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Three Essays on EFRAG
(2018)
This cumulative doctoral thesis consists of three papers that deal with the role of one specific European accounting player in the international accounting standard-setting, namely the European Financial Reporting Advisory Group (EFRAG). The first paper examines whether and how EFRAG generally fulfills its role in articulating Europe’s interests toward the International Accounting Standards Board (IASB). The qualitative data from the conducted interviews reveal that EFRAG influences the IASB’s decision making at a very early stage, long before other constituents are officially asked to comment on the IASB’s proposals. The second paper uses quantitative data and investigates the formal participation behavior of European constituents that seek to determine EFRAG’s voice. More precisely, this paper analyzes the nature of the constituents’ participation in EFRAG’s due process in terms of representation (constituent groups and geographical distribution) and the drivers of their participation behavior. EFRAG’s official decision making process is dominated by some specific constituent groups (such as preparers and the accounting profession) and by constituents from some specific countries (e.g. those with effective enforcement regimes). The third paper investigates in a first step who of the European constituents choose which lobbying channel (participation only at IASB, only at EFRAG, or at both institutions) and unveils in a second step possible reasons for their lobbying choices. The paper comprises quantitative and qualitative data. It reveals that English skills, time issues, the size of the constituent, and the country of origin are factors that can explain why the majority participates only in the IASB’s due process.
In the present thesis, the self-assembly of multi thermoresponsive block copolymers in dilute aqueous solution was investigated by a combination of turbidimetry, dynamic light scattering, TEM measurements, NMR as well as fluorescence spectroscopy. The successive conversion of such block copolymers from a hydrophilic into a hydrophobic state includes intermediate amphiphilic states with a variable hydrophilic-to-lipophilic balance. As a result, the self-organization is not following an all-or-none principle but a multistep aggregation in dilute solution was observed. The synthesis of double thermoresponsive diblock copolymers as well as triple thermoresponsive triblock copolymers was realized using twofold-TMS labeled RAFT agents which provide direct information about the average molar mass as well as residual end group functionality from a routine proton NMR spectrum. First a set of double thermosensitive diblock copolymers poly(N-n-propylacrylamide)-b-poly(N-ethylacrylamide) was synthesized which differed only in the relative size of the two blocks. Depending on the relative block lengths, different aggregation pathways were found. Furthermore, the complementary TMS-labeled end groups served as NMR-probes for the self-assembly of these diblock copolymers in dilute solution. Reversible, temperature sensitive peak splitting of the TMS-signals in NMR spectroscopy was indicative for the formation of mixed star-/flower-like micelles in some cases. Moreover, triple thermoresponsive triblock copolymers from poly(N-n-propylacrylamide) (A), poly(methoxydiethylene glycol acrylate) (B) and poly(N-ethylacrylamide) (C) were obtained from sequential RAFT polymerization in all possible block sequences (ABC, BAC, ACB). Their self-organization behavior in dilute aqueous solution was found to be rather complex and dependent on the positioning of the different blocks within the terpolymers. Especially the localization of the low-LCST block (A) had a large influence on the aggregation behavior. Above the first cloud point, aggregates were only observed when the A block was located at one terminus. Once placed in the middle, unimolecular micelles were observed which showed aggregation only above the second phase transition temperature of the B block. Carrier abilities of such triple thermosensitive triblock copolymers tested in fluorescence spectroscopy, using the solvatochromic dye Nile Red, suggested that the hydrophobic probe is less efficiently incorporated by the polymer with the BAC sequence as compared to ABC or ACB polymers above the first phase transition temperature. In addition, due to the problem of increasing loss of end group functionality during the subsequent polymerization steps, a novel concept for the one-step synthesis of multi thermoresponsive block copolymers was developed. This allowed to synthesize double thermoresponsive di- and triblock copolymers in a single polymerization step. The copolymerization of different N-substituted maleimides with a thermosensitive styrene derivative (4-vinylbenzyl methoxytetrakis(oxyethylene) ether) led to alternating copolymers with variable LCST. Consequently, an excess of this styrene-based monomer allowed the synthesis of double thermoresponsive tapered block copolymers in a single polymerization step.
Business Process Management (BPM) emerged as a means to control, analyse, and optimise business operations. Conceptual models are of central importance for BPM. Most prominently, process models define the behaviour that is performed to achieve a business value. In essence, a process model is a mapping of properties of the original business process to the model, created for a purpose. Different modelling purposes, therefore, result in different models of a business process. Against this background, the misalignment of process models often observed in the field of BPM is no surprise. Even if the same business scenario is considered, models created for strategic decision making differ in content significantly from models created for process automation. Despite their differences, process models that refer to the same business process should be consistent, i.e., free of contradictions. Apparently, there is a trade-off between strictness of a notion of consistency and appropriateness of process models serving different purposes. Existing work on consistency analysis builds upon behaviour equivalences and hierarchical refinements between process models. Hence, these approaches are computationally hard and do not offer the flexibility to gradually relax consistency requirements towards a certain setting. This thesis presents a framework for the analysis of behaviour consistency that takes a fundamentally different approach. As a first step, an alignment between corresponding elements of related process models is constructed. Then, this thesis conducts behavioural analysis grounded on a relational abstraction of the behaviour of a process model, its behavioural profile. Different variants of these profiles are proposed, along with efficient computation techniques for a broad class of process models. Using behavioural profiles, consistency of an alignment between process models is judged by different notions and measures. The consistency measures are also adjusted to assess conformance of process logs that capture the observed execution of a process. Further, this thesis proposes various complementary techniques to support consistency management. It elaborates on how to implement consistent change propagation between process models, addresses the exploration of behavioural commonalities and differences, and proposes a model synthesis for behavioural profiles.
Interpretation of and reasoning with conditionals : probabilities, mental models, and causality
(2003)
In everyday conversation "if" is one of the most frequently used conjunctions. This dissertation investigates what meaning an everyday conditional transmits and what inferences it licenses. It is suggested that the nature of the relation between the two propositions in a conditional might play a major role for both questions. Thus, in the experiments reported here conditional statements that describe a causal relationship (e.g., "If you touch that wire, you will receive an electric shock") were compared to arbitrary conditional statements in which there is no meaningful relation between the antecedent and the consequent proposition (e.g., "If Napoleon is dead, then Bristol is in England"). Initially, central assumptions from several approaches to the meaning and the reasoning from causal conditionals will be integrated into a common model. In the model the availability of exceptional situations that have the power to generate exceptions to the rule described in the conditional (e.g., the electricity is turned off), reduces the subjective conditional probability of the consequent, given the antecedent (e.g., the probability of receiving an electric shock when touching the wire). This conditional probability determines people's degree of belief in the conditional, which in turn affects their willingness to accept valid inferences (e.g., "Peter touches the wire, therefore he receives an electric shock") in a reasoning task. Additionally to this indirect pathway, the model contains a direct pathway: Cognitive availability of exceptional situations directly reduces the readiness to accept valid conclusions. The first experimental series tested the integrated model for conditional statements embedded in pseudo-natural cover stories that either established a causal relation between the antecedent and the consequent event (causal conditionals) or did not connect the propositions in a meaningful way (arbitrary conditionals). The model was supported for the causal, but not for the arbitrary conditional statements. Furthermore, participants assigned lower degrees of belief to arbitrary than to causal conditionals. Is this effect due to the presence versus absence of a semantic link between antecedent and consequent in the conditionals? This question was one of the starting points for the second experimental series. Here, the credibility of the conditionals was manipulated by adding explicit frequency information about possible combinations of presence or absence of antecedent and consequent events to the problems (i.e., frequencies of cases of 1. true antecedent with true consequent, 2. true antecedent with false consequent, 3. false antecedent with true consequent, 4. false antecedent with false consequent). This paradigm allows testing different approaches to the meaning of conditionals (Experiment 4) as well as theories of conditional reasoning against each other (Experiment 5). The results of Experiment 4 supported mainly the conditional probability approach to the meaning of conditionals (Edgington, 1995) according to which the degree of belief a listener has in a conditional statement equals the conditional probability that the consequent is true given the antecedent (e.g., the probability of receiving an electric shock when touching the wire). Participants again assigned lower degrees of belief to the arbitrary than the causal conditionals, although the conditional probability of the consequent given the antecedent was held constant within every condition of explicit frequency information. This supports the hypothesis that the mere presence of a causal link enhances the believability of a conditional statement. In Experiment 5 participants solved conditional reasoning tasks from problems that contained explicit frequency information about possible relevant cases. The data favored the probabilistic approach to conditional reasoning advanced by Oaksford, Chater, and Larkin (2000). The two experimental series reported in this dissertation provide strong support for recent probabilistic theories: for the conditional probability approach to the meaning of conditionals by Edgington (1995) and the probabilistic approach to conditional reasoning by Oaksford et al. (2000). In the domain of conditional reasoning, there was additionally support for the modified mental model approaches by Markovits and Barrouillet (2002) and Schroyens and Schaeken (2003). Probabilistic and mental model approaches could be reconciled within a dual-process-model as suggested by Verschueren, Schaeken, and d'Ydewalle (2003).
The aim of this thesis is the design, expression and purification of human cytochrome c mutants and their characterization with regard to electrochemical and structural properties as well as with respect to the reaction with the superoxide radical and the selected proteins sulfite oxidase from human and fungi bilirubin oxidase. All three interaction partners are studied here for the first time with human cyt c and with mutant forms of cyt c. A further aim is the incorporation of the different cyt c forms in two bioelectronic systems: an electrochemical superoxide biosensor with an enhanced sensitivity and a protein multilayer assembly with and without bilirubin oxidase on electrodes. The first part of the thesis is dedicated to the design, expression and characterization of the mutants. A focus is here the electrochemical characterization of the protein in solution and immobilized on electrodes. Further the reaction of these mutants with superoxide was investigated and the possible reaction mechanisms are discussed. In the second part of the work an amperometric superoxide biosensor with selected human cytochrome c mutants was constructed and the performance of the sensor electrodes was studied. The human wild-type and four of the five mutant electrodes could be applied successfully for the detection of the superoxide radical. In the third part of the thesis the reaction of horse heart cyt c, the human wild-type and seven human cyt c mutants with the two proteins sulfite oxidase and bilirubin oxidase was studied electrochemically and the influence of the mutations on the electron transfer reactions was discussed. Finally protein multilayer electrodes with different cyt form including the mutant forms G77K and N70K which exhibit different reaction rates towards BOD were investigated and BOD together with the wild-type and engineered cyt c was embedded in the multilayer assembly. The relevant electron transfer steps and the kinetic behavior of the multilayer electrodes are investigated since the functionality of electroactive multilayer assemblies with incorporated redox proteins is often limited by the electron transfer abilities of the proteins within the multilayer. The formation via the layer-by-layer technique and the kinetic behavior of the mono and bi-protein multilayer system are studied by SPR and cyclic voltammetry. In conclusion this thesis shows that protein engineering is a helpful instrument to study protein reactions as well as electron transfer mechanisms of complex bioelectronic systems (such as bi-protein multilayers). Furthermore, the possibility to design tailored recognition elements for the construction of biosensors with an improved performance is demonstrated.
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.
The Yukon Coast in Canada is an ice-rich permafrost coast and highly sensitive to changing environmental conditions. Retrogressive thaw slumps are a common thermoerosion feature along this coast, and develop through the thawing of exposed ice-rich permafrost on slopes and removal of accumulating debris. They contribute large amounts of sediment, including organic carbon and nitrogen, to the nearshore zone.
The objective of this study was to 1) identify the climatic and geomorphological drivers of sediment-meltwater release, 2) quantify the amount of released meltwater, sediment, organic carbon and nitrogen, and 3) project the evolution of sediment-meltwater release of retrogressive thaw slumps in a changing future climate.
The analysis is based on data collected over 18 days in July 2013 and 18 days in August 2012. A cut-throat flume was set up in the main sediment-meltwater channel of the largest retrogressive thaw slump on Herschel Island. In addition, two weather stations, one on top of the undisturbed tundra and one on the slump floor, measured incoming solar radiation, air temperature, wind speed and precipitation. The discharge volume eroding from the ice-rich permafrost and retreating snowbanks was measured and compared to the meteorological data collected in real time with a resolution of one minute.
The results show that the release of sediment-meltwater from thawing of the ice-rich permafrost headwall is strongly related to snowmelt, incoming solar radiation and air temperature. Snowmelt led to seasonal differences, especially due to the additional contribution of water to the eroding sediment-meltwater from headwall ablation, lead to dilution of the sediment-meltwater composition. Incoming solar radiation and air temperature were the main drivers for diurnal and inter-diurnal fluctuations. In July (2013), the retrogressive thaw slump released about 25 000 m³ of sediment-meltwater, containing 225 kg dissolved organic carbon and 2050 t of sediment, which in turn included 33 t organic carbon, and 4 t total nitrogen. In August (2012), just 15 600 m³ of sediment-meltwater was released, since there was no additional contribution from snowmelt. However, even without the additional dilution, 281 kg dissolved organic carbon was released. The sediment concentration was twice as high as in July, with sediment contents of up to 457 g l-1 and 3058 t of sediment, including 53 t organic carbon and 5 t nitrogen, being released.
In addition, the data from the 36 days of observations from Slump D were upscaled to cover the main summer season of 1 July to 31 August (62 days) and to include all 229 active retrogressive thaw slumps along the Yukon Coast. In total, all retrogressive thaw slumps along the Yukon Coast contribute a minimum of 1.4 Mio. m³ sediment-meltwater each thawing season, containing a minimum of 172 000 t sediment with 3119 t organic carbon, 327 t nitrogen and 17 t dissolved organic carbon. Therefore, in addition to the coastal erosion input to the Beaufort Sea, retrogressive thaw slumps additionally release 3 % of sediment and 8 % of organic carbon into the ocean. Finally, the future evolution of retrogressive thaw slumps under a warming scenario with summer air temperatures increasing by 2-3 °C by 2081-2100, would lead to an increase of 109-114% in release of sediment-meltwater.
It can be concluded that retrogressive thaw slumps are sensitive to climatic conditions and under projected future Arctic warming will contribute larger amounts of thawed permafrost material (including organic carbon and nitrogen) into the environment.
Multi-messenger constraints and pressure from dark matter annihilation into electron-positron pairs
(2013)
Despite striking evidence for the existence of dark matter from astrophysical observations, dark matter has still escaped any direct or indirect detection until today. Therefore a proof for its existence and the revelation of its nature belongs to one of the most intriguing challenges of nowadays cosmology and particle physics. The present work tries to investigate the nature of dark matter through indirect signatures from dark matter annihilation into electron-positron pairs in two different ways, pressure from dark matter annihilation and multi-messenger constraints on the dark matter annihilation cross-section. We focus on dark matter annihilation into electron-positron pairs and adopt a model-independent approach, where all the electrons and positrons are injected with the same initial energy E_0 ~ m_dm*c^2. The propagation of these particles is determined by solving the diffusion-loss equation, considering inverse Compton scattering, synchrotron radiation, Coulomb collisions, bremsstrahlung, and ionization. The first part of this work, focusing on pressure from dark matter annihilation, demonstrates that dark matter annihilation into electron-positron pairs may affect the observed rotation curve by a significant amount. The injection rate of this calculation is constrained by INTEGRAL, Fermi, and H.E.S.S. data. The pressure of the relativistic electron-positron gas is computed from the energy spectrum predicted by the diffusion-loss equation. For values of the gas density and magnetic field that are representative of the Milky Way, it is estimated that the pressure gradients are strong enough to balance gravity in the central parts if E_0 < 1 GeV. The exact value depends somewhat on the astrophysical parameters, and it changes dramatically with the slope of the dark matter density profile. For very steep slopes, as those expected from adiabatic contraction, the rotation curves of spiral galaxies would be affected on kiloparsec scales for most values of E_0. By comparing the predicted rotation curves with observations of dwarf and low surface brightness galaxies, we show that the pressure from dark matter annihilation may improve the agreement between theory and observations in some cases, but it also imposes severe constraints on the model parameters (most notably, the inner slope of the halo density profile, as well as the mass and the annihilation cross-section of dark matter particles into electron-positron pairs). In the second part, upper limits on the dark matter annihilation cross-section into electron-positron pairs are obtained by combining observed data at different wavelengths (from Haslam, WMAP, and Fermi all-sky intensity maps) with recent measurements of the electron and positron spectra in the solar neighbourhood by PAMELA, Fermi, and H.E.S.S.. We consider synchrotron emission in the radio and microwave bands, as well as inverse Compton scattering and final-state radiation at gamma-ray energies. For most values of the model parameters, the tightest constraints are imposed by the local positron spectrum and synchrotron emission from the central regions of the Galaxy. According to our results, the annihilation cross-section should not be higher than the canonical value for a thermal relic if the mass of the dark matter candidate is smaller than a few GeV. In addition, we also derive a stringent upper limit on the inner logarithmic slope α of the density profile of the Milky Way dark matter halo (α < 1 if m_dm < 5 GeV, α < 1.3 if m_dm < 100 GeV and α < 1.5 if m_dm < 2 TeV) assuming a dark matter annihilation cross-section into electron-positron pairs (σv) = 3*10^−26 cm^3 s^−1, as predicted for thermal relics from the big bang.
Robotic telescopes & Doppler imaging : measuring differential rotation on long-period active stars
(2004)
The sun shows a wide variety of magnetic-activity related phenomena. The magnetic field responsible for this is generated by a dynamo process which is believed to operate in the tachocline, which is located at the bottom of the convection zone. This dynamo is driven in part by differential rotation and in part by magnetic turbulences in the convection zone. The surface differential rotation, one key ingredient of dynamo theory, can be measured by tracing sunspot positions.To extend the parameter space for dynamo theories, one can extend these measurements to other stars than the sun. The primary obstacle in this endeavor is the lack of resolved surface images on other stars. This can be overcome by the Doppler imaging technique, which uses the rotation-induced Doppler-broadening of spectral lines to compute the surface distribution of a physical parameter like temperature. To obtain the surface image of a star, high-resolution spectroscopic observations, evenly distributed over one stellar rotation period are needed. This turns out to be quite complicated for long period stars. The upcoming robotic observatory STELLA addresses this problem with a dedicated scheduling routine, which is tailored for Doppler imaging targets. This will make observations for Doppler imaging not only easier, but also more efficient.As a preview of what can be done with STELLA, we present results of a Doppler imaging study of seven stars, all of which show evidence for differential rotation, but unfortunately the errors are of the same order of magnitude as the measurements due to unsatisfactory data quality, something that will not happen on STELLA. Both, cross-correlation analysis and the sheared image technique where used to double check the results if possible. For four of these stars, weak anti-solar differential rotation was found in a sense that the pole rotates faster than the equator, for the other three stars weak differential rotation in the same direction as on the sun was found.Finally, these new measurements along with other published measurements of differential rotation using Doppler imaging, were analyzed for correlations with stellar evolution, binarity, and rotation period. The total sample of stars show a significant correlation with rotation period, but if separated into antisolar and solar type behavior, only the subsample showing anti-solar differential rotation shows this correlation. Additionally, there is evidence for binary stars showing less differential rotation as single stars, as is suggested by theory. All other parameter combinations fail to deliver any results due to the still small sample of stars available.
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.