By using 3-year global positioning system (GPS)measurements from December 2013 to November 2016, we provide in this study a detailed survey on the climatology of the GPS signal loss of Swarm onboard receivers. Our results show that the GPS signal losses prefer to occur at both low latitudes between ±5 and ±20 ◦ magnetic latitude (MLAT) and high latitudes above 60 ◦ MLAT in both hemispheres. These events at all latitudes are observed mainly during equinoxes and December solstice months, while totally absent during June solstice months. At low latitudes the GPS signal losses are caused by the equatorial plasma irregularities shortly after sunset, and at high latitude they are also highly related to the large density gradients associated with ionospheric irregularities. Additionally, the high-latitude events are more often observed in the Southern Hemisphere, occurring mainly at the cusp region and along nightside auroral latitudes. The signal losses mainly happen for those GPS rays with elevation angles less than 20 ◦ , and more commonly occur when the line of sight between GPS and Swarm satellites is aligned with the shell structure of plasma irregularities. Our results also confirm that the capability of the Swarm receiver has been improved after the bandwidth of the phase-locked loop (PLL) widened, but the updates cannot radically avoid the interruption in tracking GPS satellites caused by the ionospheric plasma irregularities. Additionally, after the PLL bandwidth increased larger than 0.5 Hz, some unexpected signal losses are observed even at middle latitudes, which are not related to the ionospheric plasma irregularities. Our results suggest that rather than 1.0 Hz, a PLL bandwidth of 0.5 Hz is a more suitable value for the Swarm receiver.

The habilitation thesis presented here includes results from several studies dealing with fluid-rock interactions and rock deformation processes in active fault zones. The focus in all of these studies is on the influence of clay minerals on the geochemical and the hydro-mechanical behavior of the fault rocks. The research was conducted on rock cores and cuttings from four scientific drilling projects at the San Andreas Fault (USA), the Nankai Trough subduction zone and the Japan Trench subduction zone (Japan), as well as the Alpine Fault in New Zealand. These ICDP (International Continental Scientific Drilling Program) and IODP (International Ocean Discovery Program) funded projects were all conducted with the aim to monitor and better understand earthquakes. Chapter 1 contains a short introduction to the topic with basic principles and objectives regarding the research approach. Chapter 2 describes the state of the art in clay mineral and fault zone science, gives a short description of the individual drilling projects and their locations on which the research was based, and summarizes the most important analytical methods used. Chapter 3 comprises ten peer-reviewed publications that are connected thematically and methodologically. The papers were published in the years 2006-2015, and additional related publications including myself as co-author are given in the literature list. The ten publications address different questions concerning the formation of clay minerals and processes of fluid-rock interaction in active fault zones. Six papers contain results from the SAFOD drilling project, USA (San Andreas Fault Observatory at Depth), with the main focus on fluid-rock interaction processes in fault rocks and the formation and location of clay minerals. Three publications report on research from the NanTroSEIZE drilling project (Nankai Trough Seismogenic Zone Experiment) and the JFAST drilling project (Japan Trench Fast Drilling Project). Both projects are situated in Japan. Here, the swelling behavior of smectite clay minerals in relation to changing environmental conditions (e.g. temperature and/or humidity) was investigated. The last publication included here concerns a study from the DFDP project (Deep Fault Drilling Project) in New Zealand, where I investigated the deformation of clay minerals on the context of the hydro-mechanical behavior of the fault zone rocks. I was first author in nine of the publications and in charge of the project preparation, measurements and data analyses, and the completion of the manuscript. As co-author on the other publication I was responsible for electronmicroscopy analyses (SEM and TEM) and their interpretation. The key results from the publications in Chapter 3 are discussed in Chapter 4 with additional considerations from more recent papers. Following the major theses in Chapter 5, Chapter 6 highlights a future research project in clay mineralogy research at the GFZ. An appendix includes more detailed descriptions of the laboratory equipment and lists of all publications, conference contributions and teaching courses and modules.

The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach. Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality. Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.

Skarn deposits are found on every continents and were formed at different times from Precambrian to Tertiary. Typically, the formation of a skarn is induced by a granitic intrusion in carbonates-rich sedimentary rocks. During contact metamorphism, fluids derived from the granite interact with the sedimentary host rocks, which results in the formation of calc-silicate minerals at the expense of carbonates. Those newly formed minerals generally develop in a metamorphic zoned aureole with garnet in the proximal and pyroxene in the distal zone. Ore elements contained in magmatic fluids are precipitated due to the change in fluid composition. The temperature decrease of the entire system, due to the cooling of magmatic fluids and the entering of meteoric water, allows retrogression of some prograde minerals. The Hämmerlein skarn deposit has a multi-stage history with a skarn formation during regional metamorphism and a retrogression of primary skarn minerals during the granitic intrusion. Tin was mobilized during both events. The 340 Ma old tin-bearing skarn minerals show that tin was present in sediments before the granite intrusion, and that the first Sn enrichment occurred during the skarn formation by regional metamorphism fluids. In a second step at ca. 320 Ma, tin-bearing fluids were produced with the intrusion of the Eibenstock granite. Tin, which has been added by the granite and remobilized from skarn calc-silicates, precipitated as cassiterite. Compared to clay or marl, the skarn is enriched in Sn, W, In, Zn, and Cu. These metals have been supplied during both regional metamorphism and granite emplacement. In addition, the several isotopic and chemical data of skarn samples show that the granite selectively added elements such as Sn, and that there was no visible granitic contribution to the sedimentary signature of the skarn The example of Hämmerlein shows that it is possible to form a tin-rich skarn without associated granite when tin has already been transported from tin-bearing sediments during regional metamorphism by aqueous metamorphic fluids. These skarns are economically not interesting if tin is only contained in the skarn minerals. Later alteration of the skarn (the heat and fluid source is not necessarily a granite), however, can lead to the formation of secondary cassiterite (SnO2), with which the skarn can become economically highly interesting.

Natural extreme events are an integral part of nature on planet earth. Usually these events are only considered hazardous to humans, in case they are exposed. In this case, however, natural hazards can have devastating impacts on human societies. Especially hydro-meteorological hazards have a high damage potential in form of e.g. riverine and pluvial floods, winter storms, hurricanes and tornadoes, which can occur all over the globe. Along with an increasingly warm climate also an increase in extreme weather which potentially triggers natural hazards can be expected. Yet, not only changing natural systems, but also changing societal systems contribute to an increasing risk associated with these hazards. These can comprise increasing exposure and possibly also increasing vulnerability to the impacts of natural events. Thus, appropriate risk management is required to adapt all parts of society to existing and upcoming risks at various spatial scales. One essential part of risk management is the risk assessment including the estimation of the economic impacts. However, reliable methods for the estimation of economic impacts due to hydro-meteorological hazards are still missing. Therefore, this thesis deals with the question of how the reliability of hazard damage estimates can be improved, represented and propagated across all spatial scales. This question is investigated using the specific example of economic impacts to companies as a result of riverine floods in Germany. Flood damage models aim to describe the damage processes during a given flood event. In other words they describe the vulnerability of a specific object to a flood. The models can be based on empirical data sets collected after flood events. In this thesis tree-based models trained with survey data are used for the estimation of direct economic flood impacts on the objects. It is found that these machine learning models, in conjunction with increasing sizes of data sets used to derive the models, outperform state-of-the-art damage models. However, despite the performance improvements induced by using multiple variables and more data points, large prediction errors remain at the object level. The occurrence of the high errors was explained by a further investigation using distributions derived from tree-based models. The investigation showed that direct economic impacts to individual objects cannot be modeled by a normal distribution. Yet, most state-of-the-art approaches assume a normal distribution and take mean values as point estimators. Subsequently, the predictions are unlikely values within the distributions resulting in high errors. At larger spatial scales more objects are considered for the damage estimation. This leads to a better fit of the damage estimates to a normal distribution. Consequently, also the performance of the point estimators get better, although large errors can still occur due to the variance of the normal distribution. It is recommended to use distributions instead of point estimates in order to represent the reliability of damage estimates. In addition current approaches also mostly ignore the uncertainty associated with the characteristics of the hazard and the exposed objects. For a given flood event e.g. the estimation of the water level at a certain building is prone to uncertainties. Current approaches define exposed objects mostly by the use of land use data sets. These data sets often show inconsistencies, which introduce additional uncertainties. Furthermore, state-of-the-art approaches also imply problems of missing consistency when predicting the damage at different spatial scales. This is due to the use of different types of exposure data sets for model derivation and application. In order to face these issues a novel object-based method was developed in this thesis. The method enables a seamless estimation of hydro-meteorological hazard damage across spatial scales including uncertainty quantification. The application and validation of the method resulted in plausible estimations at all spatial scales without overestimating the uncertainty. Mainly newly available data sets containing individual buildings make the application of the method possible as they allow for the identification of flood affected objects by overlaying the data sets with water masks. However, the identification of affected objects with two different water masks revealed huge differences in the number of identified objects. Thus, more effort is needed for their identification, since the number of objects affected determines the order of magnitude of the economic flood impacts to a large extent. In general the method represents the uncertainties associated with the three components of risk namely hazard, exposure and vulnerability, in form of probability distributions. The object-based approach enables a consistent propagation of these uncertainties in space. Aside from the propagation of damage estimates and their uncertainties across spatial scales, a propagation between models estimating direct and indirect economic impacts was demonstrated. This enables the inclusion of uncertainties associated with the direct economic impacts within the estimation of the indirect economic impacts. Consequently, the modeling procedure facilitates the representation of the reliability of estimated total economic impacts. The representation of the estimates' reliability prevents reasoning based on a false certainty, which might be attributed to point estimates. Therefore, the developed approach facilitates a meaningful flood risk management and adaptation planning. The successful post-event application and the representation of the uncertainties qualifies the method also for the use for future risk assessments. Thus, the developed method enables the representation of the assumptions made for the future risk assessments, which is crucial information for future risk management. This is an important step forward, since the representation of reliability associated with all components of risk is currently lacking in all state-of-the-art methods assessing future risk. In conclusion, the use of object-based methods giving results in the form of distributions instead of point estimations is recommended. The improvement of the model performance by the means of multi-variable models and additional data points is possible, but small. Uncertainties associated with all components of damage estimation should be included and represented within the results. Furthermore, the findings of the thesis suggest that, at larger scales, the influence of the uncertainty associated with the vulnerability is smaller than those associated with the hazard and exposure. This leads to the conclusion that for an increased reliability of flood damage estimations and risk assessments, the improvement and active inclusion of hazard and exposure, including their uncertainties, is needed in addition to the improvements of the models describing the vulnerability of the objects.