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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.
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.
Semiaride Gebiete sind hauptsächlich durch geringe Wasserressourcen gekennzeichnet und unterliegen häufig dem Risiko der Wasserknappheit. In diesen Gebieten ist die Wasserbereitstellung für Bewässerung und Trinkwasserversorgung stark von der oberflächlichen Speicherung in Stauseen abhängig, deren Wasserverfügbarkeit nachteilig durch Sedimentablagerung beeinflusst wird. Zur Wiedergabe des komplexen Sedimentablagerungsverhaltens in Stauseen von semiariden Gebieten und die Auswirkungen von Sedimentmanagementmaßnahmen wird ein Sedimentationsmodell entwickelt und mit dem WASA-SED Modell gekoppelt, das für die Modellierung der Abflussbildung und des Sedimenttransportes in Einzugsgebieten geeignet ist. Das Sedimentationsmodell beinhaltet zwei Ansätze, die unter der Berücksichtigung verschiedener Stauseengrößenklassen und Datenverfügbarkeit eingesetzt werden können. Für die Stauseen mit verfügbaren Informationen über ihre geometrischen Eigenschaften (wie Stauseetopographie und Höhe-Fläche-Volumen-Beziehung) und weitere Kenngrößen wie Ablagerungsmächtigkeit, Korngrößenverteilung und Sedimentdichte, kann ein detaillierter Modellansatz für die Sedimentablagerung verwendet werden. Wo diese Informationen nicht verfügbar sind, wird auf einen vereinfachten Ansatz zurückgegriffen. Der detaillierte Modellansatz ermöglicht die Betrachtung von Ablagerungsmustern im Stausee und Einschätzungen über die Effektivität von Sedimentmanagementmaßnahmen hinsichtlich der Sedimententlastung. Dieser Ansatz beruht auf der Simulation des Sedimenttransportes entlang eines Stauseelängsprofils. Für die Berechnung des Sedimenttransfers wird der Stauseekörper in einer Folge von Querprofilen repräsentiert. Der Sedimenttransport wird dabei korngrößenspezifisch entsprechend der Transportkapazität berechnet. Dafür stehen vier verschiedenen Sedimenttransportgleichungen zur Verfügung. Der vereinfachte Modellansatz ist für die Simulation des Sedimenttransfers in Gebieten mit hoher Stauseedichte geeignet, jedoch können weder Sedimentmanagementmaßnahmen noch die räumliche Verteilung der Ablagerungen berücksichtigt werden. Dafür werden die Stauseen in Abhängigkeit von ihrer Größe und Position in kleine und strategische Stauseen unterteilt. Dabei sind strategische Stausseen solche mit mittlerem bis großem Volumen sowie einer Lage im Hauptgerinne oder solche mit sonstiger besonderer Bedeutung. Kleine Stauseen hingegen befinden sich an den Nebenflüssen und werden im Modell in aggregierter Form durch ihre Einteilung in Stauseegrößenklassen repräsentiert. Ein Kaskadenverfahren wird für den Wasser- und Sedimentlauf zwischen den Stauseeklassen verwendet. Dabei werden für jede Stauseeklasse der Wasser- sowie Sedimenthaushalt für einen hypothetischen repräsentativen Stausee mit mittleren Eigenschaften berechnet. Die Sedimentaufnahme und die Korngrößenverteilung des abgegebenen Sediments werden mit dem Überlaufanteil-Ansatz berechnet. In dieser Studie werden drei Modellanwendungen vorgestellt: • Für den 92,2 Mio.m³-großen Barasona-Stausee (Vorland der Zentralpyrenäen, Aragon, Spanien) wird die Modellierung der Sedimentablagerung mit dem detaillierten Modellansatz vorgenommen. Die Kalibrierung dafür wurde in zwei Schritten durchgeführt, um Änderungen im Stauseemanagement Rechnung zu tragen. Die ModellValidierung wird schließlich für eine andere Simulationsperiode vorgenommen. Dabei wird ersichtlich, dass die Prozesse der Sedimentablagerung gut durch das Modell wiedergegeben werden. • Das Modell wird auf das 933 km²-große Benguê-Einzugsgebiet, das sich im semiariden Nordosten Brasiliens befindet, angewendet. Dieses Einzugsgebiet ist durch eine hohe Dichte an kleinen Stauseen, charakterisiert, die fast 45% des Gebietes umfasst, wofür jedoch wenige Messdaten verfügbar sind. Deshalb werden der Wasser- und Sedimenttransport mit dem vereinfachten Modellansatz berechnet. Dabei werden drei Konfigurationen des Kaskadenverfahrens getestet. • Die Modellanwendung erfolgt erneut für den Barasona-Stausee bezüglich der Effektivität der Sedimentmanagementmaßnahmen. Eine Kostenanalyse ermöglicht die Auswahl geeigneter Maßnahmen für den Stausee. Dadurch wird eine Beurteilung der verschiedenen Sedimentmanagementstrategien ermöglicht. Im Allgemeinen unterliegen die Simulationsergebnisse großen Unsicherheiten, teilweise wegen der geringen Datenverfügbarkeit, andererseits durch die Unsicherheiten in der Modellstruktur zur korrekten Wiedergabe der Sedimentablagerungsprozesse.
This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.
Water shortage is a serious threat for many societies worldwide. In drylands, water management measures like the construction of reservoirs are affected by eroded sediments transported in the rivers. Thus, the capability of assessing water and sediment fluxes at the river basin scale is of vital importance to support management decisions and policy making. This subject was addressed by the DFG-funded SESAM-project (Sediment Export from large Semi-Arid catchments: Measurements and Modelling). As a part of this project, this thesis focuses on (1) the development and implementation of an erosion module for a meso-scale catchment model, (2) the development of upscaling and generalization methods for the parameterization of such model, (3) the execution of measurements to obtain data required for the modelling and (4) the application of the model to different study areas and its evaluation. The research was carried out in two meso-scale dryland catchments in NE-Spain: Ribera Salada (200 km²) and Isábena (450 km²). Adressing objective 1, WASA-SED, a spatially semi-distributed model for water and sediment transport at the meso-scale was developed. The model simulates runoff and erosion processes at the hillslope scale, transport processes of suspended and bedload fluxes in the river reaches, and retention and remobilisation processes of sediments in reservoirs. This thesis introduces the model concept, presents current model applications and discusses its capabilities and limitations. Modelling at larger scales faces the dilemma of describing relevant processes while maintaining a manageable demand for input data and computation time. WASA-SED addresses this challenge by employing an innovative catena-based upscaling approach: the landscape is represented by characteristic toposequences. For deriving these toposequences with regard to multiple attributes (eg. topography, soils, vegetation) the LUMP-algorithm (Landscape Unit Mapping Program) was developed and related to objective 2. It incorporates an algorithm to retrieve representative catenas and their attributes, based on a Digital Elevation Model and supplemental spatial data. These catenas are classified to provide the discretization for the WASA-SED model. For objective 3, water and sediment fluxes were monitored at the catchment outlet of the Isábena and some of its sub-catchments. For sediment yield estimation, the intermittent measurements of suspended sediment concentration (SSC) had to be interpolated. This thesis presents a comparison of traditional sediment rating curves (SRCs), generalized linear models (GLMs) and non-parametric regression using Random Forests (RF) and Quantile Regression Forests (QRF). The observed SSCs are highly variable and range over six orders of magnitude. For these data, traditional SRCs performed poorly, as did GLMs, despite including other relevant process variables (e.g. rainfall intensities, discharge characteristics). RF and QRF proved to be very robust and performed favourably for reproducing sediment dynamics. QRF additionally excels in providing estimates on the accuracy of the predictions. Subsequent analysis showed that most of the sediment was exported during intense storms of late summer. Later floods yielded successively less sediment. Comparing sediment generation to yield at the outlet suggested considerable storage effects within the river channel. Addressing objective 4, the WASA-SED model was parameterized for the two study areas in NE Spain and applied with different foci. For Ribera Salada, the uncalibrated model yielded reasonable results for runoff and sediment. It provided quantitative measures of the change in runoff and sediment yield for different land-uses. Additional land management scenarios were presented and compared to impacts caused by climate change projections. In contrast, the application for the Isábena focussed on exploring the full potential of the model's predictive capabilities. The calibrated model achieved an acceptable performance for the validation period in terms of water and sediment fluxes. The inadequate representation of the lower sub-catchments inflicted considerable reductions on model performance, while results for the headwater catchments showed good agreement despite stark contrasts in sediment yield. In summary, the application of WASA-SED to three catchments proved the model framework to be a practicable multi-scale approach. It successfully links the hillslope to the catchment scale and integrates the three components hillslope, river and reservoir in one model. Thus, it provides a feasible approach for tackling issues of water and sediment yield at the meso-scale. The crucial role of processes like transmission losses and sediment storage in the river has been identified. Further advances can be expected when the representation of connectivity of water and sediment fluxes (intra-hillslope, hillslope-river, intra-river) is refined and input data improves.
Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (Müggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.
Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment.
Despite the importance of rhizosphere properties for water flow from soil to roots, there is limited quantitative information on the distribution of water in the rhizosphere of plants.
Here, we used neutron tomography to quantify and visualize the water content in the rhizosphere of the plant species chickpea (Cicer arietinum), white lupin (Lupinus albus), and maize (Zea mays) 12 d after planting.
We clearly observed increasing soil water contents (h) towards the root surface for all three plant species, as opposed to the usual assumption of decreasing water content. This was true for tap roots and lateral roots of both upper and lower parts of the root system. Furthermore, water gradients around the lower part of the roots were smaller and extended further into bulk soil compared with the upper part, where the gradients in water content were steeper.
Incorporating the hydraulic conductivity and water retention parameters of the rhizosphere into our model, we could simulate the gradual changes of h towards the root surface, in agreement with the observations. The modelling result suggests that roots in their rhizosphere may modify the hydraulic properties of soil in a way that improves uptake under dry conditions.
Adipositas ist eine chronische Erkrankung mit erheblichen Komorbiditäten und Folgeschäden, die bereits im Kindes- und Jugendalter weit verbreitet ist. Unterschiedliche Faktoren sind an der Ätiologie dieser Störung beteiligt. Die Ernährung stellt dabei eine der Hauptsäulen dar, auf welche immer wieder Bezug genommen wird. Der Einfluss der Eltern auf die kindliche Ernährung spielt unbestritten eine zentrale Rolle – hinsichtlich genetischer Dispositionen, aber auch als Gestalter der Lebensumwelten und Vorbilder im Ernährungsbereich. Die vorliegende Arbeit hat zum Ziel, Übereinstimmungen elterlicher und kindlicher Ernährung zu untersuchen und dabei zu prüfen, inwiefern Prozesse des Modelllernens für die Zusammenhänge verantwortlich zeichnen. Grundlage ist die sozial-kognitive Theorie Albert Banduras mit dem Fokus auf seinen Ausführungen zum Beobachtungs- oder Modelllernen. Die Zusammenhänge elterlicher und kindlicher Ernährung wurden anhand einer Stichprobe 7 – 13-jähriger adipöser Kinder und ihrer Eltern in Beziehung gesetzt zu den Bedingungen des Modelllernens, die zuvor auch in anderen Studien gefunden worden waren. Eine hohe Ähnlichkeit oder gute Beziehung zwischen Modell (Mutter bzw. Vater) und Lernendem (Kind) sollte demnach moderierend auf die Stärke des Zusammenhangs wirken. Aus Banduras Ausführungen zu den Phasen des Modelllernens ergibt sich zudem ein dritter Aspekt, der in das Untersuchungsmodell einbezogen wurde. Die von Bandura postulierte Aneignungsphase setzt voraus, dass das zu lernende Verhalten auch beobachtet werden kann. Aus diesem Grund sollte die Analyse von Zusammenhängen im Verhalten nicht losgelöst von der Zeit betrachtet werden, die Modell und Beobachter miteinander verbringen bzw. verbracht haben. Zudem wurde die Wahrnehmung eines Elternteils als Vorbild beim Kind erfragt und als Moderator aufgenommen. In die Analysen eingeschlossen wurden vollständige Mutter-Vater-Kind-Triaden. Im Querschnitt der Fragebogenerhebung waren die Daten von 171 Mädchen und 176 Jungen, in einem 7 Monate darauf folgenden Längsschnitt insgesamt 75 Triaden (davon 38 Mädchen) enthalten. Es zeigte sich ein positiver Zusammenhang zwischen der kindlichen und mütterlichen Ernährung ebenso wie zwischen der kindlichen und väterlichen Ernährung. Die Übereinstimmungen zwischen Mutter und Kind waren größer als zwischen Vater und Kind. Überwiegend bestätigt werden konnten der moderierende Einfluss der Beziehungsqualität und der Vorbildwahrnehmung auf die Zusammenhänge elterlicher und kindlicher gesunder Ernährung und der Einfluss gemeinsam verbrachter Zeit vor allem in Bezug auf Vater-Kind-Zusammenhänge problematischer Ernährung. Der väterliche Einfluss, der sowohl in Studien als auch in präventiven oder therapeutischen Angeboten oft noch vernachlässigt wird und in vorliegender Arbeit besondere bzw. gleichberechtigte Beachtung fand, zeigte sich durch den Einbezug moderierender Variablen verstärkt. Eine Ansprache von Müttern und Vätern gleichermaßen ist somit unbedingtes Ziel bei der Prävention und Therapie kindlicher Adipositas. Auch jenseits des Adipositaskontextes sollten Eltern für die Bedeutung elterlicher Vorbildwirkung sensibilisiert werden, um eine gesunde Ernährungsweise ihrer Kinder zu fördern.
Systems of Systems (SoS) have received a lot of attention recently. In this thesis we will focus on SoS that are built atop the techniques of Service-Oriented Architectures and thus combine the benefits and challenges of both paradigms. For this thesis we will understand SoS as ensembles of single autonomous systems that are integrated to a larger system, the SoS. The interesting fact about these systems is that the previously isolated systems are still maintained, improved and developed on their own. Structural dynamics is an issue in SoS, as at every point in time systems can join and leave the ensemble. This and the fact that the cooperation among the constituent systems is not necessarily observable means that we will consider these systems as open systems. Of course, the system has a clear boundary at each point in time, but this can only be identified by halting the complete SoS. However, halting a system of that size is practically impossible. Often SoS are combinations of software systems and physical systems. Hence a failure in the software system can have a serious physical impact what makes an SoS of this kind easily a safety-critical system. The contribution of this thesis is a modelling approach that extends OMG's SoaML and basically relies on collaborations and roles as an abstraction layer above the components. This will allow us to describe SoS at an architectural level. We will also give a formal semantics for our modelling approach which employs hybrid graph-transformation systems. The modelling approach is accompanied by a modular verification scheme that will be able to cope with the complexity constraints implied by the SoS' structural dynamics and size. Building such autonomous systems as SoS without evolution at the architectural level --- i. e. adding and removing of components and services --- is inadequate. Therefore our approach directly supports the modelling and verification of evolution.