Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise
<p>Estimating the impact of different sources of uncertainty along the modelling chain is an important skill graduates are expected to have. Broadly speaking, educators can cover uncertainty in hydrological modelling by differentiating uncertainty in data, model parameters and model structure....
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-06-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://hess.copernicus.org/articles/26/3299/2022/hess-26-3299-2022.pdf |
| _version_ | 1811332887678550016 |
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| author | W. J. M. Knoben D. Spieler |
| author_facet | W. J. M. Knoben D. Spieler |
| author_sort | W. J. M. Knoben |
| collection | DOAJ |
| description | <p>Estimating the impact of different sources of uncertainty along the modelling chain is an important skill graduates are expected to have. Broadly speaking, educators can cover uncertainty in hydrological modelling by differentiating uncertainty in data, model parameters and model structure. This provides students with insights on the impact of uncertainties on modelling results and thus on the usability of the acquired model simulations for decision making. A survey among teachers in the Earth and environmental sciences showed that model structural uncertainty is the least represented uncertainty group in teaching. This paper introduces a computational exercise that introduces students to the basics of model structure uncertainty through two ready-to-use modelling experiments. These experiments require either Matlab or Octave, and use the open-source Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) and the open-source Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) data set. The exercise is short and can easily be integrated into an existing hydrological curriculum, with only a limited time investment needed to introduce the topic of model structure uncertainty and run the exercise. Two trial applications at the Technische Universität Dresden (Germany) showed that the exercise can be completed in two afternoons or four 90 min sessions and that the provided setup effectively transfers the intended insights about model structure uncertainty.</p> |
| first_indexed | 2024-04-13T16:43:47Z |
| format | Article |
| id | doaj.art-8205c356e92b480e9b7b64a206b2a9fa |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-04-13T16:43:47Z |
| publishDate | 2022-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-8205c356e92b480e9b7b64a206b2a9fa2022-12-22T02:39:08ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382022-06-01263299331410.5194/hess-26-3299-2022Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exerciseW. J. M. Knoben0D. Spieler1Coldwater Laboratory, University of Saskatchewan, Canmore, Alberta, CanadaInstitute of Hydrology and Meteorology, Technische Universität Dresden, Dresden, Germany<p>Estimating the impact of different sources of uncertainty along the modelling chain is an important skill graduates are expected to have. Broadly speaking, educators can cover uncertainty in hydrological modelling by differentiating uncertainty in data, model parameters and model structure. This provides students with insights on the impact of uncertainties on modelling results and thus on the usability of the acquired model simulations for decision making. A survey among teachers in the Earth and environmental sciences showed that model structural uncertainty is the least represented uncertainty group in teaching. This paper introduces a computational exercise that introduces students to the basics of model structure uncertainty through two ready-to-use modelling experiments. These experiments require either Matlab or Octave, and use the open-source Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) and the open-source Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) data set. The exercise is short and can easily be integrated into an existing hydrological curriculum, with only a limited time investment needed to introduce the topic of model structure uncertainty and run the exercise. Two trial applications at the Technische Universität Dresden (Germany) showed that the exercise can be completed in two afternoons or four 90 min sessions and that the provided setup effectively transfers the intended insights about model structure uncertainty.</p>https://hess.copernicus.org/articles/26/3299/2022/hess-26-3299-2022.pdf |
| spellingShingle | W. J. M. Knoben D. Spieler Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise Hydrology and Earth System Sciences |
| title | Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise |
| title_full | Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise |
| title_fullStr | Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise |
| title_full_unstemmed | Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise |
| title_short | Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise |
| title_sort | teaching hydrological modelling illustrating model structure uncertainty with a ready to use computational exercise |
| url | https://hess.copernicus.org/articles/26/3299/2022/hess-26-3299-2022.pdf |
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