Articles | Volume 21, issue 11
https://doi.org/10.5194/hess-21-5443-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5443-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
06 Nov 2017
Research article |
| 06 Nov 2017
Streamflow characteristics from modeled runoff time series – importance of calibration criteria selection
Department of Geography, University of Zurich, Zurich, Switzerland
Marc J. P. Vis
Department of Geography, University of Zurich, Zurich, Switzerland
Rodney R. Knight
U.S. Geological Survey Lower Mississippi-Gulf Water Science Center,
640 Grassmere Park, Suite 100, Nashville, TN 37211, USA
Jan Seibert
Department of Geography, University of Zurich, Zurich, Switzerland
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Department of Physical Geography, Stockholm University, Stockholm, Sweden
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- Exploring parameter (dis)agreement due to calibration metric selection in conceptual rainfall–runoff models E. Muñoz-Castro et al. https://doi.org/10.1080/02626667.2023.2231434
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- Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models M. Brunner et al. https://doi.org/10.5194/hess-25-105-2021
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- Delineating modelling uncertainty in river flow indicators with representative parameter sets A. Sikorska-Senoner https://doi.org/10.1016/j.advwatres.2021.104024
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- Modulation of the goodness of fit in hydrological modelling based on inner balance errors F. Pellicer-Martínez et al. https://doi.org/10.1371/journal.pone.0260117
35 citations as recorded by crossref.
- Mapping (dis)agreement in hydrologic projections L. Melsen et al. https://doi.org/10.5194/hess-22-1775-2018
- A multi‐objective approach to select hydrological models and constrain structural uncertainties for climate impact assessments D. Saavedra et al. https://doi.org/10.1002/hyp.14446
- Riverine phytoplankton functional groups response to multiple stressors variously depending on hydrological periods Y. Qu et al. https://doi.org/10.1016/j.ecolind.2018.12.049
- Dry, drier, driest: Differentiating flow patterns across a gradient of intermittency B. Kelly & L. Bruckerhoff https://doi.org/10.1002/rra.4289
- Simulating streamflow in ungauged basins under a changing climate: The importance of landscape characteristics C. Teutschbein et al. https://doi.org/10.1016/j.jhydrol.2018.03.060
- Multivariate calibration can increase simulated discharge uncertainty and model equifinality S. Pool et al. https://doi.org/10.5194/hess-30-2797-2026
- Probabilistic Predictions of Ecologically Relevant Hydrologic Indices Using a Hydrological Model J. Hernandez‐Suarez & A. Nejadhashemi https://doi.org/10.1029/2021WR031104
- Exploring parameter (dis)agreement due to calibration metric selection in conceptual rainfall–runoff models E. Muñoz-Castro et al. https://doi.org/10.1080/02626667.2023.2231434
- Calibration of hydrological models for ecologically relevant streamflow predictions: a trade-off between fitting well to data and estimating consistent parameter sets? T. Hallouin et al. https://doi.org/10.5194/hess-24-1031-2020
- Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models M. Brunner et al. https://doi.org/10.5194/hess-25-105-2021
- A hybrid time- and signature-domain Bayesian inference framework for calibration of hydrological models: a case study in the Ren River basin in China S. Liu et al. https://doi.org/10.1007/s00477-022-02282-3
- Future evolution and uncertainty of river flow regime change in a deglaciating river basin J. Mackay et al. https://doi.org/10.5194/hess-23-1833-2019
- Delineating modelling uncertainty in river flow indicators with representative parameter sets A. Sikorska-Senoner https://doi.org/10.1016/j.advwatres.2021.104024
- Hunting for Information in Streamflow Signatures to Improve Modelled Drainage R. Schneider et al. https://doi.org/10.3390/w14010110
- Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships M. Eddy et al. https://doi.org/10.1002/eco.2387
- Flood predictions from metrics to classes by multiple machine learning algorithms coupling with clustering-deduced membership degree X. Zhai et al. https://doi.org/10.1007/s11442-026-2442-8
- Reproducing different types of changes in hydrological indicators with rainfall-runoff models C. Massmann https://doi.org/10.2166/nh.2020.073
- Assessing the impacts of groundwater abstractions on flow regime and stream biota: Combining SWAT-MODFLOW with flow-biota empirical models W. Liu et al. https://doi.org/10.1016/j.scitotenv.2019.135702
- On the selection of precipitation products for the regionalisation of hydrological model parameters O. Baez-Villanueva et al. https://doi.org/10.5194/hess-25-5805-2021
- EURO-CORDEX: A Multi-Model Ensemble Fit for Assessing Future Hydrological Change? G. Aitken et al. https://doi.org/10.3389/frwa.2022.804146
- When is a hydrological model sufficiently calibrated to depict flow preferences of riverine species? J. Kiesel et al. https://doi.org/10.1002/eco.2193
- Future hydrological constraints of the Montseny brook newt (Calotriton arnoldi) under changing climate and vegetation cover J. Ledesma et al. https://doi.org/10.1002/ece3.5506
- How to make advances in hydrological modelling K. Beven https://doi.org/10.2166/nh.2019.134
- The accuracy of ecological flow metrics derived using a physics‐based distributed rainfall–runoff model in the Great Plains, USA T. Worthington et al. https://doi.org/10.1002/eco.2090
- Subjective modeling decisions can significantly impact the simulation of flood and drought events L. Melsen et al. https://doi.org/10.1016/j.jhydrol.2018.11.046
- Replication of ecologically relevant hydrological indicators following a modified covariance approach to hydrological model parameterization A. Visser-Quinn et al. https://doi.org/10.5194/hess-23-3279-2019
- Uni- and multivariate bias adjustment of climate model simulations in Nordic catchments: Effects on hydrological signatures relevant for water resources management in a changing climate F. Tootoonchi et al. https://doi.org/10.1016/j.jhydrol.2023.129807
- Climate change impacts on ecologically relevant hydrological indicators in three catchments in three European ecoregions J. Kiesel et al. https://doi.org/10.1016/j.ecoleng.2018.12.019
- A novel multi-objective model calibration method for ecohydrological applications J. Hernandez-Suarez et al. https://doi.org/10.1016/j.envsoft.2021.105161
- A review of hydrologic signatures and their applications H. McMillan https://doi.org/10.1002/wat2.1499
- Can continuous simulation be used as an alternative for flood regionalisation? A large sample example from Chile P. Acuña & A. Pizarro https://doi.org/10.1016/j.jhydrol.2023.130118
- Dependence of flood peaks and volumes in modeled discharge time series: Effect of different uncertainty sources M. Brunner & A. Sikorska-Senoner https://doi.org/10.1016/j.jhydrol.2019.03.024
- Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. https://doi.org/10.5194/hess-27-4385-2023
- Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. https://doi.org/10.1002/wat2.1520
- Modulation of the goodness of fit in hydrological modelling based on inner balance errors F. Pellicer-Martínez et al. https://doi.org/10.1371/journal.pone.0260117
Saved (final revised paper)
Latest update: 05 Jun 2026
Short summary
This modeling study explores the effect of different model calibration criteria on the accuracy of simulated streamflow characteristics (SFCs). The results imply that one has to consider significant uncertainties when simulated time series are used to derive SFCs that were not included in the calibration. Thus, we strongly recommend calibrating the runoff model explicitly for the SFCs of interest. Our study helps improve the estimation of SFCs for ungauged catchments based on runoff models.
This modeling study explores the effect of different model calibration criteria on the accuracy...
