Hyper-resolution 1D-2D urban flood modelling using LiDAR data and hybrid parallelization

Coupled 1D-2D modelling is a widely used approach to predict water movement in complicated surface and subsurface drainage systems in urban or peri-urban areas. In this study, a hybrid parallel code, H12, is developed for 1D-2D coupled urban flood modelling. Hybrid-1D-2D, or H12, enables street-reso...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2018-05, Vol.103, p.131-145
Hauptverfasser: Noh, Seong Jin, Lee, Jun-Hak, Lee, Seungsoo, Kawaike, Kenji, Seo, Dong-Jun
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Sprache:eng
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Zusammenfassung:Coupled 1D-2D modelling is a widely used approach to predict water movement in complicated surface and subsurface drainage systems in urban or peri-urban areas. In this study, a hybrid parallel code, H12, is developed for 1D-2D coupled urban flood modelling. Hybrid-1D-2D, or H12, enables street-resolving hyper-resolution simulation over a large area by combining Open Multi-Processing (OpenMP) and Message Passing Interface (MPI) parallelization. Variable grid sizing is adopted for detailed geometric representation of urban surfaces as well as efficient computation. To assess the capability of H12, simulation experiments were carried for the Johnson Creek Catchment (∼40 km2) in Arlington, Texas. The LiDAR-derived digital elevation model (DEM) and detailed land cover map at 1-m resolution are used to represent the terrain and urban features in flood modelling. Hybrid parallelization achieves up to a 79-fold reduction in simulation time compared to the serial run and is more efficient than either OpenMP or MPI alone especially in hyper-resolution simulations. •A hybrid parallel code, Hybrid-1D-2D, or H12, is developed for coupled 1D-2D urban flood modelling.•H12 enables street-resolving simulation based on LiDAR-based topography.•Variable grid sizing is used for efficient and accurate simulation in areas of interest.•Advantages of hybrid parallelization over OpenMP or MPI alone are analyzed.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2018.02.008