Data used to model and map pH and redox conditions in the Northern Atlantic Coastal Plain aquifer system, eastern USA

Dates

Publication Date: 2020-06-30
Time Period: 2020

Citation

DeSimone, L.A., and Pope, J.P., 2020, Data used to model and map pH and redox conditions in the Northern Atlantic Coastal Plain aquifer system, eastern USA: U.S. Geological Survey data release, https://doi.org/10.5066/P94DYERF.

Summary

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 documented--one model [...]

Summary

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 documented--one model for pH and one model each for the probability of dissolved oxygen less than three threshold values (0.5, 1, and 2 milligrams per liter). The data are provided in data tables and raster files, organized as follows. There is one data table for the well data used to develop all four models (well data). There is one zipped group of 10 files (one for each aquifer) for explanatory input data used to make predictions at grid points (prediction input). There are 9 zipped groups of files for model output; these include 1 zip file of predictions at grid points for each of the 4 models (prediction output), 1 zip file for combined pH and dissolved oxygen predictions (combined prediction output); and 4 zip files of uncertainty intervals for predictions for each of the 4 models (uncertainty output). Filenames for prediction input and for model output are distinguished by codes abbreviating the aquifer name and position in the vertical stack of 19 regional aquifers and confining units, as follows: Surficial aquifer, 1surf; Upper Chesapeake aquifer, 3upch; Lower Chesapeake aquifer, 5loch; Piney Point aquifer, 7pipt; Aquia aquifer, 9aqia; Monmouth - Mt. Laurel Aquifer, 11moml; Matawan aquifer, 13mtwn; Magothy Aquifer, 15mgty; Potomac-Patapsco aquifer, 17popt; Potomac-Patuxent aquifer, 19popx. The data release also contains a tif-format raster file of the prediction grid and two data tables that separately describe the explanatory variables (predictors) and their sources.

Contacts

Point of Contact :: Leslie A Desimone, New England Water Science Center
Originator :: Leslie A Desimone, Jason P Pope
Metadata Contact :: Leslie A Desimone, New England Water Science Center
Publisher :: U.S. Geological Survey
Distributor :: U.S. Geological Survey - ScienceBase
SDC Data Owner :: Earth System Processes Division
USGS Mission Area :: Water Resources

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Metadata for NACP_pH_and_redox_conditions_data.xml Original FGDC Metadata	View	81.95 KB	application/fgdc+xml
nacp_well_data_phdo_models.csv		4.88 MB	text/csv
nacp_aquifers_prediction_input_data.zip		196.36 MB	application/zip
nacp_aquifers_prediction_output_ph.zip		6.72 MB	application/zip
nacp_aquifers_prediction_output_do_catd5.zip		6.74 MB	application/zip
nacp_aquifers_prediction_output_do_cat1.zip		6.86 MB	application/zip
nacp_aquifers_prediction_output_do_cat2.zip		6.57 MB	application/zip
nacp_aquifers_prediction_output_phdo_combined.zip		8.87 MB	application/zip
nacp_aquifers_uncertainty_output_ph.zip		18.62 MB	application/zip
nacp_aquifers_uncertainty_output_do_catd5.zip		17.65 MB	application/zip
nacp_aquifers_uncertainty_output_do_cat1.zip		18.06 MB	application/zip
nacp_aquifers_uncertainty_output_do_cat2.zip		17.44 MB	application/zip
nacp_prediction_grid.zip		491.41 KB	application/zip
predictor_definitions.csv		19.75 KB	text/csv
predictor_sources.csv		6.33 KB	text/csv

Related External Resources

Type: Related Primary Publication

DeSimone, L.A., Pope, J.P., and Ransom, K.M., 2020, Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA: Journal of Hydrology: Regional Studies, v. 30, p. 100697, https://doi.org/10.1016/j.ejrh.2020.100697.	https://doi.org/10.1016/j.ejrh.2020.100697

Purpose

These data were compiled to develop models and maps of pH and redox conditions in the Northern Atlantic Coastal Plain aquifer system. pH and redox conditions are important controlling factors on the distribution of many of the common contaminants in groundwater that are of concern for human and ecological health. Models and maps of pH and redox conditions in groundwater can be used to identify areas of the aquifer system and the coastal waters receiving groundwater discharge that are potentially vulnerable to these contaminants.

Data used to model and map pH and redox conditions in the Northern Atlantic Coastal Plain aquifer system, eastern USA

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