@phdthesis{Sieg2018,
  author    = {Sieg, Tobias},
  title     = {Reliability of flood damage estimations across spatial scales},
  doi       = {10.25932/publishup-42616},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426161},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIII, 115},
  year      = {2018},
  abstract  = {Extreme Naturereignisse sind ein integraler Bestandteil der Natur der Erde. Sie werden erst dann zu Gefahren f{\"u}r die Gesellschaft, wenn sie diesen Ereignissen ausgesetzt ist. Dann allerdings k{\"o}nnen Naturgefahren verheerende Folgen f{\"u}r die Gesellschaft haben. Besonders hydro-meteorologische Gefahren wie zum Beispiel Flusshochwasser, Starkregenereignisse, Winterst{\"u}rme, Orkane oder Tornados haben ein hohes Schadenspotential und treten rund um den Globus auf. Einhergehend mit einer immer w{\"a}rmer werdenden Welt, werden auch Extremwetterereignisse, welche potentiell Naturgefahren ausl{\"o}sen k{\"o}nnen, immer wahrscheinlicher. Allerdings tr{\"a}gt nicht nur eine sich ver{\"a}ndernde Umwelt zur Erh{\"o}hung des Risikos von Naturgefahren bei, sondern auch eine sich ver{\"a}ndernde Gesellschaft. Daher ist ein angemessenes Risikomanagement erforderlich um die Gesellschaft auf jeder r{\"a}umlichen Ebene an diese Ver{\"a}nderungen anzupassen. Ein essentieller Bestandteil dieses Managements ist die Absch{\"a}tzung der {\"o}konomischen Auswirkungen der Naturgefahren. Bisher allerdings fehlen verl{\"a}ssliche Methoden um die Auswirkungen von hydro-meteorologischen Gefahren abzusch{\"a}tzen. Ein Hauptbestandteil dieser Arbeit ist daher die Entwicklung und Anwendung einer neuen Methode, welche die Verl{\"a}sslichkeit der Schadenssch{\"a}tzung verbessert. Die Methode wurde beispielhaft zur Sch{\"a}tzung der {\"o}konomischen Auswirkungen eines Flusshochwassers auf einzelne Unternehmen bis hin zu den Auswirkungen auf das gesamte Wirtschaftssystem Deutschlands erfolgreich angewendet. Bestehende Methoden geben meist wenig Information {\"u}ber die Verl{\"a}sslichkeit ihrer Sch{\"a}tzungen. Da diese Informationen Entscheidungen zur Anpassung an das Risiko erleichtern, wird die Verl{\"a}sslichkeit der Schadenssch{\"a}tzungen mit der neuen Methode dargestellt. Die Verl{\"a}sslichkeit bezieht sich dabei nicht nur auf die Schadenssch{\"a}tzung selber, sondern auch auf die Annahmen, die {\"u}ber betroffene Geb{\"a}ude gemacht werden. Nach diesem Prinzip kann auch die Verl{\"a}sslichkeit von Annahmen {\"u}ber die Zukunft dargestellt werden, dies ist ein wesentlicher Aspekt f{\"u}r Prognosen. Die Darstellung der Verl{\"a}sslichkeit und die erfolgreiche Anwendung zeigt das Potential der Methode zur Verwendung von Analysen f{\"u}r gegenw{\"a}rtige und zuk{\"u}nftige hydro-meteorologische Gefahren.},
  language  = {en}
}
@phdthesis{Kellermann2017,
  author    = {Kellermann, Patric},
  title     = {Assessing natural risks for railway infrastructure and transportation in Austria},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-103877},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 113},
  year      = {2017},
  abstract  = {Natural hazards can have serious societal and economic impacts. Worldwide, around one third of economic losses due to natural hazards are attributable to floods. The majority of natural hazards are triggered by weather-related extremes such as heavy precipitation, rapid snow melt, or extreme temperatures. Some of them, and in particular floods, are expected to further increase in terms of frequency and/or intensity in the coming decades due to the impacts of climate change. In this context, the European Alps areas are constantly disclosed as being particularly sensitive. In order to enhance the resilience of societies to natural hazards, risk assessments are substantial as they can deliver comprehensive risk information to be used as a basis for effective and sustainable decision-making in natural hazards management. So far, current assessment approaches mostly focus on single societal or economic sectors - e.g. flood damage models largely concentrate on private-sector housing - and other important sectors, such as the transport infrastructure sector, are widely neglected. However, transport infrastructure considerably contributes to economic and societal welfare, e.g. by ensuring mobility of people and goods. In Austria, for example, the national railway network is essential for the European transit of passengers and freights as well as for the development of the complex Alpine topography. Moreover, a number of recent experiences show that railway infrastructure and transportation is highly vulnerable to natural hazards. As a consequence, the Austrian Federal Railways had to cope with economic losses on the scale of several million euros as a result of flooding and other alpine hazards. The motivation of this thesis is to contribute to filling the gap of knowledge about damage to railway infrastructure caused by natural hazards by providing new risk information for actors and stakeholders involved in the risk management of railway transportation. Hence, in order to support the decision-making towards a more effective and sustainable risk management, the following two shortcomings in natural risks research are approached: i) the lack of dedicated models to estimate flood damage to railway infrastructure, and ii) the scarcity of insights into possible climate change impacts on the frequency of extreme weather events with focus on future implications for railway transportation in Austria. With regard to flood impacts to railway infrastructure, the empirically derived damage model Railway Infrastructure Loss (RAIL) proved expedient to reliably estimate both structural flood damage at exposed track sections of the Northern Railway and resulting repair cost. The results show that the RAIL model is capable of identifying flood risk hot spots along the railway network and, thus, facilitates the targeted planning and implementation of (technical) risk reduction measures. However, the findings of this study also show that the development and validation of flood damage models for railway infrastructure is generally constrained by the continuing lack of detailed event and damage data. In order to provide flood risk information on the large scale to support strategic flood risk management, the RAIL model was applied for the Austrian Mur River catchment using three different hydraulic scenarios as input as well as considering an increased risk aversion of the railway operator. Results indicate that the model is able to deliver comprehensive risk information also on the catchment level. It is furthermore demonstrated that the aspect of risk aversion can have marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies. Looking at the results of the investigation on future frequencies of extreme weather events jeopardizing railway infrastructure and transportation in Austria, it appears that an increase in intense rainfall events and heat waves has to be expected, whereas heavy snowfall and cold days are likely to decrease. Furthermore, results indicate that frequencies of extremes are rather sensitive to changes of the underlying thresholds. It thus emphasizes the importance to carefully define, validate, and — if needed — to adapt the thresholds that are used to detect and forecast meteorological extremes. For this, continuous and standardized documentation of damaging events and near-misses is a prerequisite. Overall, the findings of the research presented in this thesis agree on the necessity to improve event and damage documentation procedures in order to enable the acquisition of comprehensive and reliable risk information via risk assessments and, thus, support strategic natural hazards management of railway infrastructure and transportation.},
  language  = {en}
}