Articles | Volume 27, issue 19
https://doi.org/10.5194/hess-27-3505-2023
© 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/hess-27-3505-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2023
Research article |
| 06 Oct 2023
| 06 Oct 2023
To what extent does river routing matter in hydrological modeling?
Nicolás Cortés-Salazar
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Nicolás Vásquez
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Naoki Mizukami
National Center for Atmospheric Research, Boulder, CO, USA
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Advanced Mining Technology Center, Universidad de Chile, Santiago, Chile
Ximena Vargas
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
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Cited
16 citations as recorded by crossref.
- The matrix-vector differential-form Muskingum method for river network routing J. Zhao et al. https://doi.org/10.1016/j.advwatres.2026.105300
- What can hydrological modelling gain from spatially explicit parameterization and multi-gauge calibration? X. Zheng et al. https://doi.org/10.5194/hess-30-2493-2026
- Time-Variant Instantaneous Unit Hydrograph Based on Machine Learning Pretraining and Rainfall Spatiotemporal Patterns W. Dong et al. https://doi.org/10.3390/w17152216
- A methodology to estimate Probable Maximum Precipitation (PMP) under climate change using a numerical weather model Y. Hiraga et al. https://doi.org/10.1016/j.jhydrol.2024.132659
- Coupled hydrologic and hydraulic modeling for a lowland river basin in China J. Zhang et al. https://doi.org/10.1016/j.jhydrol.2024.132470
- Impact of Spatial Resolution on River Flow Simulation Based on the Total Runoff Integrating Pathway (TRIP) Model M. Kim et al. https://doi.org/10.3390/atmos16091083
- A GNN routing module is all you need for LSTM Rainfall–Runoff models H. Mosaffa et al. https://doi.org/10.5194/hess-30-2079-2026
- Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis F. Lema et al. https://doi.org/10.5194/hess-29-1981-2025
- Representing subgrid precipitation variability in snowpack and hydrological modeling: Is adding complexity worth it? F. Givovich et al. https://doi.org/10.1016/j.jhydrol.2025.134038
- Runoff Prediction of Tunxi Basin under Projected Climate Changes Based on Lumped Hydrological Models with Various Model Parameter Optimization Strategies B. Yan et al. https://doi.org/10.3390/su16166897
- Increasing water stress in Chile revealed by novel datasets of water availability, land use and water use J. Boisier et al. https://doi.org/10.5194/hess-29-5185-2025
- Simulation of the effects of land cover, soil degradation, and rainfall on runoff from a small tropical catchment using a minimally calibrated distributed model B. Zwartendijk et al. https://doi.org/10.1016/j.jhydrol.2026.135259
- Calibrating a large-domain land/hydrology process model in the age of AI: the SUMMA CAMELS emulator experiments M. Farahani et al. https://doi.org/10.5194/hess-29-4515-2025
- Analysis of runoff dynamics and flood formation: An investigation through an explainable deep learning framework T. Wang et al. https://doi.org/10.1016/j.gloplacha.2026.105435
- A hybrid hydrologic modeling framework-role of spatial resolution, calibration approaches and error modeling S. Guniganti et al. https://doi.org/10.1016/j.ejrh.2025.103053
- Development of a variable instantaneous unit hydrograph based on quantified rainfall spatial distribution W. Dong et al. https://doi.org/10.1016/j.jhydrol.2025.134497
16 citations as recorded by crossref.
- The matrix-vector differential-form Muskingum method for river network routing J. Zhao et al. https://doi.org/10.1016/j.advwatres.2026.105300
- What can hydrological modelling gain from spatially explicit parameterization and multi-gauge calibration? X. Zheng et al. https://doi.org/10.5194/hess-30-2493-2026
- Time-Variant Instantaneous Unit Hydrograph Based on Machine Learning Pretraining and Rainfall Spatiotemporal Patterns W. Dong et al. https://doi.org/10.3390/w17152216
- A methodology to estimate Probable Maximum Precipitation (PMP) under climate change using a numerical weather model Y. Hiraga et al. https://doi.org/10.1016/j.jhydrol.2024.132659
- Coupled hydrologic and hydraulic modeling for a lowland river basin in China J. Zhang et al. https://doi.org/10.1016/j.jhydrol.2024.132470
- Impact of Spatial Resolution on River Flow Simulation Based on the Total Runoff Integrating Pathway (TRIP) Model M. Kim et al. https://doi.org/10.3390/atmos16091083
- A GNN routing module is all you need for LSTM Rainfall–Runoff models H. Mosaffa et al. https://doi.org/10.5194/hess-30-2079-2026
- Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis F. Lema et al. https://doi.org/10.5194/hess-29-1981-2025
- Representing subgrid precipitation variability in snowpack and hydrological modeling: Is adding complexity worth it? F. Givovich et al. https://doi.org/10.1016/j.jhydrol.2025.134038
- Runoff Prediction of Tunxi Basin under Projected Climate Changes Based on Lumped Hydrological Models with Various Model Parameter Optimization Strategies B. Yan et al. https://doi.org/10.3390/su16166897
- Increasing water stress in Chile revealed by novel datasets of water availability, land use and water use J. Boisier et al. https://doi.org/10.5194/hess-29-5185-2025
- Simulation of the effects of land cover, soil degradation, and rainfall on runoff from a small tropical catchment using a minimally calibrated distributed model B. Zwartendijk et al. https://doi.org/10.1016/j.jhydrol.2026.135259
- Calibrating a large-domain land/hydrology process model in the age of AI: the SUMMA CAMELS emulator experiments M. Farahani et al. https://doi.org/10.5194/hess-29-4515-2025
- Analysis of runoff dynamics and flood formation: An investigation through an explainable deep learning framework T. Wang et al. https://doi.org/10.1016/j.gloplacha.2026.105435
- A hybrid hydrologic modeling framework-role of spatial resolution, calibration approaches and error modeling S. Guniganti et al. https://doi.org/10.1016/j.ejrh.2025.103053
- Development of a variable instantaneous unit hydrograph based on quantified rainfall spatial distribution W. Dong et al. https://doi.org/10.1016/j.jhydrol.2025.134497
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
This paper shows how important river models can be for water resource applications that involve...
