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Filters: Tags: Connecticut (X) > partyWithName: James E Reddy (X) > Types: OGC WFS Layer (X)

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This data release contains input data used in model development and TIF raster files used to predict the probability of low dissolved oxygen (DO) and high dissolved iron (Fe) in groundwater within the glacial aquifer system in the northern continental United States. Input data include measured DO and Fe concentrations at groundwater wells, and associated predictor variable data. The probability of low DO and high Fe was predicted using boosted regression tree methods using the gbm package in R (v. 4.0.0) in RStudio (v. 1.2.5042). The response variables for individual models were the occurrence of: (1) DO ≤0.5 mg/L, (2) DO ≤2 mg/L, and (3) Fe >100 µg/L. Water-quality data were compiled from three sources, as described...
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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...
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Residence time distribution (RTD) is a critically important characteristic of groundwater flow systems; however, it cannot be measured directly. RTD can be inferred from tracer data with analytical models (few parameters) or with numerical models (many parameters). The second approach permits more variation in system properties but is used less frequently than the first because large-scale numerical models can be resource intensive. With the data and computer codes in this data release users can (1) reconstruct and run 115 General Simulation Models (GSMs) of groundwater flow, (2) calculate groundwater age metrics at selected GSM cells, (3) train a boosted regression tree model using the provided data, (4) predict...


    map background search result map search result map Groundwater data, predictor variables, and rasters used for predicting redox conditions in the glacial aquifer, northern continental United States Data for three-dimensional distribution of groundwater residence time metrics in the glaciated United States using metamodels trained on general numerical simulation models Data for machine learning predictions of pH in the glacial aquifer system, northern USA Data for machine learning predictions of pH in the glacial aquifer system, northern USA Data for three-dimensional distribution of groundwater residence time metrics in the glaciated United States using metamodels trained on general numerical simulation models Groundwater data, predictor variables, and rasters used for predicting redox conditions in the glacial aquifer, northern continental United States