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Inundation Exposure Assessment for Aur Island, Aur Atoll, Republic of the Marshall Islands

Dates

Publication Date
Start Date
2022-02-14
End Date
2022-02-21

Citation

Gesch, D.B., Danielson, J.J., Nelson, J.R., Perroy, R.L., Collier, E., and Kerkering, H., 2024, Inundation Exposure Assessment for Select Islands in the Republic of the Marshall Islands: U.S. Geological Survey data release, https://doi.org/10.5066/P90GFUK5.

Summary

As a low-lying island nation, the Republic of the Marshall Islands (RMI) is at the forefront of exposure to climate change impacts, including, primarily, inundation (coastal flooding). Increased water levels can stem from episodic events (storm surge, wave run-up, king tides) or from chronic conditions (long term sea-level rise). Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, accurate coastal elevation data are a critical input for assessments of inundation exposure and vulnerability. Previous research has demonstrated that the quality of data used for elevation-based assessments must be well understood and applied to properly model potential impacts. The [...]

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Attached Files

Click on title to download individual files attached to this item.

Aur_Surveyed_GCPs.zip 3.59 KB application/zip
Aur_Bare-Earth-DEM.zip 12.98 MB application/zip
4.8 GB application/x-zip-compressed
Aur_AOI_mask.zip 55.52 KB application/zip
Aur_Inundation_Exposure_Grids.zip 4.07 MB application/zip

Purpose

The inundation grids are useful for quantifying and characterizing inundation exposure and related vulnerability of the islands’ low-relief lands and their population, buildings, infrastructure, and natural resources. The grids represent various scenarios of static inundation (without wave action). The areas subject to the modeled inundation levels are mapped separately for marine inundation (areas with a direct overland hydrologic connection to the ocean) and disconnected low-lying areas (with no direct overland flowpath connection to the ocean). The inundated areas are mapped with a probabilistic approach that incorporates consideration of vertical uncertainty, so results can be expressed at a specific probability, in this case at 66% and 95% probability of inundation at the specified increased water levels.

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