Speaker
Descrizione
The present research activity aligns with one of the main objectives of the ATLaS research infrastructure: the development of forecasting models and quantitative risk assessment methods for geo-hydrological hazards. The work focused on the development and maintenance of a forecasting system for shallow rainfall-induced landslides that works continuously providing daily outputs in near real-time at a regional scale. The research activities dealt with i) the optimisation of a selected slope stability model considering purposes and framework of the project; ii) the calibration of the system based on the hydrological, geotechnical, morphological and climatic characteristics of the study area; iii) the development of routines and algorithms aimed to enabling the system to operate continuously using weather forecasts and producing spatially aggregated (sub-basins) outputs along with the distributed outputs.
The final forecasting system is based on a distributed slope stability model (HIRESSS), it has been operational since June 2024, and it is currently deployed over Alert Zone B of the Aosta Valley Region, using precipitation forecasts from the ICON-CH2 weather prediction model as dynamic input. The system provides landslide initiation susceptibility maps (in terms of failure probability) at 10-meter spatial resolution and 3-hour temporal resolution, generating forecasts for both the current and the following day, available daily by 09:30 AM. In addition to this, the system simultaneously provides failure probabilities for each sub-basin of the area based on a calibrated system of thresholds, generating outputs ready for operational use in an early warning system. Last activities aimed to optimize the real-time dissemination of model outputs through an open data platform designed by ATLaS within the Itineris project.
