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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 22, issue 3
Hydrol. Earth Syst. Sci., 22, 1775–1791, 2018
https://doi.org/10.5194/hess-22-1775-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 1775–1791, 2018
https://doi.org/10.5194/hess-22-1775-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Mar 2018

Research article | 12 Mar 2018

Mapping (dis)agreement in hydrologic projections

Lieke A. Melsen et al.

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Climate change impacts model parameter sensitivity – What does this mean for calibration?
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Flood hazard and change impact assessments may profit from rethinking model calibration strategies
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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.
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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.
Long-term hydrological predictions are important for water management planning, but are also...
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