LamaH | Large-Sample Data for Hydrology: big data for hydrology and environmental sciences | LamaH | Large-Sample Data for Hydrology: Big data für die Hydrologie und Umweltwissenschaften

Very large and comprehensive datasets are increasingly used in the field of hydrology. Large-sample studies provide insights into the hydrological cycle that might not be available with small-scale studies. LamaH (Large-Sample Data for Hydrology) is a new dataset for large-sample studies and comparative hydrology in Central Europe. It covers the entire catchment of the upper Danube to the state border Austria/Slovakia, as well as all other Austrian catchments including their foreign upstream areas. LamaH covers an area of about 170,000 km² in 9 different countries, ranging from lowland regions characterized by a continental climate to high alpine zones dominated by snow and ice. Consequently, a wide diversity of properties is present in the individual catchments. We represent this variability in 859 gauged basins with over 60 static catchment attributes, covering topography, climatology, hydrology, land cover, vegetation, soil and geological properties. LamaH further contains a collection of runoff time series as well as meteorological time series. These time series are provided with daily and also hourly resolution. All meteorological and the majority of runoff time series cover a span of over 35 years, which enables long-term analyses, also with a high temporal resolution. The runoff time series are classified by over 20 different attributes including information about human impacts and indicators for data quality and completeness. The structure of LamaH is based on the well-known CAMELS datasets. In contrast, however, LamaH does not only consider independent basins, covering the full upstream area. Intermediate catchments are included as well, which allows, together with novel attributes, to consider the hydrological network and river topology in applications. We discuss not only the data basis and the methodology of data preparation, but also focus on possible limitations and uncertainties. Potential applications of LamaH are outlined as well, since it is intended to serve as a solid basis for further research. LamaH is available at https://doi.org/10.5281/zenodo.4525244