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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Caelan E. Simeone and John C. Hammond
EGUsphere, https://doi.org/10.5194/egusphere-2026-2731, https://doi.org/10.5194/egusphere-2026-2731, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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This study examines how quickly rivers across the U.S. shift between very dry and very wet conditions, an emerging challenge for water managers because rapid changes compress decision windows and create operational stress. Drought-to-flood transitions occur more quickly and more often than flood-to-drought transitions, with short events concentrated in certain regions. Flood-to-drought transitions are less common but can involve large and rapid declines in flow.
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
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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This study develops and applies a national framework to identify and flag issues in UK river flow data by combining systematic visual checks with automated tests. We demonstrate the importance of visual inspection, refine and sensitivity-test traditional quality-control methods, and develop new high-flow checks tailored to high-resolution data. We then quantify the frequency of these issues and demonstrate that, if overlooked, they can impact scientific results and lead to misleading conclusions
Felipe Fileni, Hayley J. Fowler, Elizabeth Lewis, Matt Fry, Hollie Cooper, Ollie Swain, Fiona McLay, Gemma Coxon, Emma Bruce, Longzhi Yang, and David Archer
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-152, https://doi.org/10.5194/essd-2026-152, 2026
Preprint under review for ESSD
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River flow data recorded at 15-minute resolution has been collected across the UK for over 70 years, but it has been difficult to access and use consistently. We brought these records together into a single national dataset, checked them for errors, harmonised different records, and clearly documented any issues and suspect values. The result is a reliable and transparent resource that supports better flood forecasting, water management, and research on climate change impacts on river flows.
Aaron Heldmyer, Roy Sando, Caelan Simeone, Michael Wieczorek, Scott Hamshaw, Philip Goodling, Ryan McShane, Jeremy Diaz, David Watkins, Bryce Pulver, Apoorva Shastry, Konrad Hafen, and John Hammond
EGUsphere, https://doi.org/10.5194/egusphere-2025-6064, https://doi.org/10.5194/egusphere-2025-6064, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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We used machine learning to explore what causes streamflow droughts across the U.S. We found that different regions are influenced by different factors like temperature, snow, and rainfall. Our new method can also predict droughts in areas without streamflow data, helping improve water resource planning.
Yining Zang, Pauline C. Treble, Kei Yoshimura, Jayson Gabriel Pinza, Fengbo Zhang, Kübra Özdemir Çallı, Xiaojun Mei, Admin Husic, Alena Gessert, Andrej Stroj, Bartolomé Andreo, Bernard Ladouche, Christine Stumpp, Diana Mance, Eleni Zagana, Fen Huang, Giuseppe Sappa, Harald Kunstmann, Heike Brielmann, Hong Zhou, Huaying Wu, Jakob Garvelmann, James Berglund, Jean-Baptiste Charlier, Jens Lange, Juan Antonio Barberá Fornell, Junbing Pu, Konstantina Katsanou, Kun Ren, Laura Toran, Laurence Gill, Maria Filippini, Martin Kralik, Matías Mudarra Martínez, Min Zhao, Mingming Luo, Nico Goldscheider, Nikolaos Lambrakis, Pantaleone De Vita, Qiong Xiao, Shi Yu, Silvia Iacurto, Silvio Coda, Ted McCormack, Vincenzo Allocca, W. George Darling, Walter D’Alessandro, Xulei Guo, Yundi Hu, Zhijun Wang, Eva Kaminsky, Jiří Faimon, Marek Lang, Pavel Pracný, and Andreas Hartmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-812, https://doi.org/10.5194/essd-2025-812, 2026
Preprint under review for ESSD
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We developed the first global database of water from karst springs and cave drips that records different forms of oxygen and hydrogen, which naturally trace how rainwater moves through rocks. By gathering and checking thousands of measurements from around the globe and linking them with flow and rainfall data, the database provides a comprehensive view of water movement, allows scientists to compare regions, understand groundwater processes, and support sustainable water management worldwide.
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 Discuss., https://doi.org/10.5194/essd-2025-608, https://doi.org/10.5194/essd-2025-608, 2025
Revised manuscript accepted for ESSD
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We present the second version of a large-sample catchment hydrology dataset for Great Britain. The dataset collates (1) climate, river flow and groundwater timeseries at monthly to hourly timescales, (2) catchment attributes characterising topography, climate, streamflow, land cover, soils, hydrogeology and human influences, and (3) catchment boundaries for 671 catchments across Great Britain. The dataset is publicly available to use in a wide range of environmental and modelling analyses.
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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We investigated what users want from the next-generation of hydrological monitoring systems to better support science and innovation. Through literature review and interviews with UK experts, we found that beyond providing high-quality data, users particularly value additional support for collecting their own data, sharing it with others, and building collaborations with other data users. Designing systems with these needs in mind can greatly boost long-term engagement, data coverage and impact.
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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We used interpretable machine learning to evaluate the accuracy of two continental-scale hydrologic models. We analyzed a suite of catchment attributes and found that soil water content had the biggest impact on model performance, especially in dry areas. Key thresholds for variables like precipitation and road density were identified, which could guide future improvements in these models. Our findings highlight the potential of data-driven methods to inform process-based models.
Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris E. Wendt
Geosci. Model Dev., 18, 4247–4271, https://doi.org/10.5194/gmd-18-4247-2025, https://doi.org/10.5194/gmd-18-4247-2025, 2025
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Groundwater is vital for people and ecosystems, but most physical models lack the representation of surface–groundwater interactions, leading to inaccurate streamflow predictions in groundwater-rich areas. This study presents DECIPHeR-GW v1, which links surface and groundwater systems to improve predictions of streamflow and groundwater levels. Tested across England and Wales, DECIPHeR-GW shows high accuracy, especially in southeast England, making it a valuable tool for large-scale water management.
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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For users of hydrological models, model suitability often hinges on how well simulated outputs match observed discharge. This study highlights the importance of including discharge observation uncertainty in hydrological model performance assessment. We highlight the need to account for this uncertainty in model comparisons and introduce a practical method suitable for any observational time series with available uncertainty estimates.
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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Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large scales. We design a new and simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain, where we can significantly improve the simulation of reservoir-impacted flow.
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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Reanalysis soil moisture products are a vital basis for hydrological and environmental research. Previous product evaluation is limited by the scale difference (point and grid scale). This paper adopts cosmic ray neutron sensor observations, a novel technique that provides root-zone soil moisture at field scale. In this paper, global harmonized CRNS observations were used to assess products. ERA5-Land, SMAPL4, CFSv2, CRA40 and GLEAM show better performance than MERRA2, GLDAS-Noah and JRA55.
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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In this work we characterise annual patterns in baseflow, the component of streamflow that comes from subsurface storage. Our research identified early-, mid-, and late-seasonality of baseflow across catchments in Great Britain over two time blocks: 1976–1995 and 1996–2015, and found that many catchments have earlier seasonal patterns of baseflow in the second time period. These changes are linked to changes in climate signals: snow-melt in highland catchments and effective rainfall changes.
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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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
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
Preprint withdrawn
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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.
Conrad Jackisch, Sibylle K. Hassler, Tobias L. Hohenbrink, Theresa Blume, Hjalmar Laudon, Hilary McMillan, Patricia Saco, and Loes van Schaik
Hydrol. Earth Syst. Sci., 25, 5277–5285, https://doi.org/10.5194/hess-25-5277-2021, https://doi.org/10.5194/hess-25-5277-2021, 2021
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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...
