Technological progress allows for producing ever more complex predictive models on the basis of increasingly big datasets. For risk management of natural hazards, a multitude of models is needed as basis for decision-making, e.g. in the evaluation of observational data, for the prediction of hazard scenarios, or for statistical estimates of expected damage. The question arises, how modern modelling approaches like machine learning or data-mining can be meaningfully deployed in this thematic field. In addition, with respect to data availability and accessibility, the trend is towards open data. Topic of this thesis is therefore to investigate the possibilities and limitations of machine learning and open geospatial data in the field of flood risk modelling in the broad sense. As this overarching topic is broad in scope, individual relevant aspects are identified and inspected in detail. A prominent data source in the flood context is satellite-based mapping of inundated areas, for example made openly available by the Copernicus service of the European Union. Great expectations are directed towards these products in scientific literature, both for acute support of relief forces during emergency response action, and for modelling via hydrodynamic models or for damage estimation. Therefore, a focus of this work was set on evaluating these flood masks. From the observation that the quality of these products is insufficient in forested and built-up areas, a procedure for subsequent improvement via machine learning was developed. This procedure is based on a classification algorithm that only requires training data from a particular class to be predicted, in this specific case data of flooded areas, but not of the negative class (dry areas). The application for hurricane Harvey in Houston shows the high potential of this method, which depends on the quality of the initial flood mask. Next, it is investigated how much the predicted statistical risk from a process-based model chain is dependent on implemented physical process details. Thereby it is demonstrated what a risk study based on established models can deliver. Even for fluvial flooding, such model chains are already quite complex, though, and are hardly available for compound or cascading events comprising torrential rainfall, flash floods, and other processes. In the fourth chapter of this thesis it is therefore tested whether machine learning based on comprehensive damage data can offer a more direct path towards damage modelling, that avoids explicit conception of such a model chain. For that purpose, a state-collected dataset of damaged buildings from the severe El Niño event 2017 in Peru is used. In this context, the possibilities of data-mining for extracting process knowledge are explored as well. It can be shown that various openly available geodata sources contain useful information for flood hazard and damage modelling for complex events, e.g. satellite-based rainfall measurements, topographic and hydrographic information, mapped settlement areas, as well as indicators from spectral data. Further, insights on damaging processes are discovered, which mainly are in line with prior expectations. The maximum intensity of rainfall, for example, acts stronger in cities and steep canyons, while the sum of rain was found more informative in low-lying river catchments and forested areas. Rural areas of Peru exhibited higher vulnerability in the presented study compared to urban areas. However, the general limitations of the methods and the dependence on specific datasets and algorithms also become obvious. In the overarching discussion, the different methods – process-based modelling, predictive machine learning, and data-mining – are evaluated with respect to the overall research questions. In the case of hazard observation it seems that a focus on novel algorithms makes sense for future research. In the subtopic of hazard modelling, especially for river floods, the improvement of physical models and the integration of process-based and statistical procedures is suggested. For damage modelling the large and representative datasets necessary for the broad application of machine learning are still lacking. Therefore, the improvement of the data basis in the field of damage is currently regarded as more important than the selection of algorithms.

Localisation of deformation is a ubiquitous feature in continental rift dynamics and observed across drastically different time and length scales. This thesis comprises one experimental and two numerical modelling studies investigating strain localisation in (1) a ductile shear zone induced by a material heterogeneity and (2) in an active continental rift setting. The studies are related by the fact that the weakening mechanisms on the crystallographic and grain size scale enable bulk rock weakening, which fundamentally enables the formation of shear zones, continental rifts and hence plate tectonics. Aiming to investigate the controlling mechanisms on initiation and evolution of a shear zone, the torsion experiments of the experimental study were conducted in a Patterson type apparatus with strong Carrara marble cylinders with a weak, planar Solnhofen limestone inclusion. Using state-of-the-art numerical modelling software, the torsion experiments were simulated to answer questions regarding localisation procedure like stress distribution or the impact of rheological weakening. 2D numerical models were also employed to integrate geophysical and geological data to explain characteristic tectonic evolution of the Southern and Central Kenya Rift. Key elements of the numerical tools are a randomized initial strain distribution and the usage of strain softening. During the torsion experiments, deformation begins to localise at the limestone inclusion tips in a process zone, which propagates into the marble matrix with increasing deformation until a ductile shear zone is established. Minor indicators for coexisting brittle deformation are found close to the inclusion tip and presumed to slightly facilitate strain localisation besides the dominant ductile deformation processes. The 2D numerical model of the torsion experiment successfully predicts local stress concentration and strain rate amplification ahead of the inclusion in first order agreement with the experimental results. A simple linear parametrization of strain weaking enables high accuracy reproduction of phenomenological aspects of the observed weakening. The torsion experiments suggest that loading conditions do not affect strain localisation during high temperature deformation of multiphase material with high viscosity contrasts. A numerical simulation can provide a way of analysing the process zone evolution virtually and extend the examinable frame. Furthermore, the nested structure and anastomosing shape of an ultramylonite band was mimicked with an additional second softening step. Rheological weakening is necessary to establish a shear zone in a strong matrix around a weak inclusion and for ultramylonite formation. Such strain weakening laws are also incorporated into the numerical models of the Southern and Central Kenya Rift that capture the characteristic tectonic evolution. A three-stage early rift evolution is suggested that starts with (1) the accommodation of strain by a single border fault and flexure of the hanging-wall crust, after which (2) faulting in the hanging-wall and the basin centre increases before (3) the early-stage asymmetry is lost and basinward localisation of deformation occurs. Along-strike variability of rifts can be produced by modifying the initial random noise distribution. In summary, the three studies address selected aspects of the broad range of mechanisms and processes that fundamentally enable the deformation of rock and govern the localisation patterns across the scales. In addition to the aforementioned results, the first and second manuscripts combined, demonstrate a procedure to find new or improve on existing numerical formulations for specific rheologies and their dynamic weakening. These formulations are essential in addressing rock deformation from the grain to the global scale. As within the third study of this thesis, where geodynamic controls on the evolution of a rift were examined and acquired by the integration of geological and geophysical data into a numerical model.

We investigate source processes of fluid-induced seismicity from The Geysers geothermal reservoir in California to determine their relation with hydraulic operations and improve the corresponding seismic hazard estimates. Analysis of 869 well-constrained full moment tensors (M-w 0.8-3.5) reveals significant non-double-couple components (>25%) for about 65% of the events. Volumetric deformation is governed by cumulative injection rates with larger non-double-couple components observed near the wells and during high injection periods. Source mechanisms are magnitude dependent and vary significantly between faulting regimes. Normal faulting events (M-w<2) reveal substantial volumetric components indicating dilatancy in contrast to strike-slip events that have a dominant double-couple source. Volumetric components indicating closure of cracks in the source region are mostly found for reverse faulting events with M-w>2.5. Our results imply that source processes and magnitudes of fluid-induced seismic events are strongly affected by the hydraulic operations, the reservoir stress state, and the faulting regime.

We present a high-resolution study of the upper mantle structure of Central Europe, including the western part of the East European Platform, based on S-receiver functions of 345 stations. A distinct contrast is found between Phanerozoic Europe and the East European Craton across the Trans-European Suture Zone. To the west, a pronounced velocity reduction with depth interpreted as lithosphere-asthenosphere boundary (LAB) is found at an average depth of 90 km. Beneath the craton, no strong and continuous LAB conversion is observed. Instead we find a distinct velocity reduction within the lithosphere, at 80-120 km depth. This mid-lithospheric discontinuity (MLD) is attributed to a compositional boundary between depleted and more fertile lithosphere created by late Proterozoic metasomatism. A potential LAB phase beneath the craton is very weak and varies in depth between 180 and 250 km, consistent with a reduced velocity contrast between the lower lithosphere and the asthenosphere. Within the Trans-European Suture Zone, lithospheric structure is characterized by strong heterogeneity. A dipping or step-wise increase to LAB depth of 150 km is imaged from Phanerozoic Europe to 20-22 degrees E, whereas no direct connection to the cratonic LAB or MLD to the east is apparent. At larger depths, a positive conversion associated with the lower boundary of the asthenosphere is imaged at 210-250 km depth beneath Phanerozoic Europe, continuing down to 300 km depth beneath the craton. Conversions from both 410 km and 660 km discontinuities are found at their nominal depth beneath Phanerozoic Europe, and the discontinuity at 410 km depth can also be traced into the craton. A potential negative conversion on top of the 410 km discontinuity found in migrated images is analyzed by modeling and attributed to interference with other converted phases.

Moderate to large earthquakes can increase the amount of water feeding stream flows, mobilizing excess water from deep groundwater, shallow groundwater, or the vadose zone. Here we examine the regional pattern of streamflow response to the Maule M8.8 earthquake across Chile's diverse topographic and hydro-climatic gradients. We combine streamflow analyses with groundwater flow modeling and a random forest classifier, and find that, after the earthquake, at least 85 streams had a change in flow. Discharge mostly increased () shortly after the earthquake, liberating an excess water volume of >1.1 km3, which is the largest ever reported following an earthquake. Several catchments had increased discharge of >50 mm, locally exceeding seasonal streamflow discharge under undisturbed conditions. Our modeling results favor enhanced vertical permeability induced by dynamic strain as the most probable process explaining the observed changes at the regional scale. Supporting this interpretation, our random forest classification identifies peak ground velocity and elevation extremes as most important for predicting streamflow response. Given the mean recurrence interval of ∼25 yr for >M8.0 earthquakes along the Peru–Chile Trench, our observations highlight the role of earthquakes in the regional water cycle, especially in arid environments.

Landscape evolution models (LEMs) allow the study of earth surface responses to changing climatic and tectonic forcings. While much effort has been devoted to the development of LEMs that simulate a wide range of processes, the numerical accuracy of these models has received less attention. Most LEMs use first-order accurate numerical methods that suffer from substantial numerical diffusion. Numerical diffusion particularly affects the solution of the advection equation and thus the simulation of retreating landforms such as cliffs and river knickpoints. This has potential consequences for the integrated response of the simulated landscape. Here we test a higher-order flux-limiting finite volume method that is total variation diminishing (TVD-FVM) to solve the partial differential equations of river incision and tectonic displacement. We show that using the TVD-FVM to simulate river incision significantly influences the evolution of simulated landscapes and the spatial and temporal variability of catchment-wide erosion rates. Furthermore, a two-dimensional TVD-FVM accurately simulates the evolution of landscapes affected by lateral tectonic displacement, a process whose simulation was hitherto largely limited to LEMs with flexible spatial discretization. We implement the scheme in TTLEM (TopoToolbox Landscape Evolution Model), a spatially explicit, raster-based LEM for the study of fluvially eroding landscapes in TopoToolbox 2.

Atmospheric transport is an understudied mechanism for leaf wax hydrogen isotope applications that contributes to mobilizing and depositing these compounds on the surface of the Earth. While previous efforts have identified the importance of atmospheric leaf wax deposition in remote marine locations, the processes are not well constrained on land in temperate latitudes where lakes are common and sedimentary leaf wax hydrogen isotope values are an attractive tool for understanding past precipitation changes. This work presents results from a field study that was conducted in 2010 and 2011 at Hainich National Park, Germany in order to evaluate the quantity and sources of leaf waxes in the atmosphere. Aerosols were sampled at approximately weekly intervals inside the forest canopy, and n-alkane distributions and hydrogen isotope values were compared with those from major tree species surrounding the sampling site. Despite sampling in what was expected to be a major production center, the distribution and hydrogen isotope values of atmospheric n-alkanes bore little resemblance to those of the local vegetation. Comparison with local meteorological data and to 10-day and 36-h back air mass trajectories indicated shifting effects of winds and temperature, and that mesoscale transport processes were more important than longrange mechanisms. Back trajectories also highlighted source effects, with easterly winds coinciding with relatively lower leaf wax hydrogen isotope values from more continental regions. These results suggest that leaf wax aerosols average over spatial scales that exceed typical surface catchment areas for small lake systems, even in forested areas, yet that the area over which these compounds are derived is still relatively regional. Depositional fluxes were also estimated in order to assess the potential importance of atmospheric transport to sedimentary archives. Although difficult to constrain, these estimates suggest that atmospheric deposition may be non-negligible for lake systems in cases where inputs from rivers or surface runoff are limited. Together, these observations provide new insights on how leaf waxes from different sources are integrated during aeolian transport and the spatial scales over which these processes occur.

The present-day vegetation in the tropics is mainly characterized by forests worldwide except in tropical East Africa, where forests only occur as patches at the coast and in the uplands. These forest patches result from the peculiar aridity that is linked to the uplift of the region during the Late Cenozoic. The Late Cenozoic vegetation history of East Africa is of particular interest as it has set the scene for the contemporary events in mammal and hominin evolution. In this study, we investigate the conditions under which these forest patches could have been connected, and a previous continuous forest belt could have extended and fragmented. We apply a dynamic vegetation model with a set of climatic scenarios in which we systematically alter the present-day environmental conditions such that they would be more favourable for a continuous forest belt in tropical East Africa. We consider varying environmental factors, namely temperature, precipitation and atmospheric CO2 concentrations. Our results show that all of these variables play a significant role in supporting the forest biomes and a continuous forest belt could have occurred under certain combinations of these settings. With our current knowledge of the palaeoenvironmental history of East Africa, it is likely that the region hosted these conditions during the Late Cenozoic. Recent improvements on environmental hypotheses of hominin evolution highlight the role of periods of short and extreme climate variability during the Late Cenozoic specific to East Africa in driving evolution. Our results elucidate how the forest biomes of East Africa can appear and disappear under fluctuating environmental conditions and demonstrate how this climate variability might be recognized on the biosphere level.

The eastern flanks of the Central Andes are characterized by deep convection, exposing them to hydrometeorological extreme events, often resulting in floods and a variety of mass movements. We assessed the spatiotemporal pattern of rainfall trends and the changes in the magnitude and frequency of extreme events (ae<yen>95th percentile) along an E-W traverse across the southern Central Andes using rain-gauge and high-resolution gridded datasets (CPC-uni and TRMM 3B42 V7). We generated different climate indices and made three key observations: (1) an increase of the annual rainfall has occurred at the transition between low (< 0.5 km) and intermediate (0.5-3 km) elevations between 1950 and 2014. Also, rainfall increases during the wet season and, to a lesser degree, decreases during the dry season. Increasing trends in annual total amounts characterize the period 1979-2014 in the arid, high-elevation southern Andean Plateau, whereas trend reversals with decreasing annual total amounts were found at low elevations. (2) For all analyzed periods, we observed small or no changes in the median values of the rainfall-frequency distribution, but significant trends with intensification or attenuation in the 95th percentile. (3) In the southern Andean Plateau, extreme rainfall events exhibit trends towards increasing magnitude and, to a lesser degree, frequency during the wet season, at least since 1979. Our analysis revealed that low (< 0.5 km), intermediate (0.5-3 km), and high-elevation (> 3 km) areas respond differently to changing climate conditions, and the transition zone between low and intermediate elevations is characterized by the most significant changes.