Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1779-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-1779-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Apr 2019
Research article |
| 02 Apr 2019
| 02 Apr 2019
The benefits of spatial resolution increase in global simulations of the hydrological cycle evaluated for the Rhine and Mississippi basins
Meteorology and Air Quality Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Chiel C. van Heerwaarden
Meteorology and Air Quality Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Albrecht H. Weerts
Hydrology and Quantitative Water Management Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Deltares, P.O. Box 177, 2600 MH Delft, the Netherlands
Wilco Hazeleger
Meteorology and Air Quality Group, Wageningen University, Droevendaalsesteeg 4, 6708 BP Wageningen, the Netherlands
Netherlands eScience Center (NLeSC), Science Park 140, 1098 XG Amsterdam, the Netherlands
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17 citations as recorded by crossref.
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- Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate V. Levizzani & E. Cattani 10.3390/rs11192301
- Sensors prioritisation for hydrological forecasting based on interpretable machine learning A. Menapace et al. 10.1016/j.jhydrol.2025.134015
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- Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale L. Guillaumot et al. 10.5194/gmd-15-7099-2022
- Regional ensemble of CMIP6 global climate models for Sakha (Yakutia) Republic, Northern Eurasia N. Tananaev 10.1016/j.polar.2024.101066
- Multi-model driven by diverse precipitation datasets increases confidence in identifying dominant factors for runoff change in a subbasin of the Qaidam Basin of China A. Lv et al. 10.1016/j.scitotenv.2021.149831
- Exploring Afro-Asian water fluxes in CMIP5 and CMIP6 models: Present-day evaluation and future projections T. Adeliyi et al. 10.1016/j.scitotenv.2025.179374
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- Spatial and temporal analysis and trends of extreme precipitation over the Mississippi River Basin, USA during 1988–2017 A. Dommo et al. 10.1016/j.ejrh.2024.101954
- 100-Year Lower Mississippi Floods in a Global Climate Model: Characteristics and Future Changes K. van der Wiel et al. 10.1175/JHM-D-18-0018.1
16 citations as recorded by crossref.
- Decline in Terrestrial Moisture Sources of the Mississippi River Basin in a Future Climate I. Benedict et al. 10.1175/JHM-D-19-0094.1
- Evaluating the Water Cycle Over CONUS at the Watershed Scale for the Energy Exascale Earth System Model Version 1 (E3SMv1) Across Resolutions B. Harrop et al. 10.1029/2022MS003490
- Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate V. Levizzani & E. Cattani 10.3390/rs11192301
- Sensors prioritisation for hydrological forecasting based on interpretable machine learning A. Menapace et al. 10.1016/j.jhydrol.2025.134015
- Digital twins of the Earth with and for humans W. Hazeleger et al. 10.1038/s43247-024-01626-x
- The role of spatial and temporal model resolution in a flood event storyline approach in western Norway N. Schaller et al. 10.1016/j.wace.2020.100259
- Review of approaches for selection and ensembling of GCMs K. Raju & D. Kumar 10.2166/wcc.2020.128
- Quantifying uncertainties in temperature projections: A factorial-analysis-based multi-ensemble downscaling (FAMED) method Y. Liu et al. 10.1016/j.atmosres.2020.105241
- A 10 km North American precipitation and land-surface reanalysis based on the GEM atmospheric model N. Gasset et al. 10.5194/hess-25-4917-2021
- Climate change multi-model projections in CMIP6 scenarios in Central Hokkaido, Japan S. Peng et al. 10.1038/s41598-022-27357-7
- Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale L. Guillaumot et al. 10.5194/gmd-15-7099-2022
- Regional ensemble of CMIP6 global climate models for Sakha (Yakutia) Republic, Northern Eurasia N. Tananaev 10.1016/j.polar.2024.101066
- Multi-model driven by diverse precipitation datasets increases confidence in identifying dominant factors for runoff change in a subbasin of the Qaidam Basin of China A. Lv et al. 10.1016/j.scitotenv.2021.149831
- Exploring Afro-Asian water fluxes in CMIP5 and CMIP6 models: Present-day evaluation and future projections T. Adeliyi et al. 10.1016/j.scitotenv.2025.179374
- A first attempt to model global hydrology at hyper-resolution B. van Jaarsveld et al. 10.5194/esd-16-29-2025
- Spatial and temporal analysis and trends of extreme precipitation over the Mississippi River Basin, USA during 1988–2017 A. Dommo et al. 10.1016/j.ejrh.2024.101954
1 citations as recorded by crossref.
Discussed (final revised paper)
Latest update: 14 Sep 2025
Short summary
The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is increasing. This model study examines the benefits of a very high-resolution GCM and GHM in representing the hydrological cycle in the Rhine and Mississippi basins. We find that a higher-resolution GCM results in an improved precipitation budget, and therefore an improved hydrological cycle for the Rhine. For the Mississippi, no substantial improvements are found with increased resolution.
The spatial resolution of global climate models (GCMs) and global hydrological models (GHMs) is...
