Articles | Volume 29, issue 5
https://doi.org/10.5194/hess-29-1295-2025
© Author(s) 2025. 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-29-1295-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Mar 2025
Research article |
| 11 Mar 2025
| 11 Mar 2025
Distribution, trends, and drivers of flash droughts in the United Kingdom
UK Centre for Ecology & Hydrology (UKCEH), Wallingford, United Kingdom
Jamie Hannaford
UK Centre for Ecology & Hydrology (UKCEH), Wallingford, United Kingdom
Irish Climate Analysis and Research UnitS (ICARUS), Maynooth University, Maynooth, Ireland
Maliko Tanguy
UK Centre for Ecology & Hydrology (UKCEH), Wallingford, United Kingdom
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom
Related authors
Bethan L. Harris, Christopher M. Taylor, Wouter Dorigo, Ruxandra-Maria Zotta, Darren Ghent, and Iván Noguera
EGUsphere, https://doi.org/10.5194/egusphere-2025-1489, https://doi.org/10.5194/egusphere-2025-1489, 2025
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An improved understanding of land-atmosphere coupling processes during flash (rapid-onset) droughts is needed to aid the development of forecasts for these events. We use satellite observations to investigate the surface energy budget during flash droughts globally. The most intense events show a perturbed surface energy budget months before onset. In some regions, vegetation observations 1–2 months before onset provide information on the likelihood of heat extremes during an event.
Burak Bulut, Eugene Magee, Rachael Armitage, Opeyemi E. Adedipe, Maliko Tanguy, Lucy J. Barker, and Jamie Hannaford
EGUsphere, https://doi.org/10.5194/egusphere-2025-3176, https://doi.org/10.5194/egusphere-2025-3176, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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This study developed a generic machine learning model to forecast drought impacts, with the UK as the main focus. The same model was successfully validated in Germany, showing potential for use in other regions. It captured local patterns of past drought impacts, matching observed events. Using weather and soil data, the model supports early warning and drought risk management. Results are promising, though testing in more climates and conditions would strengthen confidence.
Wilson Chan, Katie Facer-Childs, Maliko Tanguy, Eugene Magee, Burak Bulut, Nicky Stringer, Jeff Knight, and Jamie Hannaford
EGUsphere, https://doi.org/10.5194/egusphere-2025-2369, https://doi.org/10.5194/egusphere-2025-2369, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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The UK Hydrological Outlook river flow forecasting system recently implemented the Historic Weather Analogues method. The method improves winter river flow forecast skill across the UK, especially in upland, fast-responding catchments with low catchment storage. Forecast skill is highest in winter due to accurate prediction of atmospheric circulation patterns like the North Atlantic Oscillation. The Ensemble Streamflow prediction method remains a robust benchmark, especially for other seasons.
Bethan L. Harris, Christopher M. Taylor, Wouter Dorigo, Ruxandra-Maria Zotta, Darren Ghent, and Iván Noguera
EGUsphere, https://doi.org/10.5194/egusphere-2025-1489, https://doi.org/10.5194/egusphere-2025-1489, 2025
Short summary
Short summary
An improved understanding of land-atmosphere coupling processes during flash (rapid-onset) droughts is needed to aid the development of forecasts for these events. We use satellite observations to investigate the surface energy budget during flash droughts globally. The most intense events show a perturbed surface energy budget months before onset. In some regions, vegetation observations 1–2 months before onset provide information on the likelihood of heat extremes during an event.
Maliko Tanguy, Michael Eastman, Amulya Chevuturi, Eugene Magee, Elizabeth Cooper, Robert H. B. Johnson, Katie Facer-Childs, and Jamie Hannaford
Hydrol. Earth Syst. Sci., 29, 1587–1614, https://doi.org/10.5194/hess-29-1587-2025, https://doi.org/10.5194/hess-29-1587-2025, 2025
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Our research compares two techniques, bias correction (BC) and data assimilation (DA), for improving river flow forecasts across 316 UK catchments. BC, which corrects errors after simulation, showed broad improvements, while DA, adjusting model states before forecast, excelled under specific conditions like snowmelt and high baseflows. Each method's unique strengths suit different scenarios. These insights can enhance forecasting systems, offering reliable and user-friendly hydrological predictions.
Jamie Hannaford, Stephen Turner, Amulya Chevuturi, Wilson Chan, Lucy J. Barker, Maliko Tanguy, Simon Parry, and Stuart Allen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-293, https://doi.org/10.5194/hess-2024-293, 2024
Revised manuscript accepted for HESS
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This extended review asks whether hydrological (river flow) droughts have become more severe over time in the UK, based on literature review and original analyses. The UK is a good international exemplar, given the richness of available data. We find that there is little compelling evidence towards a trend towards worsening river flow droughts, at odds with future climate change projections. We outline reasons for this discrepancy and make recommendations to guide researchers and policymakers.
Alison L. Kay, Nick Dunstone, Gillian Kay, Victoria A. Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci., 24, 2953–2970, https://doi.org/10.5194/nhess-24-2953-2024, https://doi.org/10.5194/nhess-24-2953-2024, 2024
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Hydrological hazards affect people and ecosystems, but extremes are not fully understood due to limited observations. A large climate ensemble and simple hydrological model are used to assess unprecedented but plausible floods and droughts. The chain gives extreme flows outside the observed range: summer 2022 ~ 28 % lower and autumn 2023 ~ 42 % higher. Spatial dependence and temporal persistence are analysed. Planning for such events could help water supply resilience and flood risk management.
Ed Hawkins, Nigel Arnell, Jamie Hannaford, and Rowan Sutton
Geosci. Commun., 7, 161–165, https://doi.org/10.5194/gc-7-161-2024, https://doi.org/10.5194/gc-7-161-2024, 2024
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Climate change can often seem rather remote, especially when the discussion is about global averages which appear to have little relevance to local experiences. But those global changes are already affecting people, even if they do not fully realise it, and effective communication of this issue is critical. We use long observations and well-understood physical principles to visually highlight how global emissions influence local flood risk in one river basin in the UK.
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024, https://doi.org/10.5194/nhess-24-1065-2024, 2024
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The most recent drought in the UK was declared in summer 2022. We pooled a large sample of plausible winters from seasonal hindcasts and grouped them into four clusters based on their atmospheric circulation configurations. Drought storylines representative of what the drought could have looked like if winter 2022/23 resembled each winter circulation storyline were created to explore counterfactuals of how bad the 2022 drought could have been over winter 2022/23 and beyond.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Maliko Tanguy, Michael Eastman, Eugene Magee, Lucy J. Barker, Thomas Chitson, Chaiwat Ekkawatpanit, Daniel Goodwin, Jamie Hannaford, Ian Holman, Liwa Pardthaisong, Simon Parry, Dolores Rey Vicario, and Supattra Visessri
Nat. Hazards Earth Syst. Sci., 23, 2419–2441, https://doi.org/10.5194/nhess-23-2419-2023, https://doi.org/10.5194/nhess-23-2419-2023, 2023
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Droughts in Thailand are becoming more severe due to climate change. Understanding the link between drought impacts on the ground and drought indicators used in drought monitoring systems can help increase a country's preparedness and resilience to drought. With a focus on agricultural droughts, we derive crop- and region-specific indicator-to-impact links that can form the basis of targeted mitigation actions and an improved drought monitoring and early warning system in Thailand.
Jamie Hannaford, Jonathan D. Mackay, Matthew Ascott, Victoria A. Bell, Thomas Chitson, Steven Cole, Christian Counsell, Mason Durant, Christopher R. Jackson, Alison L. Kay, Rosanna A. Lane, Majdi Mansour, Robert Moore, Simon Parry, Alison C. Rudd, Michael Simpson, Katie Facer-Childs, Stephen Turner, John R. Wallbank, Steven Wells, and Amy Wilcox
Earth Syst. Sci. Data, 15, 2391–2415, https://doi.org/10.5194/essd-15-2391-2023, https://doi.org/10.5194/essd-15-2391-2023, 2023
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The eFLaG dataset is a nationally consistent set of projections of future climate change impacts on hydrology. eFLaG uses the latest available UK climate projections (UKCP18) run through a series of computer simulation models which enable us to produce future projections of river flows, groundwater levels and groundwater recharge. These simulations are designed for use by water resource planners and managers but could also be used for a wide range of other purposes.
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.
Lucy J. Barker, Jamie Hannaford, and Miaomiao Ma
Proc. IAHS, 383, 273–279, https://doi.org/10.5194/piahs-383-273-2020, https://doi.org/10.5194/piahs-383-273-2020, 2020
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Drought monitoring and early warning are critical aspects of drought preparedness and can help mitigate impacts on society and the environment. We reviewed academic literature in England and Chinese on the topic of drought monitoring and early warning in China. The number of papers on this topic has increased substantially but the most recent advances have not been operationalised. We identify the methods that can be translated from the experimental to national, operational systems.
Miaomiao Ma, Juan Lv, Zhicheng Su, Jamie Hannaford, Hongquan Sun, Yanping Qu, Zikang Xing, Lucy Barker, and Yaxu Wang
Proc. IAHS, 383, 267–272, https://doi.org/10.5194/piahs-383-267-2020, https://doi.org/10.5194/piahs-383-267-2020, 2020
Kerstin Stahl, Jean-Philippe Vidal, Jamie Hannaford, Erik Tijdeman, Gregor Laaha, Tobias Gauster, and Lena M. Tallaksen
Proc. IAHS, 383, 291–295, https://doi.org/10.5194/piahs-383-291-2020, https://doi.org/10.5194/piahs-383-291-2020, 2020
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Numerous indices exist for the description of hydrological drought, some are based on absolute thresholds of overall streamflows or water levels and some are based on relative anomalies with respect to the season. This article discusses paradigms and experiences with such index uses in drought monitoring and drought analysis to raise awareness of the different interpretations of drought severity.
Yaxu Wang, Juan Lv, Jamie Hannaford, Yicheng Wang, Hongquan Sun, Lucy J. Barker, Miaomiao Ma, Zhicheng Su, and Michael Eastman
Nat. Hazards Earth Syst. Sci., 20, 889–906, https://doi.org/10.5194/nhess-20-889-2020, https://doi.org/10.5194/nhess-20-889-2020, 2020
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Due to the specific applicability of drought impact indicators, this study identifies which drought indicators are suitable for characterising drought impacts and the contribution of vulnerability factors. The results show that the relationship varies across different drought impacts and cities; some factors have a strong positive correlation with drought vulnerability. This study can support drought planning work and provide background for the indices used in drought monitoring applications.
Lucy J. Barker, Jamie Hannaford, Simon Parry, Katie A. Smith, Maliko Tanguy, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 23, 4583–4602, https://doi.org/10.5194/hess-23-4583-2019, https://doi.org/10.5194/hess-23-4583-2019, 2019
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It is important to understand historic droughts in order to plan and prepare for possible future events. In this study we use the standardised streamflow index for 1891–2015 to systematically identify, characterise and rank hydrological drought events for 108 near-natural UK catchments. Results show when and where the most severe events occurred and describe events of the early 20th century, providing catchment-scale detail important for both science and planning applications of the future.
Katie A. Smith, Lucy J. Barker, Maliko Tanguy, Simon Parry, Shaun Harrigan, Tim P. Legg, Christel Prudhomme, and Jamie Hannaford
Hydrol. Earth Syst. Sci., 23, 3247–3268, https://doi.org/10.5194/hess-23-3247-2019, https://doi.org/10.5194/hess-23-3247-2019, 2019
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This paper describes the multi-objective calibration approach used to create a consistent dataset of reconstructed daily river flow data for 303 catchments in the UK over 1891–2015. The modelled data perform well when compared to observations, including in the timing and the classification of drought events. This method and data will allow for long-term studies of flow trends and past extreme events that have not been previously possible, enabling water managers to better plan for the future.
Maliko Tanguy, Christel Prudhomme, Katie Smith, and Jamie Hannaford
Earth Syst. Sci. Data, 10, 951–968, https://doi.org/10.5194/essd-10-951-2018, https://doi.org/10.5194/essd-10-951-2018, 2018
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Potential evapotranspiration (PET) is necessary input data for most hydrological models, used to simulate river flows. To reconstruct PET prior to the 1960s, simplified methods are needed because of lack of climate data required for complex methods. We found that the McGuinness–Bordne PET equation, which only needs temperature as input data, works best for the UK provided it is calibrated for local conditions. This method was used to produce a 5 km gridded PET dataset for the UK for 1891–2015.
Shaun Harrigan, Christel Prudhomme, Simon Parry, Katie Smith, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 22, 2023–2039, https://doi.org/10.5194/hess-22-2023-2018, https://doi.org/10.5194/hess-22-2023-2018, 2018
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We benchmarked when and where ensemble streamflow prediction (ESP) is skilful in the UK across a diverse set of 314 catchments. We found ESP was skilful in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. Results have practical implications for current operational use of the ESP method in the UK.
Erik Tijdeman, Jamie Hannaford, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 1051–1064, https://doi.org/10.5194/hess-22-1051-2018, https://doi.org/10.5194/hess-22-1051-2018, 2018
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In this study, a screening approach was applied on a set of streamflow records for which various human influences are indicated to identify streamflow records that have drought characteristics that deviate from those expected under pristine conditions. Prolonged streamflow drought duration, a weaker correlation between streamflow and precipitation, and changes in streamflow drought occurrence over time were related to human influences such as groundwater abstractions or reservoir operations.
Sophie Bachmair, Cecilia Svensson, Ilaria Prosdocimi, Jamie Hannaford, and Kerstin Stahl
Nat. Hazards Earth Syst. Sci., 17, 1947–1960, https://doi.org/10.5194/nhess-17-1947-2017, https://doi.org/10.5194/nhess-17-1947-2017, 2017
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This study tests the potential for developing empirical
drought impact functionsbased on hydro-meteorological drought indicators as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. We showcase three data-driven modeling approaches and assess the effect of impact report quantification method.
Gregor Laaha, Tobias Gauster, Lena M. Tallaksen, Jean-Philippe Vidal, Kerstin Stahl, Christel Prudhomme, Benedikt Heudorfer, Radek Vlnas, Monica Ionita, Henny A. J. Van Lanen, Mary-Jeanne Adler, Laurie Caillouet, Claire Delus, Miriam Fendekova, Sebastien Gailliez, Jamie Hannaford, Daniel Kingston, Anne F. Van Loon, Luis Mediero, Marzena Osuch, Renata Romanowicz, Eric Sauquet, James H. Stagge, and Wai K. Wong
Hydrol. Earth Syst. Sci., 21, 3001–3024, https://doi.org/10.5194/hess-21-3001-2017, https://doi.org/10.5194/hess-21-3001-2017, 2017
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In 2015 large parts of Europe were affected by a drought. In terms of low flow magnitude, a region around the Czech Republic was most affected, with return periods > 100 yr. In terms of deficit volumes, the drought was particularly severe around S. Germany where the event lasted notably long. Meteorological and hydrological events developed differently in space and time. For an assessment of drought impacts on water resources, hydrological data are required in addition to meteorological indices.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
S. Bachmair, C. Svensson, J. Hannaford, L. J. Barker, and K. Stahl
Hydrol. Earth Syst. Sci., 20, 2589–2609, https://doi.org/10.5194/hess-20-2589-2016, https://doi.org/10.5194/hess-20-2589-2016, 2016
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To date, there is little empirical evidence as to which indicator best represents drought impact occurrence for any given region and/or sector. We therefore exploited text-based data from the European Drought Impact report Inventory (EDII) to evaluate drought indicators, empirically determine indicator thresholds, and model drought impacts. A quantitative analysis using Germany and the UK as a testbed proved to be a useful tool for objectively appraising drought indicators.
Lucy J. Barker, Jamie Hannaford, Andrew Chiverton, and Cecilia Svensson
Hydrol. Earth Syst. Sci., 20, 2483–2505, https://doi.org/10.5194/hess-20-2483-2016, https://doi.org/10.5194/hess-20-2483-2016, 2016
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Standardised meteorological indicators are widely used in drought monitoring, but applications to hydrological drought are less extensive. Here we assess the utility of standardised indicators for characterising drought duration, severity and propagation in a diverse set of 121 UK catchments. Spatial variations in streamflow drought characteristics reflect differences in drought propagation behaviour that are themselves largely driven by heterogeneity in catchment properties around the UK.
V. D. J. Keller, M. Tanguy, I. Prosdocimi, J. A. Terry, O. Hitt, S. J. Cole, M. Fry, D. G. Morris, and H. Dixon
Earth Syst. Sci. Data, 7, 143–155, https://doi.org/10.5194/essd-7-143-2015, https://doi.org/10.5194/essd-7-143-2015, 2015
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The CEH – Gridded Estimates of Areal Rainfall (CEH–GEAR) dataset contains 1 km gridded estimates of daily and monthly rainfall for Great Britain and Northern Ireland (plus approximately 3000 km2 in the Republic of Ireland) from 1890 to 2012. The rainfall estimates are derived from the Met Office national database of observed precipitation, using a natural neighbour interpolation methodology which includes a normalisation step based on average annual rainfall.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
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. Hannaford, G. Buys, K. Stahl, and L. M. Tallaksen
Hydrol. Earth Syst. Sci., 17, 2717–2733, https://doi.org/10.5194/hess-17-2717-2013, https://doi.org/10.5194/hess-17-2717-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
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Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
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Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
Hydrol. Earth Syst. Sci., 29, 3073–3100, https://doi.org/10.5194/hess-29-3073-2025, https://doi.org/10.5194/hess-29-3073-2025, 2025
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We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical or machine learning techniques. Our results show that this approach outperforms traditional methods, especially in remote ungauged areas, suggesting that it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
Kazeem Abiodun Ishola, Gerald Mills, Ankur Prabhat Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci., 29, 2551–2582, https://doi.org/10.5194/hess-29-2551-2025, https://doi.org/10.5194/hess-29-2551-2025, 2025
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Global soil information introduces uncertainty into models that simulate soil hydrothermal changes. Using the Noah with Multiparameterization (Noah-MP) model with two different global soil datasets, we find under-represented soil properties in wet loam, causing a dry bias in soil moisture. This bias is more pronounced and drought categories are more severe in the SoilGrids dataset. We conclude that models should incorporate detailed, region-specific soil information to minimize model uncertainties.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew W. Wood
Hydrol. Earth Syst. Sci., 29, 2393–2406, https://doi.org/10.5194/hess-29-2393-2025, https://doi.org/10.5194/hess-29-2393-2025, 2025
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Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.
Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 29, 2407–2427, https://doi.org/10.5194/hess-29-2407-2025, https://doi.org/10.5194/hess-29-2407-2025, 2025
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The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
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We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
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Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
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Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Xuetong Wang, Raied S. Alharbi, Oscar M. Baez-Villanueva, Amy Green, Matthew F. McCabe, Yoshihide Wada, Albert I. J. M. Van Dijk, Muhammad A. Abid, and Hylke Beck
EGUsphere, https://doi.org/10.5194/egusphere-2025-254, https://doi.org/10.5194/egusphere-2025-254, 2025
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Our paper introduces Saudi Rainfall (SaRa), a high-resolution, near real-time rainfall product for the Arabian Peninsula. Using machine learning, SaRa combines multiple satellite and (re)analysis datasets with static predictors, outperforming existing products in the region. With the fast development and continuing growth in water demand over this region, SaRa could help to address water challenges and support resource management.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
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Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
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Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
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We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3988, https://doi.org/10.5194/egusphere-2024-3988, 2025
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Our research highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate disasters in cities. We find that inadequate representation of water surfaces, hydraulic systems, and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Gabriel Rondeau-Genesse, Louis-Philippe Caron, Kristelle Audet, Laurent Da Silva, Daniel Tarte, Rachel Parent, Élise Comeau, and Dominic Matte
EGUsphere, https://doi.org/10.5194/egusphere-2024-2595, https://doi.org/10.5194/egusphere-2024-2595, 2024
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The 2021 drought in Quebec showcased the province’s potential vulnerability. This study uses a storyline approach to explore impacts of future extreme droughts under +2 °C and +3 °C warming scenarios. By combining regional climate and hydrological simulations, it highlights the potential for severe water deficits. Collaboration with water management experts helped project the impacts of those future extreme droughts and their consequences for ecosystems and human activities.
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
EGUsphere, https://doi.org/10.5194/egusphere-2024-2312, https://doi.org/10.5194/egusphere-2024-2312, 2024
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To better utilize a given set of predictions, identifying “forecasts of opportunity” has great value. It can help anticipate when prediction skill will be higher. This study reveals that when strong L-A coupling is detected 3–4 weeks into a forecast, the prediction skill for surface air temperature at this lead increases across the Midwest and northern Great Plains. Regions experiencing strong L-A coupling exhibit warm and dry anomalies, leading to improved predictions of abnormally warm events.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, and Miroslav Trnka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1434, https://doi.org/10.5194/egusphere-2024-1434, 2024
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We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, which was clustered into 775/630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
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Short summary
The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The...
