Filters: Tags: Upper Chesapeake aquifer (X) > Categories: Data (X)
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A digital model of the sedimentary Northern Atlantic Coastal Plain aquifer system is composed of 20 rasters and hydrogeologic unit extent polygons. Rasters describe the top elevations of regional aquifers and confining units at a resolution of 2640 feet (1/2 mile). The rasters are clipped to the extent polygons, which represent the spatial extents of the hydrogeologic units onshore and several miles offshore. This three-dimensional hydrogeologic model was constructed as part of a U.S. Geological Survey Groundwater Resources Program study of groundwater availability in the Northern Atlantic Coastal Plain (NACP) aquifer system, including parts of New York, New Jersey, Delaware, Maryland, Virginia, and North Carolina....
Categories: Data,
Data Release - Revised;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Aquia aquifer,
Delaware,
Delmarva Peninsula,
Eastern Shore,
Fall Line,
Data used to model and map manganese concentrations in groundwater in the Northern Atlantic Coastal Plain (NACP) aquifer system, eastern USA, are documented in this data release. The model predicts manganese concentration within four classes and is based on concentration data from 4492 wells. The well data were compiled from U.S. Geological Survey, U.S. Environmental Protection Agency, Suffolk County Water Authority (Suffolk County, New York), and state agency sources. The four concentration classes are based on guidelines for drinking water quality: below detection (class 1, less than 10 micrograms per liter (ug/L)); detected but less than the aesthetic guideline of 50 ug/L (class 2); greater than the aesthetic...
Data used to model and map pH and redox conditions in groundwater in the Northern Atlantic Coastal Plain aquifer system, eastern USA, are documented in this data release. The models use as input data measurements of pH and dissolved oxygen concentrations at about 3000 to 5000 wells, which were compiled primarily from U.S. Geological Survey and U.S. Environmental Protection Agency databases. The boosted regression trees machine learning method was used to build the models. Explanatory variables (predictors) describe geology, hydrology, chemistry, physical characteristics, anthropogenic influence, metrics from a groundwater flow model, and groundwater residence times in the aquifer system. Data for four models are...
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