Spatially Resolved Meteorological and Ancillary Data in Central Europe for Rainfall Streamflow Modeling
This dataset enables more accurate rainfall streamflow modeling for hydrologists and researchers in central Europe, though it is incremental as it builds on existing methods by adding spatial resolution.
The authors tackled the problem of limited spatial resolution in neural network-driven hydrological modeling by creating a fully spatially resolved dataset for rainfall streamflow modeling in five central European river basins, providing harmonized daily data from 1981 to 2011 on a 9km grid.
We present a dataset for rainfall streamflow modeling that is fully spatially resolved with the aim of taking neural network-driven hydrological modeling beyond lumped catchments. To this end, we compiled data covering five river basins in central Europe: upper Danube, Elbe, Oder, Rhine, and Weser. The dataset contains meteorological forcings, as well as ancillary information on soil, rock, land cover, and orography. The data is harmonized to a regular 9km times 9km grid and contains daily values that span from October 1981 to September 2011. We also provide code to further combine our dataset with publicly available river discharge data for end-to-end rainfall streamflow modeling.