A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System

@article{Bäthge2026,
  Title = {A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System},
  Author = {Bäthge, Annemarie and Vargas, Claudia Ruz and Lischeid, Gunnar and Collenteur, Raoul and Cuthbert, Mark and Fleckenstein, Jan and Flörke, Martina and de Graaf, Inge and Gnann, Sebastian and Hartmann, Andreas and Huggins, Xander and Moosdorf, Nils and Wada, Yoshihide and Wagener, Thorsten and Reinecke, Robert},
  Editor = {},
  Journal = {Scientific Data},
  Year = {2026},
  Pages = {401},
  Volume = {13},
  Doi = {10.1038/s41597-026-06966-1},
  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.},
}

TY  - JOUR
AU  - Bäthge, Annemarie
AU  - Vargas, Claudia Ruz
AU  - Lischeid, Gunnar
AU  - Collenteur, Raoul
AU  - Cuthbert, Mark
AU  - Fleckenstein, Jan
AU  - Flörke, Martina
AU  - de Graaf, Inge
AU  - Gnann, Sebastian
AU  - Hartmann, Andreas
AU  - Huggins, Xander
AU  - Moosdorf, Nils
AU  - Wada, Yoshihide
AU  - Wagener, Thorsten
AU  - Reinecke, Robert
TI  - A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System
T2  - Scientific Data
PY  - 2026
SP  - 401
VL  - 13
DO  - 10.1038/s41597-026-06966-1
AB  - 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.
ER  -