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The role of biogenic carbonate producers in the evolution of the geometries of carbonate systems has been the subject of numerous research projects. Attempts to classify modern and ancient carbonate systems by their biotic components have led to the discrimination of biogenic carbonate producers broadly into Photozoans, which are characterised by an affinity for warm tropical waters and high dependence on light penetration, and Heterozoans which are generally associated with both cool water environments and nutrient-rich settings with little to no light penetration. These broad categories of carbonate sediment producers have also been recognised to dominate in specific carbonate systems. Photozoans are commonly dominant in flat-topped platforms with steep margins, while Heterozoans generally dominate carbonate ramps. However, comparatively little is known on how these two main groups of carbonate producers interact in the same system and impact depositional geometries responding to changes in environmental conditions such as sea level fluctuation, antecedent slope, sediment transport processes, etc. This thesis presents numerical models to investigate the evolution of Miocene carbonate systems in the Mediterranean from two shallow marine domains: 1) a Miocene flat-topped platform dominated by Photozoans, with a significant component of Hetrozoans in the slope and 2) a Heterozoan distally steepened ramp, with seagrass-influenced (Photozoan) inner ramp. The overarching aim of the three articles comprising this cumulative thesis is to provide a numerical study of the role of Photozoans and Heterozoans in the evolution of carbonate system geometries and how these biotas respond to changes in environmental conditions. This aim was achieved using stratigraphic forward modelling, which provides an approach to quantitatively integrate multi-scale datasets to reconstruct sedimentary processes and products during the evolution of a sedimentary system.
In a Photozoan-dominated carbonate system, such as the Miocene Llucmajor platform in Western Mediterranean, stratigraphic forward modelling dovetailed with a robust set of sensitivity tests reveal how the geometry of the carbonate system is determined by the complex interaction of Heterozoan and Photozoan biotas in response to variable conditions of sea level fluctuation, substrate configuration, sediment transport processes and the dominance of Photozoan over Heterozoan production. This study provides an enhanced understanding of the different carbonate systems that are possible under different ecological and hydrodynamic conditions. The research also gives insight into the roles of different biotic associations in the evolution of carbonate geometries through time and space. The results further show that the main driver of platform progradation in a Llucmajor-type system is the lowstand production of Heterozoan sediments, which form the necessary substratum for Photozoan production.
In Heterozoan systems, sediment production is mainly characterised by high transport deposits, that are prone to redistribution by waves and gravity, thereby precluding the development of steep margins. However, in the Menorca ramp, the occurrence of sediment trapping by seagrass led to the evolution of distal slope steepening. We investigated, through numerical modelling, how such a seagrass-influenced ramp responds to the frequency and amplitude of sea level changes, variable carbonate production between the euphotic and oligophotic zone, and changes in the configuration of the paleoslope. The study reinforces some previous hypotheses and presents alternative scenarios to the established concepts of high-transport ramp evolution. The results of sensitivity experiments show that steep slopes are favoured in ramps that develop in high-frequency sea level fluctuation with amplitudes between 20 m and 40 m. We also show that ramp profiles are significantly impacted by the paleoslope inclination, such that an optimal antecedent slope of about 0.15 degrees is required for the Menorca distally steepened ramp to develop.
The third part presents an experimental case to argue for the existence of a Photozoan sediment threshold required for the development of steep margins in carbonate platforms. This was carried out by developing sensitivity tests on the forward models of the flat-topped (Llucmajor) platform and the distally steepened (Menorca) platform. The results show that models with Photozoan sediment proportion below a threshold of about 40% are incapable of forming steep slopes. The study also demonstrates that though it is possible to develop steep margins by seagrass sediment trapping, such slopes can only be stabilized by the appropriate sediment fabric and/or microbial binding. In the Photozoan-dominated system, the magnitude of slope steepness depends on the proportion of Photozoan sediments in the system. Therefore, this study presents a novel tool for characterizing carbonate systems based on their biogenic components.
Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process – rather than actual changes in the dynamical properties of the system – is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.
Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process – rather than actual changes in the dynamical properties of the system – is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.
The East African Rift System (EARS) is a significant example of active tectonics, which provides opportunities to examine the stages of continental faulting and landscape evolution. The southwest extension of the EARS is one of the most significant examples of active tectonics nowadays, however, seismotectonic research in the area has been scarce, despite the fundamental importance of neotectonics. Our first study area is located between the Northern Province of Zambia and the southeastern Katanga Province of the Democratic Republic of Congo. Lakes Mweru and Mweru Wantipa are part of the southwest extension of the EARS. Fault analysis reveals that, since the Miocene, movements along the active Mweru-Mweru Wantipa Fault System (MMFS) have been largely responsible for the reorganization of the landscape and the drainage patterns across the southwestern branch of the EARS. To investigate the spatial and temporal patterns of fluvial-lacustrine landscape development, we determined in-situ cosmogenic 10Be and 26Al in a total of twenty-six quartzitic bedrock samples that were collected from knickpoints across the Mporokoso Plateau (south of Lake Mweru) and the eastern part of the Kundelungu Plateau (north of Lake Mweru). Samples from the Mporokoso Plateau and close to the MMFS provide evidence of temporary burial. By contrast, surfaces located far from the MMFS appear to have remained uncovered since their initial exposure as they show consistent 10Be and 26Al exposure ages ranging up to ~830 ka. Reconciliation of the observed burial patterns with morphotectonic and stratigraphic analysis reveals the existence of an extensive paleo-lake during the Pleistocene. Through hypsometric analyses of the dated knickpoints, the potential maximum water level of the paleo-lake is constrained to ~1200 m asl (present lake lavel: 917 m asl). High denudation rates (up to ~40 mm ka-1) along the eastern Kundelungu Plateau suggest that footwall uplift, resulting from normal faulting, caused river incision, possibly controlling paleo-lake drainage. The lake level was reduced gradually reaching its current level at ~350 ka.
Parallel to the MMFS in the north, the Upemba Fault System (UFS) extends across the southeastern Katanga Province of the Democratic Republic of Congo. This part of our research is focused on the geomorphological behavior of the Kiubo Waterfalls. The waterfalls are the currently active knickpoint of the Lufira River, which flows into the Upemba Depression. Eleven bedrock samples along the Lufira River and its tributary stream, Luvilombo River, were collected. In-situ cosmogenic 10Be and 26Al were used in order to constrain the K constant of the Stream Power Law equation. Constraining the K constant allowed us to calculate the knickpoint retreat rate of the Kiubo Waterfalls at ~0.096 m a-1. Combining the calculated retreat rate of the knickpoint with DNA sequencing from fish populations, we managed to present extrapolation models and estimate the location of the onset of the Kiubo Waterfalls, revealing its connection to the seismicity of the UFS.
Advances in hydrogravimetry
(2023)
The interest of the hydrological community in the gravimetric method has steadily increased within the last decade. This is reflected by numerous studies from many different groups with a broad range of approaches and foci. Many of those are traditionally rather hydrology-oriented groups who recognized gravimetry as a potential added value for their hydrological investigations. While this resulted in a variety of interesting and useful findings, contributing to extend the respective knowledge and confirming the methodological potential, on the other hand, many interesting and unresolved questions emerged.
This thesis manifests efforts, analyses and solutions carried out in this regard. Addressing and evaluating many of those unresolved questions, the research contributes to advancing hydrogravimetry, the combination of gravimetric and hydrological methods, in showing how gravimeters are a highly useful tool for applied hydrological field research.
In the first part of the thesis, traditional setups of stationary terrestrial superconducting gravimeters are addressed. They are commonly installed within a dedicated building, the impermeable structure of which shields the underlying soil from natural exchange of water masses (infiltration, evapotranspiration, groundwater recharge). As gravimeters are most sensitive to mass changes directly beneath the meter, this could impede their suitability for local hydrological process investigations, especially for near-surface water storage changes (WSC). By studying temporal local hydrological dynamics at a dedicated site equipped with traditional hydrological measurement devices, both below and next to the building, the impact of these absent natural dynamics on the gravity observations were quantified. A comprehensive analysis with both a data-based and model-based approach led to the development of an alternative method for dealing with this limitation. Based on determinable parameters, this approach can be transferred to a broad range of measurement sites where gravimeters are deployed in similar structures. Furthermore, the extensive considerations on this topic enabled a more profound understanding of this so called umbrella effect.
The second part of the thesis is a pilot study about the field deployment of a superconducting gravimeter. A newly developed field enclosure for this gravimeter was tested in an outdoor installation adjacent to the building used to investigate the umbrella effect. Analyzing and comparing the gravity observations from both indoor and outdoor gravimeters showed performance with respect to noise and stable environmental conditions was equivalent while the sensitivity to near-surface WSC was highly increased for the field deployed instrument. Furthermore it was demonstrated that the latter setup showed gravity changes independent of the depth where mass changes occurred, given their sufficiently wide horizontal extent. As a consequence, the field setup suits monitoring of WSC for both short and longer time periods much better. Based on a coupled data-modeling approach, its gravity time series was successfully used to infer and quantify local water budget components (evapotranspiration, lateral subsurface discharge) on the daily to annual time scale.
The third part of the thesis applies data from a gravimeter field deployment for applied hydrological process investigations. To this end, again at the same site, a sprinkling experiment was conducted in a 15 x 15 m area around the gravimeter. A simple hydro-gravimetric model was developed for calculating the gravity response resulting from water redistribution in the subsurface. It was found that, from a theoretical point of view, different subsurface water distribution processes (macro pore flow, preferential flow, wetting front advancement, bypass flow and perched water table rise) lead to a characteristic shape of their resulting gravity response curve. Although by using this approach it was possible to identify a dominating subsurface water distribution process for this site, some clear limitations stood out. Despite the advantage for field installations that gravimetry is a non-invasive and integral method, the problem of non-uniqueness could only be overcome by additional measurements (soil moisture, electric resistivity tomography) within a joint evaluation. Furthermore, the simple hydrological model was efficient for theoretical considerations but lacked the capability to resolve some heterogeneous spatial structures of water distribution up to a needed scale. Nevertheless, this unique setup for plot to small scale hydrological process research underlines the high potential of gravimetery and the benefit of a field deployment.
The fourth and last part is dedicated to the evaluation of potential uncertainties arising from the processing of gravity observations. The gravimeter senses all mass variations in an integral way, with the gravitational attraction being directly proportional to the magnitude of the change and inversely proportional to the square of the distance of the change. Consequently, all gravity effects (for example, tides, atmosphere, non-tidal ocean loading, polar motion, global hydrology and local hydrology) are included in an aggregated manner. To isolate the signal components of interest for a particular investigation, all non-desired effects have to be removed from the observations. This process is called reduction. The large-scale effects (tides, atmosphere, non-tidal ocean loading and global hydrology) cannot be measured directly and global model data is used to describe and quantify each effect. Within the reduction process, model errors and uncertainties propagate into the residual, the result of the reduction. The focus of this part of the thesis is quantifying the resulting, propagated uncertainty for each individual correction. Different superconducting gravimeter installations were evaluated with respect to their topography, distance to the ocean and the climate regime. Furthermore, different time periods of aggregated gravity observation data were assessed, ranging from 1 hour up to 12 months. It was found that uncertainties were highest for a frequency of 6 months and smallest for hourly frequencies. Distance to the ocean influences the uncertainty of the non-tidal ocean loading component, while geographical latitude affects uncertainties of the global hydrological component. It is important to highlight that the resulting correction-induced uncertainties in the residual have the potential to mask the signal of interest, depending on the signal magnitude and its frequency. These findings can be used to assess the value of gravity data across a range of applications and geographic settings.
In an overarching synthesis all results and findings are discussed with a general focus on their added value for bringing hydrogravimetric field research to a new level. The conceptual and applied methodological benefits for hydrological studies are highlighted. Within an outlook for future setups and study designs, it was once again shown what enormous potential is offered by gravimeters as hydrological field tools.
Carbonates carried in subducting slabs may play a major role in sourcing and storing carbon in the deep Earth’s interior. Current estimates indicate that between 40 to 66 million tons of carbon per year enter subduction zones, but it is uncertain how much of it reaches the lower mantle. It appears that most of this carbon might be extracted from subducting slabs at the mantle wedge and only a limited amount continues deeper and eventually reaches the deep mantle. However, estimations on deeply subducted carbon broadly range from 0.0001 to 52 million tons of carbon per year. This disparity is primarily due to the limited understanding of the survival of carbonate minerals during their transport to deep mantle conditions. Indeed, carbon has very low solubility in mantle silicates, therefore it is expected to be stored primarily in accessory phases such as carbonates. Among those carbonates, magnesite (MgCO3), as a single phase, is the most stable under all mantle conditions. However, experimental investigation on the stability of magnesite in contact with SiO2 at lower mantle conditions suggests that magnesite is stable only along a cold subducted slab geotherm. Furthermore, our understanding of magnesite’s stability when interacting with more complex mantle silicate phases remains incomplete. In the first part of this dissertation, laser-heated diamond anvil cells and multi-anvil apparatus experiments were performed to investigate the stability of magnesite in contact with iron-bearing mantle silicates. Sub-solidus reactions, melting, decarbonation and diamond formation were examined from shallow to mid-lower mantle conditions (25 to 68 GPa; 1300 to 2000 K). Multi-anvil experiments at 25 GPa show the formation of carbonate-rich melt, bridgmanite, and stishovite with melting occurring at a temperature corresponding to all geotherms except the coldest one. In situ X-ray diffraction, in laser-heating diamond anvil cells experiments, shows crystallization of bridgmanite and stishovite but no melt phase was detected in situ at high temperatures. To detect decarbonation phases such as diamond, Raman spectroscopy was used. Crystallization of diamonds is observed as a sub-solidus process even at temperatures relevant and lower than the coldest slab geotherm (1350 K at 33 GPa). Data obtained from this work suggest that magnesite is unstable in contact with the surrounding peridotite mantle in the upper-most lower mantle. The presence of magnesite instead induces melting under oxidized conditions and/or foster diamond formation under more reduced conditions, at depths ∼700 km. Consequently, carbonates will be removed from the carbonate-rich slabs at shallow lower mantle conditions, where subducted slabs can stagnate. Therefore, the transport of carbonate to deeper depths will be restricted, supporting the presence of a barrier for carbon subduction at the top of the lower mantle. Moreover, the reduction of magnesite, forming diamonds provides additional evidence that super-deep diamond crystallization is related to the reduction of carbonates or carbonated-rich melt.
The second part of this dissertation presents the development of a portable laser-heating system optimized for X-ray emission spectroscopy (XES) or nuclear inelastic scattering (NIS) spectroscopy with signal collection at near 90◦. The laser-heated diamond anvil cell is the only static pressure device that can replicate the pressure and temperatures of the Earth’s lower mantle and core. The high temperatures are reached by using high-powered lasers focused on the sample contained between the diamond anvils. Moreover, diamonds’ transparency to X-rays enables in situ X-ray spectroscopy measurements that can probe the sample under high-temperature and high-pressure conditions. Therefore, the development of portable laser-heating systems has linked high-pressure and temperature research with high-resolution X-ray spectroscopy techniques to synchrotron beamlines that do not have a dedicated, permanent, laser-heating system. A general description of the system is provided, as well as details on the use of a parabolic mirror as a reflective imaging objective for on-axis laser heating and radiospectrometric temperature measurements with zero attenuation of incoming X-rays. The parabolic mirror improves the accuracy of temperature measurements free from chromatic aberrations in a wide spectral range and its perforation permits in situ X-rays measurement at synchrotron facilities. The parabolic mirror is a well-suited alternative to refractive objectives in laser heating systems, which will facilitate future applications in the use of CO2 lasers.
Natural gas hydrates are ice-like crystalline compounds containing water cavities that trap natural gas molecules like methane (CH4), which is a potent greenhouse gas with high energy density. The Mallik site at the Mackenzie Delta in the Canadian Arctic contains a large volume of technically recoverable CH4 hydrate beneath the base of the permafrost. Understanding how the sub-permafrost hydrate is distributed can aid in searching for the ideal locations for deploying CH4 production wells to develop the hydrate as a cleaner alternative to crude oil or coal. Globally, atmospheric warming driving permafrost thaw results in sub-permafrost hydrate dissociation, releasing CH4 into the atmosphere to intensify global warming. It is therefore crucial to evaluate the potential risk of hydrate dissociation due to permafrost degradation. To quantitatively predict hydrate distribution and volume in complex sub-permafrost environments, a numerical framework was developed to simulate sub-permafrost hydrate formation by coupling the equilibrium CH4-hydrate formation approach with a fluid flow and transport simulator (TRANSPORTSE). In addition, integrating the equations of state describing ice melting and forming with TRANSPORTSE enabled this framework to simulate the permafrost evolution during the sub-permafrost hydrate formation. A modified sub-permafrost hydrate formation mechanism for the Mallik site is presented in this study. According to this mechanism, the CH4-rich fluids have been vertically transported since the Late Pleistocene from deep overpressurized zones via geologic fault networks to form the observed hydrate deposits in the Kugmallit–Mackenzie Bay Sequences. The established numerical framework was verified by a benchmark of hydrate formation via dissolved methane. Model calibration was performed based on laboratory data measured during a multi-stage hydrate formation experiment undertaken in the LArge scale Reservoir Simulator (LARS). As the temporal and spatial evolution of simulated and observed hydrate saturation matched well, the LARS model was therefore validated. This laboratory-scale model was then upscaled to a field-scale 2D model generated from a seismic transect across the Mallik site. The simulation confirmed the feasibility of the introduced sub-permafrost hydrate formation mechanism by demonstrating consistency with field observations. The 2D model was extended to the first 3D model of the Mallik site by using well-logs and seismic profiles, to investigate the geologic controls on the spatial hydrate distribution. An assessment of this simulation revealed the hydraulic contribution of each geological element, including relevant fault networks and sedimentary sequences. Based on the simulation results, the observed heterogeneous distribution of sub-permafrost hydrate resulted from the combined factors of the source-gas generation rate, subsurface temperature, and the permeability of geologic elements. Analysis of the results revealed that the Mallik permafrost was heated by 0.8–1.3 °C, induced by the global temperature increase of 0.44 °C and accelerated by Arctic amplification from the early 1970s to the mid-2000s. This study presents a numerical framework that can be applied to study the formation of the permafrost-hydrate system from laboratory to field scales, across timescales ranging from hours to millions of years. Overall, these simulations deepen the knowledge about the dominant factors controlling the spatial hydrate distribution in sub-permafrost environments with heterogeneous geologic elements. The framework can support improving the design of hydrate formation experiments and provide valuable contributions to future industrial hydrate exploration and exploitation activities.
Towards unifying approaches in exposure modelling for scenario-based multi-hazard risk assessments
(2023)
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.
Volcanoes are one of the Earth’s most dynamic zones and responsible for many changes in our planet. Volcano seismology aims to provide an understanding of the physical processes in volcanic systems and anticipate the style and timing of eruptions by analyzing the seismic records. Volcanic tremor signals are usually observed in the seismic records before or during volcanic eruptions. Their analysis contributes to evaluate the evolving volcanic activity and potentially predict eruptions. Years of continuous seismic monitoring now provide useful information for operational eruption forecasting. The continuously growing amount of seismic recordings, however, poses a challenge for analysis, information extraction, and interpretation, to support timely decision making during volcanic crises. Furthermore, the complexity of eruption processes and precursory activities makes the analysis challenging.
A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contribute to improving our understanding of the underlying physical processes. Some similar issues (data reduction, source separation, extraction, and classification) are addressed in the context of music information retrieval (MIR). The signal characteristics of acoustic and seismic recordings comprise a number of similarities. This thesis is going beyond classical signal analysis techniques usually employed in seismology by exploiting similarities of seismic and acoustic signals and building the information retrieval strategy on the expertise developed in the field of MIR.
First, inspired by the idea of harmonic–percussive separation (HPS) in musical signal processing, I have developed a method to extract harmonic volcanic tremor signals and to detect transient events from seismic recordings. This provides a clean tremor signal suitable for tremor investigation along with a characteristic function suitable for earthquake detection. Second, using HPS algorithms, I have developed a noise reduction technique for seismic signals. This method is especially useful for denoising ocean bottom seismometers, which are highly contaminated by noise. The advantage of this method compared to other denoising techniques is that it doesn’t introduce distortion to the broadband earthquake waveforms, which makes it reliable for different applications in passive seismological analysis. Third, to address the challenge of extracting information from high-dimensional data and investigating the complex eruptive phases, I have developed an advanced machine learning model that results in a comprehensive signal processing scheme for volcanic tremors. Using this method seismic signatures of major eruptive phases can be automatically detected. This helps to provide a chronology of the volcanic system. Also, this model is capable to detect weak precursory volcanic tremors prior to the eruption, which could be used as an indicator of imminent eruptive activity. The extracted patterns of seismicity and their temporal variations finally provide an explanation for the transition mechanism between eruptive phases.
The electrical resistivity tomography (ERT) method is widely used to investigate geological, geotechnical, and hydrogeological problems in inland and aquatic environments (i.e., lakes, rivers, and seas). The objective of the ERT method is to obtain reliable resistivity models of the subsurface that can be interpreted in terms of the subsurface structure and petrophysical properties. The reliability of the resulting resistivity models depends not only on the quality of the acquired data, but also on the employed inversion strategy. Inversion of ERT data results in multiple solutions that explain the measured data equally well. Typical inversion approaches rely on different deterministic (local) strategies that consider different smoothing and damping strategies to stabilize the inversion. However, such strategies suffer from the trade-off of smearing possible sharp subsurface interfaces separating layers with resistivity contrasts of up to several orders of magnitude. When prior information (e.g., from outcrops, boreholes, or other geophysical surveys) suggests sharp resistivity variations, it might be advantageous to adapt the parameterization and inversion strategies to obtain more stable and geologically reliable model solutions. Adaptations to traditional local inversions, for example, by using different structural and/or geostatistical constraints, may help to retrieve sharper model solutions. In addition, layer-based model parameterization in combination with local or global inversion approaches can be used to obtain models with sharp boundaries.
In this thesis, I study three typical layered near-surface environments in which prior information is used to adapt 2D inversion strategies to favor layered model solutions. In cooperation with the coauthors of Chapters 2-4, I consider two general strategies. Our first approach uses a layer-based model parameterization and a well-established global inversion strategy to generate ensembles of model solutions and assess uncertainties related to the non-uniqueness of the inverse problem. We apply this method to invert ERT data sets collected in an inland coastal area of northern France (Chapter~2) and offshore of two Arctic regions (Chapter~3). Our second approach consists of using geostatistical regularizations with different correlation lengths. We apply this strategy to a more complex subsurface scenario on a local intermountain alluvial fan in southwestern Germany (Chapter~4). Overall, our inversion approaches allow us to obtain resistivity models that agree with the general geological understanding of the studied field sites. These strategies are rather general and can be applied to various geological environments where a layered subsurface structure is expected. The flexibility of our strategies allows adaptations to invert other kinds of geophysical data sets such as seismic refraction or electromagnetic induction methods, and could be considered for joint inversion approaches.