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Dataset . 2024
License: CC BY
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Dataset . 2026
License: CC BY
Data sources: Datacite
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Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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CAMELS-LUX: Highly Resolved Hydro-Meteorological and Atmospheric Data for Physiographically Characterized Catchments around Luxembourg

Authors: Nijzink, Judith; Loritz, Ralf; Gourdol, Laurent; Zoccatelli, Davide; Iffly, Jean François; Pfister, Laurent;

CAMELS-LUX: Highly Resolved Hydro-Meteorological and Atmospheric Data for Physiographically Characterized Catchments around Luxembourg

Abstract

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

Keywords

Climatology, Land cover, Soil, Meteorology, Machine learning, Hydrogeology, Deep learning, Streamflow, Hydrology, Rainfall-Runoff Modelling, Benchmark dataset

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average