Validation of a Simulation Chain to Assess Climate Change Impact on Precipitation Induced Landslides

Since prehistoric times, the clayey slopes of Orvieto (Central Italy) have been affected by slow movements directly related to soil-atmosphere interaction. Understanding how climate changes could affect future evolutions of such movements is a challenging issue; to this aim, a simulation chain is set up: General Circulation model (GCM) outputs are dynamically downscaled through regional climate models (RCMs); rainfall values are then subjected to techniques to correct biases; so obtained rainfall time series can be adopted as input for tools evaluating slope stability conditions. Three bias correction techniques (BCT) have been applied: linear-scaling, quantile mapping and Analogs method. This work analyses their strength and limitations as well as their capability for outperforming the uncalibrated RCM outputs under current climate conditions (1981-2010) for the Orvieto case study. These results suggest that the BCT may be very useful tools for climate change impact studies where users require high resolution data and systematic errors to be minimized.