Skip to content
← Directory

dataset · Europe

GEMS-GER: A Machine Learning Benchmark Dataset of Long-Term Groundwater Levels in Germany with Meteorological Forcings and Site-Specific Environmental Features

This repository provides the dataset accompanying the GEMS-GER (Groundwater Levels, Environment, Meteorology, Site Properties – Germany) benchmark for machine learning-based groundwater modeling. The dataset includes long-term groundwater level time series, meteorological and hydrological forcing data, site-specific environmental properties, and benchmark model evaluation results. All data originate from official public sources and have been harmonized across the 16 German federal states

Visit source ↗

Feature or claim this listing

Feature this listing — founding Featured slots are 50% off for 6 months

Represent GEMS-GER: A Machine Learning Benchmark Dataset of Long-Term Groundwater Levels in Germany with Meteorological Forcings and Site-Specific Environmental Features? Send a claim for review so we can discuss listing updates. Claims do not automatically grant ownership or verification.

Explore paid sponsorship →

Licence
cc-by-nc-nd-4.0
Authentication
Unknown — review source docs
GitHub stars
Unknown
Last commit
Unknown
Last successful page check
16/10/2026
Page health
restricted
Package
Not recorded
Verification
Not independently verified

Provenance & evidence

Listed in zenodo public catalogue API on 2026-10-16; relevance/value screened (haiku).

Metadata observed 14/10/2026 · research sweep: sweep-2026-10-16 (zenodo)