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.

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The Harte Research Institute for Gulf of Mexico Studies of Texas A&M University-Corpus Christi, along with its partners Harwell Gentile & Associates, LC, and the University of Maryland Center for Environmental Science, proposes to develop a comprehensive framework for a Report Card on the health of the Gulf of Mexico.

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EcoCheck has partnered with the Waterfront Partnership of Baltimore to assess the baseline conditions of Baltimore's Inner Harbor and its watershed. EcoCheck will evaluate the current status of the Inner Harbor by evaluating water quality, sediments, biota, and other indicators. This baseline conditions assessment will be a starting point for an annual monitoring program that will support an annual report card for the Harbor.

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Deep Creek Lake is currently experiencing a host of environmental problems related to nutrient and sediment input from the surrounding watershed. The nonprofit organization Friends of Deep Creek Lake (FODCL) is collaborating with EcoCheck to design and produce an environmental report card for Deep Creek Lake. This project is especially important to the evolution of environmental assessment, communication, and reporting for aquatic systems in Maryland.

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The Marine Monitoring Program is a long-term water quality and ecosystem heath monitoring program carried out in the inshore region of the Great Barrier Reef Lagoon. The program is an integral component of the Reef Water Quality Protection Plan, that will help to assess the long-term effectiveness of Reef Plan in reversing decline in the quality of water entering the Great Barrier Reef Marine Park.

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The Mid-Atlantic Tributary Assessment Coalition is a unique and growing group of watershed organizations interested in advancing the use of environmental data from local organizations and citizen scientists for use in report cards and assessments. Using data collected by concerned citizens, IAN has helped to generate multi-year report cards for nine rivers since 2007.

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The University of Maryland Center for Environmental Science (UMCES) in collaboration with the University of Michigan and funded by NOAA will produce a summer dissolved oxygen forecast for Chesapeake Bay. An annual anoxia forecast will be produced for two periods (early and late summer) and a hypoxia forecast will be produced for the month of July. The results of this forecast will be published on an interactive website and included in a press release.

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The first objective of the project is to produce a Nanticoke watershed/river report card in the format that is fast becoming the standard for reporting water quality information to the public. This report card will be used to inform and involve the public as part of the Nanticoke Watershed Alliance's programmatic and mission effort to conserve the resources of this river.

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This project seeks to establish a framework to coordinate efforts among watershed organizations using or planning to use report cards as outreach tools. This project also seeks to develop clear and consistent guidelines and protocols for the development and implementation of report cards by watershed organizations. Protocols will be developed and training provided for sampling and monitoring methodology, data analysis, and science communication.

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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.

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