Articles | Volume 17, issue 7
https://doi.org/10.5194/hess-17-2845-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-2845-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Jul 2013
Research article |
| 22 Jul 2013
Disinformative data in large-scale hydrological modelling
A. Kauffeldt
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
S. Halldin
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
A. Rodhe
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
C.-Y. Xu
Department of Geosciences, University of Oslo, Oslo, Norway
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
I. K. Westerberg
Department of Civil Engineering, University of Bristol, Bristol, UK
IVL Swedish Environmental Research Institute, Stockholm, Sweden
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
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Subject: Global hydrology | Techniques and Approaches: Uncertainty analysis
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The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Seungwoo Chang, Wendy D. Graham, Syewoon Hwang, and Rafael Muñoz-Carpena
Hydrol. Earth Syst. Sci., 20, 3245–3261, https://doi.org/10.5194/hess-20-3245-2016, https://doi.org/10.5194/hess-20-3245-2016, 2016
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Projecting water deficit depends on how researchers combine possible future climate scenarios such as general circulation models (GCMs), evapotranspiration estimation method (ET), and greenhouse gas emission scenarios. Using global sensitivity analysis, we found the relative contribution of each of these factors to projecting future water deficit and the choice of ET estimation method are as important as the choice of GCM, and greenhouse gas emission scenario is less influential than the others.
Hannes Müller Schmied, Linda Adam, Stephanie Eisner, Gabriel Fink, Martina Flörke, Hyungjun Kim, Taikan Oki, Felix Theodor Portmann, Robert Reinecke, Claudia Riedel, Qi Song, Jing Zhang, and Petra Döll
Hydrol. Earth Syst. Sci., 20, 2877–2898, https://doi.org/10.5194/hess-20-2877-2016, https://doi.org/10.5194/hess-20-2877-2016, 2016
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The assessment of water balance components of the global land surface by means of hydrological models is affected by large uncertainties, in particular related to meteorological forcing. We analyze the effect of five state-of-the-art forcings on water balance components at different spatial and temporal scales modeled with WaterGAP. Furthermore, the dominant effect (precipitation/human alteration) for long-term changes in river discharge is assessed.
Dave MacLeod, Hannah Cloke, Florian Pappenberger, and Antje Weisheimer
Hydrol. Earth Syst. Sci., 20, 2737–2743, https://doi.org/10.5194/hess-20-2737-2016, https://doi.org/10.5194/hess-20-2737-2016, 2016
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Soil moisture memory is a key aspect of seasonal climate predictions, through feedback between the land surface and the atmosphere. Estimates have been made of the length of soil moisture memory; however, we show here how estimates of memory show large variation with uncertain model parameters. Explicit representation of model uncertainty may then improve the realism of simulations and seasonal climate forecasts.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
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Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
H. Müller Schmied, S. Eisner, D. Franz, M. Wattenbach, F. T. Portmann, M. Flörke, and P. Döll
Hydrol. Earth Syst. Sci., 18, 3511–3538, https://doi.org/10.5194/hess-18-3511-2014, https://doi.org/10.5194/hess-18-3511-2014, 2014
P. Roudier, A. Ducharne, and L. Feyen
Hydrol. Earth Syst. Sci., 18, 2789–2801, https://doi.org/10.5194/hess-18-2789-2014, https://doi.org/10.5194/hess-18-2789-2014, 2014
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
H. Xie, L. Longuevergne, C. Ringler, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 16, 3083–3099, https://doi.org/10.5194/hess-16-3083-2012, https://doi.org/10.5194/hess-16-3083-2012, 2012
F. Sienz, O. Bothe, and K. Fraedrich
Hydrol. Earth Syst. Sci., 16, 2143–2157, https://doi.org/10.5194/hess-16-2143-2012, https://doi.org/10.5194/hess-16-2143-2012, 2012
D. González-Zeas, L. Garrote, A. Iglesias, and A. Sordo-Ward
Hydrol. Earth Syst. Sci., 16, 1709–1723, https://doi.org/10.5194/hess-16-1709-2012, https://doi.org/10.5194/hess-16-1709-2012, 2012
S. N. Gosling, R. G. Taylor, N. W. Arnell, and M. C. Todd
Hydrol. Earth Syst. Sci., 15, 279–294, https://doi.org/10.5194/hess-15-279-2011, https://doi.org/10.5194/hess-15-279-2011, 2011
W. A. Dorigo, K. Scipal, R. M. Parinussa, Y. Y. Liu, W. Wagner, R. A. M. de Jeu, and V. Naeimi
Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010, https://doi.org/10.5194/hess-14-2605-2010, 2010
G. Schumann, D. J. Lunt, P. J. Valdes, R. A. M. de Jeu, K. Scipal, and P. D. Bates
Hydrol. Earth Syst. Sci., 13, 1545–1553, https://doi.org/10.5194/hess-13-1545-2009, https://doi.org/10.5194/hess-13-1545-2009, 2009
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