Bäthge, Annemarie, Vargas, Claudia Ruz, Lischeid, Gunnar, Collenteur, Raoul, Cuthbert, Mark, Fleckenstein, Jan, Flörke, Martina, de Graaf, Inge, Gnann, Sebastian, Hartmann, Andreas, Huggins, Xander, Moosdorf, Nils ORCID: https://orcid.org/0000-0003-2822-8261, Wada, Yoshihide, Wagener, Thorsten and Reinecke, Robert (2026) A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System. Scientific Data, 13 . p. 401. DOI https://doi.org/10.1038/s41597-026-06966-1.

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Abstract

Groundwater is a central component of the Earth system. However, our understanding of how it is dynamically interlinked with the atmosphere, hydrosphere, cryosphere, biosphere, geosphere, and anthroposphere remains limited. In the pursuit of understanding groundwater dynamics across diverse global settings, we present GROW (the global-scale integrated GROundWater package). This analysis-ready, quality-controlled dataset combines depth to groundwater and level time series from 55 countries, 91% from North America, India, Europe, and Australia, with associated Earth system variables. The dataset contains >200,000 time series with either daily, monthly, or yearly temporal resolution, accompanied by 36 time series or static attributes of meteorological, hydrological, geophysical, vegetation, and anthropogenic variables (e.g., precipitation, drainage density, rock type, NDVI, land use). 34 data flags regarding well features (e.g., coordinates and country), as well as time series characteristics (e.g., gap fraction or autocorrelation), facilitate quick data filtering. GROW provides a foundation for understanding large-scale groundwater processes in space and time, as well as for calibrating and evaluating models that simulate groundwater dynamics within the Earth system.

Document Type:	Article
Programme Area:	PA2
Research affiliation:	Biogeochemistry and Geology > Submarine Groundwater Discharge
Refereed:	Yes
Open Access Journal?:	Yes
DOI:	https://doi.org/10.1038/s41597-026-06966-1
ISSN:	2052-4463
Date Deposited:	02 Apr 2026 16:22
Last Modified:	02 Apr 2026 16:22
URI:	https://cris.leibniz-zmt.de/id/eprint/6180

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