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: 21
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 translational slides
Authors
Jacob Bryson Woodard, Sean Richard LaHusen, Benjamin B. Mirus, Katherine R. Barnhart
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 areas based o
Authors
A. B. Prescott, L. A. McGuire, K.-S. Jun, Katherine R. Barnhart, N. S. Oakley
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 these models p
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
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 runoff genera
Authors
David G Litwin, Gregory E. Tucker, Katherine R. Barnhart, Ciaran Harman
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 damage fore
Authors
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, Jason W. Kean
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 diverse communi
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
Satellite Interferometry Landslide Detection and Preliminary Tsunamigenic Plausibility Assessment in Prince William Sound, Southcentral Alaska
Regional mapping of actively deforming landslides, including measurements of landslide velocity, is integral for hazard assessments in paraglacial environments. These inventories are also critical for describing the potential impacts that the warming effects of climate change have on slope instability in mountainous and cryospheric terrain. The objective of this study is to identify slow-moving la
Authors
Lauren N. Schaefer, Jinwook Kim, Dennis M. Staley, Zhong Lu, Katherine R. Barnhart
Steady-state forms of channel profiles shaped by debris flow and fluvial processes
Debris flows regularly traverse bedrock channels that dissect steep landscapes, but our understanding of bedrock erosion by debris flows and their impact on steepland morphology is still rudimentary. Quantitative models of steep bedrock channel networks are based on geomorphic transport laws designed to represent erosion by water-dominated flows. To quantify the impact of debris flow erosion on st
Authors
Luke A. McGuire, Scott W. McCoy, Odin Marc, William Struble, Katherine R. Barnhart
Forecasting the inundation of postfire debris flows
In the semi-arid regions of the western United States, postfire debris flows are typically runoff
generated. The U.S. Geological Survey has been studying the mechanisms of postfire debris-flow initiation for multiple decades to generate operational models for forecasting the timing, location, and magnitude of postfire debris flows. Here we discuss challenges and progress for extending operational
Authors
Katherine R. Barnhart, Ryan P Jones, David L. George, Francis K. Rengers, Jason W. Kean
Runout model evaluation based on back-calculation of building damage
We evaluated the ability of three debris-flow runout models (RAMMS, FLO2D and D-Claw) to
predict the number of damaged buildings in simulations of the 9 January 2019 Montecito, California, debris-flow event. Observations of building damage after the event were combined with OpenStreetMap building footprints to construct a database of all potentially impacted buildings. At the estimated event volum
Authors
Katherine R. Barnhart, Jason W. Kean
Debris-flow process controls on steepland morphology in the San Gabriel Mountains, California
Steep landscapes evolve largely by debris flows, in addition to fluvial and hillslope processes. Abundant field observations document that debris flows incise valley bottoms and transport substantial sediment volumes, yet their contributions to steepland morphology remain uncertain. This has, in turn, limited the development of debris-flow incision rate formulations that produce morphology consist
Authors
William Struble, Luke A. McGuire, Scott W. McCoy, Katherine R. Barnhart, Odin Marc
The influence of large woody debris on post-wildfire debris flow sediment storage
Debris flows transport large quantities of water and granular material, such as sediment and wood, and this mixture can have devastating impacts on life and infrastructure. The proportion of large woody debris (LWD) incorporated into debris flows can be enhanced in forested areas recently burned by wildfire, because wood recruitment into channels accelerates in burned forests. In this study, we ex
Authors
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann Youberg, Daniel Cadol, Alexander Gorr, Olivia J. Hoch, Rebecca Beers, Jason W. Kean
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.
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.
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 discovery of
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 collected o
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 Open Stree
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 ID), Creat
Tadpole Fire Field Measurements following the 8 September 2020 Debris Flow, Gila National Forest, NM
This data release contains data summarizing observations within and adjacent to the Tadpole Fire, which burned from 6 June to 4 July 2020 in the Gila National Forest, NM. This monitoring data were focused on debris flows triggered on 8 September 2020 in four drainage basins (TAD1, TAD2, TAD3, and TAD4).
Rainfall data (1a_rain_geophones.csv) are provided in a comma-separated value (CSV) file. The
Simulated inundation extent and depth in Harriman Fjord and Barry Arm, western Prince William Sound, Alaska, resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska
Summary
This data release contains postprocessed model output from a simulation of hypothetical rapid motion of landslides, subsequent wave generation, and wave propagation. A simulated displacement wave was generated by rapid motion of unstable material into Barry Arm fjord. We consider the wave propagation in Harriman Fjord and Barry Arm, western Prince William Sound (area of interest and place
Simulated inundation extent and depth at Whittier, Alaska resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska
This data release contains postprocessed model output from simulations of hypothetical rapid motion of landslides, subsequent wave generation, and wave propagation. A modeled tsunami wave was generated by rapid motion of unstable material into Barry Arm Fjord. This wave propagated through Prince William Sound and then into Passage Canal east of Whittier. Here we consider only the largest wave-gene
Select model results from simulations of hypothetical rapid failures of landslides into Barry Arm, Prince William Sound, Alaska
This data release contains model output from simulations presented in the associated Open-File Report (Barnhart and others, 2021). In this report, we present model results from four simulations (scenarios C-290, NC-290, C-689, NC-689, Table 1) of hypothetical rapid movement of landslides into adjacent fjord water at Barry Arm, Alaska using the D-Claw model (George and Iverson, 2014; Iverson and Ge
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.
Science and Products
Filter Total Items: 21
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 translational slides
Authors
Jacob Bryson Woodard, Sean Richard LaHusen, Benjamin B. Mirus, Katherine R. Barnhart
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 areas based o
Authors
A. B. Prescott, L. A. McGuire, K.-S. Jun, Katherine R. Barnhart, N. S. Oakley
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 these models p
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
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 runoff genera
Authors
David G Litwin, Gregory E. Tucker, Katherine R. Barnhart, Ciaran Harman
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 damage fore
Authors
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, Jason W. Kean
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 diverse communi
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
Satellite Interferometry Landslide Detection and Preliminary Tsunamigenic Plausibility Assessment in Prince William Sound, Southcentral Alaska
Regional mapping of actively deforming landslides, including measurements of landslide velocity, is integral for hazard assessments in paraglacial environments. These inventories are also critical for describing the potential impacts that the warming effects of climate change have on slope instability in mountainous and cryospheric terrain. The objective of this study is to identify slow-moving la
Authors
Lauren N. Schaefer, Jinwook Kim, Dennis M. Staley, Zhong Lu, Katherine R. Barnhart
Steady-state forms of channel profiles shaped by debris flow and fluvial processes
Debris flows regularly traverse bedrock channels that dissect steep landscapes, but our understanding of bedrock erosion by debris flows and their impact on steepland morphology is still rudimentary. Quantitative models of steep bedrock channel networks are based on geomorphic transport laws designed to represent erosion by water-dominated flows. To quantify the impact of debris flow erosion on st
Authors
Luke A. McGuire, Scott W. McCoy, Odin Marc, William Struble, Katherine R. Barnhart
Forecasting the inundation of postfire debris flows
In the semi-arid regions of the western United States, postfire debris flows are typically runoff
generated. The U.S. Geological Survey has been studying the mechanisms of postfire debris-flow initiation for multiple decades to generate operational models for forecasting the timing, location, and magnitude of postfire debris flows. Here we discuss challenges and progress for extending operational
Authors
Katherine R. Barnhart, Ryan P Jones, David L. George, Francis K. Rengers, Jason W. Kean
Runout model evaluation based on back-calculation of building damage
We evaluated the ability of three debris-flow runout models (RAMMS, FLO2D and D-Claw) to
predict the number of damaged buildings in simulations of the 9 January 2019 Montecito, California, debris-flow event. Observations of building damage after the event were combined with OpenStreetMap building footprints to construct a database of all potentially impacted buildings. At the estimated event volum
Authors
Katherine R. Barnhart, Jason W. Kean
Debris-flow process controls on steepland morphology in the San Gabriel Mountains, California
Steep landscapes evolve largely by debris flows, in addition to fluvial and hillslope processes. Abundant field observations document that debris flows incise valley bottoms and transport substantial sediment volumes, yet their contributions to steepland morphology remain uncertain. This has, in turn, limited the development of debris-flow incision rate formulations that produce morphology consist
Authors
William Struble, Luke A. McGuire, Scott W. McCoy, Katherine R. Barnhart, Odin Marc
The influence of large woody debris on post-wildfire debris flow sediment storage
Debris flows transport large quantities of water and granular material, such as sediment and wood, and this mixture can have devastating impacts on life and infrastructure. The proportion of large woody debris (LWD) incorporated into debris flows can be enhanced in forested areas recently burned by wildfire, because wood recruitment into channels accelerates in burned forests. In this study, we ex
Authors
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann Youberg, Daniel Cadol, Alexander Gorr, Olivia J. Hoch, Rebecca Beers, Jason W. Kean
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.
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.
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 discovery of
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 collected o
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 Open Stree
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 ID), Creat
Tadpole Fire Field Measurements following the 8 September 2020 Debris Flow, Gila National Forest, NM
This data release contains data summarizing observations within and adjacent to the Tadpole Fire, which burned from 6 June to 4 July 2020 in the Gila National Forest, NM. This monitoring data were focused on debris flows triggered on 8 September 2020 in four drainage basins (TAD1, TAD2, TAD3, and TAD4).
Rainfall data (1a_rain_geophones.csv) are provided in a comma-separated value (CSV) file. The
Simulated inundation extent and depth in Harriman Fjord and Barry Arm, western Prince William Sound, Alaska, resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska
Summary
This data release contains postprocessed model output from a simulation of hypothetical rapid motion of landslides, subsequent wave generation, and wave propagation. A simulated displacement wave was generated by rapid motion of unstable material into Barry Arm fjord. We consider the wave propagation in Harriman Fjord and Barry Arm, western Prince William Sound (area of interest and place
Simulated inundation extent and depth at Whittier, Alaska resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska
This data release contains postprocessed model output from simulations of hypothetical rapid motion of landslides, subsequent wave generation, and wave propagation. A modeled tsunami wave was generated by rapid motion of unstable material into Barry Arm Fjord. This wave propagated through Prince William Sound and then into Passage Canal east of Whittier. Here we consider only the largest wave-gene
Select model results from simulations of hypothetical rapid failures of landslides into Barry Arm, Prince William Sound, Alaska
This data release contains model output from simulations presented in the associated Open-File Report (Barnhart and others, 2021). In this report, we present model results from four simulations (scenarios C-290, NC-290, C-689, NC-689, Table 1) of hypothetical rapid movement of landslides into adjacent fjord water at Barry Arm, Alaska using the D-Claw model (George and Iverson, 2014; Iverson and Ge
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.