An integrated approach to evaluating inland waterway disruptions using economic interdependence, agent-based, and Bayesian models

Abstract The U.S. inland waterways play a vital role in the domestic economy, but extreme weather events, especially floods, perennially threaten to disrupt their operations. Here, we develop a data-driven approach to analyzing economic risks due to flood closures along the inland waterways that combines agent-based, economic interdependence, and Bayesian modeling. We demonstrate our framework by evaluating economic impacts of various flood disruptions along the Upper Mississippi River and determining cases where a publicly operated, flood-resilient port located near the mouth of the river can reroute shipments and mitigate production losses for the region. We find that Illinois, Louisiana, Minnesota, and Missouri are the states that suffer the most production losses from flood disruptions and that agriculture and chemical manufacturing are the most impacted industries. However, during floods whose return periods exceed 30-years, the flood resilient port becomes cost-effective in mitigating losses for the region. Our methodology can be easily extended to other hazards and sections of the inland waterways.