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Logging and large earthquakes are disturbances that may significantly affect hydrological and erosional processes and process rates, although in decisively different ways. Despite numerous studies that have documented the impacts of both deforestation and earthquakes on water and sediment fluxes, a number of details regarding the timing and type of de- and reforestation; seismic impacts on subsurface water fluxes; or the overall geomorphic work involved have remained unresolved. The main objective of this thesis is to address these shortcomings and to better understand and compare the hydrological and erosional process responses to such natural and man-made disturbances. To this end, south-central Chile provides an excellent natural laboratory owing to its high seismicity and the ongoing conversion of land into highly productive plantation forests. In this dissertation I combine paired catchment experiments, data analysis techniques, and physics-based modelling to investigate: 1) the effect of plantation forests on water resources, 2) the source and sink behavior of timber harvest areas in terms of overland flow generation and sediment fluxes, 3) geomorphic work and its efficiency as a function of seasonal logging, 4) possible hydrologic responses of the saturated zone to the 2010 Maule earthquake and 5) responses of the vadose zone to this earthquake. Re 1) In order to quantify the hydrologic impact of plantation forests, it is fundamental to first establish their water balances. I show that tree species is not significant in this regard, i.e. Pinus radiata and Eucalyptus globulus do not trigger any decisive different hydrologic response. Instead, water consumption is more sensitive to soil-water supply for the local hydro-climatic conditions. Re 2) Contradictory opinions exist about whether timber harvest areas (THA) generate or capture overland flow and sediment. Although THAs contribute significantly to hydrology and sediment transport because of their spatial extent, little is known about the hydrological and erosional processes occurring on them. I show that THAs may act as both sources and sinks for overland flow, which in turn intensifies surface erosion. Above a rainfall intensity of ~20 mm/h, which corresponds to <10% of all rainfall, THAs may generate runoff whereas below that threshold they remain sinks. The overall contribution of Hortonian runoff is thus secondary considering the local rainfall regime. The bulk of both runoff and sediment is generated by Dunne, saturation excess, overland flow. I also show that logging may increase infiltrability on THAs which may cause an initial decrease in streamflow followed by an increase after the groundwater storage has been refilled. Re 3) I present changes in frequency-magnitude distributions following seasonal logging by applying Quantile Regression Forests at hitherto unprecedented detail. It is clearly the season that controls the hydro-geomorphic work efficiency of clear cutting. Logging, particularly dry seasonal logging, caused a shift of work efficiency towards less flashy and mere but more frequent moderate rainfall-runoff events. The sediment transport is dominated by Dunne overland flow which is consistent with physics-based modelling using WASA-SED. Re 4) It is well accepted that earthquakes may affect hydrological processes in the saturated zone. Assuming such flow conditions, consolidation of saturated saprolitic material is one possible response. Consolidation raises the hydraulic gradients which may explain the observed increase in discharge following earthquakes. By doing so, squeezed water saturates the soil which in turn increases the water accessible for plant transpiration. Post-seismic enhanced transpiration is reflected in the intensification of diurnal cycling. Re 5) Assuming unsaturated conditions, I present the first evidence that the vadose zone may also respond to seismic waves by releasing pore water which in turn feeds groundwater reservoirs. By doing so, water tables along the valley bottoms are elevated thus providing additional water resources to the riparian vegetation. By inverse modelling, the transient increase in transpiration is found to be 30-60%. Based on the data available, both hypotheses, are not testable. Finally, when comparing the hydrological and erosional effects of the Maule earthquake with the impact of planting exotic plantation forests, the overall observed earthquake effects are comparably small, and limited to short time scales.
Landslides are one of the biggest natural hazards in Georgia, a mountainous country in the Caucasus. So far, no systematic monitoring and analysis of the dynamics of landslides in Georgia has been made. Especially as landslides are triggered by extrinsic processes, the analysis of landslides together with precipitation and earthquakes is challenging. In this thesis I describe the advantages and limits of remote sensing to detect and better understand the nature of landslide in Georgia. The thesis is written in a cumulative form, composing a general introduction, three manuscripts and a summary and outlook chapter. In the present work, I measure the surface displacement due to active landslides with different interferometric synthetic aperture radar (InSAR) methods. The slow landslides (several cm per year) are well detectable with two-pass interferometry. In same time, the extremely slow landslides (several mm per year) could be detected only with time series InSAR techniques. I exemplify the success of InSAR techniques by showing hitherto unknown landslides, located in the central part of Georgia. Both, the landslide extent and displacement rate is quantified. Further, to determine a possible depth and position of potential sliding planes, inverse models were developed. Inverse modeling searches for parameters of source which can create observed displacement distribution. I also empirically estimate the volume of the investigated landslide using displacement distributions as derived from InSAR combined with morphology from an aerial photography. I adapted a volume formula for our case, and also combined available seismicity and precipitation data to analyze potential triggering factors. A governing question was: What causes landslide acceleration as observed in the InSAR data? The investigated area (central Georgia) is seismically highly active. As an additional product of the InSAR data analysis, a deformation area associated with the 7th September Mw=6.0 earthquake was found. Evidences of surface ruptures directly associated with the earthquake could not be found in the field, however, during and after the earthquake new landslides were observed. The thesis highlights that deformation from InSAR may help to map area prone landslides triggering by earthquake, potentially providing a technique that is of relevance for country wide landslide monitoring, especially as new satellite sensors will emerge in the coming years.
Several mechanisms are proposed to be part of the earthquake triggering process, including static stress interactions and dynamic stress transfer. Significant differences of these mechanisms are particularly expected in the spatial distribution of aftershocks. However, testing the different hypotheses is challenging because it requires the consideration of the large uncertainties involved in stress calculations as well as the appropriate consideration of secondary aftershock triggering which is related to stress changes induced by smaller pre- and aftershocks. In order to evaluate the forecast capability of different mechanisms, I take the effect of smaller--magnitude earthquakes into account by using the epidemic type aftershock sequence (ETAS) model where the spatial probability distribution of direct aftershocks, if available, is correlated to alternative source information and mechanisms. Surface shaking, rupture geometry, and slip distributions are tested. As an approximation of the shaking level, ShakeMaps are used which are available in near real-time after a mainshock and thus could be used for first-order forecasts of the spatial aftershock distribution. Alternatively, the use of empirical decay laws related to minimum fault distance is tested and Coulomb stress change calculations based on published and random slip models. For comparison, the likelihood values of the different model combinations are analyzed in the case of several well-known aftershock sequences (1992 Landers, 1999 Hector Mine, 2004 Parkfield). The tests show that the fault geometry is the most valuable information for improving aftershock forecasts. Furthermore, they reveal that static stress maps can additionally improve the forecasts of off--fault aftershock locations, while the integration of ground shaking data could not upgrade the results significantly. In the second part of this work, I focused on a procedure to test the information content of inverted slip models. This allows to quantify the information gain if this kind of data is included in aftershock forecasts. For this purpose, the ETAS model based on static stress changes, which is introduced in part one, is applied. The forecast ability of the models is systematically tested for several earthquake sequences and compared to models using random slip distributions. The influence of subfault resolution and segment strike and dip is tested. Some of the tested slip models perform very good, in that cases almost no random slip models are found to perform better. Contrastingly, for some of the published slip models, almost all random slip models perform better than the published slip model. Choosing a different subfault resolution hardly influences the result, as long the general slip pattern is still reproducible. Whereas different strike and dip values strongly influence the results depending on the standard deviation chosen, which is applied in the process of randomly selecting the strike and dip values.
The Arctic is considered as a focal region in the ongoing climate change debate. The currently observed and predicted climate warming is particularly pronounced in the high northern latitudes. Rising temperatures in the Arctic cause progressive deepening and duration of permafrost thawing during the arctic summer, creating an ‘active layer’ with high bioavailability of nutrients and labile carbon for microbial consumption. The microbial mineralization of permafrost carbon creates large amounts of greenhouse gases, including carbon dioxide and methane, which can be released to the atmosphere, creating a positive feedback to global warming. However, to date, the microbial communities that drive the overall carbon cycle and specifically methane production in the Arctic are poorly constrained. To assess how these microbial communities will respond to the predicted climate changes, such as an increase in atmospheric and soil temperatures causing increased bioavailability of organic carbon, it is necessary to investigate the current status of this environment, but also how these microbial communities reacted to climate changes in the past. This PhD thesis investigated three records from two different study sites in the Russian Arctic, including permafrost, lake shore and lake deposits from Siberia and Chukotka. A combined stratigraphic approach of microbial and molecular organic geochemical techniques were used to identify and quantify characteristic microbial gene and lipid biomarkers. Based on this data it was possible to characterize and identify the climate response of microbial communities involved in past carbon cycling during the Middle Pleistocene and the Late Pleistocene to Holocene. It is shown that previous warmer periods were associated with an expansion of bacterial and archaeal communities throughout the Russian Arctic, similar to present day conditions. Different from this situation, past glacial and stadial periods experienced a substantial decrease in the abundance of Bacteria and Archaea. This trend can also be confirmed for the community of methanogenic archaea that were highly abundant and diverse during warm and particularly wet conditions. For the terrestrial permafrost, a direct effect of the temperature on the microbial communities is likely. In contrast, it is suggested that the temperature rise in scope of the glacial-interglacial climate variations led to an increase of the primary production in the Arctic lake setting, as can be seen in the corresponding biogenic silica distribution. The availability of this algae-derived carbon is suggested to be a driver for the observed pattern in the microbial abundance. This work demonstrates the effect of climate changes on the community composition of methanogenic archae. Methanosarcina-related species were abundant throughout the Russian Arctic and were able to adapt to changing environmental conditions. In contrast, members of Methanocellales and Methanomicrobiales were not able to adapt to past climate changes. This PhD thesis provides first evidence that past climatic warming led to an increased abundance of microbial communities in the Arctic, closely linked to the cycling of carbon and methane production. With the predicted climate warming, it may, therefore, be anticipated that extensive amounts of microbial communities will develop. Increasing temperatures in the Arctic will affect the temperature sensitive parts of the current microbiological communities, possibly leading to a suppression of cold adapted species and the prevalence of methanogenic archaea that tolerate or adapt to increasing temperatures. These changes in the composition of methanogenic archaea will likely increase the methane production potential of high latitude terrestrial regions, changing the Arctic from a carbon sink to a source.
Black shales are sedimentary rocks with a high content of organic carbon, which leads to a dark grayish to black color. Due to their potential to contain oil or gas, black shales are of great interest for the support of the worldwide energy supply. An integrated seismic investigation of the Lower Palaeozoic black shales was carried out at the Danish island Bornholm to locate the shallow-lying Alum Shale layer and its surrounding formations and to characterize its potential as a source rock. Therefore, two seismic experiments at a total of three crossing profiles were carried out in October 2010 and in June 2012 in the southern part of the island. Two different active measurements were conducted with either a weight drop source or a minivibrator. Additionally, the ambient noise field was recorded at the study location over a time interval of about one day, and also a laboratory analysis of borehole samples was carried out. The seismic profiles were positioned as close as possible to two scientific boreholes which were used for comparative purposes. The seismic field data was analyzed with traveltime tomography, surface wave inversion and seismic interferometry to obtain the P-wave and S-wave velocity models of the subsurface. The P-wave velocity models which were determined for all three profiles clearly locate the Alum Shale layer between the Komstad Limestone layer on top and the Læså Sandstone Formation at the base of the models. The black shale layer has P-wave velocities around 3 km/s which are lower compared to the adjacent formations. Due to a very good agreement of the sonic log and the vertical velocity profiles of the two seismic lines, which are directly crossing the borehole where the sonic log was conducted, the reliability of the traveltime tomography is proven. A correlation of the seismic velocities with the content of organic carbon is an important task for the characterization of the reservoir properties of a black shale formation. It is not possible without calibration but in combination with a full 2D tomographic image of the subsurface it gives the subsurface distribution of the organic material. The S-wave model obtained with surface wave inversion of the vibroseis data of one of the profiles images the Alum Shale layer also very well with S-wave velocities around 2 km/s. Although individual 1D velocity models for each of the source positions were determined, the subsurface S-wave velocity distribution is very uniform with a good match between the single models. A really new approach described here is the application of seismic interferometry to a really small study area and a quite short time interval. Also new is the selective procedure of only using time windows with the best crosscorrelation signals to achieve the final interferograms. Due to the small scale of the interferometry even P-wave signals can be observed in the final crosscorrelations. In the laboratory measurements the seismic body waves were recorded for different pressure and temperature stages. Therefore, samples of different depths of the Alum Shale were available from one of the scientific boreholes at the study location. The measured velocities have a high variance with changing pressure or temperature. Recordings with wave propagation both parallel and perpendicular to the bedding of the samples reveal a great amount of anisotropy for the P-wave velocity, whereas the S-wave velocity is almost independent of the wave direction. The calculated velocity ratio is also highly anisotropic with very low values for the perpendicular samples and very high values for the parallel ones. Interestingly, the laboratory velocities of the perpendicular samples are comparable to the velocities of the field experiments indicating that the field measurements are sensitive to wave propagation in vertical direction. The velocity ratio is also calculated with the P-wave and S-wave velocity models of the field experiments. Again, the Alum Shale can be clearly separated from the adjacent formations because it shows overall very low vP/vS ratios around 1.4. The very low velocity ratio indicates the content of gas in the black shale formation. With the combination of all the different methods described here, a comprehensive interpretation of the seismic response of the black shale layer can be made and the hydrocarbon source rock potential can be estimated.
The main intention of the PhD project was to create a varve chronology for the Suigetsu Varves 2006' (SG06) composite profile from Lake Suigetsu (Japan) by thin section microscopy. The chronology was not only to provide an age-scale for the various palaeo-environmental proxies analysed within the SG06 project, but also and foremost to contribute, in combination with the SG06 14C chronology, to the international atmospheric radiocarbon calibration curve (IntCal). The SG06 14C data are based on terrestrial leaf fossils and therefore record atmospheric 14C values directly, avoiding the corrections necessary for the reservoir ages of the marine datasets, which are currently used beyond the tree-ring limit in the IntCal09 dataset (Reimer et al., 2009). The SG06 project is a follow up of the SG93 project (Kitagawa & van der Plicht, 2000), which aimed to produce an atmospheric calibration dataset, too, but suffered from incomplete core recovery and varve count uncertainties. For the SG06 project the complete Lake Suigetsu sediment sequence was recovered continuously, leaving the task to produce an improved varve count. Varve counting was carried out using a dual method approach utilizing thin section microscopy and micro X-Ray Fluorescence (µXRF). The latter was carried out by Dr. Michael Marshall in cooperation with the PhD candidate. The varve count covers 19 m of composite core, which corresponds to the time frame from ≈10 to ≈40 kyr BP. The count result showed that seasonal layers did not form in every year. Hence, the varve counts from either method were incomplete. This rather common problem in varve counting is usually solved by manual varve interpolation. But manual interpolation often suffers from subjectivity. Furthermore, sedimentation rate estimates (which are the basis for interpolation) are generally derived from neighbouring, well varved intervals. This assumes that the sedimentation rates in neighbouring intervals are identical to those in the incompletely varved section, which is not necessarily true. To overcome these problems a novel interpolation method was devised. It is computer based and automated (i.e. avoids subjectivity and ensures reproducibility) and derives the sedimentation rate estimate directly from the incompletely varved interval by statistically analysing distances between successive seasonal layers. Therefore, the interpolation approach is also suitable for sediments which do not contain well varved intervals. Another benefit of the novel method is that it provides objective interpolation error estimates. Interpolation results from the two counting methods were combined and the resulting chronology compared to the 14C chronology from Lake Suigetsu, calibrated with the tree-ring derived section of IntCal09 (which is considered accurate). The varve and 14C chronology showed a high degree of similarity, demonstrating that the novel interpolation method produces reliable results. In order to constrain the uncertainties of the varve chronology, especially the cumulative error estimates, U-Th dated speleothem data were used by linking the low frequency 14C signal of Lake Suigetsu and the speleothems, increasing the accuracy and precision of the Suigetsu calibration dataset. The resulting chronology also represents the age-scale for the various palaeo-environmental proxies analysed in the SG06 project. One proxy analysed within the PhD project was the distribution of event layers, which are often representatives of past floods or earthquakes. A detailed microfacies analysis revealed three different types of event layers, two of which are described here for the first time for the Suigetsu sediment. The types are: matrix supported layers produced as result of subaqueous slope failures, turbidites produced as result of landslides and turbidites produced as result of flood events. The former two are likely to have been triggered by earthquakes. The vast majority of event layers was related to floods (362 out of 369), which allowed the construction of a respective chronology for the last 40 kyr. Flood frequencies were highly variable, reaching their greatest values during the global sea level low-stand of the Glacial, their lowest values during Heinrich Event 1. Typhoons affecting the region represent the most likely control on the flood frequency, especially during the Glacial. However, also local, non-climatic controls are suggested by the data. In summary, the work presented here expands and revises knowledge on the Lake Suigetsu sediment and enabls the construction of a far more precise varve chronology. The 14C calibration dataset is the first such derived from lacustrine sediments to be included into the (next) IntCal dataset. References: Kitagawa & van der Plicht, 2000, Radiocarbon, Vol 42(3), 370-381 Reimer et al., 2009, Radiocarbon, Vol 51(4), 1111-1150
Water management and environmental protection is vulnerable to extreme low flows during streamflow droughts. During the last decades, in most rivers of Central Europe summer runoff and low flows have decreased. Discharge projections agree that future decrease in runoff is likely for catchments in Brandenburg, Germany. Depending on the first-order controls on low flows, different adaption measures are expected to be appropriate. Small catchments were analyzed because they are expected to be more vulnerable to a changing climate than larger rivers. They are mainly headwater catchments with smaller ground water storage. Local characteristics are more important at this scale and can increase vulnerability. This thesis mutually evaluates potential adaption measures to sustain minimum runoff in small catchments of Brandenburg, Germany, and similarities of these catchments regarding low flows. The following guiding questions are addressed: (i) Which first-order controls on low flows and related time scales exist? (ii) Which are the differences between small catchments regarding low flow vulnerability? (iii) Which adaption measures to sustain minimum runoff in small catchments of Brandenburg are appropriate considering regional low flow patterns? Potential adaption measures to sustain minimum runoff during periods of low flows can be classified into three categories: (i) increase of groundwater recharge and subsequent baseflow by land use change, land management and artificial ground water recharge, (ii) increase of water storage with regulated outflow by reservoirs, lakes and wetland water management and (iii) regional low flow patterns have to be considered during planning of measures with multiple purposes (urban water management, waste water recycling and inter-basin water transfer). The question remained whether water management of areas with shallow groundwater tables can efficiently sustain minimum runoff. Exemplary, water management scenarios of a ditch irrigated area were evaluated using the model Hydrus-2D. Increasing antecedent water levels and stopping ditch irrigation during periods of low flows increased fluxes from the pasture to the stream, but storage was depleted faster during the summer months due to higher evapotranspiration. Fluxes from this approx. 1 km long pasture with an area of approx. 13 ha ranged from 0.3 to 0.7 l\s depending on scenario. This demonstrates that numerous of such small decentralized measures are necessary to sustain minimum runoff in meso-scale catchments. Differences in the low flow risk of catchments and meteorological low flow predictors were analyzed. A principal component analysis was applied on daily discharge of 37 catchments between 1991 and 2006. Flows decreased more in Southeast Brandenburg according to meteorological forcing. Low flow risk was highest in a region east of Berlin because of intersection of a more continental climate and the specific geohydrology. In these catchments, flows decreased faster during summer and the low flow period was prolonged. A non-linear support vector machine regression was applied to iteratively select meteorological predictors for annual 30-day minimum runoff in 16 catchments between 1965 and 2006. The potential evapotranspiration sum of the previous 48 months was the most important predictor (r²=0.28). The potential evapotranspiration of the previous 3 months and the precipitation of the previous 3 months and last year increased model performance (r²=0.49, including all four predictors). Model performance was higher for catchments with low yield and more damped runoff. In catchments with high low flow risk, explanatory power of long term potential evapotranspiration was high. Catchments with a high low flow risk as well as catchments with a considerable decrease in flows in southeast Brandenburg have the highest demand for adaption. Measures increasing groundwater recharge are to be preferred. Catchments with high low flow risk showed relatively deep and decreasing groundwater heads allowing increased groundwater recharge at recharge areas with higher altitude away from the streams. Low flows are expected to stay low or decrease even further because long term potential evapotranspiration was the most important low flow predictor and is projected to increase during climate change. Differences in low flow risk and runoff dynamics between catchments have to be considered for management and planning of measures which do not only have the task to sustain minimum runoff.
Lamprophyre sind porphyrische, aus Mantelschmelzen gebildete Gesteine, die meist in Form von Gängen auftreten. Sie zeichnen sich durch auffällige und charakteristische texturelle, chemische und mineralogische Eigenschaften aus. Als ehemalige Mantelschmelzen liefern sie Information sowohl über Bedingungen der Schmelzbildung im Mantel als auch über geodynamische Prozesse, die zu metasomatischer Veränderung des Mantels geführt haben. Im Saxothuringikum Mitteleuropas, am Nordrand des Böhmischen Massivs, gibt es zahlreiche Lamprophyrvorkommen, die hier zur Charakterisierung der Mantelentwicklung während der variszischen Orogenese dienen. Die vorliegende Arbeit befaßt sich mit den mineralogischen, geochemischen und isotopischen (Sr-Nd-Pb) Signaturen von spätvariszischen kalkalkalischen Lamprophyren, von postvariszischen ultramafischen Lamprophyren, von Alkalibasalten der Lausitz und, zum Vergleich, von prävariszischen Gabbros. Darüberhinaus nutzt die Arbeit Lithium-Isotopensignaturen kombiniert mit Sr-Nd-Pb–Isotopendaten spätvariszischer kalkalkalischer Lamprophyre aus drei variszischen Domänen (Erzgebirge, Lausitz, Sudeten) zur Erkundung der lokalen Mantelüberprägungen während der variszischen Orogenese.
Within a research project about future sustainable water management options in the Elbe River basin, quasi-natural discharge scenarios had to be provided. The semi-distributed eco-hydrological model SWIM was utilised for this task. According to scenario simulations driven by the stochastical climate model STAR, the region would get distinctly drier. However, this thesis focuses on the challenge of meeting the requirement of high model fidelity even for smaller sub-basins. Usually, the quality of the simulations is lower at inner points than at the outlet. Four research paper chapters and the discussion chapter deal with the reasons for local model deviations and the problem of optimal spatial calibration. Besides other assessments, the Markov Chain Monte Carlo method is applied to show whether evapotranspiration or precipitation should be corrected to minimise runoff deviations, principal component analysis is used in an unusual way to evaluate local precipitation alterations by land cover changes, and remotely sensed surface temperatures allow for an independent view on the evapotranspiration landscape. The overall insight is that spatially explicit hydrological modelling of such a large river basin requires a lot of local knowledge. It probably needs more time to obtain such knowledge as is usually provided for hydrological modelling studies.
The Arctic tundra, covering approx. 5.5 % of the Earth’s land surface, is one of the last ecosystems remaining closest to its untouched condition. Remote sensing is able to provide information at regular time intervals and large spatial scales on the structure and function of Arctic ecosystems. But almost all natural surfaces reveal individual anisotropic reflectance behaviors, which can be described by the bidirectional reflectance distribution function (BRDF). This effect can cause significant changes in the measured surface reflectance depending on solar illumination and sensor viewing geometries. The aim of this thesis is the hyperspectral and spectro-directional reflectance characterization of important Arctic tundra vegetation communities at representative Siberian and Alaskan tundra sites as basis for the extraction of vegetation parameters, and the normalization of BRDF effects in off-nadir and multi-temporal remote sensing data. Moreover, in preparation for the upcoming German EnMAP (Environmental Mapping and Analysis Program) satellite mission, the understanding of BRDF effects in Arctic tundra is essential for the retrieval of high quality, consistent and therefore comparable datasets. The research in this doctoral thesis is based on field spectroscopic and field spectro-goniometric investigations of representative Siberian and Alaskan measurement grids. The first objective of this thesis was the development of a lightweight, transportable, and easily managed field spectro-goniometer system which nevertheless provides reliable spectro-directional data. I developed the Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS). The outcome of the field spectro-radiometrical measurements at the Low Arctic study sites along important environmental gradients (regional climate, soil pH, toposequence, and soil moisture) show that the different plant communities can be distinguished by their nadir-view reflectance spectra. The results especially reveal separation possibilities between the different tundra vegetation communities in the visible (VIS) blue and red wavelength regions. Additionally, the near-infrared (NIR) shoulder and NIR reflectance plateau, despite their relatively low values due to the low structure of tundra vegetation, are still valuable information sources and can separate communities according to their biomass and vegetation structure. In general, all different tundra plant communities show: (i) low maximum NIR reflectance; (ii) a weakly or nonexistent visible green reflectance peak in the VIS spectrum; (iii) a narrow “red-edge” region between the red and NIR wavelength regions; and (iv) no distinct NIR reflectance plateau. These common nadir-view reflectance characteristics are essential for the understanding of the variability of BRDF effects in Arctic tundra. None of the analyzed tundra communities showed an even closely isotropic reflectance behavior. In general, tundra vegetation communities: (i) usually show the highest BRDF effects in the solar principal plane; (ii) usually show the reflectance maximum in the backward viewing directions, and the reflectance minimum in the nadir to forward viewing directions; (iii) usually have a higher degree of reflectance anisotropy in the VIS wavelength region than in the NIR wavelength region; and (iv) show a more bowl-shaped reflectance distribution in longer wavelength bands (>700 nm). The results of the analysis of the influence of high sun zenith angles on the reflectance anisotropy show that with increasing sun zenith angles, the reflectance anisotropy changes to azimuthally symmetrical, bowl-shaped reflectance distributions with the lowest reflectance values in the nadir view position. The spectro-directional analyses also show that remote sensing products such as the NDVI or relative absorption depth products are strongly influenced by BRDF effects, and that the anisotropic characteristics of the remote sensing products can significantly differ from the observed BRDF effects in the original reflectance data. But the results further show that the NDVI can minimize view angle effects relative to the contrary spectro-directional effects in the red and NIR bands. For the researched tundra plant communities, the overall difference of the off-nadir NDVI values compared to the nadir value increases with increasing sensor viewing angles, but on average never exceeds 10 %. In conclusion, this study shows that changes in the illumination-target-viewing geometry directly lead to an altering of the reflectance spectra of Arctic tundra communities according to their object-specific BRDFs. Since the different tundra communities show only small, but nonetheless significant differences in the surface reflectance, it is important to include spectro-directional reflectance characteristics in the algorithm development for remote sensing products.
Even though quite different in occurrence and consequences, from a modeling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding: uncertainty about the modeling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Nevertheless deterministic approaches are still widely used in natural hazard assessments, holding the risk of underestimating the hazard with disastrous effects. The all-round probabilistic framework of Bayesian networks constitutes an attractive alternative. In contrast to deterministic proceedings, it treats response variables as well as explanatory variables as random variables making no difference between input and output variables. Using a graphical representation Bayesian networks encode the dependency relations between the variables in a directed acyclic graph: variables are represented as nodes and (in-)dependencies between variables as (missing) edges between the nodes. The joint distribution of all variables can thus be described by decomposing it, according to the depicted independences, into a product of local conditional probability distributions, which are defined by the parameters of the Bayesian network. In the framework of this thesis the Bayesian network approach is applied to different natural hazard domains (i.e. seismic hazard, flood damage and landslide assessments). Learning the network structure and parameters from data, Bayesian networks reveal relevant dependency relations between the included variables and help to gain knowledge about the underlying processes. The problem of Bayesian network learning is cast in a Bayesian framework, considering the network structure and parameters as random variables itself and searching for the most likely combination of both, which corresponds to the maximum a posteriori (MAP score) of their joint distribution given the observed data. Although well studied in theory the learning of Bayesian networks based on real-world data is usually not straight forward and requires an adoption of existing algorithms. Typically arising problems are the handling of continuous variables, incomplete observations and the interaction of both. Working with continuous distributions requires assumptions about the allowed families of distributions. To "let the data speak" and avoid wrong assumptions, continuous variables are instead discretized here, thus allowing for a completely data-driven and distribution-free learning. An extension of the MAP score, considering the discretization as random variable as well, is developed for an automatic multivariate discretization, that takes interactions between the variables into account. The discretization process is nested into the network learning and requires several iterations. Having to face incomplete observations on top, this may pose a computational burden. Iterative proceedings for missing value estimation become quickly infeasible. A more efficient albeit approximate method is used instead, estimating the missing values based only on the observations of variables directly interacting with the missing variable. Moreover natural hazard assessments often have a primary interest in a certain target variable. The discretization learned for this variable does not always have the required resolution for a good prediction performance. Finer resolutions for (conditional) continuous distributions are achieved with continuous approximations subsequent to the Bayesian network learning, using kernel density estimations or mixtures of truncated exponential functions. All our proceedings are completely data-driven. We thus avoid assumptions that require expert knowledge and instead provide domain independent solutions, that are applicable not only in other natural hazard assessments, but in a variety of domains struggling with uncertainties.
Climatic variations and human activity now and increasingly in the future cause land cover changes and introduce perturbations in the terrestrial carbon reservoirs in vegetation, soil and detritus. Optical remote sensing and in particular Imaging Spectroscopy has shown the potential to quantify land surface parameters over large areas, which is accomplished by taking advantage of the characteristic interactions of incident radiation and the physico-chemical properties of a material. The objective of this thesis is to quantify key soil parameters, including soil organic carbon, using field and Imaging Spectroscopy. Organic carbon, iron oxides and clay content are selected to be analyzed to provide indicators for ecosystem function in relation to land degradation, and additionally to facilitate a quantification of carbon inventories in semiarid soils. The semiarid Albany Thicket Biome in the Eastern Cape Province of South Africa is chosen as study site. It provides a regional example for a semiarid ecosystem that currently undergoes land changes due to unadapted management practices and furthermore has to face climate change induced land changes in the future. The thesis is divided in three methodical steps. Based on reflectance spectra measured in the field and chemically determined constituents of the upper topsoil, physically based models are developed to quantify soil organic carbon, iron oxides and clay content. Taking account of the benefits limitations of existing methods, the approach is based on the direct application of known diagnostic spectral features and their combination with multivariate statistical approaches. It benefits from the collinearity of several diagnostic features and a number of their properties to reduce signal disturbances by influences of other spectral features. In a following step, the acquired hyperspectral image data are prepared for an analysis of soil constituents. The data show a large spatial heterogeneity that is caused by the patchiness of the natural vegetation in the study area that is inherent to most semiarid landscapes. Spectral mixture analysis is performed and used to deconvolve non-homogenous pixels into their constituent components. For soil dominated pixels, the subpixel information is used to remove the spectral influence of vegetation and to approximate the pure spectral signature coming from the soil. This step is an integral part when working in natural non-agricultural areas where pure bare soil pixels are rare. It is identified as the largest benefit within the multi-stage methodology, providing the basis for a successful and unbiased prediction of soil constituents from hyperspectral imagery. With the proposed approach it is possible (1) to significantly increase the spatial extent of derived information of soil constituents to areas with about 40 % vegetation coverage and (2) to reduce the influence of materials such as vegetation on the quantification of soil constituents to a minimum. Subsequently, soil parameter quantities are predicted by the application of the feature-based soil prediction models to the maps of locally approximated soil signatures. Thematic maps showing the spatial distribution of the three considered soil parameters in October 2009 are produced for the Albany Thicket Biome of South Africa. The maps are evaluated for their potential to detect erosion affected areas as effects of land changes and to identify degradation hot spots in regard to support local restoration efforts. A regional validation, carried out using available ground truth sites, suggests remaining factors disturbing the correlation of spectral characteristics and chemical soil constituents. The approach is developed for semiarid areas in general and not adapted to specific conditions in the study area. All processing steps of the developed methodology are implemented in software modules, where crucial steps of the workflow are fully automated. The transferability of the methodology is shown for simulated data of the future EnMAP hyperspectral satellite. Soil parameters are successfully predicted from these data despite intense spectral mixing within the lower spatial resolution EnMAP pixels. This study shows an innovative approach to use Imaging Spectroscopy for mapping of key soil constituents, including soil organic carbon, for large areas in a non-agricultural ecosystem and under consideration of a partially vegetation coverage. It can contribute to a better assessment of soil constituents that describe ecosystem processes relevant to detect and monitor land changes. The maps further provide an assessment of the current carbon inventory in soils, valuable for carbon balances and carbon mitigation products.
This cumulative dissertation explored the use of the detection of natural background of fast neutrons, the so-called cosmic-ray neutron sensing (CRS) approach to measure field-scale soil moisture in cropped fields. Primary cosmic rays penetrate the top atmosphere and interact with atmospheric particles. Such interaction results on a cascade of high-energy neutrons, which continue traveling through the atmospheric column. Finally, neutrons penetrate the soil surface and a second cascade is produced with the so-called secondary cosmic-ray neutrons (fast neutrons). Partly, fast neutrons are absorbed by hydrogen (soil moisture). Remaining neutrons scatter back to the atmosphere, where its flux is inversely correlated to the soil moisture content, therefore allowing a non-invasive indirect measurement of soil moisture. The CRS methodology is mainly evaluated based on a field study carried out on a farmland in Potsdam (Brandenburg, Germany) along three crop seasons with corn, sunflower and winter rye; a bare soil period; and two winter periods. Also, field monitoring was carried out in the Schaefertal catchment (Harz, Germany) for long-term testing of CRS against ancillary data. In the first experimental site, the CRS method was calibrated and validated using different approaches of soil moisture measurements. In a period with corn, soil moisture measurement at the local scale was performed at near-surface only, and in subsequent periods (sunflower and winter rye) sensors were placed in three depths (5 cm, 20 cm and 40 cm). The direct transfer of CRS calibration parameters between two vegetation periods led to a large overestimation of soil moisture by the CRS. Part of this soil moisture overestimation was attributed to an underestimation of the CRS observation depth during the corn period ( 5-10 cm), which was later recalculated to values between 20-40 cm in other crop periods (sunflower and winter rye). According to results from these monitoring periods with different crops, vegetation played an important role on the CRS measurements. Water contained also in crop biomass, above and below ground, produces important neutron moderation. This effect was accounted for by a simple model for neutron corrections due to vegetation. It followed crop development and reduced overall CRS soil moisture error for periods of sunflower and winter rye. In Potsdam farmland also inversely-estimated soil hydraulic parameters were determined at the field scale, using CRS soil moisture from the sunflower period. A modelling framework coupling HYDRUS-1D and PEST was applied. Subsequently, field-scale soil hydraulic properties were compared against local scale soil properties (modelling and measurements). Successful results were obtained here, despite large difference in support volume. Simple modelling framework emphasizes future research directions with CRS soil moisture to parameterize field scale models. In Schaefertal catchment, CRS measurements were verified using precipitation and evapotranspiration data. At the monthly resolution, CRS soil water storage was well correlated to these two weather variables. Also clearly, water balance could not be closed due to missing information from other compartments such as groundwater, catchment discharge, etc. In the catchment, the snow influence to natural neutrons was also evaluated. As also observed in Potsdam farmland, CRS signal was strongly influenced by snow fall and snow accumulation. A simple strategy to measure snow was presented for Schaefertal case. Concluding remarks of this dissertation showed that (a) the cosmic-ray neutron sensing (CRS) has a strong potential to provide feasible measurement of mean soil moisture at the field scale in cropped fields; (b) CRS soil moisture is strongly influenced by other environmental water pools such as vegetation and snow, therefore these should be considered in analysis; (c) CRS water storage can be used for soil hydrology modelling for determination of soil hydraulic parameters; and (d) CRS approach has strong potential for long term monitoring of soil moisture and for addressing studies of water balance.
In soils and sediments there is a strong coupling between local biogeochemical processes and the distribution of water, electron acceptors, acids and nutrients. Both sides are closely related and affect each other from small scale to larger scales. Soil structures such as aggregates, roots, layers or macropores enhance the patchiness of these distributions. At the same time it is difficult to access the spatial distribution and temporal dynamics of these parameter. Noninvasive imaging techniques with high spatial and temporal resolution overcome these limitations. And new non-invasive techniques are needed to study the dynamic interaction of plant roots with the surrounding soil, but also the complex physical and chemical processes in structured soils. In this study we developed an efficient non-destructive in-situ method to determine biogeochemical parameters relevant to plant roots growing in soil. This is a quantitative fluorescence imaging method suitable for visualizing the spatial and temporal pH changes around roots. We adapted the fluorescence imaging set-up and coupled it with neutron radiography to study simultaneously root growth, oxygen depletion by respiration activity and root water uptake. The combined set up was subsequently applied to a structured soil system to map the patchy structure of oxic and anoxic zones induced by a chemical oxygen consumption reaction for spatially varying water contents. Moreover, results from a similar fluorescence imaging technique for nitrate detection were complemented by a numerical modeling study where we used imaging data, aiming to simulate biodegradation under anaerobic, nitrate reducing conditions.
The surface heat flow (qs) is paramount for modeling the thermal structure of the lithosphere. Changes in the qs over a distinct lithospheric unit are normally directly reflecting changes in the crustal composition and therewith the radiogenic heat budget (e.g., Rudnick et al., 1998; Förster and Förster, 2000; Mareschal and Jaupart, 2004; Perry et al., 2006; Hasterok and Chapman, 2011, and references therein) or, less usual, changes in the mantle heat flow (e.g., Pollack and Chapman, 1977). Knowledge of this physical property is therefore of great interest for both academic research and the energy industry. The present study focuses on the qs of central and southern Israel as part of the Sinai Microplate (SM). Having formed during Oligocene to Miocene rifting and break-up of the African and Arabian plates, the SM is characterized by a young and complex tectonic history. Resulting from the time thermal diffusion needs to pass through the lithosphere, on the order of several tens-of-millions of years (e.g., Fowler, 1990); qs-values of the area reflect conditions of pre-Oligocene times. The thermal structure of the lithosphere beneath the SM in general, and south-central Israel in particular, has remained poorly understood. To address this problem, the two parameters needed for the qs determination were investigated. Temperature measurements were made at ten pre-existing oil and water exploration wells, and the thermal conductivity of 240 drill core and outcrop samples was measured in the lab. The thermal conductivity is the sensitive parameter in this determination. Lab measurements were performed on both, dry and water-saturated samples, which is labor- and time-consuming. Another possibility is the measurement of thermal conductivity in dry state and the conversion to a saturated value by using mean model approaches. The availability of a voluminous and diverse dataset of thermal conductivity values in this study allowed (1) in connection with the temperature gradient to calculate new reliable qs values and to use them to model the thermal pattern of the crust in south-central Israel, prior to young tectonic events, and (2) in connection with comparable datasets, controlling the quality of different mean model approaches for indirect determination of bulk thermal conductivity (BTC) of rocks. The reliability of numerically derived BTC values appears to vary between different mean models, and is also strongly dependent upon sample lithology. Yet, correction algorithms may significantly reduce the mismatch between measured and calculated conductivity values based on the different mean models. Furthermore, the dataset allowed the derivation of lithotype-specific conversion equations to calculate the water-saturated BTC directly from data of dry-measured BTC and porosity (e.g., well log derived porosity) with no use of any mean model and thus provide a suitable tool for fast analysis of large datasets. The results of the study indicate that the qs in the study area is significantly higher than previously assumed. The new presented qs values range between 50 and 62 mW m⁻². A weak trend of decreasing heat flow can be identified from the east to the west (55-50 mW m⁻²), and an increase from the Dead Sea Basin to the south (55-62 mW m⁻²). The observed range can be explained by variation in the composition (heat production) of the upper crust, accompanied by more systematic spatial changes in its thickness. The new qs data then can be used, in conjunction with petrophysical data and information on the structure and composition of the lithosphere, to adjust a model of the pre-Oligocene thermal state of the crust in south-central Israel. The 2-D steady-state temperature model was calculated along an E-W traverse based on the DESIRE seismic profile (Mechie et al., 2009). The model comprises the entire lithosphere down to the lithosphere–asthenosphere boundary (LAB) involving the most recent knowledge of the lithosphere in pre-Oligocene time, i.e., prior to the onset of rifting and plume-related lithospheric thermal perturbations. The adjustment of modeled and measured qs allows conclusions about the pre-Oligocene LAB-depth. After the best fitting the most likely depth is 150 km which is consistent with estimations made in comparable regions of the Arabian Shield. It therefore comprises the first ever modelled pre-Oligocene LAB depth, and provides important clues on the thermal state of lithosphere before rifting. This, in turn, is vital for a better understanding of the (thermo)-dynamic processes associated with lithosphere extension and continental break-up.
Antarctic glacier forfields are extreme environments and pioneer sites for ecological succession. The Antarctic continent shows microbial community development as a natural laboratory because of its special environment, geographic isolation and little anthropogenic influence. Increasing temperatures due to global warming lead to enhanced deglaciation processes in cold-affected habitats and new terrain is becoming exposed to soil formation and accessible for microbial colonisation. This study aims to understand the structure and development of glacier forefield bacterial communities, especially how soil parameters impact the microorganisms and how those are adapted to the extreme conditions of the habitat. To this effect, a combination of cultivation experiments, molecular, geophysical and geochemical analysis was applied to examine two glacier forfields of the Larsemann Hills, East Antarctica. Culture-independent molecular tools such as terminal restriction length polymorphism (T-RFLP), clone libraries and quantitative real-time PCR (qPCR) were used to determine bacterial diversity and distribution. Cultivation of yet unknown species was carried out to get insights in the physiology and adaptation of the microorganisms. Adaptation strategies of the microorganisms were studied by determining changes of the cell membrane phospholipid fatty acid (PLFA) inventory of an isolated bacterium in response to temperature and pH fluctuations and by measuring enzyme activity at low temperature in environmental soil samples. The two studied glacier forefields are extreme habitats characterised by low temperatures, low water availability and small oligotrophic nutrient pools and represent sites of different bacterial succession in relation to soil parameters. The investigated sites showed microbial succession at an early step of soil formation near the ice tongue in comparison to closely located but rather older and more developed soil from the forefield. At the early step the succession is influenced by a deglaciation-dependent areal shift of soil parameters followed by a variable and prevalently depth-related distribution of the soil parameters that is driven by the extreme Antarctic conditions. The dominant taxa in the glacier forefields are Actinobacteria, Acidobacteria, Proteobacteria, Bacteroidetes, Cyanobacteria and Chloroflexi. The connection of soil characteristics with bacterial community structure showed that soil parameter and soil formation along the glacier forefield influence the distribution of certain phyla. In the early step of succession the relative undifferentiated bacterial diversity reflects the undifferentiated soil development and has a high potential to shift according to past and present environmental conditions. With progressing development environmental constraints such as water or carbon limitation have a greater influence. Adapting the culturing conditions to the cold and oligotrophic environment, the number of culturable heterotrophic bacteria reached up to 108 colony forming units per gram soil and 148 isolates were obtained. Two new psychrotolerant bacteria, Herbaspirillum psychrotolerans PB1T and Chryseobacterium frigidisoli PB4T, were characterised in detail and described as novel species in the family of Oxalobacteraceae and Flavobacteriaceae, respectively. The isolates are able to grow at low temperatures tolerating temperature fluctuations and they are not specialised to a certain substrate, therefore they are well-adapted to the cold and oligotrophic environment. The adaptation strategies of the microorganisms were analysed in environmental samples and cultures focussing on extracellular enzyme activity at low temperature and PLFA analyses. Extracellular phosphatases (pH 11 and pH 6.5), β-glucosidase, invertase and urease activity were detected in the glacier forefield soils at low temperature (14°C) catalysing the conversion of various compounds providing necessary substrates and may further play a role in the soil formation and total carbon turnover of the habitat. The PLFA analysis of the newly isolated species C. frigidisoli showed that the cold-adapted strain develops different strategies to maintain the cell membrane function under changing environmental conditions by altering the PLFA inventory at different temperatures and pH values. A newly discovered fatty acid, which was not found in any other microorganism so far, significantly increased at decreasing temperature and low pH and thus plays an important role in the adaption of C. frigidisoli. This work gives insights into the diversity, distribution and adaptation mechanisms of microbial communities in oligotrophic cold-affected soils and shows that Antarctic glacier forefields are suitable model systems to study bacterial colonisation in connection to soil formation.
Large areas in the humid tropics are currently undergoing land-use change. The decrease of tropical rainforest, which is felled for land clearing and timber production, is countered by increasing areas of tree plantations and secondary forests. These changes are known to affect the regional water cycle as a result of plant-specific water demand and by influencing key soil properties which determine hydrological flow paths. One of these key properties sensitive to land-use change is the saturated hydraulic conductivity (Ks) as it governs vertical percolation of water within the soil profile. Low values of Ks in a certain soil depth can form an impeding layer and lead to perched water tables and the development of predominantly lateral flow paths such as overland flow. These processes can induce nutrient redistribution, erosion and soil degradation and thus affect ecosystem services and human livelihoods. Due to its sensitivity to land-use change, Ks is commonly used to assess the associated changes in hydrological flow paths. The objective of this dissertation was to assess the effect of land-use change on hydrological flow paths by analysing Ks as indicator variable. Sources of Ks variability, their implications for Ks monitoring and the relationship between Ks and near-surface hydrological flow paths in the context of land-use change were studied. The research area was located in central Panama, a country widely experiencing the abovementioned changes in land use. Ks is dependent on both static, soil-inherent properties such as particle size and clay mineralogy and dynamic, land use-dependent properties such as organic carbon content. By conducting a pair of studies with one of these influences held constant in each, the importance of static and dynamic properties for Ks was assessed. Applying a space-for-time approach to sample Ks under secondary forests of different age classes on comparable soils, a recovery of Ks from the former pasture use was shown to require more than eight years. The process was limited to the 0−6 cm sampling depth and showed large variability among replicates. A wavelet analysis of a Ks transect crossing different soil map units under comparable land cover, old-growth tropical rainforest, showed large small-scale variability, which was attributed to biotic influences, as well as a possible but non-conclusive influence of soil types. The two results highlight the importance of dynamic, land use-dependent influences on Ks. Monitoring studies can help to quantify land use-induced change of Ks, but there is a variety of sampling designs which differ in efficiency of estimating mean Ks. A comparative study of four designs and their suitability for Ks monitoring is used to give recommendations about designing a Ks monitoring scheme. Quantifying changes in spatial means of Ks for small catchments with a rotational stratified sampling design did not prove to be more efficient than Simple Random Sampling. The lack of large-scale spatial structure prevented benefits of stratification, and large small-scale variability resulting from local biotic processes and artificial effects of destructive sampling caused a lack of temporal consistency in the re-sampling of locations, which is part of the rotational design. The relationship between Ks and near-surface hydrological flow paths is of critical importance when assessing the consequences of land-use change in the humid tropics. The last part of this dissertation aimed at disclosing spatial relationships between Ks and overland flow as influenced by different land cover types. The effects of Ks on overland-flow generation were spatially variable, different between planar plots and incised flowlines and strongly influenced by land-cover characteristics. A simple comparison of Ks values and rainfall intensities was insufficient to describe the observed pattern of overland flow. Likewise, event flow in the stream was apparently not directly related to overland flow response patterns within the catchments. The study emphasises the importance of combining pedological, hydrological, meteorological and botanical measurements to comprehensively understand the land use-driven change in hydrological flow paths. In summary, Ks proved to be a suitable parameter for assessing the influence of land-use change on soils and hydrological processes. The results illustrated the importance of land cover and spatial variability of Ks for decisions on sampling designs and for interpreting overland-flow generation. As relationships between Ks and overland flow were shown to be complex and dependent on land cover, an interdisciplinary approach is required to comprehensively understand the effects of land-use change on soils and near-surface hydrological flow paths in the humid tropics.
The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.
Intra-continental mountain belts typically form as a result of tectonic forces associated with distant plate collisions. In general, each mountain belt has a distinctive morphology and orogenic evolution that is highly dependent on the unique distribution and geometries of inherited structures and other crustal weaknesses. In this thesis, I have investigated the complex and irregular Cenozoic orogenic evolution of the Central Kyrgyz Tien Shan in Central Asia, which is presently one of the most active intra-continental mountain belts in the world. This work involved combining a broad array of datasets, including thermochronologic, magnetostratigraphic, sediment provenance and stable isotope data, to identify and date various changes in tectonic deformation, climate and surface processes. Many of these changes are linked and can ultimately be related to regional-scale processes that altered the orogenic evolution of the Central Kyrgyz Tien Shan. The Central Kyrgyz Tien Shan contains a sub-parallel series of structures that were reactivated in the late Cenozoic in response to the tectonic forces associated with the distant India-Eurasia collision. Over time, slip on the various reactivated structures created the succession of mountain ranges and intermontane basins which characterises the modern morphology of the region. In this thesis, new quantitative constraints on the exhumation histories of several mountain ranges have been obtained by using low temperature thermochronological data from 95 samples (zircon (U-Th)/He, apatite fission track and (U-Th)/He). Time-temperature histories derived by modelling the thermochronologic data of individual samples identify at least two stages of Cenozoic cooling in most of the region’s mountain ranges: (1) initially low cooling rates (<1°C/Myr) during the tectonic quiescent period and (2) increased cooling in the late Cenozoic, which occurred diachronously and with variable magnitude in different ranges. This second cooling stage is interpreted to represent increased erosion caused by active deformation, and in many of the sampled mountain ranges, provides the first available constraints on the timing of late Cenozoic deformation. New constraints on the timing of deformation have also been derived from the sedimentary record of intermontane basins. In the intermontane Issyk Kul basin, new magnetostratigraphic data from two sedimentary sections suggests that deposition of the first Cenozoic syn-tectonic sediments commenced at ~26 Ma. Zircon U-Pb provenance data, paleocurrent and conglomerate clast analysis reveals that these sediments were sourced from the Terskey Range to the south of the basin, suggesting that the onset of the late Cenozoic deformation occurred >26 Ma in that particular range. Elsewhere, growth strata relationships are used to identify syn-tecotnic deposition and constrain the timing of nearby deformation. Collectively, these new constraints obtained from thermochronologic and sedimentary data have allowed me to infer the spatiotemporal distribution of deformation in a transect through the Central Kyrgyz Tien Shan, and determine the order in which mountain ranges started deforming. These data suggest that deformation began in a few widely-spaced mountain ranges in the late Oligocene and early Miocene. Typically, these earlier mountain ranges are bounded on at least one side by a reactivated structure, which probably corresponds to the frictionally weakest and most suitably orientated inherited structures for accommodating the roughly north-south directed horizontal crustal shortening of the late Cenozoic. Moreover, tectonically-induced rock uplift in the Terskey Range, following the reactivation of the bounding structure before 26 Ma, likely caused significant surface uplift across the range, which in turn lead to enhanced orographic precipitation. These wetter conditions have been inferred from stable isotope data collected in the two magnetostratigraphically-dated sections in the Issyk Kul basin. Subsequently, in the late Miocene (~12‒5 Ma), more mountain ranges and inherited structures appear to have started actively deforming. Importantly, the onset of deformation at these locations in the late Miocene coincides with an increase in exhumation of ranges that had started deforming earlier in the late Oligocene‒early Miocene. Based on this observation, I have suggested that there must have been an overall increase in the rate of horizontal crustal shortening across the Central Kyrgyz Tien Shan, which likely relates to regional tectonic changes that affected much of Central Asia. Many of the mountain ranges that started deforming in the late Miocene were associated with out-of-sequence tectonic reactivation and initiation, which lead to the partitioning of larger intermontane basins. Moreover, within most of the intermontane basins in the Central Kyrgyz Tien Shan, this inferred late Miocene increase in horizontal crustal shortening occurs roughly at the same time as an increase in sedimentation rates and a significant change sediment composition. Therefore, I have suggested that the overall magnitude of deformational processes increased in the late Miocene, promoting more flexural subsidence in the intermontane basins of the Central Kyrgyz Tien Shan.
Die Anpassung von Sektoren an veränderte klimatische Bedingungen erfordert ein Verständnis von regionalen Vulnerabilitäten. Vulnerabilität ist als Funktion von Sensitivität und Exposition, welche potentielle Auswirkungen des Klimawandels darstellen, und der Anpassungsfähigkeit von Systemen definiert. Vulnerabilitätsstudien, die diese Komponenten quantifizieren, sind zu einem wichtigen Werkzeug in der Klimawissenschaft geworden. Allerdings besteht von der wissenschaftlichen Perspektive aus gesehen Uneinigkeit darüber, wie diese Definition in Studien umgesetzt werden soll. Ausdiesem Konflikt ergeben sich viele Herausforderungen, vor allem bezüglich der Quantifizierung und Aggregierung der einzelnen Komponenten und deren angemessenen Komplexitätsniveaus. Die vorliegende Dissertation hat daher zum Ziel die Anwendbarkeit des Vulnerabilitätskonzepts voranzubringen, indem es in eine systematische Struktur übersetzt wird. Dies beinhaltet alle Komponenten und schlägt für jede Klimaauswirkung (z.B. Sturzfluten) eine Beschreibung des vulnerablen Systems vor (z.B. Siedlungen), welches direkt mit einer bestimmten Richtung eines relevanten klimatischen Stimulus in Verbindung gebracht wird (z.B. stärkere Auswirkungen bei Zunahme der Starkregentage). Bezüglich der herausfordernden Prozedur der Aggregierung werden zwei alternative Methoden, die einen sektorübergreifenden Überblick ermöglichen, vorgestellt und deren Vor- und Nachteile diskutiert. Anschließend wird die entwickelte Struktur einer Vulnerabilitätsstudie mittels eines indikatorbasierten und deduktiven Ansatzes beispielhaft für Gemeinden in Nordrhein-Westfalen in Deutschland angewandt. Eine Übertragbarkeit auf andere Regionen ist dennoch möglich. Die Quantifizierung für die Gemeinden stützt sich dabei auf Informationen aus der Literatur. Da für viele Sektoren keine geeigneten Indikatoren vorhanden waren, werden in dieser Arbeit neue Indikatoren entwickelt und angewandt, beispielsweise für den Forst- oder Gesundheitssektor. Allerdings stellen fehlende empirische Daten bezüglich relevanter Schwellenwerte eine Lücke dar, beispielsweise welche Stärke von Klimaänderungen eine signifikante Auswirkung hervorruft. Dies führt dazu, dass die Studie nur relative Aussagen zum Grad der Vulnerabilität jeder Gemeinde im Vergleich zum Rest des Bundeslandes machen kann. Um diese Lücke zu füllen, wird für den Forstsektor beispielhaft die heutige und zukünftige Sturmwurfgefahr von Wäldern berechnet. Zu diesem Zweck werden die Eigenschaften der Wälder mit empirischen Schadensdaten eines vergangenen Sturmereignisses in Verbindung gebracht. Der sich daraus ergebende Sensitivitätswert wird anschließend mit den Windverhältnissen verknüpft. Sektorübergreifende Vulnerabilitätsstudien erfordern beträchtliche Ressourcen, was oft deren Anwendbarkeit erschwert. In einem nächsten Schritt wird daher das Potential einer Vereinfachung der Komplexität anhand zweier sektoraler Beispiele untersucht. Um das Auftreten von Waldbränden vorherzusagen, stehen zahlreiche meteorologische Indices zur Verfügung, welche eine Spannbreite unterschiedlicher Komplexitäten aufweisen. Bezüglich der Anzahl monatlicher Waldbrände weist die relative Luftfeuchtigkeit für die meisten deutschen Bundesländer eine bessere Vorhersagekraft als komplexere Indices auf. Dies ist er Fall, obgleich sie selbst als Eingangsvariable für die komplexeren Indices verwendet wird. Mit Hilfe dieses einzelnen meteorologischen Faktors kann also die Waldbrandgefahr in deutschen Region ausreichend genau ausgedrückt werden, was die Ressourceneffizienz von Studien erhöht. Die Methodenkomplexität wird auf ähnliche Weise hinsichtlich der Anwendung des ökohydrologischen Modells SWIM für die Region Brandenburg untersucht. Die interannuellen Bodenwasserwerte, welche durch dieses Modell simuliert werden, können nur unzureichend durch ein einfacheres statistisches Modell, welches auf denselben Eingangsdaten aufbaut, abgebildet werden. Innerhalb eines Zeithorizonts von Jahrzehnten, kann der statistische Ansatz jedoch das Bodenwasser zufriedenstellend abbilden und zeigt eine Dominanz der Bodeneigenschaft Feldkapazität. Dies deutet darauf hin, dass die Komplexität im Hinblick auf die Anzahl der Eingangsvariablen für langfristige Berechnungen reduziert werden kann. Allerdings sind die Aussagen durch fehlende beobachtete Bodenwasserwerte zur Validierung beschränkt. Die vorliegenden Studien zur Vulnerabilität und ihren Komponenten haben gezeigt, dass eine Anwendung noch immer wissenschaftlich herausfordernd ist. Folgt man der hier verwendeten Vulnerabilitätsdefinition, treten zahlreiche Probleme bei der Implementierung in regionalen Studien auf. Mit dieser Dissertation wurden Fortschritte bezüglich der aufgezeigten Lücken bisheriger Studien erzielt, indem eine systematische Struktur für die Beschreibung und Aggregierung von Vulnerabilitätskomponenten erarbeitet wurde. Hierfür wurden mehrere Ansätze diskutiert, die jedoch Vor- und Nachteile besitzen. Diese sollten vor der Anwendung von zukünftigen Studien daher ebenfalls sorgfältig abgewogen werden. Darüber hinaus hat sich gezeigt, dass ein Potential besteht einige Ansätze zu vereinfachen, jedoch sind hierfür weitere Untersuchungen nötig. Insgesamt konnte die Dissertation die Anwendung von Vulnerabilitätsstudien als Werkzeug zur Unterstützung von Anpassungsmaßnahmen stärken.