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Sharif, Md Bulbul

Publications and source records attributed to Sharif, Md Bulbul.

TRITON: A Multi-GPU open source 2D hydrodynamic flood model

A new open source multi-GPU 2D flood model called TRITON is presented in this work. The model solves the 2D shallow water equations with source terms using a time-explicit first order upwind scheme based on an Augmented Roe's solver that incorporates a careful estimation of bed strengths and a local implicit formulation of friction terms. Here, the scheme is demonstrated to be first order accurate, robust and able to solve for flows under various conditions. TRITON is implemented such that the model effectively utilizes heterogeneous architectures, from single to multiple CPUs and GPUs. Different test cases are shown to illustrate the capabilities and performance of the model, showing promising runtimes for large spatial and temporal scales when leveraging the computer power of GPUs. Under this hardware configuration, communication and input/output subroutines may impact the scalability. The code is developed under an open source license and can be freely downloaded in https://code.ornl.gov/hydro/triton.

2D flood model↗

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 ~1%, the flood extents by 65km 2 , 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.

54 ENVIRONMENTAL SCIENCES↗