wflow consists of a set of Python programs that can be run on the command line and perform hydrological simulations. The models are based on the PCRaster Python framework. In wflow this framework is extended (the wf_DynamicFramework) so that models build using the framework can be controlled using the API. Links to BMI, OpenMI and OpenDAP have been made.
A link to the latest version can always be found at https://github.com/openstreams/wflow
Reference documentation at:
Go to https://github.com/openstreams/wflow. There you can download the source or a release. Also make sure you get the required third party models first (see below).
The master branch can change rapidly (and break functionality without warning) so please use one of the releases if possible. If you want to adjust things in the model(s) we assume you should be comfortable using the master branch.
The main dependencies for wflow are an installation of Python 3.6+, and PCRaster 4.2+. Only 64 bit OS/Python is supported.
Installing Python
For Python we recommend using the Anaconda Distribution for Python 3, which is available for download from https://www.anaconda.com/download/. The installer gives the option to add python to your PATH environment variable. We will assume in the instructions below that it is available in the path, such that python, pip, and conda are all available from the command line.
Note that there is no hard requirement specifically for Anaconda's Python, but often it makes installation of required dependencies easier using the conda package manager.
Installing pcraster
- Download pcraster from http://pcraster.geo.uu.nl/ website (version 4.2+)
- Follow the installation instructions at http://pcraster.geo.uu.nl/quick-start-guide/
The easiest and most robust way to install wflow is by installing it in a separate conda environment. In the root repository directory there is an environment.yml file. This file lists all dependencies, except PCRaster, which must be installed manually as described above.
Run this command to start installing wflow with all dependencies:
conda env create -f environment.yml
This creates a new environment with the name wflow. To activate this environment in a session, run:
activate wflow
Now you should be able to start this environment's Python with python, try import wflow to see if the package is installed.
More details on how to work with conda environments can be found here: https://conda.io/docs/user-guide/tasks/manage-environments.html
Besides the recommended conda environment setup described above, you can also install wflow with pip. For the more difficult to install Python dependencies, it is best to use the conda package manager:
conda install numpy scipy gdal netcdf4 cftime pyproj python-dateutil
This will install the latest release of wflow:
pip install wflow
If you are planning to make changes and contribute to the development of wflow, it is best to make a git clone of the repository, and do a editable install in the location of you clone. This will not move a copy to your Python installation directory, but instead create a link in your Python installation pointing to the folder you installed it from, such that any changes you make there are directly reflected in your install.
git clone https://github.com/openstreams/wflow.gitcd wflowpip install -e .
Alternatively, if you want to avoid using git and simply want to test the latest version from the master branch, you can replace the first line with downloading a zip archive from GitHub: https://github.com/openstreams/wflow/archive/master.zip
To check it the install is successful, go to the examples directory and run the following command:
python -m wflow.wflow_sbm -C wflow_rhine_sbm -R testing
This should run without errors.
Although you can get everything with the python packages bundled with most linux distributions (CentOS, Ubuntu, etc) we have found that the easiest way is to install the linux version of Anaconda and use the conda tool to install all requirements apart from pcraster which has to be installed manually.
Since version 4.2, compiled versions of PCRaster are no longer distributed, so it will need to be built following the instructions given at http://pcraster.geo.uu.nl/getting-started/pcraster-on-linux/
Unfortunately there is no pcraster build for osx yet. If anybody wants to pick this up please let the guys at pcraster.eu know!
- The stats.py script was made by Keith Cherkauer (https://engineering.purdue.edu/~cherkaue/software.htm)
- pcraster is developed and maintained by Utrecht University (http://www.pcraster.eu)
- netCDF4 is developed by unidata (http://unidata.github.io/netcdf4-python/)
- GDAL is released under an X/MIT style Open Source license by the Open Source Geospatial Foundation (http://www.gdal.org).
See doi of the release you use. If you use a snapshot of the development (without a DOI) cite as follows:
Jaap Schellekens, Willem van Verseveld, Tanja Euser, Hessel Winsemius, Christophe Thiange, Laurène Bouaziz, Daniel Tollenaar, Sander de Vries, Albrecht Weerts, YEAR. openstreams/wflow: unstable-master. https://github.com/openstreams/wflow, obtained: DATE_OF_DOWNLOAD
Jaap Schellekens, Willem van Verseveld, Tanja Euser, Hessel Winsemius, Christophe Thiange, Laurène Bouaziz, Daniel Tollenaar, Sander de Vries, 2016. openstreams/wflow: 2016.04 Test release. doi:10.5281/zenodo.167057
Jaap Schellekens, Willem van Verseveld, Tanja Euser, Hessel Winsemius, Christophe Thiange, Laurène Bouaziz, Daniel Tollenaar, Sander de Vries, 2016. openstreams/wflow: 2016.03. doi:10.5281/zenodo.155389