@phdthesis{Holsten2013,
  author    = {Holsten, Anne},
  title     = {Climate change vulnerability assessments in the regional context},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-66836},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {Adapting sectors to new conditions under climate change requires an understanding of regional vulnerabilities. Conceptually, vulnerability is defined as a function of sensitivity and exposure, which determine climate impacts, and adaptive capacity of a system. Vulnerability assessments for quantifying these components have become a key tool within the climate change field. However, there is a disagreement on how to make the concept operational in studies from a scientific perspective. This conflict leads to many still unsolved challenges, especially regarding the quantification and aggregation of the components and their suitable level of complexity. This thesis therefore aims at advancing the scientific foundation of such studies by translating the concept of vulnerability into a systematic assessment structure. This includes all components and implies that for each considered impact (e.g. flash floods) a clear sensitive entity is defined (e.g. settlements) and related to a direction of change for a specific climatic stimulus (e.g. increasing impact due to increasing days with heavy precipitation). Regarding the challenging aggregation procedure, two alternative methods allowing a cross-sectoral overview are introduced and their advantages and disadvantages discussed. This assessment structure is subsequently exemplified for municipalities of the German state North Rhine-Westphalia via an indicator-based deductive approach using information from literature. It can be transferred also to other regions. As for many relevant sectors, suitable indicators to express the vulnerability components are lacking, new quantification methods are developed and applied in this thesis, for example for the forestry and health sector. A lack of empirical data on relevant thresholds is evident, for example which climatic changes would cause significant impacts. Consequently, the multi-sectoral study could only provide relative measures for each municipality, in relation to the region. To fill this gap, an exemplary sectoral study was carried out on windthrow impacts in forests to provide an absolute quantification of the present and future impact. This is achieved by formulating an empirical relation between the forest characteristics and damage based on data from a past storm event. The resulting measure indicating the sensitivity is then combined with wind conditions. Multi-sectoral vulnerability assessments require considerable resources, which often hinders the implementation. Thus, in a next step, the potential for reducing the complexity is explored. To predict forest fire occurrence, numerous meteorological indices are available, spanning over a range of complexity. Comparing their performance, the single variable relative humidity outperforms complex indicators for most German states in explaining the monthly fire pattern. This is the case albeit it is itself an input factor in most indices. Thus, this meteorological factor alone is well suited to evaluate forest fire danger in many Germany regions and allows a resource-efficient assessment. Similarly, the complexity of methods is assessed regarding the application of the ecohydrological model SWIM to the German region of Brandenburg. The inter-annual soil moisture levels simulated by this model can only poorly be represented by simpler statistical approach using the same input data. However, on a decadal time horizon, the statistical approach shows a good performance and a strong dominance of the soil characteristic field capacity. This points to a possibility to reduce the input factors for predicting long-term averages, but the results are restricted by a lack of empirical data on soil water for validation. The presented assessments of vulnerability and its components have shown that they are still a challenging scientific undertaking. Following the applied terminology, many problems arise when implementing it for regional studies. Advances in addressing shortcomings of previous studies have been made by constructing a new systematic structure for characterizing and aggregating vulnerability components. For this, multiple approaches were presented, but they have specific advantages and disadvantages, which should also be carefully considered in future studies. There is a potential to simplify some methods, but more systematic assessments on this are needed. Overall, this thesis strengthened the use of vulnerability assessments as a tool to support adaptation by enhancing their scientific basis.},
  language  = {en}
}
@phdthesis{Mester2023,
  author    = {Mester, Benedikt},
  title     = {Modeling flood-induced human displacement risk under global change},
  doi       = {10.25932/publishup-60929},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-609293},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVI, 143},
  year      = {2023},
  abstract  = {Extreme flooding displaces an average of 12 million people every year. Marginalized populations in low-income countries are in particular at high risk, but also industrialized countries are susceptible to displacement and its inherent societal impacts. The risk of being displaced results from a complex interaction of flood hazard, population exposed in the floodplains, and socio-economic vulnerability. Ongoing global warming changes the intensity, frequency, and duration of flood hazards, undermining existing protection measures. Meanwhile, settlements in attractive yet hazardous flood-prone areas have led to a higher degree of population exposure. Finally, the vulnerability to displacement is altered by demographic and social change, shifting economic power, urbanization, and technological development. These risk components have been investigated intensively in the context of loss of life and economic damage, however, only little is known about the risk of displacement under global change. This thesis aims to improve our understanding of flood-induced displacement risk under global climate change and socio-economic change. This objective is tackled by addressing the following three research questions. First, by focusing on the choice of input data, how well can a global flood modeling chain reproduce flood hazards of historic events that lead to displacement? Second, what are the socio-economic characteristics that shape the vulnerability to displacement? Finally, to what degree has climate change potentially contributed to recent flood-induced displacement events? To answer the first question, a global flood modeling chain is evaluated by comparing simulated flood extent with satellite-derived inundation information for eight major flood events. A focus is set on the sensitivity to different combinations of the underlying climate reanalysis datasets and global hydrological models which serve as an input for the global hydraulic model. An evaluation scheme of performance scores shows that simulated flood extent is mostly overestimated without the consideration of flood protection and only for a few events dependent on the choice of global hydrological models. Results are more sensitive to the underlying climate forcing, with two datasets differing substantially from a third one. In contrast, the incorporation of flood protection standards results in an underestimation of flood extent, pointing to potential deficiencies in the protection level estimates or the flood frequency distribution within the modeling chain. Following the analysis of a physical flood hazard model, the socio-economic drivers of vulnerability to displacement are investigated in the next step. For this purpose, a satellite- based, global collection of flood footprints is linked with two disaster inventories to match societal impacts with the corresponding flood hazard. For each event the number of affected population, assets, and critical infrastructure, as well as socio-economic indicators are computed. The resulting datasets are made publicly available and contain 335 displacement events and 695 mortality/damage events. Based on this new data product, event-specific displacement vulnerabilities are determined and multiple (national) dependencies with the socio-economic predictors are derived. The results suggest that economic prosperity only partially shapes vulnerability to displacement; urbanization, infant mortality rate, the share of elderly, population density and critical infrastructure exhibit a stronger functional relationship, suggesting that higher levels of development are generally associated with lower vulnerability. Besides examining the contextual drivers of vulnerability, the role of climate change in the context of human displacement is also being explored. An impact attribution approach is applied on the example of Cyclone Idai and associated extreme coastal flooding in Mozambique. A combination of coastal flood modeling and satellite imagery is used to construct factual and counterfactual flood events. This storyline-type attribution method allows investigating the isolated or combined effects of sea level rise and the intensification of cyclone wind speeds on coastal flooding. The results suggest that displacement risk has increased by 3.1 to 3.5\% due to the total effects of climate change on coastal flooding, with the effects of increasing wind speed being the dominant factor. In conclusion, this thesis highlights the potentials and challenges of modeling flood- induced displacement risk. While this work explores the sensitivity of global flood modeling to the choice of input data, new questions arise on how to effectively improve the reproduction of flood return periods and the representation of protection levels. It is also demonstrated that disentangling displacement vulnerabilities is feasible, with the results providing useful information for risk assessments, effective humanitarian aid, and disaster relief. The impact attribution study is a first step in assessing the effects of global warming on displacement risk, leading to new research challenges, e.g., coupling fluvial and coastal flood models or the attribution of other hazard types and displacement events. This thesis is one of the first to address flood-induced displacement risk from a global perspective. The findings motivate for further development of the global flood modeling chain to improve our understanding of displacement vulnerability and the effects of global warming.},
  language  = {en}
}