Manganese in the Northern Atlantic Coastal Plain aquifer system, eastern USA—Modeling regional occurrence with pH, redox, and machine learning
| Autor: | Katherine Marie Ransom, Leslie A. DeSimone |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Physical geography
Class imbalance Groundwater flow Coastal plain Water supply Aquifer Machine learning computer.software_genre Groundwater quality Earth and Planetary Sciences (miscellaneous) Xgboost Water Science and Technology Surficial aquifer geography Manganese QE1-996.5 geography.geographical_feature_category business.industry Geology Groundwater recharge Classification GB3-5030 Environmental science Water quality Artificial intelligence business computer Groundwater |
| Zdroj: | Journal of Hydrology: Regional Studies, Vol 37, Iss, Pp 100925-(2021) |
| ISSN: | 2214-5818 |
| Popis: | Study region: The study was conducted in the Northern Atlantic Coastal Plain aquifer system, eastern USA, an important water supply in a densely populated region. Study focus: Manganese (Mn), an emerging health concern and common nuisance contaminant in drinking water, is mapped and modeled using the XGBoost machine learning method, predictions of pH and redox conditions from previous models, and other explanatory variables that describe the groundwater flow system and surface characteristics. Methods to address the imbalanced occurrence of elevated and low Mn concentrations are compared and used to more accurately predict concentrations of interest for human health and drinking water quality. New hydrological insights for the region: Elevated Mn concentrations were more likely in shallow groundwater, close to recharge areas and in topographically low areas where soil or unsaturated processes influence groundwater quality. Predicted concentrations greater than the health threshold of 300 micrograms per liter extended across 17 % of the surficial aquifer area, but across |
| Databáze: | OpenAIRE |
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