Theodore B Barnhart
Biography
Theo received his PhD in geography from the University of Colorado in 2018 and studied how changes in snowmelt and land cover impacted the partitioning of precipitation between runoff and evapotranspiration. Theo works to improve hydrologic predictions using process-based hydrologic modeling and data-driven techniques. He is particularly interested in furthering our understanding of mountain and high-latitude hydrology and the distribution and variability of the mountain snowpack. To accomplish this, Theo uses hydrologic models, water balance analyses, and remote sensing.
Education:
PhD: Geography, 2018, The University of Colorado, Boulder, CO. Dissertation: The Response of Streamflow and Evapotranspiration to Changes in Snowmelt Across the Western United States.
MS: Geology, 2013, Idaho State University, Pocatello, ID. Thesis: Morphodynamics of the Selawik Retrogressive Thaw Slump, Northwest Alaska.
BA: Geology-Environmental Studies, cum laude, 2010, Whitman College, Walla Walla, WA. Thesis: Glaciomarine Sediment Flux and Transportation Mechanisms, Kronebreen/Kongsvegan, Kongsfjorden, Svalbard.
Please see his Google Scholar page for a list of peer-reviewed publications.
Science and Products
Flow-Conditioned Parameter Grids
Flow-Conditioned Parameter Grids (FCPGs) are a way of storing the upstream average of datasets, such as precipitation or land cover type, for all points on the landscape.
Geospatial Research and Development to Understand Hydrologic Processes
All natural phenomena have a spatial component. Remote sensing, GIS, and geostatistical methods can be used to evaluate the spatial components of hydrologic phenomena and understand characteristics, such as water quality, streamflow, and hydraulics.
National Hydrologic Model Alaska Domain parameter database, version 1
This data release contains input data for hydrologic simulations of the Alaska Domain application of the U.S. Geological Survey (USGS) Precipitation Runoff Modelling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The NHM Alaska Domain parameter database consists of 114 parameter files in ASCII format (CSV), two
Geospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
This metadata record documents a geospatial dataset for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) used to drive the National Hydrologic Model (NHM). The Alaska Geospatial Fabric v1 is the spatial representation of the hydrologic response units (HRUs) used for the PRMS NHM Alaska domain. These HRUs were generated using the twelve-digit Hydrologic Unit Code
Data to Estimate Water Use Associated with Continuous Oil and Gas Development, Williston Basin, United States, 1980-2017
This U.S. Geological Survey (USGS) Data Release provides data to estimate water use associated with continuous oil and gas development in the Williston Basin during 1980-2017. Data included: 1. Data records from the national hydraulic fracturing chemical registry, FracFocus, including the state, county, latitude and longitude of each well, and the year and volume of water used for...
Estimates of water use associated with continuous oil and gas development in the Williston Basin, North Dakota and Montana, 2007–17
This study of water use associated with development of continuous oil and gas resources in the Williston Basin is intended to provide a preliminary model-based analysis of water use in major regions of production of continuous oil and gas resources in the United States. Direct, indirect, and ancillary water use associated with development of...
McShane, Ryan R.; Barnhart, Theodore B.; Valder, Joshua F.; Haines, Seth S.; Macek-Rowland, Kathleen M. ; Carter, Janet M.; Delzer, Gregory C.; Thamke, Joanna N.Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of subgrid or subwatershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey...
Sexstone, Graham A.; Driscoll, Jessica M.; Hay, Lauren; Hammond, John; Barnhart, Theodore B.Analytical framework to estimate water use associated with continuous oil and gas development
An analytical framework was designed to estimate water use associated with continuous oil and gas (COG) development in support of the U.S. Geological Survey Water Availability and Use Science Program. This framework was developed to better understand the relation between the production of COG resources for energy and the amount of water needed to...
Valder, Joshua F.; McShane, Ryan R.; Barnhart, Theodore B.; Wheeling, Spencer L.; Carter, Janet M.; Macek-Rowland, Kathleen M. ; Delzer, Gregory C.; Thamke, Joanna N.Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development
As the demand for energy increases in the United States, so does the demand for water used to produce many forms of that energy. Technological advances, limited access to conventional oil and gas accumulations, and the rise of oil and gas prices resulted in increased development of unconventional oil and gas (UOG) accumulations. Unconventional oil...
Valder, Joshua F.; McShane, Ryan R.; Barnhart, Theodore B.; Sando, Roy; Carter, Janet M.; Lundgren, Robert F.Pre-USGS Publications
Flow-Conditioned Parameter Grid Tools
The Flow-Conditioned Parameter Grid (FCPG) Tools are a Python 3 library to make FCPGs for either two-digit Hydrologic Unit Code (HUC2) regions, four-digit Hydrologic Unit Code (HUC4) regions, or other geospatial tiling schemes. These tools can be used in a Linux-based high performance computing (HPC) environment or locally on your system.
StreamStats Data Preparation Tools, version 4
A Python package to pre-process and hydro-enforce digital elevation models using hydrography features for use in the U.S. Geological Survey (USGS) StreamStats project.