Collaborative Research: Understanding cascading feedbacks between human decision making and delta morphodynamics with community-engaged modeling

About This Grant

Rivers and deltas of the world have been extensively engineered for centuries. Past engineering projects have, collectively, enabled the prosperous economies of deltaic regions that are enjoyed today, but have also created conditions that limit the regions in the future. In many places, including along the United States Gulf Coast, planners and governments are implementing new projects that aim to restore coastal changes, enhance economic and environmental support, and mitigate risk to human lives and livelihoods. However, there is not a robust understanding of how past delta management has influenced human decisions and outcomes. This project uses novel numerical and computational modeling approaches to study how human engineering decisions cascade through space and time over centuries of landscape change to create system conditions that limit or enhance the portfolio of management decisions available at future times. This work develops tools with coastal planners to determine the portfolio of projects that maximize coastal survival. Delta engineering projects induce geomorphic change across space and time scales that impacts human lives and society. This project integrates cascading human decision making into landscape evolution models with three modeling approaches that inform one another and have complementary strengths: agent-based modeling, dynamical system modeling, and participatory modeling. Project research focuses on two testable hypotheses towards the tools and quantitative understanding of cascading decision making that are needed for delta planning: (1) local-scale engineering interventions can lead to less geomorphologically stable delta landscapes, when compared to a few larger system-scale interventions, and (2) human decisions can push the coupled system across tipping points, to both system benefit and detriment. Finally, research and development across all modeling approaches in this project is guided by community engagement. 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.