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Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments.
As land-cover conversion continues to expand into ever more remote areas in the humid tropics, montane rainforests are increasingly threatened. In the south Ecuadorian Andes, they are not only subject to man-made disturbances but also to naturally occurring landslides. I was interested in the impact of this ecosystem dynamics on a key parameter of the hydrologic cycle, the soil saturated hydraulic conductivity (synonym: permeability; Ks from here on), because it is a sensitive indicator for soil disturbances. My general objective was to quantify the effects of the regional natural and human disturbances on the saturated hydraulic conductivity and to describe the resulting spatial-temporal patterns. The main hypotheses were: 1) disturbances cause an apparent displacement of the less permeable soil layer towards the surface, either due to a loss of the permeable surface soil after land-sliding, or as a consequence of the surface soil compaction under cattle pastures; 2) ‘recovery’ from disturbance, either because of landslide re-vegetation or because of secondary succession after pasture abandonment, involves an apparent displacement of the less permeable layer back towards the original depth an 3) disturbances cause a simplification of the Ks spatial structure, i.e. the spatially dependent random variation diminishes; the subsequent recovery entails the re-establishment of the original structure. In my first study, I developed a synthesis of recent geostatistical research regarding its applicability to soil hydraulic data, including exploratory data analysis and variogram estimation techniques; I subsequently evaluated the results in terms of spatial prediction uncertainty. Concerning the exploratory data analysis, my main results were: 1) Gaussian uni- and bivariate distributions of the log-transformed data; 2) the existence of significant local trends; 3) no need for robust estimation; 4) no anisotropic variation. I found partly considerable differences in covariance parameters resulting from different variogram estimation techniques, which, in the framework of spatial prediction, were mainly reflected in the spatial connectivity of the Ks-field. Ignoring the trend component and an arbitrary use of robust estimators, however, would have the most severe consequences in this respect. Regarding variogram modeling, I encouraged restricted maximum likelihood estimation because of its accuracy and independence on the selected lags needed for experimental variograms. The second study dealt with the Ks spatial-temporal pattern in the sequences of natural and man-made disturbances characteristic for the montane rainforest study area. To investigate the disturbance effects both on global means and the spatial structure of Ks, a combined design-and model-based sampling approach was used for field-measurements at soil depths of 12.5, 20, and 50 cm (n=30-150/depth) under landslides of different ages (2 and 8 years), under actively grazed pasture, fallows following pasture abandonment (2 to 25 years of age), and under natural forest. Concerning global means, our main findings were 1) global means of the soil permeability generally decrease with increasing soil depth; 2) no significant Ks differences can be observed among landslides and compared to the natural forest; 3) a distinct permeability decrease of two orders of magnitude occurs after forest conversion to pasture at shallow soil depths, and 4) the slow regeneration process after pasture abandonment requires at least one decade. Regarding the Ks spatial structure, we found that 1) disturbances affect the Ks spatial structure in the topsoil, and 2) the largest differences in spatial patterns are associated with the subsoil permeability. In summary, the regional landslide activity seems to affect soil hydrology to a marginal extend only, which is in contrast to the pronounced drop of Ks after forest conversion. We used this spatial-temporal information combined with local rain intensities to assess the partitioning of rainfall into vertical and lateral flowpaths under undisturbed, disturbed, and regenerating land-cover types in the third study. It turned out that 1) the montane rainforest is characterized by prevailing vertical flowpaths in the topsoil, which can switch to lateral directions below 20 cm depth for a small number of rain events, which may, however, transport a high portion of the annual runoff; 2) similar hydrological flowpaths occur under the landslides except for a somewhat higher probability of impermeable layer formation in the topsoil of a young landslide, and 3) pronounced differences in runoff components can be observed for the human disturbance sequence involving the development of near-surface impeding layers for 24, 44, and 8 % of rain events for pasture, a two-year-old fallow, and a ten-year-old fallow, respectively.
Motivations and research objectives: During the passage of rain water through a forest canopy two main processes take place. First, water is redistributed; and second, its chemical properties change substantially. The rain water redistribution and the brief contact with plant surfaces results in a large variability of both throughfall and its chemical composition. Since throughfall and its chemistry influence a range of physical, chemical and biological processes at or below the forest floor the understanding of throughfall variability and the prediction of throughfall patterns potentially improves the understanding of near-surface processes in forest ecosystems. This thesis comprises three main research objectives. The first objective is to determine the variability of throughfall and its chemistry, and to investigate some of the controlling factors. Second, I explored throughfall spatial patterns. Finally, I attempted to assess the temporal persistence of throughfall and its chemical composition. Research sites and methods: The thesis is based on investigations in a tropical montane rain forest in Ecuador, and lowland rain forest ecosystems in Brazil and Panama. The first two studies investigate both throughfall and throughfall chemistry following a deterministic approach. The third study investigates throughfall patterns with geostatistical methods, and hence, relies on a stochastic approach. Results and Conclusions: Throughfall is highly variable. The variability of throughfall in tropical forests seems to exceed that of many temperate forests. These differences, however, do not solely reflect ecosystem-inherent characteristics, more likely they also mirror management practices. Apart from biotic factors that influence throughfall variability, rainfall magnitude is an important control. Throughfall solute concentrations and solute deposition are even more variable than throughfall. In contrast to throughfall volumes, the variability of solute deposition shows no clear differences between tropical and temperate forests, hence, biodiversity is not a strong predictor of solute deposition heterogeneity. Many other factors control solute deposition patterns, for instance, solute concentration in rainfall and antecedent dry period. The temporal variability of the latter factors partly accounts for the low temporal persistence of solute deposition. In contrast, measurements of throughfall volume are quite stable over time. Results from the Panamanian research site indicate that wet and dry areas outlast consecutive wet seasons. At this research site, throughfall exhibited only weak or pure nugget autocorrelation structures over the studies lag distances. A close look at the geostatistical tools at hand provided evidence that throughfall datasets, in particular those of large events, require robust variogram estimation if one wants to avoid outlier removal. This finding is important because all geostatistical throughfall studies that have been published so far analyzed their data using the classical, non-robust variogram estimator.
The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking.
Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011–2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations.
Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.
Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61% and 74.7 ± 23.2% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.
Evaluation of nitrogen dynamics in high-order streams and rivers based on high-frequency monitoring
(2023)
Nutrient storage, transform and transport are important processes for achieving environmental and ecological health, as well as conducting water management plans. Nitrogen is one of the most noticeable elements due to its impacts on tremendous consequences of eutrophication in aquatic systems. Among all nitrogen components, researches on nitrate are blooming because of widespread deployments of in-situ high-frequency sensors. Monitoring and studying nitrate can become a paradigm for any other reactive substances that may damage environmental conditions and cause economic losses.
Identifying nitrate storage and its transport within a catchment are inspiring to the management of agricultural activities and municipal planning. Storm events are periods when hydrological dynamics activate the exchange between nitrate storage and flow pathways. In this dissertation, long-term high-frequency monitoring data at three gauging stations in the Selke river were used to quantify event-scale nitrate concentration-discharge (C-Q) hysteretic relationships. The Selke catchment is characterized into three nested subcatchments by heterogeneous physiographic conditions and land use. With quantified hysteresis indices, impacts of seasonality and landscape gradients on C-Q relationships are explored. For example, arable area has deep nitrate legacy and can be activated with high intensity precipitation during wetting/wet periods (i.e., the strong hydrological connectivity). Hence, specific shapes of C-Q relationships in river networks can identify targeted locations and periods for agricultural management actions within the catchment to decrease nitrate output into downstream aquatic systems like the ocean.
The capacity of streams for removing nitrate is of both scientific and social interest, which makes the quantification motivated. Although measurements of nitrate dynamics are advanced compared to other substances, the methodology to directly quantify nitrate uptake pathways is still limited spatiotemporally. The major problem is the complex convolution of hydrological and biogeochemical processes, which limits in-situ measurements (e.g., isotope addition) usually to small streams with steady flow conditions. This makes the extrapolation of nitrate dynamics to large streams highly uncertain. Hence, understanding of in-stream nitrate dynamic in large rivers is still necessary. High-frequency monitoring of nitrate mass balance between upstream and downstream measurement sites can quantitatively disentangle multi-path nitrate uptake dynamics at the reach scale (3-8 km). In this dissertation, we conducted this approach in large stream reaches with varying hydro-morphological and environmental conditions for several periods, confirming its success in disentangling nitrate uptake pathways and their temporal dynamics. Net nitrate uptake, autotrophic assimilation and heterotrophic uptake were disentangled, as well as their various diel and seasonal patterns. Natural streams generally can remove more nitrate under similar environmental conditions and heterotrophic uptake becomes dominant during post-wet seasons. Such two-station monitoring provided novel insights into reach-scale nitrate uptake processes in large streams.
Long-term in-stream nitrate dynamics can also be evaluated with the application of water quality model. This is among the first time to use a data-model fusion approach to upscale the two-station methodology in large-streams with complex flow dynamics under long-term high-frequency monitoring, assessing the in-stream nitrate retention and its responses to drought disturbances from seasonal to sub-daily scale. Nitrate retention (both net uptake and net release) exhibited substantial seasonality, which also differed in the investigated normal and drought years. In the normal years, winter and early spring seasons exhibited extensive net releases, then general net uptake occurred after the annual high-flow season at later spring and early summer with autotrophic processes dominating and during later summer-autumn low-flow periods with heterotrophy-characteristics predominating. Net nitrate release occurred since late autumn until the next early spring. In the drought years, the late-autumn net releases were not so consistently persisted as in the normal years and the predominance of autotrophic processes occurred across seasons. Aforementioned comprehensive results of nitrate dynamics on stream scale facilitate the understanding of instream processes, as well as raise the importance of scientific monitoring schemes for hydrology and water quality parameters.
The Greenland Ice Sheet is the second-largest mass of ice on Earth. Being almost 2000 km long, more than 700 km wide, and more than 3 km thick at the summit, it holds enough ice to raise global sea levels by 7m if melted completely. Despite its massive size, it is particularly vulnerable to anthropogenic climate change: temperatures over the Greenland Ice Sheet have increased by more than 2.7◦C in the past 30 years, twice as much as the global mean temperature. Consequently, the ice sheet has been significantly losing mass since the 1980s and the rate of loss has increased sixfold since then. Moreover, it is one of the potential tipping elements of the Earth System, which might undergo irreversible change once a warming threshold is exceeded. This thesis aims at extending the understanding of the resilience of the Greenland Ice Sheet against global warming by analyzing processes and feedbacks relevant to its centennial to multi-millennial stability using ice sheet modeling.
One of these feedbacks, the melt-elevation-feedback is driven by the temperature rise with decreasing altitudes: As the ice sheet melts, its thickness and surface elevation decrease, exposing the ice surface to warmer air and thus increasing the melt rates even further. The glacial isostatic adjustment (GIA) can partly mitigate this melt-elevation feedback as the bedrock lifts in response to an ice load decrease, forming the negative GIA feedback. In my thesis, I show that the interaction between these two competing feedbacks can lead to qualitatively different dynamical responses of the Greenland Ice Sheet to warming – from permanent loss to incomplete recovery, depending on the feedback parameters. My research shows that the interaction of those feedbacks can initiate self-sustained oscillations of the ice volume while the climate forcing remains constant.
Furthermore, the increased surface melt changes the optical properties of the snow or ice surface, e.g. by lowering their albedo, which in turn enhances melt rates – a process known as the melt-albedo feedback. Process-based ice sheet models often neglect this melt-albedo feedback. To close this gap, I implemented a simplified version of the diurnal Energy Balance Model, a computationally efficient approach that can capture the first-order effects of the melt-albedo feedback, into the Parallel Ice Sheet Model (PISM). Using the coupled model, I show in warming experiments that the melt-albedo feedback almost doubles the ice loss until the year 2300 under the low greenhouse gas emission scenario RCP2.6, compared to simulations where the melt-albedo feedback is neglected,
and adds up to 58% additional ice loss under the high emission scenario RCP8.5. Moreover, I find that the melt-albedo feedback dominates the ice loss until 2300, compared to the melt-elevation feedback.
Another process that could influence the resilience of the Greenland Ice Sheet is the warming induced softening of the ice and the resulting increase in flow. In my thesis, I show with PISM how the uncertainty in Glen’s flow law impacts the simulated response to warming. In a flow line setup at fixed climatic mass balance, the uncertainty in flow parameters leads to a range of ice loss comparable to the range caused by different warming levels.
While I focus on fundamental processes, feedbacks, and their interactions in the first three projects of my thesis, I also explore the impact of specific climate scenarios on the sea level rise contribution of the Greenland Ice Sheet. To increase the carbon budget flexibility, some warming scenarios – while still staying within the limits of the Paris Agreement – include a temporal overshoot of global warming. I show that an overshoot by 0.4◦C increases the short-term and long-term ice loss from Greenland by several centimeters. The long-term increase is driven by the warming at high latitudes, which persists even when global warming is reversed. This leads to a substantial long-term commitment of the sea level rise contribution from the Greenland Ice Sheet.
Overall, in my thesis I show that the melt-albedo feedback is most relevant for the ice loss of the Greenland Ice Sheet on centennial timescales. In contrast, the melt-elevation feedback and its interplay with the GIA feedback become increasingly relevant on millennial timescales. All of these influence the resilience of the Greenland Ice Sheet against global warming, in the near future and on the long term.
At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO2 concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies. A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM. This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO2 concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21<sup>st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.
Water quality in river systems is of growing concern due to rising anthropogenic pressures and climate change. Mitigation efforts have been placed under the guidelines of different governance conventions during last decades (e.g., the Water Framework Directive in Europe). Despite significant improvement through relatively straightforward measures, the environmental status has likely reached a plateau. A higher spatiotemporal accuracy of catchment nitrate modeling is, therefore, needed to identify critical source areas of diffuse nutrient pollution (especially for nitrate) and to further guide implementation of spatially differentiated, cost-effective mitigation measures. On the other hand, the emerging high-frequency sensor monitoring upgrades the monitoring resolution to the time scales of biogeochemical processes and enables more flexible monitoring deployments under varying conditions. The newly available information offers new prospects in understanding nitrate spatiotemporal dynamics. Formulating such advanced process understanding into catchment models is critical for model further development and environmental status evaluation. This dissertation is targeting on a comprehensive analysis of catchment and in-stream nitrate dynamics and is aiming to derive new insights into their spatial and temporal variabilities through the new fully distributed model development and the new high-frequency data.
Firstly, a new fully distributed, process-based catchment nitrate model (the mHM-Nitrate model) is developed based on the mesoscale Hydrological Model (mHM) platform. Nitrate process descriptions are adopted from the Hydrological Predictions for the Environment (HYPE), with considerable improved implementations. With the multiscale grid-based discretization, mHM-Nitrate balances the spatial representation and the modeling complexity. The model has been thoughtfully evaluated in the Selke catchment (456 km2), central Germany, which is characterized by heterogeneous physiographic conditions. Results show that the model captures well the long-term discharge and nitrate dynamics at three nested gauging stations. Using daily nitrate-N observations, the model is also validated in capturing short-term fluctuations due to changes in runoff partitioning and spatial contribution during flooding events. By comparing the model simulations with the values reported in the literature, the model is capable of providing detailed and reliable spatial information of nitrate concentrations and fluxes. Therefore, the model can be taken as a promising tool for environmental scientists in advancing environmental modeling research, as well as for stakeholders in supporting their decision-making, especially for spatially differentiated mitigation measures.
Secondly, a parsimonious approach of regionalizing the in-stream autotrophic nitrate uptake is proposed using high-frequency data and further integrated into the new mHM-Nitrate model. The new regionalization approach considers the potential uptake rate (as a general parameter) and effects of above-canopy light and riparian shading (represented by global radiation and leaf area index data, respectively). Multi-parameter sensors have been continuously deployed in a forest upstream reach and an agricultural downstream reach of the Selke River. Using the continuous high-frequency data in both streams, daily autotrophic uptake rates (2011-2015) are calculated and used to validate the regionalization approach. The performance and spatial transferability of the approach is validated in terms of well-capturing the distinct seasonal patterns and value ranges in both forest and agricultural streams. Integrating the approach into the mHM-Nitrate model allows spatiotemporal variability of in-stream nitrate transport and uptake to be investigated throughout the river network.
Thirdly, to further assess the spatial variability of catchment nitrate dynamics, for the first time the fully distributed parameterization is investigated through sensitivity analysis. Sensitivity results show that parameters of soil denitrification, in-stream denitrification and in-stream uptake processes are the most sensitive parameters throughout the Selke catchment, while they all show high spatial variability, where hot-spots of parameter sensitivity can be explicitly identified. The Spearman rank correlation is further analyzed between sensitivity indices and multiple catchment factors. The correlation identifies that the controlling factors vary spatially, reflecting heterogeneous catchment responses in the Selke catchment. These insights are, therefore, informative in informing future parameter regionalization schemes for catchment water quality models. In addition, the spatial distributions of parameter sensitivity are also influenced by the gauging information that is being used for sensitivity evaluation. Therefore, an appropriate monitoring scheme is highly recommended to truly reflect the catchment responses.
Chemical transformations and hydraulic processes in soil and groundwater often lead to an apparent retention of nitrate in lowland catchments. Models are needed to evaluate the interaction of these processes in space and time. The objectives of this study are i) to develop a specific modelling approach by combining selected modelling tools simulating N-transport and turnover in soils and groundwater of lowland catchments, ii) to study interactions between catchment properties and nitrogen transport. Special attention was paid to potential N-loads to surface waters. The modelling approach combines various submodels for water flow and solute transport in soil and groundwater: The soil-water- and nitrogen-model mRISK-N, the groundwater flow model MODFLOW and the solute transport model RT3D. In order to investigate interactions of N-transport and catchment characteristics, the distribution and availability of reaction partners have to be taken into account. Therefore, a special reaction-module is developed, which simulates various chemical processes in groundwater, such as the degradation of organic matter by oxygen, nitrate, sulphate or pyrite oxidation by oxygen and nitrate. The model approach is applied to different simulation, focussing on specific submodels. All simulation studies are based on field data from the Schaugraben catchment, a pleistocene catchment of approximately 25 km², close to Osterburg(Altmark) in the North of Saxony-Anhalt. The following modelling studies have been carried out: i) evaluation of the soil-water- and nitrogen-model based on lysimeter data, ii) modelling of a field scale tracer experiment on nitrate transport and turnover in the groundwater as a first application of the reaction module, iii) evaluation of interactions between hydraulic and chemical aquifer properties in a two-dimensional groundwater transect, iv) modelling of distributed groundwater recharge and soil nitrogen leaching in the study area, to be used as input data for subsequent groundwater simulations, v) study of groundwater nitrate distribution and nitrate breakthrough to the surface water system in the Schaugraben catchment area and a subcatchment, using three-dimensional modelling of reactive groundwater transport. The various model applications prove the model to be capable of simulating interactions between transport, turnover and hydraulic and chemical catchment properties. The distribution of nitrate in the sediment and the resulting loads to surface waters are strongly affected by the amount of reactive substances and by the residence time within the aquifer. In the Schaugraben catchment simulations, it is found that a period of 70 years is needed to raise the average seepage concentrations of nitrate to a level corresponding to the given input situation, if no reactions are considered. Under reactive transport conditions, nitrate concentrations are reduced effectively. Simulation results show that groundwater exfiltration does not contribute considerably to the nitrate pollution of surface waters, as most nitrate entering soils and groundwater is lost by denitrification. Additional sources, such as direct inputs or tile drains have to be taken into account to explain surface water loads. The prognostic value of the models for the study site is limited by uncertainties of input data and estimation of model parameters. Nevertheless, the modelling approach is a useful aid for the identification of source and sink areas of nitrate pollution as well as the investigation of system response to management measures or landuse changes with scenario simulations. The modelling approach assists in the interpretation of observed data, as it allows to integrate local observations into a spatial and temporal framework.
This thesis presents methods, techniques and tools for developing three-dimensional representations of tactical intelligence assessments. Techniques from GIScience are combined with crime mapping methods. The range of methods applied in this study provides spatio-temporal GIS analysis as well as 3D geovisualisation and GIS programming. The work presents methods to enhance digital three-dimensional city models with application specific thematic information. This information facilitates further geovisual analysis, for instance, estimations of urban risks exposure. Specific methods and workflows are developed to facilitate the integration of spatio-temporal crime scene analysis results into 3D tactical intelligence assessments. Analysis comprises hotspot identification with kernel-density-estimation techniques (KDE), LISA-based verification of KDE hotspots as well as geospatial hotspot area characterisation and repeat victimisation analysis. To visualise the findings of such extensive geospatial analysis, three-dimensional geovirtual environments are created. Workflows are developed to integrate analysis results into these environments and to combine them with additional geospatial data. The resulting 3D visualisations allow for an efficient communication of complex findings of geospatial crime scene analysis.
In den letzten 20 Jahren sind Evaluationen Schritt für Schritt zu einem festen und gleichzeitig kontrovers diskutierten Bestandteil politischer Förderung geworden. Auf der Basis langjähriger Beobachtungen der Evaluationspraxis des Förderprogramms „Soziale Stadt“ zeigt dieses Buch zunächst, dass Evaluationstätigkeiten in Ministerien, Kommunalverwaltungen und Planungsbüros mit ganz unterschiedlichen Erwartungen, Herausforderungen, Widersprüchen und Irritationen verknüpft werden. Evaluationen werden dabei sowohl als Hoffnungsträger, als auch als Schreckgespenst gesehen. Der Autor nimmt diese Beobachtungen zum Anlass, den Umgang mit Evaluationen in politischen Organisationen kritisch zu hinterfragen und systematisch zu erklären. Reduziert auf die Frage „Wozu Evaluation?“ wird auf der Basis eines systemtheoretischen Zugangs erklärt, welche unterschiedlichen Funktionen Evaluationen in Organisationen erfüllen können. Vertiefend wird dabei auf organisationales Lernen, auf politische Steuerungslogik und auf die Notwendigkeit von Symbolisierungen eingegangen.
Ausprägungen räumlicher Identität in ehemaligen sudetendeutschen Gebieten der Tschechischen Republik
(2014)
Das tschechische Grenzgebiet ist eine der Regionen in Europa, die in der Folge des Zweiten Weltkrieges am gravierendsten von Umbrüchen in der zuvor bestehenden Bevölkerungsstruktur betroffen waren. Der erzwungenen Aussiedlung eines Großteils der ansässigen Bevölkerung folgten die Neubesiedlung durch verschiedenste Zuwanderergruppen sowie teilweise langanhaltende Fluktuationen der Einwohnerschaft. Die Stabilisierung der Bevölkerung stand sodann unter dem Zeichen der sozialistischen Gesellschafts- und Wirtschaftsordnung, die die Lebensweise und Raumwahrnehmung der neuen Einwohner nachhaltig prägte. Die Grenzöffnung von 1989, die politische Transformation sowie die Integration der Tschechischen Republik in die Europäische Union brachten neue demographische und sozioökonomische Entwicklungen mit sich. Sie schufen aber auch die Bedingungen dafür, sich neu und offen auch mit der spezifischen Geschichte des ehemaligen Sudetenlandes sowie mit dem Zustand der gegenwärtigen Gesellschaft in diesem Gebiet auseinanderzusetzen.
Im Rahmen der vorliegenden Arbeit wird anhand zweier Beispielregionen untersucht, welche Raumvorstellungen und Raumbindungen bei der heute in den ehemaligen sudetendeutschen Gebieten ansässigen Bevölkerung vorhanden sind und welche Einflüsse die unterschiedlichen raumstrukturellen Bedingungen darauf ausüben. Besonderes Augenmerk wird auf die soziale Komponente der Ausprägung räumlicher Identität gelegt, das heißt auf die Rolle von Bedeutungszuweisungen gegenüber Raumelementen im Rahmen sozialer Kommunikation und Interaktion. Dies erscheint von besonderer Relevanz in einem Raum, der sich durch eine gewisse Heterogenität seiner Einwohnerschaft hinsichtlich ihres ethnischen, kulturellen beziehungsweise biographischen Hintergrundes auszeichnet. Schließlich wird ermittelt, welche Impulse unter Umständen von einer ausgeprägten räumlichen Identität für die Entwicklung des Raumes ausgehen.
Das Schulfach Geographie war in der DDR eines der Fächer, das sehr stark mit politischen Themen im Sinne des Marxismus-Leninismus bestückt war. Ein anderer Aspekt sind die sozialistischen Erziehungsziele, die in der Schulbildung der DDR hoch im Kurs standen. Im Fokus stand diesbezüglich die Erziehung der Kinder zu sozialistischen Persönlichkeiten. Die Arbeit versucht einen klaren Blick auf diesen Umstand zu werfen, um zu erfahren, was da von den Lehrkräften gefordert wurde und wie es in der Schule umzusetzen war.
Durch den Fall der Mauer war natürlich auch eine Umstrukturierung des Bildungssystems im Osten unausweichlich. Hier will die Arbeit Einblicke geben, wie die Geographielehrkräfte diese Transformation mitgetragen und umgesetzt haben. Welche Wesenszüge aus der Sozialisierung in der DDR haben sich bei der Gestaltung des Unterrichtes und dessen Ausrichtung auf die neuen Erziehungsziele erhalten?
Hierzu wurden Geographielehrkräfte befragt, die sowohl in der DDR als auch im geeinten Deutschland unterrichtet haben. Die Fragen bezogen sich in erster Linie auf die Art und Weise des Unterrichtens vor, während und nach der Wende und der daraus entstandenen Systemtransformation.
Die Befragungen kommen zu dem Ergebnis, dass sich der Geographieunterricht in der DDR thematisch von dem in der BRD nicht sonderlich unterschied. Von daher bedurfte es keiner umfangreichen inhaltlichen Veränderung des Geographieunterrichts. Schon zu DDR-Zeiten wurden durch die Lehrkräfte offenbar eigenmächtig ideologiefreie physisch-geographische Themen oft ausgedehnt, um die Ideologie des Faches zu reduzieren. So fiel den meisten eine Anpassung ihres Unterrichts an das westdeutsche System relativ leicht. Die humanistisch geprägte Werteerziehung des DDR-Bildungssystems wurde unter Ausklammerung des sozialistischen Aspektes ebenso fortgeführt, da es auch hier viele Parallelen zum westdeutschen System gegeben hat. Deutlich wird eine Charakterisierung des Faches als Naturwissenschaft von Seiten der ostdeutschen Lehrkräfte, obwohl das Fach an den Schulen den Gesellschaftswissenschaften zugeordnet wird und auch in der DDR eine starke wirtschaftsgeographische Ausrichtung hatte.
Von der Verantwortung sozialistische Persönlichkeiten zu erziehen, wurden die Lehrkräfte mit dem Ende der DDR entbunden und die in dieser Arbeit aufgeführten Interviewauszüge lassen keinen Zweifel daran, dass es dem Großteil der Befragten darum nicht leidtat, sie sich aber bis heute an der Werteorientierung aus DDR-Zeiten orientieren.
Calibration of the global hydrological model WGHM with water mass variations from GRACE gravity data
(2010)
Since the start-up of the GRACE (Gravity Recovery And Climate Experiment) mission in 2002 time dependent global maps of the Earth's gravity field are available to study geophysical and climatologically-driven mass redistributions on the Earth's surface. In particular, GRACE observations of total water storage changes (TWSV) provide a comprehensive data set for analysing the water cycle on large scales. Therefore they are invaluable for validation and calibration of large-scale hydrological models as the WaterGAP Global Hydrology Model (WGHM) which simulates the continental water cycle including its most important components, such as soil, snow, canopy, surface- and groundwater. Hitherto, WGHM exhibits significant differences to GRACE, especially for the seasonal amplitude of TWSV. The need for a validation of hydrological models is further highlighted by large differences between several global models, e.g. WGHM, the Global Land Data Assimilation System (GLDAS) and the Land Dynamics model (LaD). For this purpose, GRACE links geodetic and hydrological research aspects. This link demands the development of adequate data integration methods on both sides, forming the main objectives of this work. They include the derivation of accurate GRACE-based water storage changes, the development of strategies to integrate GRACE data into a global hydrological model as well as a calibration method, followed by the re-calibration of WGHM in order to analyse process and model responses. To achieve these aims, GRACE filter tools for the derivation of regionally averaged TWSV were evaluated for specific river basins. Here, a decorrelation filter using GRACE orbits for its design is most efficient among the tested methods. Consistency in data and equal spatial resolution between observed and simulated TWSV were realised by the inclusion of all most important hydrological processes and an equal filtering of both data sets. Appropriate calibration parameters were derived by a WGHM sensitivity analysis against TWSV. Finally, a multi-objective calibration framework was developed to constrain model predictions by both river discharge and GRACE TWSV, realised with a respective evolutionary method, the ε-Non-dominated-Sorting-Genetic-Algorithm-II (ε-NSGAII). Model calibration was done for the 28 largest river basins worldwide and for most of them improved simulation results were achieved with regard to both objectives. From the multi-objective approach more reliable and consistent simulations of TWSV within the continental water cycle were gained and possible model structure errors or mis-modelled processes for specific river basins detected. For tropical regions as such, the seasonal amplitude of water mass variations has increased. The findings lead to an improved understanding of hydrological processes and their representation in the global model. Finally, the robustness of the results is analysed with respect to GRACE and runoff measurement errors. As a main conclusion obtained from the results, not only soil water and snow storage but also groundwater and surface water storage have to be included in the comparison of the modelled and GRACE-derived total water budged data. Regarding model calibration, the regional varying distribution of parameter sensitivity suggests to tune only parameter of important processes within each region. Furthermore, observations of single storage components beside runoff are necessary to improve signal amplitudes and timing of simulated TWSV as well as to evaluate them with higher accuracy. The results of this work highlight the valuable nature of GRACE data when merged into large-scale hydrological modelling and depict methods to improve large-scale hydrological models.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on Cross Recurrence Plots and Recurrence Quantification Analysis which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multi-dimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to Cross Recurrence Plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
Largescale patterns of global land use change are very frequently accompanied by natural habitat loss. To assess the consequences of habitat loss for the remaining natural and semi-natural biotopes, inclusion of cumulative effects at the landscape level is required. The interdisciplinary concept of vulnerability constitutes an appropriate assessment framework at the landscape level, though with few examples of its application for ecological assessments. A comprehensive biotope vulnerability analysis allows identification of areas most affected by landscape change and at the same time with the lowest chances of regeneration.
To this end, a series of ecological indicators were reviewed and developed. They measured spatial attributes of individual biotopes as well as some ecological and conservation characteristics of the respective resident species community. The final vulnerability index combined seven largely independent indicators, which covered exposure, sensitivity and adaptive capacity of biotopes to landscape changes. Results for biotope vulnerability were provided at the regional level. This seems to be an appropriate extent with relevance for spatial planning and designing the distribution of nature reserves.
Using the vulnerability scores calculated for the German federal state of Brandenburg, hot spots and clusters within and across the distinguished types of biotopes were analysed. Biotope types with high dependence on water availability, as well as biotopes of the open landscape containing woody plants (e.g., orchard meadows) are particularly vulnerable to landscape changes. In contrast, the majority of forest biotopes appear to be less vulnerable. Despite the appeal of such generalised statements for some biotope types, the distribution of values suggests that conservation measures for the majority of biotopes should be designed specifically for individual sites. Taken together, size, shape and spatial context of individual biotopes often had a dominant influence on the vulnerability score.
The implementation of biotope vulnerability analysis at the regional level indicated that large biotope datasets can be evaluated with high level of detail using geoinformatics. Drawing on previous work in landscape spatial analysis, the reproducible approach relies on transparent calculations of quantitative and qualitative indicators. At the same time, it provides a synoptic overview and information on the individual biotopes. It is expected to be most useful for nature conservation in combination with an understanding of population, species, and community attributes known for specific sites. The biotope vulnerability analysis facilitates a foresighted assessment of different land uses, aiding in identifying options to slow habitat loss to sustainable levels. It can also be incorporated into planning of restoration measures, guiding efforts to remedy ecological damage. Restoration of any specific site could yield synergies with the conservation objectives of other sites, through enhancing the habitat network or buffering against future landscape change.
Biotope vulnerability analysis could be developed in line with other important ecological concepts, such as resilience and adaptability, further extending the broad thematic scope of the vulnerability concept. Vulnerability can increasingly serve as a common framework for the interdisciplinary research necessary to solve major societal challenges.
Energy is at the heart of the climate crisis—but also at the heart of any efforts for climate change mitigation. Energy consumption is namely responsible for approximately three quarters of global anthropogenic greenhouse gas (GHG) emissions. Therefore, central to any serious plans to stave off a climate catastrophe is a major transformation of the world's energy system, which would move society away from fossil fuels and towards a net-zero energy future. Considering that fossil fuels are also a major source of air pollutant emissions, the energy transition has important implications for air quality as well, and thus also for human and environmental health. Both Europe and Germany have set the goal of becoming GHG neutral by 2050, and moreover have demonstrated their deep commitment to a comprehensive energy transition. Two of the most significant developments in energy policy over the past decade have been the interest in expansion of shale gas and hydrogen, which accordingly have garnered great interest and debate among public, private and political actors.
In this context, sound scientific information can play an important role by informing stakeholder dialogue and future research investments, and by supporting evidence-based decision-making. This thesis examines anticipated environmental impacts from possible, relevant changes in the European energy system, in order to impart valuable insight and fill critical gaps in knowledge. Specifically, it investigates possible future shale gas development in Germany and the United Kingdom (UK), as well as a hypothetical, complete transition to hydrogen mobility in Germany. Moreover, it assesses the impacts on GHG and air pollutant emissions, and on tropospheric ozone (O3) air quality. The analysis is facilitated by constructing emission scenarios and performing air quality modeling via the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The work of this thesis is presented in three research papers.
The first paper finds that methane (CH4) leakage rates from upstream shale gas development in Germany and the UK would range between 0.35% and 1.36% in a realistic, business-as-usual case, while they would be significantly lower - between 0.08% and 0.15% - in an optimistic, strict regulation and high compliance case, thus demonstrating the value and potential of measures to substantially reduce emissions. Yet, while the optimistic case is technically feasible, it is unlikely that the practices and technologies assumed would be applied and accomplished on a systematic, regular basis, owing to economics and limited monitoring resources. The realistic CH4 leakage rates estimated in this study are comparable to values reported by studies carried out in the US and elsewhere. In contrast, the optimistic rates are similar to official CH4 leakage data from upstream gas production in Germany and in the UK. Considering that there is a lack of systematic, transparent and independent reports supporting the official values, this study further highlights the need for more research efforts in this direction. Compared with national energy sector emissions, this study suggests that shale gas emissions of volatile organic compounds (VOCs) could be significant, though relatively insignificant for other air pollutants. Similar to CH4, measures could be effective for reducing VOCs emissions.
The second paper shows that VOC and nitrogen oxides (NOx) emissions from a future shale gas industry in Germany and the UK have potentially harmful consequences for European O3 air quality on both the local and regional scale. The results indicate a peak increase in maximum daily 8-hour average O3 (MDA8) ranging from 3.7 µg m-3 to 28.3 µg m-3. Findings suggest that shale gas activities could result in additional exceedances of MDA8 at a substantial percentage of regulatory measurement stations both locally and in neighboring and distant countries, with up to circa one third of stations in the UK and one fifth of stations in Germany experiencing additional exceedances. Moreover, the results reveal that the shale gas impact on the cumulative health-related metric SOMO35 (annual Sum of Ozone Means Over 35 ppb) could be substantial, with a maximum increase of circa 28%. Overall, the findings suggest that shale gas VOC emissions could play a critical role in O3 enhancement, while NOx emissions would contribute to a lesser extent. Thus, the results indicate that stringent regulation of VOC emissions would be important in the event of future European shale gas development to minimize deleterious health outcomes.
The third paper demonstrates that a hypothetical, complete transition of the German vehicle fleet to hydrogen fuel cell technology could contribute substantially to Germany's climate and air quality goals. The results indicate that if the hydrogen were to be produced via renewable-powered water electrolysis (green hydrogen), German carbon dioxide equivalent (CO2eq) emissions would decrease by 179 MtCO2eq annually, though if electrolysis were powered by the current electricity mix, emissions would instead increase by 95 MtCO2eq annually. The findings generally reveal a notable anticipated decrease in German energy emissions of regulated air pollutants. The results suggest that vehicular hydrogen demand is 1000 PJ annually, which would require between 446 TWh and 525 TWh for electrolysis, hydrogen transport and storage. When only the heavy duty vehicle segment (HDVs) is shifted to green hydrogen, the results of this thesis show that vehicular hydrogen demand drops to 371 PJ, while a deep emissions cut is still realized (-57 MtCO2eq), suggesting that HDVs are a low-hanging fruit for contributing to decarbonization of the German road transport sector with hydrogen energy.
This thesis aims to quantify the human impact on the natural resource water at the landscape scale. The drivers in the federal state of Brandenburg (Germany), the area under investigation, are land-use changes induced by policy decisions at European and federal state level. The water resources of the federal state are particularly sensitive to changes in land-use due to low precipitation rates in the summer combined with sandy soils and high evapotranspiration rates. Key elements in landscape hydrology are forests because of their unique capacity to transport water from the soil to the atmosphere. Given these circumstances, decisions made at any level of administration that may have effects on the forest sector in the state are critical in relation to the water cycle. It is therefore essential to evaluate any decision that may change forest area and structure in such a sensitive region. Thus, as a first step, it was necessary to develop and implement a model able to simulate possible interactions and feedbacks between forested surfaces and the hydrological cycle at the landscape scale. The result is a model for simulating the hydrological properties of forest stands based on a robust computation of the temporal and spatial LAI (leaf area index) dynamics. The approach allows the simulation of all relevant hydrological processes with a low parameter demand. It includes the interception of precipitation and transpiration of forest stands with and without groundwater in the rooting zone. The model also considers phenology, biomass allocation, as well as mortality and simple management practices. It has been implemented as a module in the eco-hydrological model SWIM (Soil and Water Integrated Model). This model has been tested in two pre-studies to verify the applicability of its hydrological process description for the hydrological conditions typical for the state. The newly implemented forest module has been tested for Scots Pine (Pinus sylvestris) and in parts for Common Oak (Quercus robur and Q. petraea) in Brandenburg. For Scots Pine the results demonstrate a good simulation of annual biomass increase and LAI in addition to the satisfactory simulation of litter production. A comparison of the simulated and measured data of the May sprout for Scots pine and leaf unfolding for Oak, as well as the evaluation against daily transpiration measurements for Scots Pine, does support the applicability of the approach. The interception of precipitation has also been simulated and compared with weekly observed data for a Scots Pine stand which displays satisfactory results in both the vegetation periods and annual sums. After the development and testing phase, the model is used to analyse the effects of two scenarios. The first scenario is an increase in forest area on abandoned agricultural land that is triggered by a decrease in European agricultural production support. The second one is a shift in species composition from predominant Scots Pine to Common Oak that is based on decisions of the regional forestry authority to support a more natural species composition. The scenario effects are modelled for the federal state of Brandenburg on a 50m grid utilising spatially explicit land-use patterns. The results, for the first scenario, suggest a negative impact of an increase in forest area (9.4% total state area) on the regional water balance, causing an increase in mean long-term annual evapotranspiration of 3.7% at 100% afforestation when compared to no afforestation. The relatively small annual change conceals a much more pronounced seasonal effect of a mean long-term evapotranspiration increase by 25.1% in the spring causing a pronounced reduction in groundwater recharge and runoff. The reduction causes a lag effect that aggravates the scarcity of water resources in the summer. In contrast, in the second scenario, a change in species composition in existing forests (29.2% total state area) from predominantly Scots Pine to Common Oak decreases the long-term annual mean evapotranspiration by 3.4%, accompanied by a much weaker, but apparent, seasonal pattern. Both scenarios exhibit a high spatial heterogeneity because of the distinct natural conditions in the different regions of the state. Areas with groundwater levels near the surface are particularly sensitive to changes in forest area and regions with relatively high proportion of forest respond strongly to the change in species composition. In both cases this regional response is masked by a smaller linear mean effect for the total state area. Two critical sources of uncertainty in the model results have been investigated. The first one originates from the model calibration parameters estimated in the pre-study for lowland regions, such as the federal state. The combined effect of the parameters, when changed within their physical meaningful limits, unveils an overestimation of the mean water balance by 1.6%. However, the distribution has a wide spread with 14.7% for the 90th percentile and -9.9% for the 10th percentile. The second source of uncertainty emerges from the parameterisation of the forest module. The analysis exhibits a standard deviation of 0.6 % over a ten year period in the mean of the simulated evapotranspiration as a result of variance in the key forest parameters. The analysis suggests that the combined uncertainty in the model results is dominated by the uncertainties of calibration parameters. Therefore, the effect of the first scenario might be underestimated because the calculated increase in evapotranspiration is too small. This may lead to an overestimation of the water balance towards runoff and groundwater recharge. The opposite can be assumed for the second scenario in which the decrease in evapotranspiration might be overestimated.
Bank filtration is an effective water treatment technique and is widely adopted in Europe along major rivers. It is the process where surface water penetrates the riverbed, flows through the aquifer, and then is extracted by near-bank production wells. By flowing in the subsurface flow passage, the water quality can be improved by a series of beneficial processes. Long-term riverbank filtration also produces colmation layers on the riverbed. The colmation layer may act as a bioactive zone that is governed by biochemical and physical processes owing to its enrichment of microbes and organic matter. Low permeability may strongly limit the surface water infiltration and further lead to a decreasing recoverable ratio of production wells.The removal of the colmation layer is therefore a trade-off between the treatment capacity and treatment efficiency. The goal of this Ph.D. thesis is to focus on the temporal and spatial change of the water quality and quantity along the flow path of a hydrogeological heterogeneous riverbank filtration site adjacent to an artificial-reconstructed (bottom excavation and bank reconstruction) canal in Potsdam, Germany.
To quantify the change of the infiltration rate, travel time distribution, and the thermal field brought by the canal reconstruction, a three-dimensional flow and heat transport model was created. This model has two scenarios, 1) ‘with’ canal reconstruction, and 2) ‘without’ canal reconstruction. Overall, the model calibration results of both water heads and temperatures matched those observed in the field study. In comparison to the model without reconstruction, the reconstruction model led to more water being infiltrated into the aquifer on that section, on average 521 m3/d, which corresponded to around 9% of the total pumping rate. Subsurface travel-time distribution substantially shifted towards shorter travel times. Flow paths with travel times <200 days increased by ~10% and those with <300 days by 15%. Furthermore, the thermal distribution in the aquifer showed that the seasonal variation in the scenario with reconstruction reaches deeper and laterally propagates further.
By scatter plotting of δ18O versus δ 2H, the infiltrated river water could be differentiated from water flowing in the deep aquifer, which may contain remnant landside groundwater from further north. In contrast, the increase of river water contribution due to decolmation could be shown by piper plot. Geological heterogeneity caused a substantial spatial difference in redox zonation among different flow paths, both horizontally and vertically. Using the Wilcoxon rank test, the reconstruction changed the redox potential differently in observation wells. However, taking the small absolute concentration level, the change is also relatively minor. The treatment efficiency for both organic matter and inorganic matter is consistent after the reconstruction, except for ammonium. The inconsistent results for ammonium could be explained by changes in the Cation Exchange Capacity (CEC) in the newly paved riverbed. Because the bed is new, it was not yet capable of keeping the newly produced ammonium by sorption and further led to the breakthrough of the ammonium plume. By estimation, the peak of the ammonium plume would reach the most distant observation well before February 2024, while the peaking concentration could be further dampened by sorption and diluted by the afterward low ammonium flow. The consistent DOC and SUVA level suggests that there was no clear preference for the organic matter removal along the flow path.
Zwischen 1990 und 1994 wurden rund 1000 Liegenschaften, die in der ehemaligen DDR von der Sowjetarmee und der NVA für militärische Übungen genutzt wurden, an Bund und Länder übergeben. Die größten Truppenübungsplätze liegen in Brandenburg und sind heute teilweise in Großschutzgebiete integriert, andere Plätze werden von der Bundeswehr weiterhin aktiv genutzt. Aufgrund des militärischen Betriebs sind die Böden dieser Truppenübungsplätze oft durch Blindgänger, Munitionsreste, Treibstoff- und Schmierölreste bis hin zu chemischen Kampfstoffen belastet. Allerdings existieren auf fast allen Liegenschaften neben diesen durch Munition und militärische Übungen belasteten Bereichen auch naturschutzfachlich wertvolle Flächen; gerade in den Offenlandbereichen kann dies durchaus mit einer Belastung durch Kampfmittel einhergehen. Charakteristisch für diese offenen Flächen, zu denen u.a. Zwergstrauchheiden, Trockenrasen, wüstenähnliche Sandflächen und andere nährstoffarme baumlose Lebensräume gehören, sind Großflächigkeit, Abgeschiedenheit sowie ihre besondere Nutzung und Bewirtschaftung, d.h. die Abwesenheit von land- und forstwirtschaftlichem Betrieb sowie von Siedlungsflächen. Diese Charakteristik war die Grundlage für die Entwicklung einer speziell angepassten Flora und Fauna. Nach Beendigung des Militärbetriebs setzte dann in weiten Teilen eine großflächige Sukzession – die allmähliche Veränderung der Zusammensetzung von Pflanzen- und Tiergesellschaften – ein, die diese offenen Bereiche teilweise bereits in Wald verwandelte und somit verschwinden ließ. Dies wiederum führte zum Verlust der an diese Offenlandflächen gebundenen Tier- und Pflanzenarten. Zur Erhaltung, Gestaltung und Entwicklung dieser offenen Flächen wurden daher von einer interdisziplinären Gruppe von Naturwissenschaftlern verschiedene Methoden und Konzepte auf ihre jeweilige Wirksamkeit untersucht. So konnten schließlich die für die jeweiligen Standortbedingungen geeigneten Maßnahmen eingeleitet werden. Voraussetzung für die Einleitung der Maßnahmen sind zum einen Kenntnisse zu diesen jeweiligen Standortbedingungen, d.h. zum Ist-Zustand, sowie zur Entwicklung der Flächen, d.h. zur Dynamik. So kann eine Abschätzung über die zukünftige Flächenentwicklung getroffen werden, damit ein effizienter Maßnahmeneinsatz stattfinden kann. Geoinformationssysteme (GIS) spielen dabei eine entscheidende Rolle zur digitalen Dokumentation der Biotop- und Nutzungstypen, da sie die Möglichkeit bieten, raum- und zeitbezogene Geometrie- und Sachdaten in großen Mengen zu verarbeiten. Daher wurde ein fachspezifisches GIS für Truppenübungsplätze entwickelt und implementiert. Die Aufgaben umfassten die Konzeption der Datenbank und des Objektmodells sowie fachspezifischer Modellierungs-, Analyse- und Präsentationsfunktionen. Für die Integration von Fachdaten in die GIS-Datenbank wurde zudem ein Metadatenkatalog entwickelt, der in Form eines zusätzlichen GIS-Tools verfügbar ist. Die Basisdaten für das GIS wurden aus Fernerkundungsdaten, topographischen Karten sowie Geländekartierungen gewonnen. Als Instrument für die Abschätzung der zukünftigen Entwicklung wurde das Simulationstool AST4D entwickelt, in dem sowohl die Nutzung der (Raster-)Daten des GIS als Ausgangsdaten für die Simulationen als auch die Nutzung der Simulationsergebnisse im GIS möglich ist. Zudem können die Daten in AST4D raumbezogen visualisiert werden. Das mathematische Konstrukt für das Tool war ein so genannter Zellulärer Automat, mit dem die Flächenentwicklung unter verschiedenen Voraussetzungen simuliert werden kann. So war die Bildung verschiedener Szenarien möglich, d.h. die Simulation der Flächenentwicklung mit verschiedenen (bekannten) Eingangsparametern und den daraus resultierenden unterschiedlichen (unbekannten) Endzuständen. Vor der Durchführung einer der drei in AST4D möglichen Simulationsstufen können angepasst an das jeweilige Untersuchungsgebiet benutzerspezifische Festlegungen getroffen werden.
Durch die Stilllegung der Kali-Gewinnung und -Produktion zwischen 1990 und 1993 sowie die begonnene Rekultivierung der Kali-Rückstandshalden haben sich die Salzfrachteintragsbedingungen für die Fließgwewässer im "Südharz-Kalirevier" in Thüringen zum Teil deutlich verändert. Aufgrund erheblich geringerer Salzeinträge in die Vorfluter Wipper und Bode ist es möglich geworden, zu einer ökologisch verträglichen Salzfrachtsteuerung überzugehen. Die Komplexität der zugrunde liegenden Stofftransportprozesse im Einzugsgebiet der Wipper macht es jedoch unumgänglich, den Steuerungsvorgang nicht nur durch reine Bilanzierungsvorgänge auf der betrachteten Steuerstrecke zu erfassen (so wie bisher praktiziert), sondern auch die Abflussdynamik im Fließgewässer und den Wasserhaushalt im Gebiet mit einzubeziehen. Die Ergebnisse dieser Arbeit dienen zum einen einer Vertiefung der Prozessverständnisse und der Interaktion von Wasserhaushalt, Abflussbildung sowie Stofftransport in bergbaubeeinflussten Einzugsgebieten am Beispiel der Unstrut bzw. ihrer relevanten Nebenflüsse. Zum anderen sollen sie zur Analyse und Bewertung eines Bewirtschaftungsplanes für die genannten Fließgewässer herangezogen werden können. Ziel dieser Arbeit ist die Erstellung eines prognosetauglichen Steuerungsinstrumentes, das für die Bewirtschaftung von Flusseinzugsgebieten unterschiedlicher Größe genutzt und unter den Rahmenbedingungen der bergbaubedingten salinaren Einträge effektiv zur Steuerung der anthropogenen Frachten eingesetzt werden kann. Die Quellen der anthropogen eingeleiteten Salzfracht sind vor allem die Rückstandshalden der stillgelegten Kaliwerke. Durch Niederschläge entstehen salzhaltige Haldenabwässer, die zum Teil ungesteuert über oberflächennahe Ausbreitungsvorgänge direkt in die Vorfluter gelangen, ein anderer Teil wird über die Speichereinrichtungen gefasst und gezielt abgestoßen. Durch Undichtigkeiten des Laugenstapelbeckens in Wipperdorf gelangen ebenfalls ungesteuerte Frachteinträge in die Wipper. Ein weiterer Eintragspfad ist zudem die geogene Belastung. Mit Hilfe detaillierter Angaben zu den oben genannten Eintragspfaden konnten Modellrechnungen im Zeitraum von 1992 bis 2003 durchgeführt werden. Durch die Ausarbeitung eines neuartigen Steuerungskonzeptes für das Laugenstapelbecken Wipperdorf, war es nun möglich, die gefasste Haldenlauge entsprechend der aktuellen Abflusssituation gezielt abstoßen zu können. Neben der modelltechnischen Erfassung der aktuellen hydrologischen Situation und der Vorgabe eines Chlorid-Konzentrationssteuerzieles für den Pegel Hachelbich, mussten dabei weitere Randbedingungen (Beckenkapazität, Beckenfüllstand, Mindestfüllstand, Kapazität des Ableitungskanals, usw.) berücksichtigt werden. Es zeigte sich, dass unter Anwendung des Steuerungskonzeptes die Schwankungsbreite der Chloridkonzentration insgesamt gesehen deutlich verringert werden konnte. Die Überschreitungshäufigkeiten bezüglich eines Grenzwertes von 2 g Chlorid/l am Pegel Hachelbich fielen deutlich, und auch die maximale Dauer einer solchen Periode konnte stark verkürzt werden. Kritische Situationen bei der modelltechnischen Frachtzusteuerung traten nur dann auf, wenn Niedrigwasserverhältnisse durch die Simulationsberechnungen noch unterschätzt wurden. Dies hatte deutliche Überschreitungen der Zielvorgaben für den Pegel Hachelbich zur Folge. Mit Hilfe des Steuerungsalgorithmus konnten desweiteren auch Szenarienberechnungen durchgeführt werden, um die Auswirkungen zukünftig zu erwartender Salzfrachten näher spezifizieren zu können. Dabei konnte festgestellt werden, dass Abdichtungsmaßnahmen der Haldenkörper sich direkt positiv auf die Entwicklung der Konzentration in Hachelbich auswirkten. Durch zusätzlich durchgeführte Langzeitszenarien konnte darüber hinaus nachgewiesen werden, dass langfristig eine Grenzwertfestlegung auf 1,5 g Chlorid/l in Hachelbich möglich ist, und die Stapelkapazitäten dazu ausreichend bemessen sind.
Ziel dieser Arbeit war es, die Stickstoff- und Phosphorprozesse im nordostdeutschen Tiefland detailliert zu untersuchen und Handlungsoptionen hinsichtlich der Landnutzung zur nachhaltigen Steuerung der Stickstoff- und Phosphoreinträge in die Fließgewässer aufzuzeigen. Als Grundvoraussetzung für die Modellierung des Nährstoffhaushaltes mussten zunächst die hydrologischen Prozesse und die Abflüsse für die Einzugsgebiete validiert werden. Dafür wurde in dieser Arbeit das ökohydrologische Modell SWIM verwendet. Die Abflussmodellierung umfasste den Zeitraum 1991 - 2000. Die Ergebnisse dazu zeigen, dass SWIM in der Lage war, die hydrologischen Prozesse in den Untersuchungsgebieten adäquat wiederzugeben. Auf der Grundlage der Modellierung des Wasserhaushaltes wurden mit SWIM die Stoffumsatzprozesse für den Zeitraum 1996 - 2000 simuliert. Um dabei besonders das Prozessgeschehen im Tiefland zu berücksichtigen, war die Erweiterung von SWIM um einen Ammonium-Pool mit dessen Umsatzprozessen erforderlich. Außerdem wurde der Prozess der Nährstoffversickerung so ergänzt, dass neben Nitrat auch Ammonium und Phosphat durch das gesamte Bodenprofil verlagert und über die Abflusskomponenten zum Gebietsauslass transportiert werden können. Mit diesen Modellerweiterungen konnten die Stickstoff und Phosphorprozesse in den Untersuchungsgebieten gut abgebildet werden. Mit dem so validierten Modell wurden weitere Anwendungen ermöglicht. Nährstoffsimulationen für den Zeitraum 1981 bis 2000 dienten der Untersuchung des abnehmenden Trends in den Nährstoffkonzentrationen der Nuthe. Die Untersuchungsergebnisse lassen deutlich erkennen, dass sich die Konzentrationen nach 1990 hauptsächlich auf Grund der Reduzierung der Einträge aus punktförmigen Quellen und Rieselfeldern verringert haben. Weitere Modellrechnungen zur Herkunft der Nährstoffe haben ergeben, dass Nitrat überwiegend aus diffusen Quellen, Ammonium und Phosphat dagegen aus punktförmigen Quellen stammen. Als besonders sensitiv auf die Modellergebnisse haben sich die Parameter zu Landnutzung und -management und die Durchwurzelungstiefe der Pflanzen herausgestellt. Abschließend wurden verschiedene Landnutzungsszenarien angewendet. Die Ergebnisse zu den Szenariorechnungen zeigen, dass fast alle vorgegebenen Landnutzungsszenarien zu einer Verringerung der Stickstoff- bzw. Phosphoremissionen führten. Die Anwendung von Szenarien, die alle relevanten Zielvorgaben und Empfehlungen zum Ressourcenschutz berücksichtigen, zeigen die größten Veränderungen.
River reaches protected by dikes exhibit high damage potential due to strong value accumulation in the hinterland areas. While providing an efficient protection against low magnitude flood events, dikes may fail under the load of extreme water levels and long flood durations. Hazard and risk assessments for river reaches protected by dikes have not adequately considered the fluvial inundation processes up to now. Particularly, the processes of dike failures and their influence on the hinterland inundation and flood wave propagation lack comprehensive consideration. This study focuses on the development and application of a new modelling system which allows a comprehensive flood hazard assessment along diked river reaches under consideration of dike failures. The proposed Inundation Hazard Assessment Model (IHAM) represents a hybrid probabilistic-deterministic model. It comprises three models interactively coupled at runtime. These are: (1) 1D unsteady hydrodynamic model of river channel and floodplain flow between dikes, (2) probabilistic dike breach model which determines possible dike breach locations, breach widths and breach outflow discharges, and (3) 2D raster-based diffusion wave storage cell model of the hinterland areas behind the dikes. Due to the unsteady nature of the 1D and 2D coupled models, the dependence between hydraulic load at various locations along the reach is explicitly considered. The probabilistic dike breach model describes dike failures due to three failure mechanisms: overtopping, piping and slope instability caused by the seepage flow through the dike core (micro-instability). The 2D storage cell model driven by the breach outflow boundary conditions computes an extended spectrum of flood intensity indicators such as water depth, flow velocity, impulse, inundation duration and rate of water rise. IHAM is embedded in a Monte Carlo simulation in order to account for the natural variability of the flood generation processes reflected in the form of input hydrographs and for the randomness of dike failures given by breach locations, times and widths. The model was developed and tested on a ca. 91 km heavily diked river reach on the German part of the Elbe River between gauges Torgau and Vockerode. The reach is characterised by low slope and fairly flat extended hinterland areas. The scenario calculations for the developed synthetic input hydrographs for the main river and tributary were carried out for floods with return periods of T = 100, 200, 500, 1000 a. Based on the modelling results, probabilistic dike hazard maps could be generated that indicate the failure probability of each discretised dike section for every scenario magnitude. In the disaggregated display mode, the dike hazard maps indicate the failure probabilities for each considered breach mechanism. Besides the binary inundation patterns that indicate the probability of raster cells being inundated, IHAM generates probabilistic flood hazard maps. These maps display spatial patterns of the considered flood intensity indicators and their associated return periods. Finally, scenarios of polder deployment for the extreme floods with T = 200, 500, 1000 were simulated with IHAM. The developed IHAM simulation system represents a new scientific tool for studying fluvial inundation dynamics under extreme conditions incorporating effects of technical flood protection measures. With its major outputs in form of novel probabilistic inundation and dike hazard maps, the IHAM system has a high practical value for decision support in flood management.
The Himalayas are a region that is most dependent, but also frequently prone to hazards from changing meltwater resources. This mountain belt hosts the highest mountain peaks on earth, has the largest reserve of ice outside the polar regions, and is home to a rapidly growing population in recent decades. One source of hazard has attracted scientific research in particular in the past two decades: glacial lake outburst floods (GLOFs) occurred rarely, but mostly with fatal and catastrophic consequences for downstream communities and infrastructure. Such GLOFs can suddenly release several million cubic meters of water from naturally impounded meltwater lakes. Glacial lakes have grown in number and size by ongoing glacial mass losses in the Himalayas. Theory holds that enhanced meltwater production may increase GLOF frequency, but has never been tested so far. The key challenge to test this notion are the high altitudes of >4000 m, at which lakes occur, making field work impractical. Moreover, flood waves can attenuate rapidly in mountain channels downstream, so that many GLOFs have likely gone unnoticed in past decades. Our knowledge on GLOFs is hence likely biased towards larger, destructive cases, which challenges a detailed quantification of their frequency and their response to atmospheric warming. Robustly quantifying the magnitude and frequency of GLOFs is essential for risk assessment and management along mountain rivers, not least to implement their return periods in building design codes.
Motivated by this limited knowledge of GLOF frequency and hazard, I developed an algorithm that efficiently detects GLOFs from satellite images. In essence, this algorithm classifies land cover in 30 years (~1988–2017) of continuously recorded Landsat images over the Himalayas, and calculates likelihoods for rapidly shrinking water bodies in the stack of land cover images. I visually assessed such detected tell-tale sites for sediment fans in the river channel downstream, a second key diagnostic of GLOFs. Rigorous tests and validation with known cases from roughly 10% of the Himalayas suggested that this algorithm is robust against frequent image noise, and hence capable to identify previously unknown GLOFs. Extending the search radius to the entire Himalayan mountain range revealed some 22 newly detected GLOFs. I thus more than doubled the existing GLOF count from 16 previously known cases since 1988, and found a dominant cluster of GLOFs in the Central and Eastern Himalayas (Bhutan and Eastern Nepal), compared to the rarer affected ranges in the North. Yet, the total of 38 GLOFs showed no change in the annual frequency, so that the activity of GLOFs per unit glacial lake area has decreased in the past 30 years. I discussed possible drivers for this finding, but left a further attribution to distinct GLOF-triggering mechanisms open to future research.
This updated GLOF frequency was the key input for assessing GLOF hazard for the entire Himalayan mountain belt and several subregions. I used standard definitions in flood hydrology, describing hazard as the annual exceedance probability of a given flood peak discharge [m3 s-1] or larger at the breach location. I coupled the empirical frequency of GLOFs per region to simulations of physically plausible peak discharges from all existing ~5,000 lakes in the Himalayas. Using an extreme-value model, I could hence calculate flood return periods. I found that the contemporary 100-year GLOF discharge (the flood level that is reached or exceeded on average once in 100 years) is 20,600+2,200/–2,300 m3 s-1 for the entire Himalayas. Given the spatial and temporal distribution of historic GLOFs, contemporary GLOF hazard is highest in the Eastern Himalayas, and lower for regions with rarer GLOF abundance. I also calculated GLOF hazard for some 9,500 overdeepenings, which could expose and fill with water, if all Himalayan glaciers have melted eventually. Assuming that the current GLOF rate remains unchanged, the 100-year GLOF discharge could double (41,700+5,500/–4,700 m3 s-1), while the regional GLOF hazard may increase largest in the Karakoram.
To conclude, these three stages–from GLOF detection, to analysing their frequency and estimating regional GLOF hazard–provide a framework for modern GLOF hazard assessment. Given the rapidly growing population, infrastructure, and hydropower projects in the Himalayas, this thesis assists in quantifying the purely climate-driven contribution to hazard and risk from GLOFs.
Large Central European flood events of the past have demonstrated that flooding can affect several river basins at the same time leading to catastrophic economic and humanitarian losses that can stretch emergency resources beyond planned levels of service. For Germany, the spatial coherence of flooding, the contributing processes and the role of trans-basin floods for a national risk assessment is largely unknown and analysis is limited by a lack of systematic data, information and knowledge on past events. This study investigates the frequency and intensity of trans-basin flood events in Germany. It evaluates the data and information basis on which knowledge about trans-basin floods can be generated in order to improve any future flood risk assessment. In particu-lar, the study assesses whether flood documentations and related reports can provide a valuable data source for understanding trans-basin floods. An adaptive algorithm was developed that systematically captures trans-basin floods using series of mean daily discharge at a large number of sites of even time series length (1952-2002). It identifies the simultaneous occurrence of flood peaks based on the exceedance of an initial threshold of a 10 year flood at one location and consecutively pools all causally related, spatially and temporally lagged peak recordings at the other locations. A weighted cumulative index was developed that accounts for the spatial extent and the individual flood magnitudes within an event and allows quantifying the overall event severity. The parameters of the method were tested in a sensitivity analysis. An intensive study on sources and ways of information dissemination of flood-relevant publications in Germany was conducted. Based on the method of systematic reviews a strategic search approach was developed to identify relevant documentations for each of the 40 strongest trans-basin flood events. A novel framework for assessing the quality of event specific flood reports from a user’s perspective was developed and validated by independent peers. The framework was designed to be generally applicable for any natural hazard type and assesses the quality of a document addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. The analysis of time-series of mean daily discharge resulted in the identification of 80 trans-basin flood events within the period 1952-2002 in Germany. The set is dominated by events that were recorded in the hydrological winter (64%); 36% occurred during the summer months. The occurrence of floods is characterised by a distinct clustering in time. Dividing the study period into two sub-periods, we find an increase in the percentage of winter events from 58% in the first to 70.5% in the second sub-period. Accordingly, we find a significant increase in the number of extreme trans-basin floods in the second sub-period. A large body of 186 flood relevant documentations was identified. For 87.5% of the 40 strongest trans-basin floods in Germany at least one report has been found and for the most severe floods a substantial amount of documentation could be obtained. 80% of the material can be considered grey literature (i.e. literature not controlled by commercial publishers). The results of the quality assessment show that the majority of flood event specific reports are of a good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The inclusion of this information in the process of knowledge building for flood risk assessment is recommended. Both the results as well as the data produced in this study are openly accessible and can be used for further research. The results of this study contribute to an improved spatial risk assessment in Germany. The identified set of trans-basin floods provides the basis for an assessment of the chance that flooding occurs simultaneously at a number of sites. The information obtained from flood event documentation can usefully supplement the analysis of the processes that govern flood risk.
Die automatisierte Objektidentifikation stellt ein modernes Werkzeug in den Geoinformationswissenschaften dar (BLASCHKE et al., 2012). Um bei thematischen Kartierungen untereinander vergleichbare Ergebnisse zu erzielen, sollen aus Sicht der Geoinformatik Mittel für die Objektidentifikation eingesetzt werden. Anstelle von Feldarbeit werden deshalb in der vorliegenden Arbeit multispektrale Fernerkundungsdaten als Primärdaten verwendet. Konkrete natürliche Objekte werden GIS-gestützt und automatisiert über große Flächen und Objektdichten aus Primärdaten identifiziert und charakterisiert. Im Rahmen der vorliegenden Arbeit wird eine automatisierte Prozesskette zur Objektidentifikation konzipiert. Es werden neue Ansätze und Konzepte der objektbasierten Identifikation von natürlichen isolierten terrestrischen Oberflächenformen entwickelt und implementiert. Die Prozesskette basiert auf einem Konzept, das auf einem generischen Ansatz für automatisierte Objektidentifikation aufgebaut ist. Die Prozesskette kann anhand charakteristischer quantitativer Parameter angepasst und so umgesetzt werden, womit das Konzept der Objektidentifikation modular und skalierbar wird. Die modulbasierte Architektur ermöglicht den Einsatz sowohl einzelner Module als auch ihrer Kombination und möglicher Erweiterungen. Die eingesetzte Methodik der Objektidentifikation und die daran anschließende Charakteristik der (geo)morphometrischen und morphologischen Parameter wird durch statistische Verfahren gestützt. Diese ermöglichen die Vergleichbarkeit von Objektparametern aus unterschiedlichen Stichproben. Mit Hilfe der Regressionsund Varianzanalyse werden Verhältnisse zwischen Objektparametern untersucht. Es werden funktionale Abhängigkeiten der Parameter analysiert, um die Objekte qualitativ zu beschreiben. Damit ist es möglich, automatisiert berechnete Maße und Indizes der Objekte als quantitative Daten und Informationen zu erfassen und unterschiedliche Stichproben anzuwenden. Im Rahmen dieser Arbeit bilden Thermokarstseen die Grundlage für die Entwicklungen und als Beispiel sowie Datengrundlage für den Aufbau des Algorithmus und die Analyse. Die Geovisualisierung der multivariaten natürlichen Objekte wird für die Entwicklung eines besseren Verständnisses der räumlichen Relationen der Objekte eingesetzt. Kern der Geovisualisierung ist das Verknüpfen von Visualisierungsmethoden mit kartenähnlichen Darstellungen.
Climate change is one of the greatest challenges to humanity in this century, and most noticeable consequences are expected to be impacts on the water cycle – in particular the distribution and availability of water, which is fundamental for all life on Earth. In this context, it is essential to better understand where and when water is available and what processes influence variations in water storages. While estimates of the overall terrestrial water storage (TWS) variations are available from the GRACE satellites, these represent the vertically integrated signal over all water stored in ice, snow, soil moisture, groundwater and surface water bodies. Therefore, complementary observational data and hydrological models are still required to determine the partitioning of the measured signal among different water storages and to understand the underlying processes. However, the application of large-scale observational data is limited by their specific uncertainties and the incapacity to measure certain water fluxes and storages. Hydrological models, on the other hand, vary widely in their structure and process-representation, and rarely incorporate additional observational data to minimize uncertainties that arise from their simplified representation of the complex hydrologic cycle.
In this context, this thesis aims to contribute to improving the understanding of global water storage variability by combining simple hydrological models with a variety of complementary Earth observation-based data. To this end, a model-data integration approach is developed, in which the parameters of a parsimonious hydrological model are calibrated against several observational constraints, inducing GRACE TWS, simultaneously, while taking into account each data’s specific strengths and uncertainties. This approach is used to investigate 3 specific aspects that are relevant for modelling and understanding the composition of large-scale TWS variations.
The first study focusses on Northern latitudes, where snow and cold-region processes define the hydrological cycle. While the study confirms previous findings that seasonal dynamics of TWS are dominated by the cyclic accumulation and melt of snow, it reveals that inter-annual TWS variations on the contrary, are determined by variations in liquid water storages. Additionally, it is found to be important to consider the impact of compensatory effects of spatially heterogeneous hydrological variables when aggregating the contribution of different storage components over large areas. Hence, the determinants of TWS variations are scale-dependent and underlying driving mechanism cannot be simply transferred between spatial and temporal scales. These findings are supported by the second study for the global land areas beyond the Northern latitudes as well.
This second study further identifies the considerable impact of how vegetation is represented in hydrological models on the partitioning of TWS variations. Using spatio-temporal varying fields of Earth observation-based data to parameterize vegetation activity not only significantly improves model performance, but also reduces parameter equifinality and process uncertainties. Moreover, the representation of vegetation drastically changes the contribution of different water storages to overall TWS variability, emphasizing the key role of vegetation for water allocation, especially between sub-surface and delayed water storages. However, the study also identifies parameter equifinality regarding the decay of sub-surface and delayed water storages by either evapotranspiration or runoff, and thus emphasizes the need for further constraints hereof.
The third study focuses on the role of river water storage, in particular whether it is necessary to include computationally expensive river routing for model calibration and validation against the integrated GRACE TWS. The results suggest that river routing is not required for model calibration in such a global model-data integration approach, due to the larger influence other observational constraints, and the determinability of certain model parameters and associated processes are identified as issues of greater relevance. In contrast to model calibration, considering river water storage derived from routing schemes can already significantly improve modelled TWS compared to GRACE observations, and thus should be considered for model evaluation against GRACE data.
Beyond these specific findings that contribute to improved understanding and modelling of large-scale TWS variations, this thesis demonstrates the potential of combining simple modeling approaches with diverse Earth observational data to improve model simulations, overcome inconsistencies of different observational data sets, and identify areas that require further research. These findings encourage future efforts to take advantage of the increasing number of diverse global observational data.
Studies of the role of disturbance in vegetation or ecosystems showed that disturbances are an essential and intrinsic element of ecosystems that contribute substantially to ecosystem health, to structural diversity of ecosystems and to nutrient cycling at the local as well as global level. Fire as a grassland, bush or forest fire is a special disturbance agent, since it is caused by biotic as well abiotic environmental factors. Fire affects biogeochemical cycles and plays an important role in atmospheric chemistry by releasing climate-sensitive trace gases and aerosols, and thus in the global carbon cycle by releasing approximately 3.9 Gt C p.a. through biomass burning. A combined model to describe effects and feedbacks between fire and vegetation became relevant as changes in fire regimes due to land use and land management were observed and the global dimension of biomass burnt as an important carbon flux to the atmosphere, its influence on atmospheric chemistry and climate as well as vegetation dynamics were emphasized. The existing modelling approaches would not allow these investigations. As a consequence, an optimal set of variables that best describes fire occurrence, fire spread and its effects in ecosystems had to be defined, which can simulate observed fire regimes and help to analyse interactions between fire and vegetation dynamics as well as to allude to the reasons behind changing fire regimes. Especially, dynamic links between vegetation, climate and fire processes are required to analyse dynamic feedbacks and effects of changes of single environmental factors. This led us to the point, where new fire models had to be developed that would allow the investigations, mentioned above, and could help to improve our understanding of the role of fire in global ecology. In conclusion of the thesis, one can state that moisture conditions, its persistence over time and fuel load are the important components that describe global fire pattern. If time series of a particular region are to be reproduced, specific ignition sources, fire-critical climate conditions and vegetation composition become additional determinants. Vegetation composition changes the level of fire occurrence and spread, but has limited impact on the inter-annual variability of fire. The importance to consider the full range of major fire processes and links to vegetation dynamics become apparent under climate change conditions. Increases in climate-dependent length of fire season does not automatically imply increases in biomass burnt, it can be buffered or accelerated by changes in vegetation productivity. Changes in vegetation composition as well as enhanced vegetation productivity can intensify changes in fire and lead to even more fire-related emissions. --- Anmerkung: Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2002/2003.
Permafrost, defined as ground that is frozen for at least two consecutive years, is a distinct feature of the terrestrial unglaciated Arctic. It covers approximately one quarter of the land area of the Northern Hemisphere (23,000,000 km²). Arctic landscapes, especially those underlain by permafrost, are threatened by climate warming and may degrade in different ways, including active layer deepening, thermal erosion, and development of rapid thaw features. In Siberian and Alaskan late Pleistocene ice-rich Yedoma permafrost, rapid and deep thaw processes (called thermokarst) can mobilize deep organic carbon (below 3 m depth) by surface subsidence due to loss of ground ice. Increased permafrost thaw could cause a feedback loop of global significance if its stored frozen organic carbon is reintroduced into the active carbon cycle as greenhouse gases, which accelerate warming and inducing more permafrost thaw and carbon release. To assess this concern, the major objective of the thesis was to enhance the understanding of the origin of Yedoma as well as to assess the associated organic carbon pool size and carbon quality (concerning degradability). The key research questions were:
- How did Yedoma deposits accumulate?
- How much organic carbon is stored in the Yedoma region?
- What is the susceptibility of the Yedoma region's carbon for future decomposition?
To address these three research questions, an interdisciplinary approach, including detailed field studies and sampling in Siberia and Alaska as well as methods of sedimentology, organic biogeochemistry, remote sensing, statistical analyses, and computational modeling were applied. To provide a panarctic context, this thesis additionally includes results both from a newly compiled northern circumpolar carbon database and from a model assessment of carbon fluxes in a warming Arctic.
The Yedoma samples show a homogeneous grain-size composition. All samples were poorly sorted with a multi-modal grain-size distribution, indicating various (re-) transport processes. This contradicts the popular pure loess deposition hypothesis for the origin of Yedoma permafrost. The absence of large-scale grinding processes via glaciers and ice sheets in northeast Siberian lowlands, processes which are necessary to create loess as material source, suggests the polygenetic origin of Yedoma deposits.
Based on the largest available data set of the key parameters, including organic carbon content, bulk density, ground ice content, and deposit volume (thickness and coverage) from Siberian and Alaskan study sites, this thesis further shows that deep frozen organic carbon in the Yedoma region consists of two distinct major reservoirs, Yedoma deposits and thermokarst deposits (formed in thaw-lake basins). Yedoma deposits contain ~80 Gt and thermokarst deposits ~130 Gt organic carbon, or a total of ~210 Gt. Depending on the approach used for calculating uncertainty, the range for the total Yedoma region carbon store is ±75 % and ±20 % for conservative single and multiple bootstrapping calculations, respectively. Despite the fact that these findings reduce the Yedoma region carbon pool by nearly a factor of two compared to previous estimates, this frozen organic carbon is still capable of inducing a permafrost carbon feedback to climate warming. The complete northern circumpolar permafrost region contains between 1100 and 1500 Gt organic carbon, of which ~60 % is perennially frozen and decoupled from the short-term carbon cycle.
When thawed and reintroduced into the active carbon cycle, the organic matter qualities become relevant. Furthermore, results from investigations into Yedoma and thermokarst organic matter quality studies showed that Yedoma and thermokarst organic matter exhibit no depth-dependent quality trend. This is evidence that after freezing, the ancient organic matter is preserved in a state of constant quality. The applied alkane and fatty-acid-based biomarker proxies including the carbon-preference and the higher-land-plant-fatty-acid indices show a broad range of organic matter quality and thus no significantly different qualities of the organic matter stored in thermokarst deposits compared to Yedoma deposits. This lack of quality differences shows that the organic matter biodegradability depends on different decomposition trajectories and the previous decomposition/incorporation history. Finally, the fate of the organic matter has been assessed by implementing deep carbon pools and thermokarst processes in a permafrost carbon model. Under various warming scenarios for the northern circumpolar permafrost region, model results show a carbon release from permafrost regions of up to ~140 Gt and ~310 Gt by the years 2100 and 2300, respectively. The additional warming caused by the carbon release from newly-thawed permafrost contributes 0.03 to 0.14°C by the year 2100. The model simulations predict that a further increase by the 23rd century will add 0.4°C to global mean surface air temperatures.
In conclusion, Yedoma deposit formation during the late Pleistocene was dominated by water-related (alluvial/fluvial/lacustrine) as well as aeolian processes under periglacial conditions. The circumarctic permafrost region, including the Yedoma region, contains a substantial amount of currently frozen organic carbon. The carbon of the Yedoma region is well-preserved and therefore available for decomposition after thaw. A missing quality-depth trend shows that permafrost preserves the quality of ancient organic matter. When the organic matter is mobilized by deep degradation processes, the northern permafrost region may add up to 0.4°C to the global warming by the year 2300.
On a planetary scale human populations need to adapt to both socio-economic and environmental problems amidst rapid global change. This holds true for coupled human-environment (socio-ecological) systems in rural and urban settings alike. Two examples are drylands and urban coasts. Such socio-ecological systems have a global distribution. Therefore, advancing the knowledge base for identifying socio-ecological adaptation needs with local vulnerability assessments alone is infeasible: The systems cover vast areas, while funding, time, and human resources for local assessments are limited. They are lacking in low an middle-income countries (LICs and MICs) in particular.
But places in a specific socio-ecological system are not only unique and complex – they also exhibit similarities. A global patchwork of local rural drylands vulnerability assessments of human populations to socio-ecological and environmental problems has already been reduced to a limited number of problem structures, which typically cause vulnerability. However, the question arises whether this is also possible in urban socio-ecological systems. The question also arises whether these typologies provide added value in research beyond global change. Finally, the methodology employed for drylands needs refining and standardizing to increase its uptake in the scientific community. In this dissertation, I set out to fill these three gaps in research.
The geographical focus in my dissertation is on LICs and MICs, which generally have lower capacities to adapt, and greater adaptation needs, regarding rapid global change. Using a spatially explicit indicator-based methodology, I combine geospatial and clustering methods to identify typical configurations of key factors in case studies causing vulnerability to human populations in two specific socio-ecological systems. Then I use statistical and analytical methods to interpret and appraise both the typical configurations and the global typologies they constitute.
First, I improve the indicator-based methodology and then reanalyze typical global problem structures of socio-ecological drylands vulnerability with seven indicator datasets. The reanalysis confirms the key tenets and produces a more realistic and nuanced typology of eight spatially explicit problem structures, or vulnerability profiles: Two new profiles with typically high natural resource endowment emerge, in which overpopulation has led to medium or high soil erosion. Second, I determine whether the new drylands typology and its socio-ecological vulnerability concept advance a thematically linked scientific debate in human security studies: what drives violent conflict in drylands? The typology is a much better predictor for conflict distribution and incidence in drylands than regression models typically used in peace research. Third, I analyze global problem structures typically causing vulnerability in an urban socio-ecological system - the rapidly urbanizing coastal fringe (RUCF) – with eleven indicator datasets. The RUCF also shows a robust typology, and its seven profiles show huge asymmetries in vulnerability and adaptive capacity. The fastest population increase, lowest income, most ineffective governments, most prevalent poverty, and lowest adaptive capacity are all typically stacked in two profiles in LICs. This shows that beyond local case studies tropical cyclones and/or coastal flooding are neither stalling rapid population growth, nor urban expansion, in the RUCF. I propose entry points for scaling up successful vulnerability reduction strategies in coastal cities within the same vulnerability profile.
This dissertation shows that patchworks of local vulnerability assessments can be generalized to structure global socio-ecological vulnerabilities in both rural and urban socio-ecological systems according to typical problems. In terms of climate-related extreme events in the RUCF, conflicting problem structures and means to deal with them are threatening to widen the development gap between LICs and high-income countries unless successful vulnerability reduction measures are comprehensively scaled up. The explanatory power for human security in drylands warrants further applications of the methodology beyond global environmental change research in the future. Thus, analyzing spatially explicit global typologies of socio-ecological vulnerability is a useful complement to local assessments: The typologies provide entry points for where to consider which generic measures to reduce typical problem structures – including the countless places without local assessments. This can save limited time and financial resources for adaptation under rapid global change.
The terrestrial biosphere impacts considerably on the global carbon cycle. In particular, ecosystems contribute to set off anthropogenic induced fossil fuel emissions and hence decelerate the rise of the atmospheric CO₂ concentration. However, the future net sink strength of an ecosystem will heavily depend on the response of the individual processes to a changing climate. Understanding the makeup of these processes and their interaction with the environment is, therefore, of major importance to develop long-term climate mitigation strategies. Mathematical models are used to predict the fate of carbon in the soil-plant-atmosphere system under changing environmental conditions. However, the underlying processes giving rise to the net carbon balance of an ecosystem are complex and not entirely understood at the canopy level. Therefore, carbon exchange models are characterised by considerable uncertainty rendering the model-based prediction into the future prone to error. Observations of the carbon exchange at the canopy scale can help learning about the dominant processes and hence contribute to reduce the uncertainty associated with model-based predictions. For this reason, a global network of measurement sites has been established that provides long-term observations of the CO₂ exchange between a canopy and the atmosphere along with micrometeorological conditions. These time series, however, suffer from observation uncertainty that, if not characterised, limits their use in ecosystem studies. The general objective of this work is to develop a modelling methodology that synthesises physical process understanding with the information content in canopy scale data as an attempt to overcome the limitations in both carbon exchange models and observations. Similar hybrid modelling approaches have been successfully applied for signal extraction out of noisy time series in environmental engineering. Here, simple process descriptions are used to identify relationships between the carbon exchange and environmental drivers from noisy data. The functional form of these relationships are not prescribed a priori but rather determined directly from the data, ensuring the model complexity to be commensurate with the observations. Therefore, this data-led analysis results in the identification of the processes dominating carbon exchange at the ecosystem scale as reflected in the data. The description of these processes may then lead to robust carbon exchange models that contribute to a faithful prediction of the ecosystem carbon balance. This work presents a number of studies that make use of the developed data-led modelling approach for the analysis and interpretation of net canopy CO₂ flux observations. Given the limited knowledge about the underlying real system, the evaluation of the derived models with synthetic canopy exchange data is introduced as a standard procedure prior to any real data employment. The derived data-led models prove successful in several different applications. First, the data-based nature of the presented methods makes them particularly useful for replacing missing data in the observed time series. The resulting interpolated CO₂ flux observation series can then be analysed with dynamic modelling techniques, or integrated to coarser temporal resolution series for further use e.g., in model evaluation exercises. However, the noise component in these observations interferes with deterministic flux integration in particular when long time periods are considered. Therefore, a method to characterise the uncertainties in the flux observations that uses a semi-parametric stochastic model is introduced in a second study. As a result, an (uncertain) estimate of the annual net carbon exchange of the observed ecosystem can be inferred directly from a statistically consistent integration of the noisy data. For the forest measurement sites analysed, the relative uncertainty for the annual sum did not exceed 11 percent highlighting the value of the data. Based on the same models, a disaggregation of the net CO₂ flux into carbon assimilation and respiration is presented in a third study that allows for the estimation of annual ecosystem carbon uptake and release. These two components can then be further analysed for their separate response to environmental conditions. Finally, a fourth study demonstrates how the results from data-led analyses can be turned into a simple parametric model that is able to predict the carbon exchange of forest ecosystems. Given the global network of measurements available the derived model can now be tested for generality and transferability to other biomes. In summary, this work particularly highlights the potential of the presented data-led methodologies to identify and describe dominant carbon exchange processes at the canopy level contributing to a better understanding of ecosystem functioning.
Die Hochwasserereignisse der letzten Jahre haben Mängel bei der schnellen Verfügbarkeit des klassischen Darstellungs-, Entscheidungs- und Analyseinstruments Karte offenbart. Die Erfahrungen von 1997 und 2002 verdeutlichen, dass eine homogene digitale Datengrundlage, die neben rein topographischen zusätzlich auch fachspezifische Informationen des Hochwasserschutzes enthält, für eine effektive Bekämpfung solcher Ereignisse notwendig ist. Mit den Daten des ,Amtlichen Topographisch-Kartographischen Informationssystems’ (ATKIS) liegen topographische Basisdaten in graphikfreier Form als digitales Landschaftsmodell (DLM) flächendeckend für die Bundesrepublik vor. Anhand der exemplarischen Ableitung von nutzerorientierten Kartenmodellen aus diesen graphikfreien Daten wurde deren Eignung für den besonderen Verwendungszweck im Rahmen eines Hochwasserschutz-Informationssystems überprüft. Als Anwendungsbeispiel wurde das Gebiet der Ziltendorfer Niederung, die während des Oder-Hochwassers 1997 überflutet wurde, gewählt. In Expertengesprächen wurden zunächst Inhalte identifiziert, die für einen wirksamen Hochwasserschutz Relevanz besitzen; diese Inhalte wurden anschließend analog zum ATKIS-Systemdesign strukturiert und als Objekte eines separaten Objektbereichs im digitalen Fachmodell (DFM) erfasst. Bei der Ableitung von (Bildschirm-) Karten aus den graphikfreien Daten wurden jeweils unterschiedliche Kriterien für die Basiskarte und die Fachinhalte berücksichtigt. Dabei wurden verschiedene kartographische Regeln und Gesetze mit dem Ziel der prägnanten Visualisierung und damit der eindeutigen Lesbarkeit der Karten angewendet. Beispielhaft sei hier die Schaffung einer visuellen Hierarchie zwischen Basiskarte und Fachinhalten genannt. Die besonderen Nutzungsbedingungen von Karten im Einsatzfall erfordern u.a., dass die Karten auch von Personen, die nur über geringe oder keine Erfahrung im Umgang mit Karten verfügen, schnell und einfach zu lesen sind, um so eine sichere Informationsvermittlung zu gewährleisten. Voraussetzung dafür ist einerseits die Beschränkung auf die Darstellung der wesentlichen Inhalte, andererseits die Verwendung leicht lesbarer Kartenzeichen. Aus diesem Grund wurden einheitliche Kartenzeichen zur Darstellung der Fachinhalte entwickelt, die entweder aus allgemein bekannten Symbolen, aus den im Katastrophenschutz üblicherweise verwendeten sog. taktischen Zeichen oder aus Fachzeichen des Hochwasserschutzes abgeleitet wurden. Die entwickelten Kartenmodelle wurden abschließend in qualitativen Experteninterviews in Bezug auf ihre Qualität und Verwendbarkeit im Hochwasserschutz geprüft. Die Auswertung der Interviews ergab eine insgesamt positive Beurteilung der Karten für den Einsatz in Hochwasserschutz-Informationssystemen. Damit leistet die vorliegende Arbeit einen Beitrag zur Entwicklung von (Bildschirm-) Karten zur Unterstützung bei der Entscheidungsfindung im Katastrophenmanagement.
Bilingualer Unterricht gilt als das Erfolgsmodell für den schulischen Fremdsprachenerwerb in Deutschland und die Beherrschung einer Fremdsprache in Wort und Schrift ist eine entscheidende berufsqualifizierende Kompetenz in unserer globalisierten Welt. Insbesondere die Verzahnung fachlicher und sprachlicher Inhalte im Kontext Bilingualen Unterrichts scheint gewinnbringend für den Fremdspracherwerb zu sein. Dabei ist die Diskrepanz zwischen den zumeist noch geringen fremdsprachlichen Fähigkeiten der Lernenden und den fachlichen Ansprüchen des Geographieunterrichts eine große Herausforderung für fachliches Lernen im bilingualen Sachfachunterricht. Es stellt sich die Frage, wie der Bilinguale Unterricht gestaltet sein muss, um einerseits geographische Themen fachlich komplex behandeln zu können und andererseits die Lernenden fremdsprachlich nicht zu überfordern.
Im Rahmen einer Design-Based-Research-Studie im bilingualen Geographieunterricht wurde untersucht, wie fachliches Lernen im bilingualen Geographieunterricht durch den Einsatz beider beteiligter Sprachen (Englisch/Deutsch) gefördert werden kann.
Auf Grundlage eines theoretisch fundierten Kenntnisstands zum Bilingualen Unterricht und zum Lernen mit Fachkonzepten im Geographieunterricht wurde eine Lernumgebung konzipiert, im Unterricht erprobt und weiterentwickelt, in der Strategien des Sprachwechsels zum Einsatz kommen.
Die Ergebnisse der Studie sind kontextbezogene Theorien einer zweisprachigen Didaktik für den bilingualen Geographieunterricht und Erkenntnisse zum Lernen mit Fachkonzepten im Geographieunterricht am Beispiel des geographischen Konzepts Wandel. Produkt der Studie ist eine unterrichtstaugliche Lernumgebung zum Thema Wandlungsprozesse an ausgewählten Orten für den bilingualen Geographieunterricht mit didaktischem Konzept, Unterrichtsmaterialien und -medien.
Casualties and damages from urban pluvial flooding are increasing. Triggered by short, localized, and intensive rainfall events, urban pluvial floods can occur anywhere, even in areas without a history of flooding. Urban pluvial floods have relatively small temporal and spatial scales. Although cumulative losses from urban pluvial floods are comparable, most flood risk management and mitigation strategies focus on fluvial and coastal flooding. Numerical-physical-hydrodynamic models are considered the best tool to represent the complex nature of urban pluvial floods; however, they are computationally expensive and time-consuming. These sophisticated models make large-scale analysis and operational forecasting prohibitive. Therefore, it is crucial to evaluate and benchmark the performance of other alternative methods.
The findings of this cumulative thesis are represented in three research articles. The first study evaluates two topographic-based methods to map urban pluvial flooding, fill–spill–merge (FSM) and topographic wetness index (TWI), by comparing them against a sophisticated hydrodynamic model. The FSM method identifies flood-prone areas within topographic depressions while the TWI method employs maximum likelihood estimation to calibrate a TWI threshold (τ) based on inundation maps from the 2D hydrodynamic model. The results point out that the FSM method outperforms the TWI method. The study highlights then the advantage and limitations of both methods.
Data-driven models provide a promising alternative to computationally expensive hydrodynamic models. However, the literature lacks benchmarking studies to evaluate the different models' performance, advantages and limitations. Model transferability in space is a crucial problem. Most studies focus on river flooding, likely due to the relative availability of flow and rain gauge records for training and validation. Furthermore, they consider these models as black boxes. The second study uses a flood inventory for the city of Berlin and 11 predictive features which potentially indicate an increased pluvial flooding hazard to map urban pluvial flood susceptibility using a convolutional neural network (CNN), an artificial neural network (ANN) and the benchmarking machine learning models random forest (RF) and support vector machine (SVM). I investigate the influence of spatial resolution on the implemented models, the models' transferability in space and the importance of the predictive features. The results show that all models perform well and the RF models are superior to the other models within and outside the training domain. The models developed using fine spatial resolution (2 and 5 m) could better identify flood-prone areas. Finally, the results point out that aspect is the most important predictive feature for the CNN models, and altitude is for the other models.
While flood susceptibility maps identify flood-prone areas, they do not represent flood variables such as velocity and depth which are necessary for effective flood risk management. To address this, the third study investigates data-driven models' transferability to predict urban pluvial floodwater depth and the models' ability to enhance their predictions using transfer learning techniques. It compares the performance of RF (the best-performing model in the previous study) and CNN models using 12 predictive features and output from a hydrodynamic model. The findings in the third study suggest that while CNN models tend to generalise and smooth the target function on the training dataset, RF models suffer from overfitting. Hence, RF models are superior for predictions inside the training domains but fail outside them while CNN models could control the relative loss in performance outside the training domains. Finally, the CNN models benefit more from transfer learning techniques than RF models, boosting their performance outside training domains.
In conclusion, this thesis has evaluated both topographic-based methods and data-driven models to map urban pluvial flooding. However, further studies are crucial to have methods that completely overcome the limitation of 2D hydrodynamic models.
Die effektive Erzeugung von Wissen ist eine der zentralen Herausforderungen des 21. Jahrhunderts. Informations- und Kommunikationstechnologien, wie die Neuen Medien, durchdringen alle Bereiche des täglichen Lebens. Sie ermöglichen den Zugriff auf gigantische Datenmengen, die die Grundvoraussetzung für die Generierung von Wissen darstellen, aber gleichzeitig eine Datenflut bedeuten, der wir ohnmächtig gegenüberstehen. Innerhalb der raumwissenschaftlichen Fachdisziplinen spielen die Neuen Medien für die Kommunikation von Sachinformation eine wichtige Rolle. Die internetbasierte Distribution von Karten, angereichert mit zusätzlichen Informationen in Form von Audiosequenzen oder Filmausschnitten, spiegelt diese Entwicklung wieder. Vor diesem Hintergrund erfolgt die Untersuchung der Frage, ob Neue Medien dazu genutzt werden können, raumwissenschaftliche Fachinhalte zu vermitteln. Von besonderem Interesse ist dabei die Frage, ob durch den Einsatz Neuer Medien in der Lehre ein Mehrwert für die Benutzer entsteht. Der Ausgangspunkt dieser Forschungsfrage besteht in der herausragenden Bedeutung von Visualisierung zur leicht verständlichen Darstellung komplexer Sachverhalte, sowie der entsprechenden Werkzeug- und Methodenkompetenz für die Nutzung Neuer Medien in den raumwissen-schaftlichen Disziplinen. Die Grundlage für die Entwicklung von mehrwertigen Lernangeboten ist die Betrachtung von Lernen als Kommunikationsprozess zur Konstruktion von Wissen, was bedeutet, dass der Entwickler derartiger Angebote über Möglichkeiten zur Optimierung dieses Kommunikationsprozesses verfügt. Auf dieser Basis erfolgt eine Erweiterung des in den raumwissenschaftlichen Disziplinen verwendeten Kommunikationsbegriffs um den Aspekt der Lehre von Fachinhalten. Als relevante Ansatzpunkte für die Optimierung der Kommunikation von Fachinhalten werden die didaktische und die mediale Aufbereitung identifiziert. Diese können zum einen die Motivation der Lernenden positiv beeinflussen und zum anderen durch Wirkung auf die Wahrnehmung der Lernenden zu einem vereinfachten Verständnis beitragen. Im Mittelpunkt der didaktischen Aufbereitung steht die problemorientierte Vermittlung der Inhalte, d.h. sie werden anhand konkreter Problemsituationen aus der Praxis vermittelt und gelten deshalb als besonders anschaulich und anwendungsorientiert. Bei der medialen Aufbereitung steht die Verwendung einer Kombination aus Text und Graphik/Animation im Mittelpunkt, die darauf abzielt, das Verstehen komplexer Sachverhalte zu erleichtern. Zur Überprüfung der Forschungsfrage haben Studierende raumwissenschaftlicher Studiengänge der Universität Potsdam das Lernangebot ausprobiert und anhand eines Fragebogens verschiedene Aspekte bewertet. Themenschwerpunkt dieser Evaluation waren die Akzeptanz, die Bedienbarkeit, die didak-tische und mediale Aufbereitung der Inhalte, die Auswahl und Verständlichkeit der Inhalte sowie die Praxistauglichkeit. Ein Großteil der Befragten hat dem Lernangebot einen Mehrwert gegenüber konventionellen Bildungsangeboten bescheinigt. Als Aspekte dieses Mehrwertes haben sich vor allem die Praxisnähe, die Unabhängigkeit von Zeit und Ort bei der Nutzung und die Vermittlung der Inhalte auf der Grundlage einer Kombination aus Text und interaktiven Animationen herauskristallisiert.
Die vorliegende Arbeit 'Abflußentwicklung in Teileinzugsgebieten des Rheins - Simulationen für den Ist-Zustand und für Klimaszenarien' untersucht Auswirkungen möglicher zukünftiger Klimaänderungen auf das Abflußgeschehen in ausgewählten, durch Mittelgebirge geprägten Teileinzugsgebieten des Rheins: Mosel (bis Pegel Cochem); Sieg (bis Pegel Menden 1) und Main (bis Pegel Kemmern).In einem ersten Schritt werden unter Verwendung des hydrologischen Modells HBV-D wichtige Modellprozesse entsprechend der Einzugsgebietscharakteristik parametrisiert und ein Abbild der Gebietshydrologie erzeugt, das mit Zeitreihen gemessener Tageswerte (Temperatur, Niederschlag) eine Zeitreihe der Pegeldurchflüsse simulieren kann. Die Güte der Simulation des Ist-Zustandes (Standard-Meßzeitraum 1.1.1961-31.12.1999) ist für die Kalibrierungs- und Validierungszeiträume in allen Untersuchungsgebieten gut bis sehr gut.Zur Erleichterung der umfangreichen, zeitaufwendigen einzugsgebietsbezogenen Datenaufbereitung für das hydrologische Modell HBV-D wurde eine Arbeitsumgebung auf Basis von Programmerweiterungen des Geoinformationssystems ArcView und zusätzlichen Hilfsprogrammen entwickelt. Die Arbeitsumgebung HBV-Params enthält eine graphische Benutzeroberfläche und räumt sowohl erfahrenen Hydrologen als auch hydrologisch geschulten Anwendern, z.B. Studenten der Vertiefungsrichtung Hydrologie, Flexibilität und vollständige Kontrolle bei der Ableitung von Parameterwerten und der Editierung von Parameter- und Steuerdateien ein. Somit ist HBV-D im Gegensatz zu Vorläuferversionen mit rudimentären Arbeitsumgebungen auch außerhalb der Forschung für Lehr- und Übungszwecke einsetzbar.In einem zweiten Schritt werden Gebietsniederschlagssummen, Gebietstemperaturen und simulierte Mittelwerte des Durchflusses (MQ) des Ist-Zustandes mit den Zuständen zweier Klimaszenarien für den Szenarienzeitraum 100 Jahre später (2061-2099) verglichen. Die Klimaszenarien beruhen auf simulierten Zirkulationsmustern je eines Modellaufes zweier Globaler Zirkulationsmodelle (GCM), die mit einem statistischen Regionalisierungsverfahren in Tageswertszenarien (Temperatur, Niederschlag) an Meßstationen in den Untersuchungsgebieten überführt wurden und als Eingangsdaten des hydrologischen Modells verwendet werden.Für die zweite Hälfte des 21. Jahrhunderts weisen beide regionalisierten Klimaszenarien eine Zunahme der Jahresmittel der Gebietstemperatur sowie eine Zunahme der Jahressummen der Gebietsniederschläge auf, die mit einer hohen Variabilität einhergeht. Eine Betrachtung der saisonalen (monatlichen) Änderungsbeträge von Temperatur, Niederschlag und mittlerem Durchfluß zwischen Szenarienzeitraum (2061-2099) und Ist-Zustand ergibt in allen Untersuchungsgebieten eine Temperaturzunahme (höher im Sommer als im Winter) und eine generelle Zunahme der Niederschlagssummen (mit starken Schwankungen zwischen den Einzelmonaten), die bei der hydrologischen Simulation zu deutlich höheren mittleren Durchflüssen von November bis März und leicht erhöhten mittleren Durchflüssen in den restlichen Monaten führen. Die Stärke der Durchflußerhöhung ist nach den individuellen Klimaszenarien unterschiedlich und im Sommer- bzw. Winterhalbjahr gegenläufig ausgeprägt. Hauptursache für die simulierte starke Zunahme der mittleren Durchflüsse im Winterhalbjahr ist die trotz Temperaturerhöhung der Klimaszenarien winterlich niedrige Evapotranspiration, so daß erhöhte Niederschläge direkt in erhöhten Durchfluß transformiert werden können.Der Vergleich der Untersuchungsgebiete zeigt in Einzelmonaten von West nach Ost abnehmende Änderungsbeträge der Niederschlagssummen, die als Hinweis auf die Bedeutung der Kontinentalitätseinflüsse auch unter geänderten klimatischen Bedingungen in Südwestdeutschland aufgefaßt werden könnten.Aus den regionalisierten Klimaszenarien werden Änderungsbeträge für die Modulation gemessener Zeitreihen mittels synthetischer Szenarien abgeleitet, die mit einem geringen Rechenaufwand in hydrologische Modellantworten überführt werden können. Die direkte Ableitung synthetischer Szenarien aus GCM-Ergebniswerten (bodennahe Temperatur und Gesamtniederschlag) an einzelnen GCM-Gitterpunkten erbrachte unbefriedigende Ergebnisse.Ob, in welcher Höhe und zeitlichen Verteilung die in den (synthetischen) Szenarien verwendeten Niederschlags- und Temperaturänderungen eintreten werden, kann nur die Zukunft zeigen. Eine Abschätzung, wie sich die Abflußverhältnisse und insbesondere die mittleren Durchflüsse der Untersuchungsgebiete bei möglichen Änderungen entwickeln würden, kann jedoch heute schon vorgenommen werden. Simulationen auf Szenariogrundlagen sind ein Weg, unbekannte zukünftige Randbedingungen sowie regionale Auswirkungen möglicher Änderungen des Klimasystems ausschnittsweise abzuschätzen und entsprechende Risikominderungsstrategien zu entwickeln. Jegliche Modellierung und Simulation natürlicher Systeme ist jedoch mit beträchtlichen Unsicherheiten verknüpft. Vergleichsweise große Unsicherheiten sind mit der zukünftigen Entwicklung des sozioökonomischen Systems und der Komplexität des Klimasystems verbunden. Weiterhin haben Unsicherheiten der einzelnen Modellbausteine der Modellkette Emissionsszenarien/Gaszyklusmodelle - Globale Zirkulationsmodelle/Regionalisierung - hydrologisches Modell, die eine Kaskade der Unsicherheiten ergeben, neben Datenunsicherheiten bei der Erfassung hydrometeorologischer Meßgrößen einen erheblichen Einfluß auf die Vertrauenswürdigkeit der Simulationsergebnisse, die als ein dargestellter Wert eines Ergebnisbandes zu interpretieren sind.Der Einsatz (1) robuster hydrologischer Modelle, die insbesondere temperaturbeeinflußte Prozesse adäquat beschreiben,(2) die Verwendung langer Zeitreihen (wenigsten 30 Jahre) von Meßwerten und(3) die gleichzeitige vergleichende Betrachtung von Klimaszenarien, die auf unterschiedlichen GCMs beruhen (und wenn möglich, verschiedene Emissionsszenarien berücksichtigen),sollte aus Gründen der wissenschaftlichen Sorgfalt, aber auch der besseren Vergleichbarkeit der Ergebnisse von Regionalstudien im noch jungen Forschungsfeld der Klimafolgenforschung beachtet werden.
This PhD thesis presents the spatio-temporal distribution of terrestrial carbon fluxes for the time period of 1982 to 2002 simulated by a combination of the process-based dynamic global vegetation model LPJ and a 21-year time series of global AVHRR-fPAR data (fPAR – fraction of photosynthetically active radiation). Assimilation of the satellite data into the model allows improved simulations of carbon fluxes on global as well as on regional scales. As it is based on observed data and includes agricultural regions, the model combined with satellite data produces more realistic carbon fluxes of net primary production (NPP), soil respiration, carbon released by fire and the net land-atmosphere flux than the potential vegetation model. It also produces a good fit to the interannual variability of the CO2 growth rate. Compared to the original model, the model with satellite data constraint produces generally smaller carbon fluxes than the purely climate-based stand-alone simulation of potential natural vegetation, now comparing better to literature estimates. The lower net fluxes are a result of a combination of several effects: reduction in vegetation cover, consideration of human influence and agricultural areas, an improved seasonality, changes in vegetation distribution and species composition. This study presents a way to assess terrestrial carbon fluxes and elucidates the processes contributing to interannual variability of the terrestrial carbon exchange. Process-based terrestrial modelling and satellite-observed vegetation data are successfully combined to improve estimates of vegetation carbon fluxes and stocks. As net ecosystem exchange is the most interesting and most sensitive factor in carbon cycle modelling and highly uncertain, the presented results complementary contribute to the current knowledge, supporting the understanding of the terrestrial carbon budget.
River flooding is a constant peril for societies, causing direct economic losses in the order of $100 billion worldwide each year. Under global change, the prolonged concentration of people and assets in floodplains is accompanied by an emerging intensification of flood extremes due to anthropogenic global warming, ultimately exacerbating flood risk in many regions of the world.
Flood adaptation plays a key role in the mitigation of impacts, but poor understanding of vulnerability and its dynamics limits the validity of predominant risk assessment methods and impedes effective adaptation strategies. Therefore, this thesis investigates new methods for flood risk assessment that embrace the complexity of flood vulnerability, using the understudied commercial sector as an application example.
Despite its importance for accurate risk evaluation, flood loss modeling has been based on univariable and deterministic stage-damage functions for a long time. However, such simplistic methods only insufficiently describe the large variation in damage processes, which initiated the development of multivariable and probabilistic loss estimation techniques. The first study of this thesis developed flood loss models for companies that are based on emerging statistical and machine learning approaches (i.e., random forest, Bayesian network, Bayesian regression). In a benchmarking experiment on basis of object-level loss survey data, the study showed that all proposed models reproduced the heterogeneity in damage processes and outperformed conventional stage-damage functions with respect to predictive accuracy. Another advantage of the novel methods is that they convey probabilistic information in predictions, which communicates the large remaining uncertainties transparently and, hence, supports well-informed risk assessment.
Flood risk assessment combines vulnerability assessment (e.g., loss estimation) with hazard and exposure analyses. Although all of the three risk drivers interact and change over time, such dependencies and dynamics are usually not explicitly included in flood risk models. Recently, systemic risk assessment that dissolves the isolated consideration of risk drivers has gained traction, but the move to holistic risk assessment comes with limited thoroughness in terms of loss estimation and data limitations. In the second study, I augmented a socio-hydrological system dynamics model for companies in Dresden, Germany, with the multivariable Bayesian regression loss model from the first study. The additional process-detail and calibration data improved the loss estimation in the systemic risk assessment framework and contributed to more accurate and reliable simulations. The model uses Bayesian inference to quantify uncertainty and learn the model parameters from a combination of prior knowledge and diverse data.
The third study demonstrates the potential of the socio-hydrological flood risk model for continuous, long-term risk assessment and management. Using hydroclimatic ad socioeconomic forcing data, I projected a wide range of possible risk trajectories until the end of the century, taking into account the adaptive behavior of companies. The study results underline the necessity of increased adaptation efforts to counteract the expected intensification of flood risk due to climate change. A sensitivity analysis of the effectiveness of different adaptation measures and strategies revealed that optimized adaptation has the potential to mitigate flood risk by up to 60%, particularly when combining structural and non-structural measures. Additionally, the application shows that systemic risk assessment is capable of capturing adverse long-term feedbacks in the human-flood system such as the levee effect.
Overall, this thesis advances the representation of vulnerability in flood risk modeling by offering modeling solutions that embrace the complexity of human-flood interactions and quantify uncertainties consistently using probabilistic modeling. The studies show how scarce information in data and previous experiments can be integrated in the inference process to provide model predictions and simulations that are reliable and rich in information. Finally, the focus on the flood vulnerability of companies provides new insights into the heterogeneous damage processes and distinct flood coping of this sector.
Air pollution has been a persistent global problem in the past several hundred years. While some industrialized nations have shown improvements in their air quality through stricter regulation, others have experienced declines as they rapidly industrialize. The WHO’s 2021 update of their recommended air pollution limit values reflects the substantial impacts on human health of pollutants such as NO2 and O3, as recent epidemiological evidence suggests substantial long-term health impacts of air pollution even at low concentrations. Alongside developments in our understanding of air pollution's health impacts, the new technology of low-cost sensors (LCS) has been taken up by both academia and industry as a new method for measuring air pollution. Due primarily to their lower cost and smaller size, they can be used in a variety of different applications, including in the development of higher resolution measurement networks, in source identification, and in measurements of air pollution exposure. While significant efforts have been made to accurately calibrate LCS with reference instrumentation and various statistical models, accuracy and precision remain limited by variable sensor sensitivity. Furthermore, standard procedures for calibration still do not exist and most proprietary calibration algorithms are black-box, inaccessible to the public. This work seeks to expand the knowledge base on LCS in several different ways: 1) by developing an open-source calibration methodology; 2) by deploying LCS at high spatial resolution in urban environments to test their capability in measuring microscale changes in urban air pollution; 3) by connecting LCS deployments with the implementation of local mobility policies to provide policy advice on resultant changes in air quality.
In a first step, it was found that LCS can be consistently calibrated with good performance against reference instrumentation using seven general steps: 1) assessing raw data distribution, 2) cleaning data, 3) flagging data, 4) model selection and tuning, 5) model validation, 6) exporting final predictions, and 7) calculating associated uncertainty. By emphasizing the need for consistent reporting of details at each step, most crucially on model selection, validation, and performance, this work pushed forward with the effort towards standardization of calibration methodologies. In addition, with the open-source publication of code and data for the seven-step methodology, advances were made towards reforming the largely black-box nature of LCS calibrations.
With a transparent and reliable calibration methodology established, LCS were then deployed in various street canyons between 2017 and 2020. Using two types of LCS, metal oxide (MOS) and electrochemical (EC), their performance in capturing expected patterns of urban NO2 and O3 pollution was evaluated. Results showed that calibrated concentrations from MOS and EC sensors matched general diurnal patterns in NO2 and O3 pollution measured using reference instruments. While MOS proved to be unreliable for discerning differences among measured locations within the urban environment, the concentrations measured with calibrated EC sensors matched expectations from modelling studies on NO2 and O3 pollution distribution in street canyons. As such, it was concluded that LCS are appropriate for measuring urban air quality, including for assisting urban-scale air pollution model development, and can reveal new insights into air pollution in urban environments.
To achieve the last goal of this work, two measurement campaigns were conducted in connection with the implementation of three mobility policies in Berlin. The first involved the construction of a pop-up bike lane on Kottbusser Damm in response to the COVID-19 pandemic, the second surrounded the temporary implementation of a community space on Böckhstrasse, and the last was focused on the closure of a portion of Friedrichstrasse to all motorized traffic. In all cases, measurements of NO2 were collected before and after the measure was implemented to assess changes in air quality resultant from these policies. Results from the Kottbusser Damm experiment showed that the bike-lane reduced NO2 concentrations that cyclists were exposed to by 22 ± 19%. On Friedrichstrasse, the street closure reduced NO2 concentrations to the level of the urban background without worsening the air quality on side streets. These valuable results were communicated swiftly to partners in the city administration responsible for evaluating the policies’ success and future, highlighting the ability of LCS to provide policy-relevant results.
As a new technology, much is still to be learned about LCS and their value to academic research in the atmospheric sciences. Nevertheless, this work has advanced the state of the art in several ways. First, it contributed a novel open-source calibration methodology that can be used by a LCS end-users for various air pollutants. Second, it strengthened the evidence base on the reliability of LCS for measuring urban air quality, finding through novel deployments in street canyons that LCS can be used at high spatial resolution to understand microscale air pollution dynamics. Last, it is the first of its kind to connect LCS measurements directly with mobility policies to understand their influences on local air quality, resulting in policy-relevant findings valuable for decisionmakers. It serves as an example of the potential for LCS to expand our understanding of air pollution at various scales, as well as their ability to serve as valuable tools in transdisciplinary research.
For millennia, humans have affected landscapes all over the world. Due to horizontal expansion, agriculture plays a major role in the process of fragmentation. This process is caused by a substitution of natural habitats by agricultural land leading to agricultural landscapes. These landscapes are characterized by an alternation of agriculture and other land use like forests. In addition, there are landscape elements of natural origin like small water bodies. Areas of different land use are beside each other like patches, or fragments. They are physically distinguishable which makes them look like a patchwork from an aerial perspective. These fragments are each an own ecosystem with conditions and properties that differ from their adjacent fragments. As open systems, they are in exchange of information, matter and energy across their boundaries. These boundary areas are called transition zones. Here, the habitat properties and environmental conditions are altered compared to the interior of the fragments. This changes the abundance and the composition of species in the transition zones, which in turn has a feedback effect on the environmental conditions.
The literature mainly offers information and insights on species abundance and composition in forested transition zones. Abiotic effects, the gradual changes in energy and matter, received less attention. In addition, little is known about non-forested transition zones. For example, the effects on agricultural yield in transition zones of an altered microclimate, matter dynamics or different light regimes are hardly researched or understood. The processes in transition zones are closely connected with altered provisioning and regulating ecosystem services. To disentangle the mechanisms and to upscale the effects, models can be used.
My thesis provides insights into these topics: literature was reviewed and a conceptual framework for the quantitative description of gradients of matter and energy in transition zones was introduced. The results of measurements of environmental gradients like microclimate, aboveground biomass and soil carbon and nitrogen content are presented that span from within the forest into arable land. Both the measurements and the literature review could not validate a transition zone of 100 m for abiotic effects. Although this value is often reported and used in the literature, it is likely to be smaller.
Further, the measurements suggest that on the one hand trees in transition zones are smaller compared to those in the interior of the fragments, while on the other hand less biomass was measured in the arable lands’ transition zone. These results support the hypothesis that less carbon is stored in the aboveground biomass in transition zones. The soil at the edge (zero line) between adjacent forest and arable land contains more nitrogen and carbon content compared to the interior of the fragments. One-year measurements in the transition zone also provided evidence that microclimate is different compared to the fragments’ interior.
To predict the possible yield decreases that transition zones might cause, a modelling approach was developed. Using a small virtual landscape, I modelled the effect of a forest fragment shading the adjacent arable land and the effects of this on yield using the MONICA crop growth model. In the transition zone yield was less compared to the interior due to shading. The results of the simulations were upscaled to the landscape level and exemplarily calculated for the arable land of a whole region in Brandenburg, Germany.
The major findings of my thesis are: (1) Transition zones are likely to be much smaller than assumed in the scientific literature; (2) transition zones aren’t solely a phenomenon of forested ecosystems, but significantly extend into arable land as well; (3) empirical and modelling results show that transition zones encompass biotic and abiotic changes that are likely to be important to a variety of agricultural landscape ecosystem services.
Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties.
Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult – if not impossible – to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates (‘higher export in warmer years’) that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes.
Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine Ötztal valley in Tyrol, Austria, over decadal timescales in the past and future – i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest.
The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper Ötztal, Vent, Sölden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 % of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors.
The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.
The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed – unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology.
This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves – especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.
Die visuelle Kommunikation ist eine effiziente Methode, um dynamische Phänomene zu beschreiben. Informationsobjekte präzise wahrzunehmen, einen schnellen Zugriff auf strukturierte und relevante Informationen zu ermöglichen, erfordert konsistente und nach dem formalen Minimalprinzip konzipierte Analyse- und Darstellungsmethoden. Dynamische Raumphänomene in Geoinformationssystemen können durch den Mangel an konzeptionellen Optimierungsanpassungen aufgrund ihrer statischen Systemstruktur nur bedingt die Informationen von Raum und Zeit modellieren. Die Forschung in dieser Arbeit ist daher auf drei interdisziplinäre Ansätze fokussiert. Der erste Ansatz stellt eine echtzeitnahe Datenerfassung dar, die in Geodatenbanken zeitorientiert verwaltet wird. Der zweite Ansatz betrachtet Analyse- und Simulationsmethoden, die das dynamische Verhalten analysieren und prognostizieren. Der dritte Ansatz konzipiert Visualisierungsmethoden, die insbesondere dynamische Prozesse abbilden. Die Symbolisierung der Prozesse passt sich bedarfsweise in Abhängigkeit des Prozessverlaufes und der Interaktion zwischen Datenbanken und Simulationsmodellen den verschiedenen Entwicklungsphasen an. Dynamische Aspekte können so mit Hilfe bewährter Funktionen aus der GI-Science zeitnah mit modularen Werkzeugen entwickelt und visualisiert werden. Die Analyse-, Verschneidungs- und Datenverwaltungsfunktionen sollen hierbei als Nutzungs- und Auswertungspotential alternativ zu Methoden statischer Karten dienen. Bedeutend für die zeitliche Komponente ist das Verknüpfen neuer Technologien, z. B. die Simulation und Animation, basierend auf einer strukturierten Zeitdatenbank in Verbindung mit statistischen Verfahren. Methodisch werden Modellansätze und Visualisierungstechniken entwickelt, die auf den Bereich Verkehr transferiert werden. Verkehrsdynamische Phänomene, die nicht zusammenhängend und umfassend darstellbar sind, werden modular in einer serviceorientierten Architektur separiert, um sie in verschiedenen Ebenen räumlich und zeitlich visuell zu präsentieren. Entwicklungen der Vergangenheit und Prognosen der Zukunft werden über verschiedene Berechnungsmethoden modelliert und visuell analysiert. Die Verknüpfung einer Mikrosimulation (Abbildung einzelner Fahrzeuge) mit einer netzgesteuerten Makrosimulation (Abbildung eines gesamten Straßennetzes) ermöglicht eine maßstabsunabhängige Simulation und Visualisierung des Mobilitätsverhaltens ohne zeitaufwendige Bewertungsmodellberechnungen. Zukünftig wird die visuelle Analyse raum-zeitlicher Veränderungen für planerische Entscheidungen ein effizientes Mittel sein, um Informationen übergreifend verfügbar, klar strukturiert und zweckorientiert zur Verfügung zu stellen. Der Mehrwert durch visuelle Geoanalysen, die modular in einem System integriert sind, ist das flexible Auswerten von Messdaten nach zeitlichen und räumlichen Merkmalen.
Understanding the distribution of species is fundamental for biodiversity conservation, ecosystem management, and increasingly also for climate impact assessment. The presence of a species in a given site depends on physiological limitations (abiotic factors), interactions with other species (biotic factors), migratory or dispersal processes (site accessibility) as well as the continuing
effects of past events, e.g. disturbances (site legacy). Existing approaches to predict species distributions either (i) correlate observed species occurrences with environmental variables describing abiotic limitations, thus ignoring biotic interactions, dispersal and legacy effects (statistical species distribution model, SDM); or (ii) mechanistically model the variety of processes determining species distributions (process-based model, PBM). SDMs are widely used due to their easy applicability and ability to handle varied data qualities. But they fail to reproduce the dynamic response of species distributions to changing conditions. PBMs are expected to be superior in this respect, but they need very specific data unavailable for many species, and are often more complex and require more computational effort. More recently, hybrid models link the two approaches to combine their respective strengths.
In this thesis, I apply and compare statistical and process-based approaches to predict species distributions, and I discuss their respective limitations, specifically for applications in changing environments. Detailed analyses of SDMs for boreal tree species in Finland reveal that nonclimatic predictors - edaphic properties and biotic interactions - are important limitations at the treeline, contesting the assumption of unrestricted, climatically induced range expansion. While the estimated SDMs are successful within their training data range, spatial and temporal model transfer fails. Mapping and comparing sampled predictor space among data subsets identifies spurious extrapolation as the plausible explanation for limited model transferability. Using these findings, I analyze the limited success of an established PBM (LPJ-GUESS) applied to the same problem. Examination of process representation and parameterization in the PBM identifies implemented processes to adjust (competition between species, disturbance) and missing processes that are crucial in boreal forests (nutrient limitation, forest management). Based on climatic correlations shifting over time, I stress the restricted temporal transferability of bioclimatic limits used in LPJ-GUESS and similar PBMs. By critically assessing the performance of SDM and PBM in this application, I demonstrate the importance of understanding the limitations of the
applied methods.
As a potential solution, I add a novel approach to the repertoire of existing hybrid models. By simulation experiments with an individual-based PBM which reproduces community dynamics resulting from biotic factors, dispersal and legacy effects, I assess the resilience of coastal vegetation to abrupt hydrological changes. According to the results of the resilience analysis, I then modify temporal SDM predictions, thereby transferring relevant process detail from PBM to
SDM. The direction of knowledge transfer from PBM to SDM avoids disadvantages of current hybrid models and increases the applicability of the resulting model in long-term, large-scale applications. A further advantage of the proposed framework is its flexibility, as it is readily extended to other model types, disturbance definitions and response characteristics.
Concluding, I argue that we already have a diverse range of promising modelling tools at hand, which can be refined further. But most importantly, they need to be applied more thoughtfully. Bearing their limitations in mind, combining their strengths and openly reporting underlying assumptions and uncertainties is the way forward.
Untersuchungen zur räumlichen Analyse und Visualisierung von Mietpreisdaten für Immobilienportale
(2015)
Die vorliegende Arbeit verfolgt das Ziel, aus geoinformatischer Sicht eine konzeptionelle Grundlage zur räumlichen Optimierung von Immobilienportalen zu schaffen. Die Arbeit geht dabei von zwei Hypothesen aus:
1. Verfahren der räumlichen Statistik und des Maschinellen Lernens zur Mietpreisschätzung sind den bisher eingesetzten Verfahren der hedonischen Regression überlegen und eignen sich zur räumlichen Optimierung von Immobilienportalen.
2. Die von Immobilienportalen publizierten webbasierten Mietpreiskarten geben nicht die tatsächlichen räumlichen Verhältnisse auf Immobilienmärkten wieder. Alternative webbasierte Darstellungsformen, wie z.B. Gridmaps, sind dem Status Quo der Immobilienpreiskarten von Immobilienportalen überlegen und visualisieren die tatsächlichen räumlichen Verhältnisse von Immobilienpreisen zweckmäßiger.
Beide Thesen können bewiesen werden.
Es erfolgt zunächst eine umfangreiche Erhebung des Forschungsbedarfs mittels Literaturstudien und technologischer Recherche. Zur Beantwortung der Forschungsfragen wird als quantitative Datenbasis ein 74.098 Mietangebote umfassender Datensatz (von Januar 2007 bis September 2013) eines Immobilienportals akquiriert. Dieser reicht jedoch nicht in vollem Umfang zur Beantwortung der Fragestellungen aus. Deshalb führt der Autor Experteninterviews zur Erhebung einer qualitativen Datenbasis. Deren Analyse ergibt in Kombination mit der Literaturstudie und der technologischen Recherche ein umfassendes, bisher so nicht verfügbares Bild. Es stellt den Status Quo der räumlichen Sicht sowie der raumanalytischen und geovisuellen Defizite von Immobilienportalen dar.
Zur Optimierung der raumanalytischen und geovisuellen Defizite werden forschungsbasierte Lösungsansätze herausgearbeitet und teilimplementiert. Methoden des Maschinellen Lernens und räumliche Schätzverfahren werden als Alternativen zu den von Immobilienportalen bisher genutzten „nicht räumlichen“ Analyseverfahren zur Preismodellierung untersucht. Auf Grundlage eines hierfür konzipierten Validierungsrahmens werden diese Methoden für die Nutzung im Kontext von Immobilienportalen adaptiert. Die prototypische Teilimplementierung zeigt die programmiertechnische Umsetzung des Konzeptes auf. Eine umfassende Analyse geeigneter Sekundärvariablensets zur Mietpreisschätzung liefert als methodisches Resultat, dass Interpolatoren, die Sekundärvariablen benötigen (Kriging with external drift, Ordinary Cokriging), kaum zu valideren Mietpreisschätzergebnissen gelangen als die Methode des Ordinary Kriging, die keine Sekundärvariablen benötigt. Die Methoden Random Forest aus dem Maschinellen Lernen und die Geographisch Gewichtete Regression hingegen bergen großes Potential zur Nutzung der räumlichen Mietpreisschätzung im Kontext von Immobilien-portalen. Die Forschungsergebnisse der räumlichen Preismodellierung werden in die räumliche Visualisierung von Mietpreisen transferiert.
Für die webbasierte Mietpreisdarstellung wird ein Set alternativer Darstellungsmethoden entwickelt, um Mietpreiskarten-Prototypen abzuleiten. Ein methodisches Ergebnis der Entwicklung der Mietpreiskarten-Prototypen ist die Entwicklung eines geeigneten Ansatzes der Loslösung des Preisbezugs von fachfremd verwendeten Bezugsgeometrien. Hierfür wird vom Autor der Begriff der zonenlosen Preiskarte geprägt. Diese werden mit Methoden des Gridmapping erstellt. Es werden optimale Rasterauflösungen zur Darstellung interpolierter Rastergrößen ermittelt. Zonenlose Preiskarten mit Methoden des Gridmapping, gepaart mit einer optionalen gebäudescharfen Darstellung in größeren Maßstäben, sind als Resultate der Forschung die bestmögliche, sich an realen Verhältnissen orientierende, räumliche Mietpreisdarstellung. Die entstandenen Prototypen sind eine Annäherung der wahren Verteilung des Mietpreises im Raum und um einiges schärfer, als die auf der hedonischen Regression basierenden Darstellungen. Somit kann die wahre „Topographie“ der Mietpreislandschaft abgebildet werden. Ein Einsatz der Karten für Nutzergruppen wie Makler, Investoren oder Kommunen zur Analyse städtischer Mietmärkte ist denkbar. Alle entstandenen Prototypen sind unter der Nutzung von Map APIs umgesetzt. Ein Ergebnis dessen ist, dass Map APIs noch an diversen „Kinderkrankheiten“ leiden und derart umgesetzte Mietpreiskarten noch einen weiten Weg vor sich haben, bis sie das Niveau thematischer Karten von Immhof oder Arnberger erreichen.
Die konzeptionellen Überlegungen und Teilimplementierungen münden in drei Prozessketten, die Umsetzungsoptionen für eine räumliche Optimierung von Immobilienportalen darstellen. Dabei werden zwei Szenarien für eine räumlich optimierte Mietpreisschätzung und ein Szenario für eine räumlich optimierte Mietpreisdarstellung herausgearbeitet.
The length of the vegetation period (VP) plays a central role for the interannual variation of carbon fixation of terrestrial ecosystems. Observational data analysis has indicated that the length of the VP has increased in the last decades in the northern latitudes mainly due to an advancement of bud burst (BB). This phenomenon has been widely discussed in the context of Global Warming because phenology is correlated to temperatures. Analyzing the patterns of spring phenology over the last century in Southern Germany provided two main findings: - The strong advancement of spring phases especially in the decade before 1999 is not a singular event in the course of the 20th century. Similar trends were also observed in earlier decades. Distinct periods of varying trend behavior for important spring phases could be distinguished. - Marked differences in trend behavior between the early and late spring phases were detected. Early spring phases changed as regards the magnitude of their negative trends from strong negative trends between 1931 and 1948 to moderate negative trends between 1948 and 1984 and back to strong negative trends between 1984 and 1999. Late spring phases showed a different behavior. Negative trends between 1931 and 1948 are followed by marked positive trends between 1948 and 1984 and then strong negative trends between 1984 and 1999. This marked difference in trend development between early and late spring phases was also found all over Germany for the two periods 1951 to 1984 and 1984 to 1999. The dominating influence of temperature on spring phenology and its modifying effect on autumn phenology was confirmed in this thesis. However, - temperature functions determining spring phenology were not significantly correlated with a global annual CO2 signal which was taken as a proxy for a Global Warming pattern. - an index for large scale regional circulation patterns (NAO index) could only to a small part explain the observed phenological variability in spring. The observed different trend behavior of early and late spring phases is explained by the differing behavior of mean March and April temperatures. Mean March temperatures have increased on average over the 20th century accompanied by an increasing variation in the last 50 years. April temperatures, however, decreased between the end of the 1940s and the mid-1980s, followed by a marked warming after the mid-1980s. It can be concluded that the advancement of spring phenology in recent decades are part of multi-decadal fluctuations over the 20th century that vary with the species and the relevant seasonal temperatures. Because of these fluctuations a correlation with an observed Global Warming signal could not be found. On average all investigated spring phases advanced between 5 and 20 days between 1951 and 1999 for all Natural Regions in Germany. A marked difference be! tween late and early spring phases is due to the above mentioned differing behavior before and after the mid-1980s. Leaf coloring (LC) was delayed between 1951 and 1984 for all tree species. However, after 1984 LC was advanced. Length of the VP increased between 1951 and 1999 for all considered tree species by an average of ten days throughout Germany. It is predominately the change in spring phases which contributes to a change in the potentially absorbed radiation. Additionally, it is the late spring species that are relatively more favored by an advanced BB because they can additionally exploit longer days and higher temperatures per day advancement. To assess the relative change in potentially absorbed radiation among species, changes in both spring and autumn phenology have to be considered as well as where these changes are located in the year. For the detection of the marked difference between early and late spring phenology a new time series construction method was developed. This method allowed the derivation of reliable time series that spanned over 100 years and the construction of locally combined time series increasing the available data for model development. Apart from analyzed protocolling errors, microclimatic site influences, genetic variation and the observers were identified as sources of uncertainty of phenological observational data. It was concluded that 99% of all phenological observations at a certain site will vary within approximately 24 days around the parametric mean. This supports to the proposed 30-day rule to detect outliers. New phenology models that predict local BB from daily temperature time series were developed. These models were based on simple interactions between inhibitory and promotory agents that are assumed to control the developmental status of a plant. Apart from the fact that, in general, the new models fitted and predicted the observations better than classical models, the main modeling results were: - The bias of the classical models, i.e. overestimation of early observations and underestimation of late observations, could be reduced but not completely removed. - The different favored model structures for each species indicated that for the late spring phases photoperiod played a more dominant role than for early spring phases. - Chilling only plays a subordinate role for spring BB compared to temperatures directly preceding BB.
The estimation of financial losses is an integral part of flood risk assessment. The application of existing flood loss models on locations or events different from the ones used to train the models has led to low performance, showing that characteristics of the flood damaging process have not been sufficiently well represented yet. To improve flood loss model transferability, I explore various model structures aiming at incorporating different (inland water) flood types and pathways. That is based on a large survey dataset of approximately 6000 flood-affected households which addresses several aspects of the flood event, not only the hazard characteristics but also information on the affected building, socioeconomic factors, the household's preparedness level, early warning, and impacts. Moreover, the dataset reports the coincidence of different flood pathways. Whilst flood types are a classification of flood events reflecting their generating process (e.g. fluvial, pluvial), flood pathways represent the route the water takes to reach the receptors (e.g. buildings). In this work, the following flood pathways are considered: levee breaches, river floods, surface water floods, and groundwater floods.
The coincidence of several hazard processes at the same time and place characterises a compound event. In fact, many flood events develop through several pathways, such as the ones addressed in the survey dataset used. Earlier loss models, although developed with one or multiple predictor variables, commonly use loss data from a single flood event which is attributed to a single flood type, disregarding specific flood pathways or the coincidence of multiple pathways. This gap is addressed by this thesis through the following research questions: 1. In which aspects do flood pathways of the same (compound inland) flood event differ? 2. How much do factors which contribute to the overall flood loss in a building differ in various settings, specifically across different flood pathways? 3. How well can Bayesian loss models learn from different settings? 4. Do compound, that is, coinciding flood pathways result in higher losses than a single pathway, and what does the outcome imply for future loss modelling?
Statistical analysis has found that households affected by different flood pathways also show, in general, differing characteristics of the affected building, preparedness, and early warning, besides the hazard characteristics. Forecasting and early warning capabilities and the preparedness of the population are dominated by the general flood type, but characteristics of the hazard at the object-level, the impacts, and the recovery are more related to specific flood pathways, indicating that risk communication and loss models could benefit from the inclusion of flood-pathway-specific information.
For the development of the loss model, several potentially relevant predictors are analysed: water depth, duration, velocity, contamination, early warning lead time, perceived knowledge about self-protection, warning information, warning source, gap between warning and action, emergency measures, implementation of property-level precautionary measures (PLPMs), perceived efficacy of PLPMs, previous flood experience, awareness of flood risk, ownership, building type, number of flats, building quality, building value, house/flat area, building area, cellar, age, household size, number of children, number of elderly residents, income class, socioeconomic status, and insurance against floods. After a variable selection, descriptors of the hazard, building, and preparedness were deemed significant, namely: water depth, contamination, duration, velocity, building area, building quality, cellar, PLPMs, perceived efficacy of PLPMs, emergency measures, insurance, and previous flood experience. The inclusion of the indicators of preparedness is relevant, as they are rarely involved in loss datasets and in loss modelling, although previous studies have shown their potential in reducing losses. In addition, the linear model fit indicates that the explanatory factors are, in several cases, differently relevant across flood pathways.
Next, Bayesian multilevel models were trained, which intrinsically incorporate uncertainties and allow for partial pooling (i.e. different groups of data, such as households affected by different flood pathways, can learn from each other), increasing the statistical power of the model. A new variable selection was performed for this new model approach, reducing the number of predictors from twelve to seven variables but keeping factors of the hazard, building, and preparedness, namely: water depth, contamination, duration, building area, PLPMs, insurance, and previous flood experience. The new model was trained not only across flood pathways but also across regions of Germany, divided according to general socioeconomic factors and insurance policies, and across flood events. The distinction across regions and flood events did not improve loss modelling and led to a large overlap of regression coefficients, with no clear trend or pattern. The distinction of flood pathways showed credibly distinct regression coefficients, leading to a better understanding of flood loss modelling and indicating one potential reason why model transferability has been challenging.
Finally, new model structures were trained to include the possibility of compound inland floods (i.e. when multiple flood pathways coincide on the same affected asset). The dataset does not allow for verifying in which sequence the flood pathway waves occurred and predictor variables reflect only their mixed or combined outcome. Thus, two Bayesian models were trained: 1. a multi-membership model, a structure which learns the regression coefficients for multiple flood pathways at the same time, and 2. a multilevel model wherein the combination of coinciding flood pathways makes individual categories. The multi-membership model resulted in credibly different coefficients across flood pathways but did not improve model performance in comparison to the model assuming only a single dominant flood pathway. The model with combined categories signals an increase in impacts after compound floods, but due to the uncertainty in model coefficients and estimates, it is not possible to ascertain such an increase as credible. That is, with the current level of uncertainty in differentiating the flood pathways, the loss estimates are not credibly distinct from individual flood pathways.
To overcome the challenges faced, non-linear or mixed models could be explored in the future. Interactions, moderation, and mediation effects, as well as non-linear effects, should also be further studied. Loss data collection should regularly include preparedness indicators, and either data collection or hydraulic modelling should focus on the distinction of coinciding flood pathways, which could inform loss models and further improve estimates. Flood pathways show distinct (financial) impacts, and their inclusion in loss modelling proves relevant, for it helps in clarifying the different contribution of influencing factors to the final loss, improving understanding of the damaging process, and indicating future lines of research.
Die Untersuchung widmet sich der aktuellen Bedeutung von Ethnizität im ländlichen Raum der rumänischen Dobrudscha unter dem Einfluss der politischen und ökonomischen Dimension von Globalisierung. Im Mittelpunkt der Betrachtung von Ethnizität stehen die Aspekte von Inklusion und Exklusion sowie Selbst- und Fremdbeschreibung, die dem sozialen Wandel unterliegen. Mit einem Überblick über die Geschichte der räumlich, wirtschaftlich und sozial peripheren Untersuchungsregion Dobrudscha und der ausgewählten Minderheitengruppen wird die Entwicklung der ethnischen Zusammensetzung der Bevölkerung in der Region dargestellt. Als Fallbeispiele werden sechs Minderheitengruppen gewählt: Aromunen, Roma, russische Lipowaner, Tataren, Türken und Ukrainer. Zentrales Element der Studie bilden qualitative Interviews mit professionellen Beobachtern und Akteuren einerseits, die selbst Einfluss auf die soziale Bedeutung von Ethnizität nehmen, und andererseits mit Einwohnern in 15 ausgewählten Untersuchungsorten in der Dobrudscha. Die erhobenen Daten werden mit Blick auf die soziale Rolle von Ethnizität anhand von drei Faktorengruppen ausgewertet: Globalisierung der Ökonomie, Minderheiten- und Kulturpolitik sowie internationale Beziehungen. Auf dieser Grundlage wird die regionale und lokale Bedeutung ethnischer Kategorisierungen analysiert, um die Wahrnehmung und Bewertung ethnischer Zuordnungen im örtlichen Lebensumfeld zu erfassen.
Entwicklung, Implementierung und Erprobung eines planetaren Informationssystems auf Basis von ArcGIS
(2007)
Mit der Entwicklung der modernen Raumfahrt Mitte der 60er-Jahre des zwanzigsten Jahrhunderts und der Eroberung des Weltraums brach eine neue Epoche der bis dato auf Beobachtungen mit dem Teleskop gestützten planetaren Forschung an. Während des Wettrennens um die technologische Führerschaft im All zur Zeit des Kalten Krieges war das erste Ziel die Entsendung von Satelliten zur Erdbeobachtung, denen aber schon bald Sonden zum Mond und den benachbarten Planeten folgten. Diese Missionen lieferten eine enorme Fülle von Informationen in Form von Bildern und Messergebnissen in unterschiedlichen Datenformaten. Diese galt und gilt es zu strukturieren, zu verwalten, zu aktualisieren und zu interpretieren. Für die Interpretation terrestrischer Daten werden geographische Informationssysteme (GIS) hinzugezogen, die jedoch für planetare Anwendungen aufgrund unterschiedlicher Voraussetzungen nicht ohne weiteres eingesetzt werden können. Daher wurde im Rahmen dieser Arbeit die für die Verwaltung von geographischen Daten der Erdfernerkundung kommerziell erhältliche Software ArcGIS Desktop 9.0 / 9.1 (ESRI) mit eigenen Programmen und Modulen für die Planetenforschung angepasst. Diese ermöglichen die Aufbereitung und den Import planetarer Bild- und Textinformation in die kommerzielle Software. Zusätzlich wurde eine planetare Datenbank zur Speicherung und zentralen Verwaltung der Informationen aufgebaut. Die im Rahmen dieser Arbeit entwickelten Softwarekomponenten ermöglichen die schnelle und benutzerfreundliche Aufbereitung der in der Datenbank gehaltenen Informationen und das Auslesen in Dateiformate, die für geographische Informationssysteme geeignet sind. Des Weiteren wurde eine „Werkzeugleiste“ für ArcGIS entwickelt, die das Arbeiten mit planetaren Datensätzen beträchtlich beschleunigt und vereinfacht. Sie beinhaltet auch Module zur wissenschaftlichen Interpretation der planetaren Informationen, wie beispielsweise der Berechnung der Oberflächenrauigkeit der Marsoberfläche inklusive der flächendeckenden Kalibrierung der Eingangs-Basisdaten. Exemplarisch konnte gezeigt werden, dass das Verfahren eine verbesserte Berechnung der Oberflächenrauigkeit ermöglicht, als bisher angewandte Ansätze. Zudem wurde eine auf ArcGIS basierende Prozesskette zur Berechnung von hierarchischen Flussnetzen entwickelt und erprobt. Das terrestrische Beispiel, die Analyse eines Abflusssystems auf Island, zeigte eine sehr große Übereinstimmung der errechneten Gewässernetze mit den morphologischen Gegebenheiten vor Ort. Daraus ließ sich eine hohe Genauigkeit der mit demselben Ansatz errechneten Gewässernetze auf dem Mars ableiten. Auf der Grundlage der in dieser Arbeit entwickelten Programme und Module lassen sich auch Daten zukünftiger Missionen aufbereiten und in ein solches System einbinden, um diese mit eigenen Ansätzen zu verwalten, zu aktualisieren und für neue wissenschaftliche Fragestellungen perfekt anzupassen, einzusetzen und zu präsentieren, um so neue wissenschaftliche Erkenntnisse in der Planetenforschung zu gewinnen.
Today, more than half of the world’s population lives in urban areas. With a high density of population and assets, urban areas are not only the economic, cultural and social hubs of every society, they are also highly susceptible to natural disasters. As a consequence of rising sea levels and an expected increase in extreme weather events caused by a changing climate in combination with growing cities, flooding is an increasing threat to many urban agglomerations around the globe.
To mitigate the destructive consequences of flooding, appropriate risk management and adaptation strategies are required. So far, flood risk management in urban areas is almost exclusively focused on managing river and coastal flooding. Often overlooked is the risk from small-scale rainfall-triggered flooding, where the rainfall intensity of rainstorms exceeds the capacity of urban drainage systems, leading to immediate flooding. Referred to as pluvial flooding, this flood type exclusive to urban areas has caused severe losses in cities around the world. Without further intervention, losses from pluvial flooding are expected to increase in many urban areas due to an increase of impervious surfaces compounded with an aging drainage infrastructure and a projected increase in heavy precipitation events. While this requires the integration of pluvial flood risk into risk management plans, so far little is known about the adverse consequences of pluvial flooding due to a lack of both detailed data sets and studies on pluvial flood impacts. As a consequence, methods for reliably estimating pluvial flood losses, needed for pluvial flood risk assessment, are still missing.
Therefore, this thesis investigates how pluvial flood losses to private households can be reliably estimated, based on an improved understanding of the drivers of pluvial flood loss. For this purpose, detailed data from pluvial flood-affected households was collected through structured telephone- and web-surveys following pluvial flood events in Germany and the Netherlands.
Pluvial flood losses to households are the result of complex interactions between impact characteristics such as the water depth and a household’s resistance as determined by its risk awareness, preparedness, emergency response, building properties and other influencing factors. Both exploratory analysis and machine-learning approaches were used to analyze differences in resistance and impacts between households and their effects on the resulting losses. The comparison of case studies showed that the awareness around pluvial flooding among private households is quite low. Low awareness not only challenges the effective dissemination of early warnings, but was also found to influence the implementation of private precautionary measures. The latter were predominately implemented by households with previous experience of pluvial flooding. Even cases where previous flood events affected a different part of the same city did not lead to an increase in preparedness of the surveyed households, highlighting the need to account for small-scale variability in both impact and resistance parameters when assessing pluvial flood risk.
While it was concluded that the combination of low awareness, ineffective early warning and the fact that only a minority of buildings were adapted to pluvial flooding impaired the coping capacities of private households, the often low water levels still enabled households to mitigate or even prevent losses through a timely and effective emergency response.
These findings were confirmed by the detection of loss-influencing variables, showing that cases in which households were able to prevent any loss to the building structure are predominately explained by resistance variables such as the household’s risk awareness, while the degree of loss is mainly explained by impact variables.
Based on the important loss-influencing variables detected, different flood loss models were developed. Similar to flood loss models for river floods, the empirical data from the preceding data collection was used to train flood loss models describing the relationship between impact and resistance parameters and the resulting loss to building structures. Different approaches were adapted from river flood loss models using both models with the water depth as only predictor for building structure loss and models incorporating additional variables from the preceding variable detection routine.
The high predictive errors of all compared models showed that point predictions are not suitable for estimating losses on the building level, as they severely impair the reliability of the estimates. For that reason, a new probabilistic framework based on Bayesian inference was introduced that is able to provide predictive distributions instead of single loss estimates. These distributions not only give a range of probable losses, they also provide information on how likely a specific loss value is, representing the uncertainty in the loss estimate.
Using probabilistic loss models, it was found that the certainty and reliability of a loss estimate on the building level is not only determined by the use of additional predictors as shown in previous studies, but also by the choice of response distribution defining the shape of the predictive distribution. Here, a mix between a beta and a Bernoulli distribution to account for households that are able to prevent losses to their building’s structure was found to provide significantly more certain and reliable estimates than previous approaches using Gaussian or non-parametric response distributions.
The successful model transfer and post-event application to estimate building structure loss in Houston, TX, caused by pluvial flooding during Hurricane Harvey confirmed previous findings, and demonstrated the potential of the newly developed multi-variable beta model for future risk assessments. The highly detailed input data set constructed from openly available data sources containing over 304,000 affected buildings in Harris County further showed the potential of data-driven, building-level loss models for pluvial flood risk assessment.
In conclusion, pluvial flood losses to private households are the result of complex interactions between impact and resistance variables, which should be represented in loss models. The local occurrence of pluvial floods requires loss estimates on high spatial resolutions, i.e. on the building level, where losses are variable and uncertainties are high.
Therefore, probabilistic loss estimates describing the uncertainty of the estimate should be used instead of point predictions. While the performance of probabilistic models on the building level are mainly driven by the choice of response distribution, multi-variable models are recommended for two reasons:
First, additional resistance variables improve the detection of cases in which households were able to prevent structural losses.
Second, the added variability of additional predictors provides a better representation of the uncertainties when loss estimates from multiple buildings are aggregated.
This leads to the conclusion that data-driven probabilistic loss models on the building level allow for a reliable loss estimation at an unprecedented level of detail, with a consistent quantification of uncertainties on all aggregation levels. This makes the presented approach suitable for a wide range of applications, from decision support in spatial planning to impact- based early warning systems.
River flooding poses a threat to numerous cities and communities all over the world. The detection, quantification and attribution of changes in flood characteristics is key to assess changes in flood hazard and help affected societies to timely mitigate and adapt to emerging risks. The Rhine River is one of the major European rivers and numerous large cities reside at its shores. Runoff from several large tributaries superimposes in the main channel shaping the complex from regime. Rainfall, snowmelt as well as ice-melt are important runoff components. The main objective of this thesis is the investigation of a possible transient merging of nival and pluvial Rhine flood regimes under global warming. Rising temperatures cause snowmelt to occur earlier in the year and rainfall to be more intense. The superposition of snowmelt-induced floods originating from the Alps with more intense rainfall-induced runoff from pluvial-type tributaries might create a new flood type with potentially disastrous consequences.
To introduce the topic of changing hydrological flow regimes, an interactive web application that enables the investigation of runoff timing and runoff season- ality observed at river gauges all over the world is presented. The exploration and comparison of a great diversity of river gauges in the Rhine River Basin and beyond indicates that river systems around the world undergo fundamental changes. In hazard and risk research, the provision of background as well as real-time information to residents and decision-makers in an easy accessible way is of great importance. Future studies need to further harness the potential of scientifically engineered online tools to improve the communication of information related to hazards and risks.
A next step is the development of a cascading sequence of analytical tools to investigate long-term changes in hydro-climatic time series. The combination of quantile sampling with moving average trend statistics and empirical mode decomposition allows for the extraction of high resolution signals and the identification of mechanisms driving changes in river runoff. Results point out that the construction and operation of large reservoirs in the Alps is an important factor redistributing runoff from summer to winter and hint at more (intense) rainfall in recent decades, particularly during winter, in turn increasing high runoff quantiles. The development and application of the analytical sequence represents a further step in the scientific quest to disentangling natural variability, climate change signals and direct human impacts.
The in-depth analysis of in situ snow measurements and the simulations of the Alpine snow cover using a physically-based snow model enable the quantification of changes in snowmelt in the sub-basin upstream gauge Basel. Results confirm previous investigations indicating that rising temperatures result in a decrease in maximum melt rates. Extending these findings to a catchment perspective, a threefold effect of rising temperatures can be identified: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Furthermore, results indicate that due to the wide range of elevations in the basin, snowmelt does not occur simultaneously at all elevation, but elevation bands melt together in blocks. The beginning and end of the release of meltwater seem to be determined by the passage of warm air masses, and the respective elevation range affected by accompanying temperatures and snow availability. Following those findings, a hypothesis describing elevation-dependent compensation effects in snowmelt is introduced: In a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevations, i.e., the block of elevation bands providing most water to the snowmelt-induced runoff is located at higher elevations. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier. The timing of the snowmelt-induced runoff, however, stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below.
The insights on past and present changes in river runoff, snow covers and underlying mechanisms form the basis of investigations of potential future changes in Rhine River runoff. The mesoscale Hydrological Model (mHM) forced with an ensemble of climate projection scenarios is used to analyse future changes in streamflow, snowmelt, precipitation and evapotranspiration at 1.5, 2.0 and
3.0 ◦ C global warming. Simulation results suggest that future changes in flood characteristics in the Rhine River Basin are controlled by increased precipitation amounts on the one hand, and reduced snowmelt on the other hand. Rising temperatures deplete seasonal snowpacks. At no time during the year, a warming climate results in an increase in the risk of snowmelt-driven flooding. Counterbalancing effects between snowmelt and precipitation often result in only little and transient changes in streamflow peaks. Although, investigations point at changes in both rainfall and snowmelt-driven runoff, there are no indications of a transient merging of nival and pluvial Rhine flood regimes due to climate warming. Flooding in the main tributaries of the Rhine, such as the Moselle River, as well as the High Rhine is controlled by both precipitation and snowmelt. Caution has to be exercised labelling sub-basins such as the Moselle catchment as purely pluvial-type or the Rhine River Basin at Basel as purely nival-type. Results indicate that this (over-) simplifications can entail misleading assumptions with regard to flood-generating mechanisms and changes in flood hazard. In the framework of this thesis, some progress has been made in detecting, quantifying and attributing past, present and future changes in Rhine flow/flood characteristics. However, further studies are necessary to pin down future changes in the flood genesis of Rhine floods, particularly very rare events.