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

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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.