Assessment of soil saturation from climatic data in the framework of the Shallow Landslide Instability Prediction (SLIP) model

A direct correlation between the degree of saturation of the soil and climate data easily available is very useful for many practical applications, also to predict the occurrence of rainfall-induced shallow landslides. The paper presents a simplified method to assess the mean degree of saturation of shallow soil layers by using daily air temperature and rainfall depth as driving variables. The method is derived in the framework of the model SLIP (Shallow Landslide Instability Prediction). The good performance of the method is shown by comparing the computed time series of the degree of saturation of the soil with field measurements from two test sites, affected by rainfall-induced shallow landslides in the past and subjected to different annual climatic conditions.