CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany - R. Loritz; A. Dolich; E. Acuña Espinoza; P. Ebeling; B. Guse; B. Guse; J. Götte; J. Götte; J. Götte; S. K. Hassler; C. Hauffe; I. Heidbüchel; et al. (Earth System Science Data)
Comprehensive large-sample hydrological datasets, particularly the CAMELS datasets (Catchment Attributes and MEteorology for Large-sample Studies), have advanced hydrological research and education in recent years. These datasets integrate extensive hydro-meteorological observations with landscape features, such as geology and land use, across numerous catchments within a national framework. They provide harmonised large-sample data for various purposes, such as assessing the impacts of climate change or testing hydrological models on a large number of catchments. Furthermore, these datasets are essential for the rapid progress of data-driven models in hydrology in recent years. Despite Germany's extensive hydro-meteorological measurement infrastructure, it has lacked a consistent, nationwide hydrological dataset, largely due to its decentralised management across different federal states. This fragmentation has hindered cross-state studies and made the preparation of hydrological data labour-intensive. The introduction of CAMELS-DE represents a step forward in bridging this gap. CAMELS-DE includes 1582 streamflow gauges with hydro-meteorological time series data covering up to 70 years (median length of 46 years and a minimum length of 10 years), from January 1951 to December 2020. It includes consistent catchment boundaries with areas ranging from 5 to 15 000 km2 along with detailed catchment attributes covering soil, land cover, hydrogeologic properties, and data on human influences. Furthermore, it includes a regionally trained long short-term memory (LSTM) network and a locally trained HBV (Hydrologiska Byråns Vattenbalansavdelning) model that were used as quality control and that can be used to fill gaps in discharge data or act as baseline models for the development and testing of new hydrological models. Given the large number of catchments, including numerous relatively small ones (636 catchments < 100 km2), and the time series length of up to 70 years (166 catchments with 70 years of discharge data), CAMELS-DE is one of the most comprehensive national CAMELS datasets available and offers new opportunities for research, particularly in studying long-term trends and runoff formation in small catchments and in analysing catchments with strong human influences. This article describes CAMELS-DE version 1.0, which is available at https://doi.org/10.5281/zenodo.13837553 (Dolich et al., 2024).