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Person

Melinda L Erickson

Supervisory Research Hydrologist
Upper Midwest Water Science Center

Email: merickso@usgs.gov
Office Phone: 763-272-8692
ORCID: 0000-0002-1117-2866

Location
Mounds View Business Center
2280 Woodale Drive
Mounds View , MN 55112-4900
US

Supervisor: Lisa Reynolds Fogarty
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This dataset provides aqueous nitrate+nitrite, aqueous manganese, aqueous iron, and total sulfate measurements in groundwater samples from 254 newly constructed private residential wells between 2014 and 2016. The study focuses on three geologically distinct regions of Minnesota: central, northwest, and northeast. These study regions were chosen due to their prevalent elevated As concentrations in drinking water. Each of the 254 wells were sampled in three rounds by the Minnesota Department of Health (MDH). The timing of the three sampling rounds was (1) immediately or shortly after well construction (round 1); (2) 3-6 months after initial sample collection (round 2); and (3) 12 months after initial sample collection...
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This data release contains input data used in model development and TIF raster files used to predict the probability of high arsenic (As) and high manganese (Mn) in groundwater within the glacial aquifer system in the northern United States. Input data include measured As and Mn concentrations at groundwater wells, and associated predictor variable data. The probability of high As and high Mn was predicted using boosted regression tree methods using the gbm package in R version 4.0.0. The response variables for individual models were the occurrence of: (1) As >10 µg/L, and (2) Mn >300 µg/L. Water-quality data were compiled from three sources, as described in Wilson and others (2019): a compilation of data from numerous...
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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This data release provides total and aqueous arsenic (As) determinations and associated field readings collected from groundwater sampled from 254 newly constructed private residential wells between 2014 and 2016. The study focuses on three regions of Minnesota that differ geologically: south-central (herein called central), northwest, and northeast. These study regions were chosen due to their prevalent elevated As concentrations in drinking water. Each of the 254 wells were sampled in three rounds by the Minnesota Department of Health (MDH). The timing of the three sampling rounds was (1) immediately or shortly after well construction (round 1); (2) 3-6 months after initial sample collection (round 2); and (3)...
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This data release contains: (1) ASCII grids of predicted probability of elevated arsenic in groundwater for the Northwest and Central Minnesota regions, (2) input arsenic and predictive variable data used in model development and calculation of predictions, and (3) ASCII files used to predict the probability of elevated arsenic across the two study regions. The probability of elevated arsenic was predicted using Boosted Regression Tree (BRT) modeling methods using the gbm package in R Studio version 3.4.2. The response variable was the presence or absence of arsenic >10 µg/L, the U.S. Environmental Protection Agency’s maximum contaminant level for arsenic, in 3,283 wells located throughout both study regions (1,363...
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