Articles | Volume 20, issue 4
https://doi.org/10.5194/nhess-20-1149-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-1149-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Invited perspectives
| 
29 Apr 2020
Invited perspectives |
| 29 Apr 2020
| 29 Apr 2020
Invited perspectives: How machine learning will change flood risk and impact assessment
Dennis Wagenaar
CORRESPONDING AUTHOR
Department of flood risk management, Deltares, Delft, the Netherlands
Institute for environmental studies, VU University, Amsterdam, the Netherlands
Alex Curran
Department of flood risk management, Deltares, Delft, the Netherlands
Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Mariano Balbi
Structural and Materials Lab, School of Engineering, Universidad de Buenos Aires, Buenos Aires, Argentina
Alok Bhardwaj
Earth Observatory of Singapore, Nanyang Technological University,
Singapore
Robert Soden
Columbia University, New York City, New York, USA
GFDRR, World Bank Group, Washington, D.C., USA
Co-Risk Labs, Oakland, California, USA
Emir Hartato
Planet, San Francisco, USA
Gizem Mestav Sarica
Institute of Catastrophe Risk Management, Nanyang Technological
University, Singapore
Laddaporn Ruangpan
Department of Water Resources and Ecosystems, IHE Delft Institute for Water Education, Delft, the Netherlands
Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Giuseppe Molinario
GFDRR, World Bank Group, Washington, D.C., USA
David Lallemant
Earth Observatory of Singapore, Nanyang Technological University,
Singapore
Co-Risk Labs, Oakland, California, USA
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Dennis Wagenaar, Jurjen de Jong, and Laurens M. Bouwer
Nat. Hazards Earth Syst. Sci., 17, 1683–1696, https://doi.org/10.5194/nhess-17-1683-2017, https://doi.org/10.5194/nhess-17-1683-2017, 2017
Short summary
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Flood damage models are an important component of cost–benefit analyses for flood protection measures. Currently flood damage models predict the flood damage often only based on water depth. Recently, some progress has been made in also including other variables for this prediction. Data-intensive approaches (machine learning) have been applied to do this. In practice the required data for this are rare. We apply these new approaches on a new type of dataset (combination of different sources).
This article is included in the Encyclopedia of Geosciences
D. J. Wagenaar, K. M. de Bruijn, L. M. Bouwer, and H. de Moel
Nat. Hazards Earth Syst. Sci., 16, 1–14, https://doi.org/10.5194/nhess-16-1-2016, https://doi.org/10.5194/nhess-16-1-2016, 2016
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This paper discusses the differences that are found between flood damage estimation models. Based on an explanation of these differences, a method to quantify the uncertainty in flood damage models is proposed. An uncertainty estimate is made for a case study and the potential implications of uncertainty in flood damage estimation for investment decisions is shown.
This article is included in the Encyclopedia of Geosciences
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
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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.
Mariano Balbi and David Charles Bonaventure Lallemant
Hydrol. Earth Syst. Sci., 27, 1089–1108, https://doi.org/10.5194/hess-27-1089-2023, https://doi.org/10.5194/hess-27-1089-2023, 2023
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We proposed a methodology to obtain useful and robust probabilistic predictions from computational flood simulators using satellite-borne flood extent observations. We developed a Bayesian framework to obtain the uncertainty in roughness parameters, in observations errors, and in simulator structural deficiencies. We found that it can yield improvements in predictions relative to current methodologies and can potentially lead to consistent ways of combining data from different sources.
This article is included in the Encyclopedia of Geosciences
Anirudh Rao, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, and Sang-Ho Yun
Nat. Hazards Earth Syst. Sci., 23, 789–807, https://doi.org/10.5194/nhess-23-789-2023, https://doi.org/10.5194/nhess-23-789-2023, 2023
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This article presents a framework for semi-automated building damage assessment due to earthquakes from remote-sensing data and other supplementary datasets including high-resolution building inventories, while also leveraging recent advances in machine-learning algorithms. For three out of the four recent earthquakes studied, the machine-learning framework is able to identify over 50 % or nearly half of the damaged buildings successfully.
This article is included in the Encyclopedia of Geosciences
Constance Ting Chua, Adam D. Switzer, Anawat Suppasri, Linlin Li, Kwanchai Pakoksung, David Lallemant, Susanna F. Jenkins, Ingrid Charvet, Terence Chua, Amanda Cheong, and Nigel Winspear
Nat. Hazards Earth Syst. Sci., 21, 1887–1908, https://doi.org/10.5194/nhess-21-1887-2021, https://doi.org/10.5194/nhess-21-1887-2021, 2021
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Port industries are extremely vulnerable to coastal hazards such as tsunamis. Despite their pivotal role in local and global economies, there has been little attention paid to tsunami impacts on port industries. For the first time, tsunami damage data are being extensively collected for port structures and catalogued into a database. The study also provides fragility curves which describe the probability of damage exceedance for different port industries given different tsunami intensities.
This article is included in the Encyclopedia of Geosciences
Laddaporn Ruangpan, Zoran Vojinovic, Silvana Di Sabatino, Laura Sandra Leo, Vittoria Capobianco, Amy M. P. Oen, Michael E. McClain, and Elena Lopez-Gunn
Nat. Hazards Earth Syst. Sci., 20, 243–270, https://doi.org/10.5194/nhess-20-243-2020, https://doi.org/10.5194/nhess-20-243-2020, 2020
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This article aims to provide a critical review of the literature and indicate some directions for future research based on the current knowledge gaps in the area of nature-based solutions (NBSs) for hydro-meteorological risk reduction. The final full analysis was performed on 146 closely related articles. A review showed that many advancements related to NBSs have been made to date, but there are still many challenges that will play an important role in extending knowledge in the coming years.
This article is included in the Encyclopedia of Geosciences
Dennis Wagenaar, Jurjen de Jong, and Laurens M. Bouwer
Nat. Hazards Earth Syst. Sci., 17, 1683–1696, https://doi.org/10.5194/nhess-17-1683-2017, https://doi.org/10.5194/nhess-17-1683-2017, 2017
Short summary
Short summary
Flood damage models are an important component of cost–benefit analyses for flood protection measures. Currently flood damage models predict the flood damage often only based on water depth. Recently, some progress has been made in also including other variables for this prediction. Data-intensive approaches (machine learning) have been applied to do this. In practice the required data for this are rare. We apply these new approaches on a new type of dataset (combination of different sources).
This article is included in the Encyclopedia of Geosciences
D. J. Wagenaar, K. M. de Bruijn, L. M. Bouwer, and H. de Moel
Nat. Hazards Earth Syst. Sci., 16, 1–14, https://doi.org/10.5194/nhess-16-1-2016, https://doi.org/10.5194/nhess-16-1-2016, 2016
Short summary
Short summary
This paper discusses the differences that are found between flood damage estimation models. Based on an explanation of these differences, a method to quantify the uncertainty in flood damage models is proposed. An uncertainty estimate is made for a case study and the potential implications of uncertainty in flood damage estimation for investment decisions is shown.
This article is included in the Encyclopedia of Geosciences
Related subject area
Hydrological Hazards
Floods in the Pyrenees: a global view through a regional database
Algorithmically detected rain-on-snow flood events in different climate datasets: a case study of the Susquehanna River basin
Review article: Drought as a continuum – memory effects in interlinked hydrological, ecological, and social systems
Coupling WRF with HEC-HMS and WRF-Hydro for flood forecasting in typical mountainous catchments of northern China
Precursors and pathways: dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood
Demonstrating the use of UNSEEN climate data for hydrological applications: case studies for extreme floods and droughts in England
Exploring the use of seasonal forecasts to adapt flood insurance premiums
Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event
Water depth estimate and flood extent enhancement for satellite-based inundation maps
Probabilistic flood inundation mapping through copula Bayesian multi-modeling of precipitation products
Flood occurrence and impact models for socioeconomic applications over Canada and the United States
Model-based assessment of climate change impact on inland flood risk at the German North Sea coast caused by compounding storm tide and precipitation events
An improved dynamic bidirectional coupled hydrologic–hydrodynamic model for efficient flood inundation prediction
Quantifying hazard resilience by modeling infrastructure recovery as a resource-constrained project scheduling problem
Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain
A downward-counterfactual analysis of flash floods in Germany
This article is included in the Encyclopedia of Geosciences
Hyper-resolution flood hazard mapping at the national scale
Compound droughts under climate change in Switzerland
Brief communication: SWM – stochastic weather model for precipitation-related hazard assessments using ERA5-Land data
Tangible and intangible ex-post assessment of flood-induced damages to cultural heritage
Spatiotemporal variability of flash floods and their human impacts in the Czech Republic during the 2001–2023 period
Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany
The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0
A multivariate statistical framework for mixed populations in compound flood analysis
Risk of compound flooding substantially increases in the future Mekong River delta
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María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci., 24, 3423–3443, https://doi.org/10.5194/nhess-24-3423-2024, https://doi.org/10.5194/nhess-24-3423-2024, 2024
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This paper shows the first public and systematic dataset of flood episodes referring to the entire Pyrenees massif, at municipal scale, named PIRAGUA_flood. Of the 181 flood events (1981–2015) that produced 154 fatalities, 36 were transnational, with the eastern part of the massif most affected. Dominant weather types show a southern component flow, with a talweg on the Iberian Peninsula and a depression in the vicinity. A positive and significant trend was found in Nouvelle-Aquitaine.
This article is included in the Encyclopedia of Geosciences
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
Nat. Hazards Earth Syst. Sci., 24, 3315–3335, https://doi.org/10.5194/nhess-24-3315-2024, https://doi.org/10.5194/nhess-24-3315-2024, 2024
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We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern United States, in climate data. Analyzing the Susquehanna River basin, this technique identified known events affecting river flow. Comparing four gridded datasets revealed variations in event frequency and severity, driven by different snowmelt and runoff estimates. This highlights the need for accurate climate data in flood management and risk prediction for these compound extremes.
This article is included in the Encyclopedia of Geosciences
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
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Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
This article is included in the Encyclopedia of Geosciences
Sheik Umar Jam-Jalloh, Jia Liu, Yicheng Wang, and Yuchen Liu
Nat. Hazards Earth Syst. Sci., 24, 3155–3172, https://doi.org/10.5194/nhess-24-3155-2024, https://doi.org/10.5194/nhess-24-3155-2024, 2024
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Our paper explores improving flood forecasting using advanced weather and hydrological models. By coupling the WRF model with WRF-Hydro and HEC-HMS, we achieved more accurate forecasts. WRF–WRF-Hydro excels for short, intense storms, while WRF–HEC-HMS is better for longer, evenly distributed storms. Our research shows how these models provide insights for adaptive atmospheric–hydrologic systems and aims to boost flood preparedness and response with more reliable, timely predictions.
This article is included in the Encyclopedia of Geosciences
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024, https://doi.org/10.5194/nhess-24-2995-2024, 2024
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Extreme rainfall is the leading weather-related source of damages in Europe, but it is still difficult to predict on long timescales. A recent example of this was the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allows us to better understand and predict such events.
This article is included in the Encyclopedia of Geosciences
Alison L. Kay, Nick Dunstone, Gillian Kay, Victoria A. Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci., 24, 2953–2970, https://doi.org/10.5194/nhess-24-2953-2024, https://doi.org/10.5194/nhess-24-2953-2024, 2024
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Hydrological hazards affect people and ecosystems, but extremes are not fully understood due to limited observations. A large climate ensemble and simple hydrological model are used to assess unprecedented but plausible floods and droughts. The chain gives extreme flows outside the observed range: summer 2022 ~ 28 % lower and autumn 2023 ~ 42 % higher. Spatial dependence and temporal persistence are analysed. Planning for such events could help water supply resilience and flood risk management.
This article is included in the Encyclopedia of Geosciences
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024, https://doi.org/10.5194/nhess-24-2923-2024, 2024
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Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.
This article is included in the Encyclopedia of Geosciences
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024, https://doi.org/10.5194/nhess-24-2857-2024, 2024
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Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high-resolution models resolving individual streets and buildings, we produce detailed, quantitative, and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.
This article is included in the Encyclopedia of Geosciences
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024, https://doi.org/10.5194/nhess-24-2817-2024, 2024
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The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
This article is included in the Encyclopedia of Geosciences
Francisco Javier Gomez, Keighobad Jafarzadegan, Hamed Moftakhari, and Hamid Moradkhani
Nat. Hazards Earth Syst. Sci., 24, 2647–2665, https://doi.org/10.5194/nhess-24-2647-2024, https://doi.org/10.5194/nhess-24-2647-2024, 2024
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This study utilizes the global copula Bayesian model averaging technique for accurate and reliable flood modeling, especially in coastal regions. By integrating multiple precipitation datasets within this framework, we can effectively address sources of error in each dataset, leading to the generation of probabilistic flood maps. The creation of these probabilistic maps is essential for disaster preparedness and mitigation in densely populated areas susceptible to extreme weather events.
This article is included in the Encyclopedia of Geosciences
Manuel Grenier, Mathieu Boudreault, David A. Carozza, Jérémie Boudreault, and Sébastien Raymond
Nat. Hazards Earth Syst. Sci., 24, 2577–2595, https://doi.org/10.5194/nhess-24-2577-2024, https://doi.org/10.5194/nhess-24-2577-2024, 2024
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Modelling floods at the street level for large countries like Canada and the United States is difficult and very costly. However, many applications do not necessarily require that level of detail. As a result, we present a flood modelling framework built with artificial intelligence for socioeconomic studies like trend and scenarios analyses. We find for example that an increase of 10 % in average precipitation yields an increase in displaced population of 18 % in Canada and 14 % in the US.
This article is included in the Encyclopedia of Geosciences
Helge Bormann, Jenny Kebschull, Lidia Gaslikova, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 2559–2576, https://doi.org/10.5194/nhess-24-2559-2024, https://doi.org/10.5194/nhess-24-2559-2024, 2024
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Inland flooding is threatening coastal lowlands. If rainfall and storm surges coincide, the risk of inland flooding increases. We examine how such compound events are influenced by climate change. Data analysis and model-based scenario analysis show that climate change induces an increasing frequency and intensity of compounding precipitation and storm tide events along the North Sea coast. Overload of inland drainage systems will also increase if no timely adaptation measures are taken.
This article is included in the Encyclopedia of Geosciences
Yanxia Shen, Zhenduo Zhu, Qi Zhou, and Chunbo Jiang
Nat. Hazards Earth Syst. Sci., 24, 2315–2330, https://doi.org/10.5194/nhess-24-2315-2024, https://doi.org/10.5194/nhess-24-2315-2024, 2024
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We present an improved Multigrid Dynamical Bidirectional Coupled hydrologic–hydrodynamic Model (IM-DBCM) with two major improvements: (1) automated non-uniform mesh generation based on the D-infinity algorithm was implemented to identify flood-prone areas where high-resolution inundation conditions are needed, and (2) ghost cells and bilinear interpolation were implemented to improve numerical accuracy in interpolating variables between the coarse and fine grids. The improved model was reliable.
This article is included in the Encyclopedia of Geosciences
Taylor Glen Johnson, Jorge Leandro, and Divine Kwaku Ahadzie
Nat. Hazards Earth Syst. Sci., 24, 2285–2302, https://doi.org/10.5194/nhess-24-2285-2024, https://doi.org/10.5194/nhess-24-2285-2024, 2024
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Reliance on infrastructure creates vulnerabilities to disruptions caused by natural hazards. To assess the impacts of natural hazards on the performance of infrastructure, we present a framework for quantifying resilience and develop a model of recovery based upon an application of project scheduling under resource constraints. The resilience framework and recovery model were applied in a case study to assess the resilience of building infrastructure to flooding hazards in Accra, Ghana.
This article is included in the Encyclopedia of Geosciences
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci., 24, 2215–2242, https://doi.org/10.5194/nhess-24-2215-2024, https://doi.org/10.5194/nhess-24-2215-2024, 2024
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On 22 October 2019, the Francolí River basin experienced a heavy precipitation event, resulting in a catastrophic flash flood. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors.
This article is included in the Encyclopedia of Geosciences
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 2147–2164, https://doi.org/10.5194/nhess-24-2147-2024, https://doi.org/10.5194/nhess-24-2147-2024, 2024
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To identify flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent runoff reaction. Our results show that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks of a factor of 2 or more would be achieved for most areas. The results can aid disaster risk management.
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024, https://doi.org/10.5194/nhess-24-2071-2024, 2024
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A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
This article is included in the Encyclopedia of Geosciences
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
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The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
This article is included in the Encyclopedia of Geosciences
Melody Gwyneth Whitehead and Mark Stephen Bebbington
Nat. Hazards Earth Syst. Sci., 24, 1929–1935, https://doi.org/10.5194/nhess-24-1929-2024, https://doi.org/10.5194/nhess-24-1929-2024, 2024
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Precipitation-driven hazards including floods, landslides, and lahars can be catastrophic and difficult to forecast due to high uncertainty around future weather patterns. This work presents a stochastic weather model that produces statistically similar (realistic) rainfall over long time periods at minimal computational cost. These data provide much-needed inputs for hazard simulations to support long-term, time and spatially varying risk assessments.
This article is included in the Encyclopedia of Geosciences
Claudia De Lucia, Michele Amaddii, and Chiara Arrighi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-104, https://doi.org/10.5194/nhess-2024-104, 2024
Revised manuscript under review for NHESS
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The work describes the flood damages to cultural heritage (CH) occurred in the event of September 2022 in Central Italy. Datasets related to flood impacts to cultural heritage are rare and this work aims at highlighting both tangible and intangible aspects and their correlation with physical characteristics of the flood, i.e., water depth and flow velocity. The results show that current knowledge and datasets are inadequate for risk assessment of CH.
This article is included in the Encyclopedia of Geosciences
Rudolf Brázdil, Dominika Faturová, Monika Šulc Michalková, Jan Řehoř, Martin Caletka, and Pavel Zahradníček
EGUsphere, https://doi.org/10.5194/egusphere-2024-1467, https://doi.org/10.5194/egusphere-2024-1467, 2024
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Flash floods belong to natural hazards that can be enhanced in frequency, intensity and impacts during the recent climate change. The paper present a complex analysis of spatiotemporal variability and human impacts (including material damage and fatalities) of flash floods in the Czech Republic for the 2001–2023 period. The analysis shows generally not any statistically significant trends in the characteristics analysed.
This article is included in the Encyclopedia of Geosciences
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777, https://doi.org/10.5194/nhess-24-1757-2024, https://doi.org/10.5194/nhess-24-1757-2024, 2024
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We delved into the socio-economic impacts of the 2018–2022 drought in Germany. We derived a dataset covering the impacts of droughts in Germany between 2000 and 2022 on sectors such as agriculture and forestry based on newspaper articles. Notably, our study illustrated that the longer drought had a wider reach and more varied effects. We show that dealing with longer droughts requires different plans compared to shorter ones, and it is crucial to be ready for the challenges they bring.
This article is included in the Encyclopedia of Geosciences
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696, https://doi.org/10.5194/nhess-24-1681-2024, https://doi.org/10.5194/nhess-24-1681-2024, 2024
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INSYDE 2.0 is a tool for modelling flood damage to residential buildings. By incorporating ultra-detailed survey and desk-based data, it improves the reliability and informativeness of damage assessments while addressing input data uncertainties.
This article is included in the Encyclopedia of Geosciences
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Andrew Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
EGUsphere, https://doi.org/10.5194/egusphere-2024-1122, https://doi.org/10.5194/egusphere-2024-1122, 2024
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Most of the studies on compound flooding assume events that generate extreme rainfall and coastal water level responses originate from a single population, in reality, they originate from multiple populations each with unique statistical characteristics. This paper presents a flexible statistical framework for assessing the compound flood potential from multiple flood drivers that explicitly accounts for different event types.
This article is included in the Encyclopedia of Geosciences
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Tran Ba, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
EGUsphere, https://doi.org/10.5194/egusphere-2024-949, https://doi.org/10.5194/egusphere-2024-949, 2024
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We look at how compound flooding from the combination of river flooding and storm tide (storm surge plus 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 potential to flood the region more extensively and be longer lasting than compound floods today. This is useful to know because it means that managers of deltas such as the Mekong can assess options for improving existing flood defences.
This article is included in the Encyclopedia of Geosciences
Théo St. Pierre Ostrander, Thomé Kraus, Bruno Mazzorana, Johannes Holzner, Andrea Andreoli, Francesco Comiti, and Bernhard Gems
Nat. Hazards Earth Syst. Sci., 24, 1607–1634, https://doi.org/10.5194/nhess-24-1607-2024, https://doi.org/10.5194/nhess-24-1607-2024, 2024
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Mountain river confluences are hazardous during localized flooding events. A physical model was used to determine the dominant controls over mountain confluences. Contrary to lowland confluences, in mountain regions, the channel discharges and (to a lesser degree) the tributary sediment concentration control morphological patterns. Applying conclusions drawn from lowland confluences could misrepresent depositional and erosional patterns and the related flood hazard at mountain river confluences.
This article is included in the Encyclopedia of Geosciences
Zhi Li, Hanqi Li, Zhibo Zhang, Chaomeng Dai, and Simin Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1088, https://doi.org/10.5194/egusphere-2024-1088, 2024
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This study used advanced computer simulations to investigate how earthquake-induced building collapse affects flooding of the metro stations in Shanghai. Results show that the influence of building collapse on rainfall-driven and river-driven flood are different because these two types of floods have different origination and propagation mechanisms.
This article is included in the Encyclopedia of Geosciences
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci., 24, 1163–1183, https://doi.org/10.5194/nhess-24-1163-2024, https://doi.org/10.5194/nhess-24-1163-2024, 2024
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High-resolution convection-permitting climate models (CPMs) are now available to better simulate rainstorm events leading to flash floods. In this study, two hydrological models are compared to simulate floods in a Mediterranean basin, showing a better ability of the CPM to reproduce flood peaks compared to coarser-resolution climate models. Future projections are also different, with a projected increase for the most severe floods and a potential decrease for the most frequent events.
This article is included in the Encyclopedia of Geosciences
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024, https://doi.org/10.5194/nhess-24-1065-2024, 2024
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The most recent drought in the UK was declared in summer 2022. We pooled a large sample of plausible winters from seasonal hindcasts and grouped them into four clusters based on their atmospheric circulation configurations. Drought storylines representative of what the drought could have looked like if winter 2022/23 resembled each winter circulation storyline were created to explore counterfactuals of how bad the 2022 drought could have been over winter 2022/23 and beyond.
This article is included in the Encyclopedia of Geosciences
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
EGUsphere, https://doi.org/10.5194/egusphere-2024-856, https://doi.org/10.5194/egusphere-2024-856, 2024
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We discuss the validation of flood hazard and risk assessments (FHRAs) to ensure they are useful for decision-making. We propose a new validation framework that considers not only technical aspects but also the real-world context in which decisions are made. By applying this framework to flood emergency planning, we demonstrate its practicality.
This article is included in the Encyclopedia of Geosciences
Dino Collalti, Nekeisha Spencer, and Eric Strobl
Nat. Hazards Earth Syst. Sci., 24, 873–890, https://doi.org/10.5194/nhess-24-873-2024, https://doi.org/10.5194/nhess-24-873-2024, 2024
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The risk of extreme rainfall events causing floods is likely increasing with climate change. Flash floods, which follow immediately after extreme rainfall, are particularly difficult to forecast and assess. We develop a decision rule for flash flood classification with data on all incidents between 2001 and 2018 in Jamaica with the statistical copula method. This decision rule tells us for any rainfall event of a certain duration how intense it has to be to likely trigger a flash flood.
This article is included in the Encyclopedia of Geosciences
Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg
Nat. Hazards Earth Syst. Sci., 24, 681–697, https://doi.org/10.5194/nhess-24-681-2024, https://doi.org/10.5194/nhess-24-681-2024, 2024
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This study presents a new version of a framework which allows us to model water balance components at any site on a local scale. Compared with the first version, the second incorporates new datasets used to set up and force the model. In particular, we highlight the ability of the framework to provide seasonal forecasts. This gives potential stakeholders (farmers, foresters, policymakers, etc.) the possibility to forecast, for example, soil moisture drought and thus apply the necessary measures.
This article is included in the Encyclopedia of Geosciences
Diego Fernández-Nóvoa, Alexandre M. Ramos, José González-Cao, Orlando García-Feal, Cristina Catita, Moncho Gómez-Gesteira, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci., 24, 609–630, https://doi.org/10.5194/nhess-24-609-2024, https://doi.org/10.5194/nhess-24-609-2024, 2024
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The present study focuses on an in-depth analysis of floods in the lower section of the Tagus River from a hydrodynamic perspective by means of the Iber+ numerical model and on the development of dam operating strategies to mitigate flood episodes using the exceptional floods of February 1979 as a benchmark. The results corroborate the model's capability to evaluate floods in the study area and confirm the effectiveness of the proposed strategies to reduce flood impact in the lower Tagus valley.
This article is included in the Encyclopedia of Geosciences
Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Pham Khanh Nam
Nat. Hazards Earth Syst. Sci., 24, 539–566, https://doi.org/10.5194/nhess-24-539-2024, https://doi.org/10.5194/nhess-24-539-2024, 2024
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We present a global flood model built using a new terrain data set and evaluated in the Central Highlands of Vietnam.
This article is included in the Encyclopedia of Geosciences
Andrea Abbate, Leonardo Mancusi, Francesco Apadula, Antonella Frigerio, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci., 24, 501–537, https://doi.org/10.5194/nhess-24-501-2024, https://doi.org/10.5194/nhess-24-501-2024, 2024
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CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment) is a new physically based and spatially distributed rainfall-runoff model. The main novelties consist of reproducing rainfall-induced geo-hydrological hazards such as shallow landslide, debris flow and watershed erosion through a multi-hazard approach. CRHyME was written in Python, works at a high spatial and temporal resolution, and is a tool suitable for quantifying extreme rainfall consequences at the basin scale.
This article is included in the Encyclopedia of Geosciences
Samuel Jonson Sutanto, Matthijs Janssen, Mariana Madruga de Brito, and Maria del Pozo Garcia
EGUsphere, https://doi.org/10.5194/egusphere-2024-153, https://doi.org/10.5194/egusphere-2024-153, 2024
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A conventional flood risk assessment only evaluates flood hazard in isolation without considering wildfires. This study, therefore, evaluates the cascading impact of wildfires on flood risk, considering both current and future conditions for the Ebro River basin in Spain. Results show that extreme climate change increases the risk of flooding, especially when considering the cascading impacts of wildfires, highlighting the importance of adopting a multi-hazard risk management approach.
This article is included in the Encyclopedia of Geosciences
Leanne Archer, Jeffrey Neal, Paul Bates, Emily Vosper, Dereka Carroll, Jeison Sosa, and Daniel Mitchell
Nat. Hazards Earth Syst. Sci., 24, 375–396, https://doi.org/10.5194/nhess-24-375-2024, https://doi.org/10.5194/nhess-24-375-2024, 2024
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We model hurricane-rainfall-driven flooding to assess how the number of people exposed to flooding changes in Puerto Rico under the 1.5 and 2 °C Paris Agreement goals. Our analysis suggests 8 %–10 % of the population is currently exposed to flooding on average every 5 years, increasing by 2 %–15 % and 1 %–20 % at 1.5 and 2 °C. This has implications for adaptation to more extreme flooding in Puerto Rico and demonstrates that 1.5 °C climate change carries a significant increase in risk.
This article is included in the Encyclopedia of Geosciences
Miroslav Spano and Jaromir Riha
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-21, https://doi.org/10.5194/nhess-2024-21, 2024
Revised manuscript accepted for NHESS
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Our study examines how building the Skalička Dam near the Hranice Karst affects local groundwater. We used advanced modeling to analyze two dam layouts: lateral and through-flow reservoirs. Results show the through-flow variant significantly alters water levels and mineral water discharge, while the lateral layout has less impact.
This article is included in the Encyclopedia of Geosciences
Luis Cea, Manuel Álvarez, and Jerónimo Puertas
Nat. Hazards Earth Syst. Sci., 24, 225–243, https://doi.org/10.5194/nhess-24-225-2024, https://doi.org/10.5194/nhess-24-225-2024, 2024
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Mozambique is highly exposed to the impact of floods. To reduce flood damage, it is necessary to develop mitigation measures. Hydrological software is a very useful tool for that purpose, since it allows for a precise quantification of flood hazard in different scenarios. We present a methodology to quantify flood hazard in data-scarce regions, using freely available data and software, and we show its potential by analysing the flood event that took place in the Umbeluzi Basin in February 2023.
This article is included in the Encyclopedia of Geosciences
Chinh Luu, Giuseppe Forino, Lynda Yorke, Hang Ha, Quynh Duy Bui, Hanh Hong Tran, Dinh Quoc Nguyen, Hieu Cong Duong, and Matthieu Kervyn
EGUsphere, https://doi.org/10.5194/egusphere-2024-57, https://doi.org/10.5194/egusphere-2024-57, 2024
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The study produced a novel and integrated approach to assessing the climate hazards of floods and wildfires. We explored multi-hazards assessment and risk through a machine learning modelling approach. The process includes (1) collecting a database of topography, climate, geology, environment, and building data, (2) developing models for multi-hazards assessment and coding in Google Earth Engine, and (3) producing credible multi-hazard susceptibility and building exposure maps.
This article is included in the Encyclopedia of Geosciences
Lorenzo Alfieri, Andrea Libertino, Lorenzo Campo, Francesco Dottori, Simone Gabellani, Tatiana Ghizzoni, Alessandro Masoero, Lauro Rossi, Roberto Rudari, Nicola Testa, Eva Trasforini, Ahmed Amdihun, Jully Ouma, Luca Rossi, Yves Tramblay, Huan Wu, and Marco Massabò
Nat. Hazards Earth Syst. Sci., 24, 199–224, https://doi.org/10.5194/nhess-24-199-2024, https://doi.org/10.5194/nhess-24-199-2024, 2024
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This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the Greater Horn of Africa. It is based on hydrological simulations, inundation mapping, and estimation of population and assets exposed to upcoming river floods. The system supports duty officers in African institutions in the daily monitoring of hydro-meteorological disasters. A first evaluation shows the system performance for the catastrophic floods in the Nile River basin in summer 2020.
This article is included in the Encyclopedia of Geosciences
Nejc Bezak, Panos Panagos, Leonidas Liakos, and Matjaž Mikoš
Nat. Hazards Earth Syst. Sci., 23, 3885–3893, https://doi.org/10.5194/nhess-23-3885-2023, https://doi.org/10.5194/nhess-23-3885-2023, 2023
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
This article is included in the Encyclopedia of Geosciences
Ana Paez-Trujilo, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, and Dimitri Solomatine
Nat. Hazards Earth Syst. Sci., 23, 3863–3883, https://doi.org/10.5194/nhess-23-3863-2023, https://doi.org/10.5194/nhess-23-3863-2023, 2023
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This study uses a machine learning technique, the multivariate regression tree approach, to assess the hydroclimatic characteristics that govern agricultural and hydrological drought severity. The results show that the employed technique successfully identified the primary drivers of droughts and their critical thresholds. In addition, it provides relevant information to identify the areas most vulnerable to droughts and design strategies and interventions for drought management.
This article is included in the Encyclopedia of Geosciences
Bouchra Zellou, Nabil El Moçayd, and El Houcine Bergou
Nat. Hazards Earth Syst. Sci., 23, 3543–3583, https://doi.org/10.5194/nhess-23-3543-2023, https://doi.org/10.5194/nhess-23-3543-2023, 2023
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In this study, we underscore the critical importance of strengthening drought prediction capabilities in the Mediterranean region. We present an in-depth evaluation of current drought forecasting approaches, encompassing statistical, dynamical, and hybrid statistical–dynamical models, and highlight unexplored research opportunities. Additionally, we suggest viable directions to enhance drought prediction and early warning systems within the area.
This article is included in the Encyclopedia of Geosciences
Sarra Kchouk, Louise Cavalcante, Lieke A. Melsen, David W. Walker, Germano Ribeiro Neto, Rubens Gondim, Wouter J. Smolenaars, and Pieter R. van Oel
EGUsphere, https://doi.org/10.5194/egusphere-2023-2726, https://doi.org/10.5194/egusphere-2023-2726, 2023
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Droughts impact water and people, yet monitoring often overlooks impacts on people. In Northeast Brazil, we assess official data against local experiences, finding data mismatches and blindspots. Mismatches occur due to the data's broad scope missing finer details. Blindspots arise from ignoring diverse community responses and vulnerabilities to droughts. We suggest enhanced monitoring by technical extension officers for both severe and mild droughts.
This article is included in the Encyclopedia of Geosciences
Francisco Rodrigues do Amaral, Nicolas Gratiot, Thierry Pellarin, and Tran Anh Tu
Nat. Hazards Earth Syst. Sci., 23, 3379–3405, https://doi.org/10.5194/nhess-23-3379-2023, https://doi.org/10.5194/nhess-23-3379-2023, 2023
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We propose an in-depth analysis of typhoon-induced compound flood drivers in the megacity of Ho Chi Minh, Vietnam. We use in situ and satellite measurements throughout the event to form a holistic overview of its impact. No evidence of storm surge was found, and peak precipitation presents a 16 h time lag to peak river discharge, which evacuates only 1.5 % of available water. The astronomical tide controls the river level even during the extreme event, and it is the main urban flood driver.
This article is included in the Encyclopedia of Geosciences
Juliette Godet, Olivier Payrastre, Pierre Javelle, and François Bouttier
Nat. Hazards Earth Syst. Sci., 23, 3355–3377, https://doi.org/10.5194/nhess-23-3355-2023, https://doi.org/10.5194/nhess-23-3355-2023, 2023
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This article results from a master's research project which was part of a natural hazards programme developed by the French Ministry of Ecological Transition. The objective of this work was to investigate a possible way to improve the operational flash flood warning service by adding rainfall forecasts upstream of the forecasting chain. The results showed that the tested forecast product, which is new and experimental, has a real added value compared to other classical forecast products.
This article is included in the Encyclopedia of Geosciences
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
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In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
This article is included in the Encyclopedia of Geosciences
Clément Houdard, Adrien Poupardin, Philippe Sergent, Abdelkrim Bennabi, and Jena Jeong
Nat. Hazards Earth Syst. Sci., 23, 3111–3124, https://doi.org/10.5194/nhess-23-3111-2023, https://doi.org/10.5194/nhess-23-3111-2023, 2023
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We developed a system able to to predict, knowing the appropriate characteristics of the flood defense structure and sea state, the return periods of potentially dangerous events as well as a ranking of parameters by order of uncertainty.
The model is a combination of statistical and empirical methods that have been applied to a Mediterranean earthen dike. This shows that the most important characteristics of the dyke are its geometrical features, such as its height and slope angles.
This article is included in the Encyclopedia of Geosciences
Maryam Pakdehi, Ebrahim Ahmadisharaf, Behzad Nazari, and Eunsaem Cho
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-152, https://doi.org/10.5194/nhess-2023-152, 2023
Revised manuscript accepted for NHESS
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Machine learning (ML) models have growingly received attention for predicting flood events. However, there has been concerns about the transferability of these models (their capability in predicting out-of-sample events). Here, we showed that ML models can be transferable for hindcasting maximum river flood depths across major events (Hurricanes Ida, Isaias, Sandy, and Irene) in coastal watersheds when informed by the spatial distribution of pertinent features and underlying physical processes.
This article is included in the Encyclopedia of Geosciences
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Short summary
This invited perspective paper addresses how machine learning may change flood risk and impact assessments. It goes through different modelling components and provides an analysis of how current assessments are done without machine learning, current applications of machine learning and potential future improvements. It is based on a 2-week-long intensive collaboration among experts from around the world during the Understanding Risk Field lab on urban flooding in June 2019.
This invited perspective paper addresses how machine learning may change flood risk and impact...
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