Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-353-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-353-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
13 Jan 2023
Methods for assessment of models |
| 13 Jan 2023
| 13 Jan 2023
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Nicolas Flipo
CORRESPONDING AUTHOR
Mines Paris, PSL University, Centre for geosciences and geoengineering, 77300 Fontainebleau, France
Nicolas Gallois
Mines Paris, PSL University, Centre for geosciences and geoengineering, 77300 Fontainebleau, France
Jonathan Schuite
TerraScience, 24 120 Terrasson-Lavilledieu, France
Mines Paris, PSL University, Centre for geosciences and geoengineering, 77300 Fontainebleau, France
Related authors
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
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This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Masihullah Hasanyar, Thomas Romary, Shuaitao Wang, and Nicolas Flipo
Biogeosciences, 20, 1621–1633, https://doi.org/10.5194/bg-20-1621-2023, https://doi.org/10.5194/bg-20-1621-2023, 2023
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The results of this study indicate that biodegradable dissolved organic matter is responsible for oxygen depletion at low flow during summer seasons when heterotrophic bacterial activity is so intense. Therefore, the dissolved organic matter must be well measured in the water monitoring networks in order to have more accurate water quality models. It also advocates for high-frequency data collection for better quantification of the uncertainties related to organic matter.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Masihullah Hasanyar, Thomas Romary, Shuaitao Wang, and Nicolas Flipo
Biogeosciences, 20, 1621–1633, https://doi.org/10.5194/bg-20-1621-2023, https://doi.org/10.5194/bg-20-1621-2023, 2023
Short summary
Short summary
The results of this study indicate that biodegradable dissolved organic matter is responsible for oxygen depletion at low flow during summer seasons when heterotrophic bacterial activity is so intense. Therefore, the dissolved organic matter must be well measured in the water monitoring networks in order to have more accurate water quality models. It also advocates for high-frequency data collection for better quantification of the uncertainties related to organic matter.
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Short summary
A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
A new approach is proposed to fit hydrological or land surface models, which suffer from large...
