A High-Resolution Dataset of Water Fluxes and States for Germany Accounting for Parametric Uncertainty

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. Here, we 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. These data are complemented by the daily meteorological model forcings: precipitation, air temperature (average, minimum, maximum), and potential evapotranspiration. The data can be downloaded here.

Further information / citation:
Annual water balance variables
Observed and modeled water balance variables. The different panels show: A) mean annual precipitation (P), B) mean long-time air temperature  (T), C) mean annual potential evapotranspiration (Ep), D) dryness index (EpP-1), E) mean annual evapotranspiration (Ea), F) average long-term soil moisture (SM), G) mean annual groundwater recharge (recharge), and H) gridcell generated runoff (QG). The reference period of the data is 1951-2010.

Besides the 100 ensemble realizations we provide the ensemble mean, ensemble median as well as the ensemble percentiles 5 and 95.

For any question please contact Matthias Zink .