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Katherine Barnhart

Katy Barnhart is a Research Civil Engineer in the Landslide Hazards program.  

Katy does research on the mechanisms and impacts of landslide runout, primarily using numerical simulation. Her current work focuses on postfire debris flows and landslide tsunamis. 

Professional Experience

  • 2020-present: Research Civil Engineer, Landslide Hazards Program, Geologic Hazards Science Center 

  • 2020-2021: Mendenhall Postdoctoral Fellow 

  • 2018-2020: National Science Foundation Postdoctoral Fellow, University of Colorado at Boulder, Cooperative Institute for Research in the Environment and Department of Geological Sciences

  • 2016-2018: Postdoctoral Fellow, University of Colorado, Cooperative Institute for Research in the Environment and Department of Geological Sciences

  • 2015-2016: Postdoctoral Fellow, Annenberg Public Policy Center, University of Pennsylvania 

Education and Certifications

  • University of Colorado, Ph.D., 2015, Geological Sciences

  • University of Colorado, M.S., 2010, Geological Sciences

  • Princeton University, B.S.E., 2008, Civil and Environmental Engineering

Honors and Awards

  • CSDMS Terrestrial Working Group Member Spotlight Award, 2020

  • USGS Mendenhall Fellowship, 2020

  • NSF-EAR Postdoctoral Fellowship, 2017

  • NASA Earth and Space Science Fellowship, 2012-2015

  • NSF Graduate Research Fellowship Honorable Mention, 2010

  • W. Taylor Thom Jr. Prize, Princeton Department of Civil Engineering, 2008

  • Arthur F. Buddington Award, Princeton Department of Geological Sciences, 2008

Science and Products

Filter Total Items: 16

Rock mass quality and structural geology observations in Prince William Sound, Alaska (2022) Rock mass quality and structural geology observations in Prince William Sound, Alaska (2022)

Multiple subaerial landslides adjacent to Prince William Sound, Alaska (for example, Dai and others, 2020; Higman and others, 2023; Schaefer and others, 2024) pose a threat to the public because of their potential to generate ocean waves (Barnhart and others, 2021, 2022; Dai and others, 2020) that could affect towns and marine activities. One bedrock landslide on the west side of Barry...
By
Natural Hazards Mission Area, Landslide Hazards Program

Hypothetical landslide failure extents for hazard assessment, Barry Arm, western Prince William Sound, Alaska Hypothetical landslide failure extents for hazard assessment, Barry Arm, western Prince William Sound, Alaska

This data release contains extent shapefiles for 16 hypothetical slope failure scenarios for a landslide complex at Barry Arm, western Prince William Sound, Alaska. The landslide is likely active due to debuttressing from the retreat of Barry Glacier (Dai and others, 2020) and sits above Barry Arm, posing a tsunami risk in the event of slope failure (Barnhart and others, 2021). Since...
By
Geologic Hazards Science Center

Merged topography and bathymetry, western Prince William Sound Merged topography and bathymetry, western Prince William Sound

This work integrated multiple topographic and bathymetric data sources to generate a merged topobathymetric map of western Prince William Sound. We converted all data sources to NAD 83 UTM Zone 6 N and mean higher high water (MHHW) before compiling. In Barry Arm, north of Port Wells, we used a digital terrain model (DTM) derived from subaerial light detection and ranging (lidar) data...
By
Geologic Hazards Science Center

digger: A python package for D-Claw model inputs digger: A python package for D-Claw model inputs

Digger is a python package that provides a number of pre- and post-processing tools for working with the D-Claw model.
By
Landslide Hazards Program

Select structure observations, model results, and model input parameters for debris-flow runout model simulations of the 9 January 2018 Montecito debris-flow runout event Select structure observations, model results, and model input parameters for debris-flow runout model simulations of the 9 January 2018 Montecito debris-flow runout event

This dataset contains three comma separated value files that represent a combination of previously published structure observations and select model results at the location of each structure centroid from a separate previously published simulation study. -"buildings.csv" represents the merging of structure damage observations published in Kean et al. (2019) and structure locations from...
By
Geologic Hazards Science Center

Tadpole Fire Debris Flow and Wood Collector Measurements May 2021 Tadpole Fire Debris Flow and Wood Collector Measurements May 2021

This is a dataset of location and photo data for the debris flow deposits measured in the Tadpole Wildfire. The data were collected using the ArcGIS Collector application by multiple individuals. The original data are stored in a geodatabase here, and the geodatabase has the following fields: Latitude (decimal degrees), Longitude (decimal degrees), Elevation (meters), GlobalID (a unique...
By
Geologic Hazards Science Center
No results found.
Filter Total Items: 27

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and...
Authors
Jacob Bryson Woodard, Sean Richard LaHusen, Benjamin B. Mirus, Katherine R. Barnhart
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned...
Authors
A. B. Prescott, L. A. McGuire, K.-S. Jun, Katherine R. Barnhart, N. S. Oakley
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center

Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA

As wildfire increases in the western United States, so do postfire debris-flow hazards. The U.S. Geological Survey (USGS) has developed two separate models to estimate (1) rainfall intensity thresholds for postfire debris-flow initiation and (2) debris-flow volumes. However, the information necessary to test the accuracy of these models is seldom available. Here, we studied how well...
Authors
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgeway, Brendan Murphy
By
Geologic Hazards Science Center

Catchment coevolution and the geomorphic origins of variable source area hydrology Catchment coevolution and the geomorphic origins of variable source area hydrology

Features of landscape morphology—including slope, curvature, and drainage dissection—are important controls on runoff generation in upland landscapes. Over long timescales, runoff plays an essential role in shaping these same features through surface erosion. This feedback between erosion and runoff generation suggests that modeling long-term landscape evolution together with dynamic...
Authors
David G Litwin, Gregory E. Tucker, Katherine R. Barnhart, Ciaran Harman
By
Geologic Hazards Science Center

Evaluation of debris-flow building damage forecasts Evaluation of debris-flow building damage forecasts

Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building...
Authors
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, Jason W. Kean
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center, Supplemental Appropriations for Disaster Recovery Activities

Unlearning Racism in Geoscience (URGE): Summary of U.S. Geological Survey URGE pod deliverables Unlearning Racism in Geoscience (URGE): Summary of U.S. Geological Survey URGE pod deliverables

The U.S. Geological Survey (USGS) is in a unique position to be a leader in diversity, equity, inclusion, and accessibility in the Earth sciences. As one of the largest geoscience employers, the USGS wields significant community influence and has a responsibility to adopt and implement robust, unbiased policies so that the science it is charged to deliver is better connected to the...
Authors
Matthew C. Morriss, Eleanour Snow, Jennifer L. Miselis, William F. Waite, Katherine R. Barnhart, Andria P. Ellis, Liv M. Herdman, Seth C. Moran, Annie L. Putman, Nadine G. Reitman, Wendy K. Stovall, Meagan J. Eagle, Stephen C. Phillips
By
St. Petersburg Coastal and Marine Science Center

Non-USGS Publications**

Wickert, A.D., Barnhart, K.R., Armstrong, W.H., Romero, M., Schulz, B., Ng, G.-H.C., Sandell, C.T., La Frenierre, J., Penprase, S.B., Van Wyk de Vries, M., and MacGregor, K.R., 2023, Automated ablation stakes to constrain temperature-index melt models: Annals of Glaciology, v. 64, no. 92, p. 425–438, https://doi.org/10.1017/aog.2024.21.
Gasparini, N.M., Forte, A.M., and Barnhart, K.R., 2024, Short Communication: Numerically simulated time to steady state is not a reliable measure of landscape response time: Earth Surface Dynamics, v. 12, no. 6, p. 1227–1242, https://doi.org/10.5194/esurf-12-1227-2024.
Nudurupati, S.S., Istanbulluoglu, E., Tucker, G.E., Gasparini, N.M., Hobley, D.E.J., Hutton, E.W.H., Barnhart, K.R., and Adams, J.M., On transient semi-arid ecosystem dynamics using Landlab: Vegetation shifts, topographic refugia, and response to climate. Water Resources Research, 59, e2021WR031179. https://doi.org/10.1029/2021WR031179.
Litwin, David G, Tucker, G.E., Barnhart, K.R., and Harman, C.J., Reply to comment by Anand et al. on ‘Groundwater affects the geomorphic and hydrologic properties of coevolved landscapes’: Journal of Geophysical Research—Earth Surface, 127, e2022JF006722. https://doi.org/10.1029/2022JF006722.
Litwin, D.G., Tucker, G.E., Barnhart, K.R., and Harman, C.J., 2022, Groundwater Affects the Geomorphic and Hydrologic Properties of Coevolved Landscapes: Journal of Geophysical Research: Earth Surface, v. 127, no. 1, p. e2021JF006239, doi: 10.1029/2021JF006239.
Tucker, G.E., Hutton, E.W.H., Piper, M.D., Campforts, B., Gan, T., Barnhart, K.R., Kettner, A.J., Overeem, I., Peckham, S.D., McCready, L., and Syvitski, J., 2022, Community Surface Dynamics Modeling System: a community platform for numerical modeling of Earth surface processes: Geoscientific Model Development, v. 15, no. 4, p. 1413–1439, doi: 10.5194/gmd-15-1413-2022.
Wiens, A., Kleiber, W., Nychka, D., and Barnhart, K. R. “Nonrigid Registration Using Gaussian Processes
and Local Likelihood Estimation”. In: Mathematical Geosciences (2021). DOI: 10.1007/s11004-
020-09917-7.
Anderson, S.P., Kelly, P.J., Hoffman, N., Barnhart, K., Befus, K. and Ouimet, W. (2021). Is This Steady State? Weathering and Critical Zone Architecture in Gordon Gulch, Colorado Front Range. In Hydrogeology, Chemical Weathering, and Soil Formation (eds A. Hunt, M. Egli and B. Faybishenko). https://doi.org/10.1002/9781119563952.ch13
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M. W. Rossi, and M. C. Hill. “Projections of landscape evolution on a 10,000 year timescale with assessment and partitioning of uncertainty sources”. Journal of Geophysical Research: Earth Surface (2020), 2020JF005795. https://doi.org/10.1029/2020JF005795.
A. M. Pfeiffer, K. R. Barnhart, J. A. Czuba, and E. W. H. Hutton. “NetworkSediment-Transporter: A Landlab component for bed material transport through river networks”. Journal of Open Source Software 5.53 (2020), p. 2341. https://doi.org/10.21105/joss.02341.
Barnhart, K. R., Hutton, E. W. H., Tucker, G. E., Gasparini, N. M., Istanbulluoglu, E., Hobley, D. E. J., Lyons, N. J., Mouchene, M., Nudurupati, S. S., Adams, J. M., and Bandaragoda, C.: Short communication: Landlab v2.0: a software package for Earth surface dynamics, Earth Surf. Dynam., 8, 379–397, https://doi.org/10.5194/esurf-8-379-2020, 2020.
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M. W. Rossi, and M. C. Hill. “Inverting topography for landscape evolution model process representation: Part 1, conceptualization and sensitivity analysis”. Journal of Geophysical Research: Earth Surface (2020), e2018JF004961. https://doi.org/10.1029/2018JF004961.
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M. W. Rossi, and M. C. Hill. “Inverting topography for landscape evolution model process representation: Part 2, calibration and validation”. Journal of Geophysical Research: Earth Surface (2020), e2018JF004963. https://doi.org/10.1029/2018JF004963.
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M.W. Rossi, and M. C. Hill. “Inverting topography for landscape evolution model process representation: Part 3, Determining parameter ranges for select mature geomorphic transport laws and connecting changes in fluvial erodibility to changes in climate”. Journal of Geophysical Research: Earth Surface (2020), e2019JF005287. https://doi.org/10.1029/2019JF005287.
D. Litwin, G. Tucker, K. R. Barnhart, and C. Harman. “GroundwaterDupuitPercolator: A Landlab component for groundwater flow”. Journal of Open Source Software 5.46 (2020), 1935. https://doi.org/10.21105/joss.01935.
K. R. Barnhart, R. C. Glade, C. M. Shobe, and G. E. Tucker. “Terrainbento 1.0: a Python package for multi-model analysis in long-term drainage basin evolution”. Geoscientific Model Development 12.4 (2019), pp. 1267–1297. https://doi.org/10.5194/gmd-12-1267-2019.
K. R. Barnhart, E.W. H. Hutton, and G. E. Tucker. “umami: A Python package for Earth surface dynamics objective function construction”. Journal of Open Source Software 4.42 (2019). https://doi.org/10.21105/joss.01776.
C. J. Bandaragoda, A. Castronova, E. Istanbulluoglu, R. Strauch, S. S. Nudurupati, J. Phuong, J. M. Adams, N. M. Gasparini, K. R. Barnhart, E. Hutton, D. E. J. Hobley, N. J. Lyons, G. E. Tucker, D. G. Tarboton, R. Idaszak, and S. Wang. “Enabling collaborative numerical Modeling in Earth sciences using Knowledge Infrastructure”. Environmental Modelling and Software (2019). https://doi.org/10.1016/j.envsoft.2019.03.020.
A. Wiens, W. Kleiber, K. R. Barnhart, and D. Sain. “Surface Estimation for Multiple Misaligned Point Sets”. Mathematical Geosciences 39.2 (Apr. 2019), pp. 1–16. https://doi.org/10.1007/s11004-019-09802-y.
K. R. Barnhart, E. Hutton, N. Gasparini, and G. Tucker. “Lithology: A Landlab submodule for spatially variable rock properties”. Journal of Open Source Software 3.30 (2018), pp. 979–2. https://doi.org/10.21105/joss.00979.
M. Bendixen, L. L. Iversen, A. A. Bjork, B. Elberling, A.Westergaard-Nielsen, I. Overeem, K. R. Barnhart, S. A. Khan, J. E. Box, J. Abermann, K. Langley, and A. Kroon. “Delta progradation in Greenland driven by increasing glacial mass loss”. Nature 550.7674 (2017), pp. 101–104. https://doi.org/10.1038/nature23873.
C. M. Shobe, G. E. Tucker, and K. R. Barnhart. “The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution”. Geoscientific Model Development 10.12 (2017), pp. 4577–4604. https://doi.org/10.5194/gmd-10-4577-2017.
K. R. Barnhart, C. R. Miller, I. Overeem, and J. E. Kay. “Mapping the future expansion of Arctic open water”. Nature Climate Change (2015). https://doi.org/10.1038/nclimate2848.
R. C. Mahon, J. B. Shaw, K. R. Barnhart, D. E. Hobley, and B. McElroy. “Quantifying the stratigraphic completeness of delta shoreline trajectories”. Journal of Geophysical Research-Earth Surface 120.5 (2015), pp. 799–817. https://doi.org/10.1002/2014JF003298.
K. R. Barnhart, R. S. Anderson, I. Overeem, C. Wobus, G. D. Clow, and F. E. Urban. “Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast”. Journal of Geophysical Research-Earth Surface 119.5 (2014), pp. 1155–1179. https://doi.org/10.1002/2013JF002845.
K. R. Barnhart, I. Overeem, and R. S. Anderson. “The effect of changing sea ice on the physical vulnerability of Arctic coasts”. The Cryosphere 8 (2014), pp. 1777–1799. https://doi.org/10.5194/tc-8-1777-2014.
K. R. Barnhart, K. H. Mahan, T. J. Blackburn, S. A. Bowring, and F. O. Dudas. “Deep crustal xenoliths from central Montana, USA: Implications for the timing and mechanisms of high-velocity lower crust formation”. Geosphere (2012). https://doi.org/10.1130/GES00765.1.
K. R. Barnhart, P. J. Walsh, L. S. Hollister, C. G. Daniel, and C. Andronicos. “Decompression during Late Proterozoic Al2SiO5 Triple-Point Metamorphism at Cerro Colorado, New Mexico”. The Journal of Geology (2012). https://doi.org/10.1086/665793.
T. J. Blackburn, S. A. Bowring, J. T. Perron, K. H. Mahan, F. O. Dudas, and K. R. Barnhart. “An Exhumation History of Continents over Billion-Year Time Scales”. Science 335.6064 (2012), pp. 73–76. https://doi.org/10.1126/science.1213496.

**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.

digger: A python package for D-Claw model inputs digger: A python package for D-Claw model inputs

Digger is a python package that provides a number of pre- and post-processing tools for working with the D-Claw model.
By
Landslide Hazards Program

Science and Products

Filter Total Items: 16

Rock mass quality and structural geology observations in Prince William Sound, Alaska (2022) Rock mass quality and structural geology observations in Prince William Sound, Alaska (2022)

Multiple subaerial landslides adjacent to Prince William Sound, Alaska (for example, Dai and others, 2020; Higman and others, 2023; Schaefer and others, 2024) pose a threat to the public because of their potential to generate ocean waves (Barnhart and others, 2021, 2022; Dai and others, 2020) that could affect towns and marine activities. One bedrock landslide on the west side of Barry...
By
Natural Hazards Mission Area, Landslide Hazards Program

Hypothetical landslide failure extents for hazard assessment, Barry Arm, western Prince William Sound, Alaska Hypothetical landslide failure extents for hazard assessment, Barry Arm, western Prince William Sound, Alaska

This data release contains extent shapefiles for 16 hypothetical slope failure scenarios for a landslide complex at Barry Arm, western Prince William Sound, Alaska. The landslide is likely active due to debuttressing from the retreat of Barry Glacier (Dai and others, 2020) and sits above Barry Arm, posing a tsunami risk in the event of slope failure (Barnhart and others, 2021). Since...
By
Geologic Hazards Science Center

Merged topography and bathymetry, western Prince William Sound Merged topography and bathymetry, western Prince William Sound

This work integrated multiple topographic and bathymetric data sources to generate a merged topobathymetric map of western Prince William Sound. We converted all data sources to NAD 83 UTM Zone 6 N and mean higher high water (MHHW) before compiling. In Barry Arm, north of Port Wells, we used a digital terrain model (DTM) derived from subaerial light detection and ranging (lidar) data...
By
Geologic Hazards Science Center

digger: A python package for D-Claw model inputs digger: A python package for D-Claw model inputs

Digger is a python package that provides a number of pre- and post-processing tools for working with the D-Claw model.
By
Landslide Hazards Program

Select structure observations, model results, and model input parameters for debris-flow runout model simulations of the 9 January 2018 Montecito debris-flow runout event Select structure observations, model results, and model input parameters for debris-flow runout model simulations of the 9 January 2018 Montecito debris-flow runout event

This dataset contains three comma separated value files that represent a combination of previously published structure observations and select model results at the location of each structure centroid from a separate previously published simulation study. -"buildings.csv" represents the merging of structure damage observations published in Kean et al. (2019) and structure locations from...
By
Geologic Hazards Science Center

Tadpole Fire Debris Flow and Wood Collector Measurements May 2021 Tadpole Fire Debris Flow and Wood Collector Measurements May 2021

This is a dataset of location and photo data for the debris flow deposits measured in the Tadpole Wildfire. The data were collected using the ArcGIS Collector application by multiple individuals. The original data are stored in a geodatabase here, and the geodatabase has the following fields: Latitude (decimal degrees), Longitude (decimal degrees), Elevation (meters), GlobalID (a unique...
By
Geologic Hazards Science Center
No results found.
Filter Total Items: 27

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and...
Authors
Jacob Bryson Woodard, Sean Richard LaHusen, Benjamin B. Mirus, Katherine R. Barnhart
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned...
Authors
A. B. Prescott, L. A. McGuire, K.-S. Jun, Katherine R. Barnhart, N. S. Oakley
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center

Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA

As wildfire increases in the western United States, so do postfire debris-flow hazards. The U.S. Geological Survey (USGS) has developed two separate models to estimate (1) rainfall intensity thresholds for postfire debris-flow initiation and (2) debris-flow volumes. However, the information necessary to test the accuracy of these models is seldom available. Here, we studied how well...
Authors
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgeway, Brendan Murphy
By
Geologic Hazards Science Center

Catchment coevolution and the geomorphic origins of variable source area hydrology Catchment coevolution and the geomorphic origins of variable source area hydrology

Features of landscape morphology—including slope, curvature, and drainage dissection—are important controls on runoff generation in upland landscapes. Over long timescales, runoff plays an essential role in shaping these same features through surface erosion. This feedback between erosion and runoff generation suggests that modeling long-term landscape evolution together with dynamic...
Authors
David G Litwin, Gregory E. Tucker, Katherine R. Barnhart, Ciaran Harman
By
Geologic Hazards Science Center

Evaluation of debris-flow building damage forecasts Evaluation of debris-flow building damage forecasts

Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building...
Authors
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, Jason W. Kean
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center, Supplemental Appropriations for Disaster Recovery Activities

Unlearning Racism in Geoscience (URGE): Summary of U.S. Geological Survey URGE pod deliverables Unlearning Racism in Geoscience (URGE): Summary of U.S. Geological Survey URGE pod deliverables

The U.S. Geological Survey (USGS) is in a unique position to be a leader in diversity, equity, inclusion, and accessibility in the Earth sciences. As one of the largest geoscience employers, the USGS wields significant community influence and has a responsibility to adopt and implement robust, unbiased policies so that the science it is charged to deliver is better connected to the...
Authors
Matthew C. Morriss, Eleanour Snow, Jennifer L. Miselis, William F. Waite, Katherine R. Barnhart, Andria P. Ellis, Liv M. Herdman, Seth C. Moran, Annie L. Putman, Nadine G. Reitman, Wendy K. Stovall, Meagan J. Eagle, Stephen C. Phillips
By
St. Petersburg Coastal and Marine Science Center

Non-USGS Publications**

Wickert, A.D., Barnhart, K.R., Armstrong, W.H., Romero, M., Schulz, B., Ng, G.-H.C., Sandell, C.T., La Frenierre, J., Penprase, S.B., Van Wyk de Vries, M., and MacGregor, K.R., 2023, Automated ablation stakes to constrain temperature-index melt models: Annals of Glaciology, v. 64, no. 92, p. 425–438, https://doi.org/10.1017/aog.2024.21.
Gasparini, N.M., Forte, A.M., and Barnhart, K.R., 2024, Short Communication: Numerically simulated time to steady state is not a reliable measure of landscape response time: Earth Surface Dynamics, v. 12, no. 6, p. 1227–1242, https://doi.org/10.5194/esurf-12-1227-2024.
Nudurupati, S.S., Istanbulluoglu, E., Tucker, G.E., Gasparini, N.M., Hobley, D.E.J., Hutton, E.W.H., Barnhart, K.R., and Adams, J.M., On transient semi-arid ecosystem dynamics using Landlab: Vegetation shifts, topographic refugia, and response to climate. Water Resources Research, 59, e2021WR031179. https://doi.org/10.1029/2021WR031179.
Litwin, David G, Tucker, G.E., Barnhart, K.R., and Harman, C.J., Reply to comment by Anand et al. on ‘Groundwater affects the geomorphic and hydrologic properties of coevolved landscapes’: Journal of Geophysical Research—Earth Surface, 127, e2022JF006722. https://doi.org/10.1029/2022JF006722.
Litwin, D.G., Tucker, G.E., Barnhart, K.R., and Harman, C.J., 2022, Groundwater Affects the Geomorphic and Hydrologic Properties of Coevolved Landscapes: Journal of Geophysical Research: Earth Surface, v. 127, no. 1, p. e2021JF006239, doi: 10.1029/2021JF006239.
Tucker, G.E., Hutton, E.W.H., Piper, M.D., Campforts, B., Gan, T., Barnhart, K.R., Kettner, A.J., Overeem, I., Peckham, S.D., McCready, L., and Syvitski, J., 2022, Community Surface Dynamics Modeling System: a community platform for numerical modeling of Earth surface processes: Geoscientific Model Development, v. 15, no. 4, p. 1413–1439, doi: 10.5194/gmd-15-1413-2022.
Wiens, A., Kleiber, W., Nychka, D., and Barnhart, K. R. “Nonrigid Registration Using Gaussian Processes
and Local Likelihood Estimation”. In: Mathematical Geosciences (2021). DOI: 10.1007/s11004-
020-09917-7.
Anderson, S.P., Kelly, P.J., Hoffman, N., Barnhart, K., Befus, K. and Ouimet, W. (2021). Is This Steady State? Weathering and Critical Zone Architecture in Gordon Gulch, Colorado Front Range. In Hydrogeology, Chemical Weathering, and Soil Formation (eds A. Hunt, M. Egli and B. Faybishenko). https://doi.org/10.1002/9781119563952.ch13
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M. W. Rossi, and M. C. Hill. “Projections of landscape evolution on a 10,000 year timescale with assessment and partitioning of uncertainty sources”. Journal of Geophysical Research: Earth Surface (2020), 2020JF005795. https://doi.org/10.1029/2020JF005795.
A. M. Pfeiffer, K. R. Barnhart, J. A. Czuba, and E. W. H. Hutton. “NetworkSediment-Transporter: A Landlab component for bed material transport through river networks”. Journal of Open Source Software 5.53 (2020), p. 2341. https://doi.org/10.21105/joss.02341.
Barnhart, K. R., Hutton, E. W. H., Tucker, G. E., Gasparini, N. M., Istanbulluoglu, E., Hobley, D. E. J., Lyons, N. J., Mouchene, M., Nudurupati, S. S., Adams, J. M., and Bandaragoda, C.: Short communication: Landlab v2.0: a software package for Earth surface dynamics, Earth Surf. Dynam., 8, 379–397, https://doi.org/10.5194/esurf-8-379-2020, 2020.
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M. W. Rossi, and M. C. Hill. “Inverting topography for landscape evolution model process representation: Part 1, conceptualization and sensitivity analysis”. Journal of Geophysical Research: Earth Surface (2020), e2018JF004961. https://doi.org/10.1029/2018JF004961.
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M. W. Rossi, and M. C. Hill. “Inverting topography for landscape evolution model process representation: Part 2, calibration and validation”. Journal of Geophysical Research: Earth Surface (2020), e2018JF004963. https://doi.org/10.1029/2018JF004963.
K. R. Barnhart, G. E. Tucker, S. Doty, C. M. Shobe, R. C. Glade, M.W. Rossi, and M. C. Hill. “Inverting topography for landscape evolution model process representation: Part 3, Determining parameter ranges for select mature geomorphic transport laws and connecting changes in fluvial erodibility to changes in climate”. Journal of Geophysical Research: Earth Surface (2020), e2019JF005287. https://doi.org/10.1029/2019JF005287.
D. Litwin, G. Tucker, K. R. Barnhart, and C. Harman. “GroundwaterDupuitPercolator: A Landlab component for groundwater flow”. Journal of Open Source Software 5.46 (2020), 1935. https://doi.org/10.21105/joss.01935.
K. R. Barnhart, R. C. Glade, C. M. Shobe, and G. E. Tucker. “Terrainbento 1.0: a Python package for multi-model analysis in long-term drainage basin evolution”. Geoscientific Model Development 12.4 (2019), pp. 1267–1297. https://doi.org/10.5194/gmd-12-1267-2019.
K. R. Barnhart, E.W. H. Hutton, and G. E. Tucker. “umami: A Python package for Earth surface dynamics objective function construction”. Journal of Open Source Software 4.42 (2019). https://doi.org/10.21105/joss.01776.
C. J. Bandaragoda, A. Castronova, E. Istanbulluoglu, R. Strauch, S. S. Nudurupati, J. Phuong, J. M. Adams, N. M. Gasparini, K. R. Barnhart, E. Hutton, D. E. J. Hobley, N. J. Lyons, G. E. Tucker, D. G. Tarboton, R. Idaszak, and S. Wang. “Enabling collaborative numerical Modeling in Earth sciences using Knowledge Infrastructure”. Environmental Modelling and Software (2019). https://doi.org/10.1016/j.envsoft.2019.03.020.
A. Wiens, W. Kleiber, K. R. Barnhart, and D. Sain. “Surface Estimation for Multiple Misaligned Point Sets”. Mathematical Geosciences 39.2 (Apr. 2019), pp. 1–16. https://doi.org/10.1007/s11004-019-09802-y.
K. R. Barnhart, E. Hutton, N. Gasparini, and G. Tucker. “Lithology: A Landlab submodule for spatially variable rock properties”. Journal of Open Source Software 3.30 (2018), pp. 979–2. https://doi.org/10.21105/joss.00979.
M. Bendixen, L. L. Iversen, A. A. Bjork, B. Elberling, A.Westergaard-Nielsen, I. Overeem, K. R. Barnhart, S. A. Khan, J. E. Box, J. Abermann, K. Langley, and A. Kroon. “Delta progradation in Greenland driven by increasing glacial mass loss”. Nature 550.7674 (2017), pp. 101–104. https://doi.org/10.1038/nature23873.
C. M. Shobe, G. E. Tucker, and K. R. Barnhart. “The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution”. Geoscientific Model Development 10.12 (2017), pp. 4577–4604. https://doi.org/10.5194/gmd-10-4577-2017.
K. R. Barnhart, C. R. Miller, I. Overeem, and J. E. Kay. “Mapping the future expansion of Arctic open water”. Nature Climate Change (2015). https://doi.org/10.1038/nclimate2848.
R. C. Mahon, J. B. Shaw, K. R. Barnhart, D. E. Hobley, and B. McElroy. “Quantifying the stratigraphic completeness of delta shoreline trajectories”. Journal of Geophysical Research-Earth Surface 120.5 (2015), pp. 799–817. https://doi.org/10.1002/2014JF003298.
K. R. Barnhart, R. S. Anderson, I. Overeem, C. Wobus, G. D. Clow, and F. E. Urban. “Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast”. Journal of Geophysical Research-Earth Surface 119.5 (2014), pp. 1155–1179. https://doi.org/10.1002/2013JF002845.
K. R. Barnhart, I. Overeem, and R. S. Anderson. “The effect of changing sea ice on the physical vulnerability of Arctic coasts”. The Cryosphere 8 (2014), pp. 1777–1799. https://doi.org/10.5194/tc-8-1777-2014.
K. R. Barnhart, K. H. Mahan, T. J. Blackburn, S. A. Bowring, and F. O. Dudas. “Deep crustal xenoliths from central Montana, USA: Implications for the timing and mechanisms of high-velocity lower crust formation”. Geosphere (2012). https://doi.org/10.1130/GES00765.1.
K. R. Barnhart, P. J. Walsh, L. S. Hollister, C. G. Daniel, and C. Andronicos. “Decompression during Late Proterozoic Al2SiO5 Triple-Point Metamorphism at Cerro Colorado, New Mexico”. The Journal of Geology (2012). https://doi.org/10.1086/665793.
T. J. Blackburn, S. A. Bowring, J. T. Perron, K. H. Mahan, F. O. Dudas, and K. R. Barnhart. “An Exhumation History of Continents over Billion-Year Time Scales”. Science 335.6064 (2012), pp. 73–76. https://doi.org/10.1126/science.1213496.

**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.

digger: A python package for D-Claw model inputs digger: A python package for D-Claw model inputs

Digger is a python package that provides a number of pre- and post-processing tools for working with the D-Claw model.
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Landslide Hazards Program
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