Road salt elevates salinity above background levels in freshwater streams and rivers across the Chesapeake Bay Watershed
The findings of this study show that salinity is elevated above background levels throughout most freshwater streams within the Chesapeake Bay watershed. This information can help prioritize salt management strategies for local streams and rivers.
Issue
Excess salt in freshwater streams and rivers can harm aquatic organisms and increase toxicity of other contaminants. Road salt is often applied to roads, sidewalks, and other impervious surfaces during winter weather events, which then runs off into local waterways. Agriculture and mining activities can also increase salt loading to streams. Recent trend analyses have documented increasing trends in salinity in the region. A major goal for the Chesapeake Bay Program restoration effort is to improve stream health conditions in 10% of streams. Therefore, managers need to know where salinity may be a limiting factor (or stressor) in streams and rivers to prioritize and target management actions.
USGS Study
The USGS conducted this study to predict salinity conditions across the entire Chesapeake Bay watershed. Observations of salinity and predictor variables representing salt sources were compiled. A machine-learning model was used to identify the major sources of salinity and to predict salinity conditions for all watershed streams and rivers. Finally, predicted salinity was compared to background salinity to determine the extent to which salinity was elevated.
Major Findings
- Two-thirds of stream reaches had elevated salinity compared to background levels (Fig. 1).
- Areas with the highest levels of salinity expanded and areas with low levels of salinity decreased over a 15-year period.
- Increasing salinity was associated with expanding impervious cover.
- The highest salinity conditions were in urban areas receiving winter-season snow (Fig. 1).
- Agricultural areas also had elevated salinity above background levels.
Management Implications
- Knowledge about the driving factors of salinity in Chesapeake Bay streams and rivers can inform the development of effective management strategies.
- Local predictions of salinity in Chesapeake Bay streams and rivers can be used to prioritize areas for conservation or restoration activities.
For More Information
- The full study is published online with open access: Predictive Modeling Reveals Elevated Conductivity Relative to Background Levels in Freshwater Tributaries within the Chesapeake Bay Watershed, USA
- The data used in the study is available online: Predictions of specific conductance and departures from background specific conductance in the Chesapeake Bay watershed, 2001-2016
Predictions of specific conductance and departures from background specific conductance in the Chesapeake Bay watershed, 2001-2016
Predictive modeling reveals elevated conductivity relative to background levels in freshwater tributaries within the Chesapeake Bay watershed, USA
The findings of this study show that salinity is elevated above background levels throughout most freshwater streams within the Chesapeake Bay watershed. This information can help prioritize salt management strategies for local streams and rivers.
Issue
Excess salt in freshwater streams and rivers can harm aquatic organisms and increase toxicity of other contaminants. Road salt is often applied to roads, sidewalks, and other impervious surfaces during winter weather events, which then runs off into local waterways. Agriculture and mining activities can also increase salt loading to streams. Recent trend analyses have documented increasing trends in salinity in the region. A major goal for the Chesapeake Bay Program restoration effort is to improve stream health conditions in 10% of streams. Therefore, managers need to know where salinity may be a limiting factor (or stressor) in streams and rivers to prioritize and target management actions.
USGS Study
The USGS conducted this study to predict salinity conditions across the entire Chesapeake Bay watershed. Observations of salinity and predictor variables representing salt sources were compiled. A machine-learning model was used to identify the major sources of salinity and to predict salinity conditions for all watershed streams and rivers. Finally, predicted salinity was compared to background salinity to determine the extent to which salinity was elevated.
Major Findings
- Two-thirds of stream reaches had elevated salinity compared to background levels (Fig. 1).
- Areas with the highest levels of salinity expanded and areas with low levels of salinity decreased over a 15-year period.
- Increasing salinity was associated with expanding impervious cover.
- The highest salinity conditions were in urban areas receiving winter-season snow (Fig. 1).
- Agricultural areas also had elevated salinity above background levels.
Management Implications
- Knowledge about the driving factors of salinity in Chesapeake Bay streams and rivers can inform the development of effective management strategies.
- Local predictions of salinity in Chesapeake Bay streams and rivers can be used to prioritize areas for conservation or restoration activities.
For More Information
- The full study is published online with open access: Predictive Modeling Reveals Elevated Conductivity Relative to Background Levels in Freshwater Tributaries within the Chesapeake Bay Watershed, USA
- The data used in the study is available online: Predictions of specific conductance and departures from background specific conductance in the Chesapeake Bay watershed, 2001-2016