wsimod 0.4.0

WSIMOD is for simulating water quality and quantity

Welcome to WSIMOD

WSIMOD stands for the Water Systems Integrated Modelling framework.

The terrestrial water cycle is a highly interconnected system where the movement of water is affected by physical and human processes. Thus, environmental models may become inaccurate if they do not provide a complete picture of the water cycle, missing out on unexpected opportunities and omitting impacts that arise from complex interactions. WSIMOD is a modelling framework to integrate these different processes. It provides a message passing interface to enable different subsystem models to communicate water flux and water quality information between each other, and self-contained representations of the key parts of the water cycle (rivers, reservoirs, urban and rural hydrological catchments, treatment plants, and pipe networks). We created WSIMOD to enable a user greater flexibility in setting up their water cycle models, motivated by the abundance of non-textbook water systems that we have experienced in industry collaboration. The WSIMOD Python package provides tutorials and examples to help modellers create nodes, connect them with arcs, and create simulations.

You can access our documentation below or at https://imperialcollegelondon.github.io/wsi.

Requires: Python 3 (tested on versions >=3.7), tqdm, PyYAML, dill

Optional requirements to run demos: Pandas, GeoPandas, Matplotlib, Shapely

Please consider contributing and note the code of conduct

If you use WSIMOD, please make sure to cite.

Table Of Contents

The documentation follows the best practice for project documentation as described by Daniele Procida in the Diátaxis documentation framework and consists of:

1. About

2. Installation

3. Tutorials

4. How-To Guides

5. Component library

6. API reference

7. Quickstart

8. Coverage

Installation

Install WSIMOD directly from GitHub

pip install https://github.com/ImperialCollegeLondon/wsi/archive/refs/heads/main.zip

Use [demos] to include the demos and tutorials.

pip install https://github.com/ImperialCollegeLondon/wsi/archive/refs/heads/main.zip
pip install wsimod[demos]

If you want to make changes to WSIMOD you can download/clone this folder, navigate to it, and run:

pip install -e .[dev]

or (with demos)

pip install -e .[dev,demos]

How to cite WSIMOD

If you would like to use our software, please cite it using the following:

Dobson, B., Liu, L. and Mijic, A. (2023) ‘Water Systems Integrated Modelling framework, WSIMOD: A Python package for integrated modelling of water quality and quantity across the water cycle’, Journal of Open Source Software. The Open Journal, 8(83), p. 4996. doi: 10.21105/joss.04996.

Find the bibtex citation below:

@article{Dobson2023,
        doi = {10.21105/joss.04996},
        url = {https://doi.org/10.21105/joss.04996},
        year = {2023},
        publisher = {The Open Journal},
        volume = {8},
        number = {83},
        pages = {4996},
        author = {Barnaby Dobson and Leyang Liu and Ana Mijic},
        title = {Water Systems Integrated Modelling framework, WSIMOD: A Python package for integrated modelling of water quality and quantity across the water cycle},
        journal = {Journal of Open Source Software}
        }

Acknowledgements

WSIMOD was developed by Barnaby Dobson and Leyang Liu. Theoretical support was provided by Ana Mijic. Testing the WSIMOD over a variety of applications has been performed by Fangjun Peng, Vladimir Krivstov and Samer Muhandes. Software development support was provided by Imperial College's Research Software Engineering service, in particular from Diego Alonso and Dan Davies.

We are incredibly grateful for the detailed software reviews provided by Taher Chegini and Joshua Larsen and editing by Chris Vernon. Their suggestions have significantly improved WSIMOD.

The design of WSIMOD was significantly influenced by CityDrain3, OpenMI, Belete, Voinov and Laniak, (2017), and smif.

We acknowledge funding from the CAMELLIA project (Community Water Management for a Liveable London), funded by the Natural Environment Research Council (NERC) under grant NE/S003495/1.