Linzy Foster
About Linzy Foster
Linzy Foster is a Civil Engineer and Hydrologist with over a decade of experience at the U.S. Geological Survey, specializing in computational hydrology, particularly groundwater and contaminant transport.
Work at U.S. Geological Survey
Linzy Foster has been employed at the U.S. Geological Survey (USGS) as a Civil Engineer/Hydrologist since 2012. Based in the Austin, Texas area, Foster has accumulated over 12 years of experience in this role. Prior to this position, Foster worked at USGS from 2008 to 2012, gaining four years of experience in the same capacity. This extensive tenure at USGS has allowed Foster to contribute significantly to various hydrological projects and initiatives.
Education and Expertise
Linzy Foster holds a Master of Science in Civil Engineering from Auburn University, where studies were completed from 2005 to 2008. Foster also earned a Bachelor of Arts in Mathematics from Maryville College, studying from 1997 to 2000. Foster specializes in computational hydrology, focusing on groundwater and contaminant transport. Additional expertise includes density-dependent flow modeling and inverse problem theory, as well as skills in numerical linear algebra and uncertainty analysis.
Background
Linzy Foster's educational background includes a strong foundation in mathematics and civil engineering. The transition from a Bachelor’s degree in Mathematics to a Master’s in Civil Engineering demonstrates a commitment to applying mathematical principles to engineering challenges. Foster's career has been dedicated to the field of hydrology, particularly within the framework of the U.S. Geological Survey.
Achievements
Throughout Linzy Foster's career at the U.S. Geological Survey, significant contributions have been made in the areas of groundwater management and contaminant transport. Foster's work in computational hydrology has involved advanced modeling techniques and analytical methods, enhancing the understanding of hydrological processes. The application of expertise in density-dependent flow modeling and uncertainty analysis has further supported the objectives of USGS in addressing water resource challenges.