Development of a high-resolution two-dimensional urban/rural flood simulation

• Main Author: Piotrowski, Jesse Alex
• Other Authors: Weber, Larry Joseph
• Format: Others
• Language: English
• Published: University of Iowa 2010
• Subjects: Flood; Hydrodynamic; Numerical; Simulation; Two-dimensional; Urban; Civil and Environmental Engineering
• Online Access: https://ir.uiowa.edu/etd/574; https://ir.uiowa.edu/cgi/viewcontent.cgi?article=1759&context=etd

Numerical modeling of extreme flooding in an urban area in eastern Iowa is presented. Modeling is performed using SRH-2D, an unstructured grid, finite volume model that solves the depth-averaged shallow-water equations. Data from a photogrammetric stereo compilation, contour maps, a hydrographic survey and building records were used to create a digital elevation model depicting the river channel and floodplain. A spatially distributed Manning coefficient based on land cover classification, derived from aerial photography is also used. The model is calibrated with high-resolution inundation depth data derived from a 1 m light detection and ranging survey, collected during the falling limb of the flood hydrograph, and discrete global positioning system measurements of water surface elevation at a bankfull condition. The model is validated with discrete high water marks collected immediately after the flood event. Results show the model adequately represents the water surface elevation in the main channel and floodplain and that exclusion of the discharges from minor creeks did not affect simulation accuracy. Reach scale results are not affected by the presence of buildings, but local inconsistencies occur in shallow water if buildings are not removed from the mesh. An unsteady hydrograph approximates flood hydrodynamics better than a steady-state simulation, but extreme computation time is not feasible for most investigations. The two-dimensional model was also compared to a comparable one-dimensional model of the study reach. The 1D model suffered from an inability to accurately predict inundation depth throughout the entire study area.