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
Related authors
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
Short summary
Short summary
This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
Short summary
Short summary
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.
Aloïs Tilloy, Bruce D. Malamud, and Amélie Joly-Laugel
Earth Syst. Dynam., 13, 993–1020, https://doi.org/10.5194/esd-13-993-2022, https://doi.org/10.5194/esd-13-993-2022, 2022
Short summary
Short summary
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.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
Short summary
Short summary
This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Harriet E. Thompson, Joel C. Gill, Robert Šakić Trogrlić, Faith E. Taylor, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 25, 353–381, https://doi.org/10.5194/nhess-25-353-2025, https://doi.org/10.5194/nhess-25-353-2025, 2025
Short summary
Short summary
We present a methodology to compile single hazards and multi-hazard interrelationships in data-scarce urban settings, which we apply to the Kathmandu Valley, Nepal. Using blended sources, we collate evidence of 21 single natural hazard types and 83 multi-hazard interrelationships that could impact the Kathmandu Valley. We supplement these exemplars with multi-hazard scenarios developed by practitioner stakeholders, emphasising the need for inclusive disaster preparedness and response approaches.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
Short summary
Short summary
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.
Uldis Zandovskis, Davide Pigoli, and Bruce D. Malamud
EGUsphere, https://doi.org/10.5194/egusphere-2024-2733, https://doi.org/10.5194/egusphere-2024-2733, 2024
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
This study looks at how lightning strikes happen over time and space, focusing on six storms in the UK during 2012 and 2015. By using real data, the research examines how often lightning strikes occur, how fast the storms move, and how far the strikes spread. The storms had different speeds (47–111 km/h) and times between strikes (0.01 to 100 seconds), with strikes spreading up to 80 km. The study’s findings help create models to better characterise severe storms.
Lakshmi S. Gopal, Rekha Prabha, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud
EGUsphere, https://doi.org/10.5194/egusphere-2024-1536, https://doi.org/10.5194/egusphere-2024-1536, 2024
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
We critically reviewed 250 articles from 2010 to 2023, analysed how social media is used to manage disasters, and developed the Social Media Literature Database. We summarise the methods used for data collection and filtering. Key findings include the widespread use of the latest technologies to handle data, proficiency in spatiotemporal analysis, and gaps in community interaction and resource identification. We also propose best practices for using social media to enhance disaster management.
Robert Šakić Trogrlić, Amy Donovan, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 22, 2771–2790, https://doi.org/10.5194/nhess-22-2771-2022, https://doi.org/10.5194/nhess-22-2771-2022, 2022
Short summary
Short summary
Here we present survey responses of 350 natural hazard community members to key challenges in natural hazards research and step changes to achieve the Sustainable Development Goals. Challenges identified range from technical (e.g. model development, early warning) to governance (e.g. co-production with community members). Step changes needed are equally broad; however, the majority of answers showed a need for wider stakeholder engagement, increased risk management and interdisciplinary work.
Aloïs Tilloy, Bruce D. Malamud, and Amélie Joly-Laugel
Earth Syst. Dynam., 13, 993–1020, https://doi.org/10.5194/esd-13-993-2022, https://doi.org/10.5194/esd-13-993-2022, 2022
Short summary
Short summary
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.
Faith E. Taylor, Paolo Tarolli, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 20, 2585–2590, https://doi.org/10.5194/nhess-20-2585-2020, https://doi.org/10.5194/nhess-20-2585-2020, 2020
Joel C. Gill, Bruce D. Malamud, Edy Manolo Barillas, and Alex Guerra Noriega
Nat. Hazards Earth Syst. Sci., 20, 149–180, https://doi.org/10.5194/nhess-20-149-2020, https://doi.org/10.5194/nhess-20-149-2020, 2020
Short summary
Short summary
This paper describes a replicable approach for characterising interactions between natural hazards. Guatemala is exposed to multiple natural hazards, which do not always occur independently. There can be interactions between natural hazards. For example, one hazard may trigger multiple secondary hazards, which can subsequently trigger further hazards. Here we use diverse evidence of such interactions to construct matrices of hazard interactions in Guatemala at national and sub-national scales.
Alistair Hendry, Ivan D. Haigh, Robert J. Nicholls, Hugo Winter, Robert Neal, Thomas Wahl, Amélie Joly-Laugel, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 23, 3117–3139, https://doi.org/10.5194/hess-23-3117-2019, https://doi.org/10.5194/hess-23-3117-2019, 2019
Short summary
Short summary
Flooding can arise from multiple sources, including waves, extreme sea levels, rivers, and severe rainfall. When two or more sources combine, the consequences can be greatly multiplied. We find the potential for the joint occurrence of extreme sea levels and river discharge to be greater on the western coast of the UK compared to the eastern coast. This is due to the weather conditions generating each flood source around the UK. These results will help increase our flood forecasting ability.
David Cross, Christian Onof, Hugo Winter, and Pietro Bernardara
Hydrol. Earth Syst. Sci., 22, 727–756, https://doi.org/10.5194/hess-22-727-2018, https://doi.org/10.5194/hess-22-727-2018, 2018
Short summary
Short summary
Extreme rainfall is one of the most significant natural hazards. However, estimating very large events is highly uncertain. We present a new approach to construct intense rainfall using the structure of rainfall generation in clouds. The method is particularly effective at estimating short-duration extremes, which can be the most damaging. This is expected to have immediate impact for the estimation of very rare downpours, with the potential to improve climate resilience and hazard preparedness.
Annette Witt, Bruce D. Malamud, Clara Mangili, and Achim Brauer
Hydrol. Earth Syst. Sci., 21, 5547–5581, https://doi.org/10.5194/hess-21-5547-2017, https://doi.org/10.5194/hess-21-5547-2017, 2017
Short summary
Short summary
Here we present a unique 9.5 m palaeo-lacustrine record of 771 palaeofloods which occurred over a period of 10 000 years in the Piànico–Sèllere basin (southern Alps) during an interglacial period in the Pleistocene (sometime between 400 000 and 800 000 years ago). We analyse the palaeoflood series correlation, clustering, and cyclicity properties, finding a long-range cyclicity with a period of about 2030 years superimposed onto a fractional noise.
Bruce D. Malamud, Donald L. Turcotte, and Harold E. Brooks
Nat. Hazards Earth Syst. Sci., 16, 2823–2834, https://doi.org/10.5194/nhess-16-2823-2016, https://doi.org/10.5194/nhess-16-2823-2016, 2016
Short summary
Short summary
We introduce a novel method for the spatial–temporal cluster analysis of severe tornado touchdowns that are part of tornado outbreaks. Tornado outbreaks, groups of tornadoes occurring close to each other in time and space, constitute a severe hazard that has few quantitative measures. Our new approach, which we illustrate using three USA severe tornado outbreaks and models, differentiates between types of tornado outbreaks and, within outbreaks, identifies clusters in both time and space.
Joel C. Gill and Bruce D. Malamud
Earth Syst. Dynam., 7, 659–679, https://doi.org/10.5194/esd-7-659-2016, https://doi.org/10.5194/esd-7-659-2016, 2016
Short summary
Short summary
Understanding interactions between hazards and other processes can help us to better understand the complex environment in which disasters occur. This enhanced understanding may help us to better manage hazards and reduce the risk of disasters occurring. Interactions (e.g. one hazard triggering another hazard) are noted between (i) natural hazards, such as earthquakes; (ii) human activity, such as groundwater abstraction; and (iii) technological hazards/disasters, such as building collapse.
Related subject area
Hydrological Hazards
Large-scale flood risk assessment in data-scarce areas: an application to Central Asia
Multi-scale hydraulic graph neural networks for flood modelling
The role of antecedent conditions in translating precipitation events into extreme floods at the catchment scale and in a large-basin context
Brief communication: Stay local or go global? On the construction of plausible counterfactual scenarios to assess flash flood hazards
Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
Tangible and intangible ex post assessment of flood-induced damage to cultural heritage
A multivariate statistical framework for mixed storm types in compound flood analysis
Invited perspectives: safeguarding the usability and credibility of flood hazard and risk assessments
Influence of building collapse on pluvial and fluvial flood inundation of metro stations in central Shanghai
Impact of drought hazards on flow regimes in anthropogenically impacted streams: an isotopic perspective on climate stress
The effect of wildfires on flood risk: a multi-hazard flood risk approach for the Ebro River basin, Spain
Modelling hazards impacting the flow regime in the Hranice Karst due to the proposed Skalička Dam
Spatiotemporal variability of flash floods and their human impacts in the Czech Republic during the 2001–2023 period
Risk of compound flooding substantially increases in the future Mekong River delta
Transferability of machine-learning-based modeling frameworks across flood events for hindcasting maximum river water depths in coastal watersheds
Floods in the Pyrenees: a global view through a regional database
Algorithmically detected rain-on-snow flood events in different climate datasets: a case study of the Susquehanna River basin
Review article: Drought as a continuum – memory effects in interlinked hydrological, ecological, and social systems
Coupling WRF with HEC-HMS and WRF-Hydro for flood forecasting in typical mountainous catchments of northern China
Monte-Carlo based sensitivity analysis of the RIM2D hydrodynamic model for the 2021 flood event in Western Germany
Precursors and pathways: dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood
Demonstrating the use of UNSEEN climate data for hydrological applications: case studies for extreme floods and droughts in England
Recent large inland lake outbursts on the Tibetan Plateau: Processes, causes and mechanisms
Exploring the use of seasonal forecasts to adapt flood insurance premiums
Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event
Water depth estimate and flood extent enhancement for satellite-based inundation maps
Probabilistic flood inundation mapping through copula Bayesian multi-modeling of precipitation products
Flood occurrence and impact models for socioeconomic applications over Canada and the United States
Model-based assessment of climate change impact on inland flood risk at the German North Sea coast caused by compounding storm tide and precipitation events
Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood
Dynamics and Impacts of Monsoon-Induced Geological Hazards: A 2022 Flood Study along the Swat River in Pakistan
An improved dynamic bidirectional coupled hydrologic–hydrodynamic model for efficient flood inundation prediction
Quantifying hazard resilience by modeling infrastructure recovery as a resource-constrained project scheduling problem
Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain
A downward-counterfactual analysis of flash floods in Germany
Hyper-resolution flood hazard mapping at the national scale
Compound droughts under climate change in Switzerland
Brief communication: SWM – stochastic weather model for precipitation-related hazard assessments using ERA5-Land data
Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany
The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0
Limited effect of the confluence angle and tributary gradient on Alpine confluence morphodynamics under intense sediment loads
Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods?
Added value of seasonal hindcasts to create UK hydrological drought storylines
Flash flood detection via copula-based intensity–duration–frequency curves: evidence from Jamaica
Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90: a case study of the European drought of 2018
How to mitigate flood events similar to the 1979 catastrophic floods in the lower Tagus
Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam
CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale
Current and future rainfall-driven flood risk from hurricanes in Puerto Rico under 1.5 and 2 °C climate change
Using integrated hydrological–hydraulic modelling and global data sources to analyse the February 2023 floods in the Umbeluzi Catchment (Mozambique)
Paola Ceresa, Gianbattista Bussi, Simona Denaro, Gabriele Coccia, Paolo Bazzurro, Mario Martina, Ettore Fagà, Carlos Avelar, Mario Ordaz, Benjamin Huerta, Osvaldo Garay, Zhanar Raimbekova, Kanatbek Abdrakhmatov, Sitora Mirzokhonova, Vakhitkhan Ismailov, and Vladimir Belikov
Nat. Hazards Earth Syst. Sci., 25, 403–428, https://doi.org/10.5194/nhess-25-403-2025, https://doi.org/10.5194/nhess-25-403-2025, 2025
Short summary
Short summary
A fully probabilistic flood risk assessment was carried out for five Central Asian countries to support regional and national risk financing and insurance applications. The paper presents the first high-resolution regional-scale transboundary flood risk assessment study in the area aiming to provide tools for decision-making.
Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
Nat. Hazards Earth Syst. Sci., 25, 335–351, https://doi.org/10.5194/nhess-25-335-2025, https://doi.org/10.5194/nhess-25-335-2025, 2025
Short summary
Short summary
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 1000× speed-ups. The model also generalizes to larger more complex case studies with just one additional simulation for fine-tuning.
Maria Staudinger, Martina Kauzlaric, Alexandre Mas, Guillaume Evin, Benoit Hingray, and Daniel Viviroli
Nat. Hazards Earth Syst. Sci., 25, 247–265, https://doi.org/10.5194/nhess-25-247-2025, https://doi.org/10.5194/nhess-25-247-2025, 2025
Short summary
Short summary
Various combinations of antecedent conditions and precipitation result in floods of varying degrees. Antecedent conditions played a crucial role in generating even large ones. The key predictors and spatial patterns of antecedent conditions leading to flooding at the basin's outlet were distinct. Precipitation and soil moisture from almost all sub-catchments were important for more frequent floods. For rarer events, only the predictors of specific sub-catchments were important.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 4609–4615, https://doi.org/10.5194/nhess-24-4609-2024, https://doi.org/10.5194/nhess-24-4609-2024, 2024
Short summary
Short summary
Floods have caused significant damage in the past. To prepare for such events, we rely on historical data but face issues due to rare rainfall events, lack of data and climate change. Counterfactuals, or
what ifscenarios, simulate historical rainfall in different locations to estimate flood levels. Our new study refines this by deriving more-plausible local scenarios, using the June 2024 Bavaria flood as a case study. This method could improve preparedness for future floods.
Chinh Luu, Giuseppe Forino, Lynda Yorke, Hang Ha, Quynh Duy Bui, Hanh Hong Tran, Dinh Quoc Nguyen, Hieu Cong Duong, and Matthieu Kervyn
Nat. Hazards Earth Syst. Sci., 24, 4385–4408, https://doi.org/10.5194/nhess-24-4385-2024, https://doi.org/10.5194/nhess-24-4385-2024, 2024
Short summary
Short summary
This study presents a novel and integrated approach to assessing the climate hazards of floods and wildfires. We explore multi-hazard assessment and risk through a machine learning modeling approach. The process includes collecting a database of topography, climate, geology, environment, and building data; developing models for multi-hazard assessment and coding in the Google Earth Engine; and producing credible multi-hazard susceptibility and building exposure maps.
Claudia De Lucia, Michele Amaddii, and Chiara Arrighi
Nat. Hazards Earth Syst. Sci., 24, 4317–4339, https://doi.org/10.5194/nhess-24-4317-2024, https://doi.org/10.5194/nhess-24-4317-2024, 2024
Short summary
Short summary
This work describes the flood damage to cultural heritage (CH) that occurred in September 2022 in central Italy. Datasets related to flood impacts on cultural heritage are rare, and this work aims at highlighting both tangible and intangible aspects and their correlation with physical characteristics of flood (i.e. water depth and flow velocity). The results show that current knowledge and datasets are inadequate for risk assessment of CH.
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
Nat. Hazards Earth Syst. Sci., 24, 4091–4107, https://doi.org/10.5194/nhess-24-4091-2024, https://doi.org/10.5194/nhess-24-4091-2024, 2024
Short summary
Short summary
When assessing the likelihood of compound flooding, most studies ignore that it can arise from different storm types with distinct statistical characteristics. Here, we present a new statistical framework that accounts for these differences and shows how neglecting these can impact the likelihood of compound flood potential.
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci., 24, 4015–4030, https://doi.org/10.5194/nhess-24-4015-2024, https://doi.org/10.5194/nhess-24-4015-2024, 2024
Short summary
Short summary
Flood risk assessments help us decide how to reduce the risk of flooding. Since these assessments are based on probabilities, it is hard to check their accuracy by comparing them to past data. We suggest a new way to validate these assessments, making sure they are practical for real-life decisions. This approach looks at both the technical details and the real-world situations where decisions are made. We demonstrate its practicality by applying it to flood emergency planning.
Zhi Li, Hanqi Li, Zhibo Zhang, Chaomeng Dai, and Simin Jiang
Nat. Hazards Earth Syst. Sci., 24, 3977–3990, https://doi.org/10.5194/nhess-24-3977-2024, https://doi.org/10.5194/nhess-24-3977-2024, 2024
Short summary
Short summary
This study used advanced computer simulations to investigate how earthquake-induced building collapse affects flooding of the metro stations in Shanghai. Results show that the influences of building collapse on rainfall-driven and river-driven floods are different because these two types of floods have different origination and propagation mechanisms.
Maria Magdalena Warter, Dörthe Tetzlaff, Christian Marx, and Chris Soulsby
Nat. Hazards Earth Syst. Sci., 24, 3907–3924, https://doi.org/10.5194/nhess-24-3907-2024, https://doi.org/10.5194/nhess-24-3907-2024, 2024
Short summary
Short summary
Streams are increasingly impacted by droughts and floods. Still, the amount of water needed for sustainable flows remains unclear and contested. A comparison of two streams in the Berlin–Brandenburg region of northeast Germany, using stable water isotopes, shows strong groundwater dependence with seasonal rainfall contributing to high/low flows. Understanding streamflow variability can help us assess the impacts of climate change on future water resource management.
Samuel Jonson Sutanto, Matthijs Janssen, Mariana Madruga de Brito, and Maria del Pozo Garcia
Nat. Hazards Earth Syst. Sci., 24, 3703–3721, https://doi.org/10.5194/nhess-24-3703-2024, https://doi.org/10.5194/nhess-24-3703-2024, 2024
Short summary
Short summary
A conventional flood risk assessment only evaluates flood hazard in isolation without considering wildfires. This study, therefore, evaluates the effect of wildfires on flood risk, considering both current and future conditions for the Ebro River basin in Spain. Results show that extreme climate change increases the risk of flooding, especially when considering the effect of wildfires, highlighting the importance of adopting a multi-hazard risk management approach.
Miroslav Spano and Jaromir Riha
Nat. Hazards Earth Syst. Sci., 24, 3683–3701, https://doi.org/10.5194/nhess-24-3683-2024, https://doi.org/10.5194/nhess-24-3683-2024, 2024
Short summary
Short summary
The study examines the effects of hydrogeological hazard due to construction of the Skalička Dam near the Hranice Karst on groundwater discharges and water levels in the local karst formations downstream. A simplified pipe model was used to analyze the impact of two dam layouts: lateral and through-flow reservoirs. Results show that the through-flow scheme more significantly influences water levels and the discharge of mineral water, while the lateral layout has only negligible impact.
Rudolf Brázdil, Dominika Faturová, Monika Šulc Michalková, Jan Řehoř, Martin Caletka, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 3663–3682, https://doi.org/10.5194/nhess-24-3663-2024, https://doi.org/10.5194/nhess-24-3663-2024, 2024
Short summary
Short summary
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
Nat. Hazards Earth Syst. Sci., 24, 3627–3649, https://doi.org/10.5194/nhess-24-3627-2024, https://doi.org/10.5194/nhess-24-3627-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Fenglin Xu, Yong Liu, Guoqing Zhang, Ping Zhao, R. Iestyn Woolway, Yani Zhu, Jianting Ju, Tao Zhou, Xue Wang, and Wenfeng Chen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-127, https://doi.org/10.5194/nhess-2024-127, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Glacial lake outbursts have been widely studied, but large inland lake outbursts have received less attention. Recently, with the rapid expansion of inland lakes, signs of potential outbursts have increased. However, the processes, causes, and mechanisms are still not well understood. Here, the outburst processes were investigated using a combination of field surveys, remote sensing mapping, and hydrodynamic modelling. The causes and mechanisms that triggered the two events were investigated.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
AghaKouchak, A., Huning, L. S., Chiang, F., Sadegh, M., Vahedifard, F.,
Mazdiyasni, O., Moftakhari, H., and Mallakpour, I.: How do natural hazards
cascade to cause disasters?, Nature, 561, 458–460, 2018.
Aitchison, J.: Lognormal Distribution, Cambridge University Press., Cambridge, UK, 1957.
Akaike, H.: A new look at the statistical model identification, IEEE Trans.
Automat. Contr., 19, 716–723, 1974.
Anderson, G. and Klugmann, D.: A European lightning density analysis using 5 years of ATDnet data, Nat. Hazards Earth Syst. Sci., 14, 815–829, https://doi.org/10.5194/nhess-14-815-2014, 2014.
Arnold, T. B. and Emerson, J. W.: Nonparametric goodness-of-fit tests for
discrete null distributions, R J., 3, 34–39, 2011.
Barriopedro, D., Fischer, E. M., Luterbacher, J., Trigo, R. M., and
García-Herrera, R.: The hot summer of 2010: Redrawing the temperature
map of Europe, Science, 332, 220–224, 2011.
Bedford, T. and Cooke, R. M.: Vines : A New Graphical Model for Dependent Random Variables, Ann. Stat., 30, 1031–1068, 2002.
Bevacqua, E., Maraun, D., Hobæk Haff, I., Widmann, M., and Vrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, 2017.
Brechmann, E. C. and Schepsmeier, U.: Modeling Dependence with C- and D-Vine Copulas: The RPackage CDVine, J. Stat. Softw., 52, 1–27, 2013. https://doi.org/10.18637/jss.v052.i03, 2013.
Canty, A. and Ripley, B. D.: boot: Bootstrap R (S-Plus) Functions, available at: https://cran.r-project.org/web/packages/boot/citation.html (last access: 22 June 2020), 2019.
CCR (Caisse Centrale de Réassurance): E-risk database, Paris, France,
available at: https://catastrophes-naturelles.ccr.fr (last access: 1
December 2019), 2019.
Chebana, F. and Ouarda, T. B. M. J.: Multivariate quantiles in hydrological
frequency analysis, Environmetrics, 22, 63–78, 2011.
Clare, M. A., Talling, P. J., Challenor, P. G., and Hunt, J. E.: Tempo and
Triggering of Large Submarine Landslides: Statistical Analysis for Hazard
Assessment, in: Advances in Natural and Technological Hazards Research, Vol.
41, edited by: Lamarche, G., Mountjoy, J., Bull, S., Hubble, T., Krastel, S., Lane, E., Micallef, A., Moscardelli, L., Mueller, C., Pecher, I., and Woelz, S., Springer International Publishing, Cham, Switzerland, 509–517, 2016.
Coles, S.: An Introduction to Statistical Modelling of Extreme Values,
Springer London, London, UK, 2001.
Coles, S. and Tawn, J. A.: Modelling extreme multivariate events, J. R.
Stat. Soc., 53, 285–339, 1991.
Coles, S., Heffernan, J. E., and Tawn, J. A.: Dependence measure for extreme
value analyses, Extremes, 1225, 41–42, 1999.
Cooley, D., Thibaud, E., Castillo, F., and Wehner, M. F.: A nonparametric
method for producing isolines of bivariate exceedance probabilities,
Extremes, 22, 373–390, 2019.
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J. M., and Jones,
P. D.: An ensemble version of the E-OBS temperature and precipitation data
sets, J. Geophys. Res.-Atmos., 123, 9391–9409, 2018.
Couasnon, A., Sebastian, A., and Morales-Nápoles, O.: A copula-based
Bayesian network for modeling compound flood hazard from riverine and
coastal interactions at the catchment scale: an application to the Houston
ship channel, Texas, Water, 10, 1190, https://doi.org/10.3390/w10091190,
2018.
Davison, A. C. and Hinkley, D. V.: Bootstrap Methods and Their Applications,
Cambridge University Press, Cambridge, UK, 1997.
Davison, A. C. and Huser, R.: Statistics of extremes, Annu. Rev. Stat. Appl., 2, 203–235, 2015.
De Haan, L. and De Ronde, J.: Sea and wind: multivariate extremes at work,
Extremes, 1, 7–45, 1998.
De Michele, C., Salvadori, G., Passoni, G., and Vezzoli, R.: A multivariate
model of sea storms using copulas, Coast. Eng., 54, 734–751, 2007.
De Haan, L. and Resnick, S. I.: Limit theory for multivariate sample extremes, Z. Wahrscheinlichkeit., 40, 317–337, 1977.
Dowdy, A. J. and Catto, J. L.: Extreme weather caused by concurrent cyclone,
front and thunderstorm occurrences, Sci. Rep., 7, 1–8, 2017.
Duong, T.: ks: Kernel density estimation and kernel discriminant analysis
for multivariate data, R, J. Stat. Softw., 21, 1–16,
https://doi.org/10.18637/jss.v021.i07, 2007.
Duong, T.: Non-parametric smoothed estimation of multivariate cumulative
distribution and survival functions, and receiver operating characteristic
curves, J. Korean Stat. Soc., 45, 33–50, 2015.
Dutfoy, A., Parey, S., and Roche, N.: Multivariate extreme value theory - A
tutorial with applications to hydrology and meteorology, Depend. Model.,
2, 30–48, 2014.
ECA&D: ECA&D Project, available at: https://www.ecad.eu/, last access: 12 February 2020.
Frau, R., Andreewsky, M., and Bernardara, P.: The use of historical information for regional frequency analysis of extreme skew surge, Nat. Hazards Earth Syst. Sci., 18, 949–962, https://doi.org/10.5194/nhess-18-949-2018, 2018.
Genest, C. and Favre, A.-C.: Everything you always wanted to know about
copula modeling but were afraid to ask, J. Hydrol. Eng., 12, 347–368,
2007.
Genest, C. and Nešlehová, J.: Copula Modeling for Extremes, in: Encyclopedia of Environmetrics, John Wiley & Sons Ltd, Chichester, UK, 1–6, 2013.
Genest, C., Rémillard, B., and Beaudoin, D.: Goodness-of-fit tests for
copulas: A review and a power study, Insur. Math. Econ., 44, 199–213,
2009.
Genest, C., Kojadinovic, I., Nešlehová, J., and Yan, J.: A
goodness-of-fit test for bivariate extreme-value copulas, Bernoulli, 17,
253–275, 2011.
Gill, J. C. and Malamud, B. D.: Reviewing and visualizing the interactions
of natural hazards, Rev. Geophys., 52, 680–722, 2014.
Gouldby, B., Wyncoll, D., Panzeri, M., Franklin, M., Hunt, T., Hames, D.,
Tozer, N., Hawkes, P., Dornbusch, U., and Pullen, T.: Multivariate extreme
value modelling of sea conditions around the coast of England, Proc. Inst.
Civ. Eng. Marit. Eng., 170, 3–20, 2017.
Hanea, A., Kurowicka, D., Cooke, R. M. and Ababei, D. A.: Mining and visualising ordinal data with non-parametric continuous BBNs, Comput. Stat. Data Anal., 54, 668–687, 2010.
Hanea, A., Morales Napoles, O., and Ababei, D.: Non-parametric Bayesian
networks: Improving theory and reviewing applications, Reliab. Eng. Syst.
Saf., 144, 265–284, 2015.
Hao, Z. and Singh, V. P.: Review of dependence modeling in hydrology and
water resources, Prog. Phys. Geogr., 40, 549–578, 2016.
Hao, Z., Hao, F., Singh, V. P., and Ouyang, W.: Quantitative risk assessment
of the effects of drought on extreme temperature in eastern China, J.
Geophys. Res.-Atmos., 122, 9050–9059, 2017.
Hao, Z., Singh, V., and Hao, F.: Compound extremes in hydroclimatology: A
review, Water, 10, 718, https://doi.org/10.3390/w10060718, 2018.
Hashemi, S. J., Khan, F. I. and Ahmed, S.: Multivariate probabilistic safety analysis of process facilities using the Copula Bayesian Network model, Comput. Chem. Eng., 93, 128–142, 2016.
Hatvani-Kovacs, G., Belusko, M., Pockett, J., and Boland, J.: Assessment of
heatwave impacts, Procedia. Engineer., 169, 316–323, 2016.
Hauser, M., Orth, R., and Seneviratne, S. I.: Role of soil moisture vs. recent climate
change for heat waves in western Russia, Geophys. Res. Lett., 43,
2819–2826, 2015.
Hawkes, P. J.: Joint probability analysis for estimation of extremes, J.
Hydraul. Res., 46, 246–256, 2008.
Hawkes, P. J., Gouldby, B. P., Tawn, J. A., and Owen, M. W.: The joint
probability of waves and water levels in coastal engineering design, J.
Hydraul. Res., 40, 241–251, 2002.
Heffernan, J. E.: A directory of coefficients of tail dependence, Extremes,
3, 279–290, 2000.
Heffernan, J. E. and Tawn, J. A.: A conditional approach for multivariate
extreme values (with discussion), J. Roy. Stat. Soc. B, 66, 497–546, 2004.
Hendry, A., Haigh, I. D., Nicholls, R. J., Winter, H., Neal, R., Wahl, T., Joly-Laugel, A., and Darby, S. E.: Assessing the characteristics and drivers of compound flooding events around the UK coast, Hydrol. Earth Syst. Sci., 23, 3117–3139, https://doi.org/10.5194/hess-23-3117-2019, 2019.
Hilal, S., Poon, S. H., and Tawn, J.: Hedging the black swan: Conditional
heteroskedasticity and tail dependence in S&P500 and VIX, J. Bank.
Financ., 35, 2374–2387, 2011.
Hincks, T. K., Malamud, B. D., Sparks, R. S. J., Wooster, M. J., and Lynham, T. J.: Risk assessment and management of wildfires, in: Risk and uncertainty
assessment for natural hazards, edited by: Rougier, J., Sparks, S., and Hill, L., Cambridge University Press, Cambridge, 398–444, 2013.
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface
temperature, J. Geophys. Res.-Atmos., 114, D21101,
https://doi.org/10.1029/2009JD011799, 2009.
Huser, R.: Statistical Modeling and Inference for Spatio-Temporal Extremes, PhD thesis,
EPFL, available at: https://infoscience.epfl.ch/record/188557?ln=en (last access: 28 January 2020), 2013.
Instituto National de Estatistica Portugal, https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_indicadores&indOcorrCod=0004168&contexto=bd&selTab=tab2, last access: 1 December 2019.
Joe, H.: Multivariate models and multivariate dependence concepts, Chapman and Hall/CRC, London, 1997.
Johansson, B. and Chen, D.: The influence of wind and topography on
precipitation distribution in Sweden: Statistical analysis and modelling,
Int. J. Climatol., 23, 1523–1535, 2003.
Kahle, D. and Wickham, H.: ggmap: Spatial Visualization with ggplot2, R
J., 5, 144–161, 2013.
Keef, C., Papastathopoulos, I., and Tawn, J. A.: Estimation of the
conditional distribution of a multivariate variable given that one of its
components is large: Additional constraints for the Heffernan and Tawn
model, J. Multivar. Anal., 115, 396–404, 2013.
Koopmans, L. H., Owen, D. B., and Rosenblatt, J. I.: Confidence intervals for
the coefficient of variation for the normal and log normal distributions,
Biometrika, 51, 25–32, 1964.
Ledford, A. W. and Tawn, J. A: Statistics for near independence in
multivariate extreme values, Biometrika, 83, 169–187, 1996.
Ledford, A. W. and Tawn, J. A.: Modelling dependence within joint tail
regions, J. Roy. Stat. Soc. B, 59, 475–499, 1997.
Ledford, A. W. and Tawn, J. A.: Diagnostics for dependence within time
series extremes, J. Roy. Stat. Soc. B, 65, 521–543,
2003.
Leonard, M., Westra, S., Phatak, A., Lambert, M., van den Hurk, B., McInnes,
K., Risbey, J., Schuster, S., Jakob, D., and Stafford-Smith, M.: A compound
event framework for understanding extreme impacts, Wiley Interdiscip. Rev.
Clim. Chang., 5, 113–128, 2014.
Littell, J. S., McKenzie, D., Peterson, D. L., and Westerling, A. L.:
Climate and wildfire area burned in western US ecoprovinces, 1916–2003,
Ecol. Appl., 19, 1003–1021, 2009.
Liu, Z., Cheng, L., Hao, Z., Li, J., Thorstensen, A., and Gao, H.: A
framework for exploring joint effects of conditional factors on compound
floods, Water Resour. Res., 54, 2681–2696, 2018.
Loukatou, A., Howell, S., Johnson, P., and Duck, P.: Stochastic wind speed
modelling for estimation of expected wind power output, Appl. Energ., 228,
1328–1340, 2018.
Malamud, B. D. and Turcotte, D. L.: Self-affine time series: I. Generation
and analyses, Adv. Geophys., 40, 1–90, 1999.
Malamud, B. D. and Turcotte, D. L.: The applicability of power-law frequency
statistics to floods, J. Hydrol., 322, 168–180, 2006.
Martius, O., Pfahl, S., and Chevalier, C.: A global quantification of
compound precipitation and wind extremes, Geophys. Res. Lett., 43,
7709–7717, 2016.
Maulik, K. and Resnick, S.: Characterizations and examples of hidden regular
variation, Extremes, 7, 31–67, 2005.
Mazas, F. and Hamm, L.: An event-based approach for extreme joint
probabilities of waves and sea levels, Coast. Eng., 122, 44–59, 2017.
Met Office: How we measure wind: available at: https://www.metoffice.gov.uk/weather/guides/observations/how-we-measure-wind, last access: 12 November 2019.
Ming, X., Xu, W., Li, Y., Du, J., Liu, B., and Shi, P.: Quantitative
multi-hazard risk assessment with vulnerability surface and hazard joint
return period, Stoch. Environ. Res. Risk Assess., 29, 35–44, 2015.
Miranda, P. M. A., Coelho, F. E. S., Tomé, A. R., Valente, M. A.,
Carvalho, A., Pires, C., Pires, H. O., Pires, V. C., and Ramalho, C.: 20th
Century Portuguese Climate and Climate Scenarios, in: Climate Change in
Portugal. Scenarios, Impacts and Adaptation Measures – SIAM Project, edited by: Santos,
F. D., Forbes, K., and Moita, R., Gradiva Publishers, Lisbon, 28–83, 2002.
Nelsen, R.: An Introduction to Copulas, Springer New York, New York, NY, USA,
2006.
Nguyen Sinh, H., Lombardo, F. T., and Letchford, C.: Multivariate simulation
for assessing the joint wind and ice hazard in the United States, J. Wind
Eng. Ind. Aerodyn., 184, 436–444, 2019.
Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980–2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343–3358, https://doi.org/10.5194/nhess-11-3343-2011, 2011.
Perkins, S. E.: A review on the scientific understanding of heatwaves-Their measurement, driving mechanisms, and changes at the global scale, Atmos. Res., 164–165, 242–267, 2015.
Petroliagkis, T. I.: Estimations of statistical dependence as joint return period modulator of compound events – Part 1: Storm surge and wave height, Nat. Hazards Earth Syst. Sci., 18, 1937–1955, https://doi.org/10.5194/nhess-18-1937-2018, 2018
Pickands, J.: Multivariate extreme value distribution, in: Proceedings of the 43th Session of International Statistical Institution, Buenos Aires, 1981.
Raveh-Rubin, S. and Wernli, H.: Large-scale wind and precipitation extremes
in the Mediterranean: dynamical aspects of five selected cyclone events, Q.
J. R. Meteorol. Soc., 142, 3097–3114, 2016.
Resnick, S.: Hidden regular variation, second order regular variation and
asymptotic independence, Extremes, 5, 303–336, 2002.
Resnick, S. I.: Extreme Values, Regular Variation and Point Processes,
Springer New York, New York, NY, USA, 1987.
Sachs, M. K., Yoder, M. R., Turcotte, D. L., Rundle, J. B., and Malamud, B.
D.: Black swans, power laws, and dragon-kings: Earthquakes, volcanic
eruptions, landslides, wildfires, floods, and SOC models, Eur. Phys. J.
Spec. Top., 205, 167–182, 2012.
Sadegh, M., Ragno, E., and AghaKouchak, A.: Multivariate Copula Analysis
Toolbox (MvCAT): Describing dependence and underlying uncertainty using a
Bayesian framework, Water Resour. Res., 53, 5166–5183, 2017.
Sadegh, M., Moftakhari, H., Gupta, H. V., Ragno, E., Mazdiyasni, O.,
Sanders, B., Matthew, R., and AghaKouchak, A.: Multihazard scenarios for
analysis of compound extreme events, Geophys. Res. Lett., 45,
5470–5480, 2018.
Salvadori, G.: Bivariate return periods via 2-Copulas, Stat. Methodol.,
1, 129–144, 2004.
Salvadori, G. and De Michele, C.: Multivariate multiparameter extreme value
models and return periods: A copula approach, Water Resour. Res., 46, 2009WR009040, https://doi.org/10.1029/2009WR009040, 2010.
Salvadori, G., Durante, F., De Michele, C., Bernardi, M., and Petrella, L.: A
multivariate copula-based framework for dealing with hazard scenarios and
failure probabilities, Water Resour. Res., 52, 3701–3721, 2016.
Schwarz, G.: Estimating the dimension of a model, Ann. Stat., 6,
461–464, 1978.
Serinaldi, F.: Dismissing return periods!, Stoch. Environ. Res. Risk
Assess., 29, 1179–1189, 2015.
Serinaldi, F.: Can we tell more than we can know? The limits of bivariate
drought analyses in the United States, Stoch. Environ. Res. Risk Assess.,
30, 1691–1704, 2016.
Sklar, A.: Fonction de répartition dont les marges sont données, Publications de l’Institut Statistique de l’Université de Paris, 8, 229–231, 1959.
Stephens, M. A.: Use of the Kolmogorov-Smirnov, Cramer-Von Mises and related
statistics without extensive tables, J. R. Stat. Soc. Ser. B, 32, 115–122, 1970.
Sutanto, S. J., Vitolo, C., Di Napoli, C., D'Andrea, M., and Van Lanen, H. A.
J.: Heatwaves, droughts, and fires: Exploring compound and cascading dry
hazards at the pan-European scale, Environ. Int., 134, 105276, https://doi.org/10.1016/j.envint.2019.105276, 2020.
Tedim, F., Leone, V., Amraoui, M., Bouillon, C., Coughlan, M., Delogu, G., Fernandes, P., Ferreira, C., McCaffrey, S., McGee, T., Parente, J., Paton, D., Pereira, M., Ribeiro, L., Viegas, D. and Xanthopoulos, G.: Defining Extreme Wildfire Events: Difficulties, Challenges, and Impacts, Fire, 1, 9, https://doi.org/10.3390/fire1010009, 2018.
Tencer, B., Weaver, A., and Zwiers, F.: Joint occurrence of daily temperature
and precipitation extreme events over Canada, J. Appl. Meteorol. Climatol.,
53, 2148–2162, 2014.
Terzi, S., Torresan, S., Schneiderbauer, S., Critto, A., Zebisch, M., and
Marcomini, A.: Multi-risk assessment in mountain regions: A review of
modelling approaches for climate change adaptation, J. Environ. Manage.,
232, 759–771, 2019.
Tilloy, A.: Bivariate_models, available at: https://gitlab.com/doudeg/bivariate_models, last access: 11 January 2020a.
Tilloy, A.: Comparison of bivariate extreme modelling approaches for multi-hazard scenarios, Zenodo, https://doi.org/10.5281/zenodo.3686962, 2020b.
Tilloy, A., Malamud, B. D., Winter, H., and Joly-Laugel, A.: A review of
quantification methodologies for multi-hazard interrelationships,
Earth-Sci. Rev., 196, 102881, https://doi.org/10.1016/j.earscirev.2019.102881,
2019.
UERRA: UERRA Project, available at: http://www.uerra.eu/, last access: 12 February 2020.
UNISDR (United Nations Office for Disaster Risk Reduction): UNISDR
Terminology on Disaster Risk Reduction, United Nations International Strategy for Disaster
Reduction (UNISDR), Geneva, Switzerland, 2009.
Vitolo, C., Di Napoli, C., Di Giuseppe, F., Cloke, H. L., and Pappenberger,
F.: Mapping combined wildfire and heat stress hazards to improve
evidence-based decision making, Environ. Int., 127, 21–34, 2019.
Vogel, M. M., Zscheischler, J., Fischer, E. M. and Seneviratne, S. I.: Development of future heatwaves for different hazard thresholds, J. Geophys. Res. Atmos., 125, e2019JD032070, https://doi.org/10.1029/2019JD032070, 2020.
Volpi, E. and Fiori, A.: Design event selection in bivariate hydrological
frequency analysis, Hydrol. Sci. J., 57, 1506–1515, 2012.
Webb, J. D. C. and Elsom, D. M.: Severe Hailstorms in the United Kingdom and
Ireland: A Climatological Survey with Recent and Historical Case Studies,
in: Extreme Weather: Forty Years of the Tornado and Storm Research
Organisation (TORRO), edited by: Doe, R. K., John Wiley Sons, Chichester, UK, 155–194,
2016.
Winter, H. C.: Extreme Value Modelling of Heatwaves, PhD thesis, Lancaster
University, available at: https://eprints.lancs.ac.uk/id/eprint/79961/ (last access: 28 December 2019), 2016.
Winter, H. C. and Tawn, J. A.: Modelling heatwaves in central France: A
case-study in extremal dependence, J. R. Stat. Soc. Ser. C-Appl.,
65, 345–365, 2016.
Winter, H. C., Tawn, J. A., and Brown, S. J.: Modelling the effect of the El
Niño-southern oscillation on extreme spatial temperature events over
Australia, Ann. Appl. Stat., 10, 2075–2101, 2016.
Witte, J. C., Douglass, A. R., da Silva, A., Torres, O., Levy, R., and Duncan, B. N.: NASA A-Train and Terra observations of the 2010 Russian wildfires, Atmos. Chem. Phys., 11, 9287–9301, https://doi.org/10.5194/acp-11-9287-2011, 2011.
WMO (World Meteorological Organization) OSCAR: Details for
Variable: Wind gust, available at:
https://www.wmo-sat.info/oscar/variables/view/205 (last access: 23 June 2019),
2019.
Zheng, F., Westra, S., and Sisson, S. A.: Quantifying the dependence between
extreme rainfall and storm surge in the coastal zone, J. Hydrol., 505,
172–187, 2013.
Zheng, F., Westra, S., Leonard, M., and Sisson, S. A.: Modeling dependence
between extreme rainfall and storm surge to estimate coastal flooding risk,
Water Resour. Res., 50, 2050–2071, 2014.
Zscheischler, J. and Seneviratne, S. I.: Dependence of drivers affects risks
associated with compound events, Sci. Adv., 3, e1700263, https://doi.org/10.1016/j.ecoinf.2013.03.004, 2017.
Zscheischler, J., Westra, S., Van Den Hurk, B. J. J. M., Seneviratne, S. I.,
Ward, P. J., Pitman, A., Aghakouchak, A., Bresch, D. N., Leonard, M., Wahl,
T., and Zhang, X.: Future climate risk from compound events, Nat. Clim.
Chang., 8, 469–477, 2018.
Download
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
- Article
(10957 KB) - Full-text XML
- Corrigendum
-
Supplement
(457 KB) - BibTeX
- EndNote
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....
Altmetrics
Final-revised paper
Preprint