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

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 similar to 1%, the flood extents by 65km(2), and the high danger zone by similar to 6%. On the contrary, the bathymetry correction factors may reduce the flood extent by similar to 1.4% and the high-danger zone by similar to 4%. Reducing the reservoir storage capacity to 1% may increase the flood extent by similar to 4% and the high-danger zone by similar to 17%. This study may provide supporting information to guide and prioritize the development of future high-performance computing hydrodynamic large-scale flood simulations.

Automated summary

This study highlighted the importance of hydrologic parameters in improving flood modeling and the minimal impact of initial water depths on large flood events. Manning's roughness coefficients may affect the flood extent and high-danger zones, while bathymetry correction factors and reservoir storage capacity can also have corresponding impacts on flooding.