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National Estuarine Eutrophication Assessment: Type Classification of US estuaries

Abstract

The purpose of this work is to develop a type classification of estuaries and coastal waters of the United States that describes susceptibility to development of eutrophication using physical and hydrologic characteristics. The intent is to capturing inter-system differences in a context that is useful for more accurate, quantitative and management-oriented assessment of both perturbations and system responses to nutrient over-enrichment (human-induced eutrophication). The type classification will allow modification of the NEEA method to include type specific-criteria thereby increasing the accuracy of assessments. The project will develop and implement basic tools and databases for estuary classification and provide a vehicle (i.e. website) for access to the tools and database in order to engage community involvement in the analysis. Already there is a promising type classification for the estuaries that were included in the National Estuarine Eutrophication Assessment (NEEA). The project will use remote sensing data to test these groupings to see if they make sense. Additionally, the ranges of values for the water body characteristics will be identified so that estuaries can be identified by type even if they were not included in the original clustering operation. And the tools for clustering operations (ie the DISCO tool) and data bases will be made available online.

Objectives

  • Acquiring additional (cleaner) data for more accurate descriptions of type clusters;
  • Evaluation of the necessity/criteria/priorities for adding additional sites;
  • Use a national database rather than case studies starting with and supplementing those already available, for example the Coastal Assessment and Data Synthesis database (http://cads.nos.noaa.gov/) and/or remotely sensed data;
  • Use preliminary cluster-based typologies to develop perturbation/response relationships and to test the reasonableness of the clusters. This will make use of remotely sensed color/Chl a data with loadings from the existing database;
  • Modify and expand access to the DISCO geospatial clustering tool and develop additional tools for community involvement in analysis.

Time Frame

2006.

For More Information

Project Manager:
1305 East West Highway
SSMC-IV, N/SCI-1
Silver Spring, MD 20910
301-713-3020 x139