Articles | Volume 21, issue 6
Hydrol. Earth Syst. Sci., 21, 2881–2903, 2017
https://doi.org/10.5194/hess-21-2881-2017
Hydrol. Earth Syst. Sci., 21, 2881–2903, 2017
https://doi.org/10.5194/hess-21-2881-2017

Research article 12 Jun 2017

Research article | 12 Jun 2017

Global evaluation of runoff from 10 state-of-the-art hydrological models

Hylke E. Beck et al.

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Cited articles

Adam, J. C. and Lettenmaier, D. P.: Adjustment of global gridded precipitation for systematic bias, J. Geophys. Res.-Atmos., 108, 4257, https://doi.org/10.1029/2002JD002499, 2003.
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Ajami, N. K., Duan, Q., Gao, X., and Sorooshian, S.: Multimodel Combination Techniques for Analysis of Hydrological Simulations: Application to Distributed Model Intercomparison Project Results, J. Hydrometeorol., 7, 755–768, 2006.
Andréassian, V., Lerat, J., Loumagne, C., Mathevet, T., Michel, C., Oudin, L., and Perrin, C.: What is really undermining hydrologic science today?, Hydrol. Process., 21, 2819–2822, 2007.
Andréassian, V., Le Moine, N., Perrin, C., Ramos, M. H., Oudin, L., Mathevet, T., Lerat, J., and Berthet, L.: All that glitters is not gold: the case of calibrating hydrological models, Hydrol. Process., 26, 2206–2210, 2012.
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Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.