Articles | Volume 25, issue 10
https://doi.org/10.5194/hess-25-5355-2021
© Author(s) 2021. 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-25-5355-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Oct 2021
Research article |
| 05 Oct 2021
| 05 Oct 2021
How is Baseflow Index (BFI) impacted by water resource management practices?
British Geological Survey, Wallingford, OX10 8BB, UK
Mengyi Gong
British Geological Survey, Keyworth, NG12 5GG, UK
Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, UK
Benjamin P. Marchant
British Geological Survey, Wallingford, OX10 8BB, UK
Gemma Coxon
School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
Nans Addor
Geography, University of Exeter, Exeter, EX4 4RJ, UK
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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Preprint withdrawn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.
Abrar Habib, Athanasios Paschalis, Adrian P. Butler, Christian Onof, John P. Bloomfield, and James P. R. Sorensen
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Preprint withdrawn
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Components of the hydrological cycle exhibit a “memory” in their behaviour which quantifies how long a variable would stay at high/low values. Being able to model and understand what affects it is vital for an accurate representation of the hydrological elements. In the current work, it is found that rainfall affects the fractal behaviour of groundwater levels, which implies that changes to rainfall due to climate change will change the periods of flood and drought in groundwater-fed catchments.
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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.
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Hydrol. Earth Syst. Sci., 26, 2449–2467, https://doi.org/10.5194/hess-26-2449-2022, https://doi.org/10.5194/hess-26-2449-2022, 2022
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We highlight the importance of the North Atlantic Oscillation in controlling droughts in the UK. Specifically, multi-year cycles in the NAO are shown to influence the frequency of droughts and this influence changes considerably over time. We show that the influence of these varying controls is similar to the projected effects of climate change on water resources. We also show that these time-varying behaviours have important implications for water resource forecasts used for drought planning.
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Hydrol. Earth Syst. Sci., 25, 2223–2237, https://doi.org/10.5194/hess-25-2223-2021, https://doi.org/10.5194/hess-25-2223-2021, 2021
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We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Bentje Brauns, Daniela Cuba, John P. Bloomfield, David M. Hannah, Christopher Jackson, Ben P. Marchant, Benedikt Heudorfer, Anne F. Van Loon, Hélène Bessière, Bo Thunholm, and Gerhard Schubert
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William Rust, Ian Holman, John Bloomfield, Mark Cuthbert, and Ron Corstanje
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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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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-427, https://doi.org/10.5194/essd-2024-427, 2024
Preprint under review for ESSD
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Large-sample datasets are essential in hydrological science to support modelling studies and advance process understanding. Caravan is a community initiative to create a large-sample hydrology dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world. This dataset is a subset of hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy.
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.
Nele Reyniers, Qianyu Zha, Nans Addor, Timothy J. Osborn, Nicole Forstenhäusler, and Yi He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-132, https://doi.org/10.5194/essd-2024-132, 2024
Revised manuscript accepted for ESSD
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We present two sets of bias-corrected UK Climate Projections 2018 (UKCP18) regional projections of temperature, precipitation and potential evapotranspiration for 1981–2080. All 12 members of the UKCP18 regional ensemble were bias-corrected using (1) empirical quantile mapping and (2) a change-preserving variant. The two methods were evaluated and compared to guide dataset application. The datasets improve the usability of UKCP18 and serve as a reference for selecting bias correction methods.
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.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
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CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
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
Short summary
Short summary
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.
Nele Reyniers, Timothy J. Osborn, Nans Addor, and Geoff Darch
Hydrol. Earth Syst. Sci., 27, 1151–1171, https://doi.org/10.5194/hess-27-1151-2023, https://doi.org/10.5194/hess-27-1151-2023, 2023
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In an analysis of future drought projections for Great Britain based on the Standardised Precipitation Index and the Standardised Precipitation Evapotranspiration Index, we show that the choice of drought indicator has a decisive influence on the resulting projected changes in drought characteristics, although both result in increased drying. This highlights the need to understand the interplay between increasing atmospheric evaporative demand and drought impacts under a changing climate.
Abrar Habib, Athanasios Paschalis, Adrian P. Butler, Christian Onof, John P. Bloomfield, and James P. R. Sorensen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-27, https://doi.org/10.5194/hess-2023-27, 2023
Preprint withdrawn
Short summary
Short summary
Components of the hydrological cycle exhibit a “memory” in their behaviour which quantifies how long a variable would stay at high/low values. Being able to model and understand what affects it is vital for an accurate representation of the hydrological elements. In the current work, it is found that rainfall affects the fractal behaviour of groundwater levels, which implies that changes to rainfall due to climate change will change the periods of flood and drought in groundwater-fed catchments.
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
Short summary
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.
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.
William Rust, John P. Bloomfield, Mark Cuthbert, Ron Corstanje, and Ian Holman
Hydrol. Earth Syst. Sci., 26, 2449–2467, https://doi.org/10.5194/hess-26-2449-2022, https://doi.org/10.5194/hess-26-2449-2022, 2022
Short summary
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We highlight the importance of the North Atlantic Oscillation in controlling droughts in the UK. Specifically, multi-year cycles in the NAO are shown to influence the frequency of droughts and this influence changes considerably over time. We show that the influence of these varying controls is similar to the projected effects of climate change on water resources. We also show that these time-varying behaviours have important implications for water resource forecasts used for drought planning.
Andrew J. Newman, Amanda G. Stone, Manabendra Saharia, Kathleen D. Holman, Nans Addor, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 5603–5621, https://doi.org/10.5194/hess-25-5603-2021, https://doi.org/10.5194/hess-25-5603-2021, 2021
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This study assesses methods that estimate flood return periods to identify when we would obtain a large flood return estimate change if the method or input data were changed (sensitivities). We include an examination of multiple flood-generating models, which is a novel addition to the flood estimation literature. We highlight the need to select appropriate flood models for the study watershed. These results will help operational water agencies develop more robust risk assessments.
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.
Doris E. Wendt, John P. Bloomfield, Anne F. Van Loon, Margaret Garcia, Benedikt Heudorfer, Joshua Larsen, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 21, 3113–3139, https://doi.org/10.5194/nhess-21-3113-2021, https://doi.org/10.5194/nhess-21-3113-2021, 2021
Short summary
Short summary
Managing water demand and supply during droughts is complex, as highly pressured human–water systems can overuse water sources to maintain water supply. We evaluated the impact of drought policies on water resources using a socio-hydrological model. For a range of hydrogeological conditions, we found that integrated drought policies reduce baseflow and groundwater droughts most if extra surface water is imported, reducing the pressure on water resources during droughts.
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021, https://doi.org/10.5194/hess-25-5425-2021, 2021
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Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.
Keirnan J. A. Fowler, Suwash Chandra Acharya, Nans Addor, Chihchung Chou, and Murray C. Peel
Earth Syst. Sci. Data, 13, 3847–3867, https://doi.org/10.5194/essd-13-3847-2021, https://doi.org/10.5194/essd-13-3847-2021, 2021
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This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments with long-term monitoring, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://doi.pangaea.de/10.1594/PANGAEA.921850.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
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We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
William Rust, Mark Cuthbert, John Bloomfield, Ron Corstanje, Nicholas Howden, and Ian Holman
Hydrol. Earth Syst. Sci., 25, 2223–2237, https://doi.org/10.5194/hess-25-2223-2021, https://doi.org/10.5194/hess-25-2223-2021, 2021
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In this paper, we find evidence for the cyclical behaviour (on a 7-year basis) in UK streamflow records that match the main cycle of the North Atlantic Oscillation. Furthermore, we find that the strength of these 7-year cycles in streamflow is dependent on proportional contributions from groundwater and the response times of the underlying groundwater systems. This may allow for improvements to water management practices through better understanding of long-term streamflow behaviour.
Doris E. Wendt, Anne F. Van Loon, John P. Bloomfield, and David M. Hannah
Hydrol. Earth Syst. Sci., 24, 4853–4868, https://doi.org/10.5194/hess-24-4853-2020, https://doi.org/10.5194/hess-24-4853-2020, 2020
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Groundwater use changes the availability of groundwater, especially during droughts. This study investigates the impact of groundwater use on groundwater droughts. A methodological framework is presented that was developed and applied to the UK. We identified an asymmetric impact of groundwater use on droughts, which highlights the relation between short-term and long-term strategies for sustainable groundwater use.
Gemma Coxon, Nans Addor, John P. Bloomfield, Jim Freer, Matt Fry, Jamie Hannaford, Nicholas J. K. Howden, Rosanna Lane, Melinda Lewis, Emma L. Robinson, Thorsten Wagener, and Ross Woods
Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, https://doi.org/10.5194/essd-12-2459-2020, 2020
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We present the first large-sample catchment hydrology dataset for Great Britain. The dataset collates river flows, catchment attributes, and catchment boundaries for 671 catchments across Great Britain. We characterise the topography, climate, streamflow, land cover, soils, hydrogeology, human influence, and discharge uncertainty of each catchment. The dataset is publicly available for the community to use in a wide range of environmental and modelling analyses.
Bentje Brauns, Daniela Cuba, John P. Bloomfield, David M. Hannah, Christopher Jackson, Ben P. Marchant, Benedikt Heudorfer, Anne F. Van Loon, Hélène Bessière, Bo Thunholm, and Gerhard Schubert
Proc. IAHS, 383, 297–305, https://doi.org/10.5194/piahs-383-297-2020, https://doi.org/10.5194/piahs-383-297-2020, 2020
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In Europe, ca. 65% of drinking water is groundwater. Its replenishment depends on rainfall, but droughts may cause groundwater levels to fall below normal. These
groundwater droughtscan limit supply, making it crucial to understand their regional connection. The Groundwater Drought Initiative (GDI) assesses spatial patterns in historic—recent groundwater droughts across Europe for the first time. Using an example dataset, we describe the background to the GDI and its methodological approach.
Vinícius B. P. Chagas, Pedro L. B. Chaffe, Nans Addor, Fernando M. Fan, Ayan S. Fleischmann, Rodrigo C. D. Paiva, and Vinícius A. Siqueira
Earth Syst. Sci. Data, 12, 2075–2096, https://doi.org/10.5194/essd-12-2075-2020, https://doi.org/10.5194/essd-12-2075-2020, 2020
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We present a new dataset for large-sample hydrological studies in Brazil. The dataset encompasses daily observed streamflow from 3679 gauges, as well as meteorological forcing for 897 selected catchments. It also includes 65 attributes covering topographic, climatic, hydrologic, land cover, geologic, soil, and human intervention variables. CAMELS-BR is publicly available and will enable new insights into the hydrological behavior of catchments in Brazil.
Kirsti Hakala, Nans Addor, Thibault Gobbe, Johann Ruffieux, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 3815–3833, https://doi.org/10.5194/hess-24-3815-2020, https://doi.org/10.5194/hess-24-3815-2020, 2020
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Under a changing climate, reliable information on future hydrological conditions is necessary to inform water resource management. Here, we collaborated with a hydropower company that selected streamflow and energy demand indices. Using these indices, we identified stakeholder needs and used this to tailor the production of our climate change impact projections. We show that opportunities and risks for a hydropower company depend on a range of factors beyond those covered by traditional studies.
Rosanna A. Lane, Gemma Coxon, Jim E. Freer, Thorsten Wagener, Penny J. Johnes, John P. Bloomfield, Sheila Greene, Christopher J. A. Macleod, and Sim M. Reaney
Hydrol. Earth Syst. Sci., 23, 4011–4032, https://doi.org/10.5194/hess-23-4011-2019, https://doi.org/10.5194/hess-23-4011-2019, 2019
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We evaluated four hydrological model structures and their parameters on over 1100 catchments across Great Britain, considering modelling uncertainties. Models performed well for most catchments but failed in parts of Scotland and south-eastern England. Failures were often linked to inconsistencies in the water balance. This research shows what conceptual lumped models can achieve, gives insights into where and why these models may fail, and provides a benchmark of national modelling capability.
William Rust, Ian Holman, John Bloomfield, Mark Cuthbert, and Ron Corstanje
Hydrol. Earth Syst. Sci., 23, 3233–3245, https://doi.org/10.5194/hess-23-3233-2019, https://doi.org/10.5194/hess-23-3233-2019, 2019
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We show that major groundwater resources in the UK exhibit strong multi-year cycles, accounting for up to 40 % of total groundwater level variability. By comparing these cycles with recorded widespread groundwater droughts over the past 60 years, we provide evidence that climatic systems (such as the North Atlantic Oscillation) ultimately drive drought-risk periods in UK groundwater. The recursive nature of these drought-risk periods may lead to improved preparedness for future droughts.
Gemma Coxon, Jim Freer, Rosanna Lane, Toby Dunne, Wouter J. M. Knoben, Nicholas J. K. Howden, Niall Quinn, Thorsten Wagener, and Ross Woods
Geosci. Model Dev., 12, 2285–2306, https://doi.org/10.5194/gmd-12-2285-2019, https://doi.org/10.5194/gmd-12-2285-2019, 2019
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DECIPHeR (Dynamic fluxEs and ConnectIvity for Predictions of Hydrology) is a new modelling framework that can be applied from small catchment to continental scales for complex river basins. This paper describes the modelling framework and its key components and demonstrates the model’s ability to be applied across a large model domain. This work highlights the potential for catchment- to continental-scale predictions of streamflow to support robust environmental management and policy decisions.
Anne F. Van Loon, Sally Rangecroft, Gemma Coxon, José Agustín Breña Naranjo, Floris Van Ogtrop, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 23, 1725–1739, https://doi.org/10.5194/hess-23-1725-2019, https://doi.org/10.5194/hess-23-1725-2019, 2019
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We explore the use of the classic
paired-catchmentapproach to quantify human influence on hydrological droughts. In this approach two similar catchments are compared and differences are attributed to the human activity present in one. In two case studies in UK and Australia, we found that groundwater abstraction aggravated streamflow drought by > 200 % and water transfer alleviated droughts with 25–80 %. Understanding the human influence on droughts can support water management decisions.
John P. Bloomfield, Benjamin P. Marchant, and Andrew A. McKenzie
Hydrol. Earth Syst. Sci., 23, 1393–1408, https://doi.org/10.5194/hess-23-1393-2019, https://doi.org/10.5194/hess-23-1393-2019, 2019
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Groundwater is susceptible to drought due to natural variations in climate; however, to date there is no evidence of a relationship between climate change and groundwater drought. Using two long groundwater level records from the UK, we document increases in frequency, magnitude and intensity and changes in duration of groundwater drought associated with climate warming and infer that, given the extent of shallow groundwater globally, warming may widely effect changes to groundwater droughts.
Camila Alvarez-Garreton, Pablo A. Mendoza, Juan Pablo Boisier, Nans Addor, Mauricio Galleguillos, Mauricio Zambrano-Bigiarini, Antonio Lara, Cristóbal Puelma, Gonzalo Cortes, Rene Garreaud, James McPhee, and Alvaro Ayala
Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, https://doi.org/10.5194/hess-22-5817-2018, 2018
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CAMELS-CL provides a catchment dataset in Chile, including 516 catchment boundaries, hydro-meteorological time series, and 70 catchment attributes quantifying catchments' climatic, hydrological, topographic, geological, land cover and anthropic intervention features. By using CAMELS-CL, we characterise hydro-climatic regional variations, assess precipitation and potential evapotranspiration uncertainties, and analyse human intervention impacts on catchment response.
Andreas Paul Zischg, Guido Felder, Rolf Weingartner, Niall Quinn, Gemma Coxon, Jeffrey Neal, Jim Freer, and Paul Bates
Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
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We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.
Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, https://doi.org/10.5194/hess-22-1775-2018, 2018
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Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.
Simon Brenner, Gemma Coxon, Nicholas J. K. Howden, Jim Freer, and Andreas Hartmann
Nat. Hazards Earth Syst. Sci., 18, 445–461, https://doi.org/10.5194/nhess-18-445-2018, https://doi.org/10.5194/nhess-18-445-2018, 2018
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In this study we simulate groundwater levels with a semi-distributed karst model. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. We show that our approach is able to predict groundwater levels across all considered timescales up to the 75th percentile. We then use our approach to assess future changes in groundwater dynamics and show that projected climate changes may lead to generally lower groundwater levels.
Benoit P. Guillod, Richard G. Jones, Simon J. Dadson, Gemma Coxon, Gianbattista Bussi, James Freer, Alison L. Kay, Neil R. Massey, Sarah N. Sparrow, David C. H. Wallom, Myles R. Allen, and Jim W. Hall
Hydrol. Earth Syst. Sci., 22, 611–634, https://doi.org/10.5194/hess-22-611-2018, https://doi.org/10.5194/hess-22-611-2018, 2018
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Assessing the potential impacts of extreme events such as drought and flood requires large datasets of such events, especially when looking at the most severe and rare events. Using a state-of-the-art climate modelling infrastructure that is simulating large numbers of weather time series on volunteers' computers, we generate such a large dataset for the United Kingdom. The dataset covers the recent past (1900–2006) as well as two future time periods (2030s and 2080s).
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
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Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
Nans Addor, Andrew J. Newman, Naoki Mizukami, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, https://doi.org/10.5194/hess-21-5293-2017, 2017
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We introduce a data set describing the landscape of 671 catchments in the contiguous USA: we synthesized various data sources to characterize the topography, climate, streamflow, land cover, soil, and geology of each catchment. This extends the daily time series of meteorological forcing and discharge provided by an earlier study. The diversity of these catchments will help to improve our understanding and modeling of how the interplay between catchment attributes shapes hydrological processes.
N. A. L. Archer, B. R. Rawlins, B. P. Machant, J. D. Mackay, and P. I. Meldrum
SOIL Discuss., https://doi.org/10.5194/soil-2016-40, https://doi.org/10.5194/soil-2016-40, 2016
Preprint withdrawn
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This study investigates the importance of using techniques, such as soil water release curves, soil shrinkage measurements and field observations to create reference points to determine the best-fit calibrations for estimating volumetric water content (VWC). We also show that calibrating soil moisture sensors in disturbed clay soils over-estimates VWC and we suggest that undisturbed soil cores provide better calibrations to estimate VWC in clay soils.
J. P. Bloomfield, B. P. Marchant, S. H. Bricker, and R. B. Morgan
Hydrol. Earth Syst. Sci., 19, 4327–4344, https://doi.org/10.5194/hess-19-4327-2015, https://doi.org/10.5194/hess-19-4327-2015, 2015
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To improve the design of drought monitoring networks and water resource management during episodes of drought, there is a need for a better understanding of spatial variations in the response of aquifers to major meteorological droughts. This paper is the first to describe a suite of methods to quantify such variations. Using an analysis of groundwater level data for a case study from the UK, the influence of catchment characteristics on the varied response of groundwater to droughts is explored
A. Chiverton, J. Hannaford, I. P. Holman, R. Corstanje, C. Prudhomme, T. M. Hess, and J. P. Bloomfield
Hydrol. Earth Syst. Sci., 19, 2395–2408, https://doi.org/10.5194/hess-19-2395-2015, https://doi.org/10.5194/hess-19-2395-2015, 2015
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Current hydrological change detection methods are subject to a host of limitations. This paper develops a new method, temporally shifting variograms (TSVs), which characterises variability in the river flow regime using several parameters, changes in which can then be attributed to precipitation characteristics. We demonstrate the use of the method through application to 94 UK catchments, showing that periods of extremes as well as more subtle changes can be detected.
C. K. Folland, J. Hannaford, J. P. Bloomfield, M. Kendon, C. Svensson, B. P. Marchant, J. Prior, and E. Wallace
Hydrol. Earth Syst. Sci., 19, 2353–2375, https://doi.org/10.5194/hess-19-2353-2015, https://doi.org/10.5194/hess-19-2353-2015, 2015
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The English Lowlands is a heavily populated, water-stressed region, which is vulnerable to long droughts typically associated with dry winters. We conduct a long-term (1910-present) quantitative analysis of precipitation, flow and groundwater droughts for the region, and then review potential climatic drivers. No single driver is dominant, but we demonstrate a physical link between La Nina conditions, winter rainfall and long droughts in the region.
J. P. Bloomfield and B. P. Marchant
Hydrol. Earth Syst. Sci., 17, 4769–4787, https://doi.org/10.5194/hess-17-4769-2013, https://doi.org/10.5194/hess-17-4769-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Long short-term memory networks for enhancing real-time flood forecasts: a case study for an underperforming hydrologic model
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Extended-range forecasting of stream water temperature with deep-learning models
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Projections of streamflow intermittence under climate change in European drying river networks
Economic valuation of subsurface water contributions to watershed ecosystem services using a fully integrated groundwater–surface-water model
Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events
CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric–hydrological model
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?
State updating of the Xin'anjiang model: joint assimilating streamflow and multi-source soil moisture data via the asynchronous ensemble Kalman filter with enhanced error models
Improving the hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations
Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments
The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa
Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
Seasonal variation in land cover estimates reveals sensitivities and opportunities for environmental models
Estimating response times, flow velocities, and roughness coefficients of Canadian Prairie basins
Learning landscape features from streamflow with autoencoders
Hydrological regime index for non-perennial rivers
On the use of streamflow transformations for hydrological model calibration
Simulation-based inference for parameter estimation of complex watershed simulators
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
CONCN: A high-resolution, integrated surface water-groundwater ParFlow modeling platform of continental China
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Assesing the Value of High-Resolution Data and Parameters Transferability Across Temporal Scales in Hydrological Modeling: A Case Study in Northern China
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Assessing the adequacy of traditional hydrological models for climate change impact studies: A case for long-short-term memory (LSTM) neural networks
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025, https://doi.org/10.5194/hess-29-1981-2025, 2025
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Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact that they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what they truly reflect in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and timescales for accurate drought characterization and monitoring.
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025, https://doi.org/10.5194/hess-29-1939-2025, 2025
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Accurate early-warning systems are crucial for reducing the damage caused by flooding events. In this study, we explored the potential of long short-term memory networks for enhancing the forecast accuracy of hydrologic models employed in operational flood forecasting. The presented approach elevated the investigated hydrologic model’s forecast accuracy for further ahead predictions and at flood event runoff.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025, https://doi.org/10.5194/hess-29-1919-2025, 2025
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Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
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In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025, https://doi.org/10.5194/hess-29-1685-2025, 2025
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We generate operational forecasts of daily maximum stream water temperature for 32 consecutive days at 54 stations in Switzerland with our best-performing data-driven model. The average forecast error is 0.38 °C for 1 d ahead and increases to 0.90 °C for 32 d ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025, https://doi.org/10.5194/hess-29-1749-2025, 2025
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Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025, https://doi.org/10.5194/hess-29-1615-2025, 2025
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Our study projects how climate change will affect the drying of river segments and stream networks in Europe, using advanced modelling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent and intense and will start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists for evaluating the ecological health of river ecosystem.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 1549–1568, https://doi.org/10.5194/hess-29-1549-2025, https://doi.org/10.5194/hess-29-1549-2025, 2025
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This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1277–1294, https://doi.org/10.5194/hess-29-1277-2025, https://doi.org/10.5194/hess-29-1277-2025, 2025
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Data-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
Hydrol. Earth Syst. Sci., 29, 1061–1082, https://doi.org/10.5194/hess-29-1061-2025, https://doi.org/10.5194/hess-29-1061-2025, 2025
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This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1033–1060, https://doi.org/10.5194/hess-29-1033-2025, https://doi.org/10.5194/hess-29-1033-2025, 2025
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Owing to differences in the existing published results, we conducted a detailed analysis of the runoff components and future trends in the Yarlung Tsangpo River basin and found that the contributions of snowmelt and glacier melt runoff to streamflow (both ~5 %) are limited and much lower than previous results. The streamflow in this area will continuously increase in the future, but the overestimated contribution of glacier melt could lead to an underestimation of this increasing trend.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
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This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025, https://doi.org/10.5194/hess-29-785-2025, 2025
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine learning (ML) models are increasingly being applied for flood forecasting. Such models are typically trained on large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets that maximise the spatio-temporal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025, https://doi.org/10.5194/hess-29-753-2025, 2025
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This study presents the first distributed hydrological simulation which confirms claims raised by historians that the eastward diversion project of the Tone River in Japan was conducted 4 centuries ago to increase low flows and subsequent travelling possibilities surrounding the capital, Edo (Tokyo), using inland navigation. We showed that great steps forward can be made for improving quality of life with small human engineering waterworks and small interventions in the regime of natural flows.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
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This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
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Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
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Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
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Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
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The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
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Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
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This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
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Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
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We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Pablo Fernando Dornes and Rocío Noelia Comas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-338, https://doi.org/10.5194/hess-2024-338, 2024
Revised manuscript accepted for HESS
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The Desaguadero-Salado-Chadiluevú-Curacó (DSCC) River is a semiarid river which is severely dammed in its tributaries which collect the snowmelt runoff. This runoff feeds mostly gravitational irrigation systems of very low efficiency. As a result, the DSCC River does not have natural runoff. The proposed Hydrological Regime Index (HRI) is able to discriminate and quantify regime alterations under permanent and non-permanent flow conditions and with low and high impoundment conditions.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-292, https://doi.org/10.5194/hess-2024-292, 2024
Revised manuscript accepted for HESS
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We developed the first high-resolution, integrated surface water-groundwater hydrologic model of the entire continental China using ParFlow. The model shows good performance of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-2966, https://doi.org/10.5194/egusphere-2024-2966, 2024
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We assessed the value of high-resolution data and parameters transferability across temporal scales based on 7 catchments in northern China. We found that higher resolution data does not always improve model performance, questioning the need for such data; Model parameters are transferable across different data resolutions, but not across computational time steps. It is recommended to utilize smaller computational time step when building hydrological models even without high-resolution data.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
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This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-279, https://doi.org/10.5194/hess-2024-279, 2024
Revised manuscript accepted for HESS
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Hydrologic models are needed to provide simulations of water availability, floods and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models, and thus cannot easily be used to select an appropriate model for a specific place.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
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Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
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We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
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An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Jean-Luc Martel, François Brissette, Richard Arsenault, Richard Turcotte, Mariana Castañeda-Gonzalez, William Armstrong, Edouard Mailhot, Jasmine Pelletier-Dumont, Gabriel Rondeau-Genesse, and Louis-Philippe Caron
EGUsphere, https://doi.org/10.5194/egusphere-2024-2133, https://doi.org/10.5194/egusphere-2024-2133, 2024
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This study compares Long Short-Term Memory (LSTM) neural networks with traditional hydrological models to predict future streamflow under climate change. Using data from 148 catchments, it finds that LSTM models, which learn from extensive data sequences, perform differently and often better than traditional hydrolgical models. The continental LSTM model, which includes data from diverse climate zones, is particularly effective for understanding climate impacts on water resources.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
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Addor, N., Nearing, G., Prieto, C., Newman, A. J., Le Vine, N., and Clark, M.
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Short summary
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.
Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as...
