STARS4Water (Horizon Europe supported project)

Part of EU Open Research Repository
Published June 15, 2026 | Version v1.0
Dataset Open

ConvLSTM-based Daily Snow Water Equivalent (SWE) Predictions in the Drammen River Basin

Authors/Creators

  • 1. ROR icon Forschungszentrum Jülich
  • 2. ROR icon Norwegian Water Resources and Energy Directorate

Description

This dataset contains daily Snow Water Equivalent (SWE) predictions generated  by a Convolutional Long Short-Term Memory (ConvLSTM) deep learning model in the Drammen River Basin.

ConvLSTM_ERA5_swe_1km_daily_Drammen_2018_2024.nc > Estimated SWE by ConvLSTM driven by ERA5-Land forcing data

ConvLSTM_SeNorge_swe_1km_daily_Drammen_2010_2020.nc > Estimated SWE by ConvLSTM driven by SeNorge forcing data

ConvLSTM_SeNorge_swe_1km_daily_Drammen_2018_2024.nc > Estimated SWE by ConvLSTM driven by SeNorge forcing data

Files

Files (6.3 GB)

Name Size
md5:86f7a61d175d5ffa561f39fec933ae6e
1.7 GB Download
md5:e198d8527432e680a31f08c46ff6cfda
2.9 GB Download
md5:ed3c05e1f62d204adca7eb349ff7f1ce
1.7 GB Download

Additional details

Funding

European Commission
STARS4Water - Supporting STakeholders for Adaptive, Resilient and Sustainable Water Management 101059372

Software

Repository URL
https://github.com/openearth/stars4water/tree/main/WP4/Task4.4/ConvLSTM_SWE
Programming language
Python