1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1,2,3- 1WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland (maria.grundmann@slf.ch)
- 2Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
- 3Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Davos Dorf, Switzerland
River water temperature affects water quality, ecosystem functions, and the useability of water for humans. While many data sources for water temperature time series exist at regional or national levels, retrieving and preprocessing such data for large-scale and -sample studies is often time-consuming. Therefore, studies have mainly focussed on local or regional scales, leading to widespread knowledge gaps regarding large-scale river water temperature variability and impacts. The recent push towards making large-sample hydrological data available, e.g. streamflow[1,2,3], has improved our understanding of processes and trends across hydrologically diverse regions, yet most of these datasets do not include water temperature.
With TempER (Temperatures in European Rivers), we present a large-sample, long-term and high-resolution dataset of river water temperature across Europe. We provide daily water temperature data from 4757 stations, covering up to 72 years, alongside streamflow data where available. We also provide catchment outlines and catchment aggregated land-surface attributes, such as land cover, geology and topography, as well as meteorological time series for these stations. We provide water temperature regime indices for all the stations in our dataset, and the raw data where allowed. To enable updates of this dataset, we provide detailed information on how to retrieve data from over 67 sources in 26 countries. This dataset will pave the way for research projects that improve our understanding of water temperature trends, patterns and extremes across large spatial domains through analysis and modelling.
[1] Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017.
[2] Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w
[3] do Nascimento, T.V.M., Rudlang, J., Höge, M. et al. EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe. Sci Data 11, 879 (2024). https://doi.org/10.1038/s41597-024-03706-1
How to cite: Grundmann, M. H., Heubi, C., Chartier-Rescan, C., Frank, C., Bruno, G., Astagneau, P. C., and Brunner, M. I.: TempER: A large-sample dataset of temperature in European rivers , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7752, https://doi.org/10.5194/egusphere-egu26-7752, 2026.
