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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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A soil-water balance model (SWB) was developed to estimate evapotranspiration in six ditch basins of the Glacial Ridge National Wildlife Refuge area, northwestern Minnesota, during 2002–2015. The model was used to estimate evapotranspiration in water balances in six ditch basins as part of the associated report, U.S. Geological Survey Scientific Investigations Report 2019-5041 (https://dx.doi.org/10.3133/SIR20195041). This SWB model was derived from the statewide Minnesota SWB potential recharge model, described, calibrated, and documented as part of U.S. Geological Survey Scientific Investigations Report 2015-5038 (https://dx.doi.org/10.3133/sir20155038). The data sets and calibrations from the Minnesota statewide...


    map background search result map search result map Groundwater arsenic data and ASCII grids for predicting elevated arsenic in northwestern and central Minnesota using boosted regression tree methods A Soil-Water-Balance model and precipitation data used for HEC/HMS modelling at the Glacial Ridge National Wildlife Refuge area, northwestern Minnesota, 2002–15. A Soil-Water-Balance model and precipitation data used for HEC/HMS modelling at the Glacial Ridge National Wildlife Refuge area, northwestern Minnesota, 2002–15. Groundwater arsenic data and ASCII grids for predicting elevated arsenic in northwestern and central Minnesota using boosted regression tree methods