Mapping (dis)agreement in hydrologic projections

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

doi:https://doi.org/10.5194/hess-22-1775-2018

Articles | Volume 22, issue 3

https://doi.org/10.5194/hess-22-1775-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-22-1775-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 3

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

Supplement

https://doi.org/10.5194/hess-22-1775-2018-supplement

Data sets

large sample watershed-scale hydrometeorological dataset for the contiguous USA A. Newman, K. Sampson, K., M. Clark, A. Bock, R. Viger, and D. Blodgett https://doi.org/10.5065/D6MW2F4D

The CAMELS data set: catchment attributes and meteorology for large-sample studies. version 1.0 N. Addor, A. Newman, N. Mizukami, and M. Clark https://doi.org/10.5065/D6G73C3Q

The CAMELS data set: catchment attributes and meteorology for large-sample studies N. Addor, A. J. Newman,N. Mizukami, N., and M. P. Clark https://doi.org/10.5194/hess-21-5293-2017

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance A. Newman, M. Clark, K. Sampson, A. Wood, L. Hay, A. Bock, A., R. Viger, D. Blodgett, L. Brekke, J. Arnold, T. Hopson, and Q. Duan https://doi.org/10.5194/hess-19-209-2015

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.