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Dataset of 100-year flood susceptibility maps for the continental U.S. derived with a geomorphic method.


ABSTRACT: Efficient strategies for preparing communities to protect against, respond to, recover from, and mitigate flood hazard are often hampered by the lack of information about the position and extent of flood-prone areas. Hydrologic and hydraulic analyses allow to obtain detailed flood hazard maps, but are a computationally intensive exercise requiring a significant amount of input data, which are rarely available both in developing and developed countries. As a consequence, even in data-rich environments, official flood hazard graduations are often affected by extensive gaps. In the U.S., for instance, the detailed floodplain delineation produced by the Federal Emergency Management Agency (FEMA) is incomplete, with many counties having no floodplain mapping at all. In this article we present a mapping dataset containing 100-year flood susceptibility maps for the continental U.S. with a 90 m resolution. They have been obtained performing a linear binary classification based on the Geomorphic Flood Index (GFI). To the best knowledge of the authors, there are no available flood-prone areas maps for the entire continental U.S. with resolution lower that 30??×30?? (approximatively 1 km at the equator).

SUBMITTER: Samela C 

PROVIDER: S-EPMC5397099 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Dataset of 100-year flood susceptibility maps for the continental U.S. derived with a geomorphic method.

Samela Caterina C   Manfreda Salvatore S   Troy Tara J TJ  

Data in brief 20170408


Efficient strategies for preparing communities to protect against, respond to, recover from, and mitigate flood hazard are often hampered by the lack of information about the position and extent of flood-prone areas. Hydrologic and hydraulic analyses allow to obtain detailed flood hazard maps, but are a computationally intensive exercise requiring a significant amount of input data, which are rarely available both in developing and developed countries. As a consequence, even in data-rich environ  ...[more]

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