HR: 0800h
AN: H21A-1305    [Abstracts]
TI: Use of High-Resolution Precipitation Products Derived from the Weather Research and Forecasting Model to Drive GIS-Based Hydrological Flood Inundation Modeling; Effects of Rainfall Error on Flood Accuracy
AU: * Knebl, M R
EM: mknebl@mail.utexas.edu
AF: University of Texas at Austin, Dept. of Geological Sciences 1 University Station, C-1100, Austin, TX 78712-0254 United States
AB: This paper addresses research into a new approach that couples precipitation predictions with GIS applications and hydrological modeling to predict flood potential and thus mitigate the impacts of these natural disasters in Texas. Flooding induced from storm events is a major concern in many regions of the world, including Texas, which receives extreme precipitation events numerous times annually. The goal of this research is to produce multiple precipitation realizations based on the Weather Research and Forecasting (WRF) model, and use these forecasts to drive the GIS-based hydrological model. WRF is a mesoscale numerical weather predication system developed through a collaborative partnership between numerous agencies, led by the National Center for Atmospheric Research (NCAR). For this study, nesting is incorporated into the WRF model to produce output at the 4 kilometer scale of the hydrological model. The hydrological model combines high-resolution GIS datasets, HEC-HMS, and HEC-RAS in a modified version of the Map to Map model developed at the University of Texas at Austin's Center for Research in Water Resources. The numerous realizations derived from WRF are produced from different physical parameterizations, or different intervals of initializations. These results provide additional information regarding inaccuracies in magnitude, timing, duration, and location of precipitation forecasts. Subsequent errors in stream discharge and flood inundation are measured in order to investigate the propagation of error through the hydrologic and hydraulic models. The final product of this research will be a flood forecast product that will enable decision makers to efficiently prepare for worst-case scenarios and mitigate flood damage, while continuing to model current conditions. While designed for use by Texas disaster managers, the approach used in this research can be extended to have applications in other areas of the country.
DE: 1817 Extreme events
DE: 1821 Floods
DE: 1847 Modeling
DE: 1854 Precipitation (3354)
DE: 1879 Watershed
SC: Hydrology [H]
MN: Fall Meeting 2005