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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2018-434
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2018-434
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 01 Oct 2018

Research article | 01 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Assessment of Precipitation Error Propagation in Multi-Model Global Water Resources Reanalysis

Md Abul Ehsan Bhuiyan1, Efthymios I. Nikolopoulos1, Emmanouil N. Anagnostou1, Clement Albergel2, Emanuel Dutra3, Gabriel Fink4, Alberto Martinez de la Torre5, Simon Munier2, and Jan Polcher6 Md Abul Ehsan Bhuiyan et al.
  • 1Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut, USA
  • 2CNRM UMR 3589, Météo-France/CNRS, Toulouse, France
  • 3Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Portugal
  • 4Landesanstalt für Umwelt Baden-Württemberg (LUBW), Germany
  • 5Centre for Ecology and Hydrology, Wallingford, UK
  • 6Laboratoire de Météorologie Dynamique du CNRS/IPSL, Ecole Polytechnique, Paris, France

Abstract. This study focuses on the Iberian Peninsula and investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modelling, in global water resources reanalysis. Analysis is based on ensemble hydrologic simulations for a period spanning 11 years (2000–2010). To simulate the hydrological variables of surface runoff, subsurface runoff, and evapotranspiration, we used four land surface models—JULES (Joint UK Land Environment Simulator), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), SURFEX (Surface Externalisée), and HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchange over Land)—and one global hydrological model, WaterGAP3 (Water–Global Assessment and Prognosis). Simulations were carried out for five precipitation products—CMORPH, PERSIANN, 3B42 (V7), ECMWF reanalysis, and a machine learning-based blended product. As reference, we used a ground-based observation-driven precipitation dataset, named SAFRAN, available at 5km/1 h resolution. We present relative performances of hydrologic variables for the different multi-model/multi-forcing scenarios. Overall, results reveal the complexity of the interaction between precipitation characteristics and different modelling schemes and show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure. Surface runoff is strongly sensitive to precipitation uncertainty and the degree of sensitivity depends significantly on the runoff generation scheme of each model examined. Evapotranspiration fluxes are comparatively less sensitive for this study region. Finally, our results suggest that there is no single model/forcing combination that can outperform all others consistently for all variables examined and thus reinforce the fact that there are significant benefits in exploring different model structures as part of the overall modelling approaches used for water resources applications.

Md Abul Ehsan Bhuiyan et al.
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Md Abul Ehsan Bhuiyan et al.
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This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modelling, in global water resources reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
This study investigates the propagation of precipitation uncertainty, and its interaction with...
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