4.5 Article

Extreme Flood Response: The June 2008 Flooding in Iowa

期刊

JOURNAL OF HYDROMETEOROLOGY
卷 14, 期 6, 页码 1810-1825

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-12-0191.1

关键词

Climatology; Radars; Radar observations; Numerical analysis; modeling; Flood events

资金

  1. National Science Foundation (NSF) [EAR-0847347]
  2. NASA [NNX10AI46G]
  3. NOAA Cooperative Institute for Climate Science (CICS)
  4. Iowa Flood Center
  5. Willis Research Network
  6. NASA [NNX10AI46G, 131984] Funding Source: Federal RePORTER

向作者/读者索取更多资源

The authors examine the hydroclimatology, hydrometeorology, and hydrology of extreme floods through analyses that center on the June 2008 flooding in Iowa. The most striking feature of the June 2008 flooding was the flood peak of the Cedar River at Cedar Rapids (3964 m(3) s(-1)), which was almost twice the previous maximum from a record of 110 years. The spatial extent of extreme flooding was exceptional, with more U.S. Geological Survey stream gauging stations reporting record flood peaks than in any other year. The 2008 flooding was produced by a sequence of organized thunderstorm systems over a period of two weeks. The authors examine clustering and seasonality of flooding in the Iowa study region and link these properties to features of the June 2008 flood event. They examine the environment of heavy rainfall in Iowa during June 2008 through analyses of composite rainfall fields (15-min time interval and 1-km spatial resolution) developed with the Hydro-NEXRAD system and simulations using the Weather Research and Forecasting Model (WRF). Water balance analyses of extreme flood response, based on rainfall and discharge observations from basins with extreme flooding, suggest that antecedent soil moisture plays a diminishing role in flood response as the return interval increases. Rainfall structure and evolution play a critical and poorly understood role in determining the scaling of flood response. As in other extreme flood studies, analyses of the Iowa flood data suggest that measurement errors can be significant for record discharge estimates.

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