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

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.