Katherine J Knierim, Ph.D. PG
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 and Certifications
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 Prope
M.S. Geology, 2009 -- University of Arkansas, Fayetteville, AR
Thesis: Seasonal variation of carbon and nutrient transfer in a northwestern Arkansas cave
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
Science and Products
Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables
Potentiometric surfaces (2013, 2015), groundwater quality (2010–15), and water-level changes (2011–13, 2013–15) in the Sparta-Memphis aquifer in Arkansas
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
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.
U.S. Geological Survey National Produced Waters Geochemical Database (ver. 3.0, December 2023)
Machine-learning model predictions and rasters of groundwater salinity in the Mississippi Alluvial Plain
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 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
Groundwater withdrawal rates from the Ozark Plateaus aquifer system, 1900 to 2010
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
Science and Products
Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables
Potentiometric surfaces (2013, 2015), groundwater quality (2010–15), and water-level changes (2011–13, 2013–15) in the Sparta-Memphis aquifer in Arkansas
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
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.