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<p> The fire weather index (FWI), useful as a measure of forest fire danger, is calculated from precipitation and other weather variables. In the present environmental study, precipitation, fuel moisture codes, and fire behavior indices were available for a reference site and 4 higher elevation sites around Smithers, British Columbia. The objective of the study was to determine whether the use of local precipitation would lead to a different FWI than obtained from precipitation at the reference site.</p> <p> The features of the series of daily FWI values which needed to be taken into account were: peaks following dry periods, serial correlation, and heteroscedasticity. Two types of models were developed to characterize the record as a smooth component, for the upward and downward movements of the index, and a component of correlated error terms. The first type was a parametric Fourier series in a context of a generalized linear model (GLS) that allowed for serial correlation and heteroscedasticity. The second form was a smoothing cubic spline with a bootstrap procedure for estimation of standard errors and confidence bands. The question, of whether FWI on a particular day differed between a higher elevation station and the reference station, was addressed by adding a station effect to the GLS model and by graphical comparison of the smooth curves with confidence bands for the spline method.</p> <p> The Model-3 for the combined station effect is not able to capture the sharpness of the peak and found insignificant while cubic spline smoothing curves fitted to the bootstrap behave well to capture peaks and troughs in the index but it encounter some difficulties for few lower index values.</p> / Thesis / Master of Science (MSc)

In Canada, construction companies are facing disruptions to their operations due to bad or extreme weather conditions such as thunderstorms, heavy precipitation, flooding, heatwaves and snowstorms, which cause project delays, loss of productivity and increased financial costs. This sector is prone to more disruptions due to increase in the frequency, duration and intensity of extreme weather events due to future climate change. This study examined the impacts of extreme weather events on infrastructure development companies and investigated their current practices and actions to alleviate these impacts. A survey questionnaire was developed and administrated to owners, managers, engineers, supervisors and planners of construction companies. Apart from descriptive evaluations, the survey responses were quantitatively analyzed to determine the impact of bad weather conditions on the construction companies. The findings of this study suggested that most construction companies’ operations were delayed due to bad or extreme weather events. However, construction industry is not adopting proactive measures to avoid or minimize these impacts. The main environmental factors impacting construction companies, included flooding, high winds or thunderstorms, warm/cold temperatures, heatwaves and snow/ice storms. These bad weather impacts were more significant for non-government construction companies as compared to those working in the government sector. Indirect impacts of bad weather included disruptions to their supply chain networks and changes in customer behaviors; however, these impacts were minor compared to direct environmental impacts. The study found that both government and non-government sector construction companies granted accommodations to the workers during bad weather conditions; however, government sector companies were more accommodating as compared to non-government companies. The study results also provided insight into the financial impacts of extreme weather events on construction companies. Weighted average losses for government sector companies were $2,200 per day of bad weather as compared to $8,155 per day for non-government companies. This suggested that non-government construction companies may experience serious financial consequences due to bad or extreme weather events. Study results further showed that there were no adequate guidelines, protocols or standards available to construction companies to adapt their operations and planning for extreme weather events. The study also highlighted the lack of adequate insurance products available for the construction sector to deal with bad weather. There was little tendency shown by the construction companies to use new technologies to deal with bad weather conditions. Therefore, there is an urgent need to develop guidelines, protocols or standards for construction companies by involving all levels of the government and relevant private sector organizations. This study helps to determine the nature and scale of extreme weather impacts on construction industry and explores what strategies may be developed to alleviate these impacts and risks. Such knowledge will help companies better plan and manage their operations and effectively use their human resources. It will help in timely delivery of services and savings in costs by the infrastructure development companies, which are a major contributor to the Canadian economy. / Thesis / Master of Science (MSc)

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Apple preharvest fruit drop frequently results in severe economic losses. Cultural control of preharvest drop has relied upon plant growth regulators (PGRs), but the loss of daminozide (Alar) and 2,4,5-TP has severely limited the choices of effective stop-drop compounds. A more complete understanding of factors involved in preharvest drop is therefore imperative. Experiments were conducted to provide information about cellulase activity in the abscission zone, effects of applied auxin and ethylene biosynthesis inhibition on drop, changing sensitivity to abscission induction during the season, and relationships among seed number, fruit weight, and day of drop. Observational studies were used to study effects of fruit maturity, canopy positions, and morphology of stem attachment on time of fruit drop as well as characterizing the natural timing of late-season fruit drop. Increased activity of cellulase, but not polygalacturonase, in the abscission zone was detected within 4 days of cutting fruit to induce abscission. Both aminoethoxyvinyl glycine (AVG) and naphthaleneacetic acid (NAA) applied 2 or 4 days after cutting delayed drop, but NAA delayed drop 1.6 days longer than did AVG. Fruit of "RedChief Delicious"(D) exhibited a significantly reduced sensitivity to abscission-inducing treatments from mid-June until early July compared to earlier orr later in the season. Application of plant growth regulators to cut fruit revealed a significant interaction of NAA treatment with AVG treatment such that NAA delayed drop when applied with AVG but not without AVG. Fallen fruit had lower starch and higher soluble solids than fruit on the tree on the day of collection. The highest fruit in the canopy fell an average of 4.4d earlier than the lowest fruit. Day of drop was not different for fruit from king blooms vs. side blooms within an inflorescence. There was a trend for fruit from first year wood to drop later than fruit from older wood on "Delicious", but not "Smoothee Golden Delicious" trees. There was no detectable effect of angle of orientation of the subtending spur on the limb, the pedicel:spur abscission zone, or fruit axis of symmetry on time of fruit drop. No difference was detected in time of fruit drop between East and West or North and South sides of the trees. No substantial variation in day of drop of individual fruit was explained by number of seed in the fruit. Daily drop was recorded for three cultivars ("RedChief Delicious", "Smoothee Golden Delicious", and "Commander York") for three years. Variance of average day of drop from year to year was 40.1, while variance among cultivars within a year was 51.8. Variance from tree to tree within each cultivar, within each year, was only 18.6. Multiple regression modeling to identify relationships between weather factors and daily fruit drop revealed that much of the variability in time of drop was due to factors other than the weather events modeled. The best regression models developed explained only 8% to 35% of the variability in time of drop. The most important weather factors were daily minimum temperatures and precipitation. Rain events of greater than 5.0 mm following a drier period appeared to cause increased drop of all three cultivars in one out of the three years investigated. / Ph. D.