Articles | Volume 28, issue 7
https://doi.org/10.5194/hess-28-1771-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-1771-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Apr 2024
Research article |
| 17 Apr 2024
| 17 Apr 2024
A high-resolution map of diffuse groundwater recharge rates for Australia
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, 8000, Australia
National Centre for Groundwater Research and Training, Adelaide, 5000, Australia
Dylan J. Irvine
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, 8000, Australia
National Centre for Groundwater Research and Training, Adelaide, 5000, Australia
Clément Duvert
Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, 8000, Australia
National Centre for Groundwater Research and Training, Adelaide, 5000, Australia
Gabriel C. Rau
National Centre for Groundwater Research and Training, Adelaide, 5000, Australia
School of Environmental and Life Sciences, the University of Newcastle, Callaghan, 2308, Australia
Ian Cartwright
National Centre for Groundwater Research and Training, Adelaide, 5000, Australia
School of Earth, Atmosphere and Environment, Monash University, Clayton, 3800, Australia
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Cited
13 citations as recorded by crossref.
- Hidden flux partitioning in the global water cycle G. Rau et al. https://doi.org/10.1038/s44221-025-00548-y
- Improving groundwater recharge modeling through soft information: A chloride mass balance approach S. Chen et al. https://doi.org/10.1007/s10040-025-02995-z
- From consumer to RTK-enabled UAVs: A comparative assessment of vineyard mapping accuracy and spectral indices J. Rodrigo-Comino et al. https://doi.org/10.1007/s11119-026-10363-4
- Towards global groundwater recharge estimation from GRACE-constrained GLDAS-CLSM data V. Ferreira & C. Ndehedehe https://doi.org/10.1007/s10040-026-03169-1
- An automated adaptative framework for weather data interpolation C. Magain et al. https://doi.org/10.1016/j.jhydrol.2026.136419
- Identification of potential mine sites for low-enthalpy geothermal energy extraction in Australia: a geospatial framework C. Waravita et al. https://doi.org/10.1016/j.geothermics.2026.103825
- Time series analysis of groundwater recharge estimation in a tropical basin: A comparison between the nonlinear transfer function noise model and the conventional water table fluctuation method M. Razi et al. https://doi.org/10.1016/j.pce.2026.104557
- Interaction of climate and vegetation on the spatial distribution of rainfall-induced groundwater recharge in the Central Gangetic Plain A. Karunakalage et al. https://doi.org/10.1016/j.jhydrol.2025.132758
- Geomorphological and hydrological controls on shallow karst depressions (dayas) on a planar carbonate platform: the Nullarbor Plain, Australia M. Jelovčan et al. https://doi.org/10.1016/j.geomorph.2026.110414
- Groundwater δ2H/δ18O isoscapes for New South Wales (Australia) D. Cendón et al. https://doi.org/10.1016/j.ejrh.2025.102732
- Determination of precipitation infiltration recharge coefficient based on multi-factor integration in the Huaibei Plain Region of Anhui Province, China H. Lei et al. https://doi.org/10.1080/27678490.2026.2656244
- Focused groundwater recharge is controlled by landscape and climate S. Lee et al. https://doi.org/10.1038/s43247-025-03063-w
- Irrigation-Driven Groundwater Recharge and Quality Degradation in Semi-Arid Regions: Hydrochemical, GIS-Based, and Explainable Machine Learning Assessment in Central Tunisia R. Missaoui et al. https://doi.org/10.3390/app16147014
13 citations as recorded by crossref.
- Hidden flux partitioning in the global water cycle G. Rau et al. https://doi.org/10.1038/s44221-025-00548-y
- Improving groundwater recharge modeling through soft information: A chloride mass balance approach S. Chen et al. https://doi.org/10.1007/s10040-025-02995-z
- From consumer to RTK-enabled UAVs: A comparative assessment of vineyard mapping accuracy and spectral indices J. Rodrigo-Comino et al. https://doi.org/10.1007/s11119-026-10363-4
- Towards global groundwater recharge estimation from GRACE-constrained GLDAS-CLSM data V. Ferreira & C. Ndehedehe https://doi.org/10.1007/s10040-026-03169-1
- An automated adaptative framework for weather data interpolation C. Magain et al. https://doi.org/10.1016/j.jhydrol.2026.136419
- Identification of potential mine sites for low-enthalpy geothermal energy extraction in Australia: a geospatial framework C. Waravita et al. https://doi.org/10.1016/j.geothermics.2026.103825
- Time series analysis of groundwater recharge estimation in a tropical basin: A comparison between the nonlinear transfer function noise model and the conventional water table fluctuation method M. Razi et al. https://doi.org/10.1016/j.pce.2026.104557
- Interaction of climate and vegetation on the spatial distribution of rainfall-induced groundwater recharge in the Central Gangetic Plain A. Karunakalage et al. https://doi.org/10.1016/j.jhydrol.2025.132758
- Geomorphological and hydrological controls on shallow karst depressions (dayas) on a planar carbonate platform: the Nullarbor Plain, Australia M. Jelovčan et al. https://doi.org/10.1016/j.geomorph.2026.110414
- Groundwater δ2H/δ18O isoscapes for New South Wales (Australia) D. Cendón et al. https://doi.org/10.1016/j.ejrh.2025.102732
- Determination of precipitation infiltration recharge coefficient based on multi-factor integration in the Huaibei Plain Region of Anhui Province, China H. Lei et al. https://doi.org/10.1080/27678490.2026.2656244
- Focused groundwater recharge is controlled by landscape and climate S. Lee et al. https://doi.org/10.1038/s43247-025-03063-w
- Irrigation-Driven Groundwater Recharge and Quality Degradation in Semi-Arid Regions: Hydrochemical, GIS-Based, and Explainable Machine Learning Assessment in Central Tunisia R. Missaoui et al. https://doi.org/10.3390/app16147014
Saved (final revised paper)
Latest update: 23 Sep 2026
Short summary
Global groundwater recharge studies collate recharge values estimated using different methods that apply to different timescales. We develop a recharge prediction model, based solely on chloride, to produce a recharge map for Australia. We reveal that climate and vegetation have the most significant influence on recharge variability in Australia. Our recharge rates were lower than other models due to the long timescale of chloride in groundwater. Our method can similarly be applied globally.
Global groundwater recharge studies collate recharge values estimated using different methods...
