DOI: 10.5281/zenodo.12733967
title: CAMELS-DE: hydrometeorological time series and attributes for 1582 catchments in Germany

description: Description

CAMELS-DE provides a comprehensive collection of hydro-meteorological timeseries data (e.g. discharge, water level, precipitation, air temperature) and catchment attributes for 1582 streamflow gauges across Germany. The time series data is in daily resolution and spans up to 70 years, from January 1951 to December 2020. The static catchment attributes include information on topography, soils, land cover, hydrogeology and human influences. Additionally, the dataset includes discharge simulations from a regional Long-Short Term Memory (LSTM) network and a conceptual hydrological model (HBV), providing benchmark data for future hydrological modelling studies in Germany.

The accompanying data description gives information on data sources, the structure of the data set and contains extensive information on time series and catchment attribute variables. In addition, up-to-date benchmark results of the LSTM and HBV are provided.



Important: As CAMELS-DE is continuously developed and updated, please ensure that you cite the correct version of the dataset that you are using.The CAMELS-DE data description paper is available here: https://doi.org/10.5194/essd-16-5625-2024.


Information about the code and methods for generating CAMELS-DE can be found here: CAMELS-DE Processing Pipeline.

CAMELS-DE is also part of the Caravan project, a global hydrological dataset. Due to the use of data products that are available beyond the Germany national boundaries, Caravan-DE includes  305 additional streamflow gauges, resulting in a total of 1887 streamflow gauges: https://doi.org/10.5281/zenodo.13320514.

Disclaimer for discharge and water level data provided by the German federal state agencies:

english:The state agencies do not guarantee the accuracy or completeness of the discharge or water level data provided. In addition, all hydrological data may be subject to future revisions, including adjustments to the rating curves or corrections of errors. Therefore, it is necessary to obtain the most recent discharge time series directly from the federal state authorities for projects that require water law permits. Additionally, the regulations of the respective federal state apply and specific enquiries should be made as needed. It is also important to note that the state agencies explicitly disclaim any warranty as to the accuracy or completeness of the data and therefore any liability claims against any of the federal states are also excluded.

german:Die Ländesämter gewährleisten nicht die Genauigkeit oder Vollständigkeit der bereitgestellten Abfluss oder Wasserstandsdaten. Zudem können alle hydrologischen Daten zukünftigen Überarbeitungen unterliegen, einschließlich Anpassungen der Wasserstands-Abflussbeziehung oder der Korrektur von Fehlern. Daher ist es notwendig, die aktuellsten Abflusszeitreihen direkt bei den Landesbehörden zu beziehen, falls Wasserrechtsgenehmigungen erforderlich sind. Zusätzlich gelten die Vorschriften des jeweiligen Bundeslandes, und spezifische Anfragen sollten bei Bedarf gestellt werden. Es ist ebenfalls wichtig zu beachten, dass die staatlichen Behörden ausdrücklich jegliche Gewährleistung hinsichtlich der Genauigkeit oder Vollständigkeit der Daten ausschließen und somit auch jegliche Haftungsansprüche gegenüber einem der Bundesländer ausgeschlossen sind.

Changelog



v1.1.0



LSTM benchmark results are now based on a LSTM with 10 ensemble members, changing the median NSE in the testing period from 0.83 to 0.85





The columns discharge_spec_sim_lstm and discharge_vol_sim_lstm in timeseries_simulated are now based on the median values of the 10 ensemble members.

The column NSE_lstm in CAMELS_DE_simulation_benchmark.csv is now calculated from the median simulations of the 10 ensemble members

model_parameters/LSTM/CAMELS_DE_epochs_training_lstm.zip now contains the epochs of the 10 ensemble members




The columns NSE_lstm, NSE_hbv and training_perc_complete in CAMELS_DE_simulation_benchmark.csv were calculated from 2001 - 2020, now corrected to 2000 - 2020

Fixed a bug in the calculation of high_prec_dur and low_prec_dur in CAMELS_DE_climatic_attributes.csv calculation (thank you to Bastian Klein from BfG for reporting this issue)

Bayern: removed blank space after gauge and water body name and removed water body name from some gauge names, where it was included as "[gauge_name]_[water_body_name]", e.g. "Würzburg_Main" -> "Würzburg", water body name is now only included in the `water_body_name` column in CAMELS_DE_topographic_attributes.csv

Nordrhein-Westfalen: corrected some wrong river names in CAMELS_DE_topographic_attributes.csv

Sachsen: added `gauge_elevation_metadata` information to CAMELS_DE_topographic_attributes.csv






v1.0.0



CAMELS-DE v1.0.0 is the version of the dataset that is described by the CAMELS-DE data description paper.

Addition of the federal state of Saarland, resulting in 27 additional catchments and coverage of all federal states except the city states of Berlin, Bremen and Hamburg. This also leads to a change in the title of the dataset from 1555 catchments to 1582 catchments.

Addition of HBV model parameters and LSTM model training period epochs.

Catchment DE911970: Removal of erroneous zero discharge values at the beginning of the measurement period.

Minor fixes such as the elimination of discrepancies between the variable names in the dataset and in the data description.

We were able to identify and fix some of these problems based on the feedback from the community, thank you very much!