[REVIEW]: Self-Guided Decision Support Groundwater Modelling with Python

[editorialbot]

Submitting author: @rhugman (Rui Hugman)
Repository: https://github.com/gmdsi/GMDSI_notebooks/
Branch with paper.md (empty if default branch): main
Version: v1.0
Editor: @kls2177
Reviewers: @codyalbertross, @incsanchezro
Archive: Pending
Paper kind: learning module

Status

Status badge code:

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Markdown: [![status](https://jose.theoj.org/papers/a9ae783c659717e67235744d65973365/status.svg)](https://jose.theoj.org/papers/a9ae783c659717e67235744d65973365)

Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@codyalbertross & @incsanchezro, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://openjournals.readthedocs.io/en/jose/reviewer_guidelines.html. Any questions/concerns please let @kls2177 know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @codyalbertross

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=1.86 s (236.1 files/s, 245809.7 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
CSV                             22             10              0         196080
Python                         312          21537          54873         127736
Markdown                        44           6809              0          17172
Jupyter Notebook                41              0          23849           4828
TeX                              8             14              0           3224
ReasonML                         1              2              0           1437
TOML                             3             17              4            216
YAML                             7             25             36            136
Unity-Prefab                     1              0              0             66
JSON                             1              0              0             49
-------------------------------------------------------------------------------
SUM:                           440          28414          78762         350944
-------------------------------------------------------------------------------

Commit count by author:

    68	Mike Fienen
    52	jdub
    32	rhugman
    12	briochh
     8	unknown
     2	mnfienen
     1	Brioch Hemmings
     1	J Dub
     1	edesousa-intera

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1016/j.envsoft.2016.08.017 is OK
- 10.5066/P9AUZMI7 is OK
- 10.5066/F76Q1VQV is OK
- 10.1111/gwat.13129 is OK
- 10.5194/hess-20-3739-2016 is OK

MISSING DOIs

- 10.3133/tm7c26 may be a valid DOI for title: Approaches to highly parameterized inversion: PEST...
- 10.1016/j.envsoft.2016.08.017 may be a valid DOI for title: A python framework for environmental model uncerta...
- 10.3389/feart.2020.00050 may be a valid DOI for title: Toward reproducible environmental modeling for dec...
- 10.1016/j.envsoft.2021.105022 may be a valid DOI for title: Towards improved environmental modeling outcomes: ...
- 10.1016/j.envsoft.2022.105316 may be a valid DOI for title: A model-independent tool for evolutionary constrai...
- No DOI given, and none found for title: PEST and Its Utility Support Software
- No DOI given, and none found for title: PEST: a unique computer program for model-independ...
- 10.3389/978-2-8325-3581-3 may be a valid DOI for title: Rapid, Reproducible, and Robust Environmental Mode...
- No DOI given, and none found for title: Where companies go wrong with learning and develop...

INVALID DOIs

- https://doi.org/10.1111/gwat.12413 is INVALID because of 'https://doi.org/' prefix

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 3093

✅ The paper includes a Statement of need section

[editorialbot]

License info:

🟡 License found: GNU General Public License v3.0 (Check here for OSI approval)

[kls2177]

Hi @codyalbertross, @incsanchezro, I am checking-in to see how your reviews are going. Please post your comments in this issue linked to your comments that are directly tied to the resource repo. Here is an example of how you can post your review

[incsanchezro]

I am writing to provide feedback on your paper titled "Self-Guided Decision Support Groundwater Modelling with Python.". Following the JOSE guidelines for reviewers, I would like to confirm that I have no conflicts of interest in reviewing your work. Additionally, I affirm that I have adhered to the review code of conduct of JOSE as of April 2024.

Upon reviewing the paper and associated source code, I find that the overall quality of the learning framework meets essential criteria. I congratulate the authors for making the source code readily available on the specified GitHub repository. The inclusion of a generic plain-text LICENSE file reflects a commitment to open-source principles and provides clarity regarding usage rights. However, I recommend providing explicit identification of the software version as v1.0 to enhance clarity for users.

Furthermore, I appreciate the integrity with which authorship and contributions to the module have been managed. The primary author's significant and visible contributions demonstrate a profound commitment to the project's success and broader educational goals. While some authors may not have been actively engaged in the GitHub repository, their contributions are appropriately acknowledged in the written paper.

Overall, I recommend this paper for publication with attention to the comments listed below. I acknowledge the author's efforts in developing this valuable learning framework and look forward to seeing its continued evolution.

To the authors and JOSE editor, I extend my gratitude for the opportunity to review this work. Please do not hesitate to reach out if you require further clarification or feedback. While I will happily review the reviewed version of this publication.

SPECIFIC COMMENTS AVAILABLE HERE

1. JOSE Review - comments on "Self-Guided Decision Support Groundwater Modelling with Python " [Documentation section] #244

2. JOSE Review - comments on "Self-Guided Decision Support Groundwater Modelling with Python " [Pedagogy / Instructional design ] #245

3. JOSE Review - comments on "Self-Guided Decision Support Groundwater Modelling with Python " [JOSE paper] #246

[incsanchezro]

Dear @kls2177
Please find the reviewer comments for the paper "Self-Guided Decision Support Groundwater Modelling with Python" in the comment above ( >> #240 (comment) ). Please accept my apologies for the delay.

[codyalbertross]

Review checklist for @codyalbertross

Conflict of interest

• As the reviewer I confirm that I have read the JOSE conflict of interest policy and that there are no conflicts of interest for me to review this work.

Code of Conduct

• I confirm that I read and will adhere to the JOSE code of conduct.

General checks

• Repository: Is the source for this learning module available at the https://github.com/gmdsi/GMDSI_notebooks/?
• License: Does the repository contain a plain-text LICENSE file with the contents of a standard license? (OSI-approved for code, Creative Commons for content)
• Version: Does the release version given match the repository release?
• Authorship: Has the submitting author (@rhugman) made visible contributions to the module? Does the full list of authors seem appropriate and complete?

Documentation

• A statement of need: Do the authors clearly state the need for this module and who the target audience is?
• Installation instructions: Is there a clearly stated list of dependencies?
• Usage: Does the documentation explain how someone would adopt the module, and include examples of how to use it?
• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the module 2) Report issues or problems with the module 3) Seek support

Pedagogy / Instructional design (Work-in-progress: reviewers, please comment!)

• Learning objectives: Does the module make the learning objectives plainly clear? (We don't require explicitly written learning objectives; only that they be evident from content and design.)
• Content scope and length: Is the content substantial for learning a given topic? Is the length of the module appropriate?
• Pedagogy: Does the module seem easy to follow? Does it observe guidance on cognitive load? (working memory limits of 7 +/- 2 chunks of information)
• Content quality: Is the writing of good quality, concise, engaging? Are the code components well crafted? Does the module seem complete?
• Instructional design: Is the instructional design deliberate and apparent? For example, exploit worked-example effects; effective multi-media use; low extraneous cognitive load.

JOSE paper

• Authors: Does the paper.md file include a list of authors with their affiliations?
• A statement of need: Does the paper clearly state the need for this module and who the target audience is?
• Description: Does the paper describe the learning materials and sequence?
• Does it describe how it has been used in the classroom or other settings, and how someone might adopt it?
• Could someone else teach with this module, given the right expertise?
• Does the paper tell the "story" of how the authors came to develop it, or what their expertise is?
• References: Do all archival references that should have a DOI list one (e.g., papers, datasets, software)?

[codyalbertross]

@kls2177

Thank you for your patience with my review.

Self-Guided Decision Support Groundwater Modelling with Python is a valuable contribution and satisfies a need for concise and informed guidance on PEST and pyEMU. I agree with @incsanchezro regarding the organization of the workbook and the effort put forward by the authors to develop and improve GMDSI.

I found that the detail and theoretical background was exceptional and that the workbook followed a logical trajectory that is aligned with a typical workflow.

Overall, I believe that this work is suitable for publication and that the authors seem ready to take feedback from end-users to continuously improve their experience.