Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1453-2019
© 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-23-1453-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Mar 2019
Research article |
| 14 Mar 2019
| 14 Mar 2019
Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River
Bart van Osnabrugge
CORRESPONDING AUTHOR
Deltares, Operational Water Management Department, Delft, the Netherlands
Wageningen University, Hydrology and Quantitative Water Management Group, Wageningen, the Netherlands
Remko Uijlenhoet
Wageningen University, Hydrology and Quantitative Water Management Group, Wageningen, the Netherlands
Albrecht Weerts
Deltares, Operational Water Management Department, Delft, the Netherlands
Wageningen University, Hydrology and Quantitative Water Management Group, Wageningen, the Netherlands
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Cited
17 citations as recorded by crossref.
- A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolution J. Buitink et al. https://doi.org/10.5194/gmd-13-6093-2020
- Coupled dominant factors analysis, dual attention deep learning, and uncertainty quantification for long-term pan evaporation ensemble prediction in the Wuding River Basin, China Z. Cui et al. https://doi.org/10.1016/j.ejrh.2026.103323
- Response of global evaporation to major climate modes in historical and future Coupled Model Intercomparison Project Phase 5 simulations T. Le & D. Bae https://doi.org/10.5194/hess-24-1131-2020
- A Vision for Hydrological Prediction D. Lavers et al. https://doi.org/10.3390/atmos11030237
- Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting Q. Yang et al. https://doi.org/10.5194/hess-26-941-2022
- Scaling Point‐Scale (Pedo)transfer Functions to Seamless Large‐Domain Parameter Estimates for High‐Resolution Distributed Hydrologic Modeling: An Example for the Rhine River R. Imhoff et al. https://doi.org/10.1029/2019WR026807
- Operational low-flow forecasting using LSTMs J. Deng et al. https://doi.org/10.3389/frwa.2023.1332678
- Enhancing flood event predictions: Multi-objective calibration using gauge and satellite data S. Gegenleithner et al. https://doi.org/10.1016/j.jhydrol.2024.130879
- stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts D. Asfaw et al. https://doi.org/10.5194/gmd-16-557-2023
- AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment Y. Guo et al. https://doi.org/10.5194/hess-25-5951-2021
- Large‐Sample Evaluation of Radar Rainfall Nowcasting for Flood Early Warning R. Imhoff et al. https://doi.org/10.1029/2021WR031591
- 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
- Investigating Nature-based Solutions Potential to Mitigate Urban Pluvial Flooding: A Case Study in Bochum, Germany E. Hartkopf et al. https://doi.org/10.14796/JWMM.C548
- Improving hydrological climate impact assessments using multirealizations from a global climate model F. Sperna Weiland et al. https://doi.org/10.1111/jfr3.12787
- Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin D. Purnamasari et al. https://doi.org/10.5194/hess-29-1483-2025
- Comparison of probabilistic post-processing approaches for improving numerical weather prediction-based daily and weekly reference evapotranspiration forecasts H. Medina & D. Tian https://doi.org/10.5194/hess-24-1011-2020
- Evaluating satellite-based and reanalysis precipitation datasets with gauge-observed data and hydrological modeling in the Xihe River Basin, China N. Wang et al. https://doi.org/10.1016/j.atmosres.2019.104746
17 citations as recorded by crossref.
- A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolution J. Buitink et al. https://doi.org/10.5194/gmd-13-6093-2020
- Coupled dominant factors analysis, dual attention deep learning, and uncertainty quantification for long-term pan evaporation ensemble prediction in the Wuding River Basin, China Z. Cui et al. https://doi.org/10.1016/j.ejrh.2026.103323
- Response of global evaporation to major climate modes in historical and future Coupled Model Intercomparison Project Phase 5 simulations T. Le & D. Bae https://doi.org/10.5194/hess-24-1131-2020
- A Vision for Hydrological Prediction D. Lavers et al. https://doi.org/10.3390/atmos11030237
- Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting Q. Yang et al. https://doi.org/10.5194/hess-26-941-2022
- Scaling Point‐Scale (Pedo)transfer Functions to Seamless Large‐Domain Parameter Estimates for High‐Resolution Distributed Hydrologic Modeling: An Example for the Rhine River R. Imhoff et al. https://doi.org/10.1029/2019WR026807
- Operational low-flow forecasting using LSTMs J. Deng et al. https://doi.org/10.3389/frwa.2023.1332678
- Enhancing flood event predictions: Multi-objective calibration using gauge and satellite data S. Gegenleithner et al. https://doi.org/10.1016/j.jhydrol.2024.130879
- stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts D. Asfaw et al. https://doi.org/10.5194/gmd-16-557-2023
- AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment Y. Guo et al. https://doi.org/10.5194/hess-25-5951-2021
- Large‐Sample Evaluation of Radar Rainfall Nowcasting for Flood Early Warning R. Imhoff et al. https://doi.org/10.1029/2021WR031591
- 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
- Investigating Nature-based Solutions Potential to Mitigate Urban Pluvial Flooding: A Case Study in Bochum, Germany E. Hartkopf et al. https://doi.org/10.14796/JWMM.C548
- Improving hydrological climate impact assessments using multirealizations from a global climate model F. Sperna Weiland et al. https://doi.org/10.1111/jfr3.12787
- Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin D. Purnamasari et al. https://doi.org/10.5194/hess-29-1483-2025
- Comparison of probabilistic post-processing approaches for improving numerical weather prediction-based daily and weekly reference evapotranspiration forecasts H. Medina & D. Tian https://doi.org/10.5194/hess-24-1011-2020
- Evaluating satellite-based and reanalysis precipitation datasets with gauge-observed data and hydrological modeling in the Xihe River Basin, China N. Wang et al. https://doi.org/10.1016/j.atmosres.2019.104746
Saved (final revised paper)
Latest update: 13 Sep 2026
Short summary
A correct estimate of the amount of future precipitation is the most important factor in making a good streamflow forecast, but evaporation is also an important component that determines the discharge of a river. However, in this study for the Rhine River we found that evaporation forecasts only give an almost negligible improvement compared to methods that use statistical information on climatology for a 10-day streamflow forecast. This is important to guide research on low flow forecasts.
A correct estimate of the amount of future precipitation is the most important factor in making...
