Watershed features, physiographic setting, geology, climate, and hydrologic processes combine to produce a time-variant nutrient concentration signal at the watershed outlet. Anthropogenic influences, such as increased agricultural pressures and urbanization, have increased overall nutrient loadings delivered to the fluvial network. The impact of such increased nutrient loadings on Kentucky’s drinking water remains a potential threat to the region. By coupling spatial sampling of nitrate concentrations in surface water with contemporary nutrient and water quality sensor technology, a decomposition of the Upper South Elkhorn watershed’s nitrate signal and an estimation of source timing and loading in the watershed was completed. The goal of the project was the decomposition of the integrated nitrate signal observed at the outlet of the Upper South Elkhorn watershed into contributing runoff and groundwater sources from agricultural/pasture and urban/suburban land-uses. Decomposing the watershed’s nitrate signal yielded new knowledge learned about nitrate source, fate and transport in immature fluviokarst. This thesis discusses how mean, seasonal, and fluctuating nitrate behavior is related to soil processes, groundwater transfer, streambed removal, and event dynamics. It is expected that the decomposition of the nitrate signal will allow for the targeting of both the timing and sources for nutrient reductions in a watershed.

Bimodal polyethylene resins are frequently used for pipe applications. In this work, blending was used to produce polyethylenes with comparable properties, particularly with respect to processing, stress crack resistance and tensile properties. Suitable blend components were identified, and their performance screened used ECHIP experimental design software. Blends were characterized using gel permeation chromatography (GPC), differential scanning calorimetry (DSC), tensile testing, stress crack resistance measurements, impact toughness testing, capillary rheometry and melt index measurements. GPC, DSC and melt index results reveal that the method of meltcompounding produced morphologically uniform blends, with different degrees of compatibility depending on the type and level of branching of blend components. Most of the blends produced showed higher crystallinity values compared to a reference bimodal resin. Binary high density polyethylene (HDPE) blends showed better stiffness and strength properties, whereas metallocene catalyzed linear low density polyethylene (mLLDPE) containing blends illustrated superior elongation and toughness properties compared to the reference polymer and other binary blends. The highest resistance to slow crack growth (SCG) was shown by low density polyethylene (LDPE) and mLLDPE containing blends due to their high branching content. The overall blend resistance to SCG or toughness can be enhanced with levels less than 20% by weight of LDPE or mLLDPE in the blend although the tensile properties are relatively unaffected at these low concentrations. The performance of blends was optimized by changing component polymers and their weight fractions, and a model to predict optimum blends was developed using the Maple code. Optimized blends showed higher branching content, comparable molecular weight, molecular weight distribution, tensile properties, viscosity and processing behaviour to the reference polymer. Optimized blend 3, in particular, encountered the same degree of shear thinning as the reference material. Better toughness and resistance to SCG were shown by the optimized blends when compared to the reference polymer.

The diploma thesis deals with the possibilities of using the optimization modelling software system GAMS in risk management. According to the assignment, emphasis is placed on a detailed approach to the program for those, who are interested in its use in the field of risk engineering applications. The first part of the thesis contains the knowledge to understand what the GAMS program is and what it is used for. The next part of the work provides instructions on how to download, install, activate the program and what the user interface of the program looks like. Thanks to mathematical programming, it will be explained on a project on the distribution of lung ventilators, what basic approaches may be used in risk modelling in the GAMS program on a deterministic model. The following are more complex wait-and-see models, which contains the probability parameters and here-and-now models, where we work with demand scenarios and verify whether if they meets the requirements of other scenarios or calculate costs for the highest demands. The two-stage model is also one of the here-and-now models, but it is significantly more complex in its size and range of input data, it includes additional price parameters for added or removed pieces of lung ventilators from the order.