H51J-0739:
Data Management Solutions for Tracking Restoration Progress in the Chesapeake Bay Watershed

Friday, 19 December 2014
Sucharith reddy Ravi, University of Maryland Center (UMCES) for Environmental Science, Frostburg, MD, United States, Matt Johnston, University of Maryland College Park, Department of Environmental Science and Technology, College Park, MD, United States and Jeff Sweeney, Environmental Protection Agency Chesapeake Bay Program, Annapolis, MD, United States
Abstract:
The decline of the Chesapeake Bay estuarine ecosystem due to agricultural and industrial activities has been a great concern, where excess of dissolved nutrients combined with global climate change has lead to increased storm surges, habitat destruction, and low dissolved oxygen, reduced water clarity, and increased algal growth. In 2010 The US Environmental Protection Agency established the Chesapeake Bay Total Maximum Daily Load (TMDL), which seeks to protect the Bay’s living resources by reducing nutrient and sediment runoff to its waters, and sets pollution reduction targets for sediment, nitrogen and phosphorus across 64000 sq. miles watershed that includes parts of six states - Delaware, Maryland, New York, Pennsylvania, Virginia, and West Virginia — and the entire District of Columbia. The Chesapeake Bay Program and the US EPA have developed a number of tools to track the progress of restoration. In this study we describe data management solutions, which were used in the integration of data such as land use, nutrient applications, management practices, policies among the bay jurisdictions, and a summary of a suite of tools that were developed and are being used to collect, process, and report data at various spatial scales for tracking the progress made by the seven Bay jurisdictions in achieving reductions in nutrient and sediment runoff. The described integration strategy and data management solutions can be used in the development and application of similar regulatory local or regional scale environmental management tools.