aided assessment of the landslide hazard has been developed. The program considers the factors affecting the slope instability and history of past landslides of the area as its input. The program also calculates the information and regression value in a given area and classifies the area into different grades of instability. A case study of landslide hazard assessment of a 66 km 2 area in parts of the Alkananda valley, the Gharwal Himalaya is presented. The factors considered in the analysis are angle and height of the slope, rock type and geological structures such as faults and thrusts. The results obtained are illustrated in the form of landslide hazard maps. The predicted results are compared by the above methods.