6 resultados para Spatiotemporal change model

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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To determine the size dependence of the bonding in divalent-metal clusters we use a many-electron Hamiltonian describing the interplay between van der Waals (vdW) and covalent interactions. Using a saddle-point slave-boson method and taking into account the size-dependent screening of charge fluctuations, we obtain for Hg_n a sharp transition from vdW to covalent bonding for increasing n. We show also, by solving the model Hamiltonian exactly, that for divalent metals vdW and covalent bonding coexist already in the dimers.

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Using a phenomenological model, the influence of quantum electrodynamical effects on the prediction of the chemical behavior of superheavy elements within a relativistic Dirac-Slater calculation was investigated. This influence will be small and nondetectable for elements up to Z = 114. For elements near Z = 164 some changes in the ground state configurations occur but the chemical behavior will not change. Using this heuristic model, it is also possible to calculate elements beyond Z = 175. As an example we have chosen element E184 and are now able to make more valid speculations about the chemical behavior of the element than Penneman and co-workers could.

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Land use has become a force of global importance, considering that 34% of the Earth’s ice-free surface was covered by croplands or pastures in 2000. The expected increase in global human population together with eminent climate change and associated search for energy sources other than fossil fuels can, through land-use and land-cover changes (LUCC), increase the pressure on nature’s resources, further degrade ecosystem services, and disrupt other planetary systems of key importance to humanity. This thesis presents four modeling studies on the interplay between LUCC, increased production of biofuels and climate change in four selected world regions. In the first study case two new crop types (sugarcane and jatropha) are parameterized in the LPJ for managed Lands dynamic global vegetation model for calculation of their potential productivity. Country-wide spatial variation in the yields of sugarcane and jatropha incurs into substantially different land requirements to meet the biofuel production targets for 2015 in Brazil and India, depending on the location of plantations. Particularly the average land requirements for jatropha in India are considerably higher than previously estimated. These findings indicate that crop zoning is important to avoid excessive LUCC. In the second study case the LandSHIFT model of land-use and land-cover changes is combined with life cycle assessments to investigate the occurrence and extent of biofuel-driven indirect land-use changes (ILUC) in Brazil by 2020. The results show that Brazilian biofuels can indeed cause considerable ILUC, especially by pushing the rangeland frontier into the Amazonian forests. The carbon debt caused by such ILUC would result in no carbon savings (from using plant-based ethanol and biodiesel instead of fossil fuels) before 44 years for sugarcane ethanol and 246 years for soybean biodiesel. The intensification of livestock grazing could avoid such ILUC. We argue that such an intensification of livestock should be supported by the Brazilian biofuel sector, based on the sector’s own interest in minimizing carbon emissions. In the third study there is the development of a new method for crop allocation in LandSHIFT, as influenced by the occurrence and capacity of specific infrastructure units. The method is exemplarily applied in a first assessment of the potential availability of land for biogas production in Germany. The results indicate that Germany has enough land to fulfill virtually all (90 to 98%) its current biogas plant capacity with only cultivated feedstocks. Biogas plants located in South and Southwestern (North and Northeastern) Germany might face more (less) difficulties to fulfill their capacities with cultivated feedstocks, considering that feedstock transport distance to plants is a crucial issue for biogas production. In the fourth study an adapted version of LandSHIFT is used to assess the impacts of contrasting scenarios of climate change and conservation targets on land use in the Brazilian Amazon. Model results show that severe climate change in some regions by 2050 can shift the deforestation frontier to areas that would experience low levels of human intervention under mild climate change (such as the western Amazon forests or parts of the Cerrado savannas). Halting deforestation of the Amazon and of the Brazilian Cerrado would require either a reduction in the production of meat or an intensification of livestock grazing in the region. Such findings point out the need for an integrated/multicisciplinary plan for adaptation to climate change in the Amazon. The overall conclusions of this thesis are that (i) biofuels must be analyzed and planned carefully in order to effectively reduce carbon emissions; (ii) climate change can have considerable impacts on the location and extent of LUCC; and (iii) intensification of grazing livestock represents a promising venue for minimizing the impacts of future land-use and land-cover changes in Brazil.

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The Upper Blue Nile River Basin (UBNRB) located in the western part of Ethiopia, between 7° 45’ and 12° 45’N and 34° 05’ and 39° 45’E has a total area of 174962 km2 . More than 80% of the population in the basin is engaged in agricultural activities. Because of the particularly dry climate in the basin, likewise to most other regions of Ethiopia, the agricultural productivity depends to a very large extent on the occurrence of the seasonal rains. This situation makes agriculture highly vulnerable to the impact of potential climate hazards which are about to inflict Africa as a whole and Ethiopia in particular. To analyze these possible impacts of future climate change on the water resources in the UBNRB, in the first part of the thesis climate projection for precipitation, minimum and maximum temperatures in the basin, using downscaled predictors from three GCMs (ECHAM5, GFDL21 and CSIRO-MK3) under SRES scenarios A1B and A2 have been carried out. The two statistical downscaling models used are SDSM and LARS-WG, whereby SDSM is used to downscale ECHAM5-predictors alone and LARS-WG is applied in both mono-model mode with predictors from ECHAM5 and in multi-model mode with combined predictors from ECHAM5, GFDL21 and CSIRO-MK3. For the calibration/validation of the downscaled models, observed as well as NCEP climate data in the 1970 - 2000 reference period is used. The future projections are made for two time periods; 2046-2065 (2050s) and 2081-2100 (2090s). For the 2050s future time period the downscaled climate predictions indicate rise of 0.6°C to 2.7°C for the seasonal maximum temperatures Tmax, and of 0.5°C to 2.44°C for the minimum temperatures Tmin. Similarly, during the 2090s the seasonal Tmax increases by 0.9°C to 4.63°C and Tmin by 1°C to 4.6°C, whereby these increases are generally higher for the A2 than for the A1B scenario. For most sub-basins of the UBNRB, the predicted changes of Tmin are larger than those of Tmax. Meanwhile, for the precipitation, both downscaling tools predict large changes which, depending on the GCM employed, are such that the spring and summer seasons will be experiencing decreases between -36% to 1% and the autumn and winter seasons an increase of -8% to 126% for the two future time periods, regardless of the SRES scenario used. In the second part of the thesis the semi-distributed, physically based hydrologic model, SWAT (Soil Water Assessment Tool), is used to evaluate the impacts of the above-predicted future climate change on the hydrology and water resources of the UBNRB. Hereby the downscaled future predictors are used as input in the SWAT model to predict streamflow of the Upper Blue Nile as well as other relevant water resources parameter in the basin. Calibration and validation of the streamflow model is done again on 1970-2000 measured discharge at the outlet gage station Eldiem, whereby the most sensitive out the numerous “tuneable” calibration parameters in SWAT have been selected by means of a sophisticated sensitivity analysis. Consequently, a good calibration/validation model performance with a high NSE-coefficient of 0.89 is obtained. The results of the future simulations of streamflow in the basin, using both SDSM- and LARS-WG downscaled output in SWAT reveal a decline of -10% to -61% of the future Blue Nile streamflow, And, expectedly, these obviously adverse effects on the future UBNRB-water availibiliy are more exacerbated for the 2090’s than for the 2050’s, regardless of the SRES.

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The possibility to develop automatically running models which can capture some of the most important factors driving the urban climate would be very useful for many planning aspects. With the help of these modulated climate data, the creation of the typically used “Urban Climate Maps” (UCM) will be accelerated and facilitated. This work describes the development of a special ArcGIS software extension, along with two support databases to achieve this functionality. At the present time, lacking comparability between different UCMs and imprecise planning advices going along with the significant technical problems of manually creating conventional maps are central issues. Also inflexibility and static behaviour are reducing the maps’ practicality. From experi-ence, planning processes are formed more productively, namely to implant new planning parameters directly via the existing work surface to map the impact of the data change immediately, if pos-sible. In addition to the direct climate figures, information of other planning areas (like regional characteristics / developments etc.) have to be taken into account to create the UCM as well. Taking all these requirements into consideration, an automated calculation process of urban climate impact parameters will serve to increase the creation of homogenous UCMs efficiently.

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In den letzten Jahrzehnten haben sich makroskalige hydrologische Modelle als wichtige Werkzeuge etabliert um den Zustand der globalen erneuerbaren Süßwasserressourcen flächendeckend bewerten können. Sie werden heutzutage eingesetzt um eine große Bandbreite wissenschaftlicher Fragestellungen zu beantworten, insbesondere hinsichtlich der Auswirkungen anthropogener Einflüsse auf das natürliche Abflussregime oder der Auswirkungen des globalen Wandels und Klimawandels auf die Ressource Wasser. Diese Auswirkungen lassen sich durch verschiedenste wasserbezogene Kenngrößen abschätzen, wie z.B. erneuerbare (Grund-)Wasserressourcen, Hochwasserrisiko, Dürren, Wasserstress und Wasserknappheit. Die Weiterentwicklung makroskaliger hydrologischer Modelle wurde insbesondere durch stetig steigende Rechenkapazitäten begünstigt, aber auch durch die zunehmende Verfügbarkeit von Fernerkundungsdaten und abgeleiteten Datenprodukten, die genutzt werden können, um die Modelle anzutreiben und zu verbessern. Wie alle makro- bis globalskaligen Modellierungsansätze unterliegen makroskalige hydrologische Simulationen erheblichen Unsicherheiten, die (i) auf räumliche Eingabedatensätze, wie z.B. meteorologische Größen oder Landoberflächenparameter, und (ii) im Besonderen auf die (oftmals) vereinfachte Abbildung physikalischer Prozesse im Modell zurückzuführen sind. Angesichts dieser Unsicherheiten ist es unabdingbar, die tatsächliche Anwendbarkeit und Prognosefähigkeit der Modelle unter diversen klimatischen und physiographischen Bedingungen zu überprüfen. Bisher wurden die meisten Evaluierungsstudien jedoch lediglich in wenigen, großen Flusseinzugsgebieten durchgeführt oder fokussierten auf kontinentalen Wasserflüssen. Dies steht im Kontrast zu vielen Anwendungsstudien, deren Analysen und Aussagen auf simulierten Zustandsgrößen und Flüssen in deutlich feinerer räumlicher Auflösung (Gridzelle) basieren. Den Kern der Dissertation bildet eine umfangreiche Evaluierung der generellen Anwendbarkeit des globalen hydrologischen Modells WaterGAP3 für die Simulation von monatlichen Abflussregimen und Niedrig- und Hochwasserabflüssen auf Basis von mehr als 2400 Durchflussmessreihen für den Zeitraum 1958-2010. Die betrachteten Flusseinzugsgebiete repräsentieren ein breites Spektrum klimatischer und physiographischer Bedingungen, die Einzugsgebietsgröße reicht von 3000 bis zu mehreren Millionen Quadratkilometern. Die Modellevaluierung hat dabei zwei Zielsetzungen: Erstens soll die erzielte Modellgüte als Bezugswert dienen gegen den jegliche weiteren Modellverbesserungen verglichen werden können. Zweitens soll eine Methode zur diagnostischen Modellevaluierung entwickelt und getestet werden, die eindeutige Ansatzpunkte zur Modellverbesserung aufzeigen soll, falls die Modellgüte unzureichend ist. Hierzu werden komplementäre Modellgütemaße mit neun Gebietsparametern verknüpft, welche die klimatischen und physiographischen Bedingungen sowie den Grad anthropogener Beeinflussung in den einzelnen Einzugsgebieten quantifizieren. WaterGAP3 erzielt eine mittlere bis hohe Modellgüte für die Simulation von sowohl monatlichen Abflussregimen als auch Niedrig- und Hochwasserabflüssen, jedoch sind für alle betrachteten Modellgütemaße deutliche räumliche Muster erkennbar. Von den neun betrachteten Gebietseigenschaften weisen insbesondere der Ariditätsgrad und die mittlere Gebietsneigung einen starken Einfluss auf die Modellgüte auf. Das Modell tendiert zur Überschätzung des jährlichen Abflussvolumens mit steigender Aridität. Dieses Verhalten ist charakteristisch für makroskalige hydrologische Modelle und ist auf die unzureichende Abbildung von Prozessen der Abflussbildung und –konzentration in wasserlimitierten Gebieten zurückzuführen. In steilen Einzugsgebieten wird eine geringe Modellgüte hinsichtlich der Abbildung von monatlicher Abflussvariabilität und zeitlicher Dynamik festgestellt, die sich auch in der Güte der Niedrig- und Hochwassersimulation widerspiegelt. Diese Beobachtung weist auf notwendige Modellverbesserungen in Bezug auf (i) die Aufteilung des Gesamtabflusses in schnelle und verzögerte Abflusskomponente und (ii) die Berechnung der Fließgeschwindigkeit im Gerinne hin. Die im Rahmen der Dissertation entwickelte Methode zur diagnostischen Modellevaluierung durch Verknüpfung von komplementären Modellgütemaßen und Einzugsgebietseigenschaften wurde exemplarisch am Beispiel des WaterGAP3 Modells erprobt. Die Methode hat sich als effizientes Werkzeug erwiesen, um räumliche Muster in der Modellgüte zu erklären und Defizite in der Modellstruktur zu identifizieren. Die entwickelte Methode ist generell für jedes hydrologische Modell anwendbar. Sie ist jedoch insbesondere für makroskalige Modelle und multi-basin Studien relevant, da sie das Fehlen von feldspezifischen Kenntnissen und gezielten Messkampagnen, auf die üblicherweise in der Einzugsgebietsmodellierung zurückgegriffen wird, teilweise ausgleichen kann.