Numerical model for simulating shallow water hydrodynamics on the GPU using an Adaptive Mesh Refinement type grid. The model was designed with the goal of simulating inundation (Rain, river, storm-surge or tsunami). The model uses a Block Uniform Quadtree approach that runs on the GPU using variable resolution grid.
The core SWE engine and adaptivity has been inspired and taken from St Venant solver from Basilisk and the CUDA GPU memory model has been inspired by the work from Vacondio _et al._2017)
The model is under constant development with features added to extend the processes captured and simplify user inputs. Current development includes:
- New engine
- Culverts
- groundwater module
The code is open source under a GPL License:
For Windows users we make binaries/executable available for download in the release section.
MacOS and Linux users need to compile the code. Find compile guide here.
The simplest usage of BG_Flood is to move the executable (an accompanying DLLs for Windows users) to a working folder (e.g. BG_Flood\Examples\SimpleRain) and either launch from CLI:
./BG_FLood BG_param.txt
or by double clicking the executable (BG_Flood will automatically look for BG_param.txt)
Refer to Manual and examples to understand how to use the param file and parameters.
BG_Flood has 12+ internal tests to make sure the hydrodynamics engine and input work as expected.
Below is the result of all the tests (development branch):
To run the test yourself add test = xx where xx is the test number (1 to 14) to your param file.
Bosserelle C., Lane E., Harang A., (2021) BG-Flood: A GPU adaptive, open-source, general inundation hazard model. Proceedings of the Australasian Coasts & Ports 2021 Conference. PDF
Harang, A., Lane, E. M., Bosserelle, C., Dean, S., Cattoën, C., Pearson, R., Carey-Smith, T. Srinivasan, R. Shiona, H. Wilkins, M., Smart, G, Flood Hazard in Aotearoa New Zealand under Current and Future Climates (in press)
Pozo, A., Wilson, M., Katurji, M., Méndez, F. J., Bosserelle, C., Lane, E. (2026) Hybrid Hydrodynamic-Machine Learning Modelling for Rapid Flood Scenario Assessment: A Case Study in Aotearoa New Zealand. Journal of Flood Risk Management19, no. 2: e70206. https://doi.org/10.1111/jfr3.70206.
Paulik, R., Hosse, L., Pelmard, J., Bosserelle, C., Harang, A., Powell, J., Pearson, R., Carey-Smith, T., Lane, E., Scheele, F., Zorn, C., Wotherspoon, L., Foster, L. (2026) Evaluating New Zealand’s building risk to fluvial and pluvial flooding. Discover Hazards 2, 2
Xu Z., Bosserelle C., Lane E.,(2024) Nearfield effects of the 2022 Hunga-Tonga volcanic tsunami and implications for a volcanic eruption near the coast. Ocean Engineering 321, 120465
Welsh R., Williams S., Bosserelle C., Paulik R., Chan Ting J., Wild A., Talia L. (2023) Sea-Level Rise Effects on Changing Hazard Exposure to Far-Field Tsunamis in a Volcanic Pacific Island. J. Mar. Sci. Eng. 2023, 11, 945.
Sischka L.; Bosserelle C.; Williams S.; Ting J.C.; Paulik R.; Whitworth, M.; Talia L.; Viskovic P. (2022) Reconstructing the 26 June 1917 Samoa Tsunami Disaster. Appl. Sci. 2022, 12, 3389. https://doi.org/10.3390/app12073389
Bosserelle C., Williams S., Cheung K. F., Lay T., Yamazaki Y., Simi T., et al. (2020). Effects of source faulting and fringing reefs on the 2009 South Pacific Tsunami inundation in southeast Upolu, Samoa. Journal of Geophysical Research: Oceans, 125, e2020JC016537. https://doi.org/10.1029/2020JC016537