ChatGPT examples in the hydrological sciences
Authors: | |
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Owners: | Dylan Irvine |
Type: | Resource |
Storage: | The size of this resource is 1.3 MB |
Created: | Sep 16, 2023 at 10:04 p.m. |
Last updated: | Oct 09, 2023 at 2:56 p.m. (Metadata update) |
Published date: | Oct 09, 2023 at 2:56 p.m. |
DOI: | 10.4211/hs.fc0552275ea14c7082218c42ebd63da6 |
Citation: | See how to cite this resource |
Sharing Status: | Published |
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Views: | 1047 |
Downloads: | 73 |
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Abstract
ChatGPT has forever changed the way that many industries operate. Much of the focus of Artificial Intelligence (AI) has been on their ability to generate text. However, it is likely that their ability to generate computer codes and scripts will also have a major impact. We demonstrate the use of ChatGPT to generate Python scripts to perform hydrological analyses and highlight the opportunities, limitations and risks that AI poses in the hydrological sciences.
Here, we provide four worked examples of the use of ChatGPT to generate scripts to conduct hydrological analyses. We also provide a full list of the libraries available to the ChatGPT Advanced Data Analysis plugin (only available in the paid version). These files relate to a manuscript that is to be submitted to Hydrological Processes. The authors of the manuscript are Dylan J. Irvine, Landon J.S. Halloran and Philip Brunner.
If you find these examples useful and/or use them, we would appreciate if you could cite the associated publication in Hydrological Processes. Details to be made available upon final publication.
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People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
Name | Organization | Address | Phone | Author Identifiers |
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Landon Halloran | Centre for Hydrogeology and Geothermics, University of Neuchâtel |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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