Articles | Volume 23, issue 8
https://doi.org/10.5194/nhess-23-2769-2023
© Author(s) 2023. 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-23-2769-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Aug 2023
Research article |
| 10 Aug 2023
| 10 Aug 2023
Assessing the spatial spread–skill of ensemble flood maps with remote-sensing observations
Department of Meteorology, University of Reading, Reading, UK
Sarah L. Dance
Department of Meteorology, University of Reading, Reading, UK
Department of Mathematics and Statistics, University of Reading, Reading, UK
National Centre for Earth Observation (NCEO), Reading, UK
David C. Mason
Department of Geography and Environmental Science, University of Reading, Reading, UK
John Bevington
Jeremy Benn Associates Limited (JBA Consulting), Skipton, UK
Kay Shelton
Jeremy Benn Associates Limited (JBA Consulting), Skipton, UK
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Helen Hooker, Sarah Dance, David Mason, John Bevington, and Kay Shelton
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-178, https://doi.org/10.5194/hess-2024-178, 2024
Preprint under review for HESS
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This study introduces a method that uses satellite data to enhance flood map selection for forecast-based financing applications. Tested on the 2022 Pakistan floods, it successfully triggered flood maps in four out of five regions, including those with urban areas. The approach ensures timely humanitarian aid by updating flood maps, even when initial triggers are missed, aiding in better disaster preparedness and risk management.
Helen Hooker, Sarah Dance, David Mason, John Bevington, and Kay Shelton
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-178, https://doi.org/10.5194/hess-2024-178, 2024
Preprint under review for HESS
Short summary
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This study introduces a method that uses satellite data to enhance flood map selection for forecast-based financing applications. Tested on the 2022 Pakistan floods, it successfully triggered flood maps in four out of five regions, including those with urban areas. The approach ensures timely humanitarian aid by updating flood maps, even when initial triggers are missed, aiding in better disaster preparedness and risk management.
Ben Maybee, Cathryn E. Birch, Steven J. Böing, Thomas Willis, Linda Speight, Aurore N. Porson, Charlie Pilling, Kay L. Shelton, and Mark A. Trigg
Nat. Hazards Earth Syst. Sci., 24, 1415–1436, https://doi.org/10.5194/nhess-24-1415-2024, https://doi.org/10.5194/nhess-24-1415-2024, 2024
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This paper presents the development and verification of FOREWARNS, a novel method for regional-scale forecasting of surface water flooding. We detail outcomes from a workshop held with UK forecast users, who indicated they valued the forecasts and would use them to complement national guidance. We use results of objective forecast tests against flood observations over northern England to show that this confidence is justified and that FOREWARNS meets the needs of UK flood responders.
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.
Remy Vandaele, Sarah L. Dance, and Varun Ojha
Hydrol. Earth Syst. Sci., 25, 4435–4453, https://doi.org/10.5194/hess-25-4435-2021, https://doi.org/10.5194/hess-25-4435-2021, 2021
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The acquisition of river-level data is a critical task for the understanding of flood events but is often complicated by the difficulty to install and maintain gauges able to provide such information. This study proposes applying deep learning techniques on river-camera images in order to automatically extract the corresponding water levels. This approach could allow for a new flexible way to observe flood events, especially at ungauged locations.
Elizabeth S. Cooper, Sarah L. Dance, Javier García-Pintado, Nancy K. Nichols, and Polly J. Smith
Hydrol. Earth Syst. Sci., 23, 2541–2559, https://doi.org/10.5194/hess-23-2541-2019, https://doi.org/10.5194/hess-23-2541-2019, 2019
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Flooding from rivers is a huge and costly problem worldwide. Computer simulations can help to warn people if and when they are likely to be affected by river floodwater, but such predictions are not always accurate or reliable. Information about flood extent from satellites can help to keep these forecasts on track. Here we investigate different ways of using information from satellite images and look at the effect on computer predictions. This will help to develop flood warning systems.
Joanne A. Waller, Javier García-Pintado, David C. Mason, Sarah L. Dance, and Nancy K. Nichols
Hydrol. Earth Syst. Sci., 22, 3983–3992, https://doi.org/10.5194/hess-22-3983-2018, https://doi.org/10.5194/hess-22-3983-2018, 2018
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Nat. Hazards Earth Syst. Sci., 24, 1929–1935, https://doi.org/10.5194/nhess-24-1929-2024, https://doi.org/10.5194/nhess-24-1929-2024, 2024
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Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
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Théo St. Pierre Ostrander, Thomé Kraus, Bruno Mazzorana, Johannes Holzner, Andrea Andreoli, Francesco Comiti, and Bernhard Gems
Nat. Hazards Earth Syst. Sci., 24, 1607–1634, https://doi.org/10.5194/nhess-24-1607-2024, https://doi.org/10.5194/nhess-24-1607-2024, 2024
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Mountain river confluences are hazardous during localized flooding events. A physical model was used to determine the dominant controls over mountain confluences. Contrary to lowland confluences, in mountain regions, the channel discharges and (to a lesser degree) the tributary sediment concentration control morphological patterns. Applying conclusions drawn from lowland confluences could misrepresent depositional and erosional patterns and the related flood hazard at mountain river confluences.
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-50, https://doi.org/10.5194/nhess-2024-50, 2024
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Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high resolution models resolving individual streets and buildings in, we produce detailed, quantitative and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.
Alison Kay, Nick Dunstone, Gillian Kay, Victoria Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-51, https://doi.org/10.5194/nhess-2024-51, 2024
Revised manuscript accepted for NHESS
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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 improve water supply resilience and flood risk management.
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci., 24, 1163–1183, https://doi.org/10.5194/nhess-24-1163-2024, https://doi.org/10.5194/nhess-24-1163-2024, 2024
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High-resolution convection-permitting climate models (CPMs) are now available to better simulate rainstorm events leading to flash floods. In this study, two hydrological models are compared to simulate floods in a Mediterranean basin, showing a better ability of the CPM to reproduce flood peaks compared to coarser-resolution climate models. Future projections are also different, with a projected increase for the most severe floods and a potential decrease for the most frequent events.
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.
Dino Collalti, Nekeisha Spencer, and Eric Strobl
Nat. Hazards Earth Syst. Sci., 24, 873–890, https://doi.org/10.5194/nhess-24-873-2024, https://doi.org/10.5194/nhess-24-873-2024, 2024
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The risk of extreme rainfall events causing floods is likely increasing with climate change. Flash floods, which follow immediately after extreme rainfall, are particularly difficult to forecast and assess. We develop a decision rule for flash flood classification with data on all incidents between 2001 and 2018 in Jamaica with the statistical copula method. This decision rule tells us for any rainfall event of a certain duration how intense it has to be to likely trigger a flash flood.
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian Grams
EGUsphere, https://doi.org/10.5194/egusphere-2024-415, https://doi.org/10.5194/egusphere-2024-415, 2024
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Extreme rainfall is the leading weather-related source of damages in Europe, but is still difficult to predict on long time scales. A recent example of this were the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allow us to better understand and predict such events.
Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg
Nat. Hazards Earth Syst. Sci., 24, 681–697, https://doi.org/10.5194/nhess-24-681-2024, https://doi.org/10.5194/nhess-24-681-2024, 2024
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This study presents a new version of a framework which allows us to model water balance components at any site on a local scale. Compared with the first version, the second incorporates new datasets used to set up and force the model. In particular, we highlight the ability of the framework to provide seasonal forecasts. This gives potential stakeholders (farmers, foresters, policymakers, etc.) the possibility to forecast, for example, soil moisture drought and thus apply the necessary measures.
Diego Fernández-Nóvoa, Alexandre M. Ramos, José González-Cao, Orlando García-Feal, Cristina Catita, Moncho Gómez-Gesteira, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci., 24, 609–630, https://doi.org/10.5194/nhess-24-609-2024, https://doi.org/10.5194/nhess-24-609-2024, 2024
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The present study focuses on an in-depth analysis of floods in the lower section of the Tagus River from a hydrodynamic perspective by means of the Iber+ numerical model and on the development of dam operating strategies to mitigate flood episodes using the exceptional floods of February 1979 as a benchmark. The results corroborate the model's capability to evaluate floods in the study area and confirm the effectiveness of the proposed strategies to reduce flood impact in the lower Tagus valley.
Francisco Javier Gomez, Keighobad Jafarzadegan, Hamed Moftakhari, and Hamid Moradkhani
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-26, https://doi.org/10.5194/nhess-2024-26, 2024
Revised manuscript accepted for NHESS
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This study utilizes the Global Copula Bayesian Model Averaging technique for accurate and reliable flood modeling, especially in coastal regions. By integrating multiple precipitation datasets within this framework, we can effectively address sources of error in each dataset, leading to the generation of probabilistic flood maps. The creation of these probabilistic maps is essential for disaster preparedness and mitigation in densely populated areas susceptible to extreme weather events.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
EGUsphere, https://doi.org/10.5194/egusphere-2024-421, https://doi.org/10.5194/egusphere-2024-421, 2024
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Drought is a creeping phenomenon, but it is often still analysed and managed like an event without taking into consideration what happened before and after. In this paper we review the literature and discuss five cases, where drought, its impacts and responses develop differently over time. We look at the hydrological, ecological and social system and their connections. And we provide suggestions for further research and for monitoring, modelling and management.
Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Pham Khanh Nam
Nat. Hazards Earth Syst. Sci., 24, 539–566, https://doi.org/10.5194/nhess-24-539-2024, https://doi.org/10.5194/nhess-24-539-2024, 2024
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We present a global flood model built using a new terrain data set and evaluated in the Central Highlands of Vietnam.
Andrea Abbate, Leonardo Mancusi, Francesco Apadula, Antonella Frigerio, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci., 24, 501–537, https://doi.org/10.5194/nhess-24-501-2024, https://doi.org/10.5194/nhess-24-501-2024, 2024
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CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment) is a new physically based and spatially distributed rainfall-runoff model. The main novelties consist of reproducing rainfall-induced geo-hydrological hazards such as shallow landslide, debris flow and watershed erosion through a multi-hazard approach. CRHyME was written in Python, works at a high spatial and temporal resolution, and is a tool suitable for quantifying extreme rainfall consequences at the basin scale.
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-22, https://doi.org/10.5194/nhess-2024-22, 2024
Revised manuscript accepted for NHESS
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The study proposes a new framework, named FLEXTH, to estimate flood water depths and improve satellite-based flood monitoring using topographical data. FLEXTH aims to reduce the impact of floods and is readily available as a computer code, offering a practical and scalable solution for estimating flood depths quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
Leanne Archer, Jeffrey Neal, Paul Bates, Emily Vosper, Dereka Carroll, Jeison Sosa, and Daniel Mitchell
Nat. Hazards Earth Syst. Sci., 24, 375–396, https://doi.org/10.5194/nhess-24-375-2024, https://doi.org/10.5194/nhess-24-375-2024, 2024
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We model hurricane-rainfall-driven flooding to assess how the number of people exposed to flooding changes in Puerto Rico under the 1.5 and 2 °C Paris Agreement goals. Our analysis suggests 8 %–10 % of the population is currently exposed to flooding on average every 5 years, increasing by 2 %–15 % and 1 %–20 % at 1.5 and 2 °C. This has implications for adaptation to more extreme flooding in Puerto Rico and demonstrates that 1.5 °C climate change carries a significant increase in risk.
Luis Cea, Manuel Álvarez, and Jerónimo Puertas
Nat. Hazards Earth Syst. Sci., 24, 225–243, https://doi.org/10.5194/nhess-24-225-2024, https://doi.org/10.5194/nhess-24-225-2024, 2024
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Mozambique is highly exposed to the impact of floods. To reduce flood damage, it is necessary to develop mitigation measures. Hydrological software is a very useful tool for that purpose, since it allows for a precise quantification of flood hazard in different scenarios. We present a methodology to quantify flood hazard in data-scarce regions, using freely available data and software, and we show its potential by analysing the flood event that took place in the Umbeluzi Basin in February 2023.
Lorenzo Alfieri, Andrea Libertino, Lorenzo Campo, Francesco Dottori, Simone Gabellani, Tatiana Ghizzoni, Alessandro Masoero, Lauro Rossi, Roberto Rudari, Nicola Testa, Eva Trasforini, Ahmed Amdihun, Jully Ouma, Luca Rossi, Yves Tramblay, Huan Wu, and Marco Massabò
Nat. Hazards Earth Syst. Sci., 24, 199–224, https://doi.org/10.5194/nhess-24-199-2024, https://doi.org/10.5194/nhess-24-199-2024, 2024
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This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the Greater Horn of Africa. It is based on hydrological simulations, inundation mapping, and estimation of population and assets exposed to upcoming river floods. The system supports duty officers in African institutions in the daily monitoring of hydro-meteorological disasters. A first evaluation shows the system performance for the catastrophic floods in the Nile River basin in summer 2020.
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Boutzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
EGUsphere, https://doi.org/10.5194/egusphere-2023-2862, https://doi.org/10.5194/egusphere-2023-2862, 2024
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Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.
Manuel Grenier, Mathieu Boudreault, David A. Carozza, Jérémie Boudreault, and Sébastien Raymond
EGUsphere, https://doi.org/10.22541/essoar.167751627.70583046/v2, https://doi.org/10.22541/essoar.167751627.70583046/v2, 2024
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Modelling floods at the street-level for large countries like Canada and the United States is difficult and very costly. However, many applications do not necessarily require that level of details. As a result, we present a flood modelling framework built with artificial intelligence for socioeconomic studies like trend and scenarios analyses. We find for example that an increase of 10 % in average precipitation yields an increase of population displaced of 18 % in Canada and 14 % in the U.S.
María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-206, https://doi.org/10.5194/nhess-2023-206, 2024
Revised manuscript accepted for NHESS
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Climate change is leading in the Pyrenees Massif to a change in socioeconomic increasing their sensitivity to natural risks such as floods. However, until now, no systematic study like this one had been carried out that would allow evaluating the frequency, distribution and main meteorological features of these events on a massif scale. In 35 years there have been 181 flood events that have produced 154 fatalities.
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
Ana Paez-Trujilo, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, and Dimitri Solomatine
Nat. Hazards Earth Syst. Sci., 23, 3863–3883, https://doi.org/10.5194/nhess-23-3863-2023, https://doi.org/10.5194/nhess-23-3863-2023, 2023
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This study uses a machine learning technique, the multivariate regression tree approach, to assess the hydroclimatic characteristics that govern agricultural and hydrological drought severity. The results show that the employed technique successfully identified the primary drivers of droughts and their critical thresholds. In addition, it provides relevant information to identify the areas most vulnerable to droughts and design strategies and interventions for drought management.
Bouchra Zellou, Nabil El Moçayd, and El Houcine Bergou
Nat. Hazards Earth Syst. Sci., 23, 3543–3583, https://doi.org/10.5194/nhess-23-3543-2023, https://doi.org/10.5194/nhess-23-3543-2023, 2023
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In this study, we underscore the critical importance of strengthening drought prediction capabilities in the Mediterranean region. We present an in-depth evaluation of current drought forecasting approaches, encompassing statistical, dynamical, and hybrid statistical–dynamical models, and highlight unexplored research opportunities. Additionally, we suggest viable directions to enhance drought prediction and early warning systems within the area.
Francisco Rodrigues do Amaral, Nicolas Gratiot, Thierry Pellarin, and Tran Anh Tu
Nat. Hazards Earth Syst. Sci., 23, 3379–3405, https://doi.org/10.5194/nhess-23-3379-2023, https://doi.org/10.5194/nhess-23-3379-2023, 2023
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We propose an in-depth analysis of typhoon-induced compound flood drivers in the megacity of Ho Chi Minh, Vietnam. We use in situ and satellite measurements throughout the event to form a holistic overview of its impact. No evidence of storm surge was found, and peak precipitation presents a 16 h time lag to peak river discharge, which evacuates only 1.5 % of available water. The astronomical tide controls the river level even during the extreme event, and it is the main urban flood driver.
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
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This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
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In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Clément Houdard, Adrien Poupardin, Philippe Sergent, Abdelkrim Bennabi, and Jena Jeong
Nat. Hazards Earth Syst. Sci., 23, 3111–3124, https://doi.org/10.5194/nhess-23-3111-2023, https://doi.org/10.5194/nhess-23-3111-2023, 2023
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We developed a system able to to predict, knowing the appropriate characteristics of the flood defense structure and sea state, the return periods of potentially dangerous events as well as a ranking of parameters by order of uncertainty.
The model is a combination of statistical and empirical methods that have been applied to a Mediterranean earthen dike. This shows that the most important characteristics of the dyke are its geometrical features, such as its height and slope angles.
Lisa Köhler, Torsten Masson, Sabrina Köhler, and Christian Kuhlicke
Nat. Hazards Earth Syst. Sci., 23, 2787–2806, https://doi.org/10.5194/nhess-23-2787-2023, https://doi.org/10.5194/nhess-23-2787-2023, 2023
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We analyzed the impact of flood experience on adaptive behavior and self-reported resilience. The outcomes draw a paradoxical picture: the most experienced people are the most adapted but the least resilient. We find evidence for non-linear relationships between the number of floods experienced and resilience. We contribute to existing knowledge by focusing specifically on the number of floods experienced and extending the rare scientific literature on the influence of experience on resilience.
Betina I. Guido, Ioana Popescu, Vidya Samadi, and Biswa Bhattacharya
Nat. Hazards Earth Syst. Sci., 23, 2663–2681, https://doi.org/10.5194/nhess-23-2663-2023, https://doi.org/10.5194/nhess-23-2663-2023, 2023
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We used an integrated model to evaluate the impacts of nature-based solutions (NBSs) on flood mitigation across the Little Pee Dee and Lumber River watershed, the Carolinas, US. This area is strongly affected by climatic disasters, which are expected to increase due to climate change and urbanization, so exploring an NBS approach is crucial for adapting to future alterations. Our research found that NBSs can have visible effects on the reduction in hurricane-driven flooding.
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.
Leon Scheiber, Mazen Hoballah Jalloul, Christian Jordan, Jan Visscher, Hong Quan Nguyen, and Torsten Schlurmann
Nat. Hazards Earth Syst. Sci., 23, 2313–2332, https://doi.org/10.5194/nhess-23-2313-2023, https://doi.org/10.5194/nhess-23-2313-2023, 2023
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Numerical models are increasingly important for assessing urban flooding, yet reliable input data are oftentimes hard to obtain. Taking Ho Chi Minh City as an example, this paper explores the usability and reliability of open-access data to produce preliminary risk maps that provide first insights into potential flooding hotspots. As a key novelty, a normalized flood severity index is presented which combines flood depth and duration to enhance the interpretation of hydro-numerical results.
Claudia Herbert and Petra Döll
Nat. Hazards Earth Syst. Sci., 23, 2111–2131, https://doi.org/10.5194/nhess-23-2111-2023, https://doi.org/10.5194/nhess-23-2111-2023, 2023
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This paper presents a new method for selecting streamflow drought hazard indicators for monitoring drought hazard for human water supply and river ecosystems in large-scale drought early warning systems. Indicators are classified by their inherent assumptions about the habituation of people and ecosystems to the streamflow regime and their level of drought characterization, namely drought magnitude (water deficit at a certain point in time) and severity (cumulated magnitude since drought onset).
Maryse Charpentier-Noyer, Daniela Peredo, Axelle Fleury, Hugo Marchal, François Bouttier, Eric Gaume, Pierre Nicolle, Olivier Payrastre, and Maria-Helena Ramos
Nat. Hazards Earth Syst. Sci., 23, 2001–2029, https://doi.org/10.5194/nhess-23-2001-2023, https://doi.org/10.5194/nhess-23-2001-2023, 2023
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This paper proposes a methodological framework designed for event-based evaluation in the context of an intense flash-flood event. The evaluation adopts the point of view of end users, with a focus on the anticipation of exceedances of discharge thresholds. With a study of rainfall forecasts, a discharge evaluation and a detailed look at the forecast hydrographs, the evaluation framework should help in drawing robust conclusions about the usefulness of new rainfall ensemble forecasts.
Min Li, Mingfeng Zhang, Runxiang Cao, Yidi Sun, and Xiyuan Deng
Nat. Hazards Earth Syst. Sci., 23, 1453–1464, https://doi.org/10.5194/nhess-23-1453-2023, https://doi.org/10.5194/nhess-23-1453-2023, 2023
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It is an important disaster reduction strategy to forecast hydrological drought. In order to analyse the impact of human activities on hydrological drought, we constructed the human activity factor based on the method of restoration. With the increase of human index (HI) value, hydrological droughts tend to transition to more severe droughts. The conditional distribution model involving of human activity factor can further improve the forecasting accuracy of drought in the Luanhe River basin.
Patrick Ludwig, Florian Ehmele, Mário J. Franca, Susanna Mohr, Alberto Caldas-Alvarez, James E. Daniell, Uwe Ehret, Hendrik Feldmann, Marie Hundhausen, Peter Knippertz, Katharina Küpfer, Michael Kunz, Bernhard Mühr, Joaquim G. Pinto, Julian Quinting, Andreas M. Schäfer, Frank Seidel, and Christina Wisotzky
Nat. Hazards Earth Syst. Sci., 23, 1287–1311, https://doi.org/10.5194/nhess-23-1287-2023, https://doi.org/10.5194/nhess-23-1287-2023, 2023
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Heavy precipitation in July 2021 led to widespread floods in western Germany and neighboring countries. The event was among the five heaviest precipitation events of the past 70 years in Germany, and the river discharges exceeded by far the statistical 100-year return values. Simulations of the event under future climate conditions revealed a strong and non-linear effect on flood peaks: for +2 K global warming, an 18 % increase in rainfall led to a 39 % increase of the flood peak in the Ahr river.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
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Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Katharina Lengfeld, Paul Voit, Frank Kaspar, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 1227–1232, https://doi.org/10.5194/nhess-23-1227-2023, https://doi.org/10.5194/nhess-23-1227-2023, 2023
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Estimating the severity of a rainfall event based on the damage caused is easy but highly depends on the affected region. A less biased measure for the extremeness of an event is its rarity combined with its spatial extent. In this brief communication, we investigate the sensitivity of such measures to the underlying dataset and highlight the importance of considering multiple spatial and temporal scales using the devastating rainfall event in July 2021 in central Europe as an example.
Paul D. Bates, James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith
Nat. Hazards Earth Syst. Sci., 23, 891–908, https://doi.org/10.5194/nhess-23-891-2023, https://doi.org/10.5194/nhess-23-891-2023, 2023
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We present and validate a model that simulates current and future flood risk for the UK at high resolution (~ 20–25 m). We show that UK flood losses were ~ 6 % greater in the climate of 2020 compared to recent historical values. The UK can keep any future increase to ~ 8 % if all countries implement their COP26 pledges and net-zero ambitions in full. However, if only the COP26 pledges are fulfilled, then UK flood losses increase by ~ 23 %; and potentially by ~ 37 % in a worst-case scenario.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
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In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Omar Seleem, Georgy Ayzel, Axel Bronstert, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 809–822, https://doi.org/10.5194/nhess-23-809-2023, https://doi.org/10.5194/nhess-23-809-2023, 2023
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Data-driven models are becoming more of a surrogate that overcomes the limitations of the computationally expensive 2D hydrodynamic models to map urban flood hazards. However, the model's ability to generalize outside the training domain is still a major challenge. We evaluate the performance of random forest and convolutional neural networks to predict urban floodwater depth and investigate their transferability outside the training domain.
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Short summary
Ensemble forecasts of flood inundation produce maps indicating the probability of flooding. A new approach is presented to evaluate the spatial performance of an ensemble flood map forecast by comparison against remotely observed flooding extents. This is important for understanding forecast uncertainties and improving flood forecasting systems.
Ensemble forecasts of flood inundation produce maps indicating the probability of flooding. A...
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