the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Sep 2022
A comprehensive open-source course for teaching applied hydrological modelling in Central Asia
Abstract. Numerical modelling is often used for climate impact studies in water resources management. It is, however, not yet highly accessible to many students of hydrology in Central Asia. One big hurdle for new learners is the scripting requirement for the preparation of relevant data prior to the actual modelling. We present a robust, open-source workflow and comprehensive teaching material that aims at bridging the gap between theoretical hydrological modelling know how and applied modelling for climate impact studies in Central Asia. The teaching material has been refined during two consecutive years and is being taken up by several professors teaching hydrological modelling in Central Asia.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(7421 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(7421 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-966', Hongyi Li, 21 Oct 2022
This study describes a comprehensive open-source course for teaching hydrologic modeling. It appears that the course has been well developed and tested, hence providing good experience that would benefit the others who teach hydrologic modeling like myself. It is very well written and easy to follow. I recommend acceptance as is.
Hong-Yi Li
Citation: https://doi.org/10.5194/egusphere-2022-966-RC1 -
AC1: 'Reply on RC1', Beatrice Marti, 05 Dec 2022
Dear Hong-Yi Li, thank you for taking the time to review the article and for your comments.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC1
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AC1: 'Reply on RC1', Beatrice Marti, 05 Dec 2022
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CC1: 'Comment on egusphere-2022-966', Zhanar Raimbekova, 28 Nov 2022
This course was used by me for the "Modeling of hydrological processes in GIS" course for 4-year BSc students of speciality "Hydrology" during the fall semester of 2022-2023 at Al-Farabi Kazakh National University, Kazakhstan. Open source workflow was very helpful for the learning of modeling steps in RSMinerve program, also for coding develop in R-Studio. It is very well written and easy to follow. According to clear guideliness students could creat a model of Tentek River catchment (Jetisu Alatau Mt., Kazakhstan) in RSMinerve using by just HBV. I recommend this open-source course is a necessary tool for incorporating MSc and PhD courses for using other models in RSMinerve as students of these degrees are more experienced in GIS and other modeling programs.
Citation: https://doi.org/10.5194/egusphere-2022-966-CC1 -
AC2: 'Reply on CC1', Beatrice Marti, 05 Dec 2022
Dear Zhanar Raimbekova, we are very glad that the material is useful for your work. Thank you for your comment.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC2
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AC2: 'Reply on CC1', Beatrice Marti, 05 Dec 2022
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CC2: 'Comment on egusphere-2022-966', Shamshagul Mashtayeva, 29 Nov 2022
I would like to thank the authors of the course "A comprehensive open-source course for teaching applied hydrological modelling in Central Asia" for developing a much-needed course for all students of the BSc in Hydrology of the countries of Central Asia. As a lecture teaching the course "Modeling of Hydrological processes" for students of the BSc in Hydrology at the Eurasian National University, Astana, Kazakhstan I am glad that my students can study this course on their own. The implementation of such a course into the educational process of Higher Education in Kazakhstan has begun in the last few years, since our graduated hydrologists must be able to work with various Hydrological models for effective water management between all water consumers, as well as qualitatively predict water resources due to climate change. As an educator, I am very pleased that a course like this has been developed that allows students to independently find high-quality public available data and effectively use open source watershed characterization software.
Since this academic year grad students for MS in Hydrology program have begun to study the RS Minerva program, and this course will make it easier for them to quickly master and apply in practice.
Citation: https://doi.org/10.5194/egusphere-2022-966-CC2 -
AC3: 'Reply on CC2', Beatrice Marti, 05 Dec 2022
Dear Shamshagul Mashtayeva, thank you for your comment. We are glad that the course material is of use to you and to your students. Please let us keep in touch to exchange experiences with the course material.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC3
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AC3: 'Reply on CC2', Beatrice Marti, 05 Dec 2022
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RC2: 'Comment on egusphere-2022-966', Anonymous Referee #2, 04 Dec 2022
The effectively organized and facilitated well-run learning course is summarized in this paper. By combining theory with practice, the course helps students better understand the mechanism of hydrological process and develop intellectual skills of creative thinking and problem solving. Students conduct hydrological simulations by evaluating the actual conditions and characteristics of case study basins. Additionally, the data applied in the course (such as the glacier thickness data) are up-to-date and of high quality.
I notice that the course applied Quantile Mapping to correct, To the best of my knowledge, new technologies (such as Quantile Delta Mapping, Quantile Delta Mapping, and Multivariate Bias Correction with N-dimensional probability density function transform) are available today. Introducing such technologies is valuable and will raise more interest in Climate Projections.
Overall, I believe this course would have high educational impacts. As an educator teaching the course "Advanced Hydrology" for students at Tsinghua University, I am glad that this course can provide students with a publicly available learning source on hydrological modelling. And I would recommend this course to others.Citation: https://doi.org/10.5194/egusphere-2022-966-RC2 -
AC4: 'Reply on RC2', Beatrice Marti, 05 Dec 2022
Dear reviewer, thank you for taking the time to critically review the article. We appreciate your input and we will look into more advanced bias correction methods to include in the next iteration of the course development.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC4
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AC4: 'Reply on RC2', Beatrice Marti, 05 Dec 2022
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-966', Hongyi Li, 21 Oct 2022
This study describes a comprehensive open-source course for teaching hydrologic modeling. It appears that the course has been well developed and tested, hence providing good experience that would benefit the others who teach hydrologic modeling like myself. It is very well written and easy to follow. I recommend acceptance as is.
Hong-Yi Li
Citation: https://doi.org/10.5194/egusphere-2022-966-RC1 -
AC1: 'Reply on RC1', Beatrice Marti, 05 Dec 2022
Dear Hong-Yi Li, thank you for taking the time to review the article and for your comments.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC1
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AC1: 'Reply on RC1', Beatrice Marti, 05 Dec 2022
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CC1: 'Comment on egusphere-2022-966', Zhanar Raimbekova, 28 Nov 2022
This course was used by me for the "Modeling of hydrological processes in GIS" course for 4-year BSc students of speciality "Hydrology" during the fall semester of 2022-2023 at Al-Farabi Kazakh National University, Kazakhstan. Open source workflow was very helpful for the learning of modeling steps in RSMinerve program, also for coding develop in R-Studio. It is very well written and easy to follow. According to clear guideliness students could creat a model of Tentek River catchment (Jetisu Alatau Mt., Kazakhstan) in RSMinerve using by just HBV. I recommend this open-source course is a necessary tool for incorporating MSc and PhD courses for using other models in RSMinerve as students of these degrees are more experienced in GIS and other modeling programs.
Citation: https://doi.org/10.5194/egusphere-2022-966-CC1 -
AC2: 'Reply on CC1', Beatrice Marti, 05 Dec 2022
Dear Zhanar Raimbekova, we are very glad that the material is useful for your work. Thank you for your comment.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC2
-
AC2: 'Reply on CC1', Beatrice Marti, 05 Dec 2022
-
CC2: 'Comment on egusphere-2022-966', Shamshagul Mashtayeva, 29 Nov 2022
I would like to thank the authors of the course "A comprehensive open-source course for teaching applied hydrological modelling in Central Asia" for developing a much-needed course for all students of the BSc in Hydrology of the countries of Central Asia. As a lecture teaching the course "Modeling of Hydrological processes" for students of the BSc in Hydrology at the Eurasian National University, Astana, Kazakhstan I am glad that my students can study this course on their own. The implementation of such a course into the educational process of Higher Education in Kazakhstan has begun in the last few years, since our graduated hydrologists must be able to work with various Hydrological models for effective water management between all water consumers, as well as qualitatively predict water resources due to climate change. As an educator, I am very pleased that a course like this has been developed that allows students to independently find high-quality public available data and effectively use open source watershed characterization software.
Since this academic year grad students for MS in Hydrology program have begun to study the RS Minerva program, and this course will make it easier for them to quickly master and apply in practice.
Citation: https://doi.org/10.5194/egusphere-2022-966-CC2 -
AC3: 'Reply on CC2', Beatrice Marti, 05 Dec 2022
Dear Shamshagul Mashtayeva, thank you for your comment. We are glad that the course material is of use to you and to your students. Please let us keep in touch to exchange experiences with the course material.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC3
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AC3: 'Reply on CC2', Beatrice Marti, 05 Dec 2022
-
RC2: 'Comment on egusphere-2022-966', Anonymous Referee #2, 04 Dec 2022
The effectively organized and facilitated well-run learning course is summarized in this paper. By combining theory with practice, the course helps students better understand the mechanism of hydrological process and develop intellectual skills of creative thinking and problem solving. Students conduct hydrological simulations by evaluating the actual conditions and characteristics of case study basins. Additionally, the data applied in the course (such as the glacier thickness data) are up-to-date and of high quality.
I notice that the course applied Quantile Mapping to correct, To the best of my knowledge, new technologies (such as Quantile Delta Mapping, Quantile Delta Mapping, and Multivariate Bias Correction with N-dimensional probability density function transform) are available today. Introducing such technologies is valuable and will raise more interest in Climate Projections.
Overall, I believe this course would have high educational impacts. As an educator teaching the course "Advanced Hydrology" for students at Tsinghua University, I am glad that this course can provide students with a publicly available learning source on hydrological modelling. And I would recommend this course to others.Citation: https://doi.org/10.5194/egusphere-2022-966-RC2 -
AC4: 'Reply on RC2', Beatrice Marti, 05 Dec 2022
Dear reviewer, thank you for taking the time to critically review the article. We appreciate your input and we will look into more advanced bias correction methods to include in the next iteration of the course development.
Citation: https://doi.org/10.5194/egusphere-2022-966-AC4
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AC4: 'Reply on RC2', Beatrice Marti, 05 Dec 2022
Peer review completion
Journal article(s) based on this preprint
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Beatrice Sabine Marti
Aidar Zhumabaev
Tobias Siegfried
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(7421 KB) - Metadata XML