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QUADICA - water quality, discharge and catchment attributes for large-sample studies in Germany


An older version of this resource https://doi.org/10.4211/hs.26e8238f0be14fa1a49641cd8a455e29 is available.
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Created: Jun 21, 2022 at 11:29 a.m.
Last updated: Jul 22, 2022 at 9:58 a.m.
DOI: 10.4211/hs.0ec5f43e43c349ff818a8d57699c0fe1
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Abstract

This data set provides data of water quality, discharge, driving forces (meteorological and nitrogen surplus), and catchment attributes for a set of 1386 German catchments covering a wide range of natural and anthropogenic conditions.
Data on catchment attributes and geodata, which are also part of the QUADICA data set, are available at "CCDB - catchment characteristics data base Germany" (https://doi.org/10.4211/hs.88254bd930d1466c85992a7dea6947a4). The metadata of the underlying water quality and quantity data base is available at "WQQDB - water quality and quantity data base Germany" (https://doi.org/10.4211/hs.a42addcbd59a466a9aa56472dfef8721).
The data set is decribed in detail in a corresponding paper "Water quality, discharge and catchment attributes for large-sample studies in Germany - QUADICA" by Ebeling et al. (https://doi.org/10.5194/essd-2022-6).

This repository includes:

1.) Water quality data as annual medians of observed concentration data of N, P and C species and discharge during sampling dates (c_annual.csv)
2.) Water quantity data as annual medians of observed discharge time series (q_annual.csv)
3.) Monthly medians and percentiles over the whole time series of water quality variables and discharge (c_months.csv)
4.) Monthly and annual median concentrations, flow-normalized concentrations, and mean fluxes estimated using Weighted Regressions on Time, Discharge, and Season (WRTDS) for stations with enough data availability (for details see the corresponding paper Ebeling et al.; wrtds_monthly.csv, wrtds_annual.csv).
5.) Meteorological data as monthly median average temperatures and sums of precipitation and potential evapotranspiration (tavg_monthly.csv, pre_monthly.csv, pet_monthly.csv)
6.) N surplus time series on annual basis (n_surplus.csv)
7.) Summary statistics for the stations including number of samples, covered time periods, degree of censoring (concentrations below the detection limit), outliers, availability of discharge data, and availability and performance of WRTDS models (metadata.csv).
8.) Description of all data tables (Metadata_QUADICA.pdf).

Conditions: The data set is freely and easily accessible. Please refer to the corresponding paper Ebeling et al. when using or referring to this data set. Note that the provided data were created with greatest care, but we cannot guarantee correctness of the data.

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Content

Related Resources

The content of this resource references https://doi.org/10.4211/hs.a42addcbd59a466a9aa56472dfef8721
This resource updates and replaces a previous version Ebeling, P., R. Kumar, M. Weber, A. Musolff (2022). QUADICA - water quality, discharge and catchment attributes for large-sample studies in Germany, HydroShare, https://doi.org/10.4211/hs.26e8238f0be14fa1a49641cd8a455e29
The content of this resource references https://doi.org/10.4211/hs.88254bd930d1466c85992a7dea6947a4
This resource is described by https://essd.copernicus.org/preprints/essd-2022-6/

Credits

Contributors

People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.

Name Organization Address Phone Author Identifiers
Sophie Ehrhardt Helmholtz Centre for Environmental Research – UFZ Sachsen, DE
Fanny Sarrazin Helmholtz Centre for Environmental Research - UFZ Saxony, DE
Tam Nguyen UFZ Sachsen, DE
Thomas Grau UFZ - Helmholtz-Centre for Environmental Research GmbH
Sabine Attinger Helmholtz Centre for Environmental Research – UFZ

How to Cite

Ebeling, P., R. Kumar, M. Weber, A. Musolff (2022). QUADICA - water quality, discharge and catchment attributes for large-sample studies in Germany, HydroShare, https://doi.org/10.4211/hs.0ec5f43e43c349ff818a8d57699c0fe1

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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