Expanding CAMELS-CH: increasing resolution and including new assets

New CAMELS (Catchment Attributes and MEteorology for Large-sample Studies) datasets have been increasingly released over the past decade and have allowed for the collection and dissemination of about twenty national datasets, comprising thousands of catchments all around the world. This community effort of providing hydro-meteorological time series alongside relevant catchment attributes is essential for improving hydrological process understanding and modelling across a wide range of conditions. However, the high nonlinearity of the hydrological system and scaling problems in hydrology call for expanding CAMELS datasets to different scales. Most CAMELS datasets provide daily catchment-scale time series, limiting their applicability for sub-daily processes and scaling analyses. Processes such as rainfall–runoff timing, flood generation in mountainous regions, and human flow regulation operate at sub-daily scales and cannot be adequately captured by daily data. Here, we present first efforts to upgrade the existing CAMELS-CH dataset by increasing its temporal and spatial resolution. In addition to hourly hydro-meteorological time-series and statistics extracted at an even higher temporal resolution, we subdivide hydrological Switzerland into topographical catchment units of about 2km², in order to allow for building nested catchments within the gauged catchments and for performing analyses at different scales. We also include additional attributes related to human influence and the impact of hydropower on streamflow. This dataset will be a valuable resource for different hydrological applications, and will enable the first consistent hydrological benchmarks at different spatial and temporal scales in a highly varying environment such as hydrological Switzerland.