Articles | Volume 22, issue 8
https://doi.org/10.5194/nhess-22-2473-2022
© Author(s) 2022. 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-22-2473-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Aug 2022
Research article |
| 02 Aug 2022
| 02 Aug 2022
Effectiveness of Sentinel-1 and Sentinel-2 for flood detection assessment in Europe
Angelica Tarpanelli
CORRESPONDING AUTHOR
Research Institute for Geo-Hydrological Protection, National Research
Council, Via Madonna Alta 126, 06128 Perugia, Italy
Alessandro C. Mondini
Research Institute for Geo-Hydrological Protection, National Research
Council, Via Madonna Alta 126, 06128 Perugia, Italy
Stefania Camici
Research Institute for Geo-Hydrological Protection, National Research
Council, Via Madonna Alta 126, 06128 Perugia, Italy
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Various combinations of antecedent conditions and precipitation result in floods of varying degrees. Antecedent conditions played a crucial role in generating even large ones. The key predictors and spatial patterns of antecedent conditions leading to flooding at the basin's outlet were distinct. Precipitation and soil moisture from almost all sub-catchments were important for more frequent floods. For rarer events, only the predictors of specific sub-catchments were important.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 4609–4615, https://doi.org/10.5194/nhess-24-4609-2024, https://doi.org/10.5194/nhess-24-4609-2024, 2024
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Floods have caused significant damage in the past. To prepare for such events, we rely on historical data but face issues due to rare rainfall events, lack of data and climate change. Counterfactuals, or
what ifscenarios, simulate historical rainfall in different locations to estimate flood levels. Our new study refines this by deriving more-plausible local scenarios, using the June 2024 Bavaria flood as a case study. This method could improve preparedness for future floods.
Chinh Luu, Giuseppe Forino, Lynda Yorke, Hang Ha, Quynh Duy Bui, Hanh Hong Tran, Dinh Quoc Nguyen, Hieu Cong Duong, and Matthieu Kervyn
Nat. Hazards Earth Syst. Sci., 24, 4385–4408, https://doi.org/10.5194/nhess-24-4385-2024, https://doi.org/10.5194/nhess-24-4385-2024, 2024
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This study presents a novel and integrated approach to assessing the climate hazards of floods and wildfires. We explore multi-hazard assessment and risk through a machine learning modeling approach. The process includes collecting a database of topography, climate, geology, environment, and building data; developing models for multi-hazard assessment and coding in the Google Earth Engine; and producing credible multi-hazard susceptibility and building exposure maps.
Claudia De Lucia, Michele Amaddii, and Chiara Arrighi
Nat. Hazards Earth Syst. Sci., 24, 4317–4339, https://doi.org/10.5194/nhess-24-4317-2024, https://doi.org/10.5194/nhess-24-4317-2024, 2024
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This work describes the flood damage to cultural heritage (CH) that occurred in September 2022 in central Italy. Datasets related to flood impacts on cultural heritage are rare, and this work aims at highlighting both tangible and intangible aspects and their correlation with physical characteristics of flood (i.e. water depth and flow velocity). The results show that current knowledge and datasets are inadequate for risk assessment of CH.
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
Nat. Hazards Earth Syst. Sci., 24, 4091–4107, https://doi.org/10.5194/nhess-24-4091-2024, https://doi.org/10.5194/nhess-24-4091-2024, 2024
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When assessing the likelihood of compound flooding, most studies ignore that it can arise from different storm types with distinct statistical characteristics. Here, we present a new statistical framework that accounts for these differences and shows how neglecting these can impact the likelihood of compound flood potential.
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci., 24, 4015–4030, https://doi.org/10.5194/nhess-24-4015-2024, https://doi.org/10.5194/nhess-24-4015-2024, 2024
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Flood risk assessments help us decide how to reduce the risk of flooding. Since these assessments are based on probabilities, it is hard to check their accuracy by comparing them to past data. We suggest a new way to validate these assessments, making sure they are practical for real-life decisions. This approach looks at both the technical details and the real-world situations where decisions are made. We demonstrate its practicality by applying it to flood emergency planning.
Zhi Li, Hanqi Li, Zhibo Zhang, Chaomeng Dai, and Simin Jiang
Nat. Hazards Earth Syst. Sci., 24, 3977–3990, https://doi.org/10.5194/nhess-24-3977-2024, https://doi.org/10.5194/nhess-24-3977-2024, 2024
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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 influences of building collapse on rainfall-driven and river-driven floods are different because these two types of floods have different origination and propagation mechanisms.
Maria Magdalena Warter, Dörthe Tetzlaff, Christian Marx, and Chris Soulsby
Nat. Hazards Earth Syst. Sci., 24, 3907–3924, https://doi.org/10.5194/nhess-24-3907-2024, https://doi.org/10.5194/nhess-24-3907-2024, 2024
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Streams are increasingly impacted by droughts and floods. Still, the amount of water needed for sustainable flows remains unclear and contested. A comparison of two streams in the Berlin–Brandenburg region of northeast Germany, using stable water isotopes, shows strong groundwater dependence with seasonal rainfall contributing to high/low flows. Understanding streamflow variability can help us assess the impacts of climate change on future water resource management.
Samuel Jonson Sutanto, Matthijs Janssen, Mariana Madruga de Brito, and Maria del Pozo Garcia
Nat. Hazards Earth Syst. Sci., 24, 3703–3721, https://doi.org/10.5194/nhess-24-3703-2024, https://doi.org/10.5194/nhess-24-3703-2024, 2024
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A conventional flood risk assessment only evaluates flood hazard in isolation without considering wildfires. This study, therefore, evaluates the effect of wildfires on flood risk, considering both current and future conditions for the Ebro River basin in Spain. Results show that extreme climate change increases the risk of flooding, especially when considering the effect of wildfires, highlighting the importance of adopting a multi-hazard risk management approach.
Miroslav Spano and Jaromir Riha
Nat. Hazards Earth Syst. Sci., 24, 3683–3701, https://doi.org/10.5194/nhess-24-3683-2024, https://doi.org/10.5194/nhess-24-3683-2024, 2024
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The study examines the effects of hydrogeological hazard due to construction of the Skalička Dam near the Hranice Karst on groundwater discharges and water levels in the local karst formations downstream. A simplified pipe model was used to analyze the impact of two dam layouts: lateral and through-flow reservoirs. Results show that the through-flow scheme more significantly influences water levels and the discharge of mineral water, while the lateral layout has only negligible impact.
Rudolf Brázdil, Dominika Faturová, Monika Šulc Michalková, Jan Řehoř, Martin Caletka, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 3663–3682, https://doi.org/10.5194/nhess-24-3663-2024, https://doi.org/10.5194/nhess-24-3663-2024, 2024
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Flash floods belong to natural hazards that can be enhanced in frequency, intensity, and impact during recent climate change. This paper presents a complex analysis of spatiotemporal variability and human impacts (including material damage and fatalities) of flash floods in the Czech Republic for the 2001–2023 period. The analysis generally shows no statistically significant trends in the characteristics analyzed.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
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
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We look at how compound flooding from the combination of river flooding and storm tides (storm surge and astronomical tide) may be changing over time due to climate change, with a case study of the Mekong River delta. We found that future compound flooding has the potential to flood the region more extensively and be longer lasting than compound floods today. This is useful to know because it means managers of deltas such as the Mekong can assess options for improving existing flood defences.
Maryam Pakdehi, Ebrahim Ahmadisharaf, Behzad Nazari, and Eunsaem Cho
Nat. Hazards Earth Syst. Sci., 24, 3537–3559, https://doi.org/10.5194/nhess-24-3537-2024, https://doi.org/10.5194/nhess-24-3537-2024, 2024
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Machine learning (ML) algorithms have increasingly received attention for modeling flood events. However, there are concerns about the transferability of these models (their capability in predicting out-of-sample and unseen events). Here, we show that ML models can be transferable for hindcasting maximum river flood depths across extreme events (four hurricanes) in a large coastal watershed (HUC6) when informed by the spatial distribution of pertinent features and underlying physical processes.
María Carmen Llasat, Montserrat Llasat-Botija, Erika Pardo, Raül Marcos-Matamoros, and Marc Lemus-Canovas
Nat. Hazards Earth Syst. Sci., 24, 3423–3443, https://doi.org/10.5194/nhess-24-3423-2024, https://doi.org/10.5194/nhess-24-3423-2024, 2024
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This paper shows the first public and systematic dataset of flood episodes referring to the entire Pyrenees massif, at municipal scale, named PIRAGUA_flood. Of the 181 flood events (1981–2015) that produced 154 fatalities, 36 were transnational, with the eastern part of the massif most affected. Dominant weather types show a southern component flow, with a talweg on the Iberian Peninsula and a depression in the vicinity. A positive and significant trend was found in Nouvelle-Aquitaine.
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
Nat. Hazards Earth Syst. Sci., 24, 3315–3335, https://doi.org/10.5194/nhess-24-3315-2024, https://doi.org/10.5194/nhess-24-3315-2024, 2024
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We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern United States, in climate data. Analyzing the Susquehanna River basin, this technique identified known events affecting river flow. Comparing four gridded datasets revealed variations in event frequency and severity, driven by different snowmelt and runoff estimates. This highlights the need for accurate climate data in flood management and risk prediction for these compound extremes.
Dongyu Feng, Zeli Tan, Darren Engwirda, Jonathan D. Wolfe, Donghui Xu, Chang Liao, Gautam Bisht, James J. Benedict, Tian Zhou, Mithun Deb, Hong-Yi Li, and L. Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-2785, https://doi.org/10.5194/egusphere-2024-2785, 2024
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Our study explores how riverine and coastal flooding during hurricanes is influenced by the interaction of atmosphere, land, river and ocean conditions. Using an advanced Earth system model, we simulate Hurricane Irene to evaluate how meteorological and hydrological uncertainties affect flood modeling. Our findings reveal the importance of a multi-component modeling system, how hydrological conditions play critical roles in flood modeling, and greater flood risks if multiple factors are present.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
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Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Sheik Umar Jam-Jalloh, Jia Liu, Yicheng Wang, and Yuchen Liu
Nat. Hazards Earth Syst. Sci., 24, 3155–3172, https://doi.org/10.5194/nhess-24-3155-2024, https://doi.org/10.5194/nhess-24-3155-2024, 2024
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Our paper explores improving flood forecasting using advanced weather and hydrological models. By coupling the WRF model with WRF-Hydro and HEC-HMS, we achieved more accurate forecasts. WRF–WRF-Hydro excels for short, intense storms, while WRF–HEC-HMS is better for longer, evenly distributed storms. Our research shows how these models provide insights for adaptive atmospheric–hydrologic systems and aims to boost flood preparedness and response with more reliable, timely predictions.
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024, https://doi.org/10.5194/nhess-24-2995-2024, 2024
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Extreme rainfall is the leading weather-related source of damages in Europe, but it is still difficult to predict on long timescales. A recent example of this was the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allows us to better understand and predict such events.
Alison L. Kay, Nick Dunstone, Gillian Kay, Victoria A. Bell, and Jamie Hannaford
Nat. Hazards Earth Syst. Sci., 24, 2953–2970, https://doi.org/10.5194/nhess-24-2953-2024, https://doi.org/10.5194/nhess-24-2953-2024, 2024
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Hydrological hazards affect people and ecosystems, but extremes are not fully understood due to limited observations. A large climate ensemble and simple hydrological model are used to assess unprecedented but plausible floods and droughts. The chain gives extreme flows outside the observed range: summer 2022 ~ 28 % lower and autumn 2023 ~ 42 % higher. Spatial dependence and temporal persistence are analysed. Planning for such events could help water supply resilience and flood risk management.
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024, https://doi.org/10.5194/nhess-24-2923-2024, 2024
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Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024, https://doi.org/10.5194/nhess-24-2857-2024, 2024
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Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high-resolution models resolving individual streets and buildings, we produce detailed, quantitative, and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.
Andrea Betterle and Peter Salamon
Nat. Hazards Earth Syst. Sci., 24, 2817–2836, https://doi.org/10.5194/nhess-24-2817-2024, https://doi.org/10.5194/nhess-24-2817-2024, 2024
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The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schröter, and Max Steinhausen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-139, https://doi.org/10.5194/nhess-2024-139, 2024
Revised manuscript accepted for NHESS
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This work introduces RIM2D, a hydrodynamic model for precise and rapid flood predictions, ideal for early warning systems. We demonstrate RIM2D's ability to deliver detailed and localized flood forecasts using the June 2023 flood in Braunschweig, Germany, as a case study. This research highlights the readiness of RIM2D and the required hardware for integration into operational flood warning and impact-based forecasting systems.
Francisco Javier Gomez, Keighobad Jafarzadegan, Hamed Moftakhari, and Hamid Moradkhani
Nat. Hazards Earth Syst. Sci., 24, 2647–2665, https://doi.org/10.5194/nhess-24-2647-2024, https://doi.org/10.5194/nhess-24-2647-2024, 2024
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This study utilizes the global copula Bayesian model averaging technique for accurate and reliable flood modeling, especially in coastal regions. By integrating multiple precipitation datasets within this framework, we can effectively address sources of error in each dataset, leading to the generation of probabilistic flood maps. The creation of these probabilistic maps is essential for disaster preparedness and mitigation in densely populated areas susceptible to extreme weather events.
Manuel Grenier, Mathieu Boudreault, David A. Carozza, Jérémie Boudreault, and Sébastien Raymond
Nat. Hazards Earth Syst. Sci., 24, 2577–2595, https://doi.org/10.5194/nhess-24-2577-2024, https://doi.org/10.5194/nhess-24-2577-2024, 2024
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Modelling floods at the street level for large countries like Canada and the United States is difficult and very costly. However, many applications do not necessarily require that level of detail. As a result, we present a flood modelling framework built with artificial intelligence for socioeconomic studies like trend and scenarios analyses. We find for example that an increase of 10 % in average precipitation yields an increase in displaced population of 18 % in Canada and 14 % in the US.
Helge Bormann, Jenny Kebschull, Lidia Gaslikova, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 2559–2576, https://doi.org/10.5194/nhess-24-2559-2024, https://doi.org/10.5194/nhess-24-2559-2024, 2024
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Inland flooding is threatening coastal lowlands. If rainfall and storm surges coincide, the risk of inland flooding increases. We examine how such compound events are influenced by climate change. Data analysis and model-based scenario analysis show that climate change induces an increasing frequency and intensity of compounding precipitation and storm tide events along the North Sea coast. Overload of inland drainage systems will also increase if no timely adaptation measures are taken.
Yanxia Shen, Zhenduo Zhu, Qi Zhou, and Chunbo Jiang
Nat. Hazards Earth Syst. Sci., 24, 2315–2330, https://doi.org/10.5194/nhess-24-2315-2024, https://doi.org/10.5194/nhess-24-2315-2024, 2024
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We present an improved Multigrid Dynamical Bidirectional Coupled hydrologic–hydrodynamic Model (IM-DBCM) with two major improvements: (1) automated non-uniform mesh generation based on the D-infinity algorithm was implemented to identify flood-prone areas where high-resolution inundation conditions are needed, and (2) ghost cells and bilinear interpolation were implemented to improve numerical accuracy in interpolating variables between the coarse and fine grids. The improved model was reliable.
Taylor Glen Johnson, Jorge Leandro, and Divine Kwaku Ahadzie
Nat. Hazards Earth Syst. Sci., 24, 2285–2302, https://doi.org/10.5194/nhess-24-2285-2024, https://doi.org/10.5194/nhess-24-2285-2024, 2024
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Reliance on infrastructure creates vulnerabilities to disruptions caused by natural hazards. To assess the impacts of natural hazards on the performance of infrastructure, we present a framework for quantifying resilience and develop a model of recovery based upon an application of project scheduling under resource constraints. The resilience framework and recovery model were applied in a case study to assess the resilience of building infrastructure to flooding hazards in Accra, Ghana.
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci., 24, 2215–2242, https://doi.org/10.5194/nhess-24-2215-2024, https://doi.org/10.5194/nhess-24-2215-2024, 2024
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On 22 October 2019, the Francolí River basin experienced a heavy precipitation event, resulting in a catastrophic flash flood. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors.
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 2147–2164, https://doi.org/10.5194/nhess-24-2147-2024, https://doi.org/10.5194/nhess-24-2147-2024, 2024
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To identify flash flood potential in Germany, we shifted the most extreme rainfall events from the last 22 years systematically across Germany and simulated the consequent runoff reaction. Our results show that almost all areas in Germany have not seen the worst-case scenario of flood peaks within the last 22 years. With a slight spatial change of historical rainfall events, flood peaks of a factor of 2 or more would be achieved for most areas. The results can aid disaster risk management.
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024, https://doi.org/10.5194/nhess-24-2071-2024, 2024
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A methodology of regional flood hazard mapping is proposed, based on data in Austria, which combines automatic methods with manual interventions to maximise efficiency and to obtain estimation accuracy similar to that of local studies. Flood discharge records from 781 stations are used to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. The hazard maps are used for civil protection, risk awareness and insurance purposes.
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
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The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Melody Gwyneth Whitehead and Mark Stephen Bebbington
Nat. Hazards Earth Syst. Sci., 24, 1929–1935, https://doi.org/10.5194/nhess-24-1929-2024, https://doi.org/10.5194/nhess-24-1929-2024, 2024
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Precipitation-driven hazards including floods, landslides, and lahars can be catastrophic and difficult to forecast due to high uncertainty around future weather patterns. This work presents a stochastic weather model that produces statistically similar (realistic) rainfall over long time periods at minimal computational cost. These data provide much-needed inputs for hazard simulations to support long-term, time and spatially varying risk assessments.
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-97, https://doi.org/10.5194/nhess-2024-97, 2024
Revised manuscript accepted for NHESS
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The July 2021 flood in Central Europe was one of the deadliest floods in Europe in the past decades and the most expensive flood in Germany. In this paper we show that the hydrological impact of this event in the Ahr valley could have been even worse if the rainfall footprint trajectory was only slightly different. The presented methodology of spatial counterfactuals generates plausible unprecedented events and helps better prepare for future extreme floods.
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777, https://doi.org/10.5194/nhess-24-1757-2024, https://doi.org/10.5194/nhess-24-1757-2024, 2024
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We delved into the socio-economic impacts of the 2018–2022 drought in Germany. We derived a dataset covering the impacts of droughts in Germany between 2000 and 2022 on sectors such as agriculture and forestry based on newspaper articles. Notably, our study illustrated that the longer drought had a wider reach and more varied effects. We show that dealing with longer droughts requires different plans compared to shorter ones, and it is crucial to be ready for the challenges they bring.
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696, https://doi.org/10.5194/nhess-24-1681-2024, https://doi.org/10.5194/nhess-24-1681-2024, 2024
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INSYDE 2.0 is a tool for modelling flood damage to residential buildings. By incorporating ultra-detailed survey and desk-based data, it improves the reliability and informativeness of damage assessments while addressing input data uncertainties.
Théo St. Pierre Ostrander, Thomé Kraus, Bruno Mazzorana, Johannes Holzner, Andrea Andreoli, Francesco Comiti, and Bernhard Gems
Nat. Hazards Earth Syst. Sci., 24, 1607–1634, https://doi.org/10.5194/nhess-24-1607-2024, https://doi.org/10.5194/nhess-24-1607-2024, 2024
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Mountain river confluences are hazardous during localized flooding events. A physical model was used to determine the dominant controls over mountain confluences. Contrary to lowland confluences, in mountain regions, the channel discharges and (to a lesser degree) the tributary sediment concentration control morphological patterns. Applying conclusions drawn from lowland confluences could misrepresent depositional and erosional patterns and the related flood hazard at mountain river confluences.
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci., 24, 1163–1183, https://doi.org/10.5194/nhess-24-1163-2024, https://doi.org/10.5194/nhess-24-1163-2024, 2024
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High-resolution convection-permitting climate models (CPMs) are now available to better simulate rainstorm events leading to flash floods. In this study, two hydrological models are compared to simulate floods in a Mediterranean basin, showing a better ability of the CPM to reproduce flood peaks compared to coarser-resolution climate models. Future projections are also different, with a projected increase for the most severe floods and a potential decrease for the most frequent events.
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024, https://doi.org/10.5194/nhess-24-1065-2024, 2024
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The most recent drought in the UK was declared in summer 2022. We pooled a large sample of plausible winters from seasonal hindcasts and grouped them into four clusters based on their atmospheric circulation configurations. Drought storylines representative of what the drought could have looked like if winter 2022/23 resembled each winter circulation storyline were created to explore counterfactuals of how bad the 2022 drought could have been over winter 2022/23 and beyond.
Cited articles
Amici, G., Dell'Acqua, F., Gamba, P., and Pulina, G.: A comparison of fuzzy
and neuro-fuzzy data fusion for flooded area mapping using SAR images, Int. J. Remote Sens., 25, 4425–4430, https://doi.org/10.1080/01431160412331269634, 2004.
Amitrano, D., Di Martino, G., Iodice, A., Riccio, D., and Ruello, G.:
Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images, IEEE T.
Geosci. Remote, 56, 3290–3299, https://doi.org/10.1109/tgrs.2018.2797536, 2018.
Anusha, N. and Bharathi, B.: Flood detection and flood mapping using
multi-temporal synthetic aperture radar and optical data Egypt, J. Remote
Sens. Space Sci., 23, 207–219, https://doi.org/10.1016/j.ejrs.2019.01.001, 2019.
Aschbacher, J. and Milagro-Pérez, M. P.: The European Earth monitoring (GMES) programme: Status and perspectives, Remote Sens. Environ., 20, 3–8, https://doi.org/10.1016/j.rse.2011.08.028, 2012.
Bazi, Y., Bruzzone, L., and Melgani, F.: An Unsupervised Approach Based on
the Generalized Gaussian Model to Automatic Change Detection in Multitemporal SAR Images, IEEE T. Geosci. Remote, 43, 874–887, https://doi.org/10.1109/TGRS.2004.842441, 2005.
Berger, M., Moreno, J., Johannessen, J. A., Levelt, P. F., and Hanssen, R. F.: ESA's sentinel missions in support of Earth system science, Remote Sens.
Environ., 20, 84–90, https://doi.org/10.1016/j.rse.2011.07.023, 2012.
Bioresita, F., Puissant, A., Stumpf, A., and Malet, J. P.: A Method for
Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery, Remote Sens., 10, 217, https://doi.org/10.3390/rs10020217, 2018.
Brill, F., Schlaffer, S., Martinis, S., Schröter, K., and Kreibich, H.:
Extrapolating Satellite-Based Flood Masks by One-Class Classification – A
Test Case in Houston, Remote Sens., 13, 2042, https://doi.org/10.3390/rs13112042, 2021.
Caballero, I., Ruiz, J., and Navarro, G.: Sentinel-2 satellites provide
near-real time evaluation of catastrophic floods in the west mediterranean,
Water, 11, 2499, https://doi.org/10.3390/w11122499, 2019.
Cao, H., Zhang, H., Wang, C. ,and Zhang, B.: Operational flood detection using Sentinel-1 SAR data over large areas, Water, 11, 786,
https://doi.org/10.3390/w11040786, 2019.
Carincotte, C., Derrode, S., and Bourennane, S.: Unsupervised Change
Detection on SAR Images Using Fuzzy Hidden Markov Chains, IEEE T. Geosci.
Remote, 44, 432–441, https://doi.org/10.1109/TGRS.2005.861007, 2006.
Celik, T.: A Bayesian approach to unsupervised multiscale change detection in synthetic aperture radar images, Signal Process., 90, 1471–1485, https://doi.org/10.1016/j.sigpro.2009.10.018, 2010.
Chini, M., Pulvirenti, L., and Pierdicca, N.: Analysis and interpretation of
the COSMO-SkyMed Observations of the 2011 Japan Tsunami, IEEE Geosci. Remote
Sens. Lett., 9, 467–471, https://doi.org/10.1109/LGRS.2011.2182495, 2012.
Clement, M. A., Kilsby, C. G., and Moore, P.: Multi-temporal synthetic aperture radar flood mapping using change detection, J. Flood Risk Manage.,
11, 152–168, https://doi.org/10.1111/jfr3.12303, 2018.
Cohen, S., Brakenridge, G. R., Kettner, A., Bates B., Nelson, J., McDonald, R., Huang, Y.-F., Munasinghe, D., and Zhang, J.: Estimating floodwater depths from flood inundation maps and topography, J. Am. Water Resour. Assoc., 54, 847–858, https://doi.org/10.1111/1752-1688.12609, 2018.
Copernicus: Copoernicus Emergency Management Service, https://emergency.copernicus.eu/, last access: 2 August 2022.
Crochemore, L., Isberg, K., Pimentel, R., Pineda, L., Hasan, A., and Arheimer, B.: Lessons learnt from checking the quality of openly accessible river flow data worldwide, Hydrolog. Sci. J., 65, 699–711,
https://doi.org/10.1080/02626667.2019.1659509, 2020.
DeVries, B., Huang, C., Lang, M. W., Jones, J. W., Huang, W., Creed, I. F., and Carroll, M. L.: Automated quantification of surface water inundation in
wetlands using optical satellite imagery, Remote Sens., 9, 807,
https://doi.org/10.3390/rs9080807, 2017.
Di Baldassarre, G., Schumann, G., and Bates P. D.: A technique for the
calibration of hydraulic models using uncertain satellite observations of
flood extent, J. Hydrol., 367, 276–282, https://doi.org/10.1016/j.jhydrol.2009.01.020, 2009.
Directive 2007/60/EC: DIRECTIVE 2007/60/EC Of The European Parliament And Of the Council of 23 October 2007 on the assessment and management of
flood risks, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32007L0060, (last access: 28 July 2022), 2007.
Domeneghetti, A., Schumann, G. J., and Tarpanelli, A.: Preface: remote sensing for flood mapping and monitoring of flood dynamics, Remote Sens., 11, 943, https://doi.org/10.3390/rs11080943, 2019.
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., Meygret, A., Spoto, F.,
Sy, O., Marchese, F., and Bargellini, P.: Sentinel-2: ESA's optical
high-resolution mission for GMES operational services, Remote Sens. Environ., 120, 25–36, https://doi.org/10.1016/j.rse.2011.11.026, 2012.
EM-DAT: C. R. E. D., The international disasters database, https://www.emdat.be (last access: 6 September 2021), 2019.
Gianinetto, M., Villa, P., and Lechi, G.: Postflood Damage Evaluation Using
Landsat TM and ETM+ Data Integrated With DEM, IEEE T. Geosci. Remote, 44, 236–243, https://doi.org/10.1109/TGRS.2005.859952, 2006.
Giordan, D., Notti, D., Villa, A., Zucca, F., Calò, F., Pepe, A., Dutto,
F., Pari, P., Baldo, M., and Allasia, P.: Low cost, multiscale and multi-sensor application for flooded area mapping, Nat. Hazards Earth Syst.
Sci., 18, 1493–1516, https://doi.org/10.5194/nhess-18-1493-2018, 2018.
Giustarini, L., Hostache, R., Matgen, P., Schumann, G., Bates, P., and Mason,
D. C.: A change detection approach to flood mapping in urban areas using
TerraSar-X, IEEE T. Geosci. Remote, 51, 2417–2430, https://doi.org/10.1109/TGRS.2012.2210901, 2013.
Goffi, A., Stroppiana, D., Brivio, P. A., Bordogna, G., and Boschetti, M.:
Towards an automated approach to map flooded areas from Sentinel-2 MSI data
and soft integration of water spectral features, Int. J. Appl. Earth Obs.,
84, 101951, https://doi.org/10.1016/j.jag.2019.101951, 2020.
Google Earth Engine: A planetary-scale platform for Earth science data & analysis, https://earthengine.google.com/, last access: 2 August 2022.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sens. Environ., 202, 18–27, https://doi.org/10.1016/j.rse.2017.06.031, 2017.
GRDC – The Global Runoff Data Centre: The GRDC - the world-wide repository of river discharge data and associated metadata, GRDC, Koblenz, Germany,
https://www.bafg.de/GRDC/EN/01_GRDC/grdc_node.html, last access: 28 July 2022.
Hanna, D. M., Demuth, S., van Lanen, H. A. J., Looser, U., Prudhomme, C.,
Rees, G., Stahl, K., and Tallaksen, L. M.: Large-scale river flow archives:
Importance, current status and future needs, Hydrol. Process., 25, 1191–1200, https://doi.org/10.1002/hyp.7794, 2011.
Hostache, R., Matgen, P., Schumann, G., Puech, C., Hoffmann, L., and Pfister,
L.: Water Level Estimation and Reduction of Hydraulic Model Calibration
Uncertainties Using Satellite SAR Images of Floods, IEEE T. Geosci. Remote,
47, 431–441, https://doi.org/10.1109/TGRS.2008.2008718, 2009.
Huang, W., DeVries, B., Huang, C., Lang, M. W., Jones, J. W., Creed, I. F., and Carroll, M. L.: Automated Extraction of Surface Water Extent from Sentinel-1 Data, Remote Sens., 10, 797, https://doi.org/10.3390/rs10050797, 2018.
IFRC: World Disasters Report 2020: Come Heat or High Water, in: World
Disaster Report 2020,
https://www.ifrc.org/document/world-disasters-report-2020 (last access: 28 July 2022), 2020.
Landuyt, L., Van Wesemael, A., Schumann, G. J. P., Hostache, R., Verhoest, N. E. C., and Van Coillie, F. M. B.: Flood Mapping Based on Synthetic Aperture
Radar: An Assessment of Established Approaches, IEEE T. Geosci. Remote, 57, 722–739, https://doi.org/10.1109/TGRS.2018.2860054, 2019.
Long, N. T. and Trong, B. D.: Flood monitoring of Mekong river delta, Vietnam
using ERS SAR data, in: 22nd Asian Conference on Remote Sensing, 5–9 November 2001, Singapore International Convention and Exhibition Centre, Singapore, 2001.
Longbotham, N., Pacifici, F., Glenn, T., Zare, A., Volpi, M., Tuia, D.,
Christophe, E., Michel, J., Inglada, J., Chanussot, J., and Du, Q.: Multi-modal change detection, application to the detection of flooded areas:
Outcome of the 2009–2010 data fusion contest, IEEE J. Selct. Top. Appl., 5,
331–342, https://doi.org/10.1109/JSTARS.2011.2179638, 2012.
Luo, T., Maddocks, A., Iceland, C., Ward, P., and Winsemius, H.: World's 15 Countries with the Most People Exposed to River Floods, World Resources
Institute,
https://www.wri.org/blog/2015/03/world-s-15-countries-most-people-exposed-river-floods (last access: 2 March 2021), 2015.
Malenovský, Z., Rott, H., Cihlar, J., Schaepman, M. E., García-Santos, G., Fernandes, R., and Berger, M.: Sentinels for science:
Potential of Sentinel-1, -2, and -3 missions for scientific observations of
ocean, cryosphere, and land, Remote Sens. Environ., 120, 91–101,
https://doi.org/10.1016/j.rse.2011.09.026, 2012.
Martinez, J. M. and Le Toan, T.: Mapping of flood dynamics and vegetation
spatial distribution in the Amazon flooplain using multitemporal SAR data,
Remote Sens. Environ., 108, 209–233, https://doi.org/10.1016/j.rse.2006.11.012, 2007.
Martinis, S., Twele, A., and Voigt, S.: Towards operational near real-time
flood detection using a split-based automatic thresholding procedure on high
resolution TerraSAR-X data, Nat. Hazard Earth Syst Sci.., 9, 303–314,
https://doi.org/10.5194/nhess-9-303-2009, 2009.
Mason, D. C., Horritt, M. S., Dall'Amico, J. T. , Scott, T. R., and Bates, P.
D.: Improving river flood extent delineation from synthetic aperture radar
using airborne laser altimetry, IEEE T. Geosci. Remote, 45, 3932–3943,
https://doi.org/10.1109/TGRS.2007.901032, 2007.
Mason, D. C., Schumann, G. J. P., Neal, J. C., Garcia-Pintado, J., and Bates,
P. D.: Automatic near real-time selection of flood water levels from high
resolution synthetic aperture radar images for assimilation into hydraulic
models: a case study, Remote Sens. Environ., 124, 705–716,
https://doi.org/10.1016/j.rse.2012.06.017, 2012.
Massari, C., Tarpanelli, A., and Moramarco, T.: A fast simplified model for
predicting river flood inundation probabilities conditioned on flood extent
data, Hydrol. Process., 29, 2275–2289, https://doi.org/10.1002/hyp.10367, 2015.
Matgen, P., Schumann, G., Henry, J. B., Hoffmann, L., and Pfister, L.: Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management, Int. J. Appl. Earth Obs., 9, 247–263, https://doi.org/10.1016/j.jag.2006.03.003, 2007.
Meybeck, M., Dürr, H. H., and Vörösmarty, C. J.: Global coastal
segmentation and its river catchment contributors: A new look at land-ocean
linkage, Global Biogeochem. Cy., 20, GB1S90, https://doi.org/10.1029/2005GB002540, 2006.
Moramarco, T., Barbetta, S., Pandolfo, C., Tarpanelli, A., Berni, N., and
Morbidelli, R.: The spillway collapse of the Montedoglio dam on the Tiber
River (central Italy): data collection and event analysis, J. Hydrol. Eng., 19, 1264–1270, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000890, 2014.
Mudashiru, R. B., Sabtu, N., Abustan, I., and Balogun, W.: Flood hazard mapping methods: A review, J. Hydrol., 603, 126846, https://doi.org/10.1016/j.jhydrol.2021.126846, 2021.
Musa, Z. N., Popescu, I., and Mynett, A.: A review of applications of satellite SAR, optical, altimetry and DEM data for surface water modelling, mapping and parameter estimation, Hydrol. Earth Syst. Sci., 19, 3755–3769, https://doi.org/10.5194/hess-19-3755-2015, 2015.
Notti, D., Giordan, D., Caló, F., Pepe, A., Zucca, F., and Galve, J. P.:
Potential and Limitations of Open Satellite Data for Flood Mapping, Remote
Sens., 10, 1673, https://doi.org/10.3390/rs10111673, 2018.
Oberstadler, R., Hönsch, H., and Huth, D.: Assessment of the mapping capabilities of ERS‐1 SAR data for flood mapping: a case study in Germany, Hydrol. Process., 11, 1415–1425, https://doi.org/10.1002/(SICI)1099-1085(199708)11:10<1415::AID-HYP532>3.0.CO;2-2, 1997.
Ogilvie, A., Belaud, G., Delenne, C., Bailly, J., Bader, J., Oleksiak, A.,
Ferry, L., and Martin, D.: Decadal monitoring of the Niger Inner Delta flood
dynamics using MODIS optical data, J. Hydrol., 523, 368–383,
https://doi.org/10.1016/j.jhydrol.2015.01.036, 2015.
Plank, S.: Rapid damage assessment by means of multi-temporal SAR – A
comprehensive review and outlook to Sentinel-1, Remote Sens., 6, 4870–4906, https://doi.org/10.3390/rs6064870, 2014.
Sakamoto, T., Van Nguyen, N., Kotera, A., Ohno, H., Ishitsuka, N., and Yokozawa, M.: Detecting temporal changes in the extent of annual flooding
within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series
imagery, Remote Sens. Environ., 109, 295–313, https://doi.org/10.1016/j.rse.2007.01.011, 2007.
Schumann, G. J.: The Full Potential of EO for Flood Applications: Managing Expectations, in: Earth Observation for Flood Applications, Elsevier, 305–320, https://doi.org/10.1016/B978-0-12-819412-6.00014-6, 2021.
Schumann, G. J. P.: The need for scientific rigour and accountability in flood mapping to better support disaster response, Hydrol. Process., 33,
3138–3142, https://doi.org/10.1002/hyp.13547, 2019.
Schumann, G. J. P. and Domeneghetti, A.: Exploiting the proliferation of
current and future satellite observations of rivers, Hydrol. Proceess., 30,
2891–2896, https://doi.org/10.1002/hyp.10825, 2016.
Schumann, G. J. P. and Moller, D. K.: Microwave remote sensing of flood
inundation, Phys. Chem. Earth Pt. A/B/C, 83, 84–95,
https://doi.org/10.1016/j.pce.2015.05.002, 2015.
Schumann, G. J. P., Neal, J. C., Mason, D. C., and Bates, P. D.: The accuracy of sequential aerial photography and SAR data for observing urban flood dynamics, a case study of the UK summer 2007 floods, Remote Sens. Environ.,
115, 2536–2546, https://doi.org/10.1016/j.rse.2011.04.039, 2011.
Seiler, R., Schmidt, J., Diallo, O., and Csaplovics, E.: Flood monitoring in
a semi-arid environment using spatially high resolution radar and optical
data, J. Environ. Manage., 90, 2121–2129, https://doi.org/10.1016/j.jenvman.2007.07.035, 2009.
Takeuchi, S., Konishi, T., Suga, Y., and Kishi, S.: Comparative study for flood detection using JERS-1 SAR and Landsat TM data, in: Proceedings of IGARSs'99, Hamburg, Germany, 873–875, https://doi.org/10.1109/IGARSS.1999.774470, 1999.
Tarpanelli, A.: Codes and dataset of the publication “Effectiveness of Sentinel-1 and Sentinel-2 for Flood Detection Assessment in Europe” (1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.6939820, 2022.
Tarpanelli, A., Brocca, L., Melone, F., and Moramarco, T.: Hydraulic modelling calibration in small basins by using coarse resolution synthetic aperture radar imagery, Hydrol. Process., 27, 1321–1330, https://doi.org/10.1002/hyp.9550, 2013.
Teng, J., Jakeman, A. J., Vaze, J., Croke, B. F., Dutta, D., and Kim, S. J. E. M.: Flood inundation modelling: A review of methods, recent advances and
uncertainty analysis, Environ. Model. Softw., 90, 201–216,
https://doi.org/10.1016/j.envsoft.2017.01.006, 2017.
Torres, R., Snoeij, P., Geudtner, D., Bibby, D., Davidson, M., Attema, E.,
Potin, P., Rommen, B., Floury, N., Brown, M., Navas Traver, I., Deghaye, P.,
Duesmann, B., Rosich, B., Miranda, N., Bruno, C., L'Abbate, M., Croci, R.,
Pietropaolo, A., Huchler, M., and Rostan, F.: GMES Sentinel-1 mission, Remote
Sens. Environ., 120, 9–24, https://doi.org/10.1016/j.rse.2011.05.028, 2012.
Townsend, P. A.: Estimating forest structure in wetlands using multitemporal
SAR, Remote Sens. Environ., 79, 288–304, https://doi.org/10.1016/S0034-4257(01)00280-2, 2002.
Townsend, P. A. and Walsh, S. J.: Modelling flood plain inundation using
integrated GIS with radar and optical remote sensing, Geomorphology, 21,
295–312, https://doi.org/10.1016/S0169-555X(97)00069-X, 1998.
Twele, A., Cao, W., Plank, S., and Martinis, S.: Sentinel-1-based flood mapping: a fully automated processing chain, Int. J. Remote Sens., 37, 2990–3004, https://doi.org/10.1080/01431161.2016.1192304, 2016.
Uddin, K., Matin, M. A., and Meyer, F. J.: Operational flood mapping using
multi-temporal Sentinel-1 SAR images: a case study from Bangladesh, Remote
Sens., 11, 1581, https://doi.org/10.3390/rs11131581, 2019.
Wilson, A. M. and Jetz, W.: Remotely Sensed High-Resolution Global Cloud
Dynamics for Predicting Ecosystem and Biodiversity Distributions, PLoS Biol.,
14, e1002415, https://doi.org/10.1371/journal.pbio.1002415, 2016.
Yonghua, S., Xiaojuan, L., Huili, G., Wenji, Z., and Zhaoning, G.: A study on
optical and SAR data fusion for extracting flooded area, in: Geoscience and
Remote Sensing Symposium, IGARSS 2007, 23–27 July 2007, Barcelona, Spain, 3086–3089, 2007.
Short summary
We analysed 10 years of river discharge data from almost 2000 sites in Europe, and we extracted flood events, as proxies of flood inundations, based on the overpasses of Sentinel-1 and Sentinel-2 satellites to derive the percentage of potential inundation events that they were able to observe. Results show that on average 58 % of flood events are potentially observable by Sentinel-1 and only 28 % by Sentinel-2 due to the obstacle of cloud coverage.
We analysed 10 years of river discharge data from almost 2000 sites in Europe, and we extracted...
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