@phdthesis{Kieling2015,
  author    = {Kieling, Katrin},
  title     = {Quantification of ground motions by broadband simulations},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-85989},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIV, 118},
  year      = {2015},
  abstract  = {In many procedures of seismic risk mitigation, ground motion simulations are needed to test systems or improve their effectiveness. For example they may be used to estimate the level of ground shaking caused by future earthquakes. Good physical models for ground motion simulation are also thought to be important for hazard assessment, as they could close gaps in the existing datasets. Since the observed ground motion in nature shows a certain variability, part of which cannot be explained by macroscopic parameters such as magnitude or position of an earthquake, it would be desirable that a good physical model is not only able to produce one single seismogram, but also to reveal this natural variability. In this thesis, I develop a method to model realistic ground motions in a way that is computationally simple to handle, permitting multiple scenario simulations. I focus on two aspects of ground motion modelling. First, I use deterministic wave propagation for the whole frequency range - from static deformation to approximately 10 Hz - but account for source variability by implementing self-similar slip distributions and rough fault interfaces. Second, I scale the source spectrum so that the modelled waveforms represent the correct radiated seismic energy. With this scaling I verify whether the energy magnitude is suitable as an explanatory variable, which characterises the amount of energy radiated at high frequencies - the advantage of the energy magnitude being that it can be deduced from observations, even in real-time. Applications of the developed method for the 2008 Wenchuan (China) earthquake, the 2003 Tokachi-Oki (Japan) earthquake and the 1994 Northridge (California, USA) earthquake show that the fine source discretisations combined with the small scale source variability ensure that high frequencies are satisfactorily introduced, justifying the deterministic wave propagation approach even at high frequencies. I demonstrate that the energy magnitude can be used to calibrate the high-frequency content in ground motion simulations. Because deterministic wave propagation is applied to the whole frequency range, the simulation method permits the quantification of the variability in ground motion due to parametric uncertainties in the source description. A large number of scenario simulations for an M=6 earthquake show that the roughness of the source as well as the distribution of fault dislocations have a minor effect on the simulated variability by diminishing directivity effects, while hypocenter location and rupture velocity more strongly influence the variability. The uncertainty in energy magnitude, however, leads to the largest differences of ground motion amplitude between different events, resulting in a variability which is larger than the one observed. For the presented approach, this dissertation shows (i) the verification of the computational correctness of the code, (ii) the ability to reproduce observed ground motions and (iii) the validation of the simulated ground motion variability. Those three steps are essential to evaluate the suitability of the method for means of seismic risk mitigation.},
  language  = {en}
}
@article{WeatherillKothaCotton2020,
  author    = {Weatherill, Graeme and Kotha, Sreeram Reddy and Cotton, Fabrice Pierre},
  title     = {Re-thinking site amplification in regional seismic risk assessment},
  series = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute},
  volume    = {36},
  journal   = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute},
  number    = {1_SUPPL},
  publisher = {Sage Publishing},
  address   = {Thousand Oaks, CA},
  issn      = {8755-2930},
  doi       = {10.1177/8755293019899956},
  pages     = {274 -- 297},
  year      = {2020},
  abstract  = {Probabilistic assessment of seismic hazard and risk over a geographical region presents the modeler with challenges in the characterization of the site amplification that are not present in site-specific assessment. Using site-to-site residuals from a ground motion model fit to observations from the Japanese KiK-net database, correlations between measured local amplifications and mappable proxies such as topographic slope and geology are explored. These are used subsequently to develop empirical models describing amplification as a direct function of slope, conditional upon geological period. These correlations also demonstrate the limitations of inferring 30-m shearwave velocity from slope and applying them directly into ground motion models. Instead, they illustrate the feasibility of deriving spectral acceleration amplification factors directly from sets of observed records, which are calibrated to parameters that can be mapped uniformly on a regional scale. The result is a geologically calibrated amplification model that can be incorporated into national and regional seismic hazard and risk assessment, ensuring that the corresponding total aleatory variability reflects the predictive capability of the mapped site proxy.},
  language  = {en}
}
@phdthesis{GomezZapata2023,
  author    = {G{\´o}mez Zapata, Juan Camilo},
  title     = {Towards unifying approaches in exposure modelling for scenario-based multi-hazard risk assessments},
  doi       = {10.25932/publishup-58614},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-586140},
  school      = {Universit{\"a}t Potsdam},
  pages     = {iii, xiii, 155},
  year      = {2023},
  abstract  = {This cumulative thesis presents a stepwise investigation of the exposure modelling process for risk assessment due to natural hazards while highlighting its, to date, not much-discussed importance and associated uncertainties. Although "exposure" refers to a very broad concept of everything (and everyone) that is susceptible to damage, in this thesis it is narrowed down to the modelling of large-area residential building stocks. Classical building exposure models for risk applications have been constructed fully relying on unverified expert elicitation over data sources (e.g., outdated census datasets), and hence have been implicitly assumed to be static in time and in space. Moreover, their spatial representation has also typically been simplified by geographically aggregating the inferred composition onto coarse administrative units whose boundaries do not always capture the spatial variability of the hazard intensities required for accurate risk assessments. These two shortcomings and the related epistemic uncertainties embedded within exposure models are tackled in the first three chapters of the thesis. The exposure composition of large-area residential building stocks is studied on the scope of scenario-based earthquake loss models. Then, the proposal of optimal spatial aggregation areas of exposure models for various hazard-related vulnerabilities is presented, focusing on ground-shaking and tsunami risks. Subsequently, once the experience is gained in the study of the composition and spatial aggregation of exposure for various hazards, this thesis moves towards a multi-hazard context while addressing cumulative damage and losses due to consecutive hazard scenarios. This is achieved by proposing a novel method to account for the pre-existing damage descriptions on building portfolios as a key input to account for scenario-based multi-risk assessment. Finally, this thesis shows how the integration of the aforementioned elements can be used in risk communication practices. This is done through a modular architecture based on the exploration of quantitative risk scenarios that are contrasted with social risk perceptions of the directly exposed communities to natural hazards. In Chapter 1, a Bayesian approach is proposed to update the prior assumptions on such composition (i.e., proportions per building typology). This is achieved by integrating high-quality real observations and then capturing the intrinsic probabilistic nature of the exposure model. Such observations are accounted as real evidence from both: field inspections (Chapter 2) and freely available data sources to update existing (but outdated) exposure models (Chapter 3). In these two chapters, earthquake scenarios with parametrised ground motion fields were transversally used to investigate the role of such epistemic uncertainties related to the exposure composition through sensitivity analyses. Parametrised scenarios of seismic ground shaking were the hazard input utilised to study the physical vulnerability of building portfolios. The second issue that was investigated, which refers to the spatial aggregation of building exposure models, was investigated within two decoupled vulnerability contexts: due to seismic ground shaking through the integration of remote sensing techniques (Chapter 3); and within a multi-hazard context by integrating the occurrence of associated tsunamis (Chapter 4). Therein, a careful selection of the spatial aggregation entities while pursuing computational efficiency and accuracy in the risk estimates due to such independent hazard scenarios (i.e., earthquake and tsunami) are discussed. Therefore, in this thesis, the physical vulnerability of large-area building portfolios due to tsunamis is considered through two main frames: considering and disregarding the interaction at the vulnerability level, through consecutive and decoupled hazard scenarios respectively, which were then contrasted. Contrary to Chapter 4, where no cumulative damages are addressed, in Chapter 5, data and approaches, which were already generated in former sections, are integrated with a novel modular method to ultimately study the likely interactions at the vulnerability level on building portfolios. This is tested by evaluating cumulative damages and losses after earthquakes with increasing magnitude followed by their respective tsunamis. Such a novel method is grounded on the possibility of re-using existing fragility models within a probabilistic framework. The same approach is followed in Chapter 6 to forecast the likely cumulative damages to be experienced by a building stock located in a volcanic multi-hazard setting (ash-fall and lahars). In that section, special focus was made on the manner the forecasted loss metrics are communicated to locally exposed communities. Co-existing quantitative scientific approaches (i.e., comprehensive exposure models; explorative risk scenarios involving single and multiple hazards) and semi-qualitative social risk perception (i.e., level of understanding that the exposed communities have about their own risk) were jointly considered. Such an integration ultimately allowed this thesis to also contribute to enhancing preparedness, science divulgation at the local level as well as technology transfer initiatives. Finally, a synthesis of this thesis along with some perspectives for improvement and future work are presented.},
  language  = {en}
}