Empirical verification of stochastic theory for landslide hazard forecasting (Seattle Case Study)

Abstract

This report is aimed at demonstrating that the model based on the random process theory, i.e. the renewal process model, is suitable for predicting the time of landslide activation and obtaining its dynamic parameters. The model deals with a geologically-uniform area, wherelandslide activation results from local factors, such as storm rainfall, depergelation (meltingpermafrost), and others. The proposed approach minimizes the duration of the monitoringseries necessary for landslide forecasting. We use Seattle landslide database for modelverification. We use shallow landslide occurrence data. Two main problems of modelverification were determined: 1. huge rainfalls (single storm events) that triggered a significant number of landslides; 2. human caused mitigation of landslides as well as road and publicutility impact. The distributions of time between two activation time and time between lastdate in database and last activation time have exponential and lognormal character respectivelyat significant level of 0.95. .