ABSTRACT
Tornadoes occur at a high frequency in the United States compared with other natural hazards but have a substantially smaller footprint. Even a single high-intensity tornado can result in high casualty rates and associated catastrophic economic losses as well as social consequences, particularly for small to medium communities. The city of Joplin, Missouri, USA, was hit by an EF-5 tornado on May 22, 2011. The Center for Risk-Based Community Resilience Planning simulated this event for buildings and the electrical power network of Joplin in an open source computational environment called IN-CORE. The initial damage prediction utilized the tornado path, tornado fragility curves representative of a 19-archetype building dataset, and EPN datasets. The functionality of the infrastructure was linked with a computable general equilibrium (CGE) economics model that computes household income, employment, and domestic supply before and after the tornado event occurrence. Detailed demographic data was allocated to each structure to provide resilience metrics related to population impacts such as population dislocation as a function of tenure status of households. This example demonstrates how users interact with the IN-CORE computational environment.
