Articles | Volume 22, issue 3
https://doi.org/10.5194/hess-22-1775-2018
https://doi.org/10.5194/hess-22-1775-2018
Research article
 | 
12 Mar 2018
Research article |  | 12 Mar 2018

Mapping (dis)agreement in hydrologic projections

Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling

Related authors

HESS Opinions: Drought impacts as failed prospects
Germano G. Ribeiro Neto, Sarra Kchouk, Lieke A. Melsen, Louise Cavalcante, David W. Walker, Art Dewulf, Alexandre C. Costa, Eduardo S. P. R. Martins, and Pieter R. van Oel
Hydrol. Earth Syst. Sci., 27, 4217–4225, https://doi.org/10.5194/hess-27-4217-2023,https://doi.org/10.5194/hess-27-4217-2023, 2023
Short summary
Mind the Gap: Misalignment Between Drought Monitoring and Community Realities
Sarra Kchouk, Louise Cavalcante, Lieke A. Melsen, David W. Walker, Germano Ribeiro Neto, Rubens Gondim, Wouter J. Smolenaars, and Pieter R. van Oel
EGUsphere, https://doi.org/10.5194/egusphere-2023-2726,https://doi.org/10.5194/egusphere-2023-2726, 2023
Short summary
Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023,https://doi.org/10.5194/hess-27-4057-2023, 2023
Short summary
A geography of drought indices: mismatch between indicators of drought and its impacts on water and food securities
Sarra Kchouk, Lieke A. Melsen, David W. Walker, and Pieter R. van Oel
Nat. Hazards Earth Syst. Sci., 22, 323–344, https://doi.org/10.5194/nhess-22-323-2022,https://doi.org/10.5194/nhess-22-323-2022, 2022
Short summary
Numerical daemons of hydrological models are summoned by extreme precipitation
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021,https://doi.org/10.5194/hess-25-5425-2021, 2021
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Uncertainty analysis
A data-centric perspective on the information needed for hydrological uncertainty predictions
Andreas Auer, Martin Gauch, Frederik Kratzert, Grey Nearing, Sepp Hochreiter, and Daniel Klotz
Hydrol. Earth Syst. Sci., 28, 4099–4126, https://doi.org/10.5194/hess-28-4099-2024,https://doi.org/10.5194/hess-28-4099-2024, 2024
Short summary
A decomposition approach to evaluating the local performance of global streamflow reanalysis
Tongtiegang Zhao, Zexin Chen, Yu Tian, Bingyao Zhang, Yu Li, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 28, 3597–3611, https://doi.org/10.5194/hess-28-3597-2024,https://doi.org/10.5194/hess-28-3597-2024, 2024
Short summary
How much water vapour does the Tibetan Plateau release into the atmosphere?
Chaolei Zheng, Li Jia, Guangcheng Hu, Massimo Menenti, and Joris Timmermans
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-55,https://doi.org/10.5194/hess-2024-55, 2024
Revised manuscript accepted for HESS
Short summary
Technical note: Complexity–uncertainty curve (c-u-curve) – a method to analyse, classify and compare dynamical systems
Uwe Ehret and Pankaj Dey
Hydrol. Earth Syst. Sci., 27, 2591–2605, https://doi.org/10.5194/hess-27-2591-2023,https://doi.org/10.5194/hess-27-2591-2023, 2023
Short summary
Technical note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty
Trevor Page, Paul Smith, Keith Beven, Francesca Pianosi, Fanny Sarrazin, Susana Almeida, Liz Holcombe, Jim Freer, Nick Chappell, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 27, 2523–2534, https://doi.org/10.5194/hess-27-2523-2023,https://doi.org/10.5194/hess-27-2523-2023, 2023
Short summary

Cited articles

Abebe, N., Ogden, F., and Pradhan, N.: Sensitivity and uncertainty analysis of the conceptual HBV rainfall–runoff model: Implications for parameter estimation, J. Hydrol., 389, 301–310, https://doi.org/10.1016/j.jhydrol.2010.06.007, 2010.
Addor, N., Rössler, O., Köplin, N., Huss, M., Weingartner, R., and Seibert, J.: Robust changes and sources of uncertainty in the projected hydrological regimes of Swiss catchments, Water Resour. Res., 50, 7541–7562, https://doi.org/10.1002/2014WR015549, 2014.
Addor, N., Newman, A., Mizukami, N., and Clark, M.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, version 1.0, UCAR/NCAR, Boulder, CO, https://doi.org/10.5065/D6G73C3Q, 2017a.
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017b.
Anderson, E.: National Weather Service River Forecast System – Snow accumulation and ablation model, Tech. rep., NOAA NWS, HYDRO-17, US Department of Commerce, Silver Spring, MD, 1973.
Download
Short summary
Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.