Project Details - All Projects > Agency - National Oceanic and Atmospheric Administration
The CoastSmart Communities Initiative (CCI), a program within the Maryland Department of Natural Resource’s Chesapeake and Coastal Service and staffed by IAN, is helping local communities identify and implement strategies to protect life, property, and natural resources vulnerable to coastal hazards such as storm surge, shoreline erosion, coastal flooding, and climate change. From hands-on training, planning tools, and online resources to a competitive grants program, CCI works to provide municipal and county governments with the tools that they need to identify vulnerabilities and take the necessary actions to become ready, adaptive, and resilient.
Native to the Gulf of Mexico, Karenia brevis is a toxic dinoflagellate that blooms almost annually off the west coast of Florida. K. brevis blooms are not a new phenomenon on the west Florida shelf, and ships' logs suggest bloom-related events (fish kills) dating back to the 1500s. Coastal regions of Florida have experienced some of the most rapid population growth and development in the United States. Beach clean-ups, tourism-related losses, medical expenses, and lost work days during red tide events can average over a million dollars lost annually. This is a five year, multi-insitutional research program designed to utilize scientific expertise in a collaborative laboratory, field, and modeling program. The study aimed to identify the diverse interannual physical, chemical, and biological conditions that are responsible for K. brevis blooms on the west Florida shelf.
Empirical models were developed at South Carolina beaches and estuaries to create daily forecasts of bacterial water quality for use as decision support tools. These tools predict exceedance of bacteria criteria using integrated monitoring data, remote sensing, and meteorology information. The models developed for beach areas used precipitation data from a rain gauge network, tide data, and qualitative weather information to predict criterion exceedance. Current efforts on these tools include integrating data from ocean observing systems and precipitation data from remote sensing products to create near-real time prediction updates presented in a web-based GIS. Similar predictive models for fecal coliform bacteria concentration were developed using integrated data from monitoring programs, meteorology, and remote sensing. These two related modeling efforts highlight the utility and feasibility of integrating data from observing systems and remote sensing to create empirically-based decision support tools.
Coastal management in the U.S. is in transition toward a stronger, ecosystem-based approach implemented at the regional scale and supported by strong scientific synthesis and prediction. The division of ecosystem components
among different agencies, scientific disciplines, and political boundaries, as well as the complexities of conducting Regional Ecosystem Research (RER) make effective
ecosystem management very challenging. NOAA's Center for Sponsored Coastal Ocean Science convened a best practices workshop of approximately 50 national
leaders in coastal research, management, and policy to identify the key elements of an effective RER program and policy actions to enhance future RER efforts. The results from this workshop and follow up interviews is summarized in this report.
To assess the eutrophic conditions for 141 U.S. estuaries based on data and information provided by scientists and experts from around the country. IAN developed an interactive website to collect data and produce automated summaries of eutrophication status as well as print ready graphics for the final report. Report production was a collaborative effort between Suzanne Bricker (NOAA NCCOS), EcoCheck (NOAA-UMCES Partnership) and IAN.
In partnership with the Southeast Coast Ocean Observing Regional Association (SECOORA) and the University of South Carolina, IAN automated and improved the accuracy of beach advisory decision making for Myrtle Beach South Carolina. The improvements resulted from integrating information from Ocean Observing Systems and radar-based rainfall data from the National Weather Service to improve bacteria concentration predictions. Results are presented in an easy to use, visual format for beach managers.