EAGER: Understanding Water Circulation in Semi-Enclosed Coastal Basins

Since much of the coastal population and economic activity is concentrated around bays and inlets, it is important to understand their circulation. Semi-enclosed basins are particularly interesting because their exchange with the open ocean involves the interplay of local wind forcing and conditions over the continental shelf, which may be influenced by larger scale winds elsewhere. This project will explore a dynamical framework to combine such effects and generalize findings to semi-enclosed basins globally. Expected findings will help efforts to predict impacts on coastal environments from extreme weather events, coastal flooding, erosion and water quality threats. This project will address circulation in semi-enclosed basins, investigating the various drivers including tides, density gradients, winds, and remote oceanic influences. While the role of tidal and baroclinic forcing has been extensively studied, the combined effects of local wind stress and remotely driven shelf forcing remain poorly understood. The project will integrate observational and theoretical approaches to advance understanding of wind-driven, including remote forcing from the shelf, and subtidal dynamics in semi-enclosed basins. Field observations, analytical modeling, and machine learning techniques will be combined to examine wind-driven and remotely driven, exchange flows in semi-enclosed basins. A new tetrahedral dynamical framework will facilitate the inter-comparison of semi-enclosed basins. 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. NSF Award ID: 2549261 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Arnoldo Valle-Levinson | Institution: University of Florida, GAINESVILLE, FL | Award Amount: $57,096 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2549261 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2549261.html