@phdthesis{MetinUsta2021,
  author    = {Metin Usta, Ay{\c{s}}e Duha},
  title     = {The role of risk components and spatial dependence in flood risk estimations},
  doi       = {10.25932/publishup-49255},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-492554},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIX, 97},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Krummenauer2022,
  author    = {Krummenauer, Linda},
  title     = {Global heat adaptation among urban populations and its evolution under different climate futures},
  doi       = {10.25932/publishup-55929},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-559294},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 161},
  year      = {2022},
  abstract  = {Heat and increasing ambient temperatures under climate change represent a serious threat to human health in cities. Heat exposure has been studied extensively at a global scale. Studies comparing a defined temperature threshold with the future daytime temperature during a certain period of time, had concluded an increase in threat to human health. Such findings however do not explicitly account for possible changes in future human heat adaptation and might even overestimate heat exposure. Thus, heat adaptation and its development is still unclear. Human heat adaptation refers to the local temperature to which populations are adjusted to. It can be inferred from the lowest point of the U- or V-shaped heat-mortality relationship (HMR), the Minimum Mortality Temperature (MMT). While epidemiological studies inform on the MMT at the city scale for case studies, a general model applicable at the global scale to infer on temporal change in MMTs had not yet been realised. The conventional approach depends on data availability, their robustness, and on the access to daily mortality records at the city scale. Thorough analysis however must account for future changes in the MMT as heat adaptation happens partially passively. Human heat adaptation consists of two aspects: (1) the intensity of the heat hazard that is still tolerated by human populations, meaning the heat burden they can bear and (2) the wealth-induced technological, social and behavioural measures that can be employed to avoid heat exposure. The objective of this thesis is to investigate and quantify human heat adaptation among urban populations at a global scale under the current climate and to project future adaptation under climate change until the end of the century. To date, this has not yet been accomplished. The evaluation of global heat adaptation among urban populations and its evolution under climate change comprises three levels of analysis. First, using the example of Germany, the MMT is calculated at the city level by applying the conventional method. Second, this thesis compiles a data pool of 400 urban MMTs to develop and train a new model capable of estimating MMTs on the basis of physical and socio-economic city characteristics using multivariate non-linear multivariate regression. The MMT is successfully described as a function of the current climate, the topography and the socio-economic standard, independently of daily mortality data for cities around the world. The city-specific MMT estimates represents a measure of human heat adaptation among the urban population. In a final third analysis, the model to derive human heat adaptation was adjusted to be driven by projected climate and socio-economic variables for the future. This allowed for estimation of the MMT and its change for 3 820 cities worldwide for different combinations of climate trajectories and socio-economic pathways until 2100. The knowledge on the evolution of heat adaptation in the future is a novelty as mostly heat exposure and its future development had been researched. In this work, changes in heat adaptation and exposure were analysed jointly. A wide range of possible health-related outcomes up to 2100 was the result, of which two scenarios with the highest socio-economic developments but opposing strong warming levels were highlighted for comparison. Strong economic growth based upon fossil fuel exploitation is associated with a high gain in heat adaptation, but may not be able to compensate for the associated negative health effects due to increased heat exposure in 30\% to 40\% of the cities investigated caused by severe climate change. A slightly less strong, but sustainable growth brings moderate gains in heat adaptation but a lower heat exposure and exposure reductions in 80\% to 84\% of the cities in terms of frequency (number of days exceeding the MMT) and intensity (magnitude of the MMT exceedance) due to a milder global warming. Choosing a 2 ° C compatible development by 2100 would therefore lower the risk of heat-related mortality at the end of the century. In summary, this thesis makes diverse and multidisciplinary contributions to a deeper understanding of human adaptation to heat under the current and the future climate. It is one of the first studies to carry out a systematic and statistical analysis of urban characteristics which are useful as MMT drivers to establish a generalised model of human heat adaptation, applicable at the global level. A broad range of possible heat-related health options for various future scenarios was shown for the first time. This work is of relevance for the assessment of heat-health impacts in regions where mortality data are not accessible or missing. The results are useful for health care planning at the meso- and macro-level and to urban- and climate change adaptation planning. Lastly, beyond having met the posed objective, this thesis advances research towards a global future impact assessment of heat on human health by providing an alternative method of MMT estimation, that is spatially and temporally flexible in its application.},
  language  = {en}
}