Articles | Volume 30, issue 11
https://doi.org/10.5194/hess-30-3647-2026
© Author(s) 2026. 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-30-3647-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jun 2026
Research article |
| 16 Jun 2026
| 16 Jun 2026
Continental-scale prediction of hydrologic signatures and processes
Ryoko Araki
CORRESPONDING AUTHOR
Department of Geography, San Diego State University, San Diego, CA, USA
Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, USA
Anne Holt
Department of Geography, San Diego State University, San Diego, CA, USA
John C. Hammond
U.S. Geological Survey, Maryland–Delaware–DC Water Science Center, Baltimore, MD, USA
Admin Husic
Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA
Gemma Coxon
School of Geographical Sciences, University of Bristol, Bristol, UK
Department of Geography, San Diego State University, San Diego, CA, USA
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Earth Syst. Sci. Data, 18, 7199–7225, https://doi.org/10.5194/essd-18-7199-2026, https://doi.org/10.5194/essd-18-7199-2026, 2026
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Aaron Heldmyer, Roy Sando, Caelan Simeone, Michael Wieczorek, Scott Hamshaw, Phillip Goodling, Ryan McShane, Jeremy Diaz, David Watkins, Bryce Pulver, Apoorva Shastry, Konrad Hafen, and John Hammond
Hydrol. Earth Syst. Sci., 30, 5925–5945, https://doi.org/10.5194/hess-30-5925-2026, https://doi.org/10.5194/hess-30-5925-2026, 2026
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Gemma Coxon, Yanchen Zheng, Rafael Barbedo, Hollie Cooper, Felipe Fileni, Hayley J. Fowler, Matt Fry, Amy Green, Tom Gribbin, Helen Harfoot, Elizabeth Lewis, Germano Gondim Ribeiro Neto, Xiaobin Qiu, Saskia Salwey, and Doris E. Wendt
Earth Syst. Sci. Data, 18, 4345–4371, https://doi.org/10.5194/essd-18-4345-2026, https://doi.org/10.5194/essd-18-4345-2026, 2026
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Caelan E. Simeone and John C. Hammond
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Doris E. Wendt, Gemma Coxon, Saskia Salwey, and Francesca Pianosi
Hydrol. Earth Syst. Sci., 30, 2837–2857, https://doi.org/10.5194/hess-30-2837-2026, https://doi.org/10.5194/hess-30-2837-2026, 2026
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Groundwater is a highly-used water source, which drought management is complicated. We introduce a socio-hydrological water resource model (SHOWER) to aid drought management in groundwater-rich managed environments. Results show which and when drought management interventions influence surface water and groundwater storage, with integrated interventions having most effect on reducing droughts. This encourages further exploration to reduce water shortages and improve future drought resilience.
Felipe Fileni, Hayley J. Fowler, Elizabeth Lewis, Fiona McLay, Gemma Coxon, David Archer, Emma Bruce, Longzhi Yang, Matt Fry, Hollie Cooper, and Ollie Swain
EGUsphere, https://doi.org/10.5194/egusphere-2026-277, https://doi.org/10.5194/egusphere-2026-277, 2026
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-152, https://doi.org/10.5194/essd-2026-152, 2026
Revised manuscript under review for ESSD
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William Veness, Alejandro Dussaillant, Gemma Coxon, Simon De Stercke, Gareth H. Old, Matthew Fry, Jonathan G. Evans, and Wouter Buytaert
Hydrol. Earth Syst. Sci., 29, 6201–6219, https://doi.org/10.5194/hess-29-6201-2025, https://doi.org/10.5194/hess-29-6201-2025, 2025
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Admin Husic, John Hammond, Adam N. Price, and Joshua K. Roundy
Hydrol. Earth Syst. Sci., 29, 4457–4472, https://doi.org/10.5194/hess-29-4457-2025, https://doi.org/10.5194/hess-29-4457-2025, 2025
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Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris E. Wendt
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Jerom P. M. Aerts, Jannis M. Hoch, Gemma Coxon, Nick C. van de Giesen, and Rolf W. Hut
Hydrol. Earth Syst. Sci., 28, 5011–5030, https://doi.org/10.5194/hess-28-5011-2024, https://doi.org/10.5194/hess-28-5011-2024, 2024
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Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
Hydrol. Earth Syst. Sci., 28, 4203–4218, https://doi.org/10.5194/hess-28-4203-2024, https://doi.org/10.5194/hess-28-4203-2024, 2024
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Yanchen Zheng, Gemma Coxon, Ross Woods, Daniel Power, Miguel Angel Rico-Ramirez, David McJannet, Rafael Rosolem, Jianzhu Li, and Ping Feng
Hydrol. Earth Syst. Sci., 28, 1999–2022, https://doi.org/10.5194/hess-28-1999-2024, https://doi.org/10.5194/hess-28-1999-2024, 2024
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Kathryn A. Leeming, John P. Bloomfield, Gemma Coxon, and Yanchen Zheng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-202, https://doi.org/10.5194/hess-2023-202, 2023
Preprint withdrawn
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Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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Louisa D. Oldham, Jim Freer, Gemma Coxon, Nicholas Howden, John P. Bloomfield, and Christopher Jackson
Hydrol. Earth Syst. Sci., 27, 761–781, https://doi.org/10.5194/hess-27-761-2023, https://doi.org/10.5194/hess-27-761-2023, 2023
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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.
Sarah Shannon, Anthony Payne, Jim Freer, Gemma Coxon, Martina Kauzlaric, David Kriegel, and Stephan Harrison
Hydrol. Earth Syst. Sci., 27, 453–480, https://doi.org/10.5194/hess-27-453-2023, https://doi.org/10.5194/hess-27-453-2023, 2023
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Climate change poses a potential threat to water supply in glaciated river catchments. In this study, we added a snowmelt and glacier melt model to the Dynamic fluxEs and ConnectIvity for Predictions of HydRology model (DECIPHeR). The model is applied to the Naryn River catchment in central Asia and is found to reproduce past change discharge and the spatial extent of seasonal snow cover well.
Rosanna A. Lane, Gemma Coxon, Jim Freer, Jan Seibert, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 26, 5535–5554, https://doi.org/10.5194/hess-26-5535-2022, https://doi.org/10.5194/hess-26-5535-2022, 2022
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This study modelled the impact of climate change on river high flows across Great Britain (GB). Generally, results indicated an increase in the magnitude and frequency of high flows along the west coast of GB by 2050–2075. In contrast, average flows decreased across GB. All flow projections contained large uncertainties; the climate projections were the largest source of uncertainty overall but hydrological modelling uncertainties were considerable in some regions.
Edward Le, Ali Ameli, Joseph Janssen, and John Hammond
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-106, https://doi.org/10.5194/hess-2022-106, 2022
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We used a statistical method to analyze whether snow persistence, defined as the duration of time that snow remains on the ground, explains the variability of streamflow at low and high flow conditions. Results show that as persistence of snow increases, the magnitude of low flow increases and the variability of low flow decreases, regardless of climatic aridity and seasonality. Snow persistence affects stream high flow variability at a narrow range of climatic aridity and seasonality.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 5517–5534, https://doi.org/10.5194/hess-25-5517-2021, https://doi.org/10.5194/hess-25-5517-2021, 2021
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We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.
John P. Bloomfield, Mengyi Gong, Benjamin P. Marchant, Gemma Coxon, and Nans Addor
Hydrol. Earth Syst. Sci., 25, 5355–5379, https://doi.org/10.5194/hess-25-5355-2021, https://doi.org/10.5194/hess-25-5355-2021, 2021
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Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.
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Short summary
We mapped dominant hydrologic processes across the United States by analyzing observed streamflow dynamics. Using random forest models and interpretable machine learning techniques, we predicted processes in data-scarce regions and identified key drivers such as climate, soil and geology, land cover, topography, and human influence. The resulting maps of dominant processes and their drivers reveal strong regional patterns that guide hydrologic model selection and water resource management.
We mapped dominant hydrologic processes across the United States by analyzing observed...
