Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1038/s41597-026-06966-1
Licence creative commons licence
Title (Primary) A global-scale time series dataset for groundwater studies within the Earth system
Author Bäthge, A.; Ruz Vargas, C.; Lischeid, G.; Collenteur, R.; Cuthbert, M.; Fleckenstein, J.; Flörke, M.; de Graaf, I.; Gnann, S.; Hartmann, A.; Huggins, X.; Moosdorf, N.; Wada, Y.; Wagener, T.; Reinecke, R.
Source Titel Scientific Data
Year 2026
Department HDG
Volume 13
Page From art. 401
Language englisch
Topic T5 Future Landscapes
Data and Software links https://doi.org/10.5281/zenodo.15149480
Supplements Supplement 1
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.
Bäthge, A., Ruz Vargas, C., Lischeid, G., Collenteur, R., Cuthbert, M., Fleckenstein, J., Flörke, M., de Graaf, I., Gnann, S., Hartmann, A., Huggins, X., Moosdorf, N., Wada, Y., Wagener, T., Reinecke, R. (2026):
A global-scale time series dataset for groundwater studies within the Earth system
Sci. Data 13 , art. 401
10.1038/s41597-026-06966-1