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

• Published in: Journal of flood risk management Vol. 14; no. 3
• Main Authors: Dullo, Tigstu T., Gangrade, Sudershan, Morales‐Hernández, Mario, Sharif, Md Bulbul, Kao, Shih‐Chieh, Kalyanapu, Alfred J., Ghafoor, Sheikh, Evans, Katherine J.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.09.2021; John Wiley & Sons, Inc; The Chartered Institution of Water and Environmental Management (CIWEM), Wiley; Wiley
• Subjects: Bathymetry; digital elevation model (DEM); Digital Elevation Models; ENVIRONMENTAL SCIENCES; Flood control; flood simulation; Floods; graphics processing unit (GPU); Hourly rainfall; Hurricane Harvey; Hurricanes; Hydraulic models; Hydrodynamic models; Hydrodynamics; Hydrologic data; Hydrologic models; Hydrology; model parameterization; Modelling; Parameterization; Radar; Radar data; Rain; Rainfall; Rainfall data; reservoir; Reservoir storage; Reservoirs; Sensitivity analysis; Simulation; Storage capacity; Storage conditions; Water depth; Water storage; San Jacinto River; United States > US; Texas; Buffalo Bayou
• ISSN: 1753-318X; 1753-318X
• DOI: 10.1111/jfr3.12716

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.