Snowmelt Modelling for Improving the Forecasts of Rainfall Threshold-Based Landslide Triggering

摘要

In Central Italy a significant number of landslides occurrence have been triggered by rapid snow melt: recent seasonal events in the Northern Apennines, the study area, demonstrate that it is necessary to consider this phenomenon and to integrate snow precipitation within existing statistical models for landslide prediction. The proposed snow melt modeling (SMM) is divided in two modules depending on whether or not a threshold temperature is exceeded: the first one for the accumulation of solid rainfall in the snowpack and the latter for the snow melting. For the modeling identification we employ empirical data of depth of snow cover using an optimization algorithm to deduce the optimal values of the model parameters. This work is developed to increase the predictive capacity of the statistical models for landslide prediction based on rainfall thresholds. In the study area an improvement was achieved: several landslides, caused by snow melting, were correctly detected.