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This USGS data release contains 1-kilometer resolution source-layer rasters used to predict redox conditions and contaminant concentrations in groundwater in the Fox-Wolf-Peshtigo watershed in Wisconsin and Michigan using random forest classification. The model output layers are 1-kilometer resolution rasters of the predicted probability of elevated concentrations of nitrate, iron, and arsenic. This data release supports the following publication: Tesoriero, A.J., Gronberg, J.M., Juckem, P.F., Miller, M.P., and Austin, B.P., 2017, Predicting redox-sensitive contaminant concentrations in groundwater using random forest classification: Water Resources Research, v. 53, https://doi.org/10.1002/2016WR020197.
Tags: Fox-Wolf-Peshtigo watershed,
Michigan,
National Water Quality Program,
USGS Science Data Catalog (SDC),
Water Resources, All tags...
Wisconsin,
arsenic,
drinking water quality,
groundwater,
groundwater quality,
iron,
nitrate,
random forest classification,
redox, Fewer tags
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This dataset is a 900 meter resolution raster representing the depth in meters at which the probability of oxic groundwater occurring is at least 50%, for the Chesapeake Bay watershed. Oxic groundwater was defined as containing O2 values >= 2 mg/L. The values range from 0-100 meters, with 100 representing all depths greater than 100. It was created in support of models which define the oxic/suboxic interface, which is important for determining pathways for nitrate transport in groundwater and in streams. The dataset was derived from a logistic regression of variables representing surficial geology, position in the flow system, and soil drainage.
Types: Citation;
Tags: Chesapeake Bay,
District of Columbia,
Maryland,
National Water Quality Program,
Pennsylvania, All tags...
USGS Science Data Catalog (SDC),
Virginia,
groundwater,
logistic regression,
oxic conditions, Fewer tags
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