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  • 1
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    Toward an adequate level of detail in flood risk assessments (2023)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Flood risk assessments require different disciplines to understand and model the underlying components hazard, exposure, and vulnerability. Many methods and data sets have been refined considerably to cover more details of spatial, temporal, or process information. We compile case studies indicating that refined methods and data have a considerable effect on the overall assessment of flood risk. But are these improvements worth the effort? The adequate level of detail is typically unknown and prioritization of improvements in a specific component is hampered by the lack of an overarching view on flood risk. Consequently, creating the dilemma of potentially being too greedy or too wasteful with the resources available for a risk assessment. A “sweet spot” between those two would use methods and data sets that cover all relevant known processes without using resources inefficiently. We provide three key questions as a qualitative guidance toward this “sweet spot.” For quantitative decision support, more overarching case studies in various contexts are needed to reveal the sensitivity of the overall flood risk to individual components. This could also support the anticipation of unforeseen events like the flood event in Germany and Belgium in 2021 and increase the reliability of flood risk assessments.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: BMBF http://dx.doi.org/10.13039/501100002347
    Description: Federal Environment Agency http://dx.doi.org/10.13039/501100010809
    Description: http://howas21.gfz-potsdam.de/howas21/
    Description: https://www.umwelt.niedersachsen.de/startseite/themen/wasser/hochwasser_amp_kustenschutz/hochwasserrisikomanagement_richtlinie/hochwassergefahren_und_hochwasserrisikokarten/hochwasserkarten-121920.html
    Description: https://download.geofabrik.de/europe/germany.html
    Description: https://emergency.copernicus.eu/mapping/list-of-components/EMSN024
    Description: https://data.jrc.ec.europa.eu/collection/id-0054
    Description: https://oasishub.co/dataset/surface-water-flooding-footprinthurricane-harvey-august-2017-jba
    Description: https://www.wasser.sachsen.de/hochwassergefahrenkarte-11915.html
    Keywords: ddc:551.48 ; decision support ; extreme events ; integrated flood risk management ; risk assessment
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 2
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    Coping with Pluvial Floods by Private Households (2016)
    Molecular Diversity Preservation International
    Details
    Publication Date: 2016-07-21
    Electronic ISSN: 2073-4441
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Molecular Diversity Preservation International
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  • 3
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    Probabilistic Models Significantly Reduce Uncertainty in Hurricane Harvey Pluvial Flood Loss Estimates (2019)
    American Geophysical Union
    Details
    Publication Date: 2019-04-01
    Electronic ISSN: 2328-4277
    Topics: Geosciences
    Published by American Geophysical Union
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  • 4
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    Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes (2019)
    American Geophysical Union
    Details
    Publication Date: 2019-10-01
    Description: Flood damage processes are complex and vary between events and regions. State‐of‐the‐art flood loss models are often developed on basis of empirical damage data from specific case studies and do not perform well when spatially and temporally transferred. This is due to the fact, that such localized models often cover only a small set of possible damage processes from one event and a region. On the other hand, a single generalized model covering multiple events and different regions ignores the variability in damage processes across regions and events due to variables that are not explicitly accounted for individual households. We implement a Hierarchical Bayesian approach to parameterize widely used depth‐damage functions resulting in a Hierarchical (multi‐level) Bayesian Model (HBM) for flood loss estimation that accounts for spatio‐temporal heterogeneity in damage processes. We test and prove the hypothesis that, in transfer scenarios, HBMs are superior compared to generalized and localized regression models. In order to improve loss predictions for regions and events for which no empirical damage data is available, we use variables pertaining to specific region‐ and event‐characteristics representing commonly available expert knowledge as group‐level predictors within the HBM.
    Print ISSN: 0043-1397
    Electronic ISSN: 1944-7973
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by American Geophysical Union
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  • 5
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    Damage assessment in Braunsbach 2016: data collection and analysis for an improved understanding of damaging processes during flash floods (2017)
    Copernicus
    Details
    Publication Date: 2017-12-06
    Description: Flash floods are caused by intense rainfall events and represent an insufficiently understood phenomenon in Germany. As a result of higher precipitation intensities, flash floods might occur more frequently in future. In combination with changing land use patterns and urbanisation, damage mitigation, insurance and risk management in flash-flood-prone regions are becoming increasingly important. However, a better understanding of damage caused by flash floods requires ex post collection of relevant but yet sparsely available information for research. At the end of May 2016, very high and concentrated rainfall intensities led to severe flash floods in several southern German municipalities. The small town of Braunsbach stood as a prime example of the devastating potential of such events. Eight to ten days after the flash flood event, damage assessment and data collection were conducted in Braunsbach by investigating all affected buildings and their surroundings. To record and store the data on site, the open-source software bundle KoBoCollect was used as an efficient and easy way to gather information. Since the damage driving factors of flash floods are expected to differ from those of riverine flooding, a post-hoc data analysis was performed, aiming to identify the influence of flood processes and building attributes on damage grades, which reflect the extent of structural damage. Data analyses include the application of random forest, a random general linear model and multinomial logistic regression as well as the construction of a local impact map to reveal influences on the damage grades. Further, a Spearman's Rho correlation matrix was calculated. The results reveal that the damage driving factors of flash floods differ from those of riverine floods to a certain extent. The exposition of a building in flow direction shows an especially strong correlation with the damage grade and has a high predictive power within the constructed damage models. Additionally, the results suggest that building materials as well as various building aspects, such as the existence of a shop window and the surroundings, might have an effect on the resulting damage. To verify and confirm the outcomes as well as to support future mitigation strategies, risk management and planning, more comprehensive and systematic data collection is necessary.
    Print ISSN: 1561-8633
    Electronic ISSN: 1684-9981
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
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    A comparative survey of the impacts of extreme rainfall in two international case studies (2017)
    Copernicus
    Details
    Publication Date: 2017-04-03
    Description: Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend to include cell-phones in a CATI survey to avoid biased sampling towards certain age groups.
    Electronic ISSN: 2195-9269
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
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    A comparative survey of the impacts of extreme rainfall in two international case studies (2017)
    Copernicus
    Details
    Publication Date: 2017-08-09
    Description: Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam, in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend the inclusion of cell phones in a CATI survey to avoid biased sampling towards certain age groups.
    Print ISSN: 1561-8633
    Electronic ISSN: 1684-9981
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
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    Current and future flood risk of new build homes across different socio-economic neighbourhoods in England and Wales (2021)
    Institute of Physics
    Details
    Publication Date: 2021-04-27
    Print ISSN: 1748-9318
    Electronic ISSN: 1748-9326
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Institute of Physics
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  • 9
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    Data collection for a damage assessment after the flash flood in Braunsbach (Germany) in May 2016 (2017)
    GFZ Data Services
    Details
    Publication Date: 2023-02-09
    Description: Abstract
    Description: A severe flash flood event hit the town of Braunsbach (Baden-Württemberg, Germany) on the evening of May 29, 2016, heavily damaging and destroying several dozens of buildings. It was only one of several disastrous events in Central Europe caused by the low-pressure system “Elvira”. The DFG Research Training Group “Natural hazards and risks in a changing world” (NatRiskChange, GRK 2043/1) at the University of Potsdam investigated the Braunsbach flash flood. In this context damage data for 94 affected buildings, describing building characteristics, the degree of impact and the caused damage, were collected ten days after the flood event and provide the basis for damage assessment studies (Agarwal et al., 2017; Laudan et al., 2017, Vogel et al., 2017).
    Keywords: Flash Flood ; Braunsbach
    Type: Dataset
    Format: 266005 Bytes
    Format: 2 Files
    Format: application/vnd.ms-excel
    Format: application/pdf
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    DATA GFZ
  • 10
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    Probabilistic Models Significantly Reduce Uncertainty in Hurricane Harvey Pluvial Flood Loss Estimates (2021)
    Details
    Publication Date: 2021-04-22
    Description: Pluvial flood risk is mostly excluded in urban flood risk assessment. However, the risk of pluvial flooding is a growing challenge with a projected increase of extreme rainstorms compounding with an ongoing global urbanization. Considered as a flood type with minimal impacts when rainfall rates exceed the capacity of urban drainage systems, the aftermath of rainfall‐triggered flooding during Hurricane Harvey and other events show the urgent need to assess the risk of pluvial flooding. Due to the local extent and small‐scale variations, the quantification of pluvial flood risk requires risk assessments on high spatial resolutions. While flood hazard and exposure information is becoming increasingly accurate, the estimation of losses is still a poorly understood component of pluvial flood risk quantification. We use a new probabilistic multivariable modeling approach to estimate pluvial flood losses of individual buildings, explicitly accounting for the associated uncertainties. Except for the water depth as the common most important predictor, we identified the drivers for having loss or not and for the degree of loss to be different. Applying this approach to estimate and validate building structure losses during Hurricane Harvey using a property level data set, we find that the reliability and dispersion of predictive loss distributions vary widely depending on the model and aggregation level of property level loss estimates. Our results show that the use of multivariable zero‐inflated beta models reduce the 90% prediction intervalsfor Hurricane Harvey building structure loss estimates on average by 78% (totalling U.S.$3.8 billion) compared to commonly used models.
    Description: Key Points Recent severe pluvial flood events highlight the need to integrate pluvial flooding in urban flood risk assessment Probabilistic models provide reliable estimation of pluvial flood loss across spatial scales Beta distribution model reduces the 90% prediction interval for Hurricane Harvey building loss by U.S.$3.8 billion or 78%
    Description: Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347
    Description: NSF GRFP
    Description: Fulbright Doctoral Program
    Keywords: 551.5 ; pluvial flooding ; loss modeling ; urban flooding ; probabilistic ; Hurricane Harvey ; climate change adaptation
    Type: article
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    CITATION GEO-LEO
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