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Modeling spatial and temporal variation in natural background specific conductivity
Citation:
Olson, J. AND S. Cormier. Modeling spatial and temporal variation in natural background specific conductivity. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 53(8):4316-4325, (2019). https://doi.org/10.1021/acs.est.8b06777
Impact/Purpose:
In both situations, natural variations in the constituents of freshwater can affect the potential toxicity of pollutants. This paper provides a method and results for estimating the natural background ionic concentration of freshwater. These estimates may be useful as a line of evidence for evaluating deviation from natural conditions and as an input variable in calculating toxicity of pollutants that are influenced by ionic interactions or by the ions themselves.
Description:
Understanding how background levels of specific conductivity (SC) vary in streams temporally and spatially is needed to assess salinization of fresh water, establish reasonable thresholds and restoration goals, and determine vulnerability to extreme climate events like drought. We developed a random forest (RF) model that predicts natural background SC for all stream segments in the contiguous United States at monthly time steps between the years 2001 to 2015. Models were trained using 11,796 observations made at 1,785 minimally impaired stream segments and validated with observations from an additional 92 segments. Static predictors of SC included geology, soils, and vegetation parameters. Temporal predictors were related to climate and enabled the model to make predictions for different dates. The model performed well explaining 95% of the variation in SC among validation observations (MAE = 29 µS/cm, NSE = 0.85). The model performed well across the period of interest, butinterest but exhibited bias in Coastal Plain and Xeric regions (26% and 30%, respectively). National model predictions showed large spatial variation with the greatest SC predicted to occur in the desert southwest and plains. Model predictions also reflected changes at individual streams during drought.
URLs/Downloads:
DOI: Modeling spatial and temporal variation in natural background specific conductivity
NIHMS-1025305.PDF (PDF, NA pp, 2061.814 KB, about PDF)
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