Articles | Volume 21, issue 6
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, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens

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FarmCan: a physical, statistical, and machine learning model to forecast crop water deficit for farms
Sara Sadri, James S. Famiglietti, Ming Pan, Hylke E. Beck, Aaron Berg, and Eric F. Wood
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The suitability of differentiable, learnable hydrologic models for ungauged regions and climate change impact assessment
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
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Revised manuscript accepted for HESS
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Remotely sensed reservoir water storage dynamics (1984–2015) and the influence of climate variability and management at a global scale
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On the selection of precipitation products for the regionalisation of hydrological model parameters
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
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Model cascade from meteorological drivers to river flood hazard: flood-cascade v1.0
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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,, 2003.
Adam, J. C., Clark, E. A., Lettenmaier, D. P., and Wood, E. F.: Correction of global precipitation products for orographic effects, J. Clim., 19, 15–38,, 2006.
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.
Short summary
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.