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    • Sea Level Rise: American Samoa: Extreme High-Tide Flooding: 1-Ft Scenario: 20 Days Per Year

    Metadata Updated: August 26, 2024

    This extreme high-tide flooding layer provides a prediction of future sea level rise (SLR) inundation and was produced using a passive flooding model, often referred to as a "bathtub" model. It provides an assessment of flooded areas according to a specific water level. As an alternative to the SLR scenarios in other data layers that we provide, our project also provides the ability to select specific amounts of SLR in increments of one foot, independent of any particular scenario. This information can be used if guidance for a project requires planning for a specific amount of SLR rather than a time horizon. The present layer models a sea level rise of 1 foot (30 cm).

    We apply this model to the 2022 National Geodetic Survey (NGS) lidar DEM for American Samoa with 1-meter resolution. The DEM was leveled from NAD83 (PA11) to mean sea level at 0 m (MSL=0) in 2005. The adjustment of the DEM may lead to inaccuracies due to the lack of historic information. It is also important to acknowledge that any inaccuracies in the DEM will lead to inaccuracies in the flooding estimates.

    When assessing the impacts of future sea level rise, it is important to consider how often flood conditions will occur in a given year. A low-lying location will begin to see impacts of being flooded a few times per year. Then, as sea level rise increases, it will flood tens of times per year. Eventually, that location may be flooded under a daily high tide. The present scenario models a frequency of 20 flooding days per year. Please note that this frequency represents an average number of times per year (Thompson et al., 2021). Any particular year may have substantially more or less flooding days depending on local climate variability (such as the El Nino, La Nina cycle) and year-to-year variability in the tides due to changes in the alignment of the Earth, Moon, and Sun. Secondly, flooding frequencies are based on data from the Pago Pago tide gauge on Tutuila, which means that estimates may not perfectly represent local conditions outside the harbor or on other islands. However, this is the best source of information available, and we do not expect this to lead to significant inaccuracies in the estimates of flooding frequency. In the 1-ft scenario represented here, the modeled water level for a 20-day frequency is 104 cm.

    Flood depth is provided in centimeters above the 2005 mean higher high water (MHHW) tide level.

    It is essential to emphasize that the passive flooding model used to produce this data layer does not include the effects of waves on flooding. As a result, the extent and impacts of future flooding under high-wave conditions are not represented, which should be accounted for in planning efforts. In addition, the DEM is assumed to be unchanged as sea level rises, but in fact there will be erosion and changes in the shape of the land surface, and continued subsidence. This also must be considered, and it is best practice to consider any flooding extent or depth represented in this data layer as a best-case scenario, with the effects of dynamic shoreline processes leading to greater flood extent and depth than presented.

    Access & Use Information

    License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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    Dates

    Metadata Date July 31, 2024
    Metadata Created Date August 26, 2024
    Metadata Updated Date August 26, 2024
    Reference Date(s) July 31, 2024 (creation), July 31, 2024 (issued), July 31, 2024 (revision)
    Frequency Of Update

    Metadata Source

    Harvested from ioos

    Other Data Resources

    Graphic Preview

    Sample image.

    Additional Metadata

    Resource Type Dataset
    Metadata Date July 31, 2024
    Metadata Created Date August 26, 2024
    Metadata Updated Date August 26, 2024
    Reference Date(s) July 31, 2024 (creation), July 31, 2024 (issued), July 31, 2024 (revision)
    Responsible Party University of Hawaii at Manoa (Point of Contact)
    Contact Email
    Guid as_uhslc_all_slr_xflood_1ft_20day_v2
    Access Constraints
    Bbox East Long -168.140850541878
    Bbox North Lat -11.0480017523415
    Bbox South Lat -14.559769090829
    Bbox West Long -171.089797256602
    Coupled Resource [{"title": [], "href": ["#DataIdentification"], "uuid": []}, {"title": [], "href": ["#DataIdentification"], "uuid": []}, {"title": [], "href": ["#DataIdentification"], "uuid": []}]
    Frequency Of Update
    Graphic Preview Description Sample image.
    Graphic Preview File http://pacioos.org/metadata/browse/as_uhslc_all_slr_xflood_1ft_20day_v2.png
    Harvest Object Id eaa52ec7-6de1-40a5-9f2a-8034ae98d46d
    Harvest Source Id 54e15a6e-6dde-4c9c-a8f0-345cc0dfccfb
    Harvest Source Title ioos
    Licence
    Lineage 2023-09-26T00:00:00Z Initial release (Version 1.0). 2024-07-31T00:00:00Z Data Update (Version 2.0): For improved accuracy, sea level rise inundation was recalculated using a newly released higher resolution digital elevation model (DEM) as its basis. Version 1.0 used a 2021 DEM with 1/9 arc-second resolution, except for Rose Atoll where a 2012 DEM with 1/3 arc-second resolution was used (NOAA/CIRES CUDEM). In contrast, Version 2.0 uses a NOAA National Geodetic Survey (NGS) 2022 lidar DEM with 1-meter resolution. Swains Island is now included in the Verison 2.0 results, but it and Rose Atoll do not include vertical land motion (VLM) in their estimates. All DEMs were leveled to mean sea level at 0 m (MSL=0) in 2005.
    Metadata Language eng
    Metadata Type geospatial
    Old Spatial {"type": "Polygon", "coordinates": [[[-171.089797256602, -14.559769090829], [-168.140850541878, -14.559769090829], [-168.140850541878, -11.0480017523415], [-171.089797256602, -11.0480017523415], [-171.089797256602, -14.559769090829]]]}
    Progress
    Spatial Data Service Type Open Geospatial Consortium Web Feature Service (WFS)
    Spatial Reference System
    Spatial Harvester True

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