Item talk:Q47266
From geokb
{
"USGS Staff Profile": { "@context": "https://schema.org", "@type": "Person", "dateModified": "2024-09-21T07:57:14.339977", "name": "Katherine J Knierim, Ph.D. PG", "identifier": [ { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-5361-4132" } ], "jobTitle": "Hydrologist", "hasOccupation": [ { "@type": "OrganizationalRole", "startDate": "2024-09-21T07:57:14.346001", "affiliatedOrganization": { "@type": "Organization", "name": "Lower Mississippi-Gulf Water Science Center", "url": "https://www.usgs.gov/centers/lower-mississippi-gulf-water-science-center" }, "roleName": "Hydrologist" }, { "@type": "Occupation", "additionalType": "self-claimed professional experience", "name": "Hydrologist, U.S. Geological Survey, Little Rock, AR 2015 - current" } ], "description": [ { "@type": "TextObject", "additionalType": "short description", "abstract": "Hydrologist with the Lower Mississippi-Gulf Water Science Center" }, { "@type": "TextObject", "additionalType": "staff profile page introductory statement", "abstract": "Katherine (Kathy) Knierim is a hydrologist with the Lower Mississippi-Gulf Water Science Center in Little Rock, Arkansas. Her research focuses on groundwater quality." }, { "@type": "TextObject", "additionalType": "personal statement", "abstract": "I have worked on a diversity of projects throughout my career with the USGS and maintain a focus on groundwater. I contributed to the Ozark Plateaus Groundwater Availability project, which developed a groundwater flow model of the Ozark Plateaus Regional Aquifer System (https://www.usgs.gov/publications/ozark-plateaus-regional-aquifer-study-documentation-a-groundwater-flow-model). I was a team member and lead modeler for a National Water Quality Assessment Project which used machine learning to predict groundwater quality in the Mississippi Embayment Regional Aquifer System (https://www.sciencebase.gov/catalog/item/5e8de0e282cee42d13468793). I also led the Mississippi Alluvial Plain Project Water Quality task, which collected groundwater age tracers to characterize the age and recharge rates of one of the Nation's most heavily pumped groundwater aquifers.I'm currently a team member for a national groundwater quality project, where we are using machine learning to predict salinity. I'm also working collaboratively with the Geology, Energy & Minerals Science Center to characterize lithium in the Smackover Formation (https://www.usgs.gov/centers/geology-energy-and-minerals-science-center/science/oil-and-gas-waters-project). Additionally, I work with local and State partners to help leverage USGS expertise to answer questions about water quality and availability." } ], "email": "kknierim@usgs.gov", "url": "https://www.usgs.gov/staff-profiles/katherine-j-knierim", "affiliation": [ { "@type": "Organization", "name": "Geological Society of America, Hydrogeology Division" } ], "hasCredential": [ { "@type": "EducationalOccupationalCredential", "name": "Doctor of Philosophy in Environmental Dynamics, University of Arkansas, Fayetteville, AR, 2015" }, { "@type": "EducationalOccupationalCredential", "name": "Master of Science in Geology, University of Arkansas, Fayetteville, AR, 2009" }, { "@type": "EducationalOccupationalCredential", "name": "Bachelor of Science with University Honors in Geology, Bowling Green State University, Bowling Green, OH, 2007" } ], "knowsAbout": [ { "@type": "Thing", "additionalType": "self-claimed expertise", "name": "groundwater" }, { "@type": "Thing", "additionalType": "self-claimed 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