Kathy is a hydrologist with the Lower Mississippi-Gulf Water Science Center in the Little Rock, Arkansas office where she investigates groundwater and water quality.
She is currently part of the Ozark Plateaus Aquifer Study group and has modeled groundwater use and developed a digital dataset of groundwater-surface water interaction. She is also part of the National Water Quality Assessment Mapping and Modeling Team for the Mississippi Embayment, which is modeling groundwater quality in three dimensions.
Kathy's research has included karst hydrogeology, vadose zone hydrology, groundwater quality, stable isotopes, water use, and geoscience education. She enjoys using Python programming and GIS to help her answer water availability questions.
Education:
B.S. -- Geology -- 2007 -- Bowling Green State University, Bowling Green, OH
Honors Thesis: Spectroscopic analysis of clay alteration and vegetation in the North Screamer area, Barrick Goldstrike Property
M.S. -- Geology -- 2009 -- University of Arkansas, Fayetteville, AR
Thesis: Seasonal variation of carbon and nutrient transfer in a northwestern Arkansas cave
Ph.D. -- Environmental Dynamics -- 2015 -- University of Arkansas, Fayetteville AR
Dissertation: Stable Isotopes as a Tool to Characterize Carbon Cycling and Develop Hydrologic Budgets in Mantled Karst Settings
Science and Products
Machine-learning model predictions and rasters of arsenic and manganese in groundwater in the Mississippi River Valley alluvial aquifer
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
Simulated groundwater residence times in two principal aquifers of the Mississippi embayment physiographic region
Prediction grids of pH for the Mississippi River Valley Alluvial and Claiborne Aquifers
Machine-learning model predictions and groundwater-quality rasters of specific conductance, total dissolved solids, and chloride in aquifers of the Mississippi embayment
Carbonate geochemistry dataset of the soil and an underlying cave in the Ozark Plateaus, central United States
Machine-learning predictions of redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States
Predicted pH of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States
Salinity and total dissolved solids measurements for natural waters: An overview and a new salinity method based on specific conductance and water type
Mapped predictions of manganese and arsenic in an alluvial aquifer using boosted regression trees
Airborne geophysical surveys of the lower Mississippi Valley demonstrate system-scale mapping of subsurface architecture
The impact of ventilation patterns on calcite dissolution rates within karst conduits
Using boosted regression tree models to predict salinity in Mississippi embayment aquifers, central United States
Groundwater availability in the Ozark Plateaus aquifer system
Encylopedia of Caves
The Ozark Plateaus Regional Aquifer Study—Documentation of a groundwater-flow model constructed to assess water availability in the Ozark Plateaus
Challenges for creating a site-specific groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010
Carbon cycling in the mantled karst of the Ozark Plateaus, central United States
Using stable isotopes of carbon to investigate the seasonal variation of carbon transfer in a northwestern Arkansas cave
Using isotopes of dissolved inorganic carbon species and water to separate sources of recharge in a cave spring, northwestern Arkansas, USA Blowing Spring Cave
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
- Data
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 maMachine-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 dSimulated groundwater residence times in two principal aquifers of the Mississippi embayment physiographic region
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 QuaterPrediction 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 dMachine-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 accommodCarbonate geochemistry dataset of the soil and an underlying cave in the Ozark Plateaus, central United States
The nature of carbon (C) cycling in the vadose zone where groundwater is in contact with abundant gas-filled voids is poorly understood. The objective of this study was to trace C cycling in a karst landscape using stable-C isotopes, with emphasis on a shallow groundwater flow path through the soil, to an underlying cave, and to the spring outlet of a cave stream in the Ozark Plateaus of northwest - Maps
Machine-learning predictions of redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States
Machine-learning models developed by the U.S. Geological Survey were used to predict iron concentrations and the probability of dissolved oxygen (DO) concentrations exceeding a threshold of 1 milligram per liter (mg/L) in groundwater in aquifers of the Mississippi embayment physiographic region. DO and iron concentrations are driven by and reflect the oxidation-reduction (redox) conditions in grouPredicted pH of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States
Regional aquifers in the Mississippi embayment are the principal sources of water used for public and domestic supply, irrigation, and industrial uses throughout the region. An understanding of how water quality varies spatially, temporally, and with depth are critical aspects to ensuring long-term sustainable use of these resources. A boosted regression tree (BRT) model was used by the U.S. Geolo - Publications
Filter Total Items: 13
Salinity and total dissolved solids measurements for natural waters: An overview and a new salinity method based on specific conductance and water type
The total concentration of dissolved constituents in water is routinely quantified by measurements of salinity or total dissolved solids (TDS). However, salinity and TDS are operationally defined by their analytical methods and are not equivalent for most waters. Furthermore, multiple methods are available to determine salinity and TDS, and these methods have inherent differences. TDS is defined aAuthorsR. Blaine McCleskey, Charles A. Cravotta, Matthew P. Miller, Fred D. Tillman, Paul Stackelberg, Katherine J. Knierim, Daniel WiseMapped predictions of manganese and arsenic in an alluvial aquifer using boosted regression trees
Manganese (Mn) concentrations and the probability of arsenic (As) exceeding the drinking-water standard of 10 μg/L were predicted in the Mississippi River Valley alluvial aquifer (MRVA) using boosted regression trees (BRT). BRT, a type of ensemble-tree machine-learning model, were created using predictor variables that affect Mn and As distribution in groundwater. These variables included iron (FeAuthorsKatherine J. Knierim, James A. Kingsbury, Kenneth Belitz, Paul Stackelberg, Burke J. Minsley, James Robert RigbyAirborne geophysical surveys of the lower Mississippi Valley demonstrate system-scale mapping of subsurface architecture
The Mississippi Alluvial Plain hosts one of the most prolific shallow aquifer systems in the United States but is experiencing chronic groundwater decline. The Reelfoot rift and New Madrid seismic zone underlie the region and represent an important and poorly understood seismic hazard. Despite its societal and economic importance, the shallow subsurface architecture has not been mapped with the spAuthorsBurke J. Minsley, James Robert Rigby, Stephanie R. James, Bethany L. Burton, Katherine J. Knierim, Michael Pace, Paul A. Bedrosian, Wade KressThe impact of ventilation patterns on calcite dissolution rates within karst conduits
Erosion rates in streams vary dramatically over time, as differences in streamflow and sediment load enhance or inhibit erosion processes. Within cave streams, and other bedrock channels incising soluble rocks, changes in water chemistry are an important factor in determining how erosion rates will vary in both time and space. Prior studies in surface streams, springs, and caves suggest that variaAuthorsMatthew D. Covington, Katherine J. Knierim, Holly H Young, Josue Rodriguez, Hannah GnozaUsing boosted regression tree models to predict salinity in Mississippi embayment aquifers, central United States
High salinity limits groundwater use in parts of the Mississippi embayment. Machine learning was used to create spatially continuous and three‐dimensional predictions of salinity across drinking‐water aquifers in the embayment. Boosted regression tree (BRT) models, a type of machine learning, were used to predict specific conductance (SC) and chloride (Cl), and total dissolved solids (TDS) was calAuthorsKatherine J. Knierim, James A. Kingsbury, Connor J. Haugh, Katherine Marie RansomGroundwater availability in the Ozark Plateaus aquifer system
Executive SummaryThe study described in this report, initiated by the U.S. Geological Survey in 2014, was designed to evaluate fresh groundwater resources within the Ozark Plateaus, central United States, as an area within a broader national assessment of groundwater availability. The goals of the Ozark study were to evaluate historical effects of human activities on water levels and groundwater aAuthorsBrian R. Clark, Leslie L. Duncan, Katherine J. KnierimEncylopedia of Caves
For many people, a visit to a cave is a wondrous event directing our minds to ponder the mysteries presented by these unique places and inspiring questions: How old is the cave? What was the role of water in forming the cave and where did the water come from? How is the cave connected to the surface environment? These are intriguing questions to ask, and karst scientists use isotope geochemistry tAuthorsKatherine J. Knierim, Phillip D. HaysThe Ozark Plateaus Regional Aquifer Study—Documentation of a groundwater-flow model constructed to assess water availability in the Ozark Plateaus
Recent short-term drought conditions have emphasized the need to better understand the delicate balance between abundance, sustainability, and scarcity of groundwater in the Ozark Plateaus aquifer system. In 2014, the U.S. Geological Survey began construction of a groundwater-flow model as a tool for the assessment of groundwater availability in the Ozark Plateaus aquifer system. The model was devAuthorsBrian R. Clark, Joseph M. Richards, Katherine J. KnierimChallenges for creating a site-specific groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010
Hydrologic budgets to determine groundwater availability are important tools for water-resource managers. One challenging component for developing hydrologic budgets is quantifying water use through time because historical and site-specific water-use data can be sparse or poorly documented. This research developed a groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 19AuthorsKatherine J. Knierim, Anna M. Nottmeier, Scott C. Worland, Drew A. Westerman, Brian R. ClarkCarbon cycling in the mantled karst of the Ozark Plateaus, central United States
The nature of carbon (C) cycling in the unsaturated zone where groundwater is in contact with abundant gas-filled voids is poorly understood. The objective of this study was to trace inorganic-C cycling in a karst landscape using stable-C isotopes, with emphasis on a shallow groundwater flow path through the soil, to an underlying cave, and to the spring outlet of a cave stream in the Ozark PlateaAuthorsKatherine J. Knierim, Erik D. Pollock, Matthew D. Covington, Phillip D. Hays, Kristofor R. BryeUsing stable isotopes of carbon to investigate the seasonal variation of carbon transfer in a northwestern Arkansas cave
Stable-isotope analyses are valuable in karst settings, where characterizing biogeochemical cycling of carbon along groundwater flow paths is critical for understanding and protecting sensitive cave and karst water resources. This study quantified the seasonal changes in concentration and isotopic composition (δ13C) of aqueous and gaseous carbon species—dissolved inorganic carbon (DIC) and gaseousAuthorsKatherine J. Knierim, Erik Pollock, Phillip D. Hays, Jam KhojastehUsing isotopes of dissolved inorganic carbon species and water to separate sources of recharge in a cave spring, northwestern Arkansas, USA Blowing Spring Cave
Blowing Spring Cave in northwestern Arkansas is representative of cave systems in the karst of the Ozark Plateaus, and stable isotopes of water (δ18O and δ2H) and inorganic carbon (δ13C) were used to quantify soil-water, bedrock-matrix water, and precipitation contributions to cave-spring flow during storm events to understand controls on cave water quality. Water samples from recharge-zone soilsAuthorsKatherine J. Knierim, Erik Pollock, Phillip D. HaysNon-USGS Publications**
Knierim, K.J., Hays, P.D., and Bowman, D., 2015, Quantifying the variability in Escherichia coli (E. coli) throughout storm events at a karst spring in northwestern Arkansas, United States: Environmental Earth Sciences, v. 74, p. 4607–4623, doi: 10.1007/s12665-015-4416-5.Knierim, K., Turner, H., and Davis, R.K., 2015, Two-Stage Exams Improve Student Learning in an Introductory Geology Course: Logistics, Attendance, and Grades: Journal of Geoscience Education, v. 63, p. 157–164, doi: 10.5408/14-051.1Knierim, K.J. and Hays, P.D., 2014, PECCI Code (PythonTM Estimation for Carbon Concentration and Isotopes) for calculating the concentration and stable carbon isotopic composition of dissolved inorganic carbon (DIC) in precipitation for northwestern Arkansas: Arkansas Water Resources Center MSC Publication 370, 26 p.**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.