Details

Autor(en) / Beteiligte

• Gourley, Jonathan J.
• Hong, Yang
• Flamig, Zachary L.
• Arthur, Ami
• Clark, Robert
• Calianno, Martin
• Ruin, Isabelle
• Ortel, Terry
• Wieczorek, Michael E.
• Kirstetter, Pierre-Emmanuel
• Clark, Edward
• Krajewski, Witold F.

Titel

A Unified Flash Flood Database across the United States

Ist Teil von

• Bulletin of the American Meteorological Society, 2013-06, Vol.94 (6), p.799-805

Ort / Verlag

Boston: American Meteorological Society

Erscheinungsjahr

2013

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Despite flash flooding being one of the most deadly and costly weather-related natural hazards worldwide, individual datasets to characterize them in the United States are hampered by limited documentation and can be difficult to access. This study is the first of its kind to assemble, reprocess, describe, and disseminate a georeferenced U.S. database providing a long-term, detailed characterization of flash flooding in terms of spatiotemporal behavior and specificity of impacts. The database is composed of three primary sources: 1) the entire archive of automated discharge observations from the U.S. Geological Survey that has been reprocessed to describe individual flooding events, 2) flash-flooding reports collected by the National Weather Service from 2006 to the present, and 3) witness reports obtained directly from the public in the Severe Hazards Analysis and Verification Experiment during the summers 2008–10. Each observational data source has limitations; a major asset of the unified flash flood database is its collation of relevant information from a variety of sources that is now readily available to the community in common formats. It is anticipated that this database will be used for many diverse purposes, such as evaluating tools to predict flash flooding, characterizing seasonal and regional trends, and improving understanding of dominant flood-producing processes. We envision the initiation of this community database effort will attract and encompass future datasets.