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A study was conducted to quantify weather conditions at specific growth stages of Canadian western Spring wheat (Triticum aestivum) and relate those growing conditions to variations in wheat grade and quality characteristics and to develop pre-harvest prediction models for wheat quality using weather input data. Six Canadian western spring wheat genotypes were grown in five locations across the Canadian prairies during the 2003 and 2004 growing seasons. Intensive weather data was collected during the growing season at each location and used to calculate accumulated heat stress, useful heat, moisture demand, moisture supply, moisture use and moisture stress variables for numerous crop development stages. Grain samples were graded, milled and underwent an extensive analysis of flour, dough, and bread making quality. ANOVA indicated that genotype, environment and their interactions had significant effects on most quality parameters tested. Environmental contribution to wheat quality variance was considerably larger than the variance contribution of either genotype or GxE interaction. Using the weather and crop development stage information, significant regression equations with high regression coefficients were developed for most quality parameters using just a single independent weather variable. Multiple regression equations with even higher R2 values were developed using three complex weather variables, leading to the opportunity to predict wheat quality 2-5 weeks prior to harvest. Equally strong prediction models were developed utilizing basic weather variables which could be obtained from weather stations monitoring only daily maximum and minimum air temperature and precipitation. The development periods of planting to jointing and anthesis to soft dough were the stages most frequently exhibiting the highest correlation to wheat quality indicating weather needs to be monitored during the entire growing season to accurately predict quality. Grain quality forecast models were validated using 2005 weather and crop data. Prediction models developed from the 2003 and 2004 data required modification in order to accurately and consistently predict the grain properties in 2005.

Most decision making processes involve risk associated with the uncertainty of a range of outcomes that may, or may not, occur at some time in the future. In recent years, many of the recent advances in risk theory have come from the field of financial mathematics. While the latter subject is now well developed we claim that there are still some important aspects of decision-making involving risk that are not covered by the existing theory. In particular, we believe that the following three questions require further investigations. 1. In the financial portfolio management context, if decisions need to be taken at multiple stages, is it possible to devise a time consistent risk minimization policy? 2. If the value of an asset of interest is strongly influenced by a climatic variable (such as temperature or rainfall) that is best modelled by techniques that are not normally used in financial modelling, how should financial derivatives on such an asset be priced? 3. If the undesirable risky phenomenon depends on both the upper and lower tails of a, possibly asymmetric, probability distribution (e.g., that of amount of rainfall), what is a suitable measure of risk in this context? This thesis supplies, at least partial, answers to each of these challenging questions. We hope that these results will motivate others to develop even better solutions. / First, for the purpose of defining a dynamic measure of risk, we introduce the time consistency concept that is inspired by the so-called principle of optimality of dynamic programming and demonstrate - via an example - that the conditional value-at-risk (CVaR) need not be time consistent in a multi-stage case. Then, we give the formulation of the target-percentile risk measure which is time consistent and hence more suitable in the multi-stage investment context. / Second, in order to hedge the risk related to the uncertainty of weather we study pricing of derivatives where the underlying asset is sensitive to the weather and the price is a function of a weather variable, for instance, temperature or rain-fall. We use time series to model the temperature and assume that the price of the underlying asset is a deterministic function of the temperature. We discuss both the continuous and discrete time models using the replicating portfolio approach. We obtain a partial differential equation that is similar to the Black-Scholes PDE in the continuous time case. We also provide a binomial approximation for the continuous time model and the corresponding PDE, and report on some numerical experiments. / Next, we analyze the risk encountered in many environmental problems that appear to exhibit special "two-sided" characteristics. For instance, in a given area and in a given period, farmers do not want to see too much or too little rainfall. We formulate and solve this problem with the help of a "two-sided loss function" that depends on the above ranges. Even in financial portfolio optimization a loss and a gain are "two sides of a coin", so it is desirable to deal with them in a manner that reflects an investor's relative concern. Consequently, we define Type I risk: "the loss is too big" and Type II risk: "the gain is too small". Ideally, we would want to minimize the two risks simultaneously. However, this may be impossible and hence we try to balance these two types of risk. / Thesis (PhDMathematics)--University of South Australia, 2006.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. Philip Cunningham, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Sept. 22, 2004). Includes bibliographical references.

Thesis--Bonn. / Vita. Includes bibliographical references (p. 311-339) and index.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p. 134-143).

Thesis (M.S.)--University of Wisconsin--Madison, 1962. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 45).

Thesis (M.S.)--University of Wisconsin--Madison, 1967. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 67).