Articles | Volume 27, issue 3
https://doi.org/10.5194/hess-27-761-2023
© Author(s) 2023. 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-27-761-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Feb 2023
Research article |
| 14 Feb 2023
| 14 Feb 2023
Evidence-based requirements for perceptualising intercatchment groundwater flow in hydrological models
Louisa D. Oldham
CORRESPONDING AUTHOR
School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, United Kingdom
Jim Freer
School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, United Kingdom
Cabot Institute, University of Bristol, Bristol BS5 9LT, United
Kingdom
Centre for Hydrology, University of Saskatchewan, Canmore, Alberta
T1W 3G1, Canada
Gemma Coxon
School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, United Kingdom
Cabot Institute, University of Bristol, Bristol BS5 9LT, United
Kingdom
Nicholas Howden
Department of Civil Engineering, University of Bristol, Bristol BS8
1TR, United Kingdom
John P. Bloomfield
British Geological Survey, Wallingford OX10 8BB, United Kingdom
Christopher Jackson
British Geological Survey, Keyworth NG12 5GG, United Kingdom
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Cited
14 citations as recorded by crossref.
- Comparative study of daily streamflow prediction based on coupling SWAT+ with interpretable machine learning algorithms C. Cao & M. Ying https://doi.org/10.1016/j.ecoinf.2025.103406
- Effects of model complexity on karst catchment runoff modeling for flood warning systems P. Knöll et al. https://doi.org/10.1016/j.hydroa.2024.100194
- Application of a parsimonious large-scale distributed groundwater flow model to quantify inter-catchment groundwater flow M. Rahman et al. https://doi.org/10.1016/j.jhydrol.2025.133900
- Inter-Basin groundwater flow in West-Central Florida S. Elrashedy et al. https://doi.org/10.1016/j.jhydrol.2025.133423
- Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics F. Clerc-Schwarzenbach & T. do Nascimento https://doi.org/10.5194/hess-30-119-2026
- DECIPHeR-GW v1: a coupled hydrological model with improved representation of surface–groundwater interactions Y. Zheng et al. https://doi.org/10.5194/gmd-18-4247-2025
- Quantifying Groundwater Contributions To Streamflow Using a Multi-method Hydrological Approach B. Trust et al. https://doi.org/10.1007/s40710-025-00764-4
- Forty-Year Landscape Fragmentation and Its Hydro–Climate–Human Drivers Identified Through Entropy and Gray Relational Analysis in the Tuwei River Watershed, China Y. Huo et al. https://doi.org/10.3390/land15010024
- Developing water supply reservoir operating rules for large-scale hydrological modelling S. Salwey et al. https://doi.org/10.5194/hess-28-4203-2024
- Flux tracking of groundwater via integrated modelling for abstraction management L. Liu et al. https://doi.org/10.1016/j.jhydrol.2024.131379
- Evidence of Geological Control on the Hydrological Response of Tropical Volcanic Catchments T. Grangeon et al. https://doi.org/10.1002/hyp.70321
- Deciphering inter-catchment groundwater flow: A water balance perspective in the Choshui River Basin, Taiwan H. Chen et al. https://doi.org/10.1016/j.ejrh.2024.101742
- Location, location, location – Considering relative catchment location to understand subsurface losses M. Kiraz-Safari et al. https://doi.org/10.1016/j.jhydrol.2024.132328
- Paired catchment experiments can overestimate water yield gains from deforestation by neglecting potential changes in unmonitored subsurface discharge contributions P. Huang et al. https://doi.org/10.1016/j.jhydrol.2025.134318
14 citations as recorded by crossref.
- Comparative study of daily streamflow prediction based on coupling SWAT+ with interpretable machine learning algorithms C. Cao & M. Ying https://doi.org/10.1016/j.ecoinf.2025.103406
- Effects of model complexity on karst catchment runoff modeling for flood warning systems P. Knöll et al. https://doi.org/10.1016/j.hydroa.2024.100194
- Application of a parsimonious large-scale distributed groundwater flow model to quantify inter-catchment groundwater flow M. Rahman et al. https://doi.org/10.1016/j.jhydrol.2025.133900
- Inter-Basin groundwater flow in West-Central Florida S. Elrashedy et al. https://doi.org/10.1016/j.jhydrol.2025.133423
- Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics F. Clerc-Schwarzenbach & T. do Nascimento https://doi.org/10.5194/hess-30-119-2026
- DECIPHeR-GW v1: a coupled hydrological model with improved representation of surface–groundwater interactions Y. Zheng et al. https://doi.org/10.5194/gmd-18-4247-2025
- Quantifying Groundwater Contributions To Streamflow Using a Multi-method Hydrological Approach B. Trust et al. https://doi.org/10.1007/s40710-025-00764-4
- Forty-Year Landscape Fragmentation and Its Hydro–Climate–Human Drivers Identified Through Entropy and Gray Relational Analysis in the Tuwei River Watershed, China Y. Huo et al. https://doi.org/10.3390/land15010024
- Developing water supply reservoir operating rules for large-scale hydrological modelling S. Salwey et al. https://doi.org/10.5194/hess-28-4203-2024
- Flux tracking of groundwater via integrated modelling for abstraction management L. Liu et al. https://doi.org/10.1016/j.jhydrol.2024.131379
- Evidence of Geological Control on the Hydrological Response of Tropical Volcanic Catchments T. Grangeon et al. https://doi.org/10.1002/hyp.70321
- Deciphering inter-catchment groundwater flow: A water balance perspective in the Choshui River Basin, Taiwan H. Chen et al. https://doi.org/10.1016/j.ejrh.2024.101742
- Location, location, location – Considering relative catchment location to understand subsurface losses M. Kiraz-Safari et al. https://doi.org/10.1016/j.jhydrol.2024.132328
- Paired catchment experiments can overestimate water yield gains from deforestation by neglecting potential changes in unmonitored subsurface discharge contributions P. Huang et al. https://doi.org/10.1016/j.jhydrol.2025.134318
Saved (final revised paper)
Latest update: 03 Jun 2026
Short summary
Water can move between river catchments via the subsurface, termed intercatchment groundwater flow (IGF). We show how a perceptual model of IGF can be developed with relatively simple geological interpretation and data requirements. We find that IGF dynamics vary in space, correlated to the dominant underlying geology. We recommend that IGF
loss functionsmay be used in conceptual rainfall–runoff models but should be supported by perceptualisation of IGF processes and connectivities.
Water can move between river catchments via the subsurface, termed intercatchment groundwater...
