CAMELS-LUX: Highly Resolved Hydro-Meteorological and Atmospheric Data for Physiographically Characterized Catchments around Luxembourg
Authors/Creators
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1.
University of Luxembourg
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2.
Luxembourg Institute of Science and Technology
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3.
Karlsruhe Institute of Technology
Description
The CAMELS-LUX dataset encompasses hydro-meteorological time series and catchment attributes for 56 partly nested stream gauges feeding into the Luxembourgish stream network. The data is available at three temporal resolutions: daily, hourly and at a 15-minute resolution and spans the hydrological years from 2004-11-01 to 2021-10-31. The static catchment attributes cover parameters classifying the topography, geology and land use as well as climatic and hydrologic annual statistics of the 17-year time period.
While an in depth description of the dataset as well as background information on catchments, the environment and exact calculation methods is provided in the accompanying publication in ESSD, the dataset description below isolates information on the available parameters and data structure contained in the provided files.
Data structure
Time series data
- Hydrologic parameters
- Precipitation parameters
- Air temperature and potential evapotranspiration parameters
- Thunderstorm relevant atmospheric parameters
- Soil Moisture parameters
Static catchment attributes
- Meta catchment attributes
- Climatic catchment attributes
- Geologic catchment attributes
- Land use catchment attributes
- Topographic catchment attributes
Spatial data - shapefiles
Files
CAMELS-LUX.zip
Additional details
Related works
- Is reviewed by
- Data paper: 10.5194/essd-2024-482 (DOI)
Funding
- Fonds National de la Recherche
- PRIDE15/10623093/HYDRO-CSI
Dates
- Updated
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2025-11-17In comparison to version 1 of CAMELS-LUX, version 2 includes an updated data validation of the discharge raw data in 2021. Furthermore, more climate stations were interpolated to provide precipitation station data, and also air temperature was processed and added to the dataset. More specifically, and to stay closer to the ERA5 raw data, NaN values in the atmospheric parameter CIN were retained and not filled as previously. Inconsistencies in time stamps and the timing of data were closely analysed and revised where necessary.