The hydrology of the Canadian Prairies has been well described in the scientific literature. 20th C observations show that snowmelt over frozen soils accounted for over 80% of the annual runoff, and streamflow hydrographs peaked in April and ceased in May due to a lack of runoff or groundwater contributions. Since then, the region has undergone rapid changes in land use and climate, both which affect streamflow generating processes. This study evaluates the detailed hydrological impact of regional changes to climate on an instrumented research catchment, the Smith Creek Research Basin (SCRB); an unregulated, wetland and agriculture dominated prairie catchment in south-eastern Saskatchewan. Wetlands have been drained for decades, reducing wetland extent by 58% and maximum storage volume by 79%, and increasing drainage channels lengths by 780%. Long term meteorological records show that there have been gradual changes to the climate: though there are no trends in annual precipitation amount, increasing temperatures since 1942 have brought on a gradual increase in the rainfall fraction of precipitation and an earlier snowmelt by two weeks. In the summer months, the number of multiple day rainfall events has increased by 5 events per year, which may make rainfall-runoff generation mechanisms more efficient. Streamflow records show that annual streamflow volume and runoff ratios have increased 14-fold and 12-fold, respectively since 1975, with major shifts in 1994 and 2010. Streamflow contributions from rainfall-runoff and mixed-runoff regimes increased substantially. Snowmelt runoff declined from 86% of annual discharge volume in the 1970’s to 47% recently while rainfall runoff increased from 7% to 34%. Annual peak discharge tripled over the period from 1975 to 2014, with a major shift in 1994, while the duration of flow doubled in length to 147 days after a changepoint in 1990. Recent flooding in the SCRB has produced abnormally large streamflow volumes, and flooding in June 2012 and 2014 was caused solely by rainfall, something never before recorded at the basin. Although the observed changes in climate and wetland drainage are substantial, it is unlikely that a single change can explain the dramatic shifts in the surface hydrology of the SCRB. Further investigation using process hydrology simulations is needed to help explain the observed regime changes.

This study aims at developing a model to estimate flood damage cost caused in Gonaives, Haiti by Hurricane Jeanne in 2004. In order to reach this goal, the influence of income, inundation duration and inundation depth, slope, population density and distance to major roads on the loss costs was investigated. Surveyed data were analyzed using Excel and ArcGIS 10 software. The ordinary least square and the geographically weighted regression analyses were used to predict flood damage costs. Then, the estimates were delineated using voronoi geostatistical map tool. As a result, the factors account for the costs as high as 83%. The flood damage cost in a household varies between 24,315 through 37,693 Haitian Gourdes (approximately 607.875 through 942.325 U.S. Dollars). Severe damages were spotted in the urban area and in the rural section of Bassin whereas very low and low losses are essentially found in Labranle. The urban area was more severely affected by comparison with the rural area. Damages in the urban area are estimated at 41,206,869.57USD against 698,222,174.10 17,455,554.35USD in the rural area. In the urban part, damages were more severe in Raboteau-Jubilée and in Downtown but Bigot-Parc Vincent had the highest overall damage cost estimated at 9,729,368.95 USD. The lowest cost 7,602,040.42USD was recorded in Raboteau. Approximately, 39.38% of the rural area underwent very low to moderate damages. Bassin was the most severely struck by the 2004 floods, but Bayonnais turned out to have the highest loss cost: 4,988,487.66 USD. Bassin along with Labranle had the least damage cost, 2,956,131.11 and 2,268,321.41 USD respectively. Based on the findings, we recommended the implementation and diversification of income-generating activities, the maintenance and improvement of drains, sewers and gullies cleaning and the establishment of conservation practices upstream of the watersheds. In addition, the model should be applied and validated using actual official records as reference data. Finally, the use of a calculation-based approach is suggested to determine flood damage costs in order to reduce subjectivity during surveys.

For processing the theme of dissertation were prepared two walks and one field trip. 1-he first walk is focused naturally and the second walk is focused geographically. The aim of dissertation is to provide to schoolchildren a contact with a direct surroundings of the school and a place of residence. Chosen activities lead to recognition of \tilevsko and his outskirt.

China has undergone significant urban growth and industrialization over the last 30 years and its incredible development continues to move ahead at an increasingly rapid pace. In terms of urban expansion, China has just recently surpassed the world’s average urbanization rate of 50%, as it moves its massive population from rural to urban areas at an astonishing speed. It’s massive population and fast urbanizing speed aside, China is also unique in terms of its socio-political system and historical-cultural context: it is a hybrid of government planning and market forces. Since it encompasses a large part of the global population and has had a vastly different urbanization experience than that of Western countries, around which most theories are based, studying China’s urbanization is an opportunity to contribute to the field of urban studies in an unprecedented manner. However, these differences also make it difficult to develop a comprehensive study of China’s urban system since the predominant theories in the field are best suited to Western cities. This research rises to this challenge by systematically studying the relationship between the socioeconomic and biophysical processes in the Chinese urban system to understand the interaction between human and physical factors, and the landscape patterns that result from these interactions. This complex urban system is examined using a hierarchical, top-down approach. At the highest level is a Macro-scale analysis of the national urban system, followed by a study of the regional urban system: the JingJinJi Metropolitan Area at the Meso-scale, and finally a Micro-scale examination with a focus on the city of Beijing. Since urban systems develop over both time and space, the urban system is analyzed spatio-temporally on all three levels. Research at the national scale is composed of two parts. First, the challenges and opportunities of China’s urban development since the foundation of the People’s Republic of China in 1949 are investigated in a general context. The institutional barriers that impede the management and continuation of China’s urban development are also discussed. Rank-size Analysis and satellite images are used to present the structural transitions of city scaling and urban clusters. These changes come with a series of challenges that are also iterated and discussed. This is followed by an analysis of the spatial distribution and transition patterns of China’s urban system using Centrographic Analysis, particularly since the post-1979 reforms. Second, the Macro-scale research focuses on a study of the urban hierarchy that is based on inter-city interactions as determined by the Synthesized Gravity Model (SGM). Under this model socioeconomic variables are synthesized and represented by the Influential Factor, while the Function Distance is derived from a Network Analysis that is based on multiple transportation methods. As an improvement on the conventional Gravity Model (GM), the SGM is used to accurately establish and represent the nodal structure of China’s urban system, the evolution of its hierarchical structure, and the relationships that exist between the nodal structure and socioeconomic factors. The results based on the SGM indicate that China’s national urban system is characterized by the emergence of urban clusters with stronger inter-city interactions since the 1990s. However, development among cities within certain urban clusters is not even, although the general pattern indicates a lessening inequality among cities. Spatially, while most cities at the top of the hierarchy are located in the east of China, cities in the middle and west of the country are also gaining higher positions in the hierarchy over time. On the Meso-scale, the applicability of the Cellular Automata (CA)-based SLEUTH model for regional urban growth pattern is studied through a focus on the JingJinJi Metropolitan Area (Beijing-Tianjin-Hebei). By integrating socioeconomic factors into a modified SLEUTH model, the urban growth dynamics and future development scenarios of the area are simulated and predicted. The results based on the CA model show that this region is characterized by a dynamic development pattern with high spreading and breeding growth rules that relies greatly on the growing transportation systems. It also allows for the projection of three possible future urban growth scenarios, each occurring under different environmental and development conditions, showing the future urban growth with or without further intervention. This research confirms that four factors play essential roles in the formulation of the urban growth mechanism of the JingJinJi Metropolitan Area: Urban policies, Industry restructuring, Rural-urban migration, and Reclassification of urban boundaries. The Micro-scale study of Beijing is conducted from two perspectives: the social and natural. The social aspect adopts the factorial ecology approach to identify the social landscape patterns and the factors that have shaped Beijing’s social space in 1990 and 2000. The social mosaic has experienced a significant change due to suburbanization, resulting in a more dynamic and complex internal structure since the 2000s. From a natural perspective, Beijing’s physical landscape patterns are extracted by processing remotely sensed images that have the same temporal span. The physical change through landscape metrics demonstrates that Beijing’s expansion has generated a more complex and fragmented land use/cover pattern. Meanwhile, transportation systems play a significant role in urban expansion, although the expansion across the space (zonal rings and directional sectors) is not even. Finally, the relationship between the social and physical landscapes is quantitatively defined by the Geographically Weighted Regression (GWR) technique, using physical landscape metrics as dependent variables and social areas as independent variables. The GWR is able to demonstrate the relationship between the social and physical landscapes at this level: as a city’s social mosaic becomes more varied over time it results in the fragmentation of that city’s physical space.

A large number of quantitative studies have examined social inequities in the geographic distribution of air pollution. Although previous research has made strides towards understanding the nature and extent of inequities, they have been limited methodologically in three ways. First, the presence of pollutants have been rarely linked to their adverse health effects, with many studies using proximity to sources as a proxy for risk. Second, there has been a tendency to study a single pollution source instead of assessing multiple types of sources. Finally, conventional statistical methods such as multivariate regression have been limited by their inability to discern spatial variations in the relationships between dependent and explanatory variables. This thesis addresses these gaps in environmental justice analysis of air pollution by using data from U.S. Environmental Protection Agency's 1999 National-Scale Air Toxics Assessment in combination with 2000 U.S. Census data to evaluate inequities in the geography of cancer risks from hazardous air pollutants in Florida. The objective is to determine if there are racial/ethnic inequities in the distribution of estimated cancer risks from outdoor exposure to point and mobile sources of air pollutants, after controlling for well-documented contextual variables. The first phase of the study utilizes traditional correlation and regression techniques to reveal that cancer risk from most air pollution sources are distributed inequitably with respect to race, ethnicity, and socioeconomic state. In the second phase, geographically weighted regression is used along with choropleth mapping to explore the spatial nonstationarity of regression model parameters and geographic variations in the statistical association between cancer risks and various explanatory variables. Results indicate that while Black and Hispanic proportions remain consistent indicators of cancer risk from most pollution sources, these relationships vary across space within Florida. This thesis contributes to environmental justice analysis by demonstrating that conventional multivariate regression can hide important local variations in the relationships between environmental risk and explanatory variables such as race, ethnicity, and socioeconomic status. Since this spatial nonstationarity can be significant within an entire region or a single urban area, understanding its nature and extent is imperative to advancing environmental justice goals.

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Both distributed work and DevOps are on an upward trend. There is a slight resemblance between the problems that DevOps is trying to find answers to, the solutions, and the common problems that geographically distributed work faces. Mainly, they are related to isolated environments that have difficulties in mutual understanding and communication, collaboration. All this leads to inefficiencies and costs that affect the overall efficiency of companies. This report identifies how DevOps engineering principles and implementations provide solutions to common problems in globally distributed work environments. It uses a literature systematic literature search and review to extract the recent and relevant academic data in the scope of the two research questions. Then, a proof-of-concept is implemented for DevOps, which confirms the literature. In parallel, a survey addressed to Swedish companies provides subject-related data from the professional environment, which largely supports the literature and brings extra knowledge. All of this is considered in data analysis and formulation of conclusions, showing DevOps features that can improve and support work in globally distributed environments and outlining the importance of the tailored organizational culture for the modern need of large-scale distributed work.

Many investigators have documented high levels of stress in the U.S. workplace and the underutilization of employee assistance programs (EAP). Researchers in other studies have concluded that an employee's perception of a service influences participation and service use. However, the perceptions of geographically distributed employees, who represent a growing population, have not been sufficiently examined. The purpose of this study was to investigate geographically distributed employees' perceptions regarding access to EAP stress management services to address the problem of EAP underutilization. Organizational justice theory served as the theoretical framework. The study design was generic qualitative. A purposeful sample of 15 geographically distributed employees provided rich data through semi structured interviews and online questionnaires. The use of generic inductive coding yielded emergent themes regarding geographically distributed employees. Results indicated that geographically distributed employee's perceived access to EAP stress management services as unclear, time-consuming, and inconvenient due to physical separation. This research is significant for human service, employee assistance, and human resource professionals who want to improve geographically distributed employees' perceptions of access to EAP stress management programs. More effective marketing may increase employee use of EAP services and alleviate workplace stress, thus positively impacting social change by helping to cultivate a healthy workforce.

Open space provides a wide range of ecosystem services to communities. In growing communities, open space offers relief from congestion and other negative externalities associated with rapid development. To make effective policy and planning decisions pertaining to open space preservation, it is important to estimate monetary values of its benefits. In addition, assessing public opinions regarding open space provides information on demand and how residents value open space. This study estimated the monetary value of open space in Mississippi and Alabama Gulf Coast communities. The study also collected information on coastal residents’ attitudes towards open space, working waterfronts, and their willingness to support waterfront open space preservation monetarily. Two methodological approaches were employed to estimate the monetary value of waterfront open space: contingent valuation (CVM) and hedonic price (HPM) methods. Data were collected using a mail survey, the Multiple Listing Service (MLS), and publicly available data sources such as the U.S. Census. Data were analyzed using an interval regression, ordinary least squares, and geographically weighted regression (GWR) models. Mail survey results indicated that the majority of residents valued open space and were willing to pay from $80.52 to $162.14 per household as estimated by four different interval-censored econometric models. Respondent’s membership in groups promoting conservation goals, income, age, and residence duration were major factors associated with their willingness to pay. Results from the HPM indicated proximities to waterfronts, with the exception of bayous, were positively related to home prices, suggesting open space produced positive economic benefits. Findings from the HPM analysis using publicly available data were consistent and comparable with the results from the HPM that used MLS data. This similarity of results indicates the use of publicly available data is feasible in HPM analysis, which is important for broad applications of the method during city planning. In addition, GWR estimates provided site specific monetary values of waterfront open space benefits, which will be helpful for policymakers and city planners in developing site-specific conservation and preservation strategies. Findings can help formulate future decisions related to alternative development scenarios of coastal areas and conservation efforts to preserve open space.

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