Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-443
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
26 Sep 2016
Review status
A revision of this discussion paper was accepted for the journal Hydrology and Earth System Sciences (HESS) and is expected to appear here in due course.
A High-Resolution Dataset of Water Fluxes and States for Germany Accounting for Parametric Uncertainty
Matthias Zink, Rohini Kumar, Matthias Cuntz, and Luis Samaniego Helmholtz Centre for Environmental Research – UFZ, Department Computational Hydrosystems, Permoserstrasse 15, 04318 Leipzig, Germany
Abstract. Long term, high-resolution data about hydrologic fluxes and states are needed for many hydrological applications. Because continuous large-scale observations of such variables are not feasible, hydrologic or land surface models are applied to derive them. This study aims to analyze and provide a consistent high-resolution dataset of land surface variables over Germany, accounting for uncertainties caused by equifinal model parameters. The mesoscale Hydrological Model (mHM) is employed to derive an ensemble (100 members) of evapotranspiration, groundwater recharge, soil moisture and generated runoff at high spatial and temporal resolutions (4 km and daily, respectively) for the period 1951–2010. The model is cross-evaluated against the observed runoff in 222 catchments, which are not used for model calibration. The mean (standard deviation) of the ensemble median NSE estimated for these catchments is 0.68 (0.09) for daily discharge simulations. The modeled evapotranspiration and soil moisture reasonably represent the observations from eddy covariance stations. Our analysis indicates the lowest parametric uncertainty for evapotranspiration, and the largest is observed for groundwater recharge. The uncertainty of the hydrologic variables varies over the course of a year, with the exception of evapotranspiration, which remains almost constant. This study emphasizes the role of accounting for the parametric uncertainty in model-derived hydrological datasets.

Citation: Zink, M., Kumar, R., Cuntz, M., and Samaniego, L.: A High-Resolution Dataset of Water Fluxes and States for Germany Accounting for Parametric Uncertainty, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-443, in review, 2016.
Matthias Zink et al.
Matthias Zink et al.

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Short summary
We discuss the estimation of a long-term, high resolution, continuous, and consistent dataset of hydro-meteorological variables for Germany. Here we describe the derivation of national scale parameter sets and analyzes the uncertainty of the estimated hydrologic variables (focusing on the parametric uncertainty). Our study highlights the role of accounting for the parametric uncertainty in model-derived hydrological datasets.
We discuss the estimation of a long-term, high resolution, continuous, and consistent dataset of...
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