Articles | Volume 25, issue 3
https://doi.org/10.5194/hess-25-1307-2021
© 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-25-1307-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Mar 2021
Research article |
| 18 Mar 2021
| 18 Mar 2021
Climate change impacts model parameter sensitivity – implications for calibration strategy and model diagnostic evaluation
Hydrology and Quantitative Water Management, Wageningen University, Wageningen, the Netherlands
Björn Guse
GFZ German Research Centre for Geosciences, Section Hydrology, Potsdam, Germany
Christian-Albrechts-University of Kiel, Institute of Natural Resource Conservation, Department of Hydrology and Water Resources Management, Kiel, Germany
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Cited
18 citations as recorded by crossref.
- Temporal Scale‐Dependent Sensitivity Analysis for Hydrological Model Parameters Using the Discrete Wavelet Transform and Active Subspaces D. Bittner et al. https://doi.org/10.1029/2020WR028511
- Navigating Uncertainties in Quantifying Water Availability Amidst the Climate and Land Use Changes N. Devkota et al. https://doi.org/10.1007/s11269-025-04275-7
- Why do we have so many different hydrological models? A review based on the case of Switzerland P. Horton et al. https://doi.org/10.1002/wat2.1574
- Sensitivity of snow magnitude and duration to hydrology model parameters B. Singh et al. https://doi.org/10.1016/j.jhydrol.2024.132193
- Seasonality of Recharge Drives Spatial and Temporal Nitrate Removal in a Karst Conduit as Evidenced by Nitrogen Isotope Modeling A. Husic et al. https://doi.org/10.1029/2021JG006454
- Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient U. Sepúlveda et al. https://doi.org/10.5194/hess-26-3419-2022
- Investigating the spatiotemporal behavior of VIC model parameters over the Tibetan plateau via global sensitivity analysis and machine learning Y. Li et al. https://doi.org/10.1080/17538947.2026.2625537
- Climate Change Impacts on Groundwater Recharge in Cold and Humid Climates: Controlling Processes and Thresholds E. Dubois et al. https://doi.org/10.3390/cli10010006
- What controls the tail behaviour of flood series: rainfall or runoff generation? E. Macdonald et al. https://doi.org/10.5194/hess-28-833-2024
- Irrigation buffers climate influence: Stable parameter sensitivities in APSIM-wheat under warm-temperate monsoon conditions H. Wang et al. https://doi.org/10.1016/j.ecolmodel.2026.111586
- Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions K. Çallı et al. https://doi.org/10.1016/j.jhydrol.2023.129549
- Effect of increasing conceptual model detail on simulated crop yield-drainage base relations J. van den Brink et al. https://doi.org/10.1016/j.agwat.2026.110383
- Hydro-meteorological variability of the Barak River Basin using CMIP6 multimodel ensemble projection M. Turjo et al. https://doi.org/10.2166/wcc.2026.813
- Detecting the resilience of soil moisture dynamics to drought periods as a function of soil type and climatic region N. Aqel et al. https://doi.org/10.5194/hess-30-2523-2026
- Mitigating El Niño impacts on hydro-energy vulnerability through identifying resilient run-of-river small hydropower sites C. Thakur et al. https://doi.org/10.1016/j.ejrh.2023.101622
- Evaluating Seasonal Forecast Models for Cambodia’s Northern Tonle Sap Basin L. Brigadier et al. https://doi.org/10.1007/s13143-025-00393-9
- Rainfall and maximum temperature are dominant climatic factors influencing APSIM-Maize cultivar parameters sensitivity in semiarid regions X. Yang et al. https://doi.org/10.1016/j.eja.2024.127494
- What makes a robust calibration period? Insights into the effects of data properties O. Jaffar et al. https://doi.org/10.1080/02626667.2026.2619031
18 citations as recorded by crossref.
- Temporal Scale‐Dependent Sensitivity Analysis for Hydrological Model Parameters Using the Discrete Wavelet Transform and Active Subspaces D. Bittner et al. https://doi.org/10.1029/2020WR028511
- Navigating Uncertainties in Quantifying Water Availability Amidst the Climate and Land Use Changes N. Devkota et al. https://doi.org/10.1007/s11269-025-04275-7
- Why do we have so many different hydrological models? A review based on the case of Switzerland P. Horton et al. https://doi.org/10.1002/wat2.1574
- Sensitivity of snow magnitude and duration to hydrology model parameters B. Singh et al. https://doi.org/10.1016/j.jhydrol.2024.132193
- Seasonality of Recharge Drives Spatial and Temporal Nitrate Removal in a Karst Conduit as Evidenced by Nitrogen Isotope Modeling A. Husic et al. https://doi.org/10.1029/2021JG006454
- Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient U. Sepúlveda et al. https://doi.org/10.5194/hess-26-3419-2022
- Investigating the spatiotemporal behavior of VIC model parameters over the Tibetan plateau via global sensitivity analysis and machine learning Y. Li et al. https://doi.org/10.1080/17538947.2026.2625537
- Climate Change Impacts on Groundwater Recharge in Cold and Humid Climates: Controlling Processes and Thresholds E. Dubois et al. https://doi.org/10.3390/cli10010006
- What controls the tail behaviour of flood series: rainfall or runoff generation? E. Macdonald et al. https://doi.org/10.5194/hess-28-833-2024
- Irrigation buffers climate influence: Stable parameter sensitivities in APSIM-wheat under warm-temperate monsoon conditions H. Wang et al. https://doi.org/10.1016/j.ecolmodel.2026.111586
- Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions K. Çallı et al. https://doi.org/10.1016/j.jhydrol.2023.129549
- Effect of increasing conceptual model detail on simulated crop yield-drainage base relations J. van den Brink et al. https://doi.org/10.1016/j.agwat.2026.110383
- Hydro-meteorological variability of the Barak River Basin using CMIP6 multimodel ensemble projection M. Turjo et al. https://doi.org/10.2166/wcc.2026.813
- Detecting the resilience of soil moisture dynamics to drought periods as a function of soil type and climatic region N. Aqel et al. https://doi.org/10.5194/hess-30-2523-2026
- Mitigating El Niño impacts on hydro-energy vulnerability through identifying resilient run-of-river small hydropower sites C. Thakur et al. https://doi.org/10.1016/j.ejrh.2023.101622
- Evaluating Seasonal Forecast Models for Cambodia’s Northern Tonle Sap Basin L. Brigadier et al. https://doi.org/10.1007/s13143-025-00393-9
- Rainfall and maximum temperature are dominant climatic factors influencing APSIM-Maize cultivar parameters sensitivity in semiarid regions X. Yang et al. https://doi.org/10.1016/j.eja.2024.127494
- What makes a robust calibration period? Insights into the effects of data properties O. Jaffar et al. https://doi.org/10.1080/02626667.2026.2619031
Saved (final revised paper)
Latest update: 30 May 2026
Short summary
Certain hydrological processes become more or less relevant when the climate changes. This should also be visible in the models that are used for long-term predictions of river flow as a consequence of climate change. We investigated this using three different models. The change in relevance should be reflected in how the parameters of the models are determined. In the different models, different processes become more relevant in the future: they disagree with each other.
Certain hydrological processes become more or less relevant when the climate changes. This...
