Flood depth projections at Elim, Alaska

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What does this data set describe?

Title: Flood depth projections at Elim, Alaska
Abstract:
Flood depths from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Elim, Alaska. These projections focus on areas landward of the present-day shoreline. The flood depth products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTiffs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).
Supplemental_Information:
Work was funded by US Geological Survey Climate Adaptation Science Center Project EN05ES9 and partly with funds from Title VII of Division N in the Consolidated Appropriations Act, 2023 (Public Law 117–328) to support direct recovery and rebuilding decisions in the wake of declared disasters related to hurricanes and typhoons in 2022. For more information on these efforts, see Projects - Climate Adaptation Science Centers and https://www.usgs.gov/supplemental-appropriations-for-disaster-recovery-activities/typhoon-merbok-coastal-community. For more information on coastal storm modeling, see https://www.usgs.gov/centers/pcmsc/science/coastal-storm-modeling-system-cosmos.
  1. How might this data set be cited?
    Erikson, Li H., Engelstad, Anita C., Nederhoff, Kees, Nereson, Alexander L., Gibbs, Ann E., Williams, Dee M., Hayden, Maya K., and Herman-Mercer, Nicole, 20250912, Flood depth projections at Elim, Alaska: data release DOI: 10.5066/P143S6SG, U.S. Geological Survey, Alaska Climate Adaptation Science Center, Anchorage, AK.

    Online Links:

    This is part of the following larger work.

    Erikson, Li H., Engelstad, Anita C., Nederhoff, Kees, Nereson, Alexander L., Gibbs, Ann E., Williams, Dee M., Hayden, Maya K., and Herman-Mercer, Nicole, 2025, CoSMoS-AK Modeled Flood and Erosion Hazards at Elim - Coastal Alaska: data release DOI: 10.5066/P143S6SG, U.S. Geological Survey, Alaska Climate Adaptation Science Center, Anchorage, AK.

    Online Links:

    Other_Citation_Details:
    Suggested Citation: Erikson, L.H., Engelstad, A.C., Nederhoff, K., Nereson, A.L., Gibbs, A.E., Williams, D.M., Hayden, M.K., and Herman-Mercer, N., 2025, CoSMoS-AK Modeled Flood and Erosion Hazards at Elim - Coastal Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/P143S6SG.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -162.285098
    East_Bounding_Coordinate: -162.228122
    North_Bounding_Coordinate: 64.625831
    South_Bounding_Coordinate: 64.601214
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2025
    Currentness_Reference:
    publication year
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: geoTIFF
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Raster data set. It contains the following raster data types:
      • Dimensions, type Pixel
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 4
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -159.00000
      Latitude_of_Projection_Origin: 0.00000
      False_Easting: 500000.0
      False_Northing: 0.00
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 1
      Ordinates (y-coordinates) are specified to the nearest 1
      Planar coordinates are specified in Meters
      The horizontal datum used is NAD83.
      The ellipsoid used is GRS 1980.
      The semi-major axis of the ellipsoid used is 6378137.00.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Depth_System_Definition:
      Depth_Datum_Name: North American Vertical Datum of 1988
      Depth_Resolution: 0.01
      Depth_Distance_Units: meters
      Depth_Encoding_Method: Implicit coordinate
  7. How does the data set describe geographic features?
    flood depth projections (Flood_depth_projections-Elim.zip and Flood_depth_projections_MHHW-Elim.zip)
    GeoTIFF files contain projections of flood-hazard depths. Additional GeoTIFF files are available to show flood depths only above local mean higher high water (MHHW). (Source: Producer defined)
    flood depth
    maximum flood depth associated with corresponding flood extent of indicated sea-level rise (SLR) and return period (RP) (Source: model-derived)
    Range of values
    Minimum:0.01
    Maximum:16.67
    Units:meters
    Resolution:0.01
    Entity_and_Attribute_Overview:
    The data contain flood depths (depth of water associated with coincident flood hazards) and are organized by return periods. Return periods include the no storm ‘average’ condition (rp000), and statistical once-a-year storms (rp001), every 10 (rp10), every 20 (rp20) and every 100 years (rp100) storms. File names reflect the geographic area of the projection (community, here Elim), the attribute, here flood depth (fldDepth), the sea-level rise (slr) scenario, and the return period (rp) of storm conditions. SLR scenarios are listed in centimeters and range from no SLR (slr000) to a SLR of 300 cm (slr300). For example, Elim_fldDpth_MHHW_slr200_rp100 contains flood depths above the mean higher high water (MHHW) line for a sea level rise of 200 cm (2 m) during a projected hundred-year storm in Elim, Alaska.
    Entity_and_Attribute_Detail_Citation: U.S. Geological Survey

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Li H. Erikson
    • Anita C. Engelstad
    • Kees Nederhoff
    • Alexander L. Nereson
    • Ann E. Gibbs
    • Dee M. Williams
    • Maya K. Hayden
    • Nicole Herman-Mercer
  2. Who also contributed to the data set?
    Resources supporting this work were provided by USGS Advanced Research Computing (Falgout and others, 2024). The authors would like to acknowledge the following important contributions: Rich Buzard (formerly USGS, now Alaska Native Tribal Health Consortium, ANTHC), Dana Brown (National Oceanic and Atmospheric Administration, NOAA), Amanda Stoltz (University of Delaware), Jacquelyn R Overbeck (ANTHC), Amber Deem (Kawerak, Inc.), Dave Kriebel, Sean McKnight (Kawerak, Inc.), City, Tribe and Corporation of Elim and Unalakleet, Scott Evans and Hina Kilioni, North Slope Burrough, Utqiagvik , and Harper Baldwind (NOAA-Affiliate).
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Pacific Coastal and Marine Science Center
    Attn: PCMSC Science Data Coordinator
    2885 Mission Street
    Santa Cruz, CA

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

Why was the data set created?

This product was created to fulfill the Bureau-wide vision of an integrated, predictive science capability to support Alaska Native communities in building resiliency from natural disasters, sovereignty and self-determination, and emergency response and planning capacity.

How was the data set created?

  1. From what previous works were the data drawn?
    downscaled wave data (source 1 of 5)
    Engelstad, Anita C., Erikson, Li H., Reguero, Borja G., Gibbs, Ann E., and Nederhoff, Kees M., 2024, Nearshore wave time-series along the coast of Alaska computed with a numerical wave model (ver. 2.0, November 2024): U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: downscaled wave data
    CMIP6 (source 2 of 5)
    Erikson, Li H., Herdman, Liv, Flanary, Chris, Engelstad, Anita C., Pusuluri, Prasad, Barnard, Patrick L., Storlazzi, Curt D., Beck, Michael, Reguero, Borja G., and Parker, Kai A., 2022, Ocean wave time-series data simulated with a global-scale numerical wave model under the influence historical and projectedCMIP6 wind and sea ice fields (ver. 2.0, October 2024), Edition: 2.0: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: projected wave data
    XBeach model (source 3 of 5)
    Nederhoff, Kees M., Erikson, Li H., and Engelstad, Anita C., 2025, Flood and erosion hazard model Elim, Alaska: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: XBeach model
    TBDEM (source 4 of 5)
    Nereson, Alexander L., Gibbs, Ann E., and Erikson, Li H., 2025, Topobathymetric digital elevation models – coastal Alaska: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: Topographic and bathymetry elevation data used in models
    VLM (source 5 of 5)
    Shirzaei, Manoocher, and Erikson, Li H., 2025, Vertical land motion rates for the years 2007 to 2021 - Coastal Alaska: U.S. Geological Survey, online.

    Online Links:

    Type_of_Source_Media: online database
    Source_Contribution: vertical land motion rates
  2. How were the data generated, processed, and modified?
    Date: 01-Feb-2023 (process 1 of 5)
    Individual surfbeat and non-hydrostatic 2D XBeach models were stood up and tested against known past storm events (models can be found in this release). Data sources used in this process:
    • TBDEM
    • XBeach model
    Date: 01-Nov-2024 (process 2 of 5)
    A set of extreme water level and wave conditions was identified at the approximate open boundaries of each 2D XBeach model. These extreme conditions were derived using wind, atmospheric pressure, and sea ice fields from high-resolution global climate models (GCMs) as forcing inputs to wave and hydrodynamic models. The dynamic downscaling process is described in Erikson and others (2022) and the manuscript of Engelstad and others (2024). Extreme value statistics for 1-, 10-, 20-, 50-, and 100-year return period coastal storms were calculated from both historical (1979–2015) and future projection (2020–2050) GCM runs. The percent change between historical and projected extremes was then computed and applied to similar statistics derived from model runs forced by ERA5 reanalysis wind, pressure, and sea ice data (1979-2022). Percent changes were calculated from the ensemble mean of four GCM simulations: CMCC-CM2-VHR4-r1i1p1f1_gn, CNRM-CM6-1-HR-r1i1p1f2, EC-Earth3P-HR- r1i1p2f1_gr, and HadGEM3-GC31-HM_highresSST-future_r1i1p1f1_gn. Data sources used in this process:
    • CMIP6
    • downscaled wave data
    Date: 01-Mar-2025 (process 3 of 5)
    2DXBeach production runs: All scenario simulations were done in a two-staged approach whereby XBeach was first run in the surfbeat mode (XB-SB), bed level changes interpolated onto the non-hydrostatic (XB-NH) model grid, and the latter model run. This two-stage approach leverages the strengths of both XBeach modes for a comprehensive simulation of wave dynamics, particularly in the context of swash zone (active beach area) processes and wave runup. The SB mode is computationally efficient and well-suited for capturing long-wave (infragravity) variations and their interactions with the shoreline, including morphodynamic change (erosion and sedimentation). The NH mode provides a detailed, wave-resolved simulation that includes individual wave overtopping. Ran each of the 2DXBeach SB models 30 times for all combinations of 6 SLR scenarios and the 1-, 10-, 20-, 50-, and 100-year return period water level and wave extremes. Interpolated the final bed elevations onto the 2DXBeach NH model grids and ran each of the 2DXBeach NH models 36 times for all combinations of SLR and storms plus the no storm condition. Data sources used in this process:
    • XBeach model
    Date: 30-May-2025 (process 4 of 5)
    Post-process and finalize data products: All simulation data were downloaded from the USGS Advanced Research Computing Center’s Hovenweep Supercomputer and post-processed to extract maximum water levels at each grid point over the entire simulation and subsequently interpolated onto the finer resolution (1m x 1m) digital elevation mesh. Interpolations were done using The Mathworks MATLAB linear scatteredinterpolant function which in turn uses a Delaunay triangulation algorithm of the sample points. Significant wave height, erosion and sedimentation, and the velocity-depth product were similarly processed. Maximum water elevation surfaces were depth-differenced to the DEM to separate low-lying vulnerable areas from contiguous coastal flooding. Other output data (water elevation, maximum depth x velocity, sedimentation/erosion, and maximum wave heights) were clipped to the same final flood hazard extent. Additionally, all data below the mean higher high-water line (MHHW) were removed from flood depth projections. Flood potentials (maximum and minimum flood uncertainty) were derived by adding/subtracting estimated model error, DEM uncertainty, 95th percent confidence intervals of the storm event water level, and projected vertical land motion (VLM) for a given SLR to the respective water elevation surface. See O'Neill and others (2018) for a similar approach. GeoTIFFs were created for all combinations of six SLRs (0, 0.5, 1.0, 1.5, 2.0 and 3.0 m), 5 storms (1-year, 10-year, 20-year, 50-year, and 100-year return period coastal events), and the non-storm condition for a total of 36 scenarios. Final geoTIFFs were separated by community (Flood_depth_projections-Elim.zip). Additionally, all data below the mean higher high-water line (MHHW) were removed from flood depth projections for a version that only shows results landward of the present-day shoreline (Flood_depth_projections_MHHW-Elim.zip). Data for this version are not available for the background condition with no SLR, since this scenario does not exceed the present-day shoreline). Data are organized by storm scenario (’RP’) and SLR amount. Data sources used in this process:
    • VLM
    Date: 16-Jan-2026 (process 5 of 5)
    Minor corrections to the online links were made to remove extra spaces. No data were changed. (mau@usgs.gov)
  3. What similar or related data should the user be aware of?
    Haarsma, R.J., Roberts, M.J., Vidale, P.L., Senior, C.A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N.S., Guemas, V., Hardenberg, J. von, Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.J., Mao, J., Mizielinski, M.S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and Storch, J.S. von, 2016, High resolution model intercomparison project (HighResMIP v1.0) for CMIP6.

    Online Links:

    Other_Citation_Details:
    Haarsma, R.J., Roberts, M.J., Vidale, P.L., Senior, C.A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N.S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J. J., Mao, J., Mizielinski, M.S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.S., 2016, High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6: Geoscientific Model Development, vol. 9, p. 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
    Engelstad, Anita C, Erikson, Li H, Reguero, Borja G, Gibbs, Ann E, and Nederhoff, Kees, 2024, Database and Time Series of Nearshore Waves Along the Alaskan Coast from the United States-Canada Border to the Bering Sea.

    Online Links:

    Other_Citation_Details:
    Engelstad, A.C., Erikson, L.H., Reguero, B.G., Gibbs, A.E., and Nederhoff, K., 2024, Database and time series of nearshore waves along the Alaskan coast from the United States-Canada border to the Bering Sea: U.S. Geological Survey Open-File Report 2023–1094, 23 p., https://doi.org/10.3133/ofr20231094.
    Falgout, J.T., Gordon, J., Williams, B., and Davis, M.J., 2024, USGS Advanced Research Computing, USGS Denali Supercomputer..

    Online Links:

    Other_Citation_Details:
    Falgout, J.T., Gordon J., Williams B., Davis M. J., USGS Advanced Research Computing, USGS Denali Supercomputer: U.S. Geological Survey, https://doi.org/10.5066/P9PSW367
    O'Neill, A.C., Erikson, L.H., Barnard, P.L., Limber, P.W., Vitousek, S., Warrick, J., Foxgrover, A.C., and Lovering, J.L., 2018, Projected 21st Century Coastal Flooding in the Southern California Bight. Part 1: Development of the Third Generation CoSMoS Model.

    Online Links:

    Other_Citation_Details:
    O'Neill, A.C., Erikson, L.H., Barnard, P.L., Limber, P.W., Vitousek, S., Warrick, J.A., Foxgrover, A.C., Lovering, J., 2018, Projected 21st Century Coastal Flooding in the Southern California Bight. Part 1: Development of the Third Generation CoSMoS Model: Journal of Marine Science and Engineering, vol. 6, art. 59, https://doi.org/10.3390/jmse6020059.

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

  1. How well have the observations been checked?
    Attribute values are model-derived water depths due to plausible sea-level rise and future storm conditions and therefore cannot be validated against observations. The projections were generated using the latest downscaled climate projections from the Coupled Model Intercomparison Project (CMIP6).
  2. How accurate are the geographic locations?
    Data are concurrent with topobathymetric DEM locations.
  3. How accurate are the heights or depths?
    Model-derived data are accurate within published uncertainty bounds, indicative of total uncertainty from elevation data sources, model processes, and vertical land motion. This value is spatially variable and dependent on scenario (return period plus sea level rise). See Process Steps for details on total contributions to uncertainty.
  4. Where are the gaps in the data? What is missing?
    Dataset is considered complete for the information presented.
  5. How consistent are the relationships among the observations, including topology?
    Data have undergone quality checks and meet standards.

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 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

    831-427-4747 (voice)
    pcmsc_data@usgs.gov
  2. What's the catalog number I need to order this data set? These data are available in GeoTIFF format contained in a single zip file with filenames of “Flood_depth_projections-Elim.zip” and “Flood_depth_projections_MHHW-Elim.zip” accompanied by CSDGM FGDC-compliant metadata.
  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. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: Zip file Flood_depth_projections-Elim.zip contains GeoTIFF files for Elim, AK in format GeoTIFF Size: 103.8
      Network links: https://doi.org/10.5066/P143S6SG
      Data format: Zip file Flood_depth_projections_MHHW-Elim.zip contains GeoTIFF files with results above MHHW for Elim, AK in format GeoTIFF Size: 22.2
      Network links: https://doi.org/10.5066/P143S6SG
    • Cost to order the data: None.

  5. What hardware or software do I need in order to use the data set?
    These data can be viewed with ArcGIS or other spatial analysis software.

Who wrote the metadata?

Dates:
Last modified: 16-Jan-2026
Metadata author:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Attn: PCMSC Science Data Coordinator
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_P143S6SG/Flood_depth_proj_Elim_metadata.faq.html>
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