Articles | Volume 20, issue 8
https://doi.org/10.5194/nhess-20-2091-2020
© Author(s) 2020. 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-20-2091-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Aug 2020
Research article |
| 06 Aug 2020
| 06 Aug 2020
Evaluating the efficacy of bivariate extreme modelling approaches for multi-hazard scenarios
Department of Geography, King's College London, London, WC2B 4BG,
United Kingdom
Bruce D. Malamud
Department of Geography, King's College London, London, WC2B 4BG,
United Kingdom
Hugo Winter
EDF Energy R&D UK Centre, Croydon, CR0 2AJ, United Kingdom
Amélie Joly-Laugel
EDF Energy R&D UK Centre, Croydon, CR0 2AJ, United Kingdom
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This is the first study that uses spatial patterns (clusters/hotspots) and meta-analysis in order to identify the regions at a European level at risk of multi-hazards. The findings point out the socioeconomic dimension as a determining factor in the potential risk of multi-hazards. The outcome provides valuable input for the disaster risk management policy support and will assist national authorities on the implementation of a multi-hazard approach in national risk assessment preparation.
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This article presents a reanalysis of Europe's rivers streamflow for the period 1950–2020, using a state-of-the-art hydrological simulation framework. The dataset, called HERA (Hydrological European ReAnalysis), uses detailed information about the landscape, climate, and human activities to estimate river flow. HERA can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources, flood and drought risks.
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Compound hazards occur when two different natural hazards impact the same time period and spatial area. This article presents a methodology for the spatiotemporal identification of compound hazards (SI–CH). The methodology is applied to compound precipitation and wind extremes in Great Britain for the period 1979–2019. The study finds that the SI–CH approach can accurately identify single and compound hazard events and represent their spatial and temporal properties.
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We describe a methodology to systematically gather evidence of the breadth of single natural hazards and their multi-hazard interrelationships in data-scarce urban settings. We apply this methodology to Kathmandu Valley, Nepal, where we find evidence of 21 single hazard types, and 83 multi-hazard interrelationships. This evidence is supplemented with multi-hazard scenarios developed by practitioner stakeholders engaged in disaster risk reduction research and practice in Kathmandu Valley.
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This article presents a reanalysis of Europe's rivers streamflow for the period 1950–2020, using a state-of-the-art hydrological simulation framework. The dataset, called HERA (Hydrological European ReAnalysis), uses detailed information about the landscape, climate, and human activities to estimate river flow. HERA can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources, flood and drought risks.
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Flash floods belong to natural hazards that can be enhanced in frequency, intensity, and impact during recent climate change. This paper presents a complex analysis of spatiotemporal variability and human impacts (including material damage and fatalities) of flash floods in the Czech Republic for the 2001–2023 period. The analysis generally shows no statistically significant trends in the characteristics analyzed.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
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We look at how compound flooding from the combination of river flooding and storm tides (storm surge and astronomical tide) may be changing over time due to climate change, with a case study of the Mekong River delta. We found that future compound flooding has the potential to flood the region more extensively and be longer lasting than compound floods today. This is useful to know because it means managers of deltas such as the Mekong can assess options for improving existing flood defences.
Maryam Pakdehi, Ebrahim Ahmadisharaf, Behzad Nazari, and Eunsaem Cho
Nat. Hazards Earth Syst. Sci., 24, 3537–3559, https://doi.org/10.5194/nhess-24-3537-2024, https://doi.org/10.5194/nhess-24-3537-2024, 2024
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Machine learning (ML) algorithms have increasingly received attention for modeling flood events. However, there are concerns about the transferability of these models (their capability in predicting out-of-sample and unseen events). Here, we show that ML models can be transferable for hindcasting maximum river flood depths across extreme events (four hurricanes) in a large coastal watershed (HUC6) when informed by the spatial distribution of pertinent features and underlying physical processes.
María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci., 24, 3423–3443, https://doi.org/10.5194/nhess-24-3423-2024, https://doi.org/10.5194/nhess-24-3423-2024, 2024
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This paper shows the first public and systematic dataset of flood episodes referring to the entire Pyrenees massif, at municipal scale, named PIRAGUA_flood. Of the 181 flood events (1981–2015) that produced 154 fatalities, 36 were transnational, with the eastern part of the massif most affected. Dominant weather types show a southern component flow, with a talweg on the Iberian Peninsula and a depression in the vicinity. A positive and significant trend was found in Nouvelle-Aquitaine.
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
Nat. Hazards Earth Syst. Sci., 24, 3315–3335, https://doi.org/10.5194/nhess-24-3315-2024, https://doi.org/10.5194/nhess-24-3315-2024, 2024
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We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern United States, in climate data. Analyzing the Susquehanna River basin, this technique identified known events affecting river flow. Comparing four gridded datasets revealed variations in event frequency and severity, driven by different snowmelt and runoff estimates. This highlights the need for accurate climate data in flood management and risk prediction for these compound extremes.
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
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
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Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Sheik Umar Jam-Jalloh, Jia Liu, Yicheng Wang, and Yuchen Liu
Nat. Hazards Earth Syst. Sci., 24, 3155–3172, https://doi.org/10.5194/nhess-24-3155-2024, https://doi.org/10.5194/nhess-24-3155-2024, 2024
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Our paper explores improving flood forecasting using advanced weather and hydrological models. By coupling the WRF model with WRF-Hydro and HEC-HMS, we achieved more accurate forecasts. WRF–WRF-Hydro excels for short, intense storms, while WRF–HEC-HMS is better for longer, evenly distributed storms. Our research shows how these models provide insights for adaptive atmospheric–hydrologic systems and aims to boost flood preparedness and response with more reliable, timely predictions.
Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
EGUsphere, https://doi.org/10.5194/egusphere-2024-2621, https://doi.org/10.5194/egusphere-2024-2621, 2024
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Deep learning methods are increasingly used as surrogates for spatio-temporal flood models but struggle with generalization and speed. Here, we propose a multi-resolution approach using graph neural networks that predicts dike breach floods across different meshes, topographies, and boundary conditions with high accuracy and up to 1000x speedups. The model also generalizes to larger, more complex case studies with just one additional simulation for fine-tuning.
Shahin Khosh Bin Ghomash, Patricio Yeste, Heiko Apel, and Viet Dung Nguyen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-77, https://doi.org/10.5194/nhess-2024-77, 2024
Revised manuscript accepted for NHESS
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Hydrodynamic models are vital for predicting floods, like those in Germany's Ahr region in July 2021. We refine an RIM2D model for the Ahr region, analyzing the impact of various factors using Monte Carlo simulations. Accurate parameter assignment is crucial, with channel roughness and resolution playing key roles. Coarser resolutions are suitable for flood extent predictions, aiding early warning systems. Our work provides guidelines for optimizing hydrodynamic models in the Ahr region.
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024, https://doi.org/10.5194/nhess-24-2995-2024, 2024
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Extreme rainfall is the leading weather-related source of damages in Europe, but it is still difficult to predict on long timescales. A recent example of this was the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allows us to better understand and predict such events.
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.
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024, https://doi.org/10.5194/nhess-24-2923-2024, 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.
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024, https://doi.org/10.5194/nhess-24-2857-2024, 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, 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.
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024, https://doi.org/10.5194/nhess-24-2817-2024, 2024
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The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
Francisco Javier Gomez, Keighobad Jafarzadegan, Hamed Moftakhari, and Hamid Moradkhani
Nat. Hazards Earth Syst. Sci., 24, 2647–2665, https://doi.org/10.5194/nhess-24-2647-2024, https://doi.org/10.5194/nhess-24-2647-2024, 2024
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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.
Manuel Grenier, Mathieu Boudreault, David A. Carozza, Jérémie Boudreault, and Sébastien Raymond
Nat. Hazards Earth Syst. Sci., 24, 2577–2595, https://doi.org/10.5194/nhess-24-2577-2024, https://doi.org/10.5194/nhess-24-2577-2024, 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 detail. 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 in displaced population of 18 % in Canada and 14 % in the US.
Helge Bormann, Jenny Kebschull, Lidia Gaslikova, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 2559–2576, https://doi.org/10.5194/nhess-24-2559-2024, https://doi.org/10.5194/nhess-24-2559-2024, 2024
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Inland flooding is threatening coastal lowlands. If rainfall and storm surges coincide, the risk of inland flooding increases. We examine how such compound events are influenced by climate change. Data analysis and model-based scenario analysis show that climate change induces an increasing frequency and intensity of compounding precipitation and storm tide events along the North Sea coast. Overload of inland drainage systems will also increase if no timely adaptation measures are taken.
Belinda Rhein and Heidi Kreibich
EGUsphere, https://doi.org/10.5194/egusphere-2024-2066, https://doi.org/10.5194/egusphere-2024-2066, 2024
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The 2021 flood killed 190 people in Germany, 134 of them in the Ahr valley, making it the deadliest flood in recent German history. The flash flood was extreme in terms of water levels, flow velocities and flood extent, early warning and evacuation were inadequate. Many died on the ground floor or in the street, with older and impaired individuals especially vulnerable. Clear warnings should urge people to seek safety rather than save belongings, and timely evacuations are essential.
Nazir Ahmed Bazai, Mehtab Alam, Peng Cui, Wang Hao, Adil Poshad Khan, Muhammad Waseem, Yao Shunyu, Muhammad Ramzan, Li Wanhong, and Tashfain Ahmed
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-95, https://doi.org/10.5194/nhess-2024-95, 2024
Revised manuscript accepted for NHESS
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This study examines the 2022 monsoon in the Swat River basin, Pakistan, where record rainfall exceeded averages by 7–8 %, causing catastrophic debris flows and floods. These events worsened challenges for low-income communities, resulting in extensive damage and financial instability. Field investigations, remote sensing, and simulations identified deforestation and steep topography as key factors. The study advocates for disaster mitigation, reforestation, and better land use planning.
Yanxia Shen, Zhenduo Zhu, Qi Zhou, and Chunbo Jiang
Nat. Hazards Earth Syst. Sci., 24, 2315–2330, https://doi.org/10.5194/nhess-24-2315-2024, https://doi.org/10.5194/nhess-24-2315-2024, 2024
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We present an improved Multigrid Dynamical Bidirectional Coupled hydrologic–hydrodynamic Model (IM-DBCM) with two major improvements: (1) automated non-uniform mesh generation based on the D-infinity algorithm was implemented to identify flood-prone areas where high-resolution inundation conditions are needed, and (2) ghost cells and bilinear interpolation were implemented to improve numerical accuracy in interpolating variables between the coarse and fine grids. The improved model was reliable.
Taylor Glen Johnson, Jorge Leandro, and Divine Kwaku Ahadzie
Nat. Hazards Earth Syst. Sci., 24, 2285–2302, https://doi.org/10.5194/nhess-24-2285-2024, https://doi.org/10.5194/nhess-24-2285-2024, 2024
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Reliance on infrastructure creates vulnerabilities to disruptions caused by natural hazards. To assess the impacts of natural hazards on the performance of infrastructure, we present a framework for quantifying resilience and develop a model of recovery based upon an application of project scheduling under resource constraints. The resilience framework and recovery model were applied in a case study to assess the resilience of building infrastructure to flooding hazards in Accra, Ghana.
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci., 24, 2215–2242, https://doi.org/10.5194/nhess-24-2215-2024, https://doi.org/10.5194/nhess-24-2215-2024, 2024
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On 22 October 2019, the Francolí River basin experienced a heavy precipitation event, resulting in a catastrophic flash flood. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 2147–2164, https://doi.org/10.5194/nhess-24-2147-2024, https://doi.org/10.5194/nhess-24-2147-2024, 2024
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To identify flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent runoff reaction. Our results show that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks of a factor of 2 or more would be achieved for most areas. The results can aid disaster risk management.
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024, https://doi.org/10.5194/nhess-24-2071-2024, 2024
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A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
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The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Melody Gwyneth Whitehead and Mark Stephen Bebbington
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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Precipitation-driven hazards including floods, landslides, and lahars can be catastrophic and difficult to forecast due to high uncertainty around future weather patterns. This work presents a stochastic weather model that produces statistically similar (realistic) rainfall over long time periods at minimal computational cost. These data provide much-needed inputs for hazard simulations to support long-term, time and spatially varying risk assessments.
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777, https://doi.org/10.5194/nhess-24-1757-2024, https://doi.org/10.5194/nhess-24-1757-2024, 2024
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We delved into the socio-economic impacts of the 2018–2022 drought in Germany. We derived a dataset covering the impacts of droughts in Germany between 2000 and 2022 on sectors such as agriculture and forestry based on newspaper articles. Notably, our study illustrated that the longer drought had a wider reach and more varied effects. We show that dealing with longer droughts requires different plans compared to shorter ones, and it is crucial to be ready for the challenges they bring.
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696, https://doi.org/10.5194/nhess-24-1681-2024, https://doi.org/10.5194/nhess-24-1681-2024, 2024
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INSYDE 2.0 is a tool for modelling flood damage to residential buildings. By incorporating ultra-detailed survey and desk-based data, it improves the reliability and informativeness of damage assessments while addressing input data uncertainties.
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.
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.
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.
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.
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.
Laurent Pascal Malang Diémé, Christophe Bouvier, Ansoumana Bodian, and Alpha Sidibé
EGUsphere, https://doi.org/10.5194/egusphere-2023-2458, https://doi.org/10.5194/egusphere-2023-2458, 2024
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We propose a decision support tool that detect the occurrence of flooding by drainage overflow, with sufficiently short calculation times. The simulations are based on a drainage topology on 5m grids, incorporating changes to surface flows induced urbanization. The method can be used for flood mapping in project mode and in real time. It applies to the present situation as well as to any scenario involving climate change or urban growth.
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Short summary
Estimating risks induced by interacting natural hazards remains a challenge for practitioners. An approach to tackle this challenge is to use multivariate statistical models. Here we evaluate the efficacy of six models. The models are compared against synthetic data which are comparable to time series of environmental variables. We find which models are more appropriate to estimate relations between hazards in a range of cases. We highlight the benefits of this approach with two examples.
Estimating risks induced by interacting natural hazards remains a challenge for practitioners....
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