ALBERT

Description: Private precautionary measures play an increasingly important role in flood risk management. The degree to which private precautionary measures mitigate flood risk depends mainly on the type of measure (and how effective it is) and how frequently and successfully it is implemented. These aspects are influenced by a complex interaction of physical and socio-economic processes, which makes the assessment and the prediction of the mitigation of flood risk via private precautionary measures a challenge. This paper provides an overview of factors and processes that influence the implementation and effectiveness of private precaution in mitigating flood risk, underpinning it with highlights from international examples. We recommend private precautionary measures for further use to improve flood risk mitigation, but stress that they need to be considered and implemented through a holistic systems approach to maximize their effectiveness

Description: Flooding is a vast problem in many parts of the world, including Europe. It occurs mainly due to extreme weather conditions (e.g. heavy rainfall and snowmelt) and the consequences of flood events can be devastating. Flood risk is mainly defined as a combination of the probability of an event and its potential adverse impacts. Therefore, it covers three major dynamic components: hazard (physical characteristics of a flood event), exposure (people and their physical environment that being exposed to flood), and vulnerability (the elements at risk). Floods are natural phenomena and cannot be fully prevented. However, their risk can be managed and mitigated. For a sound flood risk management and mitigation, a proper risk assessment is needed. First of all, this is attained by a clear understanding of the flood risk dynamics. For instance, human activity may contribute to an increase in flood risk. Anthropogenic climate change causes higher intensity of rainfall and sea level rise and therefore an increase in scale and frequency of the flood events. On the other hand, inappropriate management of risk and structural protection measures may not be very effective for risk reduction. Additionally, due to the growth of number of assets and people within the flood-prone areas, risk increases. To address these issues, the first objective of this thesis is to perform a sensitivity analysis to understand the impacts of changes in each flood risk component on overall risk and further their mutual interactions. A multitude of changes along the risk chain are simulated by regional flood model (RFM) where all processes from atmosphere through catchment and river system to damage mechanisms are taken into consideration. The impacts of changes in risk components are explored by plausible change scenarios for the mesoscale Mulde catchment (sub-basin of the Elbe) in Germany. A proper risk assessment is ensured by the reasonable representation of the real-world flood event. Traditionally, flood risk is assessed by assuming homogeneous return periods of flood peaks throughout the considered catchment. However, in reality, flood events are spatially heterogeneous and therefore traditional assumption misestimates flood risk especially for large regions. In this thesis, two different studies investigate the importance of spatial dependence in large scale flood risk assessment for different spatial scales. In the first one, the “real” spatial dependence of return period of flood damages is represented by continuous risk modelling approach where spatially coherent patterns of hydrological and meteorological controls (i.e. soil moisture and weather patterns) are included. Further the risk estimations under this modelled dependence assumption are compared with two other assumptions on the spatial dependence of return periods of flood damages: complete dependence (homogeneous return periods) and independence (randomly generated heterogeneous return periods) for the Elbe catchment in Germany. The second study represents the “real” spatial dependence by multivariate dependence models. Similar to the first study, the three different assumptions on the spatial dependence of return periods of flood damages are compared, but at national (United Kingdom and Germany) and continental (Europe) scales. Furthermore, the impacts of the different models, tail dependence, and the structural flood protection level on the flood risk under different spatial dependence assumptions are investigated. The outcomes of the sensitivity analysis framework suggest that flood risk can vary dramatically as a result of possible change scenarios. The risk components that have not received much attention (e.g. changes in dike systems and in vulnerability) may mask the influence of climate change that is often investigated component. The results of the spatial dependence research in this thesis further show that the damage under the false assumption of complete dependence is 100 % larger than the damage under the modelled dependence assumption, for the events with return periods greater than approximately 200 years in the Elbe catchment. The complete dependence assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139 %, 188 % and 246 % for the UK, Germany and Europe, respectively. The misestimation of risk under different assumptions can vary from upstream to downstream of the catchment. Besides, tail dependence in the model and flood protection level in the catchments can affect the risk estimation and the differences between different spatial dependence assumptions. In conclusion, the broader consideration of the risk components, which possibly affect the flood risk in a comprehensive way, and the consideration of the spatial dependence of flood return periods are strongly recommended for a better understanding of flood risk and consequently for a sound flood risk management and mitigation.

Description: Hochwasser sind ein großes Problem und treten hauptsächlich aufgrund extremer Wetterbedingungen (z. B. starker Regen und Schneeschmelze) auf. Die Folgen von Hochwasserereignissen können verheerend sein. Das Konzept des Hochwasserrisikos beinhaltet die drei Komponenten: Gefahr, Exposition und Vulnerabilität. Hochwasser sind natürliche Phänomene und können nicht sicher verhindert werden. Das Risiko kann jedoch gesteuert und gemindert werden. Für ein solides Hochwasserrisikomanagement und die Minderung des Risikos ist eine ordnungsgemäße Risikobewertung und ein klares Verständnis der Hochwasserrisikodynamik erforderlich. Beispielsweise verursacht der anthropogene Klimawandel eine höhere Intensität der Niederschläge und einen Anstieg des Meeresspiegels und damit eine Zunahme des Ausmaßes und der Häufigkeit von Hochwasserereignissen. Andererseits können unangemessene strukturelle Schutzmaßnahmen, das Anwachsen von Vermögenswerten und eine steigende Anzahl betroffener Personen in den hochwassergefährdeten Gebieten das Risiko erhöhen. Um diese Probleme zu adressieren, besteht ein Ziel dieser Arbeit aus der Durchführung einer Sensitivitätsanalyse, um die Auswirkungen von Änderungen in jeder Hochwasserrisikokomponente auf das Gesamtrisiko und deren Wechselwirkungen untereinander zu verstehen. Eine angemessene Risikobewertung wird auch durch die korrekte k Darstellung des realen Hochwasserereignisses erreicht. Traditionell wird das Hochwasserrisiko bewertet, indem homogene Wiederkehrintervalle von Hochwasserspitzen im gesamten Einzugsgebiet angenommen werden. In der Realität sind Hochwasserereignisse jedoch räumlich heterogen, weshalb die traditionelle Annahme von Homogenität das Hochwasserrisiko insbesondere für große Einzugsgebiete falsch einschätzt. In dieser Arbeit wird die Bedeutung der räumlichen Abhängigkeit bei der Bewertung des Hochwasserrisikos in großem Maßstab in zwei Studien für verschiedene räumliche Skalen untersucht. In der ersten Untersuchung wird die „reale“ räumliche Abhängigkeit durch einen kontinuierlichen Risikomodellierungsansatz dargestellt. Zusätzlich werden die Risikoabschätzungen unter dieser modellierten Abhängigkeitsannahme mit zwei weiteren Annahmen zur räumlichen Abhängigkeit der Wiederkehrintervalle von Hochwasser verglichen: vollständige Abhängigkeit und Unabhängigkeit für das Elbeeinzugsgebiet in Deutschland. Die zweite Studie repräsentiert die „reale“ räumliche Abhängigkeit durch ein copula-basiertes Abhängigkeitsmodell. In ähnlicher Weise werden die drei verschiedenen Annahmen zur räumlichen Abhängigkeit der Wiederkehrintervalle von Hochwasser auf nationaler und kontinentaler Ebene verglichen. Außerdem wird der Einfluss von „Tail-dependences“ im Modell sowie von Hochwasserschutzmaßnahmen auf die räumliche Abhängigkeit untersucht. Die Ergebnisse dieser Arbeit unter Anwendung des Sensitivitätsanalyse-Frameworks zeigen, dass das Hochwasserrisiko aufgrund möglicher Änderungsszenarien dramatisch variieren kann. Der Einfluss des Klimawandels kann durch Änderungen anderer Risikokomponenten (z. B. Änderungen der Deichsysteme und der Vulnerabilität) überdeckt werden. Die Untersuchung zur räumlichen Abhängigkeit zeigen, dass der Schaden unter der Annahme vollständiger Abhängigkeit für Ereignisse mit Wiederkehrintervalle von mehr als ungefähr 200 Jahren im Elbeeinzugsgebiet 100 % größer als der Schaden unter modellierter Abhängigkeit. Die Annahme vollständiger Abhängigkeit überschätzt den 200-jährigen Hochwasserschaden, einen Referenzindikator für die Versicherungsbranche, um 139 %, 188 % und 246 % für Vereinigte Königreich, Deutschland und Europa. Die Fehleinschätzung des Hochwasserrisikos kann unter verschiedenen Annahmen von Abhängigkeit zwischen Oberlauf und Unterlauf eines Einzugsgebietes stark variieren. Zudem können „Tail-dependences“ im Modell sowie der Hochwasserschutz im Einzugsgebiet die Ergebnisse der Risikoabschätzung, unter verschiedenen Annahmen der räumlichen Abhängigkeit, beeinflussen. Abschließend wird eine umfangreiche Berücksichtigung der Risikokomponenten und insbesondere der räumlichen Abhängigkeit von Wiederkehrintervallen stark empfohlen, um das Hochwasserrisiko und damit dessen Management und Minderung besser verstehen zu können.

Description: Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100 % for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.

Description: Fluvial flood risk systems are characterized by complex interactions and feedbacks as well as subject to changes of hazard, exposure and vulnerability. Disregarding spatial and temporal dependencies and changes in the components of risk introduces biases to risk estimates. A systems approach to large-scale flood risk assessment and management is proposed to account for the complexity and dynamic nature of flood risk. The systems approach provides methods and tools that offer a more comprehensive view to flood risk, reveal the relevant interactions, and quantify feedbacks in flood risk systems. Policymakers and flood risk managers can benefit from the systems approach in the development of comprehensive risk reduction strategies.

Description: Recently, flood risk assessments have been extended to national and continental scales. Most of these assessments assume homogeneous scenarios, i.e. the regional risk estimate is obtained by summing up the local estimates, whereas each local damage value has the same probability of exceedance. This homogeneity assumption ignores the spatial variability in the flood generation processes. Here, we develop a multi-site, extreme value statistical model for 379 catchments across Europe, generate synthetic flood time series which consider the spatial correlation between flood peaks in all catchments, and compute corresponding economic damages. We find that the homogeneity assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139%, 188% and 246% for the United Kingdom (UK), Germany and Europe, respectively. Our study demonstrates the importance of considering the spatial dependence patterns, particularly of extremes, in large-scale risk assessments.