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
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
Filter Total Items: 14
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
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
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
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 Joan Andrea Khoury Hoch, Rebecca Beers, Jason W. Kean
User needs assessment for postfire debris-flow inundation hazard products
Debris flows are a type of mass movement that is more likely after wildfires, and while existing hazard assessments evaluate the rainfall intensities that are likely to trigger debris flows, no operational hazard assessment exists for identifying the areas where they will run out after initiation. Fifteen participants who work in a wide range of job functions associated with southern California po
Authors
Katherine R. Barnhart, Veronica Romero, Katherine R. Clifford
Simulating debris flow and levee formation in the 2D shallow flow model D-Claw: Channelized and unconfined flow
Debris flow runout poses a hazard to life and infrastructure. The expansion of human population into mountainous areas and onto alluvial fans increases the need to predict and mitigate debris flow runout hazards. Debris flows on unconfined alluvial fans can exhibit spontaneous self-channelization through levee formation that reduces lateral spreading and extends runout distances compared to unchan
Authors
Ryan P. Jones, Francis K. Rengers, Katherine R. Barnhart, David L. George, Dennis M. Staley, Jason W. Kean
New model of the Barry Arm landslide in Alaska reveals potential tsunami wave heights of 2 meters, values much lower than previously estimated
The retreat of Barry Glacier has contributed to the destabilization of slopes in Barry Arm, creating the possibility that a landslide could rapidly enter the fjord and trigger a tsunami.The U.S. Geological Survey (USGS) recently released a report documenting potential tsunami wave heights in the event of a large, fast-moving landslide at the Barry Arm fiord near Prince William Sound, Alaska (Barnh
Authors
Marísa A. Macías, Katherine R. Barnhart, Dennis M. Staley
Multi-model comparison of computed debris flow runout for the 9 January 2018 Montecito, California post-wildfire event
Hazard assessment for post-wildfire debris flows, which are common in the steep terrain of the western United States, has focused on the susceptibility of upstream basins to generate debris flows. However, reducing public exposure to this hazard also requires an assessment of hazards in downstream areas that might be inundated during debris flow runout. Debris flow runout models are widely availab
Authors
Katherine R. Barnhart, Ryan P. Jones, David L. George, Brian W. McArdell, Francis K. Rengers, Dennis M. Staley, Jason W. Kean
Preliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska
We simulated the concurrent rapid motion of landslides on an unstable slope at Barry Arm, Alaska. Movement of landslides into the adjacent fjord displaced fjord water and generated a tsunami, which propagated out of Barry Arm. Rather than assuming an initial sea surface height, velocity, and location for the tsunami, we generated the tsunami directly using a model capable of simulating the dynamic
Authors
Katherine R. Barnhart, Ryan P. Jones, David L. George, Jeffrey A. Coe, Dennis M. Staley
Postwildfire soil‐hydraulic recovery and the persistence of debris flow hazards
Deadly and destructive debris flows often follow wildfire, but understanding of changes in the hazard potential with time since fire is poor. We develop a simulation‐based framework to quantify changes in the hydrologic triggering conditions for debris flows as postwildfire infiltration properties evolve through time. Our approach produces time‐varying rainfall intensity‐duration thresholds for ru
Authors
Matthew A. Thomas, Francis K. Rengers, Jason W. Kean, Luke A. McGuire, Dennis M. Staley, Katherine R. Barnhart, Brian A. Ebel
Offset channels may not accurately record strike-slip fault displacement: Evidence from landscape evolution models
Slip distribution, slip rate, and slip per event for strike‐slip faults are commonly determined by correlating offset stream channels—under the assumption that they record seismic slip—but offset channels are formed by the interplay of tectonic and geomorphic processes. To constrain offset channel development under known tectonic and geomorphic conditions, we use numerical landscape evolution simu
Authors
Nadine G. Reitman, Karl J. Mueller, Gregory E. Tucker, Ryan D. Gold, Richard W. Briggs, Katherine R. Barnhart
Non-USGS Publications**
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.
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
- Data
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 ofMerged 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 oSelect 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 StreeTadpole 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), CreatTadpole 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. TheSimulated 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 placeSimulated 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-geneSelect 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 - Multimedia
No results found.
- Publications
Filter Total Items: 14
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 stAuthorsLuke A. McGuire, Scott W. McCoy, Odin Marc, William Struble, Katherine R. BarnhartRunout 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 volumAuthorsKatherine R. Barnhart, Jason W. KeanForecasting 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 operationalAuthorsKatherine R. Barnhart, Ryan P Jones, David L. George, Francis K. Rengers, Jason W. KeanDebris-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 consistAuthorsWilliam Struble, Luke A. McGuire, Scott W. McCoy, Katherine R. Barnhart, Odin MarcThe 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 exAuthorsFrancis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann Youberg, Daniel Cadol, Alexander Gorr, Olivia Joan Andrea Khoury Hoch, Rebecca Beers, Jason W. KeanUser needs assessment for postfire debris-flow inundation hazard products
Debris flows are a type of mass movement that is more likely after wildfires, and while existing hazard assessments evaluate the rainfall intensities that are likely to trigger debris flows, no operational hazard assessment exists for identifying the areas where they will run out after initiation. Fifteen participants who work in a wide range of job functions associated with southern California poAuthorsKatherine R. Barnhart, Veronica Romero, Katherine R. CliffordSimulating debris flow and levee formation in the 2D shallow flow model D-Claw: Channelized and unconfined flow
Debris flow runout poses a hazard to life and infrastructure. The expansion of human population into mountainous areas and onto alluvial fans increases the need to predict and mitigate debris flow runout hazards. Debris flows on unconfined alluvial fans can exhibit spontaneous self-channelization through levee formation that reduces lateral spreading and extends runout distances compared to unchanAuthorsRyan P. Jones, Francis K. Rengers, Katherine R. Barnhart, David L. George, Dennis M. Staley, Jason W. KeanNew model of the Barry Arm landslide in Alaska reveals potential tsunami wave heights of 2 meters, values much lower than previously estimated
The retreat of Barry Glacier has contributed to the destabilization of slopes in Barry Arm, creating the possibility that a landslide could rapidly enter the fjord and trigger a tsunami.The U.S. Geological Survey (USGS) recently released a report documenting potential tsunami wave heights in the event of a large, fast-moving landslide at the Barry Arm fiord near Prince William Sound, Alaska (BarnhAuthorsMarísa A. Macías, Katherine R. Barnhart, Dennis M. StaleyMulti-model comparison of computed debris flow runout for the 9 January 2018 Montecito, California post-wildfire event
Hazard assessment for post-wildfire debris flows, which are common in the steep terrain of the western United States, has focused on the susceptibility of upstream basins to generate debris flows. However, reducing public exposure to this hazard also requires an assessment of hazards in downstream areas that might be inundated during debris flow runout. Debris flow runout models are widely availabAuthorsKatherine R. Barnhart, Ryan P. Jones, David L. George, Brian W. McArdell, Francis K. Rengers, Dennis M. Staley, Jason W. KeanPreliminary assessment of the wave generating potential from landslides at Barry Arm, Prince William Sound, Alaska
We simulated the concurrent rapid motion of landslides on an unstable slope at Barry Arm, Alaska. Movement of landslides into the adjacent fjord displaced fjord water and generated a tsunami, which propagated out of Barry Arm. Rather than assuming an initial sea surface height, velocity, and location for the tsunami, we generated the tsunami directly using a model capable of simulating the dynamicAuthorsKatherine R. Barnhart, Ryan P. Jones, David L. George, Jeffrey A. Coe, Dennis M. StaleyPostwildfire soil‐hydraulic recovery and the persistence of debris flow hazards
Deadly and destructive debris flows often follow wildfire, but understanding of changes in the hazard potential with time since fire is poor. We develop a simulation‐based framework to quantify changes in the hydrologic triggering conditions for debris flows as postwildfire infiltration properties evolve through time. Our approach produces time‐varying rainfall intensity‐duration thresholds for ruAuthorsMatthew A. Thomas, Francis K. Rengers, Jason W. Kean, Luke A. McGuire, Dennis M. Staley, Katherine R. Barnhart, Brian A. EbelOffset channels may not accurately record strike-slip fault displacement: Evidence from landscape evolution models
Slip distribution, slip rate, and slip per event for strike‐slip faults are commonly determined by correlating offset stream channels—under the assumption that they record seismic slip—but offset channels are formed by the interplay of tectonic and geomorphic processes. To constrain offset channel development under known tectonic and geomorphic conditions, we use numerical landscape evolution simuAuthorsNadine G. Reitman, Karl J. Mueller, Gregory E. Tucker, Ryan D. Gold, Richard W. Briggs, Katherine R. BarnhartNon-USGS Publications**
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.ch13K. 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.
- Software
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.