Sublacustrine landslide and tsunami models from Lake Quinault, Washington

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Frequently anticipated questions:

What does this data set describe?

Title:
Sublacustrine landslide and tsunami models from Lake Quinault, Washington
Abstract:
This USGS data release provides model setup files to simulate a hypothetical sublacustrine landslide in Lake Quinault and resulting tsunami waves. The BingClaw model (Kim and others, 2019; Kim and others, 2025) is used to model slope failure and GeoClaw (Berger and LeVeque, 2023; Clawpack Development Team, 2025) is used to model tsunami propagation and inundation. A topobathymetric digital terrain model (DTM) used in both models is provided and was merged from several elevation data sources (National Centers for Environmental Information, 2023; Washington Geological Survey, 2012; 2018; 2019; 2020). Zip files are provided for each model that can be used to reproduce the simulations. An example set of modeled outputs are also provided in each zip file.
Supplemental_Information:
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  1. How might this data set be cited?
    SeanPaul M. La Selle, Løvholt, Finn, Gibbons, Steven J., Derosier, Boe J., and Brothers, Daniel S., 20251220, Sublacustrine landslide and tsunami models from Lake Quinault, Washington: data release DOI:10.5066/P14CB2SN, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

    Online Links:

    Other_Citation_Details:
    Suggested Citation: La Selle, S.M., Løvholt, F., Gibbons, S. J., Derosier, B.J., Brothers, D.S., 2025, Sublacustrine landslide and tsunami models from Lake Quinault, Washington: U.S. Geological Survey data release, https://doi.org/10.5066/P14CB2SN.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -123.99420
    East_Bounding_Coordinate: -123.77104
    North_Bounding_Coordinate: 47.56284
    South_Bounding_Coordinate: 47.41273
  3. What does it look like?
    quinault_mccormick_preview_image.png (PNG)
    a) Red-relief image of topobathymetric digital terrain model at McCormick Creek in Lake Quinault. b) BingClaw model output of slide thickness in meters. c) Resulting tsunami modeled in GeoClaw.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 30-Jul-2025
    Ending_Date: 04-Dec-2025
    Currentness_Reference:
    ground condition at time data were collected
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: text
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      Indirect_Spatial_Reference:
      Horizontal coordinates are in the UTM Zone 10 N coordinate system for all arc-ascii format model files (.asc and .tt3). Elevation values in these format are adjusted to the NAVD88 vertical datum, in meters. The raster properties below are for the topobathymetric DTM
      This is a Raster data set. It contains the following raster data types:
      • Dimensions 6014 x 6200 x 1, type Grid Cell
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 10
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -123.0
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      False_Northing: 0.0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 2.74
      Ordinates (y-coordinates) are specified to the nearest 2.74
      Planar coordinates are specified in Meter
      The horizontal datum used is D_North_American_1983.
      The ellipsoid used is GRS_1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: North American Vertical Datum of 1988
      Altitude_Resolution: 0.001
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?
    Entity_and_Attribute_Overview:
    Compressed .zip archives contain files of various types and formats. Model input files compatible with BingClaw v5.6.1 and GeoClaw v5.11.0 are provided in the zip archives "quinault_landslide_model_bingclaw.zip" and "quinault_tsunami_model_geoclaw.zip". An example set of modeled outputs are also provided in each zip file. For additional information, see the File Structure section of the supplemental file "readme.md". Source code for BingClaw and GeoClaw can be installed using instructions in Kim and others, 2025 and Clawpack Development Team, 2025.
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information were generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • SeanPaul M. La Selle
    • Finn Løvholt
    • Steven J. Gibbons
    • Boe J. Derosier
    • Daniel S. Brothers
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    PCMSC Science Data Coordinator
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    2885 Mission Street
    Santa Cruz, CA
    USA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov

Why was the data set created?

Lake Quinault, on the Olympic Peninsula (Washington, U.S.), is located above the Cascadia megathrust and near several mapped upper crustal faults. Past earthquakes on these faults have likely triggered slope failures in Lake Quinault (Leithold and others, 2018). The models in this data release were run to assess the tsunamigenic potential of a hypothetical sublacustrine landslide in Lake Quinault. These data are intended for science researchers, students, policy makers, and the general public.

How was the data set created?

  1. From what previous works were the data drawn?
    NCEI, 2023 (source 1 of 5)
    National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI), 2023, Descriptive Report for D00278: NOAA, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: bathymetry data
    Washington Geological Survey, 2012 (source 2 of 5)
    Survey, Washington Geological, 2012, Quinault River Basin 2011 project [lidar data]: Washington Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    lidar data, originally contracted by the Quinault Indian Nation and Puget Sound LiDAR Consortium
    Washington Geological Survey, 2018 (source 3 of 5)
    Survey, Washington Geological, 2018, Olympic National Forest 2017 project [lidar data]: Washington Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    lidar data, originally contracted by the USDA Forest Service, Region 6
    Washington Geological Survey, 2019 (source 4 of 5)
    Survey, Washington Geological, 2019, Olympic Peninsula, Washington 3DEP 2019 project [lidar data]: Washington Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: lidar data, originally contracted by the U.S. Geological Survey
    Washington Geological Survey, 2020 (source 5 of 5)
    Survey, Washington Geological, 2020, Olympic Park 2014 project [lidar data]: Washington Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution:
    lidar data, originally contracted by NASA Airborne Snow Observatory.
  2. How were the data generated, processed, and modified?
    Date: 30-Jul-2025 (process 1 of 5)
    A topobathymetric digital terrain model (DTM) was generated by merging several topographic light detection and ranging (LiDAR) datasets and a multibeam bathymetric dataset. Bathymetry was collected in 2023 by the NOAA Navigation Response Team Seattle (NCEI, 2023), and topographic LiDAR data were accessed through the Washington LiDAR portal (Washington Geological Survey, 2012, 2018, 2019, and 2020). If needed, datasets were reprojected into NAD83/UTM Zone 10 N [EPSG:26910]. Topographic LiDAR data were provided in the NAVD88 vertical datum. Bathymetric soundings were collected in a vertical datum based on averaged water level data at the outlet of Lake Quinault from 2016-2021 at USGS streamgage 12039500 (NCEI, 2023). The bathymetric vertical datum was adjusted to NAVD88 by applying a vertical offset of +56.317 meters (m), based on a modeled orthometric height provided in the hydrographic survey report (NCEI, 2023). Hydroflattened "water surfaces" were removed from LiDAR datasets overlapping Lake Quinault, resulting in a ring of no data values between the bathymetric and topographic data, representing shallow water depths where the multibeam survey could not reach. A bilinear interpolation was used to fill in the missing data using the SciPy package in Python. Artifacts from interpolation are apparent in the merged DTM, especially along the broad shallows of the northeastern Lake Quinault shoreline. Merged datasets were regridded to a final grid resolution of 2.74 m, based on the resolution of the coarsest LiDAR dataset used (Washington Geological Survey, 2020).
    Date: 17-Nov-2025 (process 2 of 5)
    A portion of the topobathymetric DTM was extracted in the vicinity of McCormick Creek along the northern shore of Lake Quinault in order to run the BingClaw landslide model. The geomorphic expression of slide runout from a previous slope failure are visible in the bathymetric data. A DTM representing a possible pre-slide lake-bed surface was generated by tracing the footprint of the observed runout debris, removing this region from the topobathymetric DTM, and performing a spline interpolation to fill in the gap. A minimum volume for the observed runout debris of 210,000 cubic meters was estimated by differencing the smoothed pre-slide DTM with the modern DTM. A raster of initial slide thickness was created by tracing the upslope region of the observed runout and filling this region with an initial guess of 5 m of sediment that tapers to 0 m thickness along the edges of the traced region. Including the modern delta, the initial modeled slide volume provided in the BingClaw example is 260,000 cubic meters.
    Date: 18-Nov-2025 (process 3 of 5)
    A suite of BingClaw models was run with the modeled slide thickness inputs, varying rheologic input parameters until the modeled runout roughly matched the observed perimeter of runout debris. In the example provided in this data release, an initial yield stress of 5,000 Pascals, residual yield stress of 500 Pascals, and remolding coefficient (gamma) of 0.005 was used. The model was run using a spatial resolution of 10 m, and model results were written to output files every 2 seconds over 120 seconds of simulation time. The resulting model outputs of evolving slide thickness were used to force the GeoClaw tsunami model. BingClaw outputs were converted to GeoClaw inputs using a python script. Simple plots of slide thickness were generated using python scripts (setplot.py) provided with the BingClaw model.
    Date: 18-Nov-2025 (process 4 of 5)
    GeoClaw models were run using the BingClaw model outputs as initial water level conditions based on the method of Kim and others (2019). For each output timestep in the BingClaw model, the change in water depth due to the change in landslide thickness is used as a change in the GeoClaw water surface elevations, assuming hydrostatic pressure. This coupling scheme does not directly account for longitudinal momentum transfer from the slide to the generated tsunami waves. Two types of hydrodynamic tsunami propagation models were run: a non-dispersive wave model using the nonlinear shallow water equations (swe) and a dispersive wave model using the Serre-Green-Naghdi Boussinesq-type equations (bouss). Both models use the shallow water equations for inundation and in modeled water depths less than 5 m. Both models were run with adaptive mesh refinement (AMR) at refinement level resolutions of 1000, 200, 40, 10, and 5 m. The parameter for sea level in GeoClaw was set to 57 m to represent the lake water surface elevation. Model figures and animations were plotted using the included "tsunami_plots.ipynb" Python Jupyter Notebooks.
    Date: 12-Dec-2025 (process 5 of 5)
    Files needed to run BingClaw and GeoClaw models along with example modeled outputs, were compiled into compressed archives for distribution. A supplemental information file "readme.md " describes in greater detail the file structure of the included compressed archived, and limited instructions on usage.
  3. What similar or related data should the user be aware of?
    Kim, J., Løvholt, F., Issler, D., and Forsberg, C.F., 2019, Landslide material control on tsunami genesis - The Storegga Slide and tsunami (8,100 years BP)..

    Online Links:

    Other_Citation_Details:
    Kim, J., Løvholt, F., Issler, D., and Forsberg, C. F. (2019). Landslide material control on tsunami genesis - The Storegga Slide and tsunami (8,100 years BP). Journal of Geophysical Research: Oceans, 124(6), 3607-3627.
    Kim, J., Gibbons, S.J., and Løvholt, F., 2025, BingClaw_5.6.1 (Version v1.0.3) [Computer software].

    Online Links:

    Other_Citation_Details:
    Kim, J., Gibbons, S. J., and Løvholt, F. (2025). BingCLAW_5.6.1 (Version v1.0.3) [Computer software]. Accessed August, 2025. https://github.com/norwegian-geotechnical-institute/BingCLAW_5.6.1
    Berger, M.J., and LeVeque, R.J., 2023, Implicit adaptive mesh refinement for dispersive tsunami propagation.

    Online Links:

    Other_Citation_Details:
    Berger, M. J., and LeVeque, R. J. (2023). Implicit adaptive mesh refinement for dispersive tsunami propagation. Society for Industrial Applied Mathematics Journal on Scientific Computing, 46(2), B554-B578.
    Team, Clawpack Development, 2025, Clawpack Version 5.12.00 [Computer software].

    Online Links:

    Other_Citation_Details:
    Clawpack Development Team (2024), Clawpack Version 5.11.00 [Computer software], Accessed August, 2025. http://www.clawpack.org.
    Leithold, E.L., Wegmann, K. W., Bohnenstiehl, D. R., Smith, S. G., Noren, A., and O'Grady, R., 2018, Slope failures within and upstream of Lake Quinault, Washington, as uneven responses to Holocene earthquakes along the Cascadia subduction zone..

    Online Links:

    Other_Citation_Details:
    Leithold, E. L., Wegmann, K. W., Bohnenstiehl, D. R., Smith, S. G., Noren, A., and O'Grady, R. (2018). Slope failures within and upstream of Lake Quinault, Washington, as uneven responses to Holocene earthquakes along the Cascadia subduction zone. Quaternary Research, 89(1), 178-200.

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    No formal attribute accuracy tests were conducted.
  2. How accurate are the geographic locations?
    A formal accuracy assessment of the horizontal positional information in the data set has either not been conducted or is not applicable.
  3. How accurate are the heights or depths?
    A formal accuracy assessment of the vertical positional information in the data set has either not been conducted or is not applicable.
  4. Where are the gaps in the data? What is missing?
    Dataset is considered complete for the information presented, as described in the abstract. Users are advised to read the metadata for each part of this data release carefully for additional details.
  5. How consistent are the relationships among the observations, including topology?
    No formal logical accuracy tests were conducted.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints No access constraints
Use_Constraints USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator(s) of the dataset and in products derived from these data. This information is not intended for navigation purposes.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - CMGDS
    2885 Mission Street
    Santa Cruz, CA
    USA

    831-427-4747 (voice)
    pcmsc_data@usgs.gov
  2. What's the catalog number I need to order this data set? Compressed .zip archives contain files of various types and formats. Model input files compatible with BingClaw v5.6.1 and GeoClaw v5.11.0 are provided in the zip archives "quinault_landslide_model_bingclaw.zip" and "quinault_tsunami_model_geoclaw.zip". Source code for BingClaw and GeoClaw can be installed using instructions in Kim and others, 2025 and Clawpack Development Team, 2025
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: zipped file folders containing model input and output files for BingClaw v5.6.1 (quinault_landslide_model_bingclaw.zip) and GeoClaw v5.11.0 (quinault_tsunami_model_geoclaw.zip). Each zip file contains a folder named "mccormick_slide". Within the "mccormick_slide" folders are relevant model input files such as topobathymetric DTMs and slide thickness. One example run is provided for BingClaw, in the folder "run01_i5000_r500_g005". Two example tsunami model runs using non-dispersive (swe) and dispersive (bouss) equations are provided for GeoClaw along with modeled outputs. See supplemental files "readme.md" or "readme.pdf" for more details. in format ASCII, plain text (version BingClaw v5.6.1 and GeoClaw v5.11.0) Size: 2202.93
      Network links: https://doi.org/10.5066/P14CB2SN
    • Cost to order the data: None

Who wrote the metadata?

Dates:
Last modified: 20-Dec-2025
Metadata author:
PCMSC Science Data Coordinator
U.S. Geological Survey, Pacific Coastal and Marine Science Center
2885 Mission Street
Santa Cruz, CA

831-427-4747 (voice)
pcmsc_data@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/pcmsc/DataReleases/CMGDS_DR_tool/DR_P14CB2SN/quinault_landslide_tsunami_model_metadata.faq.html>
Generated by mp version 2.9.51 on Mon Jan 12 12:51:45 2026