Filters: Tags: Groundwater Quality (X) > partyWithName: Katherine J Knierim (X)

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Machine-learning model predictions and rasters of arsenic and manganese in groundwater in the Mississippi River Valley alluvial aquifer Groundwater from the Mississippi River Valley alluvial aquifer (MRVA) is a vital resource for agriculture and drinking-water supplies in the central United States. Water availability can be limited in some areas of the aquifer by high concentrations of trace elements, including manganese and arsenic. Boosted regression trees, a type of ensemble-tree machine-learning method, were used to predict manganese concentration and the probability of arsenic concentration exceeding a 10 µg/L threshold throughout the MRVA. Explanatory variables for the BRT models included attributes associated with well location and construction, surficial variables (such as hydrologic position and recharge), variables extracted from a MODFLOW-2005... Categories: Data; Tags: Arkansas, Geochemistry, Hydrology, Illinois, Kentucky, All tags... Louisiana, Mississippi, Missouri, Tennessee, USGS Science Data Catalog (SDC), Water Quality, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Machine-learning model predictions and groundwater-quality rasters of specific conductance, total dissolved solids, and chloride in aquifers of the Mississippi embayment Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to... Categories: Data; Tags: Alabama, Arkansas, Geochemistry, Hydrology, Illinois, All tags... Kentucky, Louisiana, Mississippi, Tennessee, USGS Science Data Catalog (SDC), Water Quality, Water Resources, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Depth rasters in aquifers of the Mississippi Embayment Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Prediction grids of pH for the Mississippi River Valley Alluvial and Claiborne Aquifers Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical flow models and water quality in principal aquifer systems provide context for the long-term availability of these water resources. An innovative approach using machine learning was employed to predict groundwater pH across drinking water aquifers of the Mississippi embayment. The region includes two principal regional aquifer systems; the Mississippi River Valley alluvial (MRVA) aquifer and the Mississippi embayment aquifer system that includes several regional aquifers and confining units. Based on the distribution of groundwater use for... Categories: Data; Tags: Alabama, Arkansas, Kentucky, Louisiana, Mississippi, All tags... Tennessee, USGS Science Data Catalog (SDC), Water Quality, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Machine-learning model predictions and groundwater-quality rasters of total dissolved solids in aquifers of the Mississippi Embayment Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Dissolved oxygen probability rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of trace elements. The concentration of trace elements in groundwater is largely driven by oxidation-reduction (redox) processes. Redox processes are a group of biotically driven reactions in which energy is derived from the exchange of electrons. In groundwater, this commonly occurs through decomposition of organic matter (carbon) by microbes, which consumes dissolved oxygen (DO). Under low DO conditions, iron (Fe), manganese, and arsenic can dissolve from coatings on aquifer sediments and be released into groundwater. Therefore,... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Iron concentration rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of trace elements. The concentration of trace elements in groundwater is largely driven by oxidation-reduction (redox) processes. Redox processes are a group of biotically driven reactions in which energy is derived from the exchange of electrons. In groundwater, this commonly occurs through decomposition of organic matter (carbon) by microbes, which consumes dissolved oxygen (DO). Under low DO conditions, iron (Fe), manganese, and arsenic can dissolve from coatings on aquifer sediments and be released into groundwater. Therefore,... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Depth rasters of redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of trace elements. The concentration of trace elements in groundwater is largely driven by oxidation-reduction (redox) processes. Redox processes are a group of biotically driven reactions in which energy is derived from the exchange of electrons. In groundwater, this commonly occurs through decomposition of organic matter (carbon) by microbes, which consumes dissolved oxygen (DO). Under low DO conditions, iron (Fe), manganese, and arsenic can dissolve from coatings on aquifer sediments and be released into groundwater. Therefore,... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Machine-learning model predictions and rasters of dissolved oxygen probability, iron concentration, and redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of trace elements. The concentration of trace elements in groundwater is largely driven by oxidation-reduction (redox) processes. Redox processes are a group of biotically driven reactions in which energy is derived from the exchange of electrons. In groundwater, this commonly occurs through decomposition of organic matter (carbon) by microbes, which consumes dissolved oxygen (DO). Under low DO conditions, iron (Fe), manganese, and arsenic can dissolve from coatings on aquifer sediments and be released into groundwater. Therefore,... Categories: Data; Tags: Alabama, Arkansas, Geochemistry, Hydrology, Illinois, All tags... Kentucky, Louisiana, Mississippi, Tennessee, USGS Science Data Catalog (SDC), Water Quality, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Groundwater age categories based on tritium concentrations in samples collected from the Mississippi River Valley alluvial aquifer and aquifers of the Mississippi embayment principal aquifer system The Mississippi River Valley alluvial aquifer (MRVA) overlies and is bounded by several regional aquifers that make up the Mississippi embayment aquifer system (MEAS) in the central United States. The MRVA, which consists of Quaternary alluvium, is one of the most heavily pumped aquifers in the nation and is a major source of groundwater for irrigation. Large groundwater-level declines in portions of the aquifer have raised concerns about sustainable use of this important resource. An aquifer-scale assessment of groundwater-age categories based on tritium concentrations was completed to better understand groundwater availability and susceptibility. The presence of tritium, a radioactive isotope of hydrogen, in a... Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Arkansas, Hydrology, Kentucky, Louisiana, Mississippi, All tags... Mississippi Alluvial Plain, Mississippi Embayment, Missouri, Tennessee, USGS Science Data Catalog (SDC), Water Quality, groundwater, groundwater age, groundwater quality, tritium, tritium analysis, Fewer tags Redox zone rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of trace elements. The concentration of trace elements in groundwater is largely driven by oxidation-reduction (redox) processes. Redox processes are a group of biotically driven reactions in which energy is derived from the exchange of electrons. In groundwater, this commonly occurs through decomposition of organic matter (carbon) by microbes, which consumes dissolved oxygen (DO). Under low DO conditions, iron (Fe), manganese, and arsenic can dissolve from coatings on aquifer sediments and be released into groundwater. Therefore,... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Machine-learning model predictions and rasters of groundwater salinity in the Mississippi Alluvial Plain Groundwater from the Mississippi River Valley alluvial aquifer (MRVA), coincident with the Mississippi Alluvial Plain (MAP), is a vital resource for agriculture and drinking-water supplies in the central United States. Water availability can be limited in some areas of the aquifer by high concentrations of salinity, measured as specific conductance. Boosted regression trees (BRT), a type of ensemble-tree machine-learning method, were used to predict specific conductance concentration at multiple depths throughout the MRVA and underlying aquifers. Two models were created to test the incorporation of datasets from a regional aerial electromagnetic (AEM) survey and evaluate model performance. Explanatory variables... Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Arkansas (AR), Illinois (IL), Kentucky (KY), Louisiana (LA), Mississippi (MS), All tags... Missouri (MO), Tennessee (TN), USGS Science Data Catalog (SDC), alluvial aquifer, aquifer, boosted regression trees, groundwater, groundwater quality, machine learning, mathematical modeling, water quailty, Fewer tags Machine-learning model predictions and groundwater-quality rasters of chloride in aquifers of the Mississippi Embayment Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags Machine-learning model predictions and groundwater-quality rasters of specific conductance in aquifers of the Mississippi Embayment Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to... Tags: Alabama, Arkansas, Illinois, Kentucky, Louisiana, All tags... Mississippi, Tennessee, aquifer, boosted regression tree, groundwater, groundwater quality, machine learning, mathematical modeling, Fewer tags