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

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.

Performance Execution Plan 2021 ORNL/AF R&D Collaboration

“…A preliminary comparison showed that the LIS-HyMAP driven inundation is underestimated compared to the observation-based ORNL TRITON hindcast results Dullo et al [2021b], where ST4-VIC-RAPID driven TRITON produces higher flood inundation depths across the domain. The main difference is likely due to the lower simulated precipitation (i.e., modeled vs. ST4 observation) used to drive LIS-HyMAP.…”

“…In addition to the research tasks, we have also started to set up some modeling tools on Miller, the AF HPC11 system at ORNL, which will eventually be used to conduct the operational flood and inundation forecasting. Three peer-reviewed journal papers were accepted/published in the past project year (Morales-Hernández et al [2021], Dullo et al [2021b], Dullo et al [2021a]). In addition, Sharif et al [2020] received the Best Paper Award in the 2020 Platform for Advanced Scientific Computing Conference (PASC20).…”

“…To demonstrate the applicability of the targeted modeling framework, we conducted TRITON simulations using runoff and streamflow hindcast data provided by NASA and ERDC (i.e., LIS-HyMAP-NoahMP and LIS-HyMAP-JULES). We leveraged our existing TRITON implementation (Dullo et al [2021b]) developed for the simulation of the 2017 Hurricane Harvey flood event in the Houston, TX metropolitan area. We developed processing scripts to convert the outputs from LIS-HyMAP into the runoff and streamflow hydrographs inputs for TRITON.…”

A Framework for Mechanistic Flood Inundation Forecasting at the Metropolitan Scale

“…In fact, Dullo et al. (2021) also documented differences between Houston Metro bathymetry captured by a 10 m resolution DEM and estimates inferred from gage information. As a result, we applied a bathymetric error correction to the DEM as follows.…”

Hydraulic Numerical Simulations of La Sabana River Floodplain, Mexico, as a Tool for a Flood Terrain Response Analysis

“…The methodologies developed in recent decades to calculate rainfall thresholds responsible for triggering floods are based on the use of distributed and semi-distributed hydrological models [23,24]. The combination of a hydrological study and a hydraulic model not only allows to accurately predict the design hydrographs of the basin but, very important, consent to simulate flooding in the alluvial plain in order to analyze the specific terrain response to flooding [25,26]. This combined methodological approach is particularly useful in the case of ungauged rivers where in-situ measurements of river critical levels as well as flood susceptibility maps are lacking.…”