In this paper, I estimate the economic cost associated with flood risks in Sweden. A hedonic price model combined with a distance defined difference-in-differences method is used to estimate the marginal change in property prices due to new information regarding flood risks. The results reveal a robust effect on owner-occupied properties from predicted floods from the sea. The willingness to pay for increasing the distance to the predicted flooded area is estimated to be 0.187% per meter. A similar, though smaller (0.045% per meter) effect is found for all properties in proximity to floods from streams. The effects of the information regarding flood risks are limited to the year after the release. The results are especially important in a Swedish setting due to its numerous streams and lakes and extensive coastline. That the value of the risk of floods is limited to one year should be further investigated and considered when establishing policies regarding the information provided when a property is listed for sale.

The Bac Hung Hai zone is the greatest basin in the Red River Delta in Vietnam and also one of the most densely populated regions of the planet. It is mainly a rural region and its economy is dominated by agriculture. In the context of frequent and larger floods in the Bac Hung Hai zone, causing deep socio-economical consequences, the focus of this study is to establish cartography of the high risk areas for flooding in the Bac Hung Hai region using remote sensing and GIS to assist land management. The preparation of a map describing land management in this region is more complicated because parcels for farming are very small and not homogeneous. A consistent and precise map of land use is essential for studies of flooding. The secondary objective is to improve the land use map. To this effect, a classification has been applied to the combination of the spectral bands and textures (TM and ETM[indice supérieur +]) of Landsat and a radar image (ERS). The addition of this information to the spectral bands increases the accuracy of classification by 1% to 4%, according to the dates selected. Additionally, in the study zone where there are few days without clouds, a problem related to the optical satellite image is the cloud cover. Then, the use of radar images will provide ground information for areas hidden by clouds where spectral images are not sufficient. To reach these goals, we have determined the main biophysical considerations that influence flooding. Then, these considerations have been combined in a multi-criteria analysis to evaluate the risks of flooding in the entire basin area. The results show that high to very high risks affect 47% of the area studied and that the south-east region, center, and north-east present the greatest risk.

The thesis is focused on the issue of black swans in the water structure. More detail risks and hazard dam. History has shown us that sophisticatedly structure as dam is not perfect. Failure can cause weather, natural disaster, bad chance or deliberate attack. A detailed analysis of the current situation, I mapped historic dam failure, which can cause black swan. In thesis is a reseach on knowledge of the population in this issue. Based on the analysis and obteined information was proposed measures to improve the situation.

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Flood risks in urban settlements are often determined based upon hydrological and hydrodynamic design events and the existing building stock. After a flood event, a high discrepancy between the assessed risk, the observed flow conditions and resulting loss and damage in flood prone areas is mostly found. This illustrates that flood risks are subject to high spatial and temporal dynamics. Hence, the assessment of the dynamics of flood risks involves considerable variability (variations in the mean state) and change (medium-/long-term trends). In addition, uncertainties play a significant role. Current risk assessment approaches do not sufficiently represent all processes relevant for the dynamics and uncertainties of flood risk generation. The aim of the thesis is a comprehensive research on the dynamics and uncertainties of fluvial flood risks due to variability and change. It pursues the objective to generate risk curves describing the dynamics (variability and change) and their epistemic uncertainties. To achieve this three research questions are answered. The first research question (RQ1) “What are the influences of the dynamics of flood risks?” identifies (i) major processes involved in flood risk generation, (ii) factors of these processes prone to variability and change, and (iii) drivers triggering the factor’s alteration. The second research question (RQ2) “What is an appropriate way to simulate and analyse the dynamics of flood risks?” concentrates on modules and tools for simulations of the entire flood risk system, the impacts of the drivers, and uncertainties. The answer of RQ2 focuses on climate change as one (group of) driver(s) of dynamics (change) and simulates the current state and future scenarios. The third research question (RQ3) ”What are the flood risk dynamics in a specific catchment?” is determined quantitatively resulting in risk curves with their uncertainty bounds. To investigate the dynamics and uncertainties of flood risks a three-tiered framework is designed including (1) a conceptual, (2) a methodological and (3) a technological framework. The Conceptual Framework (CF) is assigned to RQ1 focusing on the main drivers of the dynamics by conceptualisation of different subsystems for the assessment of flood risks. The Methodological Framework (MF) is used to answer RQ2 providing an appropriate way to simulate and analyse the dynamics of flood risks by methodical operationalisation of the subsystems through modules. It focuses on climate change considering simulations of future scenarios and various sources of uncertainties. The Technological Framework (TF) describes how different modules and methods are combined to implement the MF by technical realisation of the sequence of modules. An investigation area is selected for empirical testing of the three-tiered framework. Four modules are developed and tested by a comprehensive multi-model chain representing the flood risk system of the Mulde River catchment and the municipality of Bennewitz. The first module Climate Data Ensemble applies two climate data ensembles: WEREX V and COSMO-CLM accounting for climate variability as well as future change by climate scenarios and uncertainties due to climate models and realisation runs. The second module Hydrologic Modelling uses two models: HBV and WaSiM-ETH optimised by AMALGAM to generate flood events. This module addresses model and parameter uncertainty. The third module Hydrodynamic Modelling applies HEC-RAS and LISFLOOD-FP to derive inundation areas and to account for model uncertainty. The fourth module Damage Modelling combines construction and inventory damage. Risk curves with their bandwidth due dynamics and uncertainties are generated. The analysis of the dynamics and uncertainties is carried out by means of the ANOVA approach allowing for a quantification of the impacts due to the selected climate scenario, climate model, realisation, and hydrological parameter set. A large contribution of climate models and the rather small influence of hydrological parametrisation on rare flood events are detected. A wide range in the risk curves illustrates the influence of climate scenarios, climate models, and hydrologic parametrisations on monetary damages. The large number of high resolution, continuous long-term model runs as well as model coupling for the flood risk system, makes high performance computing (HPC) and big data assessment essential.:1 Introduction 1.1 Background 1.2 Problem Statement 1.3 Aim, Objective and Research Questions 1.4 Research Strategy and Outline 2 State of the Art 2.1 Flood Risks and Flood Risk Systems 2.2 Dynamics of Flood Risk Systems 2.3 Assessment of Flood Risk Considering Change and Uncertainty 3 Three-tiered Framework for the Assessment of the Dynamics of Flood Risks 3.1 Conceptual Framework 3.1.1 Major Processes of Flood Risk Generation 3.1.1.1 Atmospheric Processes 3.1.1.2 Hydrologic Processes 3.1.1.3 Hydrodynamic Processes 3.1.1.4 Loss and Damage Processes 3.1.1.5 Flood Risks 3.1.2 Factors Prone to Variability and Change 3.1.3 Identification of Drivers and Dynamics 3.2 Methodological Framework 3.2.1 Simulation of Flood Risks 3.2.1.1 Atmospheric Processes – Climate Data Ensemble Module 3.2.1.2 Hydrologic Processes – Hydrological Modelling Module 3.2.1.3 Hydrodynamic Processes – Hydrodynamic Modelling Module 3.2.1.4 Loss and Damage Processes – Damage Modelling Module 3.2.1.5 Flood Risks 3.2.2 Dynamics of Flood Risks Caused by Climate Change as Driver and Uncertainties 3.3 Technological Framework 3.3.1 Software Components 3.3.1.1 Climate Data Ensemble Module 3.3.1.2 Hydrological Modelling Module 3.3.1.3 Hydrodynamic Modelling Module 3.3.1.4 Damage Modelling Module 3.3.1.5 Flood Risks Investigated by Visual Analytics 3.3.2 Development Protocols 4 Implementation of the Framework as Methodology and Empirical Testing 4.1 Flood Risk System of the Mulde River and the Municipality of Bennewitz 4.2 Methodology Testing for the Mulde River and the Municipality of Bennewitz 4.2.1 Climate Data Ensemble Module 4.2.1.1 Module Implementation 4.2.1.2 Results for the Reference Period 4.2.1.3 Results for Future Projections 4.2.2 Hydrologic Modelling Module 4.2.2.1 Module Implementation 4.2.2.2 Results for the Reference Period 4.2.2.3 Results for Future Projections 4.2.3 Hydrodynamic Modelling Module 4.2.3.1 Module Implementation 4.2.3.2 Results for the Reference Period 4.2.3.3 Results for Future Projections 4.2.4 Damage Modelling Module 4.2.4.1 Module Implementation 4.2.4.2 Results for Future Projections 4.3 Dynamics of Flood Risks Resulting in Flood Risk Curves and Uncertainty Quantification 5 Discussion 5.1 Discussion of the Three-tiered Framework 5.2 Discussion of the Implementation of the Framework as Methodology and Empirical Testing 5.2.1 Climate Data Ensemble Module 5.2.2 Hydrologic Modelling Module 5.2.3 Hydrodynamic Modelling Module 5.2.4 Damage Modelling Module 5.2.5 Dynamics of Flood Risks Resulting in Flood Risk Curves and Uncertainty Quantification 6 Conclusions and Outlook 6.1 Conclusions 6.2 Outlook References A Appendix Basic Information B Appendix Results B.1 Appendix Results Climate Data Ensemble Module B.2 Appendix Results Hydrologic Modelling Module B.3 Appendix Results Hydrodynamic Modelling Module B.4 Appendix Results Damage Modelling Module B.5 Appendix Results Dynamics and Uncertainties of Flood Risks

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