Filters: Tags: ph (X) > Types: OGC WMS Service (X) > Categories: Data (X) > partyWithName: Craig Brown (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Types Map Service (1) OGC WFS Layer (1) OGC WMS Layer (1) Contacts Melinda L Erickson Sarah M Elliott U.S. Geological Survey Leon J Kauffman Kenneth Belitz More... Tag Types Place (1) Theme (1) USGS Scientific Topic Keyword (1) Harvest Set (1) Tag Schemes None (1) View Results as: JSON ATOM CSV

Data for machine learning predictions of pH in the glacial aquifer system, northern USA A boosted regression tree (BRT) model was developed to predict pH conditions in three-dimensions throughout the glacial aquifer system (GLAC) of the contiguous United States using pH measurements in samples from 18,258 wells and predictor variables that represent aspects of the hydrogeologic setting. Model results indicate that the carbonate content of soils and aquifer materials strongly controls pH and when coupled with long flow paths, results in the most alkaline conditions. Conversely, in areas where glacial sediments are thin and carbonate-poor, pH conditions remain acidic. At depths typical of drinking-water supplies, predicted pH > 7.5 – which is associated with arsenic mobilization – occurs more frequently... Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Boosted regression trees, Calcite saturation index, Connecticut, Geochemistry, Geochemistry, All tags... Glacial aquifer system, Groundwater, Groundwater corrosivity, Hydrology, Idaho, Illinois, Indiana, Iowa, Kansas, Machine learning, Maine, Massachusetts, Michigan, Minnesota, Missouri, Montana, NAWQA, Nebraska, New Hampshire, New Jersey, New York, North Dakota, Ohio, Pennsylvania, Rhode Island, South Dakota, USGS Science Data Catalog (SDC), Vermont, Washington, Water Quality, Wisconsin, pH, Fewer tags