Experimentelle und numerische Untersuchungen zur Dispersion von Dichteströmungen in einem stochastischen Modellaquifer

Es ist bekannt, dass die Dichte eines gelösten Stoffes die Richtung und die Stärke seiner Bewegung im Untergrund entscheidend bestimmen kann. Eine Vielzahl von Untersuchungen hat gezeigt, dass die Verteilung der Durchlässigkeiten eines porösen Mediums diese Dichteffekte verstärken oder abmindern kann. Wie sich dieser gekoppelte Effekt auf die Vermischung zweier Fluide auswirkt, wurde in dieser Arbeit untersucht und dabei das experimentelle sowohl mit dem numerischen als auch mit dem analytischen Modell gekoppelt. Die auf der Störungstheorie basierende stochastische Theorie der macrodispersion wurde in dieser Arbeit für den Fall der transversalen Makodispersion. Für den Fall einer stabilen Schichtung wurde in einem Modelltank (10m x 1.2m x 0.1m) der Universität Kassel eine Serie sorgfältig kontrollierter zweidimensionaler Experimente an einem stochastisch heterogenen Modellaquifer durchgeführt. Es wurden Versuchsreihen mit variierenden Konzentrationsdifferenzen (250 ppm bis 100 000 ppm) und Strömungsgeschwindigkeiten (u = 1 m/ d bis 8 m/d) an drei verschieden anisotrop gepackten porösen Medien mit variierender Varianzen und Korrelationen der lognormal verteilten Permeabilitäten durchgeführt. Die stationäre räumliche Konzentrationsausbreitung der sich ausbreitenden Salzwasserfahne wurde anhand der Leitfähigkeit gemessen und aus der Höhendifferenz des 84- und 16-prozentigen relativen Konzentrationsdurchgang die Dispersion berechnet. Parallel dazu wurde ein numerisches Modell mit dem dichteabhängigen Finite-Elemente-Strömungs- und Transport-Programm SUTRA aufgestellt. Mit dem kalibrierten numerischen Modell wurden Prognosen für mögliche Transportszenarien, Sensitivitätsanalysen und stochastische Simulationen nach der Monte-Carlo-Methode durchgeführt. Die Einstellung der Strömungsgeschwindigkeit erfolgte - sowohl im experimentellen als auch im numerischen Modell - über konstante Druckränder an den Ein- und Auslauftanks. Dabei zeigte sich eine starke Sensitivität der räumlichen Konzentrationsausbreitung hinsichtlich lokaler Druckvariationen. Die Untersuchungen ergaben, dass sich die Konzentrationsfahne mit steigendem Abstand von der Einströmkante wellenförmig einem effektiven Wert annähert, aus dem die Makrodispersivität ermittelt werden kann. Dabei zeigten sich sichtbare nichtergodische Effekte, d.h. starke Abweichungen in den zweiten räumlichen Momenten der Konzentrationsverteilung der deterministischen Experimente von den Erwartungswerten aus der stochastischen Theorie. Die transversale Makrodispersivität stieg proportional zur Varianz und Korrelation der lognormalen Permeabilitätsverteilung und umgekehrt proportional zur Strömungsgeschwindigkeit und Dichtedifferenz zweier Fluide. Aus dem von Welty et al. [2003] mittels Störungstheorie entwickelten dichteabhängigen Makrodispersionstensor konnte in dieser Arbeit die stochastische Formel für die transversale Makrodispersion weiter entwickelt und - sowohl experimentell als auch numerisch - verifiziert werden.

Cleanliness versus cow comfort – an insolvable problem?

Cubicle should provide good resting comfort as well as clean udders. Dairy cows in cubicle houses often face a restrictive environment with regard to resting behaviour, whereas cleanliness may still be impaired. This study aimed to determine reliable behavioural measures regarding resting comfort applicable in on-farm welfare assessments. Furthermore, relationships between cubicle design, cow sizes, management factors and udder cleanliness (namely teats and teat tips) were investigated. Altogether 15 resting measures were examined in terms of feasibility, inter-observer reliability (IOR) and consistency of results per farm over time. They were recorded during three farm visits on farms in Germany and Austria with cubicle, deep litter and tie stall systems. Seven measures occurred to infrequently to allow reliable recording within a limited observation time. IOR was generally acceptable to excellent except for 'collisions during lying down', which only showed good IOR after improvement of the definition. Only three measures were acceptably repeatable over time: 'duration of lying down', 'percentage of collisions during lying down' and 'percentage of cows lying partly or completely outside lying area'. These measures were evaluated as suitable animal based welfare measures regarding resting behaviour in the framework of an on-farm welfare assessment protocol. The second part of the thesis comprises a cross-sectional study on resting comfort and cow cleanliness including 23 Holstein Friesian dairy herds with very low within-farm variation in cubicle measures. Height at withers, shoulder width and diagonal body length were measured in 79-100 % of the cows (herd size 30 to115 cows). Based on the 25 % largest animals, compliance with recommendations for cubicle measures was calculated. Cleanliness of different body parts, the udder, teats and teat tips was assessed for each cow in the herd prior to morning milking. No significant correlation was found between udder soiling and teat or teat tip soiling on herd level. The final model of a stepwise regression regarding the percentage of dirty teats per farm explained 58.5 % the variance and contained four factors. Teat dipping after milking which might be associated with an overall clean and accurate management style, deep bedded cubicles, increasing cubicle maintenance times and decreasing compliance concerning total cubicle length predicted lower teat soiling. The final model concerning teat tip soiling explained 46.0 % of the variance and contained three factors. Increasing litter height in the rear part of the cubicle and increased alley soiling which is difficult to explain, predicted for less soiled teat tips, whereas increasing compliance concerning resting length was associated with higher percentages of dirty teat tips. The dependent variable ‘duration of lying down’ was analysed using again stepwise regression. The final model explained 54.8 % of the total variance. Lying down duration was significantly shorter in deep bedded cubicles. Further explanatory though not significant factors in the model were neck-rail height, deep bedding or comfort mattresses versus concrete floor or rubber mats and clearance height of side partitions. In the attempt to create a more comprehensive lying down measure, another analysis was carried out with percentage of ‘impaired lying down’ (i.e. events exceeding 6.3 seconds, with collisions or being interrupted) as dependent variable. The explanatory value of this final model was 41.3 %. An increase in partition length, in compliance concerning cubicle width and the presence of straw within bedding predicted a lower proportion of impaired lying down. The effect of partition length is difficult to interpret, but partition length and height were positively correlated on the study farms, possibly leading to a bigger zone of clear space for pelvis freedom. No associations could be found between impaired lying down and teat or teat tip soiling. Altogether, in agreement with earlier studies it was found that cubicle dimensions in practice are often inadequate with regard to the body dimensions of the cows, leading to high proportions of impaired lying down behaviour, whereas teat cleanliness is still unsatisfactory. Connections between cleanliness and cow comfort are far from simplistic. Especially the relationship between cubicle characteristics and lying down behaviour apparently is very complex, so that it is difficult to identify single influential factors that are valid for all farm situations. However, based on the results of the present study the use of deep bedded cubicles can be recommended as well as improved management with special regard to cubicle and litter maintenance in order to achieve both better resting comfort and teat cleanliness.

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.