Flood hazard zones for for the island of Ta'u, American Samoa

FEMA Flood hazard zones for Aunu'u, American Samoa.

FEMA Flood hazard zones for the islands of Ofu and Olosega, American Samoa

FEMA Flood Hazard Zones for Guam.

Minor watersheds of Tutuila, American Samoa.

Hydrography of Tutuila, American Samoa.

Nuuuli Jurisdictional Wetland Line - Tutuila, American Samoa

Multi-hazard inundation around Honolulu. The study area includes the urban corridor stretching from Honolulu International Airport to Waikiki and Diamond Head along the south shore of Oahu. Shows inundation from the following two hazards: 1) Tsunami Run-Up Inundation Computer model simulation of tsunami run-up inundation using current sea level at mean higher high water (MHHW) as its baseline water level. The model simulates maximum inundation based on five major historical tsunamis that have impacted Hawaii: 1) The 1946 Aleutian earthquake (8.2 Mw), 2) 1952 Kamchatka earthquake (9.0 Mw), 3) 1957 Aleutian earthquake (8.6 Mw), 4) 1960 Chile earthquake (9.5 Mw), and 5) the 1964 Alaska earthquake (9.2 Mw). 2) Hurricane Storm Surge Inundation Computer model simulation of hurricane storm surge inundation using current sea level at mean higher high water (MHHW) as its baseline water level. The model simulates a Category 4 hurricane, similar to Hurricane Iniki which devastated the island of Kauai in 1992, with a central pressure ranging from 910 to 970 mbar and maximum sustained winds ranging from 90 to 150 mph as it tracked from open ocean to land to open ocean again. The model result shows the Maximum of the Maximum Envelope of High Water (MEOW), or MOM, providing a worst-case snapshot for a particular storm category under "perfect" storm conditions. Data produced in 2014 by Dr. Kwok Fai Cheung of the department of Ocean and Resources Engineering (ORE) in the School of Ocean and Earth Science and Technology (SOEST) of the University of Hawaii at Manoa. Supported in part by the NOAA Coastal Storms Program (CSP) and the University of Hawaii Sea Grant College Program. While considerable effort has been made to implement all model components in a thorough, correct, and accurate manner, numerous sources of error are possible. The entire risk associated with the results and performance of these data is assumed by the user. These data should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.

Shoreline of Ta'u, American Samoa

This 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 3 feet (91 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. 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.