Fully differentiable, fully distributed River Discharge Prediction: data sets

This repository contains the data sets used in: Scholz et al. (2024). Fully differentiable, fully distributed River Discharge Prediction.

dem_1000.h5 based on EU-DEM v1.1, reprojected to RADOLAN grid: https://sdi.eea.europa.eu/catalogue/srv/api/records/3473589f-0854-4601-919e-2e7dd172ff50

efas.h5 based on EFAS historical: https://ewds.climate.copernicus.eu/datasets/efas-historical?tab=overview

era5_tsr_neckar*.h5 based on ERA5 provided by ECMWF, reprojected to RADOLAN grid: https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5

radolan_neckar*.h5 based on RADOLAN rw product provided by the Deutsche Wetterdienst: https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/

Due to copyright, the discharge data has to be downloaded manually from the Global Runoff Data Centre (https://grdc.bafg.de/), and then preprocessed with the provided bafg_parser.py python script. We use the following stations in our work:

6335290: STEIN

6335291: GAILDORF

6335565: BAD IMNAU

6335600: ROCKENAU SKA

6335601: LAUFFEN

6335602: PLOCHINGEN

6335603: ROTTWEIL

6335604: KIRCHENTELLINSFURT

6335620: MOSBACH

6335660: PFORZHEIM

6335665: DENKENDORF

6335671: ALTENSTEIG

6335675: MURR

6335676: OPPENWEILER

6335680: SCHWABSBERG

6335681: UNTERGRIESHEIM

6335690: NEUSTADT

To preprocess the discharge data, additionally the river network data "Fließgewässer (AWGN)" provided by the Landesanstalt für Umwelt Baden-Württemberg (LUBW) is required: https://rips-metadaten.lubw.de/trefferanzeige?docuuid=7251515f-6aed-4555-8319-ab6314155ab1