GROW-Qual: A global observational groundwater quality dataset linked to water table dynamics and Earth system variables
Abstract
Groundwater underpins freshwater supply, food production and ecosystem health across the globe. Yet, groundwater levels and quality are increasingly threatened by overextraction, contamination, and climate change. Understanding how water table dynamics and quality are interlinked and affected by these pressures requires integrated observational groundwater datasets combined with Earth system variables that represent potential environmental drivers. Here we present GROW-Qual, a global dataset that standardises, harmonises and combines ~25 million groundwater quality observations across 92 constituents from 68 countries. Groundwater quality observations are linked to co-located water table timeseries (i.e. depth or level), in addition to a diverse range of contextual Earth system datasets spanning meteorological, hydrological, geophysical, biological and anthropogenic variables. GROW-Qual can support a broad range of applications, from empirical analysis to large-scale groundwater modelling, while its structural consistency with the companion river water quality dataset (Caravan-Qual) enables integrated study of groundwater-river water quantity and quality dynamics.
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BibTeX
@misc{jones2026growqual,
title = {{GROW-Qual: A global observational groundwater quality dataset linked to water table dynamics and Earth system variables}},
author = {Edward Russell Jones and Annemarie Bäthge and Andrew Pearson and Nicole Gyakowah Otoo and Moritz Heinle and Robert Reinecke and Michelle T H van Vliet},
howpublished = {EarthArXiv},
year = {2026},
month = oct,
doi = {10.31223/x55f8g},
url = {https://eartharxiv.org/repository/view/15518/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - GROW-Qual: A global observational groundwater quality dataset linked to water table dynamics and Earth system variables
AU - Edward Russell Jones
AU - Annemarie Bäthge
AU - Andrew Pearson
AU - Nicole Gyakowah Otoo
AU - Moritz Heinle
AU - Robert Reinecke
AU - Michelle T H van Vliet
PY - 2026
DA - 2026/10/21
PB - EarthArXiv
DO - 10.31223/x55f8g
UR - https://eartharxiv.org/repository/view/15518/
AB - Groundwater underpins freshwater supply, food production and ecosystem health across the globe. Yet, groundwater levels and quality are increasingly threatened by overextraction, contamination, and climate change. Understanding how water table dynamics and quality are interlinked and affected by these pressures requires integrated observational groundwater datasets combined with Earth system variables that represent potential environmental drivers. Here we present GROW-Qual, a global dataset that standardises, harmonises and combines ~25 million groundwater quality observations across 92 constituents from 68 countries. Groundwater quality observations are linked to co-located water table timeseries (i.e. depth or level), in addition to a diverse range of contextual Earth system datasets spanning meteorological, hydrological, geophysical, biological and anthropogenic variables. GROW-Qual can support a broad range of applications, from empirical analysis to large-scale groundwater modelling, while its structural consistency with the companion river water quality dataset (Caravan-Qual) enables integrated study of groundwater-river water quantity and quality dynamics.
ER -