ANUGA (pronounced "AHnooGAH") is open-source software for the simulation of the shallow water equation, in particular it can be used to model tsunamis and floods.

ANUGA is a python 3 package with some C and Cython extensions (and an optional fortran extension).

ANUGA was created in a collaboration by Geoscience Australia and Mathematical Sciences Institute at the Australian National University, though now it is further developed and maintained by a community of volunteers.

Copyright Commonwealth of Australia (Geoscience Australia) and Australian National University 2004-Now

ANUGA is available from either https://github.com/anuga-community/anuga_core or https://github.com/GeoscienceAustralia/anuga_core.

The Python 3.x version is the default and available in the main branches of both repositories.

If you rely on the old Python 2.7 version, it is available in branches named anuga_py2.

The python 3 version of ANUGA will continue to be developed and the most up-to-date versions will be available from the anuga-community repository.

If you use conda to provide your python environment, then you can install anuga from the conda-forge channel as follows. First setup the conda-forge channel:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, anuga can be installed with conda:

conda install anuga

For more installation instructions, see https://anuga.readthedocs.io/en/latest/installation.html

Click the Open in GitHub Codespaces badge above to launch ANUGA in a fully configured cloud environment — no local install required. The environment installs all dependencies and compiles the C/Cython extensions automatically.

Once the Codespace is ready, open any notebook and select the Python (anuga_env) kernel from the kernel picker in the top-right corner.

ANUGA documentation is available via "read the docs" at

https://anuga.readthedocs.io

Also you can obtain help via the old user_manual

Also helpful information is available online at

http://anuga.anu.edu.au

A collection of online jupyter notebooks which can run under google's colab environment can be found at:

https://github.com/anuga-community/anuga-clinic

You can subscribe to our mailing via:

https://lists.sourceforge.net/lists/listinfo/anuga-user

and send questions using the address

anuga-user@lists.sourceforge.net

You can also submit issues to:

https://github.com/anuga-community/anuga_core/issues

• http://anuga.anu.edu.au: Collection of information, talks and papers about ANUGA.
• https://en.wikipedia.org/wiki/ANUGA_Hydro: The Wikipedia site for ANUGA.
• https://github.com/anuga-community/anuga_core: The active GitHub repository for ANUGA.
• https://github.com/GeoscienceAustralia/anuga_core: Mirror GitHub repository for ANUGA.
• https://github.com/anuga-community/anuga-viewer: Viewer for animating the ANUGA sww output files.

The latest development version of ANUGA's sources are is available at:

https://github.com/anuga-community/anuga_core

They can be downloaded as a zip file or using the Git client as follows

git clone https://github.com/anuga-community/anuga_core #(for read only)
git clone git@github.com:anuga-community/anuga_core.git #(to contribute)

For the latter option see e.g. https://help.github.com/articles/adding-a-new-ssh-key-to-your-github-account/ for instructions on how to authenticate using ssh keys.

To search for bugs or report them, please use the ANUGA's Bug Tracker at:

https://github.com/anuga-community/anuga_core/issues

If you would like to take part in ANUGA development, take a look at CONTRIBUTING.rst.

ANUGA was created by Geoscience Australia and the Mathematical Sciences Institute at the Australian National University, and is developed and maintained by a community of volunteers.

The GPU and multicore solver introduced in ANUGA 4.0 (the unified compute mode and its OpenMP target offloading) was developed in collaboration with the Centre for Development of Advanced Computing (C-DAC), India, and the National Computational Infrastructure (NCI), Australia. The C-DAC collaboration is part of a catchment flood prediction project aimed at two-day flood forecasts, and grew out of GPU hackathons held from 2023; NCI's Gadi supercomputer provided the GPU systems on which the work was developed, tested and benchmarked. We thank Samir Shaikh, Shweta Das and Rutvik Gulhane (C-DAC) and Jorge Luis Gálvez Vallejo (NCI) for their contributions, and both organisations for their support.

See the file LICENSE.txt for information on the history of this software, terms & conditions for usage, and a DISCLAIMER OF ALL WARRANTIES.

At the Australian National University: Stephen Roberts Lead Developer <stephen.roberts@anu.edu.au>

At Geoscience Australia: Gareth Davies Developer <gareth.davies@ga.gov.au>

ANUGA Community: Ole Nielsen Architect and Developer <ole.moller.nielsen@gmail.com>