Skip to main content
Advanced Search

Filters: partyWithName: Katherine J Knierim (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)

Folders: ROOT > ScienceBase Catalog > USGS Lower Mississippi-Gulf Water Science Center ( Show direct descendants )

17 results (53ms)   

View Results as: JSON ATOM CSV
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
Of the approximately 6.6 million people living in the Mississippi embayment (MISE) region in the central United States, approximately 65 percent rely on groundwater for their drinking water (Dieter, Linsey, and others, 2017). Regional assessments of water quality in principal aquifer systems provide context for the long-term availability of these water resources for drinking-water supplies. To assess the current (2018) status of water quality in MISE in relation to drinking water supplies, groundwater withdrawal zones used for domestic and public supply were modeled using available groundwater well and hydrogeologic framework data. Three dimensional surfaces were modeled to map the depth zones at which groundwater...
thumbnail
Groundwater residence times and flow path lengths were simulated for two major aquifers of the Mississippi embayment region using particle tracking (Pollock, 2012; Starn and Belitz, 2018) in a regional groundwater-flow model (Haugh and others, 2020). The Mississippi embayment physiographic region includes two principal aquifer systems: the surficial aquifer system, which is dominated by the Quaternary Mississippi River Valley alluvial aquifer (MRVA), and the Mississippi embayment aquifer system, which includes deeper Tertiary aquifers and confining units. The groundwater residence time simulation focused on the MRVA and two hydrogeologic units of the Claiborne Group (CLBG) from the deeper system, including the middle...
thumbnail
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...
thumbnail
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,...
thumbnail
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,...
thumbnail
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,...
thumbnail
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,...
thumbnail
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...
thumbnail
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,...
thumbnail
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...
thumbnail
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...
thumbnail
These datasets provide the locations of and groundwater-level altitudes from 273 wells that were used to construct a 2015 potentiometric contour surface of the Sparta-Memphis aquifer. Measurements were made from January through June 2015 and represent synoptic conditions. All wells were cased completely in and screened in the Sparta-Memphis aquifer. Groundwater-level data are also available from the USGS National Water Information System (U.S. Geological Survey, 2017). The groundwater-level change maps for the Sparta-Memphis aquifer are constructed as a point-to-point comparison with wells measured in both 2011 and 2013 and both 2013 and 2015. Wells not measured in both 2011 and 2013 and both 2013 and 2015 were...
thumbnail
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...


    map background search result map search result map Datasets for the 2015 potentiometric surface and water-level changes (2011-2013, 2013-2015) in the Sparta-Memphis aquifer, in Arkansas Groundwater withdrawal zones for drinking water from the Mississippi River Valley alluvial aquifer and Mississippi embayment aquifers Simulated groundwater residence times in two principal aquifers of the Mississippi embayment physiographic region Machine-learning model predictions and groundwater-quality rasters of specific conductance, total dissolved solids, and chloride in aquifers of the Mississippi embayment Prediction grids of pH for the Mississippi River Valley Alluvial and Claiborne Aquifers Machine-learning model predictions and groundwater-quality rasters of chloride in aquifers of the Mississippi Embayment Depth rasters in aquifers of the Mississippi Embayment Machine-learning model predictions and groundwater-quality rasters of specific conductance in aquifers of the Mississippi Embayment Machine-learning model predictions and groundwater-quality rasters of total dissolved solids in aquifers of the Mississippi Embayment Machine-learning model predictions and rasters of groundwater salinity in the Mississippi Alluvial Plain 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 Depth rasters of redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Dissolved oxygen probability rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Iron concentration rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Redox zone rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Machine-learning model predictions and rasters of arsenic and manganese in groundwater in the Mississippi River Valley alluvial aquifer 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 Datasets for the 2015 potentiometric surface and water-level changes (2011-2013, 2013-2015) in the Sparta-Memphis aquifer, in Arkansas Machine-learning model predictions and rasters of groundwater salinity in the Mississippi Alluvial Plain 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 Groundwater withdrawal zones for drinking water from the Mississippi River Valley alluvial aquifer and Mississippi embayment aquifers Simulated groundwater residence times in two principal aquifers of the Mississippi embayment physiographic region Machine-learning model predictions and groundwater-quality rasters of specific conductance, total dissolved solids, and chloride in aquifers of the Mississippi embayment Prediction grids of pH for the Mississippi River Valley Alluvial and Claiborne Aquifers Machine-learning model predictions and groundwater-quality rasters of chloride in aquifers of the Mississippi Embayment Depth rasters in aquifers of the Mississippi Embayment Machine-learning model predictions and groundwater-quality rasters of specific conductance in aquifers of the Mississippi Embayment Machine-learning model predictions and groundwater-quality rasters of total dissolved solids in aquifers of the Mississippi Embayment 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 Depth rasters of redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Dissolved oxygen probability rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Iron concentration rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Redox zone rasters of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers Machine-learning model predictions and rasters of arsenic and manganese in groundwater in the Mississippi River Valley alluvial aquifer