Articles | Volume 25, issue 5
https://doi.org/10.5194/hess-25-2353-2021
© Author(s) 2021. 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-25-2353-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 May 2021
Research article |
| 03 May 2021
| 03 May 2021
Projected changes in Rhine River flood seasonality under global warming
Institute of Environmental Science and Geography, University of Potsdam, Karl-Liebknecht-Straße 24–25, 14476 Potsdam, Germany
Axel Bronstert
Institute of Environmental Science and Geography, University of Potsdam, Karl-Liebknecht-Straße 24–25, 14476 Potsdam, Germany
Gerd Bürger
Institute of Environmental Science and Geography, University of Potsdam, Karl-Liebknecht-Straße 24–25, 14476 Potsdam, Germany
Oldrich Rakovec
UFZ-Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Prague – Suchdol, 165 00, Czech Republic
Viewed
Total article views: 7,473 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 23 Nov 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,469 | 1,897 | 107 | 7,473 | 142 | 168 |
- HTML: 5,469
- PDF: 1,897
- XML: 107
- Total: 7,473
- BibTeX: 142
- EndNote: 168
Total article views: 6,530 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 May 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 4,942 | 1,484 | 104 | 6,530 | 129 | 160 |
- HTML: 4,942
- PDF: 1,484
- XML: 104
- Total: 6,530
- BibTeX: 129
- EndNote: 160
Total article views: 943 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 23 Nov 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 527 | 413 | 3 | 943 | 13 | 8 |
- HTML: 527
- PDF: 413
- XML: 3
- Total: 943
- BibTeX: 13
- EndNote: 8
Viewed (geographical distribution)
Total article views: 7,473 (including HTML, PDF, and XML)
Thereof 7,174 with geography defined
and 299 with unknown origin.
Total article views: 6,530 (including HTML, PDF, and XML)
Thereof 6,311 with geography defined
and 219 with unknown origin.
Total article views: 943 (including HTML, PDF, and XML)
Thereof 863 with geography defined
and 80 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
36 citations as recorded by crossref.
- Rhine flood stories: Spatio‐temporal analysis of historic and projected flood genesis in the Rhine River basin E. Rottler et al. https://doi.org/10.1002/hyp.14918
- Transboundary water security challenges in the Upper Heilong-Amur River Basin under climate stress: Insights from a hydrological perspective K. Zhang et al. https://doi.org/10.1016/j.geosus.2026.100450
- Assessment of snow model uncertainty in relation to the effect of a 1 °C warming using the snow modelling framework openAMUNDSEN E. Rottler et al. https://doi.org/10.5194/tc-20-2351-2026
- Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters L. Bouaziz et al. https://doi.org/10.5194/hess-26-1295-2022
- Understanding the flood seasonality in a Himalayan River Basin under changing climate P. Singhal et al. https://doi.org/10.1007/s00704-025-05585-x
- Diverging trends in large floods across Europe in a warming climate B. Fang et al. https://doi.org/10.1038/s43247-025-02734-y
- Weakened Snowmelt Contribution to Floods in a Climate-Changed Tibetan Basin L. Niu et al. https://doi.org/10.3390/w17040507
- Machine learning-enhanced flood forecasting using snow water equivalent: validation across multiple flood events A. Dash & E. McBean https://doi.org/10.2166/wcc.2026.348
- Catchment response to climatic variability: implications for root zone storage and streamflow predictions N. Tempel et al. https://doi.org/10.5194/hess-28-4577-2024
- Spatiotemporal hydroclimatic characteristics of arid and semi-arid river basin under climate change: a case study of Iraq F. Saeed et al. https://doi.org/10.1007/s12517-022-10548-x
- Melting Alpine Water Towers Aggravate Downstream Low Flows: A Stress‐Test Storyline Approach M. van Tiel et al. https://doi.org/10.1029/2022EF003408
- Future changes in water resources, floods and droughts under the joint impact of climate and land-use changes in the Chao Phraya basin, Thailand S. Yang et al. https://doi.org/10.1016/j.jhydrol.2023.129454
- Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning W. Liang et al. https://doi.org/10.1038/s41612-025-00918-z
- Seasonal diversity of global flood changes and their drivers X. Gu et al. https://doi.org/10.1016/j.jhydrol.2025.133976
- Flood Seasonality Analysis in Iran: A Circular Statistics Approach M. Bagheri-Gavkosh & S. Hosseini https://doi.org/10.1061/JHYEFF.HEENG-5786
- Climate impact on flood changes – an Austrian-Ukrainian comparison S. Snizhko et al. https://doi.org/10.2478/johh-2023-0017
- Evolution of flood generating processes under climate change in France Y. Tramblay et al. https://doi.org/10.5194/hess-29-7023-2025
- An integrated view on the uncertainties of sea-level rise, hazards and impacts, and adaptation T. Hermans et al. https://doi.org/10.1017/cft.2025.10003
- Real-time peak flow prediction based on signal matching X. Wang et al. https://doi.org/10.1016/j.envsoft.2023.105926
- Increased high flows in Germany under 1.5 K, 2.0 K and 3.0 K warming based on a large regional climate model ensemble A. Chandrasekar et al. https://doi.org/10.1007/s10584-026-04165-w
- River flooding mechanisms and their changes in Europe revealed by explainable machine learning S. Jiang et al. https://doi.org/10.5194/hess-26-6339-2022
- Streamflow simulations for the extreme drought event of 2018 on the Rhine River Basin using WRF-Hydro A. Campoverde et al. https://doi.org/10.1080/15715124.2025.2581608
- Challenges in the attribution of river flood events P. Scussolini et al. https://doi.org/10.1002/wcc.874
- The effects of changing channel retention: Unravelling the mechanisms behind the spatial and temporal trends of suspended sediment in the Rhine basin J. Cox et al. https://doi.org/10.1002/esp.5929
- Machine Learning Reveals a Significant Shift in Water Regime Types Due to Projected Climate Change G. Ayzel https://doi.org/10.3390/ijgi10100660
- Uncertainties of Annual Suspended Sediment Transport Estimates Driven by Temporal Variability A. Slabon & T. Hoffmann https://doi.org/10.1029/2022WR032628
- Continuous Negotiation in Climate Adaptation: The Challenge of Co-Evolution for the Capability Approach to Justice L. Brackel https://doi.org/10.3390/su132313072
- Manifestations of the long-term transformation of the lower Elbe channel in Czechia and opportunities for its restoration J. Hradecký et al. https://doi.org/10.37040/geografie.2024.012
- Future Changes in High and Low Flows under the Impacts of Climate and Land Use Changes in the Jiulong River Basin of Southeast China S. Yang et al. https://doi.org/10.3390/atmos13020150
- Modeling Land Use Change in Sana’a City of Yemen with MOLUSCE E. Alshari et al. https://doi.org/10.1155/2022/7419031
- Insights into the impact of light-absorbing impurities on radiative forcing and snowmelt in the Ili Basin in Central Asia B. Wu et al. https://doi.org/10.1016/j.envres.2025.121768
- IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling B. Mohammadi et al. https://doi.org/10.1038/s41598-022-16215-1
- Present and Future Hydrological Response to Land Use and Climate Change in the Jhikhukhola Watershed in Nepal R. Prajapati et al. https://doi.org/10.1061/JSWBAY.SWENG-627
- Hydrologic response of arid and semi-arid river basins in Iraq under a changing climate F. Saeed et al. https://doi.org/10.2166/wcc.2022.418
- Spatio‐temporal wet snow dynamics from model simulations and remote sensing: A case study from the Rofental, Austria E. Rottler et al. https://doi.org/10.1002/hyp.15279
- Improving hydrological climate impact assessments using multirealizations from a global climate model F. Sperna Weiland et al. https://doi.org/10.1111/jfr3.12787
36 citations as recorded by crossref.
- Rhine flood stories: Spatio‐temporal analysis of historic and projected flood genesis in the Rhine River basin E. Rottler et al. https://doi.org/10.1002/hyp.14918
- Transboundary water security challenges in the Upper Heilong-Amur River Basin under climate stress: Insights from a hydrological perspective K. Zhang et al. https://doi.org/10.1016/j.geosus.2026.100450
- Assessment of snow model uncertainty in relation to the effect of a 1 °C warming using the snow modelling framework openAMUNDSEN E. Rottler et al. https://doi.org/10.5194/tc-20-2351-2026
- Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters L. Bouaziz et al. https://doi.org/10.5194/hess-26-1295-2022
- Understanding the flood seasonality in a Himalayan River Basin under changing climate P. Singhal et al. https://doi.org/10.1007/s00704-025-05585-x
- Diverging trends in large floods across Europe in a warming climate B. Fang et al. https://doi.org/10.1038/s43247-025-02734-y
- Weakened Snowmelt Contribution to Floods in a Climate-Changed Tibetan Basin L. Niu et al. https://doi.org/10.3390/w17040507
- Machine learning-enhanced flood forecasting using snow water equivalent: validation across multiple flood events A. Dash & E. McBean https://doi.org/10.2166/wcc.2026.348
- Catchment response to climatic variability: implications for root zone storage and streamflow predictions N. Tempel et al. https://doi.org/10.5194/hess-28-4577-2024
- Spatiotemporal hydroclimatic characteristics of arid and semi-arid river basin under climate change: a case study of Iraq F. Saeed et al. https://doi.org/10.1007/s12517-022-10548-x
- Melting Alpine Water Towers Aggravate Downstream Low Flows: A Stress‐Test Storyline Approach M. van Tiel et al. https://doi.org/10.1029/2022EF003408
- Future changes in water resources, floods and droughts under the joint impact of climate and land-use changes in the Chao Phraya basin, Thailand S. Yang et al. https://doi.org/10.1016/j.jhydrol.2023.129454
- Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning W. Liang et al. https://doi.org/10.1038/s41612-025-00918-z
- Seasonal diversity of global flood changes and their drivers X. Gu et al. https://doi.org/10.1016/j.jhydrol.2025.133976
- Flood Seasonality Analysis in Iran: A Circular Statistics Approach M. Bagheri-Gavkosh & S. Hosseini https://doi.org/10.1061/JHYEFF.HEENG-5786
- Climate impact on flood changes – an Austrian-Ukrainian comparison S. Snizhko et al. https://doi.org/10.2478/johh-2023-0017
- Evolution of flood generating processes under climate change in France Y. Tramblay et al. https://doi.org/10.5194/hess-29-7023-2025
- An integrated view on the uncertainties of sea-level rise, hazards and impacts, and adaptation T. Hermans et al. https://doi.org/10.1017/cft.2025.10003
- Real-time peak flow prediction based on signal matching X. Wang et al. https://doi.org/10.1016/j.envsoft.2023.105926
- Increased high flows in Germany under 1.5 K, 2.0 K and 3.0 K warming based on a large regional climate model ensemble A. Chandrasekar et al. https://doi.org/10.1007/s10584-026-04165-w
- River flooding mechanisms and their changes in Europe revealed by explainable machine learning S. Jiang et al. https://doi.org/10.5194/hess-26-6339-2022
- Streamflow simulations for the extreme drought event of 2018 on the Rhine River Basin using WRF-Hydro A. Campoverde et al. https://doi.org/10.1080/15715124.2025.2581608
- Challenges in the attribution of river flood events P. Scussolini et al. https://doi.org/10.1002/wcc.874
- The effects of changing channel retention: Unravelling the mechanisms behind the spatial and temporal trends of suspended sediment in the Rhine basin J. Cox et al. https://doi.org/10.1002/esp.5929
- Machine Learning Reveals a Significant Shift in Water Regime Types Due to Projected Climate Change G. Ayzel https://doi.org/10.3390/ijgi10100660
- Uncertainties of Annual Suspended Sediment Transport Estimates Driven by Temporal Variability A. Slabon & T. Hoffmann https://doi.org/10.1029/2022WR032628
- Continuous Negotiation in Climate Adaptation: The Challenge of Co-Evolution for the Capability Approach to Justice L. Brackel https://doi.org/10.3390/su132313072
- Manifestations of the long-term transformation of the lower Elbe channel in Czechia and opportunities for its restoration J. Hradecký et al. https://doi.org/10.37040/geografie.2024.012
- Future Changes in High and Low Flows under the Impacts of Climate and Land Use Changes in the Jiulong River Basin of Southeast China S. Yang et al. https://doi.org/10.3390/atmos13020150
- Modeling Land Use Change in Sana’a City of Yemen with MOLUSCE E. Alshari et al. https://doi.org/10.1155/2022/7419031
- Insights into the impact of light-absorbing impurities on radiative forcing and snowmelt in the Ili Basin in Central Asia B. Wu et al. https://doi.org/10.1016/j.envres.2025.121768
- IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling B. Mohammadi et al. https://doi.org/10.1038/s41598-022-16215-1
- Present and Future Hydrological Response to Land Use and Climate Change in the Jhikhukhola Watershed in Nepal R. Prajapati et al. https://doi.org/10.1061/JSWBAY.SWENG-627
- Hydrologic response of arid and semi-arid river basins in Iraq under a changing climate F. Saeed et al. https://doi.org/10.2166/wcc.2022.418
- Spatio‐temporal wet snow dynamics from model simulations and remote sensing: A case study from the Rofental, Austria E. Rottler et al. https://doi.org/10.1002/hyp.15279
- Improving hydrological climate impact assessments using multirealizations from a global climate model F. Sperna Weiland et al. https://doi.org/10.1111/jfr3.12787
Saved (final revised paper)
Latest update: 01 Jun 2026
Short summary
The mesoscale hydrological model (mHM) forced with an ensemble of climate projection scenarios was used to assess potential future changes in flood seasonality in the Rhine River basin. Results indicate that future changes in flood characteristics are controlled by increases in precipitation sums and diminishing snowpacks. The decreases in snowmelt can counterbalance increasing precipitation, resulting in only small and transient changes in streamflow maxima.
The mesoscale hydrological model (mHM) forced with an ensemble of climate projection scenarios...
