Simulation of Hurricane Harvey flood event through coupled hydrologic‐hydraulic models: Challenges and next steps

Journal of Flood Risk Management

Mario Morales‐Hernández¹  Tigstu T. Dullo²  Alfred J. Kalyanapu²  Sheikh Ghafoor³  Md Bulbul Sharif³  Katherine J. Evans⁴  Shih‐Chieh Kao⁴  Sudershan Gangrade⁴ 

[1] Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge Tennessee USA;Department of Civil and Environmental Engineering Tennessee Technological University Cookeville Tennessee USA;Department of Computer Science Tennessee Technological University Cookeville Tennessee USA;The Bredesen Center University of Tennessee Knoxville Tennessee USA;

关键词: digital elevation model (DEM);    flood simulation;    graphics processing unit (GPU);    Hurricane Harvey;    model parameterization;    reservoir;   

DOI  :  10.1111/jfr3.12716

来源: DOAJ

【 摘 要 】

Abstract Using the 2017 Hurricane Harvey flood event as a test case, this study set up a series of sensitivity analyses to highlight three challenges associated with large‐scale flood inundation modeling, including (a) model parameterization, (b) errors in digital elevation models, and (c) effects of reservoir retention. Driven by radar‐based hourly rainfall data, a series of hydrologic‐hydraulic models including the VIC hydrologic model, RAPID routing model, and Flood2D‐GPU hydrodynamic model are set up over Harris County, Texas, to simulate flood inundation and hazards. The results demonstrate the importance of hydrologic parameters in improving flood modeling. For a large flood event such as Hurricane Harvey, the effect of the initial water depths is insignificant. The Manning's n values may increase the peak water depth by ~1%, the flood extents by 65km2, and the high danger zone by ~6%. On the contrary, the bathymetry correction factors may reduce the flood extent by ~1.4% and the high‐danger zone by ~4%. Reducing the reservoir storage capacity to 1% may increase the flood extent by ~4% and the high‐danger zone by ~17%. This study may provide supporting information to guide and prioritize the development of future high‐performance computing hydrodynamic large‐scale flood simulations.

【 授权许可】

Unknown