Articles | Volume 26, issue 1
https://doi.org/10.5194/nhess-26-343-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-343-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jan 2026
Research article |
| 20 Jan 2026
| 20 Jan 2026
Signals without action: a value chain analysis of Luxembourg's 2021 flood disaster
Jeff Da Costa
CORRESPONDING AUTHOR
Department Geography and Environmental Science, University of Reading, RG6 6AB, Reading, United Kingdom
Elizabeth Ebert
Bureau of Meteorology, 3001, Melbourne, Victoria, Australia
David Hoffmann
Bureau of Meteorology, 3001, Melbourne, Victoria, Australia
Hannah L. Cloke
Department Geography and Environmental Science, University of Reading, RG6 6AB, Reading, United Kingdom
Department of Meteorology, University of Reading, RG6 6ET, Reading, United Kingdom
Jessica Neumann
Department Geography and Environmental Science, University of Reading, RG6 6AB, Reading, United Kingdom
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Douglas Mulangwa, Evet Naturinda, Charles Koboji, Benon T. Zaake, Emily Black, Hannah Cloke, and Elisabeth M. Stephens
EGUsphere, https://doi.org/10.5194/egusphere-2025-5009, https://doi.org/10.5194/egusphere-2025-5009, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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This study traced how floodwaters move from Lake Victoria to the Sudd Wetland to explain South Sudan's 2022 floods. Using satellite images, rainfall, and lake level data, we found that water takes about 17 months to travel through the system, much longer than previously thought. The findings show that long-lasting floods were caused by slow movement and delays within the lakes and wetlands, helping improve flood forecasts and early warning in the White Nile Basin.
Gwyneth Matthews, Hannah L. Cloke, Sarah L. Dance, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 29, 6157–6179, https://doi.org/10.5194/hess-29-6157-2025, https://doi.org/10.5194/hess-29-6157-2025, 2025
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Forecasts provide information crucial for managing floods and for water resource planning, but they often have errors. “Post-processing” reduces these errors but is usually only applied at river gauges, leaving areas without gauges uncorrected. We developed a new method that uses spatial information contained within the forecast to spread information about the errors from gauged locations to ungauged areas. Our results show that the method successfully makes river forecasts more accurate.
Hamidreza Mosaffa, Florian Pappenberger, Christel Prudhomme, Matthew Chantry, Christoph Rüdiger, and Hannah Cloke
EGUsphere, https://doi.org/10.5194/egusphere-2025-5008, https://doi.org/10.5194/egusphere-2025-5008, 2025
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This study improves river flow prediction by combining two types of artificial intelligence models to better represent how rainfall turns into runoff and moves through river systems. Tested on the Upper Danube River Basin, the new model more accurately predicts streamflow, especially in large and connected rivers. These findings can help enhance flood forecasting and water management.
Joy Ommer, Milan Kalas, Jessica Neumann, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 25, 2929–2938, https://doi.org/10.5194/nhess-25-2929-2025, https://doi.org/10.5194/nhess-25-2929-2025, 2025
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What do we regret about our disaster preparedness? This paper explores the regrets of 438 citizens who were affected by flooding in Germany in 2021. It shows that regret can primarily be associated with inaction (instead of actions), which contrasts with psychological studies from fields other than disaster science. The findings of this study suggest that the no-regret approach could be a suitable framework for moving towards longer-term disaster preparedness to reduce future regrets.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
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What’s the worst that could happen? Recent floods are often claimed to be beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe-weather forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Clare Lewis, Tim Smyth, Jess Neumann, and Hannah Cloke
Nat. Hazards Earth Syst. Sci., 24, 121–131, https://doi.org/10.5194/nhess-24-121-2024, https://doi.org/10.5194/nhess-24-121-2024, 2024
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Meteotsunami are the result of atmospheric disturbances and can impact coastlines causing injury, loss of life, and damage to assets. This paper introduces a novel intensity index to allow for the quantification of these events at the shoreline. This has the potential to assist in the field of natural hazard assessment. It was trialled in the UK but designed for global applicability and to become a widely accepted standard in coastal planning, meteotsunami forecasting, and early warning systems.
Brian Golding, Elizabeth Ebert, David Hoffmann, and Sally Potter
Adv. Sci. Res., 20, 85–90, https://doi.org/10.5194/asr-20-85-2023, https://doi.org/10.5194/asr-20-85-2023, 2023
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In 2021, several weather disasters occurred in which conditions surpassed recorded extremes. Comparative analysis of the warnings issued for these disasters shows that the conditions were generally forecast but that lack of preparedness and/or communication failures led to loss of life in particularly vulnerable groups.
Clare Lewis, Tim Smyth, David Williams, Jess Neumann, and Hannah Cloke
Nat. Hazards Earth Syst. Sci., 23, 2531–2546, https://doi.org/10.5194/nhess-23-2531-2023, https://doi.org/10.5194/nhess-23-2531-2023, 2023
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Meteotsunami are globally occurring water waves initiated by atmospheric disturbances. Previous research has suggested that in the UK, meteotsunami are a rare phenomenon and tend to occur in the summer months. This article presents a revised and updated catalogue of 98 meteotsunami that occurred between 1750 and 2022. Results also demonstrate a larger percentage of winter events and a geographical pattern highlighting the
hotspotregions that experience these events.
David Hoffmann, Elizabeth E. Ebert, Carla Mooney, Brian Golding, and Sally Potter
Adv. Sci. Res., 20, 73–79, https://doi.org/10.5194/asr-20-73-2023, https://doi.org/10.5194/asr-20-73-2023, 2023
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The weather information value chain is a framework that describes how information is produced, communicated, and used in an end-to-end warning system for weather and hazard monitoring. A project under the WMO aims to explore value chain approaches to describe and evaluate high-impact weather events. The project developed a template for high-impact weather event case study collection, which allows scientists and practitioners to assess the effectiveness of warning value chains.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Gwyneth Matthews, Christopher Barnard, Hannah Cloke, Sarah L. Dance, Toni Jurlina, Cinzia Mazzetti, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 2939–2968, https://doi.org/10.5194/hess-26-2939-2022, https://doi.org/10.5194/hess-26-2939-2022, 2022
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The European Flood Awareness System creates flood forecasts for up to 15 d in the future for the whole of Europe which are made available to local authorities. These forecasts can be erroneous because the weather forecasts include errors or because the hydrological model used does not represent the flow in the rivers correctly. We found that, by using recent observations and a model trained with past observations and forecasts, the real-time forecast can be corrected, thus becoming more useful.
Chloe Brimicombe, Claudia Di Napoli, Rosalind Cornforth, Florian Pappenberger, Celia Petty, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-242, https://doi.org/10.5194/nhess-2021-242, 2021
Revised manuscript not accepted
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Heatwaves are an increasing risk to African communities. This hazard can have a negative impact on peoples lives and in some cases results in their death. This study shows new information about heatwave characteristics through a list of heatwave events that have been reported for the African continent from 1980 until 2020. Case studies are useful helps to inform the development of early warning systems and forecasting, which is an urgent priority and needs significant improvement.
Jamie Towner, Andrea Ficchí, Hannah L. Cloke, Juan Bazo, Erin Coughlan de Perez, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci., 25, 3875–3895, https://doi.org/10.5194/hess-25-3875-2021, https://doi.org/10.5194/hess-25-3875-2021, 2021
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We examine whether several climate indices alter the magnitude, timing and duration of floods in the Amazon. We find significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative SST years in the central Pacific Ocean. This response is not repeated when the negative anomaly is positioned further east. These results have important implications for both social and physical sectors working towards the improvement of flood early warning systems.
Chiara Marsigli, Elizabeth Ebert, Raghavendra Ashrit, Barbara Casati, Jing Chen, Caio A. S. Coelho, Manfred Dorninger, Eric Gilleland, Thomas Haiden, Stephanie Landman, and Marion Mittermaier
Nat. Hazards Earth Syst. Sci., 21, 1297–1312, https://doi.org/10.5194/nhess-21-1297-2021, https://doi.org/10.5194/nhess-21-1297-2021, 2021
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This paper reviews new observations for the verification of high-impact weather and provides advice for their usage in objective verification. New observations include remote sensing datasets, products developed for nowcasting, datasets derived from telecommunication systems, data collected from citizens, reports of impacts and reports from insurance companies. This work has been performed in the framework of the Joint Working Group on Forecast Verification Research (JWGFVR) of the WMO.
Sazzad Hossain, Hannah L. Cloke, Andrea Ficchì, Andrew G. Turner, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-97, https://doi.org/10.5194/hess-2021-97, 2021
Manuscript not accepted for further review
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Hydrometeorological drivers are investigated to study three different flood types: long duration, rapid rise and high water level of the Brahmaputra river basin in Bangladesh. Our results reveal that long duration floods have been driven by basin-wide rainfall whereas rapid rate of rise due to more localized rainfall. We find that recent record high water levels are not coincident with extreme river flows. Understanding these drivers is key for flood forecasting and early warning.
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Short summary
This paper examines why multiple early indicators of the July 2021 floods in Luxembourg did not lead to better anticipatory action. Using a value chain approach and the Waterdrop Model, it identifies how thresholds, procedures, and institutional responsibilities limited the use of available forecast information under uncertainty. The findings show how aligning information with decision processes can improve timely disaster response.
This paper examines why multiple early indicators of the July 2021 floods in Luxembourg did not...
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