Paper No. 276-13
Presentation Time: 11:30 AM
THE U.S. GEOLOGICAL SURVEY’S SEDIMENT-BOUND CONTAMINANT RESILIENCY AND RESPONSE STRATEGY: A TIERED MULTI-METRIC APPROACH TO ENVIRONMENTAL HEALTH AND HAZARDS IN THE NORTHEASTERN USA
Coastal communities are uniquely vulnerable to sea-level rise and severe storms such as hurricanes. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms, which could adversely impact the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey (USGS) has developed the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy to define baseline and post-event sediment-bound environmental health stressors. A tiered, multi-metric approach will be used to: (a) identify and map contaminant sources and potential exposure pathways for human and ecological receptors, (b) define the baseline mixtures of environmental health stressors present in sediments and correlations of relevance, (c) document post-event changes in EH stressors present in sediments, and (d) establish and apply metrics to quantify changes in coastal resilience associated with sediment-bound contaminants. Integration of this information provides a means to better assess the baseline status of a complex system and the significance of changes in contaminant hazards due to storm-induced (episodic) and sea-level rise (incremental) disturbances. This talk describes the construction of a decision support tool to identify candidate stations vulnerable to contaminants that may be mobilized by coastal storms. The support tool is designed to accommodate a broad array of geologic, land-use, and climatic variables and utilizes public, nationally available data sources to define contaminant sources and storm vulnerabilities. By employing a flexible and adaptable strategy built upon publically available data, the method can readily be applied to other site selection or landscape evaluation efforts. Examples from the SCoRR pilot study and future applications will be discussed in addition to ongoing method developments.