SCC-IRG Track 1 Designing Smart, Sustainable Risk Reduction in Hazard-Prone Communities: Modeling Risk Across Scales of Time and Space

The exponential increase in extreme events over the last decade compels new methods of managing risk in communities exposed to recurring natural hazards. This project advances the National Science Foundation's goal Growing Convergence Research to enable smart and connected communities by initiating and expanding collective learning capacity through integrating digital twin technologies and social games. This project proposes to engage decision makers across sectors and scales of jurisdiction in managing risk by reallocating attention, time, resources and overcoming barriers to act collectively as hazardscapes change. This project will use the threat of wildfire across two communities in northern California as community engagement study sites. Working with thirteen community partners, the project will develop an innovative sociotechnical digital twin of the San Francisco Bay Area that integrates virtual models of physical infrastructure systems, social/commercial networks, and insurance mechanisms that distribute risk over space and time. Serious games will be designed to activate learning processes inherent in play to engage community's awareness and commitment to collective action.

This project will use a complex systems approach to hazard reduction across multiple scales of risk by developing a new generation of socio-technical digital twin that integrates models of physical infrastructure systems and virtual networks of communication with social games to engage community stakeholders' awareness and commitment to collective action. Using a conceptual framework of complex adaptive systems, this project will investigate whether community learning processes that focus on cognition and action will mitigate wildfire risk in the short-term and lead to sustainable adaptation to recurring risk conditions in the long-term. This inquiry advances risk management theory by testing a prototype sociotechnical framework for developing shared knowledge to support decision making by multiple actors at different scales to reduce hazard risk. The sociotechnical digital twin provides a macro view of risk at the regional scale, as well as detailed views of interactions at the micro scale, essential to manage operations. Translating risk information into formats that are easily understood by different groups and embedding learning processes in gaming scenarios to advance risk reduction is transformative. A major goal is to shift the perspective from reaction to extreme events after they occur to anticipation of risk and mitigation of potential losses before hazards occur. Using serious games, a process of iterative learning for diverse community actors increases the level of shared cognition of risk and commitment to action. The project will engage under-represented minorities in affected regions and support decision-makers in vulnerable communities.