Various types of natural disasters, such as geophysical (earthquake, landslide, avalanche), hydrological (flash‐floods, debris flow, floods), climatological (extreme temperature, drought, wildfire) and meteorological (tropical storm, heavy rainfall), have caused losses of many lives and huge economic damages in the last years. According to the United Nations, for the period 1998‐2017, disasters associated with natural hazards killed 1.3 million people and affected 4.4 billion people, along with economic losses of $2.9 trillion.

Therefore, a key element of the Industry 4.0 roadmap is Digital Twin (DT), as a digitization technology that allows the physical and virtual space to communicate. This is a big chance for Integrated Risk Management 4.0 (IRM 4.0) approach based on a DT that integrates Artificial Intelligence (AI), Machine Learning (ML) and Data Analytics to create dynamic digital models able to learn and update the status of the physical environment with multiple information sources.

In this context, a Regional Digital Twin (RDT) can be considered, simply speaking, a virtual model of the environment, including buildings, roads, woods, rivers, etc., all readily available as data components in a digital model, integrating Building Information Model (BIM) and Geographic Information System (GIS). This big data base, updated in real-time, con be used to perform simulations and make predictions regarding the evolution of extreme events in order to warn authority and people.