Articles | Volume 18, issue 8
https://doi.org/10.5194/hess-18-3301-2014
© Author(s) 2014. 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-18-3301-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Aug 2014
Research article |
| 29 Aug 2014
The importance of hydrological uncertainty assessment methods in climate change impact studies
M. Honti
Water Research Group of the Hungarian Academy of Sciences, Müegyetem rkp. 3., Budapest, 1111, Hungary
Eawag: Swiss Federal Institute of Aquatic Sciences and Technology, Überlandstrasse 133, Dübendorf, 8600, Switzerland
A. Scheidegger
Eawag: Swiss Federal Institute of Aquatic Sciences and Technology, Überlandstrasse 133, Dübendorf, 8600, Switzerland
Eawag: Swiss Federal Institute of Aquatic Sciences and Technology, Überlandstrasse 133, Dübendorf, 8600, Switzerland
Viewed
Total article views: 4,690 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Jan 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,586 | 1,919 | 185 | 4,690 | 184 | 165 |
- HTML: 2,586
- PDF: 1,919
- XML: 185
- Total: 4,690
- BibTeX: 184
- EndNote: 165
Total article views: 3,414 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Aug 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,988 | 1,288 | 138 | 3,414 | 176 | 159 |
- HTML: 1,988
- PDF: 1,288
- XML: 138
- Total: 3,414
- BibTeX: 176
- EndNote: 159
Total article views: 1,276 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 14 Jan 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 598 | 631 | 47 | 1,276 | 8 | 6 |
- HTML: 598
- PDF: 631
- XML: 47
- Total: 1,276
- BibTeX: 8
- EndNote: 6
Cited
25 citations as recorded by crossref.
- How to assess climate change impact models: uncertainty analysis of streamflow statistics via approximate Bayesian computation (ABC) J. Romero-Cuellar & F. Francés 10.1080/02626667.2023.2231437
- Climate change and the hydropower sector: A global review A. Wasti et al. 10.1002/wcc.757
- Multi-driver ensemble to evaluate the water utility business interruption cost induced by hydrological drought risk scenarios in Brazil D. Guzmán et al. 10.1080/1573062X.2022.2058564
- Regional climate change trends and uncertainty analysis using extreme indices: A case study of Hamilton, Canada T. Razavi et al. 10.1016/j.crm.2016.06.002
- The critical role of uncertainty in projections of hydrological extremes H. Meresa & R. Romanowicz 10.5194/hess-21-4245-2017
- Hydrological simulation of Po River (North Italy) discharge under climate change scenarios using the RCM COSMO-CLM R. Vezzoli et al. 10.1016/j.scitotenv.2015.03.096
- Assessment of the impact of climate change on current and future flows of the ungauged Aga-Foua-Djilas watershed: a comparative study of hydrological models CWatM under ISIMIP and HMF-WA P. Dione et al. 10.1007/s13201-024-02219-x
- Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development? M. Honti et al. 10.5194/hess-21-1593-2017
- Projection of climate change impacts on extreme temperature and precipitation in Central Poland B. Ghazi et al. 10.1038/s41598-023-46199-5
- Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations Y. Zhang et al. 10.5194/hess-27-4529-2023
- Climate and hydrological models to assess the impact of climate change on hydrological regime: a review R. Kour et al. 10.1007/s12517-016-2561-0
- Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China F. Yuan et al. 10.1016/j.jhydrol.2017.08.034
- Xinanjiang-Based Interval Forecasting Model for Daily Streamflow Considering Climate Change Impacts H. Ke et al. 10.1007/s11269-024-03909-6
- Quantifying future changes in glacier melt and river runoff in the headwaters of the Urumqi River, China Y. Zhang et al. 10.1007/s12665-016-5563-z
- Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models? B. Majone et al. 10.5194/hess-26-3863-2022
- Bias in streamflow projections due to climate‐induced shifts in catchment response M. Saft et al. 10.1002/2015GL067326
- Modelling biocide and herbicide concentrations in catchments of the Rhine basin A. Moser et al. 10.5194/hess-22-4229-2018
- Climate model bias correction for nonstationary conditions M. Madani et al. 10.1139/cjce-2018-0692
- Ensemble estimation of future rainfall extremes with temperature dependent censored simulation D. Cross et al. 10.1016/j.advwatres.2019.103479
- Use of ACRU, a distributed hydrological model, to evaluate how errors from downscaled rainfall are propagated in simulated runoff in uMngeni catchment, South Africa S. Kusangaya et al. 10.1080/02626667.2017.1349317
- Similarity Metrics-Based Uncertainty Analysis of River Water Quality Models S. Karimi et al. 10.1007/s11269-019-02205-y
- Comparative study of GCMs, RCMs, downscaling and hydrological models: a review toward future climate change impact estimation N. Chokkavarapu & V. Mandla 10.1007/s42452-019-1764-x
- The integrated effects of climate and hydrologic uncertainty on future flood risk assessments S. Steinschneider et al. 10.1002/hyp.10409
- Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections A. Aryal et al. 10.1007/s00704-017-2359-3
- Rainfall variation prediction using SD technology based on temperature model for Weihe River basin X. Gao et al. 10.2166/wcc.2018.048
22 citations as recorded by crossref.
- How to assess climate change impact models: uncertainty analysis of streamflow statistics via approximate Bayesian computation (ABC) J. Romero-Cuellar & F. Francés 10.1080/02626667.2023.2231437
- Climate change and the hydropower sector: A global review A. Wasti et al. 10.1002/wcc.757
- Multi-driver ensemble to evaluate the water utility business interruption cost induced by hydrological drought risk scenarios in Brazil D. Guzmán et al. 10.1080/1573062X.2022.2058564
- Regional climate change trends and uncertainty analysis using extreme indices: A case study of Hamilton, Canada T. Razavi et al. 10.1016/j.crm.2016.06.002
- The critical role of uncertainty in projections of hydrological extremes H. Meresa & R. Romanowicz 10.5194/hess-21-4245-2017
- Hydrological simulation of Po River (North Italy) discharge under climate change scenarios using the RCM COSMO-CLM R. Vezzoli et al. 10.1016/j.scitotenv.2015.03.096
- Assessment of the impact of climate change on current and future flows of the ungauged Aga-Foua-Djilas watershed: a comparative study of hydrological models CWatM under ISIMIP and HMF-WA P. Dione et al. 10.1007/s13201-024-02219-x
- Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development? M. Honti et al. 10.5194/hess-21-1593-2017
- Projection of climate change impacts on extreme temperature and precipitation in Central Poland B. Ghazi et al. 10.1038/s41598-023-46199-5
- Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations Y. Zhang et al. 10.5194/hess-27-4529-2023
- Climate and hydrological models to assess the impact of climate change on hydrological regime: a review R. Kour et al. 10.1007/s12517-016-2561-0
- Evaluation on uncertainty sources in projecting hydrological changes over the Xijiang River basin in South China F. Yuan et al. 10.1016/j.jhydrol.2017.08.034
- Xinanjiang-Based Interval Forecasting Model for Daily Streamflow Considering Climate Change Impacts H. Ke et al. 10.1007/s11269-024-03909-6
- Quantifying future changes in glacier melt and river runoff in the headwaters of the Urumqi River, China Y. Zhang et al. 10.1007/s12665-016-5563-z
- Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models? B. Majone et al. 10.5194/hess-26-3863-2022
- Bias in streamflow projections due to climate‐induced shifts in catchment response M. Saft et al. 10.1002/2015GL067326
- Modelling biocide and herbicide concentrations in catchments of the Rhine basin A. Moser et al. 10.5194/hess-22-4229-2018
- Climate model bias correction for nonstationary conditions M. Madani et al. 10.1139/cjce-2018-0692
- Ensemble estimation of future rainfall extremes with temperature dependent censored simulation D. Cross et al. 10.1016/j.advwatres.2019.103479
- Use of ACRU, a distributed hydrological model, to evaluate how errors from downscaled rainfall are propagated in simulated runoff in uMngeni catchment, South Africa S. Kusangaya et al. 10.1080/02626667.2017.1349317
- Similarity Metrics-Based Uncertainty Analysis of River Water Quality Models S. Karimi et al. 10.1007/s11269-019-02205-y
- Comparative study of GCMs, RCMs, downscaling and hydrological models: a review toward future climate change impact estimation N. Chokkavarapu & V. Mandla 10.1007/s42452-019-1764-x
3 citations as recorded by crossref.
- The integrated effects of climate and hydrologic uncertainty on future flood risk assessments S. Steinschneider et al. 10.1002/hyp.10409
- Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections A. Aryal et al. 10.1007/s00704-017-2359-3
- Rainfall variation prediction using SD technology based on temperature model for Weihe River basin X. Gao et al. 10.2166/wcc.2018.048
Saved (final revised paper)
Saved (preprint)
Latest update: 18 Sep 2025
