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

Area of Science:

• Earth System Science
• Hydrology
• Hydrogeology

Background:

• Groundwater is a critical Earth system component, yet its dynamic interconnections with other spheres remain poorly understood.
• Existing datasets often lack the scale and integration needed for comprehensive analysis of global groundwater dynamics.

Purpose of the Study:

• To present the global-scale integrated Groundwater (GROW) package, an analysis-ready dataset for studying groundwater dynamics.
• To facilitate understanding of large-scale groundwater processes and improve Earth system models.

Main Methods:

• Compiled depth to groundwater and level time series from 55 countries, primarily North America, India, Europe, and Australia.
• Integrated >200,000 time series with 36 associated Earth system variables (meteorological, hydrological, geophysical, vegetation, anthropogenic).
• Included 34 data flags for well features and time series characteristics to enable efficient data filtering.

Main Results:

• The GROW package offers a quality-controlled, analysis-ready dataset with daily, monthly, or yearly temporal resolutions.
• The dataset combines extensive groundwater data with diverse environmental and anthropogenic variables, providing a holistic view.
• Data flags enhance usability for filtering and selecting relevant groundwater time series for specific research needs.

Conclusions:

• The GROW package provides a robust foundation for investigating large-scale groundwater dynamics across diverse global settings.
• This integrated dataset is crucial for calibrating and evaluating numerical models simulating groundwater interactions within the Earth system.