Abstract
AbstractLarge-sample hydrology datasets have become increasingly available, contributing to significant scientific advances. However, in Europe, only a few such datasets have been published, capturing only a fraction of the wealth of information from national data providers in terms of available spatial density and temporal extent. We present “EStreams”, an extensive dataset of hydro-climatic variables and landscape descriptors and a catalogue of openly available stream records for 17,130 European catchments. Spanning up to 120 years, the dataset includes streamflow indices, catchment-aggregated hydro-climatic signatures and landscape attributes (topography, soils, geology, vegetation and landcover). The catalogue provides detailed descriptions that allow users to directly access streamflow data sources, overcoming challenges related to data redistribution policies, language barriers and varied data portal structures. EStreams also provides Python scripts for data retrieval, aggregation and processing, making it dynamic in contrast to static datasets. This approach enables users to update their data as new records become available. Our goal is to extend current large-sample datasets and further integrate hydro-climatic and landscape data across Europe.
Funder
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Publisher
Springer Science and Business Media LLC
Reference104 articles.
1. Addor, N., Newman, A. J., Mizukami, N. & Clark, M. P. The CAMELS data set: Catchment attributes and meteorology for large-sample studies. Hydrol Earth Syst Sci 21, 5293–5313 (2017).
2. Coxon, G. et al. CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain. Earth Syst Sci Data 12, 2459–2483 (2020).
3. Kratzert, F. et al. Caravan - A global community dataset for large-sample hydrology. Scientific Data 10, 1–11 (2023).
4. Fowler, K. J. A., Acharya, S. C., Addor, N., Chou, C. & Peel, M. C. CAMELS-AUS: Hydrometeorological time series and landscape attributes for 222 catchments in Australia. Earth Syst. Sci Data 13, 3847–3867 (2021).
5. Chagas, V. B. P. et al. CAMELS-BR: Hydrometeorological time series and landscape attributes for 897 catchments in Brazil. Earth Syst Sci Data 12, 2075–2096 (2020).