Predictive Modeling Reveals Elevated Conductivity Relative to Background Levels in Freshwater Tributaries within the Chesapeake Bay Watershed, USA.

Rosemary M Fanelli, Joel Moore, Charles C Stillwell, Andrew J Sekellick, Richard H Walker
Author Information
  1. Rosemary M Fanelli: U.S. Geological Survey, South Atlantic Water Science Center, 3916 Sunset Ridge Road, Raleigh, North Carolina 27607, United States. ORCID
  2. Joel Moore: Towson University, 8000 York Road, Towson, Maryland 21252, United States. ORCID
  3. Charles C Stillwell: U.S. Geological Survey, South Atlantic Water Science Center, 3916 Sunset Ridge Road, Raleigh, North Carolina 27607, United States. ORCID
  4. Andrew J Sekellick: U.S. Geological Survey, MD-DE-DC Water Science Center, 5522 Research Park Drive, Catonsville, Maryland 21228, United States. ORCID
  5. Richard H Walker: University of Tennessee, 615 McCallie Ave, Chattanooga, Tennessee 37403, United States.

Abstract

Elevated conductivity (i.e., specific conductance or SC) causes osmotic stress in freshwater aquatic organisms and may increase the toxicity of some contaminants. Indices of benthic macroinvertebrate integrity have declined in urban areas across the Chesapeake Bay watershed (CBW), and more information is needed about whether these declines may be due to elevated conductivity. A predictive SC model for the CBW was developed using monitoring data from the National Water Quality Portal. Predictor variables representing SC sources were compiled for nontidal reaches across the CBW. Random forests modeling was conducted to predict SC at four time periods (1999-2001, 2004-2006, 2009-2011, and 2014-2016), which were then compared to a national data set of background SC to quantify departures from background SC. Carbonate geology, impervious cover, forest cover, and snow depth were the most important variables for predicting SC. Observations and modeled results showed snow depth amplified the effect of impervious cover on SC. Elevated SC was predicted in two-thirds of reaches in the CBW, and these elevated conditions persisted over time in many areas. These results can be used in stressor identification assessments to prioritize future monitoring and to determine where management activities could be implemented to reduce salinization.

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