RAPID: Infrastructure, Communication, and Decision-Making During Rapid-Onset Flooding

About This Grant

When disasters strike suddenly, people must make life-or-death decisions within minutes based on limited and rapidly changing information. Catastrophic flash flooding events have revealed critical gaps in how communities, emergency managers, and visitors respond to fast-developing hazards. This interdisciplinary research addresses a fundamental challenge in understanding why some individuals and organizations successfully evacuate while others in similar circumstances, with similar information, do not. This project serves the national interest by advancing scientific knowledge that can save lives and reduce disaster impacts across the United States. The research generates evidence-based frameworks for improving emergency communication systems and decision-making processes during rapidly evolving crises. The findings benefit a range of communities facing various hazards, from coastal areas threatened by hurricanes to mountain regions at risk of wildfires and urban centers vulnerable to technological disasters. By developing tools and recommendations that account for the varying knowledge levels and constraints of different populations, this work supports the NSF's mission to advance national health and welfare through scientific progress that strengthens disaster resilience nationwide. This research project will develop a Dynamic Sensemaking Framework to understand decision-making processes during rapid-onset disasters. The project employs four integrated research approaches. First, researchers capture ephemeral data through semi-structured interviews using photo elicitation methods across four stakeholder groups: successful evacuees, emergency managers, individuals who did not evacuate despite danger, and people with limited local knowledge. Second, the team develops innovative cognitive mapping techniques to capture how mental representations of risk and response options evolve spatially and temporally during disasters. Third, the project leverages artificial intelligence-enhanced analysis to identify patterns in communication effectiveness, infrastructure failure cascades, and decision making under uncertainty. Fourth, researchers create geographic and temporal maps identifying locations where constraints limit evacuation decision windows. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.