Articles | Volume 25, issue 2
https://doi.org/10.5194/nhess-25-747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
20 Feb 2025
Review article |
| 20 Feb 2025
| 20 Feb 2025
Review article: A comprehensive review of compound flooding literature with a focus on coastal and estuarine regions
School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, European Way, Southampton SO14 3ZH, UK
Fathom, Clifton Heights, Bristol BS8 1EJ, UK
Ivan D. Haigh
School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, European Way, Southampton SO14 3ZH, UK
Fathom, Clifton Heights, Bristol BS8 1EJ, UK
Niall Quinn
Fathom, Clifton Heights, Bristol BS8 1EJ, UK
Jeff Neal
Fathom, Clifton Heights, Bristol BS8 1EJ, UK
School of Geographical Sciences, University of Bristol, University Road, Bristol BS8 1SS, UK
Thomas Wahl
Department of Civil, Environmental, and Construction Engineering and National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL 32816, USA
Melissa Wood
School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, European Way, Southampton SO14 3ZH, UK
Dirk Eilander
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
Deltares, 2629 HV Delft, the Netherlands
Marleen de Ruiter
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
Philip Ward
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
Deltares, 2629 HV Delft, the Netherlands
Paula Camus
School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, European Way, Southampton SO14 3ZH, UK
Geomatics and Ocean Engineering Group, Departamento de Ciencias y Técnicas del Agua y del Medio Ambiente, ETSICCP, Universidad de Cantabria, 39005 Santander, Spain
Related authors
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates
Nat. Hazards Earth Syst. Sci., 24, 2403–2423, https://doi.org/10.5194/nhess-24-2403-2024, https://doi.org/10.5194/nhess-24-2403-2024, 2024
Short summary
Short summary
Coastal areas are at risk of flooding from rising sea levels and extreme weather events. This study applies a new approach to estimating the likelihood of coastal flooding around the world. The method uses data from observations and computer models to create a detailed map of where these coastal floods might occur. The approach can predict flooding in areas for which there are few or no data available. The results can be used to help prepare for and prevent this type of flooding.
Ekta Aggarwal, Marleen C. de Ruiter, Kartikeya S. Sangwan, Rajiv Sinha, Sophie Buijs, Ranjay Shrestha, Sanjeev Gupta, and Alexander C. Whittaker
EGUsphere, https://doi.org/10.5194/egusphere-2024-3901, https://doi.org/10.5194/egusphere-2024-3901, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
The occurrence of frequent floods in recent years due to changing weather, heavy rainfall, and the natural landscape, has caused major damage to lives and property. This study looks at flood risks in the Ganga Basin, focusing on the factors that cause floods, the areas affected, and the vulnerability of people. The study uses NASA's night-time lights to track human activities. This helps to show how risks are connected to expanding human activities, and changing resilience to floods.
Julius Schlumberger, Tristian Stolte, Helena Margaret Garcia, Antonia Sebastian, Wiebke Jäger, Philip Ward, Marleen de Ruiter, Robert Šakić Trogrlić, Annegien Tijssen, and Mariana Madruga de Brito
EGUsphere, https://doi.org/10.5194/egusphere-2025-850, https://doi.org/10.5194/egusphere-2025-850, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
The risk flood of flood impacts is dynamic as society continuously responds to specific events or ongoing developments. We analyzed 28 studies that assess such dynamics of vulnerability. Most research uses surveys and basic statistics data, while integrated, flexible models are seldom used. The studies struggle to link specific events or developments to the observed changes. Our findings highlight needs and possible directions towards a better assessment of vulnerability dynamics.
Nivedita Sairam and Marleen de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2025-920, https://doi.org/10.5194/egusphere-2025-920, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
This paper highlights gaps in disaster risk assessments, particularly regarding disease outbreaks after natural hazards. It calls for: 1) learning from compound risk models to understand disaster and disease probabilities, 2) including health metrics in risk frameworks, and 3) improving data and modeling for health impacts. The authors propose a research agenda to enhance disaster risk management.
Sadhana Nirandjan, Elco E. Koks, Mengqi Ye, Raghav Pant, Kees C. H. Van Ginkel, Jeroen C. J. H. Aerts, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 24, 4341–4368, https://doi.org/10.5194/nhess-24-4341-2024, https://doi.org/10.5194/nhess-24-4341-2024, 2024
Short summary
Short summary
Critical infrastructures (CIs) are exposed to natural hazards, which may result in significant damage and burden society. Vulnerability is a key determinant for reducing these risks, yet crucial information is scattered in the literature. Our study reviews over 1510 fragility and vulnerability curves for CI assets, creating a unique publicly available physical vulnerability database that can be directly used for hazard risk assessments, including floods, earthquakes, windstorms, and landslides.
Julius Schlumberger, Robert Šakić Trogrlić, Jeroen C. J. H. Aerts, Jung-Hee Hyun, Stefan Hochrainer-Stigler, Marleen de Ruiter, and Marjolijn Haasnoot
EGUsphere, https://doi.org/10.5194/egusphere-2024-3655, https://doi.org/10.5194/egusphere-2024-3655, 2024
Short summary
Short summary
This study presents a dashboard to help decision-makers manage risks in a changing climate. Using interactive visualizations, it simplifies complex choices, even with uncertain information. Tested with 54 users of varying expertise, it enabled accurate responses to 71–80 % of questions. Users valued its scenario exploration and detailed data features. While effective, the guidance and set of visualizations could be extended and the prototype could be adapted for broader applications.
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.
Rodrigo Campos-Caba, Jacopo Alessandri, Paula Camus, Andrea Mazzino, Francesco Ferrari, Ivan Federico, Michalis Vousdoukas, Massimo Tondello, and Lorenzo Mentaschi
Ocean Sci., 20, 1513–1526, https://doi.org/10.5194/os-20-1513-2024, https://doi.org/10.5194/os-20-1513-2024, 2024
Short summary
Short summary
Here we show the development of high-resolution simulations of storm surge in the northern Adriatic Sea employing different atmospheric forcing data and physical configurations. Traditional metrics favor a simulation forced by a coarser database and employing a less sophisticated setup. Closer examination allows us to identify a baroclinic model forced by a high-resolution dataset as being better able to capture the variability and peak values of the storm surge.
Angélique Melet, Roderik van de Wal, Angel Amores, Arne Arns, Alisée A. Chaigneau, Irina Dinu, Ivan D. Haigh, Tim H. J. Hermans, Piero Lionello, Marta Marcos, H. E. Markus Meier, Benoit Meyssignac, Matthew D. Palmer, Ronja Reese, Matthew J. R. Simpson, and Aimée B. A. Slangen
State Planet, 3-slre1, 4, https://doi.org/10.5194/sp-3-slre1-4-2024, https://doi.org/10.5194/sp-3-slre1-4-2024, 2024
Short summary
Short summary
The EU Knowledge Hub on Sea Level Rise’s Assessment Report strives to synthesize the current scientific knowledge on sea level rise and its impacts across local, national, and EU scales to support evidence-based policy and decision-making, primarily targeting coastal areas. This paper complements IPCC reports by documenting the state of knowledge of observed and 21st century projected changes in mean and extreme sea levels with more regional information for EU seas as scoped with stakeholders.
Roderik van de Wal, Angélique Melet, Debora Bellafiore, Paula Camus, Christian Ferrarin, Gualbert Oude Essink, Ivan D. Haigh, Piero Lionello, Arjen Luijendijk, Alexandra Toimil, Joanna Staneva, and Michalis Vousdoukas
State Planet, 3-slre1, 5, https://doi.org/10.5194/sp-3-slre1-5-2024, https://doi.org/10.5194/sp-3-slre1-5-2024, 2024
Short summary
Short summary
Sea level rise has major impacts in Europe, which vary from place to place and in time, depending on the source of the impacts. Flooding, erosion, and saltwater intrusion lead, via different pathways, to various consequences for coastal regions across Europe. This causes damage to assets, the environment, and people for all three categories of impacts discussed in this paper. The paper provides an overview of the various impacts in Europe.
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.
Gwendoline Ducros, Timothy Tiggeloven, Lin Ma, Anne Sophie Daloz, Nina Schuhen, and Marleen C. de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2024-3158, https://doi.org/10.5194/egusphere-2024-3158, 2024
Short summary
Short summary
Our study finds that heatwave, drought and wildfire events occurring simultaneously in Scandinavia are pronounced in the summer months; and the heat-drought 2018 event led to a drop in gross domestic product, affecting agriculture and forestry imports, further impacting Europe’s trade balance. This research shows the importance of ripple effects of multi-hazard, and that forest management and adaptation measures are vital to reducing the risks of heat-related multi-hazards in vulnerable areas.
Lucas Terlinden-Ruhl, Anaïs Couasnon, Dirk Eilander, Gijs G. Hendrickx, Patricia Mares-Nasarre, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-196, https://doi.org/10.5194/nhess-2024-196, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study develops a conceptual framework that uses active learning to accelerate compound flood risk assessments. A case study of Charleston County shows that the framework achieves faster and more accurate risk quantifications compared to the state-of-the-art. This win-win allows for increasing the number of flooding parameters, which results in an 11.6 % difference in the expected annual damages. Therefore, this framework allows for more comprehensive compound flood risk assessments.
Jun Yu Puah, Ivan D. Haigh, David Lallemant, Kyle Morgan, Dongju Peng, Masashi Watanabe, and Adam D. Switzer
Ocean Sci., 20, 1229–1246, https://doi.org/10.5194/os-20-1229-2024, https://doi.org/10.5194/os-20-1229-2024, 2024
Short summary
Short summary
Coastal currents have wide implications for port activities, transport of sediments, and coral reef ecosystems; thus a deeper understanding of their characteristics is needed. We collected data on current velocities for a year using current meters at shallow waters in Singapore. The strength of the currents is primarily affected by tides and winds and generally increases during the monsoon seasons across various frequencies.
Christopher J. White, Mohammed Sarfaraz Gani Adnan, Marcello Arosio, Stephanie Buller, YoungHwa Cha, Roxana Ciurean, Julia M. Crummy, Melanie Duncan, Joel Gill, Claire Kennedy, Elisa Nobile, Lara Smale, and Philip J. Ward
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-178, https://doi.org/10.5194/nhess-2024-178, 2024
Preprint under review for NHESS
Short summary
Short summary
Indicators contain observable and measurable characteristics to understand the state of a concept or phenomenon and/or monitor it over time. There have been limited efforts to understand how indicators are being used in multi-hazard and multi-risk contexts. We find most of existing indicators do not include the interactions between hazards or risks. We propose 12 recommendations to enable the development and uptake of multi-hazard and multi-risk indicators.
Nicole van Maanen, Joël J.-F. G. De Plaen, Timothy Tiggeloven, Maria Luisa Colmenares, Philip J. Ward, Paolo Scussolini, and Elco Koks
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-137, https://doi.org/10.5194/nhess-2024-137, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Understanding coastal flood protection is vital for assessing risks from natural disasters and climate change. However, current global data on coastal flood protection is limited and based on simplified assumptions, leading to potential uncertainties in risk estimates. As a step in this direction, we propose a comprehensive dataset, COASTPROS-EU, which compiles coastal flood protection standards in Europe.
Lou Brett, Christopher J. White, Daniela I.V. Domeisen, Bart van den Hurk, Philip Ward, and Jakob Zscheischler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-182, https://doi.org/10.5194/nhess-2024-182, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
Compound events, where multiple weather or climate hazards occur together, pose significant risks to both society and the environment. These events, like simultaneous wind and rain, can have more severe impacts than single hazards. Our review of compound event research from 2012–2022 reveals a rise in studies, especially on events that occur concurrently, hot and dry events and compounding flooding. The review also highlights opportunities for research in the coming years.
Sönke Dangendorf, Qiang Sun, Thomas Wahl, Philip Thompson, Jerry X. Mitrovica, and Ben Hamlington
Earth Syst. Sci. Data, 16, 3471–3494, https://doi.org/10.5194/essd-16-3471-2024, https://doi.org/10.5194/essd-16-3471-2024, 2024
Short summary
Short summary
Sea-level information from the global ocean is sparse in time and space, with comprehensive data being limited to the period since 2005. Here we provide a novel reconstruction of sea level and its contributing causes, as determined by a Kalman smoother approach applied to tide gauge records over the period 1900–2021. The new reconstruction shows a continuing acceleration in global mean sea-level rise since 1970 that is dominated by melting land ice. Contributors vary significantly by region.
Wiebke S. Jäger, Marleen C. de Ruiter, Timothy Tiggeloven, and Philip J. Ward
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-134, https://doi.org/10.5194/nhess-2024-134, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
Multiple hazards, occurring at the same time or shortly after one another, can have more extreme impacts than single hazards. We examined the disaster records in the global emergency events database EM-DAT to better understand this phenomenon. We developed a method to identify such multi-hazards and analyzed their reported impacts using statistics. Multi-hazards have accounted for a disproportionate amount of the overall impacts, but there are different patterns in which the impacts compound.
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
Short summary
Short summary
This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates
Nat. Hazards Earth Syst. Sci., 24, 2403–2423, https://doi.org/10.5194/nhess-24-2403-2024, https://doi.org/10.5194/nhess-24-2403-2024, 2024
Short summary
Short summary
Coastal areas are at risk of flooding from rising sea levels and extreme weather events. This study applies a new approach to estimating the likelihood of coastal flooding around the world. The method uses data from observations and computer models to create a detailed map of where these coastal floods might occur. The approach can predict flooding in areas for which there are few or no data available. The results can be used to help prepare for and prevent this type of flooding.
Hung Nghia Nguyen, Quan Quan Le, Dung Viet Nguyen, Tan Hong Cao, Toan Quang To, Hai Do Dac, Melissa Wood, and Ivan D. Haigh
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-107, https://doi.org/10.5194/nhess-2024-107, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
The paper focuses on inundation process in a highest climate vulnerability area of the Mekong Delta, main drivers and future impacts, this is importance alert to decision makers and stakeholder for investment of infrastructure, adaptation approaches and mitigating impacts.
Ziyu Chen, Philip Orton, James Booth, Thomas Wahl, Arthur DeGaetano, Joel Kaatz, and Radley Horton
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-135, https://doi.org/10.5194/hess-2024-135, 2024
Preprint under review for HESS
Short summary
Short summary
Urban flooding can be driven by rain and storm surge or the combination of the two, which is called compound flooding. In this study we analyzed hourly historical rain and surge data for New York City to provide a more detailed statistical analysis than prior studies of this topic. The analyses reveal that tropical cyclones (e.g. hurricanes) have potential for causing more extreme compound floods than other storms, while extratropical cyclones cause more frequent, lesser compound events.
Irene Benito, Jeroen C. J. H. Aerts, Philip J. Ward, Dirk Eilander, and Sanne Muis
EGUsphere, https://doi.org/10.5194/egusphere-2024-1354, https://doi.org/10.5194/egusphere-2024-1354, 2024
Short summary
Short summary
Global flood models are key for mitigating coastal flooding impacts, yet they still have limitations to provide actionable insights locally. We present a multiscale framework that couples dynamic water level and flood models, and bridges between fully global and local modelling approaches. We apply it to three storms to present the merits of a multiscale approach. Our findings reveal that the importance of model refinements varies based on the study area characteristics and the storm’s nature.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
Short summary
Short summary
We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Eric Mortensen, Timothy Tiggeloven, Toon Haer, Bas van Bemmel, Dewi Le Bars, Sanne Muis, Dirk Eilander, Frederiek Sperna Weiland, Arno Bouwman, Willem Ligtvoet, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 24, 1381–1400, https://doi.org/10.5194/nhess-24-1381-2024, https://doi.org/10.5194/nhess-24-1381-2024, 2024
Short summary
Short summary
Current levels of coastal flood risk are projected to increase in coming decades due to various reasons, e.g. sea-level rise, land subsidence, and coastal urbanization: action is needed to minimize this future risk. We evaluate dykes and coastal levees, foreshore vegetation, zoning restrictions, and dry-proofing on a global scale to estimate what levels of risk reductions are possible. We demonstrate that there are several potential adaptation pathways forward for certain areas of the world.
Simon Treu, Sanne Muis, Sönke Dangendorf, Thomas Wahl, Julius Oelsmann, Stefanie Heinicke, Katja Frieler, and Matthias Mengel
Earth Syst. Sci. Data, 16, 1121–1136, https://doi.org/10.5194/essd-16-1121-2024, https://doi.org/10.5194/essd-16-1121-2024, 2024
Short summary
Short summary
This article describes a reconstruction of monthly coastal water levels from 1900–2015 and hourly data from 1979–2015, both with and without long-term sea level rise. The dataset is based on a combination of three datasets that are focused on different aspects of coastal water levels. Comparison with tide gauge records shows that this combination brings reconstructions closer to the observations compared to the individual datasets.
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.
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.
Sophie Kaashoek, Žiga Malek, Nadia Bloemendaal, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-182, https://doi.org/10.5194/nhess-2023-182, 2023
Revised manuscript accepted for NHESS
Short summary
Short summary
Tropical storms are expected to get stronger all over the world, and this will have a big impact on people, buildings, and important activities like growing bananas. Already, in different parts of the world, banana farms are being hurt by these storms, which makes banana prices go up and affects the people who grow them. We're not sure how these storms will affect bananas everywhere in the future. We studied what happened to banana farms during storms in different parts of the world.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, Joël J.-M. Hirschi, Robert J. Nicholls, and Nadia Bloemendaal
Nat. Hazards Earth Syst. Sci., 23, 2475–2504, https://doi.org/10.5194/nhess-23-2475-2023, https://doi.org/10.5194/nhess-23-2475-2023, 2023
Short summary
Short summary
We used a novel database of simulated tropical cyclone tracks to explore whether typhoon-induced storm surges present a future flood risk to low-lying coastal communities around the South China Sea. We found that future climate change is likely to change tropical cyclone behaviour to an extent that this increases the severity and frequency of storm surges to Vietnam, southern China, and Thailand. Consequently, coastal flood defences need to be reviewed for resilience against this future hazard.
Dirk Eilander, Anaïs Couasnon, Frederiek C. Sperna Weiland, Willem Ligtvoet, Arno Bouwman, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 2251–2272, https://doi.org/10.5194/nhess-23-2251-2023, https://doi.org/10.5194/nhess-23-2251-2023, 2023
Short summary
Short summary
This study presents a framework for assessing compound flood risk using hydrodynamic, impact, and statistical modeling. A pilot in Mozambique shows the importance of accounting for compound events in risk assessments. We also show how the framework can be used to assess the effectiveness of different risk reduction measures. As the framework is based on global datasets and is largely automated, it can easily be applied in other areas for first-order assessments of compound flood risk.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
Short summary
Short summary
A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Job C. M. Dullaart, Sanne Muis, Hans de Moel, Philip J. Ward, Dirk Eilander, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 23, 1847–1862, https://doi.org/10.5194/nhess-23-1847-2023, https://doi.org/10.5194/nhess-23-1847-2023, 2023
Short summary
Short summary
Coastal flooding is driven by storm surges and high tides and can be devastating. To gain an understanding of the threat posed by coastal flooding and to identify areas that are especially at risk, now and in the future, it is crucial to accurately model coastal inundation and assess the coastal flood hazard. Here, we present a global dataset with hydrographs that represent the typical evolution of an extreme sea level. These can be used to model coastal inundation more accurately.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
Short summary
Short summary
As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
Short summary
Short summary
This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Ed Hawkins, Philip Brohan, Samantha N. Burgess, Stephen Burt, Gilbert P. Compo, Suzanne L. Gray, Ivan D. Haigh, Hans Hersbach, Kiki Kuijjer, Oscar Martínez-Alvarado, Chesley McColl, Andrew P. Schurer, Laura Slivinski, and Joanne Williams
Nat. Hazards Earth Syst. Sci., 23, 1465–1482, https://doi.org/10.5194/nhess-23-1465-2023, https://doi.org/10.5194/nhess-23-1465-2023, 2023
Short summary
Short summary
We examine a severe windstorm that occurred in February 1903 and caused significant damage in the UK and Ireland. Using newly digitized weather observations from the time of the storm, combined with a modern weather forecast model, allows us to determine why this storm caused so much damage. We demonstrate that the event is one of the most severe windstorms to affect this region since detailed records began. The approach establishes a new tool to improve assessments of risk from extreme weather.
Paul D. Bates, James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith
Nat. Hazards Earth Syst. Sci., 23, 891–908, https://doi.org/10.5194/nhess-23-891-2023, https://doi.org/10.5194/nhess-23-891-2023, 2023
Short summary
Short summary
We present and validate a model that simulates current and future flood risk for the UK at high resolution (~ 20–25 m). We show that UK flood losses were ~ 6 % greater in the climate of 2020 compared to recent historical values. The UK can keep any future increase to ~ 8 % if all countries implement their COP26 pledges and net-zero ambitions in full. However, if only the COP26 pledges are fulfilled, then UK flood losses increase by ~ 23 %; and potentially by ~ 37 % in a worst-case scenario.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
Short summary
Short summary
In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Yinxue Liu, Paul D. Bates, and Jeffery C. Neal
Nat. Hazards Earth Syst. Sci., 23, 375–391, https://doi.org/10.5194/nhess-23-375-2023, https://doi.org/10.5194/nhess-23-375-2023, 2023
Short summary
Short summary
In this paper, we test two approaches for removing buildings and other above-ground objects from a state-of-the-art satellite photogrammetry topography product, ArcticDEM. Our best technique gives a 70 % reduction in vertical error, with an average difference of 1.02 m from a benchmark lidar for the city of Helsinki, Finland. When used in a simulation of rainfall-driven flooding, the bare-earth version of ArcticDEM yields a significant improvement in predicted inundation extent and water depth.
Paolo Scussolini, Job Dullaart, Sanne Muis, Alessio Rovere, Pepijn Bakker, Dim Coumou, Hans Renssen, Philip J. Ward, and Jeroen C. J. H. Aerts
Clim. Past, 19, 141–157, https://doi.org/10.5194/cp-19-141-2023, https://doi.org/10.5194/cp-19-141-2023, 2023
Short summary
Short summary
We reconstruct sea level extremes due to storm surges in a past warmer climate. We employ a novel combination of paleoclimate modeling and global ocean hydrodynamic modeling. We find that during the Last Interglacial, about 127 000 years ago, seasonal sea level extremes were indeed significantly different – higher or lower – on long stretches of the global coast. These changes are associated with different patterns of atmospheric storminess linked with meridional shifts in wind bands.
Weihua Zhu, Kai Liu, Ming Wang, Philip J. Ward, and Elco E. Koks
Nat. Hazards Earth Syst. Sci., 22, 1519–1540, https://doi.org/10.5194/nhess-22-1519-2022, https://doi.org/10.5194/nhess-22-1519-2022, 2022
Short summary
Short summary
We present a simulation framework to analyse the system vulnerability and risk of the Chinese railway system to floods. To do so, we develop a method for generating flood events at both the national and river basin scale. Results show flood system vulnerability and risk of the railway system are spatially heterogeneous. The event-based approach shows how we can identify critical hotspots, taking the first steps in developing climate-resilient infrastructure.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
Short summary
Short summary
The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Katherine L. Towey, James F. Booth, Alejandra Rodriguez Enriquez, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 22, 1287–1300, https://doi.org/10.5194/nhess-22-1287-2022, https://doi.org/10.5194/nhess-22-1287-2022, 2022
Short summary
Short summary
Coastal flooding due to storm surge from tropical cyclones is a significant hazard. The influence of tropical cyclone characteristics, including its proximity, intensity, path angle, and speed, on the magnitude of storm surge is examined along the eastern United States. No individual characteristic was found to be strongly related to how much surge occurred at a site, though there is an increased likelihood of high surge occurring when tropical cyclones are both strong and close to a location.
Ahmed A. Nasr, Thomas Wahl, Md Mamunur Rashid, Paula Camus, and Ivan D. Haigh
Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, https://doi.org/10.5194/hess-25-6203-2021, 2021
Short summary
Short summary
We analyse dependences between different flooding drivers around the USA coastline, where the Gulf of Mexico and the southeastern and southwestern coasts are regions of high dependence between flooding drivers. Dependence is higher during the tropical season in the Gulf and at some locations on the East Coast but higher during the extratropical season on the West Coast. The analysis gives new insights on locations, driver combinations, and the time of the year when compound flooding is likely.
Gang Zhao, Paul Bates, Jeffrey Neal, and Bo Pang
Hydrol. Earth Syst. Sci., 25, 5981–5999, https://doi.org/10.5194/hess-25-5981-2021, https://doi.org/10.5194/hess-25-5981-2021, 2021
Short summary
Short summary
Design flood estimation is a fundamental task in hydrology. We propose a machine- learning-based approach to estimate design floods anywhere on the global river network. This approach shows considerable improvement over the index-flood-based method, and the average bias in estimation is less than 18 % for 10-, 20-, 50- and 100-year design floods. This approach is a valid method to estimate design floods globally, improving our prediction of flood hazard, especially in ungauged areas.
Julia Rulent, Lucy M. Bricheno, J. A. Mattias Green, Ivan D. Haigh, and Huw Lewis
Nat. Hazards Earth Syst. Sci., 21, 3339–3351, https://doi.org/10.5194/nhess-21-3339-2021, https://doi.org/10.5194/nhess-21-3339-2021, 2021
Short summary
Short summary
High coastal total water levels (TWLs) can lead to flooding and hazardous conditions for coastal communities and environment. In this research we are using numerical models to study the interactions between the three main components of the TWL (waves, tides, and surges) on UK and Irish coasts during winter 2013/14. The main finding of this research is that extreme waves and surges can indeed happen together, even at high tide, but they often occurred simultaneously 2–3 h before high tide.
Lucas Wouters, Anaïs Couasnon, Marleen C. de Ruiter, Marc J. C. van den Homberg, Aklilu Teklesadik, and Hans de Moel
Nat. Hazards Earth Syst. Sci., 21, 3199–3218, https://doi.org/10.5194/nhess-21-3199-2021, https://doi.org/10.5194/nhess-21-3199-2021, 2021
Short summary
Short summary
This research introduces a novel approach to estimate flood damage in Malawi by applying a machine learning model to UAV imagery. We think that the development of such a model is an essential step to enable the swift allocation of resources for recovery by humanitarian decision-makers. By comparing this method (EUR 10 140) to a conventional land-use-based approach (EUR 15 782) for a specific flood event, recommendations are made for future assessments.
Samuel Tiéfolo Diabaté, Didier Swingedouw, Joël Jean-Marie Hirschi, Aurélie Duchez, Philip J. Leadbitter, Ivan D. Haigh, and Gerard D. McCarthy
Ocean Sci., 17, 1449–1471, https://doi.org/10.5194/os-17-1449-2021, https://doi.org/10.5194/os-17-1449-2021, 2021
Short summary
Short summary
The Gulf Stream and the Kuroshio are major currents of the North Atlantic and North Pacific, respectively. They transport warm water northward and are key components of the Earth climate system. For this study, we looked at how they affect the sea level of the coasts of Japan, the USA and Canada. We found that the inshore sea level
co-varies with the north-to-south shifts of the Gulf Stream and Kuroshio. In the paper, we discuss the physical mechanisms that could explain the agreement.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
Short summary
Short summary
Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Georg Umgiesser, Marco Bajo, Christian Ferrarin, Andrea Cucco, Piero Lionello, Davide Zanchettin, Alvise Papa, Alessandro Tosoni, Maurizio Ferla, Elisa Coraci, Sara Morucci, Franco Crosato, Andrea Bonometto, Andrea Valentini, Mirko Orlić, Ivan D. Haigh, Jacob Woge Nielsen, Xavier Bertin, André Bustorff Fortunato, Begoña Pérez Gómez, Enrique Alvarez Fanjul, Denis Paradis, Didier Jourdan, Audrey Pasquet, Baptiste Mourre, Joaquín Tintoré, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2679–2704, https://doi.org/10.5194/nhess-21-2679-2021, https://doi.org/10.5194/nhess-21-2679-2021, 2021
Short summary
Short summary
The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review of storm surge forecasting, starting from examples in Europe and focusing on the Adriatic Sea and the Lagoon of Venice. We discuss the physics of storm surge, as well as the particular aspects of Venice and new techniques in storm surge modeling. We also give recommendations on what a future forecasting system should look like.
Marleen Carolijn de Ruiter, Anaïs Couasnon, and Philip James Ward
Geosci. Commun., 4, 383–397, https://doi.org/10.5194/gc-4-383-2021, https://doi.org/10.5194/gc-4-383-2021, 2021
Short summary
Short summary
Many countries can get hit by different hazards, such as earthquakes and floods. Generally, measures and policies are aimed at decreasing the potential damages of one particular hazard type despite their potential of having unwanted effects on other hazard types. We designed a serious game that helps professionals to improve their understanding of these potential negative effects of measures and policies that reduce the impacts of disasters across many different hazard types.
Jiayi Fang, Thomas Wahl, Jian Fang, Xun Sun, Feng Kong, and Min Liu
Hydrol. Earth Syst. Sci., 25, 4403–4416, https://doi.org/10.5194/hess-25-4403-2021, https://doi.org/10.5194/hess-25-4403-2021, 2021
Short summary
Short summary
A comprehensive assessment of compound flooding potential is missing for China. We investigate dependence, drivers, and impacts of storm surge and precipitation for coastal China. Strong dependence exists between driver combinations, with variations of seasons and thresholds. Sea level rise escalates compound flood potential. Meteorology patterns are pronounced for low and high compound flood potential. Joint impacts from surge and precipitation were much higher than from each individually.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
Short summary
Short summary
We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
Paula Camus, Ivan D. Haigh, Ahmed A. Nasr, Thomas Wahl, Stephen E. Darby, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2021–2040, https://doi.org/10.5194/nhess-21-2021-2021, https://doi.org/10.5194/nhess-21-2021-2021, 2021
Short summary
Short summary
In coastal regions, floods can arise through concurrent drivers, such as precipitation, river discharge, storm surge, and waves, which exacerbate the impact. In this study, we identify hotspots of compound flooding along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea. This regional assessment can be considered a screening tool for coastal management that provides information about which areas are more predisposed to experience compound flooding.
James Shaw, Georges Kesserwani, Jeffrey Neal, Paul Bates, and Mohammad Kazem Sharifian
Geosci. Model Dev., 14, 3577–3602, https://doi.org/10.5194/gmd-14-3577-2021, https://doi.org/10.5194/gmd-14-3577-2021, 2021
Short summary
Short summary
LISFLOOD-FP has been extended with new shallow-water solvers – DG2 and FV1 – for modelling all types of slow- or fast-moving waves over any smooth or rough surface. Using GPU parallelisation, FV1 is faster than the simpler ACC solver on grids with millions of elements. The DG2 solver is notably effective on coarse grids where river channels are hard to capture, improving predicted river levels and flood water depths. This marks a new step towards real-world DG2 flood inundation modelling.
Yasser Hamdi, Ivan D. Haigh, Sylvie Parey, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 21, 1461–1465, https://doi.org/10.5194/nhess-21-1461-2021, https://doi.org/10.5194/nhess-21-1461-2021, 2021
Jerom P. M. Aerts, Steffi Uhlemann-Elmer, Dirk Eilander, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 20, 3245–3260, https://doi.org/10.5194/nhess-20-3245-2020, https://doi.org/10.5194/nhess-20-3245-2020, 2020
Short summary
Short summary
We compare and analyse flood hazard maps from eight global flood models that represent the current state of the global flood modelling community. We apply our comparison to China as a case study, and for the first time, we include industry models, pluvial flooding, and flood protection standards. We find substantial variability between the flood hazard maps in the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods and in expected annual exposed GDP.
Robert Jane, Luis Cadavid, Jayantha Obeysekera, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 20, 2681–2699, https://doi.org/10.5194/nhess-20-2681-2020, https://doi.org/10.5194/nhess-20-2681-2020, 2020
Short summary
Short summary
Full dependence is assumed between drivers in flood protection assessments of coastal water control structures in south Florida. A 2-D analysis of rainfall and coastal water level showed that the magnitude of the conservative assumption in the original design is highly sensitive to the regional sea level rise projection considered. The vine copula and HT04 model outperformed five higher-dimensional copulas in capturing the dependence between rainfall, coastal water level, and groundwater level.
Jens A. de Bruijn, James E. Daniell, Antonios Pomonis, Rashmin Gunasekera, Joshua Macabuag, Marleen C. de Ruiter, Siem Jan Koopman, Nadia Bloemendaal, Hans de Moel, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-282, https://doi.org/10.5194/nhess-2020-282, 2020
Revised manuscript not accepted
Short summary
Short summary
Following hurricanes and other natural hazards, it is important to quickly estimate the damage caused by the hazard such that recovery aid can be granted from organizations such as the European Union and the World Bank. To do so, it is important to estimate the vulnerability of buildings to the hazards. In this research, we use post-disaster observations from social media to improve these vulnerability assessments and show its application in the Bahamas following Hurricane Dorian.
Paolo De Luca, Gabriele Messori, Davide Faranda, Philip J. Ward, and Dim Coumou
Earth Syst. Dynam., 11, 793–805, https://doi.org/10.5194/esd-11-793-2020, https://doi.org/10.5194/esd-11-793-2020, 2020
Short summary
Short summary
In this paper we quantify Mediterranean compound temperature and precipitation dynamical extremes (CDEs) over the 1979–2018 period. The strength of the temperature–precipitation coupling during summer increased and is driven by surface warming. We also link the CDEs to compound hot–dry and cold–wet events during summer and winter respectively.
Thomas O'Shea, Paul Bates, and Jeffrey Neal
Nat. Hazards Earth Syst. Sci., 20, 2281–2305, https://doi.org/10.5194/nhess-20-2281-2020, https://doi.org/10.5194/nhess-20-2281-2020, 2020
Short summary
Short summary
Outlined here is a multi-disciplinary framework for analysing and evaluating the nature of vulnerability to, and capacity for, flood hazard within a complex urban society. It provides scope beyond the current, reified, descriptors of
flood riskand models the role of affected individuals within flooded areas. Using agent-based modelling coupled with the LISFLOOD-FP hydrodynamic model, potentially influential behaviours that give rise to the flood hazard system are identified and discussed.
Philip J. Ward, Veit Blauhut, Nadia Bloemendaal, James E. Daniell, Marleen C. de Ruiter, Melanie J. Duncan, Robert Emberson, Susanna F. Jenkins, Dalia Kirschbaum, Michael Kunz, Susanna Mohr, Sanne Muis, Graeme A. Riddell, Andreas Schäfer, Thomas Stanley, Ted I. E. Veldkamp, and Hessel C. Winsemius
Nat. Hazards Earth Syst. Sci., 20, 1069–1096, https://doi.org/10.5194/nhess-20-1069-2020, https://doi.org/10.5194/nhess-20-1069-2020, 2020
Short summary
Short summary
We review the scientific literature on natural hazard risk assessments at the global scale. In doing so, we examine similarities and differences between the approaches taken across the different hazards and identify potential ways in which different hazard communities can learn from each other. Finally, we discuss opportunities for learning from methods and approaches being developed and applied to assess natural hazard risks at more continental or regional scales.
Timothy Tiggeloven, Hans de Moel, Hessel C. Winsemius, Dirk Eilander, Gilles Erkens, Eskedar Gebremedhin, Andres Diaz Loaiza, Samantha Kuzma, Tianyi Luo, Charles Iceland, Arno Bouwman, Jolien van Huijstee, Willem Ligtvoet, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 20, 1025–1044, https://doi.org/10.5194/nhess-20-1025-2020, https://doi.org/10.5194/nhess-20-1025-2020, 2020
Short summary
Short summary
We present a framework to evaluate the benefits and costs of coastal adaptation through dikes to reduce future flood risk. If no adaptation takes place, we find that global coastal flood risk increases 150-fold by 2080, with sea-level rise contributing the most. Moreover, 15 countries account for 90 % of this increase; that adaptation shows high potential to cost-effectively reduce flood risk. The results will be integrated into the Aqueduct Global Flood Analyzer web tool.
Scott A. Stephens, Robert G. Bell, and Ivan D. Haigh
Nat. Hazards Earth Syst. Sci., 20, 783–796, https://doi.org/10.5194/nhess-20-783-2020, https://doi.org/10.5194/nhess-20-783-2020, 2020
Short summary
Short summary
Extreme sea levels in New Zealand occur in nearby places and at similar times, which means that flooding impacts and losses may be linked in space and time. The most extreme sea levels depend on storms coinciding with very high tides because storm surges are relatively small in New Zealand. The type of storm weather system influences where the extreme sea levels occur, and the annual timing is influenced by the low-amplitude (~10 cm) annual sea-level cycle.
Anaïs Couasnon, Dirk Eilander, Sanne Muis, Ted I. E. Veldkamp, Ivan D. Haigh, Thomas Wahl, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 20, 489–504, https://doi.org/10.5194/nhess-20-489-2020, https://doi.org/10.5194/nhess-20-489-2020, 2020
Short summary
Short summary
When a high river discharge coincides with a high storm surge level, this can exarcebate flood level, depth, and duration, resulting in a so-called compound flood event. These events are not currently included in global flood models. In this research, we analyse the timing and correlation between modelled discharge and storm surge level time series in deltas and estuaries. Our results provide a first indication of regions along the global coastline with a high compound flooding potential.
Maria Cortès, Marco Turco, Philip Ward, Josep A. Sánchez-Espigares, Lorenzo Alfieri, and Maria Carmen Llasat
Nat. Hazards Earth Syst. Sci., 19, 2855–2877, https://doi.org/10.5194/nhess-19-2855-2019, https://doi.org/10.5194/nhess-19-2855-2019, 2019
Short summary
Short summary
The main objective of this paper is to estimate changes in the probability of damaging flood events with global warming of 1.5, 2 and 3 °C above pre-industrial levels and taking into account different socioeconomic scenarios in two western Mediterranean regions. The results show a general increase in the probability of a damaging event, with larger increments when higher warming is considered. Moreover, this increase is higher when both climate and population change are included.
Johanna Englhardt, Hans de Moel, Charles K. Huyck, Marleen C. de Ruiter, Jeroen C. J. H. Aerts, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 19, 1703–1722, https://doi.org/10.5194/nhess-19-1703-2019, https://doi.org/10.5194/nhess-19-1703-2019, 2019
Short summary
Short summary
Large-scale risk assessments can be improved by a more direct relation between the type of exposed buildings and their flood impact. Compared to the common land-use-based approach, this model reflects heterogeneous structures and defines building-material-based vulnerability classes. This approach is particularly interesting for areas with large variations of building types, such as developing countries and large scales, and enables vulnerability comparison across different natural disasters.
Jannis M. Hoch, Dirk Eilander, Hiroaki Ikeuchi, Fedor Baart, and Hessel C. Winsemius
Nat. Hazards Earth Syst. Sci., 19, 1723–1735, https://doi.org/10.5194/nhess-19-1723-2019, https://doi.org/10.5194/nhess-19-1723-2019, 2019
Short summary
Short summary
Flood events are often complex in their origin and dynamics. The choice of computer model to simulate can hence determine which level of complexity can be represented. We here compare different models varying in complexity (hydrology with routing, 1-D routing, 1D/2D hydrodynamics) and assess how model choice influences the accuracy of results. This was achieved by using GLOFRIM, a model coupling framework. Results show that accuracy depends on the model choice and the output variable considered.
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.
Gemma Coxon, Jim Freer, Rosanna Lane, Toby Dunne, Wouter J. M. Knoben, Nicholas J. K. Howden, Niall Quinn, Thorsten Wagener, and Ross Woods
Geosci. Model Dev., 12, 2285–2306, https://doi.org/10.5194/gmd-12-2285-2019, https://doi.org/10.5194/gmd-12-2285-2019, 2019
Short summary
Short summary
DECIPHeR (Dynamic fluxEs and ConnectIvity for Predictions of Hydrology) is a new modelling framework that can be applied from small catchment to continental scales for complex river basins. This paper describes the modelling framework and its key components and demonstrates the model’s ability to be applied across a large model domain. This work highlights the potential for catchment- to continental-scale predictions of streamflow to support robust environmental management and policy decisions.
Shiqiang Du, Xiaotao Cheng, Qingxu Huang, Ruishan Chen, Philip J. Ward, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 19, 715–719, https://doi.org/10.5194/nhess-19-715-2019, https://doi.org/10.5194/nhess-19-715-2019, 2019
Short summary
Short summary
A mega-flood in 1998 caused tremendous losses in China and triggered major policy adjustments in flood-risk management. This paper rethinks these policy adjustments and discusses how China should adapt to newly emerging flood challenges. We suggest that China needs novel flood-risk management approaches to address the new challenges from rapid urbanization and climate change. These include risk-based urban planning and a coordinated water governance system.
Giuliano Di Baldassarre, Heidi Kreibich, Sergiy Vorogushyn, Jeroen Aerts, Karsten Arnbjerg-Nielsen, Marlies Barendrecht, Paul Bates, Marco Borga, Wouter Botzen, Philip Bubeck, Bruna De Marchi, Carmen Llasat, Maurizio Mazzoleni, Daniela Molinari, Elena Mondino, Johanna Mård, Olga Petrucci, Anna Scolobig, Alberto Viglione, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 5629–5637, https://doi.org/10.5194/hess-22-5629-2018, https://doi.org/10.5194/hess-22-5629-2018, 2018
Short summary
Short summary
One common approach to cope with floods is the implementation of structural flood protection measures, such as levees. Numerous scholars have problematized this approach and shown that increasing levels of flood protection can generate a false sense of security and attract more people to the risky areas. We briefly review the literature on this topic and then propose a research agenda to explore the unintended consequences of structural flood protection.
Anouk I. Gevaert, Ted I. E. Veldkamp, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 4649–4665, https://doi.org/10.5194/hess-22-4649-2018, https://doi.org/10.5194/hess-22-4649-2018, 2018
Short summary
Short summary
Drought is a natural hazard that has severe environmental and socioeconomic impacts around the globe. Here, we quantified the time taken for drought to propagate from precipitation droughts to soil moisture and streamflow droughts. Results show that propagation timescales are strongly related to climate type, with fast responses in tropical regions and slow responses in arid regions. Insight into the timescales of drought propagation globally may help improve seasonal drought forecasting.
Andreas Paul Zischg, Guido Felder, Rolf Weingartner, Niall Quinn, Gemma Coxon, Jeffrey Neal, Jim Freer, and Paul Bates
Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
Short summary
Short summary
We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.
Jannis M. Hoch, Jeffrey C. Neal, Fedor Baart, Rens van Beek, Hessel C. Winsemius, Paul D. Bates, and Marc F. P. Bierkens
Geosci. Model Dev., 10, 3913–3929, https://doi.org/10.5194/gmd-10-3913-2017, https://doi.org/10.5194/gmd-10-3913-2017, 2017
Short summary
Short summary
To improve flood hazard assessments, it is vital to model all relevant processes. We here present GLOFRIM, a framework for coupling hydrologic and hydrodynamic models to increase the number of physical processes represented in hazard computations. GLOFRIM is openly available, versatile, and extensible with more models. Results also underpin its added value for model benchmarking, showing that not only model forcing but also grid properties and the numerical scheme influence output accuracy.
Marleen C. de Ruiter, Philip J. Ward, James E. Daniell, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 17, 1231–1251, https://doi.org/10.5194/nhess-17-1231-2017, https://doi.org/10.5194/nhess-17-1231-2017, 2017
Short summary
Short summary
This study provides cross-discipline lessons for earthquake and flood vulnerability assessment methods by comparing indicators used in both fields. It appears that there is potential for improvement of these methods that can be obtained for both earthquake and flood vulnerability assessment indicators. This increased understanding is beneficial for both scientists as well as practitioners working with earthquake and/or flood vulnerability assessment methods.
Tom Brouwer, Dirk Eilander, Arnejan van Loenen, Martijn J. Booij, Kathelijne M. Wijnberg, Jan S. Verkade, and Jurjen Wagemaker
Nat. Hazards Earth Syst. Sci., 17, 735–747, https://doi.org/10.5194/nhess-17-735-2017, https://doi.org/10.5194/nhess-17-735-2017, 2017
Short summary
Short summary
The increasing number and severity of floods, driven by e.g. urbanization, subsidence and climate change, create a growing need for accurate and timely flood maps. At the same time social media is a source of much real-time data that is still largely untapped in flood disaster management. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.
Robert Marsh, Ivan D. Haigh, Stuart A. Cunningham, Mark E. Inall, Marie Porter, and Ben I. Moat
Ocean Sci., 13, 315–335, https://doi.org/10.5194/os-13-315-2017, https://doi.org/10.5194/os-13-315-2017, 2017
Short summary
Short summary
To the west of Britain and Ireland, a strong ocean current follows the steep slope that separates the deep Atlantic and the continental shelf. This “Slope Current” exerts an Atlantic influence on the North Sea and its ecosystems. Using a combination of computer modelling and archived data, we find that the Slope Current weakened over 1988–2007, reducing Atlantic influence on the North Sea, due to a combination of warming of the subpolar North Atlantic and weakening winds to the west of Scotland.
Melissa Wood, Renaud Hostache, Jeffrey Neal, Thorsten Wagener, Laura Giustarini, Marco Chini, Giovani Corato, Patrick Matgen, and Paul Bates
Hydrol. Earth Syst. Sci., 20, 4983–4997, https://doi.org/10.5194/hess-20-4983-2016, https://doi.org/10.5194/hess-20-4983-2016, 2016
Short summary
Short summary
We propose a methodology to calibrate the bankfull channel depth and roughness parameters in a 2-D hydraulic model using an archive of medium-resolution SAR satellite-derived flood extent maps. We used an identifiability methodology to locate the parameters and suggest the SAR images which could be optimally used for model calibration. We found that SAR images acquired around the flood peak provide best calibration potential for the depth parameter, improving when SAR images are combined.
Paolo Scussolini, Jeroen C. J. H. Aerts, Brenden Jongman, Laurens M. Bouwer, Hessel C. Winsemius, Hans de Moel, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 16, 1049–1061, https://doi.org/10.5194/nhess-16-1049-2016, https://doi.org/10.5194/nhess-16-1049-2016, 2016
Short summary
Short summary
Assessments of flood risk, on global to local scales, are becoming more urgent with ongoing climate change and with rapid socioeconomic developments. Such assessments need information about existing flood protection, still largely unavailable. Here we present the first open-source database of FLood PROtection Standards, FLOPROS, which enables more accurate modelling of flood risk. We also invite specialists to contribute new information to this evolving database.
Yus Budiyono, Jeroen C. J. H. Aerts, Daniel Tollenaar, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 16, 757–774, https://doi.org/10.5194/nhess-16-757-2016, https://doi.org/10.5194/nhess-16-757-2016, 2016
Short summary
Short summary
The paper describes a model framework for assessing flood risk in Jakarta under current and future scenarios (2030 and 2050) including climate change, sea level rise, land use change, and land subsidence. The results shows individual impact of future changes and serve as a basis to evaluate adaptation strategies in cities. They also show while the impacts of climate change alone on flood risk in Jakarta are highly uncertain, the combined impacts of all drivers reveal a strong increase in risk.
O. Q. Gutiérrez, F. Filipponi, A. Taramelli, E. Valentini, P. Camus, and F. J. Méndez
Ocean Sci., 12, 39–49, https://doi.org/10.5194/os-12-39-2016, https://doi.org/10.5194/os-12-39-2016, 2016
Short summary
Short summary
High-resolution wave hindcast has been performed for the N Adriatic Sea using a hybrid methodology, combining a regional wave hindcast database, wind reanalysis, satellite SAR wind fields and data mining techniques. Comparison with in situ instrumental data indicates the good quality of the downscaled waves; moreover, a good correlation was found on the downscaled waves forced with different wind fields. Results demonstrate how SAR wind fields can be successfully up-taken in wave downscaling.
D. Lee, P. Ward, and P. Block
Hydrol. Earth Syst. Sci., 19, 4689–4705, https://doi.org/10.5194/hess-19-4689-2015, https://doi.org/10.5194/hess-19-4689-2015, 2015
Short summary
Short summary
This paper presents a global approach to defining high-flow seasons by identifying temporal patterns of streamflow. Simulations of streamflow from the PCR-GLOBWB model are evaluated to define dominant and minor high-flow seasons globally, and verified with GRDC observations and flood records from Dartmouth Flood Observatory.
M. P. Wadey, J. M. Brown, I. D. Haigh, T. Dolphin, and P. Wisse
Nat. Hazards Earth Syst. Sci., 15, 2209–2225, https://doi.org/10.5194/nhess-15-2209-2015, https://doi.org/10.5194/nhess-15-2209-2015, 2015
T. I. E. Veldkamp, S. Eisner, Y. Wada, J. C. J. H. Aerts, and P. J. Ward
Hydrol. Earth Syst. Sci., 19, 4081–4098, https://doi.org/10.5194/hess-19-4081-2015, https://doi.org/10.5194/hess-19-4081-2015, 2015
Short summary
Short summary
Freshwater shortage is one of the most important risks, partially driven by climate variability. Here we present a first global scale sensitivity assessment of water scarcity events to El Niño-Southern Oscillation, the most dominant climate variability signal. Given the found correlations, covering a large share of the global land area, and seen the developments of water scarcity impacts under changing socioeconomic conditions, we show that there is large potential for ENSO-based risk reduction.
M. P. Wadey, I. D. Haigh, and J. M. Brown
Ocean Sci., 10, 1031–1045, https://doi.org/10.5194/os-10-1031-2014, https://doi.org/10.5194/os-10-1031-2014, 2014
B. Merz, J. Aerts, K. Arnbjerg-Nielsen, M. Baldi, A. Becker, A. Bichet, G. Blöschl, L. M. Bouwer, A. Brauer, F. Cioffi, J. M. Delgado, M. Gocht, F. Guzzetti, S. Harrigan, K. Hirschboeck, C. Kilsby, W. Kron, H.-H. Kwon, U. Lall, R. Merz, K. Nissen, P. Salvatti, T. Swierczynski, U. Ulbrich, A. Viglione, P. J. Ward, M. Weiler, B. Wilhelm, and M. Nied
Nat. Hazards Earth Syst. Sci., 14, 1921–1942, https://doi.org/10.5194/nhess-14-1921-2014, https://doi.org/10.5194/nhess-14-1921-2014, 2014
B. Jongman, E. E. Koks, T. G. Husby, and P. J. Ward
Nat. Hazards Earth Syst. Sci., 14, 1245–1255, https://doi.org/10.5194/nhess-14-1245-2014, https://doi.org/10.5194/nhess-14-1245-2014, 2014
P. J. Ward, S. Eisner, M. Flörke, M. D. Dettinger, and M. Kummu
Hydrol. Earth Syst. Sci., 18, 47–66, https://doi.org/10.5194/hess-18-47-2014, https://doi.org/10.5194/hess-18-47-2014, 2014
H. C. Winsemius, L. P. H. Van Beek, B. Jongman, P. J. Ward, and A. Bouwman
Hydrol. Earth Syst. Sci., 17, 1871–1892, https://doi.org/10.5194/hess-17-1871-2013, https://doi.org/10.5194/hess-17-1871-2013, 2013
B. Jongman, H. Kreibich, H. Apel, J. I. Barredo, P. D. Bates, L. Feyen, A. Gericke, J. Neal, J. C. J. H. Aerts, and P. J. Ward
Nat. Hazards Earth Syst. Sci., 12, 3733–3752, https://doi.org/10.5194/nhess-12-3733-2012, https://doi.org/10.5194/nhess-12-3733-2012, 2012
Related subject area
Sea, Ocean and Coastal Hazards
Tsunami detection methods for ocean-bottom pressure gauges
Using random forests to forecast daily extreme sea level occurrences at the Baltic Coast
Probabilistic tsunami hazard analysis of Batukaras, a tourism village in Indonesia
Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines
Changing sea level, changing shorelines: integration of remote-sensing observations at the Terschelling barrier island
Regional modelling of extreme sea levels induced by hurricanes
New insights into combined surfzone, embayment, and estuarine bathing hazards
Dynamic projections of extreme sea levels for western Europe based on ocean and wind-wave modelling
Brief communication: From modelling to reality – flood modelling gaps highlighted by a recent severe storm surge event along the German Baltic Sea coast
Inundation and evacuation of shoreline populations during landslide-triggered tsunamis: an integrated numerical and statistical hazard assessment
Untangling the Waves: Decomposing Extreme Sea Levels in a non-tidal basin, the Baltic Sea
Rapid simulation of wave runup on morphologically diverse, reef-lined coasts with the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process model
Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA)
A brief history of tsunamis in the Vanuatu Arc
Tsunami inundation and vulnerability analysis on the Makran coast, Pakistan
Influence of data source and copula statistics on estimates of compound flood extremes in a river mouth environment
Volcano tsunamis and their effects on moored vessel safety: the 2022 Tonga event
Modelling tsunami initial conditions due to rapid coseismic seafloor displacement: efficient numerical integration and a tool to build unit source databases
Estuarine hurricane wind can intensify surge-dominated extreme water level in shallow and converging coastal systems
Revisiting regression methods for estimating long-term trends in sea surface temperature
Global application of a regional frequency analysis to extreme sea levels
Tsunami hazard assessment in the South China Sea based on geodetic locking of the Manila subduction zone
The impact of long-term changes in ocean waves and storm surge on coastal shoreline change: a case study of Bass Strait and south-east Australia
Brief communication: Implications of outstanding solitons for the occurrence of rogue waves at two additional sites in the North Sea
A systemic and comprehensive assessment of coastal hazard changes: method and application to France and its overseas territories
Simulating sea level extremes from synthetic low-pressure systems
Nonlinear processes in tsunami simulations for the Peruvian coast with focus on Lima and Callao
Advancing nearshore and onshore tsunami hazard approximation with machine learning surrogates
The potential of global coastal flood risk reduction using various DRR measures
Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach
Nearshore tsunami amplitudes across the Maldives archipelago due to worst-case seismic scenarios in the Indian Ocean
Evidence of Middle Holocene landslide-generated tsunamis recorded in lake sediments from Saqqaq, West Greenland
Investigation of historical severe storms and storm tides in the German Bight with century reanalysis data
Proposal for a new meteotsunami intensity index
Total water levels along the South Atlantic Bight during three along-shelf propagating tropical cyclones: relative contributions of storm surge and wave runup
Hurricane Irma: an unprecedented event over the last 3700 years? Geomorphological changes and sedimentological record in Codrington Lagoon, Barbuda
Bayesian extreme value analysis of extreme sea levels along the German Baltic coast using historical information
Storm characteristics influence nitrogen removal in an urban estuarine environment
A new European coastal flood database for low–medium intensity events
Boulder transport and wave height of a seventeenth-century South China Sea tsunami on Penghu Islands, Taiwan
A wave-resolving modeling study of rip current variability, rip hazard, and swimmer escape strategies on an embayed beach
Human displacements from Tropical Cyclone Idai attributable to climate change
Three decades of coastal subsidence in the slow-moving Nice Côte d'Azur Airport area (France) revealed by InSAR (interferometric synthetic-aperture radar): insights into the deformation mechanism
Modelling extreme water levels using intertidal topography and bathymetry derived from multispectral satellite images
Regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast
Joint probability analysis of storm surges and waves caused by tropical cyclones for the estimation of protection standard: a case study on the eastern coast of the Leizhou Peninsula and the island of Hainan in China
Meteotsunami in the United Kingdom: the hidden hazard
Climate-induced storminess forces major increases in future storm surge hazard in the South China Sea region
Assessing Typhoon Soulik-induced morphodynamics over the Mokpo coastal region in South Korea based on a geospatial approach
Bayesian hierarchical modelling of sea-level extremes in the Finnish coastal region
Cesare Angeli, Alberto Armigliato, Martina Zanetti, Filippo Zaniboni, Fabrizio Romano, Hafize Başak Bayraktar, and Stefano Lorito
Nat. Hazards Earth Syst. Sci., 25, 1169–1185, https://doi.org/10.5194/nhess-25-1169-2025, https://doi.org/10.5194/nhess-25-1169-2025, 2025
Short summary
Short summary
To issue precise and timely tsunami alerts, detecting the propagating tsunami is fundamental. The most used instruments are pressure sensors positioned at the ocean bottom, called ocean-bottom pressure gauges (OBPGs). In this work, we study four different techniques that allow us to recognize a tsunami as soon as it is recorded by an OBPG and a methodology to calibrate them. The techniques are compared in terms of their ability to detect and characterize the tsunami wave in real time.
Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci., 25, 1139–1162, https://doi.org/10.5194/nhess-25-1139-2025, https://doi.org/10.5194/nhess-25-1139-2025, 2025
Short summary
Short summary
We designed a tool to predict the storm surges at the Baltic Sea coast with satisfactory predictability (80 % correct predictions), using lead times of a few days. The proportion of false warnings is typically as low as 10 % to 20 %. We were able to identify the relevant predictor regions and their patterns – such as low-pressure systems and strong winds. Due to its short computing time, the method can be used as a pre-warning system to trigger the application of more sophisticated algorithms.
Wiwin Windupranata, Muhammad Wahyu Al Ghifari, Candida Aulia De Silva Nusantara, Marsyanisa Shafa, Intan Hayatiningsih, Iyan Eka Mulia, and Alqinthara Nuraghnia
Nat. Hazards Earth Syst. Sci., 25, 1057–1069, https://doi.org/10.5194/nhess-25-1057-2025, https://doi.org/10.5194/nhess-25-1057-2025, 2025
Short summary
Short summary
Batukaras is a village on the southern coast of Java that is prone to tsunami hazards. To assess the potential tsunami hazard in the area, the probabilistic tsunami hazard analysis method was employed. It resulted in tsunami heights of 0.84, 1.63, 2.97, and 5.7 m for each earthquake return period of 250, 500, 1000, and 2500 years, respectively. The largest contribution of earthquake sources comes from the West Java–Central Java megathrust segment.
Enrico Duo, Juan Montes, Marine Le Gal, Tomás Fernández-Montblanc, Paolo Ciavola, and Clara Armaroli
Nat. Hazards Earth Syst. Sci., 25, 13–39, https://doi.org/10.5194/nhess-25-13-2025, https://doi.org/10.5194/nhess-25-13-2025, 2025
Short summary
Short summary
The present work, developed within the EU H2020 European Coastal Flood Awareness System (ECFAS) project, presents an approach used to estimate direct impacts of coastal flood on population, buildings, and roads along European coasts. The findings demonstrate that the ECFAS impact approach offers valuable estimates for affected populations, reliable damage assessments for buildings and roads, and improved accuracy compared to traditional grid-based approaches.
Benedikt Aschenneller, Roelof Rietbroek, and Daphne van der Wal
Nat. Hazards Earth Syst. Sci., 24, 4145–4177, https://doi.org/10.5194/nhess-24-4145-2024, https://doi.org/10.5194/nhess-24-4145-2024, 2024
Short summary
Short summary
Shorelines retreat or advance in response to sea level changes, subsidence or uplift of the ground, and morphological processes (sedimentation and erosion). We show that the geometrical influence of each of these drivers on shoreline movements can be quantified by combining different remote sensing observations, including radar altimetry, lidar and optical satellite images. The focus here is to illustrate the uncertainties of these observations by comparing datasets that cover similar processes.
Alisée A. Chaigneau, Melisa Menéndez, Marta Ramírez-Pérez, and Alexandra Toimil
Nat. Hazards Earth Syst. Sci., 24, 4109–4131, https://doi.org/10.5194/nhess-24-4109-2024, https://doi.org/10.5194/nhess-24-4109-2024, 2024
Short summary
Short summary
Tropical cyclones drive extreme sea levels, causing large storm surges due to low atmospheric pressure and strong winds. This study explores factors affecting the numerical modelling of storm surges induced by hurricanes in the tropical Atlantic. Two ocean models are compared and used for sensitivity experiments. ERA5 atmospheric reanalysis forcing generally improves surge estimates compared to parametric wind models. Including ocean circulations reduces errors in surge estimates in some areas.
Christopher Stokes, Timothy Poate, Gerd Masselink, Tim Scott, and Steve Instance
Nat. Hazards Earth Syst. Sci., 24, 4049–4074, https://doi.org/10.5194/nhess-24-4049-2024, https://doi.org/10.5194/nhess-24-4049-2024, 2024
Short summary
Short summary
Currents at beaches with an estuary mouth have rarely been studied before. Using field measurements and computer modelling, we show that surfzone currents can be driven by both estuary flow and rip currents. We show that an estuary mouth beach can have flows reaching 1.5 m s−1 and have a high likelihood of taking bathers out of the surfzone. The river channels on the beach direct the flows, and even though they change position over time, it was possible to predict when peak hazards would occur.
Alisée A. Chaigneau, Angélique Melet, Aurore Voldoire, Maialen Irazoqui Apecechea, Guillaume Reffray, Stéphane Law-Chune, and Lotfi Aouf
Nat. Hazards Earth Syst. Sci., 24, 4031–4048, https://doi.org/10.5194/nhess-24-4031-2024, https://doi.org/10.5194/nhess-24-4031-2024, 2024
Short summary
Short summary
Climate-change-induced sea level rise increases the frequency of extreme sea levels. We analyze projected changes in extreme sea levels for western European coasts produced with high-resolution models (∼ 6 km). Unlike commonly used coarse-scale global climate models, this approach allows us to simulate key processes driving coastal sea level variations, such as long-term sea level rise, tides, storm surges induced by low atmospheric surface pressure and winds, waves, and their interactions.
Joshua Kiesel, Claudia Wolff, and Marvin Lorenz
Nat. Hazards Earth Syst. Sci., 24, 3841–3849, https://doi.org/10.5194/nhess-24-3841-2024, https://doi.org/10.5194/nhess-24-3841-2024, 2024
Short summary
Short summary
In October 2023, one of the strongest storm surges on record hit the southwestern Baltic Sea coast, causing severe impacts in the German federal state of Schleswig-Holstein, including dike failures. Recent studies on coastal flooding from the same region align well with the October 2023 surge, with differences in peak water levels of less than 30 cm. This rare coincidence is used to assess current capabilities and limitations of coastal flood modelling and derive key areas for future research.
Emmie Malika Bonilauri, Catherine Aaron, Matteo Cerminara, Raphaël Paris, Tomaso Esposti Ongaro, Benedetta Calusi, Domenico Mangione, and Andrew John Lang Harris
Nat. Hazards Earth Syst. Sci., 24, 3789–3813, https://doi.org/10.5194/nhess-24-3789-2024, https://doi.org/10.5194/nhess-24-3789-2024, 2024
Short summary
Short summary
Currently on the island of Stromboli, only 4 min of warning time is available for a locally generated tsunami. We combined tsunami simulations and human exposure to complete a risk analysis. We linked the predicted inundation area and the tsunami warning signals to assess the hazard posed by future tsunamis and to design escape routes to reach safe areas and to optimise evacuation times. Such products can be used by civil protection agencies on Stromboli.
Marvin Lorenz, Katri Viigand, and Ulf Gräwe
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-198, https://doi.org/10.5194/nhess-2024-198, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study divides the sea level components that contribute to extreme sea levels in the Baltic Sea into three parts: the filling state of the Baltic Sea, seiches and storm surges. In the western part of the Baltic Sea, storm surges are the main factor, while in the central and northern parts, the filling state plays a larger role. Using a numerical model, we show that wind and air pressure are the main drivers of these events, with Atlantic sea level also playing a small role.
Robert McCall, Curt Storlazzi, Floortje Roelvink, Stuart G. Pearson, Roel de Goede, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci., 24, 3597–3625, https://doi.org/10.5194/nhess-24-3597-2024, https://doi.org/10.5194/nhess-24-3597-2024, 2024
Short summary
Short summary
Accurate predictions of wave-driven flooding are essential to manage risk on low-lying, reef-lined coasts. Models to provide this information are, however, computationally expensive. We present and validate a modeling system that simulates flood drivers on diverse and complex reef-lined coasts as competently as a full-physics model but at a fraction of the computational cost to run. This development paves the way for application in large-scale early-warning systems and flood risk assessments.
Lucas Terlinden-Ruhl, Anaïs Couasnon, Dirk Eilander, Gijs G. Hendrickx, Patricia Mares-Nasarre, and José A. Á. Antolínez
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-196, https://doi.org/10.5194/nhess-2024-196, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study develops a conceptual framework that uses active learning to accelerate compound flood risk assessments. A case study of Charleston County shows that the framework achieves faster and more accurate risk quantifications compared to the state-of-the-art. This win-win allows for increasing the number of flooding parameters, which results in an 11.6 % difference in the expected annual damages. Therefore, this framework allows for more comprehensive compound flood risk assessments.
Jean H. M. Roger and Bernard Pelletier
Nat. Hazards Earth Syst. Sci., 24, 3461–3478, https://doi.org/10.5194/nhess-24-3461-2024, https://doi.org/10.5194/nhess-24-3461-2024, 2024
Short summary
Short summary
We present a catalogue of tsunamis that occurred in the Vanuatu Arc. It has been built based on the analysis of existing catalogues, historical documents, and sea-level data from five coastal tide gauges. Since 1863, 100 tsunamis of local, regional, or far-field origins have been listed; 15 of them show maximum wave amplitudes and/or run-up heights of above 1 m, and 8 are between 0.3 and 1 m. Details are provided for particular events, including debated events or events with no known origin(s).
Rashid Haider, Sajid Ali, Gösta Hoffmann, and Klaus Reicherter
Nat. Hazards Earth Syst. Sci., 24, 3279–3290, https://doi.org/10.5194/nhess-24-3279-2024, https://doi.org/10.5194/nhess-24-3279-2024, 2024
Short summary
Short summary
The coastlines bordering the Arabian Sea have yielded various tsunamites reflecting its high hazard potential and recurrences. My PhD project aims at the estimation and zonation of the hazards and risks associated with. This publication is a continuation of the previous publication (Haider et al., 2023), which focused on hazard estimation through a multi-proxy approach. This part of the study estimates the risk potential through integrated tsunami inundation analysis.
Kévin Dubois, Morten Andreas Dahl Larsen, Martin Drews, Erik Nilsson, and Anna Rutgersson
Nat. Hazards Earth Syst. Sci., 24, 3245–3265, https://doi.org/10.5194/nhess-24-3245-2024, https://doi.org/10.5194/nhess-24-3245-2024, 2024
Short summary
Short summary
Both extreme river discharge and storm surges can interact at the coast and lead to flooding. However, it is difficult to predict flood levels during such compound events because they are rare and complex. Here, we focus on the quantification of uncertainties and investigate the sources of limitations while carrying out such analyses at Halmstad, Sweden. Based on a sensitivity analysis, we emphasize that both the choice of data source and statistical methodology influence the results.
Sergio Padilla, Íñigo Aniel-Quiroga, Rachid Omira, Mauricio González, Jihwan Kim, and Maria A. Baptista
Nat. Hazards Earth Syst. Sci., 24, 3095–3113, https://doi.org/10.5194/nhess-24-3095-2024, https://doi.org/10.5194/nhess-24-3095-2024, 2024
Short summary
Short summary
The eruption of the Hunga Tonga–Hunga Ha'apai volcano in January 2022 triggered a global phenomenon, including an atmospheric wave and a volcano-meteorological tsunami (VMT). The tsunami, reaching as far as Callao, Peru, 10 000 km away, caused significant coastal impacts. This study delves into understanding these effects, particularly on vessel mooring safety. The findings underscore the importance of enhancing early warning systems and preparing port authorities for managing such rare events.
Alice Abbate, José M. González Vida, Manuel J. Castro Díaz, Fabrizio Romano, Hafize Başak Bayraktar, Andrey Babeyko, and Stefano Lorito
Nat. Hazards Earth Syst. Sci., 24, 2773–2791, https://doi.org/10.5194/nhess-24-2773-2024, https://doi.org/10.5194/nhess-24-2773-2024, 2024
Short summary
Short summary
Modelling tsunami generation due to a rapid submarine earthquake is a complex problem. Under a variety of realistic conditions in a subduction zone, we propose and test an efficient solution to this problem: a tool that can compute the generation of any potential tsunami in any ocean in the world. In the future, we will explore solutions that would also allow us to model tsunami generation by slower (time-dependent) seafloor displacement.
Mithun Deb, James J. Benedict, Ning Sun, Zhaoqing Yang, Robert D. Hetland, David Judi, and Taiping Wang
Nat. Hazards Earth Syst. Sci., 24, 2461–2479, https://doi.org/10.5194/nhess-24-2461-2024, https://doi.org/10.5194/nhess-24-2461-2024, 2024
Short summary
Short summary
We coupled earth system, hydrology, and hydrodynamic models to generate plausible and physically consistent ensembles of hurricane events and their associated water levels from the open coast to tidal rivers of Delaware Bay and River. Our results show that the hurricane landfall locations and the estuarine wind can significantly amplify the extreme surge in a shallow and converging system, especially when the wind direction aligns with the surge propagation direction.
Ming-Huei Chang, Yen-Chen Huang, Yu-Hsin Cheng, Chuen-Teyr Terng, Jinyi Chen, and Jyh Cherng Jan
Nat. Hazards Earth Syst. Sci., 24, 2481–2494, https://doi.org/10.5194/nhess-24-2481-2024, https://doi.org/10.5194/nhess-24-2481-2024, 2024
Short summary
Short summary
Monitoring the long-term trends in sea surface warming is crucial for informed decision-making and adaptation. This study offers a comprehensive examination of prevalent trend extraction methods. We identify the least-squares regression as suitable for general tasks yet highlight the need to address seasonal signal-induced bias, i.e., the phase–distance imbalance. Our developed method, evaluated using simulated and real data, is unbiased and better than the conventional SST anomaly method.
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates
Nat. Hazards Earth Syst. Sci., 24, 2403–2423, https://doi.org/10.5194/nhess-24-2403-2024, https://doi.org/10.5194/nhess-24-2403-2024, 2024
Short summary
Short summary
Coastal areas are at risk of flooding from rising sea levels and extreme weather events. This study applies a new approach to estimating the likelihood of coastal flooding around the world. The method uses data from observations and computer models to create a detailed map of where these coastal floods might occur. The approach can predict flooding in areas for which there are few or no data available. The results can be used to help prepare for and prevent this type of flooding.
Guangsheng Zhao and Xiaojing Niu
Nat. Hazards Earth Syst. Sci., 24, 2303–2313, https://doi.org/10.5194/nhess-24-2303-2024, https://doi.org/10.5194/nhess-24-2303-2024, 2024
Short summary
Short summary
The purpose of this study is to estimate the spatial distribution of the tsunami hazard in the South China Sea from the Manila subduction zone. The plate motion data are used to invert the degree of locking on the fault plane. The degree of locking is used to estimate the maximum possible magnitude of earthquakes and describe the slip distribution. A spatial distribution map of the 1000-year return period tsunami wave height in the South China Sea was obtained by tsunami hazard assessment.
Mandana Ghanavati, Ian R. Young, Ebru Kirezci, and Jin Liu
Nat. Hazards Earth Syst. Sci., 24, 2175–2190, https://doi.org/10.5194/nhess-24-2175-2024, https://doi.org/10.5194/nhess-24-2175-2024, 2024
Short summary
Short summary
The paper examines the changes in shoreline position of the coast of south-east Australia over a 26-year period to determine whether changes are consistent with observed changes in ocean wave and storm surge climate. The results show that in regions where there have been significant changes in wave energy flux or wave direction, there have also been changes in shoreline position consistent with non-equilibrium longshore drift.
Ina Teutsch, Ralf Weisse, and Sander Wahls
Nat. Hazards Earth Syst. Sci., 24, 2065–2069, https://doi.org/10.5194/nhess-24-2065-2024, https://doi.org/10.5194/nhess-24-2065-2024, 2024
Short summary
Short summary
We investigate buoy and radar measurement data from shallow depths in the southern North Sea. We analyze the role of solitons for the occurrence of rogue waves. This is done by computing the nonlinear soliton spectrum of each time series. In a previous study that considered a single measurement site, we found a connection between the shape of the soliton spectrum and the occurrence of rogue waves. In this study, results for two additional sites are reported.
Marc Igigabel, Marissa Yates, Michalis Vousdoukas, and Youssef Diab
Nat. Hazards Earth Syst. Sci., 24, 1951–1974, https://doi.org/10.5194/nhess-24-1951-2024, https://doi.org/10.5194/nhess-24-1951-2024, 2024
Short summary
Short summary
Changes in sea levels alone do not determine the evolution of coastal hazards. Coastal hazard changes should be assessed using additional factors describing geomorphological configurations, metocean event types (storms, cyclones, long swells, and tsunamis), and the marine environment (e.g., coral reef state and sea ice extent). The assessment completed here, at regional scale including the coasts of mainland and overseas France, highlights significant differences in hazard changes.
Jani Särkkä, Jani Räihä, Mika Rantanen, and Matti Kämäräinen
Nat. Hazards Earth Syst. Sci., 24, 1835–1842, https://doi.org/10.5194/nhess-24-1835-2024, https://doi.org/10.5194/nhess-24-1835-2024, 2024
Short summary
Short summary
We study the relationship between tracks of low-pressure systems and related sea level extremes. We perform the studies by introducing a method to simulate sea levels using synthetic low-pressure systems. We test the method using sites located along the Baltic Sea coast. We find high extremes, where the sea level extreme reaches up to 3.5 m. In addition, we add the maximal value of the mean level of the Baltic Sea (1 m), leading to a sea level of 4.5 m.
Alexey Androsov, Sven Harig, Natalia Zamora, Kim Knauer, and Natalja Rakowsky
Nat. Hazards Earth Syst. Sci., 24, 1635–1656, https://doi.org/10.5194/nhess-24-1635-2024, https://doi.org/10.5194/nhess-24-1635-2024, 2024
Short summary
Short summary
Two numerical codes are used in a comparative analysis of the calculation of the tsunami wave due to an earthquake along the Peruvian coast. The comparison primarily evaluates the flow velocity fields in flooded areas. The relative importance of the various parts of the equations is determined, focusing on the nonlinear terms. The influence of the nonlinearity on the degree and volume of flooding, flow velocity, and small-scale fluctuations is determined.
Naveen Ragu Ramalingam, Kendra Johnson, Marco Pagani, and Mario Martina
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-72, https://doi.org/10.5194/nhess-2024-72, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
By combining limited tsunami simulations with a machine learning, we developed a fast and efficient framework to predict tsunami impacts such as wave heights and inundation depths along different coastal regions. Testing our model with historical tsunami source scenarios helped assess its reliability and broad applicability. This work enables more efficient and comprehensive tsunami hazard modelling workflow, essential for tsunami risk evaluations and enhancing coastal disaster preparedness.
Eric Mortensen, Timothy Tiggeloven, Toon Haer, Bas van Bemmel, Dewi Le Bars, Sanne Muis, Dirk Eilander, Frederiek Sperna Weiland, Arno Bouwman, Willem Ligtvoet, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 24, 1381–1400, https://doi.org/10.5194/nhess-24-1381-2024, https://doi.org/10.5194/nhess-24-1381-2024, 2024
Short summary
Short summary
Current levels of coastal flood risk are projected to increase in coming decades due to various reasons, e.g. sea-level rise, land subsidence, and coastal urbanization: action is needed to minimize this future risk. We evaluate dykes and coastal levees, foreshore vegetation, zoning restrictions, and dry-proofing on a global scale to estimate what levels of risk reductions are possible. We demonstrate that there are several potential adaptation pathways forward for certain areas of the world.
Charlotte Lyddon, Nguyen Chien, Grigorios Vasilopoulos, Michael Ridgill, Sogol Moradian, Agnieszka Olbert, Thomas Coulthard, Andrew Barkwith, and Peter Robins
Nat. Hazards Earth Syst. Sci., 24, 973–997, https://doi.org/10.5194/nhess-24-973-2024, https://doi.org/10.5194/nhess-24-973-2024, 2024
Short summary
Short summary
Recent storms in the UK, like Storm Ciara in 2020, show how vulnerable estuaries are to the combined effect of sea level and river discharge. We show the combinations of sea levels and river discharges that cause flooding in the Conwy estuary, N Wales. The results showed flooding was amplified under moderate conditions in the middle estuary and elsewhere sea state or river flow dominated the hazard. Combined sea and river thresholds can improve prediction and early warning of compound flooding.
Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 24, 737–755, https://doi.org/10.5194/nhess-24-737-2024, https://doi.org/10.5194/nhess-24-737-2024, 2024
Short summary
Short summary
Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the island scale. The results indicate that several factors contribute to mitigating and amplifying tsunami waves at the island scale.
Niels J. Korsgaard, Kristian Svennevig, Anne S. Søndergaard, Gregor Luetzenburg, Mimmi Oksman, and Nicolaj K. Larsen
Nat. Hazards Earth Syst. Sci., 24, 757–772, https://doi.org/10.5194/nhess-24-757-2024, https://doi.org/10.5194/nhess-24-757-2024, 2024
Short summary
Short summary
A tsunami wave will leave evidence of erosion and deposition in coastal lakes, making it possible to determine the runup height and when it occurred. Here, we use four lakes now located at elevations of 19–91 m a.s.l. close to the settlement of Saqqaq, West Greenland, to show that at least two giant tsunamis occurred 7300–7600 years ago with runup heights larger than 40 m. We infer that any tsunamis from at least nine giga-scale landslides must have happened 8500–10 000 years ago.
Elke Magda Inge Meyer and Lidia Gaslikova
Nat. Hazards Earth Syst. Sci., 24, 481–499, https://doi.org/10.5194/nhess-24-481-2024, https://doi.org/10.5194/nhess-24-481-2024, 2024
Short summary
Short summary
Storm tides for eight extreme historical storms in the German Bight are modelled using sets of slightly varying atmospheric conditions from the century reanalyses. Comparisons with the water level observations from the gauges Norderney, Cuxhaven and Husum show that single members of the reanalyses are suitable for the reconstruction of extreme storms. Storms with more northerly tracks show less variability within a set and have more potential for accurate reconstruction of extreme water levels.
Clare Lewis, Tim Smyth, Jess Neumann, and Hannah Cloke
Nat. Hazards Earth Syst. Sci., 24, 121–131, https://doi.org/10.5194/nhess-24-121-2024, https://doi.org/10.5194/nhess-24-121-2024, 2024
Short summary
Short summary
Meteotsunami are the result of atmospheric disturbances and can impact coastlines causing injury, loss of life, and damage to assets. This paper introduces a novel intensity index to allow for the quantification of these events at the shoreline. This has the potential to assist in the field of natural hazard assessment. It was trialled in the UK but designed for global applicability and to become a widely accepted standard in coastal planning, meteotsunami forecasting, and early warning systems.
Chu-En Hsu, Katherine A. Serafin, Xiao Yu, Christie A. Hegermiller, John C. Warner, and Maitane Olabarrieta
Nat. Hazards Earth Syst. Sci., 23, 3895–3912, https://doi.org/10.5194/nhess-23-3895-2023, https://doi.org/10.5194/nhess-23-3895-2023, 2023
Short summary
Short summary
Total water levels (TWLs) induced by tropical cyclones (TCs) are among the leading hazards faced by coastal communities. Using numerical models, we examined how TWL components (surge and wave runup) along the South Atlantic Bight varied during hurricanes Matthew (2016), Dorian (2019), and Isaias (2020). Peak surge and peak wave runup were dominated by wind speeds and relative positions to TCs. The exceedance time of TWLs was controlled by normalized distances to TC and TC translation speeds.
Maude Biguenet, Eric Chaumillon, Pierre Sabatier, Antoine Bastien, Emeline Geba, Fabien Arnaud, Thibault Coulombier, and Nathalie Feuillet
Nat. Hazards Earth Syst. Sci., 23, 3761–3788, https://doi.org/10.5194/nhess-23-3761-2023, https://doi.org/10.5194/nhess-23-3761-2023, 2023
Short summary
Short summary
This work documents the impact of Hurricane Irma (2017) on the Codrington barrier and lagoon on Barbuda Island. Irma caused two wide breaches in the sandy barrier, which remained unopened for 250 years. The thick and extensive sand sheet at the top of the lagoon fill was attributed to Irma. This unique deposit in a 3700-year record confirms Irma's exceptional character. This case study illustrates the consequences of high-intensity hurricanes in low-lying islands in a global warming context.
Leigh Richard MacPherson, Arne Arns, Svenja Fischer, Fernando Javier Méndez, and Jürgen Jensen
Nat. Hazards Earth Syst. Sci., 23, 3685–3701, https://doi.org/10.5194/nhess-23-3685-2023, https://doi.org/10.5194/nhess-23-3685-2023, 2023
Short summary
Short summary
Efficient adaptation planning for coastal flooding caused by extreme sea levels requires accurate assessments of the underlying hazard. Tide-gauge data alone are often insufficient for providing the desired accuracy but may be supplemented with historical information. We estimate extreme sea levels along the German Baltic coast and show that relying solely on tide-gauge data leads to underestimations. Incorporating historical information leads to improved estimates with reduced uncertainties.
Anne Margaret H. Smiley, Suzanne P. Thompson, Nathan S. Hall, and Michael F. Piehler
Nat. Hazards Earth Syst. Sci., 23, 3635–3649, https://doi.org/10.5194/nhess-23-3635-2023, https://doi.org/10.5194/nhess-23-3635-2023, 2023
Short summary
Short summary
Floodwaters can deliver reactive nitrogen to sensitive aquatic systems and diminish water quality. We assessed the nitrogen removal capabilities of flooded habitats and urban landscapes. Differences in processing rates across land cover treatments and between nutrient treatments suggest that abundance and spatial distributions of habitats, as well as storm characteristics, influence landscape-scale nitrogen removal. Results have important implications for coastal development and climate change.
Marine Le Gal, Tomás Fernández-Montblanc, Enrico Duo, Juan Montes Perez, Paulo Cabrita, Paola Souto Ceccon, Véra Gastal, Paolo Ciavola, and Clara Armaroli
Nat. Hazards Earth Syst. Sci., 23, 3585–3602, https://doi.org/10.5194/nhess-23-3585-2023, https://doi.org/10.5194/nhess-23-3585-2023, 2023
Short summary
Short summary
Assessing coastal hazards is crucial to mitigate flooding disasters. In this regard, coastal flood databases are valuable tools. This paper describes a new coastal flood map catalogue covering the entire European coastline, as well as the methodology to build it and its accuracy. The catalogue focuses on frequent extreme events and relies on synthetic scenarios estimated from local storm conditions. Flood-prone areas and regions sensitive to storm duration and water level peak were identified.
Neng-Ti Yu, Cheng-Hao Lu, I-Chin Yen, Jia-Hong Chen, Jiun-Yee Yen, and Shyh-Jeng Chyi
Nat. Hazards Earth Syst. Sci., 23, 3525–3542, https://doi.org/10.5194/nhess-23-3525-2023, https://doi.org/10.5194/nhess-23-3525-2023, 2023
Short summary
Short summary
A paleotsunami deposit of cliff-top basalt debris was identified on the Penghu Islands in the southern Taiwan Strait and related to the 1661 earthquake in southwest Taiwan. A minimum wave height of 3.2 m is estimated to have rotated the biggest boulder for over 30 m landwards onto the cliff top at 2.5 m a.s.l. The event must have been huge compared to the 1994 M 6.4 earthquake with the ensuing 0.4 m high tsunami in the same area, validating the intimidating tsunami risks in the South China Sea.
Ye Yuan, Huaiwei Yang, Fujiang Yu, Yi Gao, Benxia Li, and Chuang Xing
Nat. Hazards Earth Syst. Sci., 23, 3487–3507, https://doi.org/10.5194/nhess-23-3487-2023, https://doi.org/10.5194/nhess-23-3487-2023, 2023
Short summary
Short summary
Rip currents are narrow jets of offshore-directed flow that originated in the surf zone, which can take swimmers of all ability levels into deeper water unawares. In this study, a 1 m fine-resolution wave-resolving model was configured to study rip current variability and the optimal swimmer escape strategies. Multiple factors contribute to the survival of swimmers. However, for weak-to-moderate rip and longshore currents, swimming onshore consistently seems to be the most successful strategy.
Benedikt Mester, Thomas Vogt, Seth Bryant, Christian Otto, Katja Frieler, and Jacob Schewe
Nat. Hazards Earth Syst. Sci., 23, 3467–3485, https://doi.org/10.5194/nhess-23-3467-2023, https://doi.org/10.5194/nhess-23-3467-2023, 2023
Short summary
Short summary
In 2019, Cyclone Idai displaced more than 478 000 people in Mozambique. In our study, we use coastal flood modeling and satellite imagery to construct a counterfactual cyclone event without the effects of climate change. We show that 12 600–14 900 displacements can be attributed to sea level rise and the intensification of storm wind speeds due to global warming. Our impact attribution study is the first one on human displacement and one of very few for a low-income country.
Olivier Cavalié, Frédéric Cappa, and Béatrice Pinel-Puysségur
Nat. Hazards Earth Syst. Sci., 23, 3235–3246, https://doi.org/10.5194/nhess-23-3235-2023, https://doi.org/10.5194/nhess-23-3235-2023, 2023
Short summary
Short summary
Coastal areas are fragile ecosystems that face multiple hazards. In this study, we measured the downward motion of the Nice Côte d'Azur Airport (France) that was built on reclaimed area and found that it has subsided from 16 mm yr-1 in the 1990s to 8 mm yr-1 today. A continuous remote monitoring of the platform will provide key data for a detailed investigation of future subsidence maps, and this contribution will help to evaluate the potential failure of part of the airport platform.
Wagner L. L. Costa, Karin R. Bryan, and Giovanni Coco
Nat. Hazards Earth Syst. Sci., 23, 3125–3146, https://doi.org/10.5194/nhess-23-3125-2023, https://doi.org/10.5194/nhess-23-3125-2023, 2023
Short summary
Short summary
For predicting flooding events at the coast, topo-bathymetric data are essential. However, elevation data can be unavailable. To tackle this issue, recent efforts have centred on the use of satellite-derived topography (SDT) and bathymetry (SDB). This work is aimed at evaluating their accuracy and use for flooding prediction in enclosed estuaries. Results show that the use of SDT and SDB in numerical modelling can produce similar predictions when compared to the surveyed elevation data.
Joshua Kiesel, Marvin Lorenz, Marcel König, Ulf Gräwe, and Athanasios T. Vafeidis
Nat. Hazards Earth Syst. Sci., 23, 2961–2985, https://doi.org/10.5194/nhess-23-2961-2023, https://doi.org/10.5194/nhess-23-2961-2023, 2023
Short summary
Short summary
Among the Baltic Sea littoral states, Germany is anticipated to experience considerable damage as a result of increased coastal flooding due to sea-level rise (SLR). Here we apply a new modelling framework to simulate how flooding along the German Baltic Sea coast may change until 2100 if dikes are not upgraded. We find that the study region is highly exposed to flooding, and we emphasise the importance of current plans to update coastal protection in the future.
Zhang Haixia, Cheng Meng, and Fang Weihua
Nat. Hazards Earth Syst. Sci., 23, 2697–2717, https://doi.org/10.5194/nhess-23-2697-2023, https://doi.org/10.5194/nhess-23-2697-2023, 2023
Short summary
Short summary
Simultaneous storm surge and waves can cause great damage due to cascading effects. Quantitative joint probability analysis is critical to determine their optimal protection design values. The joint probability of the surge and wave for the eastern coasts of Leizhou Peninsula and Hainan are estimated with a Gumbel copula based on 62 years of numerically simulated data, and the optimal design values under various joint return periods are derived using the non-linear programming method.
Clare Lewis, Tim Smyth, David Williams, Jess Neumann, and Hannah Cloke
Nat. Hazards Earth Syst. Sci., 23, 2531–2546, https://doi.org/10.5194/nhess-23-2531-2023, https://doi.org/10.5194/nhess-23-2531-2023, 2023
Short summary
Short summary
Meteotsunami are globally occurring water waves initiated by atmospheric disturbances. Previous research has suggested that in the UK, meteotsunami are a rare phenomenon and tend to occur in the summer months. This article presents a revised and updated catalogue of 98 meteotsunami that occurred between 1750 and 2022. Results also demonstrate a larger percentage of winter events and a geographical pattern highlighting the
hotspotregions that experience these events.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, Joël J.-M. Hirschi, Robert J. Nicholls, and Nadia Bloemendaal
Nat. Hazards Earth Syst. Sci., 23, 2475–2504, https://doi.org/10.5194/nhess-23-2475-2023, https://doi.org/10.5194/nhess-23-2475-2023, 2023
Short summary
Short summary
We used a novel database of simulated tropical cyclone tracks to explore whether typhoon-induced storm surges present a future flood risk to low-lying coastal communities around the South China Sea. We found that future climate change is likely to change tropical cyclone behaviour to an extent that this increases the severity and frequency of storm surges to Vietnam, southern China, and Thailand. Consequently, coastal flood defences need to be reviewed for resilience against this future hazard.
Sang-Guk Yum, Moon-Soo Song, and Manik Das Adhikari
Nat. Hazards Earth Syst. Sci., 23, 2449–2474, https://doi.org/10.5194/nhess-23-2449-2023, https://doi.org/10.5194/nhess-23-2449-2023, 2023
Short summary
Short summary
This study performed analysis on typhoon-induced coastal morphodynamics for the Mokpo coast. Wetland vegetation was severely impacted by Typhoon Soulik, with 87.35 % of shoreline transects experiencing seaward migration. This result highlights the fact that sediment resuspension controls the land alteration process over the typhoon period. The land accretion process dominated during the pre- to post-typhoon periods.
Olle Räty, Marko Laine, Ulpu Leijala, Jani Särkkä, and Milla M. Johansson
Nat. Hazards Earth Syst. Sci., 23, 2403–2418, https://doi.org/10.5194/nhess-23-2403-2023, https://doi.org/10.5194/nhess-23-2403-2023, 2023
Short summary
Short summary
We studied annual maximum sea levels in the Finnish coastal region. Our aim was to better quantify the uncertainty in them compared to previous studies. Using four statistical models, we found out that hierarchical models, which shared information on sea-level extremes across Finnish tide gauges, had lower uncertainty in their results in comparison with tide-gauge-specific fits. These models also suggested that the shape of the distribution for extreme sea levels is similar on the Finnish coast.
Cited articles
Abbaszadeh, P., Muñoz, D. F., Moftakhari, H., Jafarzadegan, K., and Moradkhani, H.: Perspective on uncertainty quantification and reduction in compound flood modeling and forecasting, iScience, 25, 105201, https://doi.org/10.1016/j.isci.2022.105201, 2022.
Acreman, M. C.: Assessing the Joint Probability of Fluvial and Tidal Floods in the River Roding, Water Environ. J., 8, 490–496, https://doi.org/10.1111/j.1747-6593.1994.tb01140.x, 1994.
Adhikari, P., Hong, Y., Douglas, K. R., Kirschbaum, D. B., Gourley, J., Adler, R., and Brakenridge, G. R.: A digitized global flood inventory (1998–2008): Compilation and preliminary results, Natural Hazards, 55, 405-422, https://doi.org/10.1007/S11069-010-9537-2, 2010.
AghaKouchak, A., Chiang, F., Huning, L. S., Love, C. A., Mallakpour, I., Mazdiyasni, O., Moftakhari, H., Papalexiou, S. M., Ragno, E., and Sadegh, M.: Climate Extremes and Compound Hazards in a Warming World, Annu. Rev. Earth Pl. Sc., 48, 519–548, https://doi.org/10.1146/annurev-earth-071719-055228, 2020.
Ai, P., Yuan, D., and Xiong, C.: Copula-based joint probability analysis of compound floods from rainstorm and typhoon surge: A case study of Jiangsu Coastal Areas, China, Sustainability, 10, 2232, https://doi.org/10.3390/SU10072232, 2018.
Apel, H., Martínez Trepat, O., Hung, N. N., Chinh, D. T., Merz, B., and Dung, N. V.: Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam, Nat. Hazards Earth Syst. Sci., 16, 941–961, https://doi.org/10.5194/nhess-16-941-2016, 2016.
Archetti, R., Bolognesi, A., Casadio, A., and Maglionico, M.: Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach, Hydrol. Earth Syst. Sci., 15, 3115–3122, https://doi.org/10.5194/hess-15-3115-2011, 2011.
Bacopoulos, P., Tang, Y., Asce, S. M., Wang, D., Asce, A. M., Hagen, S. C., and Asce, F.: Integrated Hydrologic-Hydrodynamic Modeling of Estuarine-Riverine Flooding: 2008 Tropical Storm Fay, J. Hydrol. Eng., 22, 04017022, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001539, 2017.
Bakhtyar, R., Maitaria, K., Velissariou, P., Trimble, B., Mashriqui, H., Moghimi, S., Abdolali, A., Van der Westhuysen, A. J., Ma, Z., Clark, E. P., and Flowers, T.: A New 1D/2D Coupled Modeling Approach for a Riverine-Estuarine System Under Storm Events: Application to Delaware River Basin, J. Geophys. Res.-Oceans, 125, e2019JC015822, https://doi.org/10.1029/2019JC015822, 2020.
Ballesteros, C., Jiménez, J. A., and Viavattene, C.: A multi-component flood risk assessment in the Maresme coast (NW Mediterranean), Nat. Hazards, 90, 265–292, https://doi.org/10.1007/s11069-017-3042-9, 2018.
Banfi, F. and De Michele, C.: Compound flood hazard at Lake Como, Italy, is driven by temporal clustering of rainfall events, Commun. Earth Environ., 3, 234, https://doi.org/10.1038/s43247-022-00557-9, 2022.
Bao, D., Xue, Z. G., Warner, J. C., Moulton, M., Yin, D., Hegermiller, C. A., Zambon, J. B., and He, R.: A Numerical Investigation of Hurricane Florence-Induced Compound Flooding in the Cape Fear Estuary Using a Dynamically Coupled Hydrological-Ocean Model, J. Adv. Model. Earth Sy., 14, e2022MS003131, https://doi.org/10.1029/2022MS003131, 2022.
Bass, B. and Bedient, P.: Surrogate modeling of joint flood risk across coastal watersheds, J. Hydrol., 558, 159–173, https://doi.org/10.1016/j.jhydrol.2018.01.014, 2018.
Bates, P. D., Quinn, N., Sampson, C., Smith, A., Wing, O., Sosa, J., Savage, J., Olcese, G., Neal, J., Schumann, G., Giustarini, L., Coxon, G., Porter, J. R., Amodeo, M. F., Chu, Z., Lewis-Gruss, S., Freeman, N. B., Houser, T., Delgado, M., Hamidi, A., Bolliger, I., E. McCusker, K., Emanuel, K., Ferreira, C. M., Khalid, A., Haigh, I. D., Couasnon, A., E. Kopp, R., Hsiang, S., and Krajewski, W. F.: Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates, Water Resour. Res., 57, https://doi.org/10.1029/2020WR028673, 2021.
Baxter, R. M.: Environmental Effects of Dams and Impoundments, Annu. Rev. Ecol. Syst., 8, 255–283, 1977.
Bayazýt, Y. and Koç, C.: The impact of forest fires on floods and erosion: Marmaris, Turkey, Environ. Dev. Sustain., 24, 13426–13445, https://doi.org/10.1007/s10668-022-02624-9, 2022.
Beardsley, R. C., Chen, C., and Xu, Q.: Coastal flooding in Scituate (MA): A FVCOM study of the 27 December 2010 nor'easter, J. Geophys. Res.-Oceans, 118, 6030–6045, https://doi.org/10.1002/2013JC008862, 2013.
Befus, K. M., Barnard, P. L., Hoover, D. J., Finzi Hart, J. A., and Voss, C. I.: Increasing threat of coastal groundwater hazards from sea-level rise in California, Nat. Clim. Change, 10, 946–952, https://doi.org/10.1038/s41558-020-0874-1, 2020.
Belongia, M. F., Hammond Wagner, C., Seipp, K. Q., and Ajami, N. K.: Building water resilience in the face of cascading wildfire risks, Science Advances, 9, eadf9534, https://doi.org/10.1126/sciadv.adf9534, 2023.
Bender, J., Wahl, T., Müller, A., and Jensen, J.: A multivariate design framework for river confluences, Hydrolog. Sci. J., 61, 471–482, https://doi.org/10.1080/02626667.2015.1052816, 2016.
Benestad, R. E. and Haugen, J. E.: On complex extremes: Flood hazards and combined high spring-time precipitation and temperature in Norway, Climatic Change, 85, 381–406, https://doi.org/10.1007/S10584-007-9263-2, 2007.
Bengtsson, L., Hagemann, S., and Hodges, K. I.: Can climate trends be calculated from reanalysis data?, J. Geophys. Res.-Atmos., 109, D11111, https://doi.org/10.1029/2004JD004536, 2004.
Bensi, M., Mohammadi, S., Kao, S.-C., and DeNeale, S. T.: Multi-Mechanism Flood Hazard Assessment: Critical Review of Current Practice and Approaches, Oak Ridge National Lab, United States, https://doi.org/10.2172/1637939, 2020.
Berghuijs, W. R., Harrigan, S., Molnar, P., Slater, L. J., and Kirchner, J. W.: The Relative Importance of Different Flood-Generating Mechanisms Across Europe, Water Resour. Res., 55, 4582–4593, https://doi.org/10.1029/2019WR024841, 2019.
Bermúdez, M., Cea, L., and Sopelana, J.: Quantifying the role of individual flood drivers and their correlations in flooding of coastal river reaches, Stoch. Environ. Res. Risk A., 33, 1851–1861, https://doi.org/10.1007/S00477-019-01733-8, 2019.
Bermúdez, M., Farfán, J. F., Willems, P., and Cea, L.: Assessing the Effects of Climate Change on Compound Flooding in Coastal River Areas, Water Resour. Res., 57, e2020WR029321, https://doi.org/10.1029/2020WR029321, 2021.
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.
Bevacqua, E., Maraun, D., Vousdoukas, M. I., Voukouvalas, E., Vrac, M., Mentaschi, L., and Widmann, M.: Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change, Science Advances, 5, eaaw5531, https://doi.org/10.1126/SCIADV.AAW5531, 2019.
Bevacqua, E., Vousdoukas, M. I., Shepherd, T. G., and Vrac, M.: Brief communication: The role of using precipitation or river discharge data when assessing global coastal compound flooding, Nat. Hazards Earth Syst. Sci., 20, 1765–1782, https://doi.org/10.5194/nhess-20-1765-2020, 2020a.
Bevacqua, E., Vousdoukas, M. I., Zappa, G., Hodges, K., Shepherd, T. G., Maraun, D., Mentaschi, L., and Feyen, L.: More meteorological events that drive compound coastal flooding are projected under climate change, Communications Earth and Environment, 1, 47, https://doi.org/10.1038/S43247-020-00044-Z, 2020b.
Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S., Ramos, A. M., Vignotto, E., Bastos, A., Blesic, S., Durante, F., Hillier, J., Oliveira, S. C., Pinto, J. G., Ragno, E., Rivoire, P., Saunders, K., Van Der Wiel, K., Wu, W., Zhang, T., and Zscheischler, J.: Bottom-up identification of key elements of compound events, ESS Open Archive, https://doi.org/10.1002/ESSOAR.10507809.1, 2022.
Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S., Ramos, A. M., Vignotto, E., Bastos, A., Blesiæ, S., Durante, F., Hillier, J., Oliveira, S. C., Pinto, J. G., Ragno, E., Rivoire, P., Saunders, K., van der Wiel, K., Wu, W., Zhang, T., and Zscheischler, J.: Guidelines for Studying Diverse Types of Compound Weather and Climate Events, Earth's Future, 9, e2021EF002340, https://doi.org/10.1029/2021EF002340, 2021.
Bevere, L. and Remondi, F.: Natural catastrophes in 2021: the floodgates are open, Swiss Re Institute, Zurich, Switzerland, https://www.swissre.com/dam/jcr:326182d5-d433-46b1-af36-06f2aedd9d9a/swiss-re-institute-sigma-natcat-2022-en.pdf (last access: 17 July 2024), 2022.
Bilskie, M. V. and Hagen, S. C.: Defining Flood Zone Transitions in Low-Gradient Coastal Regions, Geophys. Res. Lett., 45, 2761–2770, https://doi.org/10.1002/2018GL077524, 2018.
Bilskie, M. V., Zhao, H., Resio, D., Atkinson, J., Cobell, Z., and Hagen, S. C.: Enhancing Flood Hazard Assessments in Coastal Louisiana Through Coupled Hydrologic and Surge Processes, Frontiers in Water, 3, 609231, https://doi.org/10.3389/FRWA.2021.609231, 2021.
Bischiniotis, K., van den Hurk, B., Jongman, B., Coughlan de Perez, E., Veldkamp, T., de Moel, H., and Aerts, J.: The influence of antecedent conditions on flood risk in sub-Saharan Africa, Nat. Hazards Earth Syst. Sci., 18, 271–285, https://doi.org/10.5194/nhess-18-271-2018, 2018.
Blanton, B., McGee, J., Fleming, J., Kaiser, C., Kaiser, H., Lander, H., Luettich, R., Dresback, K., and Kolar, R.: Urgent Computing of Storm Surge for North Carolina's Coast, Procedia Comput. Sci., 9, 1677–1686, https://doi.org/10.1016/J.PROCS.2012.04.185, 2012.
Blanton, B., Dresback, K., Colle, B., Kolar, R., Vergara, H., Hong, Y., Leonardo, N., Davidson, R., Nozick, L., and Wachtendorf, T.: An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2 – Hazard Modeling, Risk Anal., 40, 117–133, https://doi.org/10.1111/RISA.13004, 2018.
Bloemendaal, N., Haigh, I. D., de Moel, H., Muis, S., Haarsma, R. J., and Aerts, J. C. J. H.: Generation of a global synthetic tropical cyclone hazard dataset using STORM, Scientific Data, 7, 40, https://doi.org/10.1038/s41597-020-0381-2, 2020.
Blöschl, G., Hall, J., Parajka, J., Perdigão, R. A. P., Merz, B., Arheimer, B., Aronica, G. T., Bilibashi, A., Bonacci, O., Borga, M., Èanjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Fiala, K., Frolova, N., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S., Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J., Ledvinka, O., Macdonald, N., Mavrova-Guirguinova, M., Mediero, L., Merz, R., Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski, I., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J., Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Živkoviæ, N.: Changing climate shifts timing of European floods, Science, 357, 588–590, https://doi.org/10.1126/science.aan2506, 2017.
Borrero, J. C., Cronin, S. J., Latu'ila, F. H., Tukuafu, P., Heni, N., Tupou, A. M., Kula, T., Fa'anunu, O., Bosserelle, C., Lane, E., Lynett, P., and Kong, L.: Tsunami Runup and Inundation in Tonga from the January 2022 Eruption of Hunga Volcano, Pure Appl. Geophys., 180, 1–22, https://doi.org/10.1007/s00024-022-03215-5, 2023.
Brönnimann, S., Martius, O., Rohr, C., Bresch, D. N., and Lin, K.-H. E.: Historical weather data for climate risk assessment, Ann. NY Acad. Sci., 1436, 121–137, https://doi.org/10.1111/nyas.13966, 2019.
Bronstert, A., Niehoff, D., and Schiffler, G. R.: Modelling infiltration and infiltration excess: The importance of fast and local processes, Hydrol. Process., 37, e14875, https://doi.org/10.1002/hyp.14875, 2023.
Brown, J. D., Spencer, T., and Moeller, I.: Modeling storm surge flooding of an urban area with particular reference to modeling uncertainties: A case study of Canvey Island, United Kingdom, Water Resour. Res., 43, W06402, https://doi.org/10.1029/2005WR004597, 2007.
Bunya, S., Dietrich, J. C., Westerink, J. J., Ebersole, B. A., Smith, J. M., Atkinson, J. H., Jensen, R., Resio, D. T., Luettich, R. A., Dawson, C., Cardone, V. J., Cox, A. T., Powell, M. D., Westerink, H. J., and Roberts, H. J.: A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part I: Model Development and Validation, Mon. Weather Rev., 138, 345–377, https://doi.org/10.1175/2009MWR2906.1, 2010.
Burn, D. H. and Whitfield, P. H.: Climate related changes to flood regimes show an increasing rainfall influence, J. Hydrol., 617, 129075, https://doi.org/10.1016/j.jhydrol.2023.129075, 2023.
Bush, S. T., Dresback, K. M., Szpilka, C. M., and Kolar, R. L.: Use of 1D Unsteady HEC-RAS in a Coupled System for Compound Flood Modeling: North Carolina Case Study, Journal of Marine Science and Engineering, 10, 306, https://doi.org/10.3390/JMSE10030306, 2022.
Camus, P., Haigh, I. D., Nasr, A. A., Wahl, T., Darby, S. E., and Nicholls, R. J.: Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns, Nat. Hazards Earth Syst. Sci., 21, 2021–2040, https://doi.org/10.5194/nhess-21-2021-2021, 2021.
Camus, P., Haigh, I. D., Wahl, T., Nasr, A. A., Méndez, F. J., Darby, S. E., and Nicholls, R. J.: Daily synoptic conditions associated with occurrences of compound events in estuaries along North Atlantic coastlines, Int. J. Climatol., 42, 5694–5713, https://doi.org/10.1002/JOC.7556, 2022.
Cannon, S. H., Gartner, J. E., Wilson, R. C., Bowers, J. C., and Laber, J. L.: Storm rainfall conditions for floods and debris flows from recently burned areas in southwestern Colorado and southern California, Geomorphology, 96, 250–269, https://doi.org/10.1016/j.geomorph.2007.03.019, 2008.
Čepienė, E., Dailidytė, L., Stonevičius, E., and Dailidienė, I.: Sea Level Rise Impact on Compound Coastal River Flood Risk in Klaipėda City (Baltic Coast, Lithuania), Water, 14, 414, https://doi.org/10.3390/W14030414, 2022.
Chen, A. S., Djordjeviæ, S., Leandro, J., and Saviæ, D. A.: An analysis of the combined consequences of pluvial and fluvial flooding, Water Sci. Technol., 62, 1491–1498, https://doi.org/10.2166/wst.2010.486, 2010.
Chen, C. N., Tsai, C. H., Wu, M. H., and Tsai, C. T.: Numerical simulation of potential inundation in a coastal zone, J. Flood Risk Manag., 8, 208–223, https://doi.org/10.1111/JFR3.12088, 2015.
Chen, W. B. and Liu, W. C.: Modeling flood inundation induced by river flow and storm surges over a river basin, Water, 6, 3182–3199, https://doi.org/10.3390/W6103182, 2014.
Chen, W. B. and Liu, W. C.: Assessment of storm surge inundation and potential hazard maps for the southern coast of Taiwan, Nat. Hazards, 82, 591–616, https://doi.org/10.1007/S11069-016-2199-Y, 2016.
Chou, L. W.: Typhoon water surface analysis for west coast of Saipan: Mariana Islands, Coastal Engineering Research Center, https://hdl.handle.net/11681/12955 (last access: 17 July 2024), 1989.
Christian, J., Fang, Z., Torres, J., Deitz, R., and Bedient, P.: Modeling the Hydraulic Effectiveness of a Proposed Storm Surge Barrier System for the Houston Ship Channel during Hurricane Events, Nat. Hazards Rev., 16, 04014015, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000150, 2015.
Church, J., Clark, P., Cazenave, A., Gregory, J., Jevrejeva, S., Levermann, A., Merrifield, M., Milne, G., Nerem, R., and Nunn, P.: Climate Change 2013: The Physical Science Basis: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom, New York, USA, 1137–1216, https://doi.org/10.1017/CBO9781107415324.026, 2013.
Church, J. A., Gregory, J. M., Huybrechts, P., Kuhn, M., Lambeck, K., Nhuan, M. T., Qin, D., and Woodworth, P. L.: Changes in Sea Level, in: Climate Change 2001: The Scientific Basis: Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel, 639–694, 10013/epic.15081.d001, 2001.
Cifelli, R., Johnson, L. E., Kim, J., Coleman, T., Pratt, G., Herdman, L., Martyr-Koller, R., Finzihart, J. A., Erikson, L., Barnard, P., and Anderson, M.: Assessment of flood forecast products for a coupled tributary-coastal model, Water, 13, 1–24, https://doi.org/10.3390/W13030312, 2021.
Claassen, J., Ward, P., Daniell, J., Koks, E., Tiggeloven, T., and de Ruiter, M.: MYRIAD-HESA: A New Method to Generate Global Multi-Hazard Event Sets, Vrije Universiteit Amsterdam, https://doi.org/10.21203/rs.3.rs-2635188/v1, 2023.
Coles, S., Heffernan, J., and Tawn, J.: Dependence Measures for Extreme Value Analyses, Extremes, 2, 339–365, https://doi.org/10.1023/A:1009963131610, 1999.
Coles, S. G. and Tawn, J. A.: Statistical Methods for Multivariate Extremes: An Application to Structural Design, J. R. Stat. Soc. C-Appl., 43, 1–48, https://doi.org/10.2307/2986112, 1994.
Comer, J., Olbert, A. I., Nash, S., and Hartnett, M.: Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding, Nat. Hazards Earth Syst. Sci., 17, 205–224, https://doi.org/10.5194/nhess-17-205-2017, 2017.
Costa, J. E.: Floods from dam failures, Report 85-560, https://doi.org/10.3133/ofr85560, 1985.
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.
Couasnon, A., Eilander, D., Muis, S., Veldkamp, T. I. E., Haigh, I. D., Wahl, T., Winsemius, H. C., and Ward, P. J.: Measuring compound flood potential from river discharge and storm surge extremes at the global scale, Nat. Hazards Earth Syst. Sci., 20, 489–504, https://doi.org/10.5194/nhess-20-489-2020, 2020.
Curtis, S., Mukherji, A., Kruse, J., Helgeson, J., Ghosh, A., and Adeniji, N.: Perceptions of risk to compound coastal water events: A case study in eastern North Carolina, USA, Progress in Disaster Science, 16, 100266–100266, https://doi.org/10.1016/J.PDISAS.2022.100266, 2022.
Cutter, S. L.: Compound, Cascading, or Complex Disasters: What's in a Name?, Environment: Science and Policy for Sustainable Development, 60, 16–25, https://doi.org/10.1080/00139157.2018.1517518, 2018.
Dahl, K. A., Fitzpatrick, M. F., and Spanger-Siegfried, E.: Sea level rise drives increased tidal flooding frequency at tide gauges along the U.S. East and Gulf Coasts: Projections for 2030 and 2045, PLOS ONE, 12, e0170949, https://doi.org/10.1371/journal.pone.0170949, 2017.
Daniell, J. E., Schaefer, A. M., and Wenzel, F.: Losses Associated with Secondary Effects in Earthquakes, Front. Built Environ., 3, 30, https://doi.org/10.3389/fbuil.2017.00030, 2017.
Daoued, A. B., Mouhous-Voyneau, N., Hamdi, Y., and Sergent, P.: Development of a Probabilistic Multi-flood Hazard Approach Considering Uncertainties and Climate Change–Application to the Coastal Flooding of the Havre (France), Recent Advances in Environmental Science from the Euro-Mediterranean and Surrounding Regions (2nd Edition), Cham, 2011–2016, https://doi.org/10.1007/978-3-030-51210-1_315, 2021.
de Bruijn, K. M., Diermanse, F. L. M., and Beckers, J. V. L.: An advanced method for flood risk analysis in river deltas, applied to societal flood fatality risk in the Netherlands, Nat. Hazards Earth Syst. Sci., 14, 2767–2781, https://doi.org/10.5194/nhess-14-2767-2014, 2014.
Deidda, C., Rahimi, L., and de Michele, C.: Causes of dependence between extreme floods, Environ. Res. Lett., 16, 084002, https://doi.org/10.1088/1748-9326/AC07D5, 2021.
De Michele, C., Meroni, V., Rahimi, L., Deidda, C., and Ghezzi, A.: Dependence Types in a Binarized Precipitation Network, Geophys. Res. Lett., 47, e2020GL090196, https://doi.org/10.1029/2020GL090196, 2020.
De Ruiter, M. C., Couasnon, A., van den Homberg, M. J. C., Daniell, J. E., Gill, J. C., and Ward, P. J.: Why We Can No Longer Ignore Consecutive Disasters, Earth's Future, 8, e2019EF001425, https://doi.org/10.1029/2019EF001425, 2020.
Del-Rosal-Salido, J., Folgueras, P., Bermúdez, M., Ortega-Sánchez, M., and Losada, M.: Flood management challenges in transitional environments: Assessing the effects of sea-level rise on compound flooding in the 21st century, Coast. Eng., 167, 103872, https://doi.org/10.1016/J.COASTALENG.2021.103872, 2021.
Dietrich, J. C., Bunya, S., Westerink, J. J., Ebersole, B. A., Smith, J. M., Atkinson, J. H., Jensen, R., Resio, D. T., Luettich, R. A., Dawson, C., Cardone, V. J., Cox, A. T., Powell, M. D., Westerink, H. J., and Roberts, H. J.: A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part II: Synoptic Description and Analysis of Hurricanes Katrina and Rita, Mon. Weather Rev., 138, 378–404, https://doi.org/10.1175/2009mwr2907.1, 2010.
Dixon, M. J. and Tawn, J. A.: Extreme sea-levels at the UK A-class sites: site-by-site analyses, Proudman Oceanographic Laboratory, https://ntslf.org/sites/ntslf/files/pdf/other_reports/id65.pdf (last access: 17 July 2024), 1994.
Donges, J. F., Schleussner, C. F., Siegmund, J. F., and Donner, R. V.: Event coincidence analysis for quantifying statistical interrelationships between event time series, The European Physical Journal Special Topics, 225, 471–487, https://doi.org/10.1140/epjst/e2015-50233-y, 2016.
Dresback, K. M., Fleming, J. G., Blanton, B. O., Kaiser, C., Gourley, J. J., Tromble, E. M., Luettich, R. A., Kolar, R. L., Hong, Y., Van Cooten, S., Vergara, H. J., Flamig, Z. L., Lander, H. M., Kelleher, K. E., and Nemunaitis-Monroe, K. L.: Skill assessment of a real-time forecast system utilizing a coupled hydrologic and coastal hydrodynamic model during Hurricane Irene (2011), Cont. Shelf Res., 71, 78–94, https://doi.org/10.1016/J.CSR.2013.10.007, 2013.
Dykstra, S. L. and Dzwonkowski, B.: The Role of Intensifying Precipitation on Coastal River Flooding and Compound River-Storm Surge Events, Northeast Gulf of Mexico, Water Resour. Res., 57, e2020WR029363, https://doi.org/10.1029/2020WR029363, 2021.
EAA: Green Infrastructure and Flood Management, European Environment Agency (EEA), Copenhagen, Denmark, https://doi.org/10.2800/324289, 2017.
Easterling, D. R., Kunkel, K. E., Wehner, M. F., and Sun, L.: Detection and attribution of climate extremes in the observed record, Weather and Climate Extremes, 11, 17–27, https://doi.org/10.1016/j.wace.2016.01.001, 2016.
Eilander, D., Couasnon, A., Ikeuchi, H., Muis, S., Yamazaki, D., Winsemius, H. C., and Ward, P. J.: The effect of surge on riverine flood hazard and impact in deltas globally, Environ. Res. Lett., 15, 104007–104007, https://doi.org/10.1088/1748-9326/AB8CA6, 2020.
Eilander, D., Couasnon, A., Leijnse, T., Ikeuchi, H., Yamazaki, D., Muis, S., Dullaart, J., Winsemius, H. C., and Ward, P. J.: A globally-applicable framework for compound flood hazard modeling, EGUsphere, 1-40, https://doi.org/10.5194/egusphere-2022-149, 2022.
Eilander, D., Couasnon, A., Sperna Weiland, F. C., Ligtvoet, W., Bouwman, A., Winsemius, H. C., and Ward, P. J.: Modeling compound flood risk and risk reduction using a globally applicable framework: a pilot in the Sofala province of Mozambique, Nat. Hazards Earth Syst. Sci., 23, 2251–2272, https://doi.org/10.5194/nhess-23-2251-2023, 2023.
EM-DAT: International Disaster Database, https://www.emdat.be (last access: 17 July 2024), 2022.
Erikson, L. H., O'Neill, A. C., and Barnard, P. L.: Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS, J. Coastal Res., 85, 791–795, https://doi.org/10.2112/SI85-159.1, 2018.
Eshrati, L., Mahmoudzadeh, A., and Taghvaei, M.: Multi hazards risk assessment, a new methodology, International Journal of Health System and Disaster Management, 3, 79, https://www.researchgate.net/publication/331687882 (last access: 17 July 2024), 2015.
Familkhalili, R., Talke, S. A., and Jay, D. A.: Compound flooding in convergent estuaries: insights from an analytical model, Ocean Sci., 18, 1203–1220, https://doi.org/10.5194/os-18-1203-2022, 2022.
Fang, J., Wahl, T., Fang, J., Sun, X., Kong, F., and Liu, M.: Compound flood potential from storm surge and heavy precipitation in coastal China: dependence, drivers, and impacts, Hydrol. Earth Syst. Sci., 25, 4403–4416, https://doi.org/10.5194/hess-25-4403-2021, 2021.
Feng, Y. and Brubaker, K. L.: Change and Sea-Level Rise Using a One-Dimensional Hydraulic Model, J. Hydrol. Eng., 21, 05016015, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001378, 2016.
Ferrarin, C., Lionello, P., Orlić, M., Raicich, F., and Salvadori, G.: Venice as a paradigm of coastal flooding under multiple compound drivers, Sci. Rep., 12, 5754, https://doi.org/10.1038/s41598-022-09652-5, 2022.
Flick, R. E.: Joint Occurrence of High Tide and Storm Surge in California, World Marina'91, 52–60, https://escholarship.org/uc/item/0h62w9w3 (last access: 17 July 2024), 1991.
Galiatsatou, P. and Prinos, P.: Joint probability analysis of extreme wave heights and storm surges in the Aegean Sea in a changing climate, FLOODrisk 2016 – 3rd European Conference on Flood Risk Management, 7, 12, https://doi.org/10.1051/e3sconf/20160702002, 2016.
Gallien, T. W., Kalligeris, N., Delisle, M. P. C., Tang, B. X., Lucey, J. T. D., and Winters, M. A.: Coastal flood modeling challenges in defended urban backshores, Geosciences, 8, 450, https://doi.org/10.3390/geosciences8120450, 2018.
Gallina, V., Torresan, S., Critto, A., Sperotto, A., Glade, T., and Marcomini, A.: A review of multi-risk methodologies for natural hazards: Consequences and challenges for a climate change impact assessment, J. Environ. Manage., 168, 123–132, https://doi.org/10.1016/J.JENVMAN.2015.11.011, 2016.
Ganguli, P. and Merz, B.: Extreme Coastal Water Levels Exacerbate Fluvial Flood Hazards in Northwestern Europe, Sci. Rep., 9, 13165, https://doi.org/10.1038/s41598-019-49822-6, 2019a.
Ganguli, P. and Merz, B.: Trends in Compound Flooding in Northwestern Europe During 1901–2014, Geophys. Res. Lett., 46, 10810–10820, https://doi.org/10.1029/2019GL084220, 2019b.
Ganguli, P., Nandamuri, Y. R., and Chatterjee, C.: Analysis of persistence in the flood timing and the role of catchment wetness on flood generation in a large river basin in India, Theor. Appl. Climatol., 139, 373–388, https://doi.org/10.1007/s00704-019-02964-z, 2019.
Ganguli, P., Paprotny, D., Hasan, M., Güntner, A., and Merz, B.: Projected Changes in Compound Flood Hazard From Riverine and Coastal Floods in Northwestern Europe, Earth's Future, 8, e2020EF001752, https://doi.org/10.1029/2020EF001752, 2020.
Georgas, N., Blumberg, A., Herrington, T., Wakeman, T., Saleh, F., Runnels, D., Jordi, A., Ying, K., Yin, L., Ramaswamy, V., Yakubovskiy, A., Lopez, O., McNally, J., Schulte, J., and Wang, Y.: The stevens flood advisory system: operational H3Eflood forecasts for the greater New York/New Jersey metropolitan region, International Journal of Safety and Security Engineering, 6, 648–662, https://doi.org/10.2495/SAFE-V6-N3-648-662, 2016.
Ghanbari, M., Arabi, M., Kao, S. C., Obeysekera, J., and Sweet, W.: Climate Change and Changes in Compound Coastal-Riverine Flooding Hazard Along the U.S. Coasts, Earth's Future, 9, e2021EF002055, https://doi.org/10.1029/2021EF002055, 2021.
Gill, J. C. and Malamud, B. D.: Reviewing and visualizing the interactions of natural hazards, Rev. Geophys., 52, 680–722, https://doi.org/10.1002/2013RG000445, 2014.
Gill, J. C., Duncan, M., Ciurean, R., Smale, L., Stuparu, D., Schlumberger, J., de Ruiter, M., Tiggeloven, T., Torresan, S., Gottardo, S., Mysiak, J., Harris, R., Petrescu, E.-C., Girard, T., Khazai, B., Claassen, J., Dai, R., Champion, A., Daloz, A. S., Blanco Cipollone, F., Campillo Torres, C., Palomino Antolin, I., Ferrario, D., Tatman, S., Tijessen, A., Vaidya, S., Adesiyun, A., Goger, T., Angiuli, A., Audren, M., Machado, M., Hochrainer-Stigler, S., Šakiæ Trogrliæ, R., Daniell, J., Bulder, B., Krishna Swamy, S., Wiggelinkhuizen, E.-J., Díaz Pacheco, J., López Díez, A., Mendoza Jiménez, J., Padrón-Fumero, N., Appulo, L., Orth, R., Sillmann, J., and Ward, P.: MYRIAD-EU Project D1.2 Handbook of multi-hazard, multi-risk definitions and concepts, 75, http://nora.nerc.ac.uk/id/eprint/533237/ (last access: 17 July 2024), 2020.
Gori, A. and Lin, N.: Projecting compound flood hazard under climate change with physical models and joint probability methods, Earth's Future, 10, e2022EF003097, https://doi.org/10.1029/2022EF003097, 2022.
Gori, A., Lin, N., and Smith, J.: Assessing Compound Flooding From Landfalling Tropical Cyclones on the North Carolina Coast, Water Resour. Res., 56, e2019WR026788, https://doi.org/10.1029/2019WR026788, 2020a.
Gori, A., Lin, N., and Xi, D.: Tropical Cyclone Compound Flood Hazard Assessment: From Investigating Drivers to Quantifying Extreme Water Levels, Earth's Future, 8, e2020EF001660, https://doi.org/10.1029/2020EF001660, 2020b.
Gori, A., Lin, N., Xi, D., and Emanuel, K.: Tropical cyclone climatology change greatly exacerbates US extreme rainfall–surge hazard, Nat. Clim. Change, 12, 171–178, https://doi.org/10.1038/s41558-021-01272-7, 2022.
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, P. I. Civil Eng.-Mar. Eng., 170, 3–20, https://doi.org/10.1680/jmaen.2016.16, 2017.
Green, J.: Green et al. 2024 – Compound Flood Literature Review Database, Zenodo [data set], https://doi.org/10.5281/zenodo.14274658, 2024.
Guan, X., Vorogushyn, S., Apel, H., and Merz, B.: Assessing compound pluvial-fluvial flooding: Research status and ways forward, Water Security, 19, 100136, https://doi.org/10.1016/j.wasec.2023.100136, 2023.
Gutenson, J. L., Tavakoly, A. A., Islam, M. S., Wing, O. E. J., Lehman, W. P., Hamilton, C. O., Wahl, M. D., and Massey, T. C.: Comparison of estimated flood exposure and consequences generated by different event-based inland flood inundation maps, Nat. Hazards Earth Syst. Sci., 23, 261–277, https://doi.org/10.5194/nhess-23-261-2023, 2023.
Habel, S., Fletcher, C. H., Anderson, T. R., and Thompson, P. R.: Sea-Level Rise Induced Multi-Mechanism Flooding and Contribution to Urban Infrastructure Failure, Sci. Rep., 10, 1–12, https://doi.org/10.1038/s41598-020-60762-4, 2020.
Haigh, I. and Nicholls, R. J.: Coastal Flooding, Marine Climate Change Impacts Partnership, 98-104, https://doi.org/10.14465/2017.arc10.009-cof, 2017.
Haigh, I. D., Wadey, M. P., Wahl, T., Ozsoy, O., Nicholls, R. J., Brown, J. M., Horsburgh, K., and Gouldby, B.: Spatial and temporal analysis of extreme sea level and storm surge events around the coastline of the UK, Scientific Data, 3, 160107, https://doi.org/10.1038/SDATA.2016.107, 2016.
Haigh, I. D., Pickering, M. D., Green, J. A. M., Arbic, B. K., Arns, A., Dangendorf, S., Hill, D. F., Horsburgh, K., Howard, T., Idier, D., Jay, D. A., Jänicke, L., Lee, S. B., Müller, M., Schindelegger, M., Talke, S. A., Wilmes, S. B., and Woodworth, P. L.: The Tides They Are A-Changin': A Comprehensive Review of Past and Future Nonastronomical Changes in Tides, Their Driving Mechanisms, and Future Implications, Rev. Geophys., 58, e2018RG000636, https://doi.org/10.1029/2018RG000636, 2020.
Hall, T. M. and Jewson, S.: Statistical modelling of North Atlantic tropical cyclone tracks, Tellus A, 59, 486–498, https://doi.org/10.1111/j.1600-0870.2007.00240.x, 2007.
Hall, T. and Yonekura, E.: North American Tropical Cyclone Landfall and SST: A Statistical Model Study, J. Climate, 26, 8422–8439, https://doi.org/10.1175/JCLI-D-12-00756.1, 2013.
Hallegatte, S., Green, C., Nicholls, R. J., and Corfee-Morlot, J.: Future flood losses in major coastal cities, Nat. Clim. Change, 3, 802–806, https://doi.org/10.1038/NCLIMATE1979, 2013.
Hao, Z. and Singh, V. P.: Compound Events under Global Warming: A Dependence Perspective, J. Hydrol. Eng., 25, 03120001, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001991, 2020.
Hao, Z., Singh, V. P., and Hao, F.: Compound extremes in hydroclimatology: A review, Water, 10, 718, https://doi.org/10.3390/W10060718, 2018.
Harrison, L. M., Coulthard, T. J., Robins, P. E., and Lewis, M. J.: Sensitivity of Estuaries to Compound Flooding, Estuar. Coast., 45, 1250–1269, https://doi.org/10.1007/S12237-021-00996-1, 2022.
Hawkes, P.: Extreme water levels in estuaries and rivers: the combined influence of tides, river flows and waves, Defra/Environment Agency R&D Technical Report FD0206/TR1, HR Wallingford, https://assets.publishing.service.gov.uk/media/60254e8de90e070561b313da/Joint_probability_of_extreme_estuarine_water_levels__technical_report.pdf (last access: 17 July 2024), 2003.
Hawkes, P. J.: Joint probability analysis for estimation of extremes, J. Hydraul. Res., 46, 246–256, https://doi.org/10.1080/00221686.2008.9521958, 2008.
Hawkes, P. and Svensson, C.: Joint Probability: Dependence Mapping and Best Practice, Defra/Environment Agency R&D Interim Technical Report FD2308/TR1, HR Wallingford, https://assets.publishing.service.gov.uk/media/602bae1fe90e07055e422831/Technical_Report_-_Interim_Product__Joint_probability_dependence_mapping_and_best_practice__.pdf (last access: 17 July 2024), 2003.
Hawkes, P. and Svensson, C.: Use of Joint Probability Methods in Flood Management: A guide to best practice, Defra/Environment Agency R&D Technical Report FD2308/TR2, HR Wallingford, https://assets.publishing.service.gov.uk/media/602bae7ae90e070559970fbc/Use_of_joint_probability_methods_in_flood_management_A_guide_to_best_practice_technical_report.pdf (last access: 17 July 2024), 2006.
Hawkes, P. J., Gouldby, B. P., Tawn, J. A., and Owen, M. W.: The joint probability of waves and water levels in coastal engineering, J. Hydraul. Res., 40, 241–251, https://doi.org/10.1080/00221680209499940, 2002.
Helaire, L. T., Talke, S. A., Jay, D. A., and Chang, H.: Present and Future Flood Hazard in the Lower Columbia River Estuary: Changing Flood Hazards in the Portland-Vancouver Metropolitan Area, J. Geophys. Res.-Oceans, 125, e2019JC015928, https://doi.org/10.1029/2019JC015928, 2020.
Hemer, M. A., Wang, X. L., Church, J. A., and Swail, V. R.: Coordinating Global Ocean Wave Climate Projections, B. Am. Meteorol. Soc., 91, 451–454, https://doi.org/10.1175/2009BAMS2951.1, 2010.
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.
Herdman, L., Erikson, L., and Barnard, P.: Storm Surge Propagation and Flooding in Small Tidal Rivers during Events of Mixed Coastal and Fluvial Influence, Journal of Marine Science and Engineering, 6, 158–158, https://doi.org/10.3390/JMSE6040158, 2018.
Herring, D.: What is an “extreme event”? Is there evidence that global warming has caused or contributed to any particular extreme event?, National Oceanic and Atmospheric Administration (NOAA), https://www.climate.gov/news-features/climate-qa/what-extreme-event-there-evidence-global-warming-has-caused-or-contributed (last access: 1 January 2024), 2020.
Hewitt, K. and Burton, I.: Hazardousness of a place: A regional ecology of damaging events, University of Toronto Press, https://www.researchgate.net/publication/275689020 (last access: 17 July 2024), 1971.
Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S. J., Marzeion, B., Fettweis, X., Ionescu, C., and Levermann, A.: Coastal flood damage and adaptation costs under 21st century sea-level rise, P. Natl. Acad. Sci. USA, 111, 3292–3297, https://doi.org/10.1073/PNAS.1222469111, 2014.
Ho, F. P. and Myers, V. A.: Joint probability method of tide frequency analysis applied to Apalachicola Bay and St. George Sound, Florida, NOAA, https://repository.library.noaa.gov/view/noaa/33908/noaa_33908_DS1.pdf (last access: 17 July 2024), 1975.
Hoitink, A. J. F. and Jay, D. A.: Tidal river dynamics: Implications for deltas, Rev. Geophys., 54, 240–272, https://doi.org/10.1002/2015RG000507, 2016.
Holt, C.: What is groundwater flooding?, Environment Agency, UK, https://environmentagency.blog.gov.uk/2019/12/23/what-is-groundwater-flooding/ (last access: 1 January 2024), 2019.
Hsiao, S. C., Chiang, W. S., Jang, J. H., Wu, H. L., Lu, W. S., Chen, W. B., and Wu, Y. T.: Flood risk influenced by the compound effect of storm surge and rainfall under climate change for low-lying coastal areas, Sci. Total Environ., 764, 144439, https://doi.org/10.1016/j.scitotenv.2020.144439, 2021.
Huang, P. C.: An effective alternative for predicting coastal floodplain inundation by considering rainfall, storm surge, and downstream topographic characteristics, J. Hydrol., 607, 127544–127544, https://doi.org/10.1016/J.JHYDROL.2022.127544, 2022.
Huang, W., Ye, F., Zhang, Y. J., Park, K., Du, J., Moghimi, S., Myers, E., Pe'eri, S., Calzada, J. R., Yu, H. C., Nunez, K., and Liu, Z.: Compounding factors for extreme flooding around Galveston Bay during Hurricane Harvey, Ocean Model., 158, 101735, https://doi.org/10.1016/j.ocemod.2020.101735, 2021.
Hutton, E. W. H., Piper, M. D., and Tucker, G. E.: The Basic Model Interface 2.0: A standard interface for coupling numerical models in the geosciences, Journal of Open Source Software, 51, 5, https://doi.org/10.21105/joss.02317, 2020.
Idier, D., Bertin, X., Thompson, P., and Pickering, M.: Interactions Between Mean Sea Level, Tide, Surge, Waves and Flooding: Mechanisms and Contributions to Sea Level Variations at the Coast, Surv. Geophys., 40, 1603–1630, https://doi.org/10.1007/s10712-019-09549-5, 2019.
Ikeuchi, H., Hirabayashi, Y., Yamazaki, D., Muis, S., Ward, P. J., Winsemius, H. C., Verlaan, M., and Kanae, S.: Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model: Model development and its application to 2007 Cyclone Sidr in Bangladesh, J. Adv. Model. Earth Sy., 9, 1847–1862, https://doi.org/10.1002/2017MS000943, 2017.
IOTIC: What Causes Tsunami, Indian Ocean Tsunami InformationCentre (IOTIC), https://iotic.ioc-unesco.org/what-causes-tsunami/, (last access: 17 July 2024), 2020.
IPCC: Glossary of Terms, Cambridge University Press, Cambridge, United Kingdom, New York, USA, 555–564, https://doi.org/10.1017/CBO9781139177245.014, 2012.
IPCC: Annex II: Glossary, IPCC, Geneva, Switzerland, 117-130, ISBN 978-92-9169-143-2, https://archive.ipcc.ch/pdf/assessment-report/ar5/syr/SYR_AR5_FINAL_full_wcover.pdf (last access: 17 July 2024), 2014.
Jafarzadegan, K., Moradkhani, H., Pappenberger, F., Moftakhari, H., Bates, P., Abbaszadeh, P., Marsooli, R., Ferreira, C., Cloke, H. L., Ogden, F., and Duan, Q.: Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling, Rev. Geophys., 61, e2022RG000788, https://doi.org/10.1029/2022RG000788, 2023.
Jalili Pirani, F. and Najafi, M. R.: Recent Trends in Individual and Multivariate Compound Flood Drivers in Canada's Coasts, Water Resour. Res., 56, e2020WR027785, https://doi.org/10.1029/2020WR027785, 2020.
Jalili Pirani, F. and Najafi, M. R.: Characterizing compound flooding potential and the corresponding driving mechanisms across coastal environments, Stoch. Environ. Res. Risk A., 37, 1943–1961, https://doi.org/10.1007/s00477-022-02374-0, 2022a.
Jalili Pirani, F. and Najafi, M. R.: Multivariate Analysis of Compound Flood Hazard Across Canada's Atlantic, Pacific and Great Lakes Coastal Areas, Earth's Future, 10, e2022EF002655, https://doi.org/10.1029/2022EF002655, 2022b.
Jane, R., Cadavid, L., Obeysekera, J., and Wahl, T.: Multivariate statistical modelling of the drivers of compound flood events in south Florida, Nat. Hazards Earth Syst. Sci., 20, 2681–2699, https://doi.org/10.5194/nhess-20-2681-2020, 2020.
Jane, R., Wahl, T., Santos Victor, M., Misra Shubhra, K., and White Kathleen, D.: Assessing the Potential for Compound Storm Surge and Extreme River Discharge Events at the Catchment Scale with Statistical Models: Sensitivity Analysis and Recommendations for Best Practice, J. Hydrol. Eng., 27, 16, https://doi.org/10.1061/(ASCE)HE.1943-5584.0002154, 2022.
Jang, J. H. and Chang, T. H.: Flood risk estimation under the compound influence of rainfall and tide, J. Hydrol., 606, 127446, https://doi.org/10.1016/j.jhydrol.2022.127446, 2022.
Jasim, F. H., Vahedifard, F., Alborzi, A., Moftakhari, H., and AghaKouchak, A.: Effect of Compound Flooding on Performance of Earthen Levees, Geo-Congress 2020, 707–716, https://doi.org/10.1061/9780784482797.069, 2020.
Jenkins, L. J., Haigh, I. D., Camus, P., Pender, D., Sansom, J., Lamb, R., and Kassem, H.: The temporal clustering of storm surge, wave height, and high sea level exceedances around the UK coastline, Nat. Hazards, 115, 1761–1797, https://doi.org/10.1007/s11069-022-05617-z, 2023.
Jones, D.: Joint Probability Fluvial-Tidal Analyses: Structure Functions and Historical Emulation, Institute of Hydrology, https://nora.nerc.ac.uk/id/eprint/6919/ (last access: 17 July 2024), 1998.
Jong-Levinger, A., Banerjee, T., Houston, D., and Sanders, B. F.: Compound Post-Fire Flood Hazards Considering Infrastructure Sedimentation, Earth's Future, 10, e2022EF002670, https://doi.org/10.1029/2022EF002670, 2022.
Joyce, J., Chang, N. B., Harji, R., Ruppert, T., and Singhofen, P.: Cascade impact of hurricane movement, storm tidal surge, sea level rise and precipitation variability on flood assessment in a coastal urban watershed, Clim. Dynam., 51, 383–409, https://doi.org/10.1007/S00382-017-3930-4, 2018.
Juárez, B., Stockton, S. A., Serafin, K. A., and Valle-Levinson, A.: Compound Flooding in a Subtropical Estuary Caused by Hurricane Irma 2017, Geophys. Res. Lett., 49, e2022GL099360, https://doi.org/10.1029/2022GL099360, 2022.
Kappes, M., Keiler, M., and Glade, T.: From Single- to Multi-Hazard Risk analyses: a concept addressing emerging challenges, Mountain Risks International Conference, Firenze, Italy, 24–26 November 2010, 351–356, ISBN 2-95183317-1-5, 2010.
Kappes, M. S., Keiler, M., von Elverfeldt, K., and Glade, T.: Challenges of analyzing multi-hazard risk: A review, Nat. Hazards, 64, 1925–1958, https://doi.org/10.1007/S11069-012-0294-2, 2012.
Karamouz, M., Ahmadvand, F., and Zahmatkesh, Z.: Distributed Hydrologic Modeling of Coastal Flood Inundation and Damage: Nonstationary Approach, J. Irrig. Drain. Eng., 143, 04017019, https://doi.org/10.1061/(ASCE)IR.1943-4774.0001173, 2017.
Karamouz, M., Zahmatkesh, Z., Goharian, E., and Nazif, S.: Combined Impact of Inland and Coastal Floods: Mapping Knowledge Base for Development of Planning Strategies, J. Water Res. Plan. Man., 141, 04014098, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000497, 2014.
Katwala, A.: How Long Droughts Make Flooding Worse, WIRED, https://www.wired.co.uk/article/drought-causing-floods (last access: 17 July 2024), 2022.
Kerr, P. C., Westerink, J. J., Dietrich, J. C., Martyr, R. C., Tanaka, S., Resio, D. T., Smith, J. M., Westerink, H. J., Westerink, L. G., Wamsley, T., Ledden, M. v., and Jong, W. d.: Surge Generation Mechanisms in the Lower Mississippi River and Discharge Dependency, J. Waterw. Port C., 139, 326-335, https://doi.org/10.1061/(ASCE)WW.1943-5460.0000185, 2013.
Kew, S. F., Selten, F. M., Lenderink, G., and Hazeleger, W.: The simultaneous occurrence of surge and discharge extremes for the Rhine delta, Nat. Hazards Earth Syst. Sci., 13, 2017–2029, https://doi.org/10.5194/nhess-13-2017-2013, 2013.
Khalil, U., Yang, S., Sivakumar, M., Enever, K., Bin Riaz, M. Z., and Sajid, M.: Modelling the compound flood hydrodynamics under mesh convergence and future storm surge events in Brisbane River Estuary, Australia, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2021-284, 2022.
Khanal, S., Ridder, N., de Vries, H., Terink, W., and van den Hurk, B.: Storm Surge and Extreme River Discharge: A Compound Event Analysis Using Ensemble Impact Modeling, Front. Earth Sci., 7, 224, https://doi.org/10.3389/feart.2019.00224, 2019.
Khanam, M., Sofia, G., Koukoula, M., Lazin, R., Nikolopoulos, E. I., Shen, X., and Anagnostou, E. N.: Impact of compound flood event on coastal critical infrastructures considering current and future climate, Nat. Hazards Earth Syst. Sci., 21, 587–605, https://doi.org/10.5194/nhess-21-587-2021, 2021.
Khatun, A., Ganguli, P., Bisht, D. S., Chatterjee, C., and Sahoo, B.: Understanding the impacts of predecessor rain events on flood hazard in a changing climate, Hydrol. Process., 36, e14500, https://doi.org/10.1002/HYP.14500, 2022.
Kim, H., Villarini, G., Jane, R., Wahl, T., Misra, S., and Michalek, A.: On the generation of high-resolution probabilistic design events capturing the joint occurrence of rainfall and storm surge in coastal basins, Int. J. Climatol., 43, 761–771, https://doi.org/10.1002/JOC.7825, 2022.
Kim, B. and Sanders, B.: Dam-Break Flood Model Uncertainty Assessment: Case Study of Extreme Flooding with Multiple Dam Failures in Gangneung, South Korea, J. Hydraul. Eng., 142, 05016002, https://doi.org/10.1061/(ASCE)HY.1943-7900.0001097, 2016.
Kirezci, E., Young, I. R., Ranasinghe, R., Muis, S., Nicholls, R. J., Lincke, D., and Hinkel, J.: Projections of global-scale extreme sea levels and resulting episodic coastal flooding over the 21st Century, Sci. Rep., 10, 11629, https://doi.org/10.1038/s41598-020-67736-6, 2020.
Kirkpatrick, J. I. M. and Olbert, A. I.: Modelling the effects of climate change on urban coastal-fluvial flooding, J. Water Clim. Change, 11, 270-288, https://doi.org/10.2166/wcc.2020.166, 2020.
Klerk, W. J., Winsemius, H. C., Van Verseveld, W. J., Bakker, A. M. R., and Diermanse, F. L. M.: The co-incidence of storm surges and extreme discharges within the Rhine-Meuse Delta, Environ. Res. Lett., 10, 035005, https://doi.org/10.1088/1748-9326/10/3/035005, 2015.
Komendantova, N., Mrzyglocki, R., Mignan, A., Khazai, B., Wenzel, F., Patt, A., and Fleming, K.: Multi-hazard and multi-risk decision-support tools as a part of participatory risk governance: Feedback from civil protection stakeholders, Int. J. Disast. Risk Re., 8, 50–67, https://doi.org/10.1016/J.IJDRR.2013.12.006, 2014.
Koskinas, A., Tegos, A., Tsira, P., Dimitriadis, P., Iliopoulou, T., Papanicolaou, P., Koutsoyiannis, D., and Williamson, T.: Insights into the Oroville Dam 2017 Spillway Incident, https://doi.org/10.3390/geosciences9010037, 2019.
Kowalik, Z. and Proshutinsky, A.: Tsunami-tide interactions: A Cook Inlet case study, Cont. Shelf Res., 30, 633–642, https://doi.org/10.1016/j.csr.2009.10.004, 2010.
Kuleshov, Y., McGree, S., Jones, D., Charles, A., Cottrill, D., Prakash, B., Atalifo, T., Nihmei, S., Lagomauitumua, F., and Seuseu, S.: Extreme Weather and Climate Events and Their Impacts on Island Countries in the Western Pacific: Cyclones, Floods and Droughts, Atmos. Clim. Sci., 4, 803–818, https://doi.org/10.4236/acs.2014.45071, 2014.
Kumbier, K., Carvalho, R. C., Vafeidis, A. T., and Woodroffe, C. D.: Investigating compound flooding in an estuary using hydrodynamic modelling: a case study from the Shoalhaven River, Australia, Nat. Hazards Earth Syst. Sci., 18, 463–477, https://doi.org/10.5194/nhess-18-463-2018, 2018.
Kupfer, S., Santamaria-Aguilar, S., van Niekerk, L., Lück-Vogel, M., and Vafeidis, A. T.: Investigating the interaction of waves and river discharge during compound flooding at Breede Estuary, South Africa, Nat. Hazards Earth Syst. Sci., 22, 187–205, https://doi.org/10.5194/nhess-22-187-2022, 2022.
Kudryavtseva, N., Räämet, A., and Soomere, T.: Coastal Flooding: Joint Probability of Extreme Water Levels and Waves along the Baltic Sea Coast, J. Coastal Res., 95, 1146–1151, https://doi.org/10.2112/SI95-222.1, 2020.
Lai, Y., Li, J., Gu, X., Liu, C., and Chen, Y. D.: Global compound floods from precipitation and storm surge: Hazards and the roles of cyclones, J. Climate, 34, 8319–8339, https://doi.org/10.1175/JCLI-D-21-0050.1, 2021a.
Lai, Y., Li, Q., Li, J., Zhou, Q., Zhang, X., and Wu, G.: Evolution of Frequency and Intensity of Concurrent Heavy Precipitation and Storm Surge at the Global Scale: Implications for Compound Floods, Frontiers in Earth Science, 9, 660359, https://doi.org/10.3389/feart.2021.660359, 2021b.
Láng-Ritter, J., Berenguer, M., Dottori, F., Kalas, M., and Sempere-Torres, D.: Compound flood impact forecasting: integrating fluvial and flash flood impact assessments into a unified system, Hydrol. Earth Syst. Sci., 26, 689–709, https://doi.org/10.5194/hess-26-689-2022, 2022.
Lanzoni, S. and Seminara, G.: On tide propagation in convergent estuaries, J. Geophys. Res.-Oceans, 103, 30793–30812, https://doi.org/10.1029/1998JC900015, 1998.
Latif, S. and Mustafa, F.: Copula-based multivariate flood probability construction: a review, Arab. J. Geosci., 13, 132, https://doi.org/10.1007/s12517-020-5077-6, 2020.
Latif, S. and Simonovic, S. P.: Trivariate Joint Distribution Modelling of Compound Events Using the Nonparametric D-Vine Copula Developed Based on a Bernstein and Beta Kernel Copula Density Framework, Hydrology, 9, 221, https://doi.org/10.3390/hydrology9120221, 2022a.
Latif, S. and Simonovic, S. P.: Parametric Vine Copula Framework in the Trivariate Probability Analysis of Compound Flooding Events, Water, 14, 2214, https://doi.org/10.3390/W14142214, 2022b.
Latif, S. and Simonovic, S. P.: Compounding joint impact of rainfall, storm surge and river discharge on coastal flood risk: an approach based on 3D fully nested Archimedean copulas, Environ. Earth Sci., 82, 63, https://doi.org/10.1007/s12665-022-10719-9, 2023.
Lavigne, F., Paris, R., Grancher, D., Wassmer, P., Brunstein, D., Vautier, F., Leone, F., Flohic, F., De Coster, B., Gunawan, T., Gomez, C., Setiawan, A., Cahyadi, R., and Fachrizal: Reconstruction of Tsunami Inland Propagation on December 26, 2004 in Banda Aceh, Indonesia, through Field Investigations, Pure Appl. Geophys., 166, 259–281, https://doi.org/10.1007/s00024-008-0431-8, 2009.
Lawrence, D., Paquet, E., Gailhard, J., and Fleig, A. K.: Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall–snowmelt flood regimes, Nat. Hazards Earth Syst. Sci., 14, 1283–1298, https://doi.org/10.5194/nhess-14-1283-2014, 2014.
Lee, C., Hwang, S., Do, K., and Son, S.: Increasing flood risk due to river runoff in the estuarine area during a storm landfall, Estuar. Coast. Shelf S., 221, 104–118, https://doi.org/10.1016/J.ECSS.2019.03.021, 2019.
Lee, S., Kang, T., Sun, D., and Park, J. J.: Enhancing an analysis method of compound flooding in coastal areas by linking flow simulation models of coasts and watershed, Sustainability, 12, 6572, https://doi.org/10.3390/SU12166572, 2020.
Leijnse, T., van Ormondt, M., Nederhoff, K., and van Dongeren, A.: Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes, Coast. Eng., 163, 103796, https://doi.org/10.1016/j.coastaleng.2020.103796, 2021.
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, Wires Clim. Change, 5, 113–128, https://doi.org/10.1002/WCC.252, 2014.
Leone, F., Lavigne, F., Paris, R., Denain, J.-C., and Vinet, F.: A spatial analysis of the December 26th, 2004 tsunami-induced damages: Lessons learned for a better risk assessment integrating buildings vulnerability, Appl. Geogr., 31, 363–375, https://doi.org/10.1016/j.apgeog.2010.07.009, 2011.
Lex, A., Gehlenborg, N., Strobelt, H., Vuillemot, R., and Pfister, H.: UpSet: Visualization of Intersecting Sets, IEEE T. Vis. Comput. Gr., 20, 1983–1992, https://doi.org/10.1109/TVCG.2014.2346248, 2014.
Li, L. and Jun, K. S.: The Joint Effect of River Flow and Tides on the Determination of Design Flood Levels in the Han River, J. Coastal Res., 95, 257–261, https://doi.org/10.2112/SI95-050.1, 2020.
Li, Y., Shen, P., Yan, Y., and Zhou, W.-H.: Flood risk assessment of artificial islands under compound rain-tide-wind effects during tropical cyclones, J. Hydrol., 615, 128736, https://doi.org/10.1016/J.JHYDROL.2022.128736, 2022.
Lian, J. J., Xu, K., and Ma, C.: Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China, Hydrol. Earth Syst. Sci., 17, 679–689, https://doi.org/10.5194/hess-17-679-2013, 2013.
Lian, J., Xu, H., Xu, K., and Ma, C.: Optimal management of the flooding risk caused by the joint occurrence of extreme rainfall and high tide level in a coastal city, Nat. Hazards, 89, 183–200, https://doi.org/10.1007/s11069-017-2958-4, 2017.
Liang, H. and Zhou, X.: Impact of Tides and Surges on Fluvial Floods in Coastal Regions, Remote Sensing, 14, 5779–5779, https://doi.org/10.3390/RS14225779, 2022.
Lin, N., Smith, J. A., Villarini, G., Marchok, T. P., and Baeck, M. L.: Modeling extreme rainfall, winds, and surge from Hurricane Isabel (2003), Weather Forecast., 25, 1342–1361, https://doi.org/10.1175/2010WAF2222349.1, 2010.
Liu, Q., Xu, H., and Wang, J.: Assessing tropical cyclone compound flood risk using hydrodynamic modelling: a case study in Haikou City, China, Nat. Hazards Earth Syst. Sci., 22, 665–675, https://doi.org/10.5194/nhess-22-665-2022, 2022.
Loganathan, G. V., Kuo, C. Y., and Yannaccone, J.: Joint Probability Distribution of Streamflows and Tides in Estuaries, Hydrol. Res., 18, 237–246, https://doi.org/10.2166/NH.1987.0017, 1987.
Loveland, M., Kiaghadi, A., Dawson, C. N., Rifai, H. S., Misra, S., Mosser, H., and Parola, A.: Developing a Modeling Framework to Simulate Compound Flooding: When Storm Surge Interacts With Riverine Flow, Frontiers in Climate, 2, 609610, https://doi.org/10.3389/fclim.2020.609610, 2021.
Lu, W., Tang, L., Yang, D., Wu, H., and Liu, Z.: Compounding Effects of Fluvial Flooding and Storm Tides on Coastal Flooding Risk in the Coastal-Estuarine Region of Southeastern China, Atmosphere, 13, 238, https://doi.org/10.3390/ATMOS13020238, 2022.
Lucey, J. T. D. and Gallien, T. W.: Characterizing multivariate coastal flooding events in a semi-arid region: the implications of copula choice, sampling, and infrastructure, Nat. Hazards Earth Syst. Sci., 22, 2145–2167, https://doi.org/10.5194/nhess-22-2145-2022, 2022.
Lyddon, C., Robins, P., Lewis, M., Barkwith, A., Vasilopoulos, G., Haigh, I., and Coulthard, T.: Historic Spatial Patterns of Storm-Driven Compound Events in UK Estuaries, Estuar. Coast., 30, 30–56, https://doi.org/10.1007/S12237-022-01115-4, 2022.
Manneela, S. and Kumar, S.: Overview of the Hunga Tonga-Hunga Ha'apai Volcanic Eruption and Tsunami, J. Geol. Soc. India, 98, 299–304, https://doi.org/10.1007/s12594-022-1980-7, 2022.
Manoj J, A., Guntu, R. K., and Agarwal, A.: Spatiotemporal dependence of soil moisture and precipitation over India, J. Hydrol., 610, 127898–127898, https://doi.org/10.1016/J.JHYDROL.2022.127898, 2022.
Mantz, P. A. and Wakeling, H. L.: Forecasting Flood Levels for Joint Events of Rainfall and Tidal Surge Flooding using Extreme Values Statistics, P. Civil Eng., 67, 31–50, https://doi.org/10.1680/iicep.1979.2315, 1979.
Mark, O., Weesakul, S., Apirumanekul, C., Aroonnet, S. B., and Djordjeviæ, S.: Potential and limitations of 1D modelling of urban flooding, J. Hydrol., 299, 284–299, https://doi.org/10.1016/j.jhydrol.2004.08.014, 2004.
Martyr, R. C., Dietrich, J. C., Westerink, J. J., Kerr, P. C., Dawson, C., Smith, J. M., Pourtaheri, H., Powell, N., Ledden, M. V., Tanaka, S., Roberts, H. J., Westerink, H. J., and Westerink, L. G.: Simulating Hurricane Storm Surge in the Lower Mississippi River under Varying Flow Conditions, J. Hydraul. Eng., 139, 492–501, https://doi.org/10.1061/(ASCE)HY.1943-7900.0000699, 2013.
Mashriqui, H. S., Halgren, J. S., and Reed, S. M.: 1D River Hydraulic Model for Operational Flood Forecasting in the Tidal Potomac: Evaluation for Freshwater, Tidal, and Wind-Driven Events, J. Hydraul. Eng., 140, 04014005, https://doi.org/10.1061/(ASCE)HY.1943-7900.0000862, 2014.
Mashriqui, H. S., Reed, S., and Aschwanden, C.: Toward Modeling of River-Estuary-Ocean Interactions to Enhance Operational River Forecasting in the NOAA National Weather Service, 2nd Joint Federal Interagency Conference, Las Vegas, NV, https://hdsc.nws.noaa.gov/pub/hdsc/data/papers/articles/HRL_Pubs_PDF_May12_2009/New_Scans_December_2010/11F_Mashriqui_12_31_09.pdf (last access: 17 July 2024), 2010.
Masina, M., Lamberti, A., and Archetti, R.: Coastal flooding: A copula based approach for estimating the joint probability of water levels and waves, Coast. Eng., 97, 37–52, https://doi.org/10.1016/J.COASTALENG.2014.12.010, 2015.
Maskell, J., Horsburgh, K., Lewis, M., and Bates, P.: Investigating River–Surge Interaction in Idealised Estuaries, J. Coastal Res., 30, 248–259, https://doi.org/10.2112/JCOASTRES-D-12-00221.1, 2014.
Maymandi, N., Hummel, M. A., and Zhang, Y.: Compound Coastal, Fluvial, and Pluvial Flooding During Historical Hurricane Events in the Sabine–Neches Estuary, Texas, Water Resour. Res., 58, e2022WR033144, https://doi.org/10.1029/2022WR033144, 2022.
Mazas, F., Kergadallan, X., Garat, P., and Hamm, L.: Applying POT methods to the Revised Joint Probability Method for determining extreme sea levels, Coast. Eng., 91, 140–150, https://doi.org/10.1016/j.coastaleng.2014.05.006, 2014.
McGuigan, K., Webster, T., and Collins, K.: A Flood Risk Assessment of the LaHave River Watershed, Canada Using GIS Techniques and an Unstructured Grid Combined River-Coastal Hydrodynamic Model, Journal of Marine Science and Engineering, 3, 1093–1116, https://doi.org/10.3390/jmse3031093, 2015.
McInnes, K. L., Hubbert, G. D., Abbs, D. J., and Oliver, S. E.: A numerical modelling study of coastal flooding, Meteorol. Atmos. Phys., 80, 217–233, https://doi.org/10.1007/S007030200027, 2002.
Melone, A. M.: Flood Producing Mechanisms in Coastal British Columbia, Can. Water Resour. J., 10, 46–64, https://doi.org/10.4296/cwrj1003046, 1985.
Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., Domeisen, D. I. V., Feser, F., Koszalka, I., Kreibich, H., Pantillon, F., Parolai, S., Pinto, J. G., Punge, H. J., Rivalta, E., Schröter, K., Strehlow, K., Weisse, R., and Wurpts, A.: Impact Forecasting to Support Emergency Management of Natural Hazards, Rev. Geophys., 58, e2020RG000704, https://doi.org/10.1029/2020RG000704, 2020.
Meyers, S. D., Landry, S., Beck, M. W., and Luther, M. E.: Using logistic regression to model the risk of sewer overflows triggered by compound flooding with application to sea level rise, Urban Clim., 35, 100752, https://doi.org/10.1016/j.uclim.2020.100752, 2021.
Ming, X., Liang, Q., Dawson, R., Xia, X., and Hou, J.: A quantitative multi-hazard risk assessment framework for compound flooding considering hazard inter-dependencies and interactions, J. Hydrol., 607, 127477, https://doi.org/10.1016/j.jhydrol.2022.127477, 2022.
Mishra, A., Alnahit, A., and Campbell, B.: Impact of land uses, drought, flood, wildfire, and cascading events on water quality and microbial communities: A review and analysis, J. Hydrol., 596, 125707, https://doi.org/10.1016/j.jhydrol.2020.125707, 2021.
Mishra, A., Mukherjee, S., Merz, B., Singh, V. P., Wright, D. B., Villarini, G., Paul, S., Kumar, D. N., Khedun, C. P., Niyogi, D., Schumann, G., and Stedinger, J. R.: An Overview of Flood Concepts, Challenges, and Future Directions, J. Hydrol. Eng., 27, 03122001, https://doi.org/10.1061/(ASCE)HE.1943-5584.0002164, 2022.
Modrakowski, L.-C., Su, J., and Nielsen, A. B.: The Precautionary Principles of the Potential Risks of Compound Events in Danish Municipalities, Frontiers in Climate, 3, 772629, https://doi.org/10.3389/fclim.2021.772629, 2022.
Moftakhari, H., Schubert, J. E., AghaKouchak, A., Matthew, R. A., and Sanders, B. F.: Linking statistical and hydrodynamic modeling for compound flood hazard assessment in tidal channels and estuaries, Adv. Water Resour., 128, 28–38, https://doi.org/10.1016/j.advwatres.2019.04.009, 2019.
Moftakhari, H. R., Salvadori, G., AghaKouchak, A., Sanders, B. F., and Matthew, R. A.: Compounding effects of sea level rise and fluvial flooding, P. Natl. Acad. Sci. USA, 114, 9785–9790, https://doi.org/10.1073/PNAS.1620325114, 2017.
Mohammadi, S., Bensi, M., Kao, S.-C., and Deneale, S. T.: Multi-Mechanism Flood Hazard Assessment: Example Use Case Studies, https://doi.org/10.2172/1637939, 2021.
Mohanty, M. P., Sherly, M. A., Ghosh, S., and Karmakar, S.: Tide-rainfall flood quotient: an incisive measure of comprehending a region's response to storm-tide and pluvial flooding, Environ. Res. Lett., 15, 064029, https://doi.org/10.1088/1748-9326/ab8092, 2020.
Munich Re: Topics Geo natural catastrophes 2016: analyses, assessments, positions, Munich Reinsurance, https://www.preventionweb.net/publication/topics-geo-natural-catastrophes-2016-analyses-assessments-positions (last access: 17 July 2024), 2017.
Muñoz, D. F., Moftakhari, H., and Moradkhani, H.: Compound Effects of Flood Drivers and Wetland Elevation Correction on Coastal Flood Hazard Assessment, Water Resour. Res., 56, e2020WR027544, https://doi.org/10.1029/2020WR027544, 2020.
Muñoz, D. F., Muñoz, P., Moftakhari, H., and Moradkhani, H.: From local to regional compound flood mapping with deep learning and data fusion techniques, Sci. Total Environ., 782, 146927, https://doi.org/10.1016/j.scitotenv.2021.146927, 2021.
Muñoz, D. F., Abbaszadeh, P., Moftakhari, H., and Moradkhani, H.: Accounting for uncertainties in compound flood hazard assessment: The value of data assimilation, Coast. Eng., 171, 104057, https://doi.org/10.1016/j.coastaleng.2021.104057, 2022a.
Muñoz, D. F., Moftakhari, H., Kumar, M., and Moradkhani, H.: Compound Effects of Flood Drivers, Sea Level Rise, and Dredging Protocols on Vessel Navigability and Wetland Inundation Dynamics, Frontiers in Marine Science, 9, 906376, https://doi.org/10.3389/fmars.2022.906376, 2022b.
Myers, V. A.: Joint probability method of tide frequency analysis applied to Atlantic City and Long Beach Island, N.J, Environmental Sciences Services Administration (ESSA), https://doi.org/10.7282/T3ZK5DVQ, 1970.
Najafi, M. R., Zhang, Y., and Martyn, N.: A flood risk assessment framework for interdependent infrastructure systems in coastal environments, Sustain. Cities Soc., 64, 102516, https://doi.org/10.1016/j.scs.2020.102516, 2021.
Naseri, K. and Hummel, M. A.: A Bayesian copula-based nonstationary framework for compound flood risk assessment along US coastlines, J. Hydrol., 610, 128005, https://doi.org/10.1016/j.jhydrol.2022.128005, 2022.
Nash, S., Comer, J., Olbert, A., and Hartnett, M.: High Resolution Urban Flood Modelling: A Case Study of Cork City, Ireland, EPiC Series in Engineering, 3, 1495–1504, https://doi.org/10.29007/RZWJ, 2018.
Nasr, A. A., Wahl, T., Rashid, M. M., Camus, P., and Haigh, I. D.: Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline, Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, 2021.
NCEI: U.S. Billion-Dollar Weather and Climate Disasters, National Centers for Environmental Information (NCEI) [data set], https://doi.org/10.25921/stkw-7w73, 2023.
Neumann, B., Vafeidis, A. T., Zimmermann, J., and Nicholls, R. J.: Future Coastal Population Growth and Exposure to Sea-Level Rise and Coastal Flooding – A Global Assessment, PLOS ONE, 10, e0118571, https://doi.org/10.1371/journal.pone.0118571, 2015.
Olabarrieta, M., Warner, J. C., Armstrong, B., Zambon, J. B., and He, R.: Ocean–atmosphere dynamics during Hurricane Ida and Nor’Ida: An application of the coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system, Ocean Model., 43–44, 112–137, https://doi.org/10.1016/j.ocemod.2011.12.008, 2012.
Olbert, A. I., Nash, S., Cunnane, C., and Hartnett, M.: Tide–surge interactions and their effects on total sea levels in Irish coastal waters, Ocean Dynam., 63, 599–614, https://doi.org/10.1007/s10236-013-0618-0, 2013.
Olbert, A. I., Comer, J., Nash, S., and Hartnett, M.: High-resolution multi-scale modelling of coastal flooding due to tides, storm surges and rivers inflows. A Cork City example, Coast. Eng., 121, 278–296, https://doi.org/10.1016/J.COASTALENG.2016.12.006, 2017.
Oppenheimer, M., Glavovic, B., Hinkel, J., van de Wal, R., Magnan, A., Abd-EIgawad, A., Cai, R., Cifuentes-Jara, M., DeConto, R., Ghosh, T., Hay, J., Isla, F., Marzeion, B., Meyssignac, B., and Sebesvari, Z.: Sea Level Rise and Implications for Low-Lying Islands, Coasts and Communities, Intergovernmental Panel on Climate Change, Geneva, 321–446, https://doi.org/10.1017/9781009157964.006, 2019.
Orton, P., Georgas, N., Blumberg, A., and Pullen, J.: Detailed modeling of recent severe storm tides in estuaries of the New York City region, J. Geophys. Res.-Oceans, 117, C09030, https://doi.org/10.1029/2012JC008220, 2012.
Orton, P., Conticello, F., Cioffi, F., Hall, T., Georgas, N., Lall, U., Blumberg, A., Conticello, F., Cioffi, F., Hall, T., Georgas, N., Lall, U., and Blumberg, A.: Hazard Assessment from Storm Tides and Rainfall on a Tidal River Estuary, 36th IAHR World Congress, The Hague, Netherlands, 1–10, https://ntrs.nasa.gov/api/citations/20150021054/downloads/20150021054.pdf (last access: 17 July 2024), 2015.
Orton, P. M., Hall, T. M., Talke, S. A., Blumberg, A. F., Georgas, N., and Vinogradov, S.: A validated tropical-extratropical flood hazard assessment for New York Harbor, J. Geophys. Res.-Oceans, 121, 8904–8929, https://doi.org/10.1002/2016JC011679, 2016.
Orton, P. M., Conticello, F. R., Cioffi, F., Hall, T. M., Georgas, N., Lall, U., Blumberg, A. F., and MacManus, K.: Flood hazard assessment from storm tides, rain and sea level rise for a tidal river estuary, Nat. Hazards, 102, 729–757, https://doi.org/10.1007/S11069-018-3251-X, 2018.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., and Moher, D.: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews, BMJ, 372, n71, https://doi.org/10.1136/bmj.n71, 2021.
Pandey, S., Rao, A. D., and Haldar, R.: Modeling of Coastal Inundation in Response to a Tropical Cyclone Using a Coupled Hydraulic HEC-RAS and ADCIRC Model, J. Geophys. Res.-Oceans, 126, e2020JC016810, https://doi.org/10.1029/2020JC016810, 2021.
Paprotny, D., Vousdoukas, M. I., Morales-Nápoles, O., Jonkman, S. N., and Feyen, L.: Pan-European hydrodynamic models and their ability to identify compound floods, Nat. Hazards, 101, 933–957, https://doi.org/10.1007/S11069-020-03902-3, 2020.
Park, G. H., Kim, I. C., Suh, K. S., and Lee, J. L.: Prediction of Storm Surge and Runoff Combined Inundation, J. Coast. Res., Proceedings of the 11th International Coastal Symposium, Szczecin, Poland, 1150–1154, https://www.jstor.org/stable/pdf/26482354.pdf (last access: 17 July 2024), 2011.
Pasquier, U., He, Y., Hooton, S., Goulden, M., and Hiscock, K. M.: An integrated 1D–2D hydraulic modelling approach to assess the sensitivity of a coastal region to compound flooding hazard under climate change, Nat. Hazards, 98, 915–937, https://doi.org/10.1007/S11069-018-3462-1, 2019.
Peña, F., Nardi, F., Melesse, A., Obeysekera, J., Castelli, F., Price, R. M., Crowl, T., and Gonzalez-Ramirez, N.: Compound flood modeling framework for surface–subsurface water interactions, Nat. Hazards Earth Syst. Sci., 22, 775–793, https://doi.org/10.5194/nhess-22-775-2022, 2022.
Pescaroli, G. and Alexander, D.: A definition of cascading disasters and cascading effects: Going beyond the “toppling dominos” metaphor, Global Risk Forum GRF Davos, Planet@Risk, 2, 58–67, https://discovery.ucl.ac.uk/id/eprint/1465510/ (last access: 17 July 2024), 2015.
Pescaroli, G. and Alexander, D.: Understanding Compound, Interconnected, Interacting, and Cascading Risks: A Holistic Framework, Risk Anal., 38, 2245–2257, https://doi.org/10.1111/RISA.13128, 2018.
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.
Petroliagkis, T. I., Voukouvalas, E., Disperati, J., Bidlot, J., and European Commission. Joint Research Center: Joint Probabilities of Storm Surge, Significant Wave Height and River Discharge Components of Coastal Flooding Events. Utilising statistical dependence methodologies & techniques, Publications Office of the European Union, ISBN 978-92-79-57666-9, https://doi.org/10.2788/951583, 2016.
Phillips, M.: The Dynamics of the Upper Ocean, J. Fluid Mech., 29, 261, https://doi.org/10.1017/S0022112067211193, 1966.
Phillips, R. C., Samadi, S., Hitchcock, D. B., Meadows, M. E., and Wilson, C. A. M. E.: The Devil Is in the Tail Dependence: An Assessment of Multivariate Copula-Based Frameworks and Dependence Concepts for Coastal Compound Flood Dynamics, Earth's Future, 10, e2022EF002705, https://doi.org/10.1029/2022EF002705, 2022.
Pickering, M. D., Horsburgh, K. J., Blundell, J. R., Hirschi, J. J. M., Nicholls, R. J., Verlaan, M., and Wells, N. C.: The impact of future sea-level rise on the global tides, Cont. Shelf Res., 142, 50–68, https://doi.org/10.1016/j.csr.2017.02.004, 2017.
Piecuch, C. G., Coats, S., Dangendorf, S., Landerer, F. W., Reager, J. T., Thompson, P. R., and Wahl, T.: High-Tide Floods and Storm Surges During Atmospheric Rivers on the US West Coast, Geophys. Res. Lett., 49, e2021GL096820, https://doi.org/10.1029/2021GL096820, 2022.
Pietrafesa, L. J., Zhang, H., Bao, S., Gayes, P. T., and Hallstrom, J. O.: Coastal flooding and inundation and inland flooding due to downstream blocking, Journal of Marine Science and Engineering, 7, 336, https://doi.org/10.3390/JMSE7100336, 2019.
Plane, E., Hill, K., and May, C.: A Rapid Assessment Method to Identify Potential Groundwater Flooding Hotspots as Sea Levels Rise in Coastal Cities, https://doi.org/10.3390/w11112228, 2019.
Poulos, S., Karditsa, A., Hatzaki, M., Tsapanou, A., Papapostolou, C., and Chouvardas, K.: An Insight into the Factors Controlling Delta Flood Events: The Case of the Evros River Deltaic Plain (NE Aegean Sea), Water, 14, 497, https://doi.org/10.3390/W14030497, 2022.
Prandle, D.: Storm surges in the southern North Sea and River Thames, P. R. Soc. Lond. A., 344, 509–539, https://doi.org/10.1098/rspa.1975.0117, 1975.
Prandle, D. and Wolf, J.: The interaction of surge and tide in the North Sea and River Thames, Geophys. J. Int., 55, 203–216, https://doi.org/10.1111/j.1365-246X.1978.tb04758.x, 1978.
Preisser, M., Passalacqua, P., Bixler, R. P., and Hofmann, J.: Intersecting near-real time fluvial and pluvial inundation estimates with sociodemographic vulnerability to quantify a household flood impact index, Hydrology and Earth System Sciences, 26, 3941-3964, https://doi.org/10.5194/hess-26-3941-2022, 2022.
Pugh, D. T.: Tides, surges and mean sea-level, John Wiley & Sons Ltd, Chichester, 472 pp.1987.
Pugh, D. T. and Vassie, J. M.: Applications of the Joint Probability Method for Extreme Sea Level Computations, Proceedings of the Institution of Civil Engineers, 69, 959-975, https://doi.org/10.1680/iicep.1980.2179, 1980.
Qiang, Y., He, J., Xiao, T., Lu, W., Li, J., and Zhang, L.: Coastal town flooding upon compound rainfall-wave overtopping-storm surge during extreme tropical cyclones in Hong Kong, Journal of Hydrology: Regional Studies, 37, https://doi.org/10.1016/j.ejrh.2021.100890, 2021.
Qiu, J., Liu, B., Yang, F., Wang, X., and He, X.: Quantitative Stress Test of Compound Coastal-Fluvial Floods in China's Pearl River Delta, Earth's Future, 10, e2021EF002638, https://doi.org/10.1029/2021EF002638, 2022.
Quagliolo, C., Comino, E., and Pezzoli, A.: Experimental Flash Floods Assessment Through Urban Flood Risk Mitigation (UFRM) Model: The Case Study of Ligurian Coastal Cities, Front. Water, 3, 663378, https://doi.org/10.3389/FRWA.2021.663378, 2021.
Rahimi, R., Tavakol-Davani, H., Graves, C., Gomez, A., and Valipour, M. F.: Compound inundation impacts of coastal climate change: Sea-level rise, groundwater rise, and coastal precipitation, Water, 12, https://doi.org/10.3390/W12102776, 2020.
Ray, T., Asce, M., Stepinski, E., Sebastian, A., Bedient, P. B., and Asce, F.: Dynamic Modeling of Storm Surge and Inland Flooding in a Texas Coastal Floodplain, J. Hydraul. Eng., 137, 1103–1110, https://doi.org/10.1061/(ASCE)HY.1943-7900.0000398, 2011.
Raymond, C., Horton, R. M., Zscheischler, J., Martius, O., AghaKouchak, A., Balch, J., Bowen, S. G., Camargo, S. J., Hess, J., Kornhuber, K., Oppenheimer, M., Ruane, A. C., Wahl, T., and White, K.: Understanding and managing connected extreme events, Nature Climate Change, 10, 611-621, https://doi.org/10.1038/s41558-020-0790-4, 2020.
Razmi, A., Mardani-Fard, H. A., Golian, S., and Zahmatkesh, Z.: Time-Varying Univariate and Bivariate Frequency Analysis of Nonstationary Extreme Sea Level for New York City, Environ. Process., 9, 8, https://doi.org/10.1007/S40710-021-00553-9, 2022.
Reimann, L., Vafeidis, A. T., and Honsel, L. E.: Population development as a driver of coastal risk: Current trends and future pathways, Cambridge Prisms: Coastal Futures, 1, e14, https://doi.org/10.1017/cft.2023.3, 2023.
ReliefWeb: South America: Floods and Landslides – Nov 2015–Dec 2016, UN Office for the Coordination of Humanitarian Affairs, https://reliefweb.int/disaster/fl-2015-000171-pry (last access: 17 July 2024), 2016.
ReliefWeb: South America: Floods and Landslides – Dec 2016, UN Office for the Coordination of Humanitarian Affairs, https://reliefweb.int/disaster/fl-2016-000137-arg (last access: 17 July 2024), 2017.
ReliefWeb: Libya: Flood update Flash Update No. 3 September 16 2023, UN Office for the Coordination of Humanitarian Affairs, https://reliefweb.int/report/libya/libya-flood-update-flash-update-no3-16-september-2023-5pm-local-time (last access: 17 July 2024), 2023.
Rentschler, J., Salhab, M., and Jafino, B. A.: Flood exposure and poverty in 188 countries, Nat. Commun., 13, 3527, https://doi.org/10.1038/s41467-022-30727-4, 2022.
Ridder, N., De Vries, H., and Drijfhout, S.: The role of atmospheric rivers in compound events consisting of heavy precipitation and high storm surges along the Dutch coast, Natural Hazards and Earth System Sciences, 18, 3311-3326, https://doi.org/10.5194/NHESS-18-3311-2018, 2018.
Ridder, N. N., Pitman, A. J., Westra, S., Ukkola, A., Hong, X. D., Bador, M., Hirsch, A. L., Evans, J. P., Di Luca, A., and Zscheischler, J.: Global hotspots for the occurrence of compound events, Nature Communications, 11, 1–10, https://doi.org/10.1038/s41467-020-19639-3, 2020.
Robins, P. E., Davies, A. G., and Jones, R.: Application of a coastal model to simulate present and future inundation and aid coastal management, J. Coast. Conserv., 15, 1–14, https://doi.org/10.1007/S11852-010-0113-4, 2011.
Robins, P. E., Lewis, M. J., Elnahrawi, M., Lyddon, C., Dickson, N., and Coulthard, T. J.: Compound Flooding: Dependence at Sub-daily Scales Between Extreme Storm Surge and Fluvial Flow, Frontiers in Built Environment, 7, https://doi.org/10.3389/fbuil.2021.727294, 2021.
Rodríguez, G., Nistal, A., and Pérez, B.: Joint occurrence of high tide, surge and storm-waves on the northwest Spanish coast, Boletín-Instituto Español de Oceanografía, 1999.
Rossiter, J. R.: Interaction Between Tide and Surge in the Thames, Geophysical Journal International, 6, 29-53, https://doi.org/10.1111/j.1365-246X.1961.tb02960.x, 1961.
Rozell, D. J.: Overestimating coastal urban resilience: The groundwater problem, Cities, 118, 103369, https://doi.org/10.1016/j.cities.2021.103369, 2021.
Rueda, A., Camus, P., Tomás, A., Vitousek, S., and Méndez, F. J.: A multivariate extreme wave and storm surge climate emulator based on weather patterns, Ocean Modelling, 104, 242-251, https://doi.org/10.1016/J.OCEMOD.2016.06.008, 2016.
Ruggiero, P., Serafin, K., Parker, K., and Hill, D.: Assessing the Impacts of Coastal Flooding on Treaty of Olympia Infrastructure: A report to the Quinault Indian Nation, Hoh Tribe, and Quileute Tribe, Corvallis, Oregon, https://www.cakex.org/sites/default/files/documents/QTAII_Report_Final_withAppendices.pdf (last access: 17 July 2024), 2019.
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, https://doi.org/10.1029/2018GL077317, 2018.
Saharia, A. M., Zhu, Z., and Atkinson, J. F.: Compound flooding from lake seiche and river flow in a freshwater coastal river, J. Hydrol., 603, https://doi.org/10.1016/j.jhydrol.2021.126969, 2021.
Saleh, F., Ramaswamy, V., Wang, Y., Georgas, N., Blumberg, A., and Pullen, J.: A multi-scale ensemble-based framework for forecasting compound coastal-riverine flooding: The Hackensack-Passaic watershed and Newark Bay, Advances in Water Resources, 110, 371-386, https://doi.org/10.1016/j.advwatres.2017.10.026, 2017.
Salvadori, G. and De Michele, C.: Frequency analysis via copulas: Theoretical aspects and applications to hydrological events, Water Resour. Res., 40, https://doi.org/10.1029/2004WR003133, 2004.
Salvadori, G. and De Michele, C.: On the Use of Copulas in Hydrology: Theory and Practice, Journal of Hydrologic Engineering, 12, 369-380, https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(369), 2007.
Sampurno, J., Vallaeys, V., Ardianto, R., and Hanert, E.: Integrated hydrodynamic and machine learning models for compound flooding prediction in a data-scarce estuarine delta, Nonlinear Processes in Geophysics, 29, 301-315, https://doi.org/10.5194/npg-29-301-2022, 2022a.
Sampurno, J., Vallaeys, V., Ardianto, R., and Hanert, E.: Modeling interactions between tides, storm surges, and river discharges in the Kapuas River delta, Biogeosciences, 19, 2741-2757, https://doi.org/10.5194/bg-19-2741-2022, 2022b.
Sangsefidi, Y., Bagheri, K., Davani, H., and Merrifield, M.: Vulnerability of coastal drainage infrastructure to compound flooding under climate change, J. Hydrol., 128823-128823, https://doi.org/10.1016/J.JHYDROL.2022.128823, 2022.
Santiago-Collazo, F. L., Bilskie, M. V., and Hagen, S. C.: A comprehensive review of compound inundation models in low-gradient coastal watersheds, Environmental Modelling and Software, 119, 166-181, https://doi.org/10.1016/j.envsoft.2019.06.002, 2019.
Santiago-Collazo, F. L., Bilskie, M. V., Bacopoulos, P., and Hagen, S. C.: An Examination of Compound Flood Hazard Zones for Past, Present, and Future Low-Gradient Coastal Land-Margins, Frontiers in Climate, 3, 684035, https://doi.org/10.3389/FCLIM.2021.684035, 2021.
Santos, V. M., Haigh, I. D., and Wahl, T.: Spatial and temporal clustering analysis of extreme wave events around the UK coastline, Journal of Marine Science and Engineering, 5, https://doi.org/10.3390/JMSE5030028, 2017.
Santos, V. M., Wahl, T., Jane, R., Misra, S. K., and White, K. D.: Assessing compound flooding potential with multivariate statistical models in a complex estuarine system under data constraints, Journal of Flood Risk Management, 14, https://doi.org/10.1111/JFR3.12749, 2021a.
Santos, V. M., Casas-Prat, M., Poschlod, B., Ragno, E., Van Den Hurk, B., Hao, Z., Kalmár, T., Zhu, L., and Najafi, H.: Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: A case study in the Netherlands, Hydrology and Earth System Sciences, 25, 3595-3615, https://doi.org/10.5194/HESS-25-3595-2021, 2021b.
Sarewitz, D. and Pielke, R.: Extreme Events: A Research and Policy Framework for Disasters in Context, International Geology Review, 43, 406-418, https://doi.org/10.1080/00206810109465022, 2001.
Schaake, J. C., Hamill, T. M., Buizza, R., and Clark, M.: HEPEX: The Hydrological Ensemble Prediction Experiment, Bulletin of the American Meteorological Society, 88, 1541-1548, https://doi.org/10.1175/BAMS-88-10-1541, 2007.
Sebastian, A.: Chapter 7 – Compound Flooding, in: Coastal Flood Risk Reduction: The Netherlands and the U.S. Upper Texas Coast, Elsevier, 77-88, https://doi.org/10.1016/B978-0-323-85251-7.00007-X, 2022.
Seneviratne, S. I., Nicholls, N., Easterling, D., Goodess, C. M., Kanae, S., Kossin, J., Luo, Y., Marengo, J., Mc Innes, K., Rahimi, M., Reichstein, M., Sorteberg, A., Vera, C., Zhang, X., Rusticucci, M., Semenov, V., Alexander, L. V., Allen, S., Benito, G., Cavazos, T., Clague, J., Conway, D., Della-Marta, P. M., Gerber, M., Gong, S., Goswami, B. N., Hemer, M., Huggel, C., Van den Hurk, B., Kharin, V. V., Kitoh, A., Klein Tank, A. M. G., Li, G., Mason, S., Mc Guire, W., Van Oldenborgh, G. J., Orlowsky, B., Smith, S., Thiaw, W., Velegrakis, A., Yiou, P., Zhang, T., Zhou, T., and Zwiers, F. W.: Changes in Climate Extremes and their Impacts on the Natural Physical Environment, Cambridge University Press, Cambridge, United Kingdom, New York, USA9781139177245, 109-230, https://doi.org/10.1017/CBO9781139177245.006, 2012.
Serafin, K. A. and Ruggiero, P.: Simulating extreme total water levels using a time-dependent, extreme value approach, Journal of Geophysical Research: Oceans, 119, 6305-6329, https://doi.org/10.1002/2014JC010093, 2014.
Serafin, K. A., Ruggiero, P., Parker, K., and Hill, D. F.: What's streamflow got to do with it? A probabilistic simulation of the competing oceanographic and fluvial processes driving extreme along-river water levels, Natural Hazards and Earth System Sciences, 19, 1415-1431, https://doi.org/10.5194/NHESS-19-1415-2019, 2019.
Shahapure, S. S., Eldho, T. I., and Rao, E. P.: Coastal Urban Flood Simulation Using FEM, GIS and Remote Sensing, Water Resources Management, 24, 3615-3640, https://doi.org/10.1007/s11269-010-9623-y, 2010.
Shen, Y., Morsy, M. M., Huxley, C., Tahvildari, N., and Goodall, J. L.: Flood risk assessment and increased resilience for coastal urban watersheds under the combined impact of storm tide and heavy rainfall, J. Hydrol., 579, 124159-124159, https://doi.org/10.1016/J.JHYDROL.2019.124159, 2019.
Shen, Y., Tahvildari, N., Morsy, M. M., Huxley, C., Chen, T. D., and Goodall, J. L.: Dynamic Modeling of Inland Flooding and Storm Surge on Coastal Cities under Climate Change Scenarios: Transportation Infrastructure Impacts in Norfolk, Virginia USA as a Case Study, https://doi.org/10.3390/geosciences12060224, 2022.
Sheng, Y. P., Paramygin, V. A., Yang, K., and Rivera-Nieves, A. A.: A sensitivity study of rising compound coastal inundation over large flood plains in a changing climate, Scientific Reports, 12, https://doi.org/10.1038/s41598-022-07010-z, 2022.
Shi, S., Yang, B., and Jiang, W.: Numerical simulations of compound flooding caused by storm surge and heavy rain with the presence of urban drainage system, coastal dam and tide gates: A case study of Xiangshan, China, Coastal Engineering, 172, https://doi.org/10.1016/j.coastaleng.2021.104064, 2022.
Shields, G., Olsen, R., Medina, M., Obeysekera, J., Ganguli, P., DeMichele, C., Salvadori, G., Najafi Mohammad, R., Moftakhari, H., Diermanse, F., and AghaKouchak, A.: Compound Flooding in a Non-Stationary World: A Primer for Practice, in: ASCE Inspire 2023, Proceedings, 18–27, https://doi.org/10.1061/9780784485163.003, 2023.
Silva-Araya, W. F., Santiago-Collazo, F. L., Gonzalez-Lopez, J., and Maldonado-Maldonado, J.: Dynamic Modeling of Surface Runoff and Storm Surge during Hurricane and Tropical Storm Events, Hydrology, 5, 13–13, https://doi.org/10.3390/HYDROLOGY5010013, 2018.
Simmonds, R., White, C. J., Douglas, J., Sauter, C., and Brett, L.: A review of interacting natural hazards and cascading impacts in Scotland Research funded by the National Centre for Resilience, https://eprints.gla.ac.uk/267515/ (last access: 17 July 2024), 2022.
Skinner, C. J., Coulthard, T. J., Parsons, D. R., Ramirez, J. A., Mullen, L., and Manson, S.: Simulating tidal and storm surge hydraulics with a simple 2D inertia based model, in the Humber Estuary, U.K, Estuarine, Coastal and Shelf Science, 155, 126–136, https://doi.org/10.1016/J.ECSS.2015.01.019, 2015.
Sklar, M.: Fonctions de répartition à n dimensions et leurs marges, Annales de l'ISUP, 229–231, https://hal.science/hal-04094463 (last access: 17 July 2024), 1959.
Sopelana, J., Cea, L., and Ruano, S.: A continuous simulation approach for the estimation of extreme flood inundation in coastal river reaches affected by meso- and macrotides, Nat. Hazards, 93, 1337–1358, https://doi.org/10.1007/S11069-018-3360-6, 2018.
Stamey, B., Smith, W., Carey, K., Garbin, D., Klein, F., Wang, H., Shen, J., Gong, W., Cho, J., Forrest, D., Friedrichs, C., Boicourt, W., Li, M., Koterba, M., King, D., Titlow, J., Smith, E., Siebers, A., Billet, J., Lee, J., Manning, D., Szatkowski, G., Wilson, D., Ahnert, P., and Ostrowski, J.: Chesapeake Inundation Prediction System (CIPS): A regional prototype for a national problem, Oceans 2007, Vancouver, https://doi.org/10.1109/OCEANS.2007.4449222, 2007.
Stein, L., Pianosi, F., and Woods, R.: Event-based classification for global study of river flood generating processes, Hydrol. Process., 34, 1514–1529, https://doi.org/10.1002/hyp.13678, 2019.
Steinschneider, S.: A hierarchical Bayesian model of storm surge and total water levels across the Great Lakes shoreline – Lake Ontario, J. Great Lakes Res., 47, 829–843, https://doi.org/10.1016/J.JGLR.2021.03.007, 2021.
Stephens, S. A. and Wu, W.: Mapping Dependence between Extreme Skew-Surge, Rainfall, and River-Flow, Journal of Marine Science and Engineering, 10, 1818, https://doi.org/10.3390/JMSE10121818, 2022.
Stephens, T. A., Savant, G., Sanborn, S. C., Wallen, C. M., and Roy, S.: Monolithic Multiphysics Simulation of Compound Flooding, J. Hydraul. Eng., 148, 05022003, https://doi.org/10.1061/(ASCE)HY.1943-7900.0002000, 2022.
Stevens, C. L. and Lawrence, G. A.: Estimation of wind-forced internal seiche amplitudes in lakes and reservoirs, with data from British Columbia, Canada, Aquat. Sci., 59, 115–134, https://doi.org/10.1007/BF02523176, 1997.
Svensson, C. and Jones, D. A.: Dependence between extreme sea surge, river flow and precipitation in eastern Britain, Int. J. Climatol., 22, 1149–1168, https://doi.org/10.1002/JOC.794, 2002.
Svensson, C. and Jones, D. A.: Dependence between extreme sea surge, river flow and precipitation: a study in south and west Britain, CEH Wallingford, R&D Interim Technical Report FD2308/TR1, https://assets.publishing.service.gov.uk/media/602bae1fe90e07055e422831/Technical_Report_-_Interim_Product__Joint_probability_dependence_mapping_and_best_practice__.pdf (last access: 17 July 2024), 2003.
Svensson, C. and Jones, D. A.: Dependence between sea surge, river flow and precipitation in south and west Britain, Hydrol. Earth Syst. Sci., 8, 973–992, https://doi.org/10.5194/hess-8-973-2004, 2004.
Swain, D. L., Wing, O. E. J., Bates, P. D., Done, J. M., Johnson, K. A., and Cameron, D. R.: Increased Flood Exposure Due to Climate Change and Population Growth in the United States, Earth's Future, 8, e2020EF001778, https://doi.org/10.1029/2020EF001778, 2020.
Sweet, W., Dusek, G., Obeysekera, J. T. B., and Marra, J. J.: Patterns and projections of high tide flooding along the U.S. coastline using a common impact threshold, NOAA, Technical Report NOS CO-OPs 086, https://doi.org/10.7289/V5/TR-NOS-COOPS-086, 2018.
Tahvildari, N., Abi Aad, M., Sahu, A., Shen, Y., Morsy, M., Murray-Tuite, P., Goodall, J. L., Heaslip, K., and Cetin, M.: Quantification of Compound Flooding over Roadway Network during Extreme Events for Planning Emergency Operations, Nat. Hazards Rev., 23, 04021067, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000524, 2022.
Tanim, A. H. and Goharian, E.: Developing a hybrid modeling and multivariate analysis framework for storm surge and runoff interactions in urban coastal flooding, J. Hydrol., 595, 125670, https://doi.org/10.1016/j.jhydrol.2020.125670, 2021.
Tanir, T., Sumi, S. J., de Lima, A. d. S., de A. Coelho, G., Uzun, S., Cassalho, F., and Ferreira, C. M.: Multi-scale comparison of urban socio-economic vulnerability in the Washington, DC metropolitan region resulting from compound flooding, Int. J. Disast. Risk Re., 61, 102362, https://doi.org/10.1016/j.ijdrr.2021.102362, 2021.
Tao, K., Fang, J., Yang, W., Fang, J., and Liu, B.: Characterizing compound floods from heavy rainfall and upstream–downstream extreme flow in middle Yangtze River from 1980 to 2020, Nat. Hazards, 115, 1097–1114, https://doi.org/10.1007/S11069-022-05585-4, 2022.
Tawn, J. A.: Estimating Probabilities of Extreme Sea-Levels, J. Roy. Stat. Soc.-C App., 41, 77–93, https://doi.org/10.2307/2347619, 1992.
Tehranirad, B., Herdman, L., Nederhoff, K., Erikson, L., Cifelli, R., Pratt, G., Leon, M., and Barnard, P.: Effect of fluvial discharges and remote non-tidal residuals on compound flood forecasting in San Francisco Bay, Water, 12, 2481, https://doi.org/10.3390/W12092481, 2020.
Thompson, C. M. and Frazier, T. G.: Deterministic and probabilistic flood modeling for contemporary and future coastal and inland precipitation inundation, Appl. Geogr., 50, 1–14, https://doi.org/10.1016/J.APGEOG.2014.01.013, 2014.
Tilloy, A., Malamud, B. D., Winter, H., and Joly-Laugel, A.: A review of quantification methodologies for multi-hazard interrelationships, Earth-Sci. Rev., 196, 102881–102881, https://doi.org/10.1016/J.EARSCIREV.2019.102881, 2019.
Torres, J. M., Bass, B., Irza, N., Fang, Z., Proft, J., Dawson, C., Kiani, M., and Bedient, P.: Characterizing the hydraulic interactions of hurricane storm surge and rainfall-runoff for the Houston-Galveston region, Coast. Eng., 106, 7–19, https://doi.org/10.1016/j.coastaleng.2015.09.004, 2015.
Tramblay, Y., Arnaud, P., Artigue, G., Lang, M., Paquet, E., Neppel, L., and Sauquet, E.: Changes in Mediterranean flood processes and seasonality, Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023, 2023.
Tromble, E., Kolar, R., Dresback, K., Hong, Y., Vieux, B., Luettich, R., Gourley, J., Kelleher, K., and Van Cooten, S.: Aspects of Coupled Hydrologic-Hydrodynamic Modeling for Coastal Flood Inundation, Proceedings of the International Conference on Estuarine and Coastal Modeling, 388, 724–743, https://doi.org/10.1061/41121(388)42, 2010.
Tu, X., Du, Y., Singh, V. P., and Chen, X.: Joint distribution of design precipitation and tide and impact of sampling in a coastal area, Int. J. Climatol., 38, e290–e302, https://doi.org/10.1002/JOC.5368, 2018.
UNDRR: Sendai Framework for Disaster Risk Reduction 2015–2030, Sendai, Japan, https://www.undrr.org/media/16176 (last access: 17 July 2024), 2015.
UNDRR: Report of the open ended intergovernmental expert working group on indicators and terminology relating to disaster risk reduction, United Nations Office for Disaster Risk Reduction (UNDRR), 41, https://www.undrr.org/publication/report-open-ended-intergovernmental-expert-working-group-indicators-and-terminology (last access: 17 July 2024), 2016.
UNDRR: Global Assessment Report on Disaster Risk Reduction, United Nations Office for Disaster Risk Reduction (UNDRR), Geneva, Switzerland, 425, ISBN 978-92-1-004180-5, 2019.
Valle-Levinson, A., Olabarrieta, M., and Heilman, L.: Compound flooding in Houston-Galveston Bay during Hurricane Harvey, Sci. Total Environ., 747, 141272, https://doi.org/10.1016/j.scitotenv.2020.141272, 2020.
Van Berchum, E. C., Van Ledden, M., Timmermans, J. S., Kwakkel, J. H., and Jonkman, S. N.: Rapid flood risk screening model for compound flood events in Beira, Mozambique, Natural Hazards and Earth System Sciences, 20, 2633-2646, https://doi.org/10.5194/NHESS-20-2633-2020, 2020.
Van Cooten, S., Kelleher, K. E., Howard, K., Zhang, J., Gourley, J. J., Kain, J. S., Nemunaitis-Monroe, K., Flamig, Z., Moser, H., Arthur, A., Langston, C., Kolar, R., Hong, Y., Dresback, K., Tromble, E., Vergara, H., Luettich, R. A., Blanton, B., Lander, H., Galluppi, K., Losego, J. P., Blain, C. A., Thigpen, J., Mosher, K., Figurskey, D., Moneypenny, M., Blaes, J., Orrock, J., Bandy, R., Goodall, C., Kelley, J. G. W., Greenlaw, J., Wengren, M., Eslinger, D., Payne, J., Olmi, G., Feldt, J., Schmidt, J., Hamill, T., Bacon, R., Stickney, R., and Spence, L.: The CI-FLOW Project: A System for Total Water Level Prediction from the Summit to the Sea, B. Am. Meteorol. Soc., 92, 1427–1442, https://doi.org/10.1175/2011BAMS3150.1, 2011.
van den Brink, H. W., Können, G. P., Opsteegh, J. D., van Oldenborgh, G. J., and Burgers, G.: Estimating return periods of extreme events from ECMWF seasonal forecast ensembles, Int. J. Climatol., 25, 1345–1354, https://doi.org/10.1002/joc.1155, 2005.
Van Den Hurk, B., Van Meijgaard, E., De Valk, P., Van Heeringen, K. J., and Gooijer, J.: Analysis of a compounding surge and precipitation event in the Netherlands, Environ. Res. Lett., 10, 035001, https://doi.org/10.1088/1748-9326/10/3/035001, 2015.
Van den Hurk, B. J. J. M., White, C. J., Ramos, A. M., Ward, P. J., Martius, O., Olbert, I., Roscoe, K., Goulart, H. M. D., and Zscheischler, J.: Consideration of compound drivers and impacts in the disaster risk reduction cycle, iScience, 26, 106030, https://doi.org/10.1016/j.isci.2023.106030, 2023.
Vitousek, S., Barnard, P. L., Fletcher, C. H., Frazer, N., Erikson, L., and Storlazzi, C. D.: Doubling of coastal flooding frequency within decades due to sea-level rise, Sci. Rep., 7, 1–9, https://doi.org/10.1038/s41598-017-01362-7, 2017.
Vongvisessomjai, S. and Rojanakamthorn, S.: Interaction of Tide and River Flow, Journal of Waterway, Port, Coastal, and Ocean Engineering, 115, 86–104, https://doi.org/10.1061/(ASCE)0733-950X(1989)115:1(86), 1989.
Vormoor, K., Lawrence, D., Heistermann, M., and Bronstert, A.: Climate change impacts on the seasonality and generation processes of floods – projections and uncertainties for catchments with mixed snowmelt/rainfall regimes, Hydrol. Earth Syst. Sci., 19, 913–931, https://doi.org/10.5194/hess-19-913-2015, 2015.
Wadey, M. P., Brown, J. M., Haigh, I. D., Dolphin, T., and Wisse, P.: Assessment and comparison of extreme sea levels and waves during the 2013/14 storm season in two UK coastal regions, Nat. Hazards Earth Syst. Sci., 15, 2209–2225, https://doi.org/10.5194/nhess-15-2209-2015, 2015.
Wahl, T., Jain, S., Bender, J., Meyers, S. D., and Luther, M. E.: Increasing risk of compound flooding from storm surge and rainfall for major US cities, Nat. Clim. Change, 5, 1093–1097, https://doi.org/10.1038/NCLIMATE2736, 2015.
Walden, A. T., Prescott, P., and Webber, N. B.: The examination of surge-tide interaction at two ports on the central south coast of England, Coast. Eng., 6, 59–70, https://doi.org/10.1016/0378-3839(82)90015-1, 1982.
Wang, H. V., Loftis, J. D., Liu, Z., Forrest, D., and Zhang, J.: The Storm Surge and Sub-Grid Inundation Modeling in New York City during Hurricane Sandy, Journal of Marine Science and Engineering, 2, 226–246, https://doi.org/10.3390/JMSE2010226, 2014.
Wang, H. V., Loftis, J. D., Forrest, D., Smith, W., and Stamey, B.: Modeling Storm Surge and Inundation in Washington, DC, during Hurricane Isabel and the 1936 Potomac River Great Flood, Journal of Marine Science and Engineering, 3, 607–629, https://doi.org/10.3390/jmse3030607, 2015.
Wang, S., Najafi, M. R., Cannon, A. J., and Khan, A. A.: Uncertainties in Riverine and Coastal Flood Impacts under Climate Change, Water, 13, 1774–1774, https://doi.org/10.3390/W13131774, 2021.
Ward, P. J., Couasnon, A., Eilander, D., Haigh, I. D., Hendry, A., Muis, S., Veldkamp, T. I. E., Winsemius, H. C., and Wahl, T.: Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries, Environ. Res. Lett., 13, 084012, https://doi.org/10.1088/1748-9326/AAD400, 2018.
Wasko, C., Nathan, R., Stein, L., and O'Shea, D.: Evidence of shorter more extreme rainfalls and increased flood variability under climate change, J. Hydrol., 603, 126994, https://doi.org/10.1016/j.jhydrol.2021.126994, 2021.
Webster, T., McGuigan, K., Collins, K., and MacDonald, C.: Integrated River and Coastal Hydrodynamic Flood Risk Mapping of the LaHave River Estuary and Town of Bridgewater, Nova Scotia, Canada, Water, 6, 517–546, https://doi.org/10.3390/w6030517, 2014.
White, C.: The use of joint probability analysis to predict flood frequency in estuaries and tidal rivers, School of Civil Engineering and the Environment, University of Southampton, 357 pp., https://eprints.soton.ac.uk/63847/ (last access: 17 July 2024), 2007.
Williams, J., Horsburgh, K. J., Williams, J. A., and Proctor, R. N. F.: Tide and skew surge independence: New insights for flood risk, Geophys. Res. Lett., 43, 6410–6417, https://doi.org/10.1002/2016GL069522, 2016.
Wolf, J.: Coastal flooding: Impacts of coupled wave-surge-tide models, Nat. Hazards, 49, 241–260, https://doi.org/10.1007/S11069-008-9316-5, 2009.
Wood, M., Haigh, I. D., Le, Q. Q., Nguyen, H. N., Ba, H. T., Darby, S. E., Marsh, R., Skliris, N., and Hirschi, J. J.-M.: Risk of compound flooding substantially increases in the future Mekong River delta, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-949, 2024.
Wood, M., Haigh, I. D., Le, Q. Q., Nguyen, H. N., Tran, H. B., Darby, S. E., Marsh, R., Skliris, N., Hirschi, J. J.-M., Nicholls, R. J., and Bloemendaal, N.: Climate-induced storminess forces major increases in future storm surge hazard in the South China Sea region, Nat. Hazards Earth Syst. Sci., 23, 2475–2504, https://doi.org/10.5194/nhess-23-2475-2023, 2023.
Woodruff, J. D., Irish, J. L., and Camargo, S. J.: Coastal flooding by tropical cyclones and sea-level rise, Nature, 504, 44–52, https://doi.org/10.1038/nature12855, 2013.
Wu, W. and Leonard, M.: Impact of ENSO on dependence between extreme rainfall and storm surge, Environ. Res. Lett., 14, 124043, https://doi.org/10.1088/1748-9326/AB59C2, 2019.
Wu, W., Westra, S., and Leonard, M.: Estimating the probability of compound floods in estuarine regions, Hydrol. Earth Syst. Sci., 25, 2821–2841, https://doi.org/10.5194/hess-25-2821-2021, 2021.
Wu, W., Emerton, R., Duan, Q., Wood, A. W., Wetterhall, F., and Robertson, D. E.: Ensemble flood forecasting: Current status and future opportunities, Wiley Interdisciplinary Reviews: Water, 7, e1432, https://doi.org/10.1002/WAT2.1432, 2020.
Wu, W., McInnes, K., O'Grady, J., Hoeke, R., Leonard, M., and Westra, S.: Mapping Dependence Between Extreme Rainfall and Storm Surge, J. Geophys. Res.-Oceans, 123, 2461–2474, https://doi.org/10.1002/2017JC013472, 2018.
Xiao, Z., Yang, Z., Wang, T., Sun, N., Wigmosta, M., and Judi, D.: Characterizing the Non-linear Interactions Between Tide, Storm Surge, and River Flow in the Delaware Bay Estuary, United States, Frontiers in Marine Science, 8, 715557, https://doi.org/10.3389/fmars.2021.715557, 2021.
Xu, H., Xu, K., Lian, J., and Ma, C.: Compound effects of rainfall and storm tides on coastal flooding risk, Stoch. Environ. Res. Risk A., 33, 1249–1261, https://doi.org/10.1007/S00477-019-01695-X, 2019.
Xu, K., Wang, C., and Bin, L.: Compound flood models in coastal areas: a review of methods and uncertainty analysis, Nat. Hazards, 116, 469–496, https://doi.org/10.1007/s11069-022-05683-3, 2022.
Xu, K., Ma, C., Lian, J., and Bin, L.: Joint probability analysis of extreme precipitation and storm tide in a coastal city under changing environment, PLoS ONE, 9, e109341, https://doi.org/10.1371/journal.pone.0109341, 2014.
Xu, Z., Zhang, Y., Blöschl, G., and Piao, S.: Mega Forest Fires Intensify Flood Magnitudes in Southeast Australia, Geophys. Res. Lett., 50, e2023GL103812, https://doi.org/10.1029/2023GL103812, 2023.
Yang, X. and Qian, J.: Joint occurrence probability analysis of typhoon-induced storm surges and rainstorms using trivariate Archimedean copulas, Ocean Eng., 171, 533–539, https://doi.org/10.1016/j.oceaneng.2018.11.039, 2019.
Yang, X., Wang, J., and Weng, S.: Joint Probability Study of Destructive Factors Related to the “Triad” Phenomenon during Typhoon Events in the Coastal Regions: Taking Jiangsu Province as an Example, J. Hydrol. Eng., 25, 05020038, https://doi.org/10.1061/(ASCE)HE.1943-5584.0002007, 2020.
Yang, Y., Yin, J., Zhang, W., Zhang, Y., Lu, Y., Liu, Y., Xiao, A., Wang, Y., and Song, W.: Modeling of a compound flood induced by the levee breach at Qianbujing Creek, Shanghai, during Typhoon Fitow, Nat. Hazards Earth Syst. Sci., 21, 3563–3572, https://doi.org/10.5194/nhess-21-3563-2021, 2021.
Ye, F., Huang, W., Zhang, Y. J., Moghimi, S., Myers, E., Pe'eri, S., and Yu, H.-C.: A cross-scale study for compound flooding processes during Hurricane Florence, Nat. Hazards Earth Syst. Sci., 21, 1703–1719, https://doi.org/10.5194/nhess-21-1703-2021, 2021.
Ye, F., Zhang, Y. J., Yu, H., Sun, W., Moghimi, S., Myers, E., Nunez, K., Zhang, R., Wang, H. V., Roland, A., Martins, K., Bertin, X., Du, J., and Liu, Z.: Simulating storm surge and compound flooding events with a creek-to-ocean model: Importance of baroclinic effects, Ocean Model., 145, 101526, https://doi.org/10.1016/j.ocemod.2019.101526, 2020.
Yeh, S.-P., Ou, S.-H., Doong, D.-J., Kao, C., and Hsieh, D.: Joint Probability Analysis of Waves and Water Level during Typhoons, Proceedings of the 3rd Chinese-German joint symposium on coastal and ocean engineering, https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=a7707b7ede5eb8792559dcbea297c5ab2bd2349b (last access: 17 July 2024), 2006.
Zahura, F. T. and Goodall, J. L.: Predicting combined tidal and pluvial flood inundation using a machine learning surrogate model, J. Hydrol., 41, 101087, https://doi.org/10.1016/j.ejrh.2022.101087, 2022.
Zellou, B. and Rahali, H.: Assessment of the joint impact of extreme rainfall and storm surge on the risk of flooding in a coastal area, J. Hydrol., 569, 647–665, https://doi.org/10.1016/J.JHYDROL.2018.12.028, 2019.
Zhang, L. and Chen, X.: Temporal and spatial distribution of compound flood potential in China's coastal areas, J. Hydrol., 615, 128719, https://doi.org/10.1016/J.JHYDROL.2022.128719, 2022.
Zhang, W., Liu, Y., Tang, W., Wang, W., and Liu, Z.: Assessment of the effects of natural and anthropogenic drivers on extreme flood events in coastal regions, Stoch. Environ. Res. Risk A., 37, 697–715, https://doi.org/10.1007/S00477-022-02306-Y, 2022.
Zhang, W., Luo, M., Gao, S., Chen, W., Hari, V., and Khouakhi, A.: Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods, Frontiers in Earth Science, 9, 673495, https://doi.org/10.3389/FEART.2021.673495, 2021a.
Zhang, Y., Sun, X., and Chen, C.: Characteristics of concurrent precipitation and wind speed extremes in China, Weather and Climate Extremes, 32, 100322, https://doi.org/10.1016/j.wace.2021.100322, 2021b.
Zhang, Y. J., Witter, R. C., and Priest, G. R.: Tsunami–tide interaction in 1964 Prince William Sound tsunami, Ocean Model., 40, 246–259, https://doi.org/10.1016/J.OCEMOD.2011.09.005, 2011.
Zhang, Y. J., Ye, F., Yu, H., Sun, W., Moghimi, S., Myers, E., Nunez, K., Zhang, R., Wang, H., Roland, A., Du, J., and Liu, Z.: Simulating compound flooding events in a hurricane, Ocean Dynam., 70, 621–640, https://doi.org/10.1007/S10236-020-01351-X, 2020.
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, https://doi.org/10.1016/j.jhydrol.2013.09.054, 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, https://doi.org/10.1002/2013wr014616, 2014.
Zhong, H., van Overloop, P.-J., and van Gelder, P. H. A. J. M.: A joint probability approach using a 1-D hydrodynamic model for estimating high water level frequencies in the Lower Rhine Delta, Nat. Hazards Earth Syst. Sci., 13, 1841–1852, https://doi.org/10.5194/nhess-13-1841-2013, 2013.
Zschau, J.: Where are we with multihazards, multirisks assessment capacities?, European Union Joint Research Council, Luxembourg, https://doi.org/10.2788/688605, 2017.
Zscheischler, J. and Seneviratne, S. I.: Dependence of drivers affects risks associated with compound events, Science Advances, 3, e1700263, https://doi.org/10.1126/SCIADV.1700263, 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. Change, 8, 469–477, https://doi.org/10.1038/S41558-018-0156-3, 2018.
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R. M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D., Maraun, D., Ramos, A. M., Ridder, N. N., Thiery, W., and Vignotto, E.: A typology of compound weather and climate events, Nat. Rev. Earth Environ., 1, 333–347, https://doi.org/10.1038/s43017-020-0060-z, 2020.
Short summary
Compound flooding, involving the combination or successive occurrence of two or more flood drivers, can amplify flood impacts in coastal/estuarine regions. This paper reviews the practices, trends, methodologies, applications, and findings of coastal compound flooding literature at regional to global scales. We explore the types of compound flood events, their mechanistic processes, and the range of terminology. Lastly, this review highlights knowledge gaps and implications for future practices.
Compound flooding, involving the combination or successive occurrence of two or more flood...
Altmetrics
Final-revised paper
Preprint