@phdthesis{Zeckra2020,
  author    = {Zeckra, Martin},
  title     = {Seismological and seismotectonic analysis of the northwestern Argentine Central Andean foreland},
  doi       = {10.25932/publishup-47324},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-473240},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 120},
  year      = {2020},
  abstract  = {After a severe M W 5.7 earthquake on October 17, 2015 in El Galp{\´o}n in the province of Salta NW Argentina, I installed a local seismological network around the estimated epicenter. The network covered an area characterized by inherited Cretaceous normal faults and neotectonic faults with unknown recurrence intervals, some of which may have been reactivated normal faults. The 13 three-component seismic stations recorded data continuously for 15 months. The 2015 earthquake took place in the Santa B{\´a}rbara System of the Andean foreland, at about 17km depth. This region is the easternmost morphostructural region of the central Andes. As a part of the broken foreland, it is bounded to the north by the Subandes fold-and-thrust belt and the Sierras Pampeanas to the south; to the east lies the Chaco-Paran{\´a} basin. A multi-stage morphotectonic evolution with thick-skinned basement uplift and coeval thin-skinned deformation in the intermontane basins is suggested for the study area. The release of stresses associated with the foreland deformation can result in strong earthquakes, as the study area is known for recurrent and historical, destructive earthquakes. The available continuous record reaches back in time, when the strongest event in 1692 (magnitude 7 or intensity IX) destroyed the city of Esteco. Destructive earthquakes and surface deformation are thus a hallmark of this part of the Andean foreland. With state-of-the-art Python packages (e.g. pyrocko, ObsPy), a semi-automatic approach is followed to analyze the collected continuous data of the seismological network. The resulting 1435 hypocenter locations consist of three different groups: 1.) local crustal earthquakes (nearly half of the events belong to this group), 2.) interplate activity, of regional distance in the slab of the Nazca-plate, and 3.) very deep earthquakes at about 600km depth. My major interest focused on the first event class. Those crustal events are partly aftershock events of the El Galp{\´o}n earthquake and a second earthquake, in the south of the same fault. Further events can be considered as background seismicity of other faults within the study area. Strikingly, the seismogenic zone encompass the whole crust and propagates brittle deformation down, close to the Moho. From the collected seismological data, a local seismic velocity model is estimated, using VELEST. After the execution of various stability tests, the robust minimum 1D-velocity model implies guiding values for the composition of the local, subsurface structure of the crust. Afterwards, performing a hypocenter relocation enables the assignment of individual earthquakes to aftershock clusters or extended seismotectonic structures. This allows the mapping of previously unknown seismogenic faults. Finally, focal mechanisms are modeled for events with acurately located hypocenters, using the newly derived local velocity model. A compressive regime is attested by the majority of focal mechanisms, while the strike direction of the individual seismogenic structures is in agreement with the overall north - south orientation of the Central Andes, its mountain front, and individual mountain ranges in the southern Santa-B{\´a}rbara-System.},
  language  = {en}
}
@phdthesis{Sharma2024,
  author    = {Sharma, Shubham},
  title     = {Integrated approaches to earthquake forecasting},
  doi       = {10.25932/publishup-63612},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-636125},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvi, 76},
  year      = {2024},
  abstract  = {A comprehensive study on seismic hazard and earthquake triggering is crucial for effective mitigation of earthquake risks. The destructive nature of earthquakes motivates researchers to work on forecasting despite the apparent randomness of the earthquake occurrences. Understanding their underlying mechanisms and patterns is vital, given their potential for widespread devastation and loss of life. This thesis combines methodologies, including Coulomb stress calculations and aftershock analysis, to shed light on earthquake complexities, ultimately enhancing seismic hazard assessment. The Coulomb failure stress (CFS) criterion is widely used to predict the spatial distributions of aftershocks following large earthquakes. However, uncertainties associated with CFS calculations arise from non-unique slip inversions and unknown fault networks, particularly due to the choice of the assumed aftershocks (receiver) mechanisms. Recent studies have proposed alternative stress quantities and deep neural network approaches as superior to CFS with predefined receiver mechanisms. To challenge these propositions, I utilized 289 slip inversions from the SRCMOD database to calculate more realistic CFS values for a layered-half space and variable receiver mechanisms. The analysis also investigates the impact of magnitude cutoff, grid size variation, and aftershock duration on the ranking of stress metrics using receiver operating characteristic (ROC) analysis. Results reveal the performance of stress metrics significantly improves after accounting for receiver variability and for larger aftershocks and shorter time periods, without altering the relative ranking of the different stress metrics. To corroborate Coulomb stress calculations with the findings of earthquake source studies in more detail, I studied the source properties of the 2005 Kashmir earthquake and its aftershocks, aiming to unravel the seismotectonics of the NW Himalayan syntaxis. I simultaneously relocated the mainshock and its largest aftershocks using phase data, followed by a comprehensive analysis of Coulomb stress changes on the aftershock planes. By computing the Coulomb failure stress changes on the aftershock faults, I found that all large aftershocks lie in regions of positive stress change, indicating triggering by either co-seismic or post-seismic slip on the mainshock fault. Finally, I investigated the relationship between mainshock-induced stress changes and associated seismicity parameters, in particular those of the frequency-magnitude (Gutenberg-Richter) distribution and the temporal aftershock decay (Omori-Utsu law). For that purpose, I used my global data set of 127 mainshock-aftershock sequences with the calculated Coulomb Stress (ΔCFS) and the alternative receiver-independent stress metrics in the vicinity of the mainshocks and analyzed the aftershocks properties depend on the stress values. Surprisingly, the results show a clear positive correlation between the Gutenberg-Richter b-value and induced stress, contrary to expectations from laboratory experiments. This observation highlights the significance of structural heterogeneity and strength variations in seismicity patterns. Furthermore, the study demonstrates that aftershock productivity increases nonlinearly with stress, while the Omori-Utsu parameters c and p systematically decrease with increasing stress changes. These partly unexpected findings have significant implications for future estimations of aftershock hazard. The findings in this thesis provides valuable insights into earthquake triggering mechanisms by examining the relationship between stress changes and aftershock occurrence. The results contribute to improved understanding of earthquake behavior and can aid in the development of more accurate probabilistic-seismic hazard forecasts and risk reduction strategies.},
  language  = {en}
}
@phdthesis{Sen2014,
  author    = {Sen, Ali Tolga},
  title     = {Inversion of seismic source parameters for weak mining-induced and natural earthquakes},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-71914},
  school      = {Universit{\"a}t Potsdam},
  year      = {2014},
  abstract  = {The purpose of this thesis is to develop an automated inversion scheme to derive point and finite source parameters for weak earthquakes, here intended with the unusual meaning of earthquakes with magnitudes at the limit or below the bottom magnitude threshold of standard source inversion routines. The adopted inversion approaches entirely rely on existing inversion software, the methodological work mostly targeting the development and tuning of optimized inversion flows. The resulting inversion scheme is tested for very different datasets, and thus allows the discussion on the source inversion problem at different scales. In the first application, dealing with mining induced seismicity, the source parameters determination is addressed at a local scale, with source-sensor distance of less than 3 km. In this context, weak seismicity corresponds to event below magnitude MW 2.0, which are rarely target of automated source inversion routines. The second application considers a regional dataset, namely the aftershock sequence of the 2010 Maule earthquake (Chile), using broadband stations at regional distances, below 300 km. In this case, the magnitude range of the target aftershocks range down to MW 4.0. This dataset is here considered as a weak seismicity case, since the analysis of such moderate seismicity is generally investigated only by moment tensor inversion routines, with no attempt to resolve source duration or finite source parameters. In this work, automated multi-step inversion schemes are applied to both datasets with the aim of resolving point source parameters, both using double couple (DC) and full moment tensor (MT) models, source duration and finite source parameters. A major result of the analysis of weaker events is the increased size of resulting moment tensor catalogues, which interpretation may become not trivial. For this reason, a novel focal mechanism clustering approach is used to automatically classify focal mechanisms, allowing the investigation of the most relevant and repetitive rupture features. The inversion of the mining induced seismicity dataset reveals the repetitive occurrence of similar rupture processes, where the source geometry is controlled by the shape of the mined panel. Moreover, moment tensor solutions indicate a significant contribution of tensile processes. Also the second application highlights some characteristic geometrical features of the fault planes, which show a general consistency with the orientation of the slab. The additional inversion for source duration allowed to verify the empirical correlation for moment normalized earthquakes in subduction zones among a decreasing rupture duration with increasing source depth, which was so far only observed for larger events.},
  language  = {en}
}
@phdthesis{Roessler2006,
  author    = {R{\"o}ßler, Dirk},
  title     = {Retrieval of earthquake source parameters in inhomogeneous anisotropic mediawith application to swarm events in West Bohemia in 2000},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7758},
  school      = {Universit{\"a}t Potsdam},
  year      = {2006},
  abstract  = {Earthquakes form by sudden brittle failure of rock mostly as shear ruptures along a rupture plane. Beside this, mechanisms other than pure shearing have been observed for some earthquakes mainly in volcanic areas. Possible explanations include complex rupture geometries and tensile earthquakes. Tensile earthquakes occur by opening or closure of cracks during rupturing. They are likely to be often connected with fluids that cause pressure changes in the pore space of rocks leading to earthquake triggering. Tensile components have been reported for swarm earthquakes in West Bohemia in 2000. The aim and subject of this work is an assessment and the accurate determination of such tensile components for earthquakes in anisotropic media. Currently used standard techniques for the retrieval of earthquake source mechanisms assume isotropic rock properties. By means of moment tensors, equivalent forces acting at the source are used to explain the radiated wavefield. Conversely, seismic anisotropy, i.e. directional dependence of elastic properties, has been observed in the earth's crust and mantle such as in West Bohemia. In comparison to isotropy, anisotropy causes modifications in wave amplitudes and shear-wave splitting. In this work, effects of seismic anisotropy on true or apparent tensile source components of earthquakes are investigated. In addition, earthquake source parameters are determined considering anisotropy. It is shown that moment tensors and radiation patterns due to shear sources in anisotropic media may be similar to those of tensile sources in isotropic media. In contrast, similarities between tensile earthquakes in anisotropic rocks and shear sources in isotropic media may exist. As a consequence, the interpretation of tensile source components is ambiguous. The effects that are due to anisotropy depend on the orientation of the earthquake source and the degree of anisotropy. The moment of an earthquake is also influenced by anisotropy. The orientation of fault planes can be reliably determined even if isotropy instead of anisotropy is assumed and if the spectra of the compressional waves are used. Greater difficulties may arise when the spectra of split shear waves are additionally included. Retrieved moment tensors show systematic artefacts. Observed tensile source components determined for events in West Bohemia in 1997 can only partly be attributed to the effects of moderate anisotropy. Furthermore, moment tensors determined earlier for earthquakes induced at the German Continental Deep Drilling Program (KTB), Bavaria, were reinterpreted under assumptions of anisotropic rock properties near the borehole. The events can be consistently identified as shear sources, although their moment tensors comprise tensile components that are considered to be apparent. These results emphasise the necessity to consider anisotropy to uniquely determine tensile source parameters. Therefore, a new inversion algorithm has been developed, tested, and successfully applied to 112 earthquakes that occurred during the most recent intense swarm episode in West Bohemia in 2000 at the German-Czech border. Their source mechanisms have been retrieved using isotropic and anisotropic velocity models. Determined local magnitudes are in the range between 1.6 and 3.2. Fault-plane solutions are similar to each other and characterised by left-lateral faulting on steeply dipping, roughly North-South oriented rupture planes. Their dip angles decrease above a depth of about 8.4km. Tensile source components indicating positive volume changes are found for more than 60\% of the considered earthquakes. Their size depends on source time and location. They are significant at the beginning of the swarm and at depths below 8.4km but they decrease in importance later in the course of the swarm. Determined principle stress axes include P axes striking Northeast and Taxes striking Southeast. They resemble those found earlier in Central Europe. However, depth-dependence in plunge is observed. Plunge angles of the P axes decrease gradually from 50° towards shallow angles with increasing depth. In contrast, the plunge angles of the T axes change rapidly from about 8° above a depth of 8.4km to 21° below this depth. By this thesis, spatial and temporal variations in tensile source components and stress conditions have been reported for the first time for swarm earthquakes in West Bohemia in 2000. They also persist, when anisotropy is assumed and can be explained by intrusion of fluids into the opened cracks during tensile faulting.},
  subject      = {Seismologie},
  language  = {en}
}
@phdthesis{Metz2023,
  author    = {Metz, Malte},
  title     = {Finite fault earthquake source inversions},
  doi       = {10.25932/publishup-61974},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-619745},
  school      = {Universit{\"a}t Potsdam},
  pages     = {143},
  year      = {2023},
  abstract  = {Earthquake modeling is the key to a profound understanding of a rupture. Its kinematics or dynamics are derived from advanced rupture models that allow, for example, to reconstruct the direction and velocity of the rupture front or the evolving slip distribution behind the rupture front. Such models are often parameterized by a lattice of interacting sub-faults with many degrees of freedom, where, for example, the time history of the slip and rake on each sub-fault are inverted. To avoid overfitting or other numerical instabilities during a finite-fault estimation, most models are stabilized by geometric rather than physical constraints such as smoothing. As a basis for the inversion approach of this study, we build on a new pseudo-dynamic rupture model (PDR) with only a few free parameters and a simple geometry as a physics-based solution of an earthquake rupture. The PDR derives the instantaneous slip from a given stress drop on the fault plane, with boundary conditions on the developing crack surface guaranteed at all times via a boundary element approach. As a side product, the source time function on each point on the rupture plane is not constraint and develops by itself without additional parametrization. The code was made publicly available as part of the Pyrocko and Grond Python packages. The approach was compared with conventional modeling for different earthquakes. For example, for the Mw 7.1 2016 Kumamoto, Japan, earthquake, the effects of geometric changes in the rupture surface on the slip and slip rate distributions could be reproduced by simply projecting stress vectors. For the Mw 7.5 2018 Palu, Indonesia, strike-slip earthquake, we also modelled rupture propagation using the 2D Eikonal equation and assuming a linear relationship between rupture and shear wave velocity. This allowed us to give a deeper and faster propagating rupture front and the resulting upward refraction as a new possible explanation for the apparent supershear observed at the Earth's surface. The thesis investigates three aspects of earthquake inversion using PDR: (1) to test whether implementing a simplified rupture model with few parameters into a probabilistic Bayesian scheme without constraining geometric parameters is feasible, and whether this leads to fast and robust results that can be used for subsequent fast information systems (e.g., ground motion predictions). (2) To investigate whether combining broadband and strong-motion seismic records together with near-field ground deformation data improves the reliability of estimated rupture models in a Bayesian inversion. (3) To investigate whether a complex rupture can be represented by the inversion of multiple PDR sources and for what type of earthquakes this is recommended. I developed the PDR inversion approach and applied the joint data inversions to two seismic sequences in different tectonic settings. Using multiple frequency bands and a multiple source inversion approach, I captured the multi-modal behaviour of the Mw 8.2 2021 South Sandwich subduction earthquake with a large, curved and slow rupturing shallow earthquake bounded by two faster and deeper smaller events. I could cross-validate the results with other methods, i.e., P-wave energy back-projection, a clustering analysis of aftershocks and a simple tsunami forward model. The joint analysis of ground deformation and seismic data within a multiple source inversion also shed light on an earthquake triplet, which occurred in July 2022 in SE Iran. From the inversion and aftershock relocalization, I found indications for a vertical separation between the shallower mainshocks within the sedimentary cover and deeper aftershocks at the sediment-basement interface. The vertical offset could be caused by the ductile response of the evident salt layer to stress perturbations from the mainshocks. The applications highlight the versatility of the simple PDR in probabilistic seismic source inversion capturing features of rather different, complex earthquakes. Limitations, as the evident focus on the major slip patches of the rupture are discussed as well as differences to other finite fault modeling methods.},
  language  = {en}
}
@phdthesis{Lilienkamp2024,
  author    = {Lilienkamp, Henning},
  title     = {Enhanced computational approaches for data-driven characterization of earthquake ground motion and rapid earthquake impact assessment},
  doi       = {10.25932/publishup-63195},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-631954},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 145},
  year      = {2024},
  abstract  = {Rapidly growing seismic and macroseismic databases and simplified access to advanced machine learning methods have in recent years opened up vast opportunities to address challenges in engineering and strong motion seismology from novel, datacentric perspectives. In this thesis, I explore the opportunities of such perspectives for the tasks of ground motion modeling and rapid earthquake impact assessment, tasks with major implications for long-term earthquake disaster mitigation. In my first study, I utilize the rich strong motion database from the Kanto basin, Japan, and apply the U-Net artificial neural network architecture to develop a deep learning based ground motion model. The operational prototype provides statistical estimates of expected ground shaking, given descriptions of a specific earthquake source, wave propagation paths, and geophysical site conditions. The U-Net interprets ground motion data in its spatial context, potentially taking into account, for example, the geological properties in the vicinity of observation sites. Predictions of ground motion intensity are thereby calibrated to individual observation sites and earthquake locations. The second study addresses the explicit incorporation of rupture forward directivity into ground motion modeling. Incorporation of this phenomenon, causing strong, pulse like ground shaking in the vicinity of earthquake sources, is usually associated with an intolerable increase in computational demand during probabilistic seismic hazard analysis (PSHA) calculations. I suggest an approach in which I utilize an artificial neural network to efficiently approximate the average, directivity-related adjustment to ground motion predictions for earthquake ruptures from the 2022 New Zealand National Seismic Hazard Model. The practical implementation in an actual PSHA calculation demonstrates the efficiency and operational readiness of my model. In a follow-up study, I present a proof of concept for an alternative strategy in which I target the generalizing applicability to ruptures other than those from the New Zealand National Seismic Hazard Model. In the third study, I address the usability of pseudo-intensity reports obtained from macroseismic observations by non-expert citizens for rapid impact assessment. I demonstrate that the statistical properties of pseudo-intensity collections describing the intensity of shaking are correlated with the societal impact of earthquakes. In a second step, I develop a probabilistic model that, within minutes of an event, quantifies the probability of an earthquake to cause considerable societal impact. Under certain conditions, such a quick and preliminary method might be useful to support decision makers in their efforts to organize auxiliary measures for earthquake disaster response while results from more elaborate impact assessment frameworks are not yet available. The application of machine learning methods to datasets that only partially reveal characteristics of Big Data, qualify the majority of results obtained in this thesis as explorative insights rather than ready-to-use solutions to real world problems. The practical usefulness of this work will be better assessed in the future by applying the approaches developed to growing and increasingly complex data sets.},
  language  = {en}
}
@phdthesis{Koehler2009,
  author    = {K{\"o}hler, Andreas},
  title     = {Recognition and investigation of temporal patterns in seismic wavefields using unsupervised learning techniques},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-29702},
  school      = {Universit{\"a}t Potsdam},
  year      = {2009},
  abstract  = {Modern acquisition of seismic data on receiver networks worldwide produces an increasing amount of continuous wavefield recordings. Hence, in addition to manual data inspection, seismogram interpretation requires new processing utilities for event detection, signal classification and data visualization. Various machine learning algorithms, which can be adapted to seismological problems, have been suggested in the field of pattern recognition. This can be done either by means of supervised learning using manually defined training data or by unsupervised clustering and visualization. The latter allows the recognition of wavefield patterns, such as short-term transients and long-term variations, with a minimum of domain knowledge. Besides classical earthquake seismology, investigations of temporal patterns in seismic data also concern novel approaches such as noise cross-correlation or ambient seismic vibration analysis in general, which have moved into focus within the last decade. In order to find records suitable for the respective approach or simply for quality control, unsupervised preprocessing becomes important and valuable for large data sets. Machine learning techniques require the parametrization of the data using feature vectors. Applied to seismic recordings, wavefield properties have to be computed from the raw seismograms. For an unsupervised approach, all potential wavefield features have to be considered to reduce subjectivity to a minimum. Furthermore, automatic dimensionality reduction, i.e. feature selection, is required in order to decrease computational cost, enhance interpretability and improve discriminative power. This study presents an unsupervised feature selection and learning approach for the discovery, imaging and interpretation of significant temporal patterns in seismic single-station or network recordings. In particular, techniques permitting an intuitive, quickly interpretable and concise overview of available records are suggested. For this purpose, the data is parametrized by real-valued feature vectors for short time windows using standard seismic analysis tools as feature generation methods, such as frequency-wavenumber, polarization, and spectral analysis. The choice of the time window length is dependent on the expected durations of patterns to be recognized or discriminated. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure, which is particularly suitable for high-dimensional data sets. Using synthetics composed of Rayleigh and Love waves and three different types of real-world data sets, we show the robustness and reliability of our unsupervised learning approach with respect to the effect of algorithm parameters and data set properties. Furthermore, we approve the capability of the clustering and imaging techniques. For all data, we find improved discriminative power of our feature selection procedure compared to feature subsets manually selected from individual wavefield parametrization methods. In particular, enhanced performance is observed compared to the most favorable individual feature generation method, which is found to be the frequency spectrum. The method is applied to regional earthquake records at the European Broadband Network with the aim to define suitable features for earthquake detection and seismic phase classification. For the latter, we find that a combination of spectral and polarization features favor S wave detection at a single receiver. However, SOM-based visualization of phase discrimination shows that clustering applied to the records of two stations only allows onset or P wave detection, respectively. In order to improve the discrimination of S waves on receiver networks, we recommend to consider additionally the temporal context of feature vectors. The application to continuous recordings of seismicity close to an active volcano (Mount Merapi, Java, Indonesia) shows that two typical volcano-seismic events (VTB and Guguran) can be detected and distinguished by clustering. In contrast, so-called MP events cannot be discriminated. Comparable results are obtained for selected features and recognition rates regarding a previously implemented supervised classification system. Finally, we test the reliability of wavefield clustering to improve common ambient vibration analysis methods such as estimation of dispersion curves and horizontal to vertical spectral ratios. It is found, that in general, the identified short- and long-term patterns have no significant impact on those estimates. However, for individual sites, effects of local sources can be identified. Leaving out the corresponding clusters, yields reduced uncertainties or allows for improving estimation of dispersion curves.},
  language  = {en}
}
@phdthesis{Kulikova2015,
  author    = {Kulikova, Galina},
  title     = {Source parameters of the major historical earthquakes in the Tien-Shan region from the late 19th to the early 20th century},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-88370},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 164},
  year      = {2015},
  abstract  = {The Tien-Shan and the neighboring Pamir region are two of the largest mountain belts in the world. Their deformation is dominated by intermontane basins bounded by active thrust and reverse faulting. The Tien-Shan mountain belt is characterized by a very high rate of seismicity along its margins as well as within the Tien-Shan interior. The study area of the here presented thesis, the western part of the Tien-Shan region, is currently seismically active with small and moderate sized earthquakes. However, at the end of the 19th beginning of the 20th century, this region was struck by a remarkable series of large magnitude (M>7) earthquakes, two of them reached magnitude 8. Those large earthquakes occurred prior to the installation of the global digital seismic network and therefore were recorded only by analog seismic instruments. The processing of the analog data brings several difficulties, for example, not always the true parameters of the recording system are known. Another complicated task is the digitization of those records - a very time-consuming and delicate part. Therefore a special set of techniques is developed and modern methods are adapted for the digitized instrumental data analysis. The main goal of the presented thesis is to evaluate the impact of large magnitude M≥7.0 earthquakes, which occurred at the turn of 19th to 20th century in the Tien-Shan region, on the overall regional tectonics. A further objective is to investigate the accuracy of previously estimated source parameters for those earthquakes, which were mainly based on macroseismic observations, and re-estimate them based on the instrumental data. An additional aim of this study is to develop the tools and methods for faster and more productive usage of analog seismic data in modern seismology. In this thesis, the ten strongest and most interesting historical earthquakes in Tien-Shan region are analyzed. The methods and tool for digitizing and processing the analog seismic data are presented. The source parameters of the two major M≥8.0 earthquakes in the Northern Tien-Shan are re-estimated in individual case studies. Those studies are published as peer-reviewed scientific articles in reputed journals. Additionally, the Sarez-Pamir earthquake and its connection with one of the largest landslides in the world, Usoy landslide, is investigated by seismic modeling. These results are also published as a research paper. With the developed techniques, the source parameters of seven more major earthquakes in the region are determined and their impact on the regional tectonics was investigated. The large magnitudes of those earthquakes are confirmed by instrumental data. The focal mechanism of these earthquakes were determined providing evidence for responsible faults or fault systems.},
  language  = {en}
}
@phdthesis{Illien2023,
  author    = {Illien, Luc},
  title     = {Time-dependent properties of the shallow subsurface},
  doi       = {10.25932/publishup-59936},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-599367},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xviii, 133},
  year      = {2023},
  abstract  = {The shallow Earth's layers are at the interplay of many physical processes: some being driven by atmospheric forcing (precipitation, temperature...) whereas others take their origins at depth, for instance ground shaking due to seismic activity. These forcings cause the subsurface to continuously change its mechanical properties, therefore modulating the strength of the surface geomaterials and hydrological fluxes. Because our societies settle and rely on the layers hosting these time-dependent properties, constraining the hydro-mechanical dynamics of the shallow subsurface is crucial for our future geographical development. One way to investigate the ever-changing physical changes occurring under our feet is through the inference of seismic velocity changes from ambient noise, a technique called seismic interferometry. In this dissertation, I use this method to monitor the evolution of groundwater storage and damage induced by earthquakes. Two research lines are investigated that comprise the key controls of groundwater recharge in steep landscapes and the predictability and duration of the transient physical properties due to earthquake ground shaking. These two types of dynamics modulate each other and influence the velocity changes in ways that are challenging to disentangle. A part of my doctoral research also addresses this interaction. Seismic data from a range of field settings spanning several climatic conditions (wet to arid climate) in various seismic-prone areas are considered. I constrain the obtained seismic velocity time-series using simple physical models, independent dataset, geophysical tools and nonlinear analysis. Additionally, a methodological development is proposed to improve the time-resolution of passive seismic monitoring.},
  language  = {en}
}