Self-guided decision support groundwater modelling with Python
The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.
Citation Information
Publication Year | 2024 |
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Title | Self-guided decision support groundwater modelling with Python |
DOI | 10.21105/jose.00240 |
Authors | Rui Hugman, Jeremy T. White, Michael N. Fienen, Brioch Hemmings, Katie Markovich |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | Journal of Open Source Education |
Index ID | 70261835 |
Record Source | USGS Publications Warehouse |
USGS Organization | Upper Midwest Water Science Center |