Abstract
Due to the climate change, extreme weather phenomena are becoming increasingly intense and occur with higher frequencies, even in unusual areas. Nevertheless, historical data showed as Natech accidents can be triggered not only by natural disasters, like earthquakes or tornadoes, but even by natural phenomena that are considered of minor importance, such as rain and lightning. Only recently, the Natech issue has gained a great deal of attention, but there is still a lack of consolidated Natech risk-analysis methodologies and tools. The focus of this work is to include natural hazards into a dynamic risk assessment system beside the typical parameters of process risks. In Italy, rainfall represents the most common triggering factor for landslides. Generally, the determination of trigger and propagation can rely on physically-based approaches, which require the calibration of many parameters and are often difficult to apply, or on empirical correlations between rainfall and landslide built from historical data. On the other hand, by using a data driven approach, available data can be exploited to define the system state over time, anticipate the systems outcome, support decision-making, and adopt the most appropriate adjustments, allowing to enhance system resilience and knowledge. The actual capability of the proposed approach was evaluated on a simple case-study represented by an LPG storage facility located in landslides sensitive zone of Liguria Region.
