RAISE: Co-developing modeling frameworks to mitigate the effects of compounding flood hazards in coastal communities

This project will develop tools and solution alternatives for coastal communities impacted by compounding flood hazards from multiple simultaneous sources (e.g., abundant rainfall, high tides, storm surges). Historically, scientists and engineers have focused on flood mitigation solutions for individual flood causes rather than combined scenarios from multiple simultaneous flood sources. This team will partner with local organizations to use advanced computer models and affordable flood sensors to improve flood modeling for coastal communities. This project will produce guidelines for incorporating local perspectives into designing flood-mitigating infrastructure, identifying flood zones, and developing evacuation maps and better early warning systems for vulnerable residents for a test case in San Juan, Puerto Rico. The project will assess hydrologic and coastal flood drivers individually and combined from events in coastal communities. The research team will develop efficient, inclusive methodologies capable of holistically integrating flood assessment techniques. This approach will accurately assess coastal floods utilizing local knowledge to develop better, more resilient flood mitigation solutions for compound flood events. Physics-based numerical modeling techniques will be used to develop a single modeling framework capable of assessing compound floods to better understand compound flood dynamics. Multiple techniques, such as flood sensor courses, participatory mapping exercises, and semi-structured interviews, will engage the community and allow the integration of local knowledge into flood modeling frameworks and aid in the design process of flood-mitigating infrastructure. The project will provide several direct, immediate solutions to the community, such as resilient infrastructure plans, a pilot impact-based forecast, and a web dashboard for flood sensor monitoring. Long-term goals include stationary flood risk maps and an improvement in the local rainfall forecasts. 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.