This thesis is about rainmaking amongst the Ihanzu (or Isanzu), a 30,000-strong matrilineal, Bantu-speaking agricultural group of north-central Tanzania. By examining rain rituals and their cosmological underpinnings as locally envisaged, I suggest that central to the Ihanzu cultural imagination lies the notion of gender complementarity. In a number of contexts, but particularly in the context of rainmaking, I show how masculine and feminine principles of a gendered universe, when combined, are seen as a site of cosmic and divine powers. To join the genders is to transform, to create, to rejuvenate. Using oral and archival sources, the first section examines the nature of the Ihanzu dual monarchy between 1885 and 1976. In spite of the radical political, economic and social changes that took place throughout this period, the dual leadership-with one male and one female-and people's understandings of royal power and legitimacy remained constant: control over rains is control over reigns. Section two examines annual rainmaking rites as they occur today. The point is to show the extent to which gender complementarity pervades these rites, and the local logic as to why this must be so. An indigenously grounded, gendered model of transformation is developed that applies equally to making children as to making rain. Power, in Ihanzu eyes, comes in gendered pairs. Section three discusses measures taken when annual rain rites fail to bring rain, and how the gendered model of transformation applies to these remedial rites. The penultimate chapter, on rain-witchcraft, suggests that gendered witches are a cosmological inversion of gendered rulers, yet for both duos their powers are based on gender complementarity. In the conclusion it is argued that the notion of gendered complementarity as developed in the thesis might be equally useful in explaining rain rites elsewhere in Africa.

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Stochastic generation of daily precipitation at multiple sites is frequently needed to evaluate the long-term effects of hydrologic and climate-change in design and operation of water resources systems. Capturing the spatial dependence of precipitation at multiple sites into a stochastic model presents a great challenge because of the non-normal bivariate distributions of precipitation-amounts. Without normalizing the precipitation amounts, many models have attempted to establish spatial dependence through alternative methods that tended to be cumbersome. In contrast, representing precipitation in Gaussian fields provides a generic structure that is well-amenable to statistical analyses facilitating easy implementation of models. The thrust of this thesis is to generate normalized precipitation data and transform them back into the original domain for applications and analyses. A multivariate censored distribution (MCD) and a multivariate autoregressive censored process (MACP) are developed to formulate two weather generation (WG) models. Parameters of censored distributions were estimated by using the maximum likelihood method. To reduce the magnanimity in the number of parameters and their temporal variation, elements of covariance matrices of models were represented by periodic functions. The performance of models was evaluated by comparing discrepancies in attributes. Three performance measures (i.e., the coefficient of determination, the coefficient efficiency and the root mean square error) suggested that simulated data to be indistinguishable from the historical precipitation sequences. The models were implemented with other techniques to address the three most common problems encountered in daily precipitation records. The first implementation is related to simulation of precipitation at un-gauged sites using the WG-MACP model with general regression neural networks or Kriging methods. The second implementation was related to infilling of missing observations a using the WG-MCD and WG-MACP models with Gibbs sampling. The third implementation was related to downscaling of monthly and daily output of the Canadian regional climate model (CRCM) using traditional and parametric Delta change methods.

Cold weather masonry construction is a major concern for contractors as they either have to implement heating practices for laying and curing masonry systems or postpone the construction to warmer periods. This can lead to loss of productivity rate and delays in construction schedules with associated extra costs. This thesis explores a novel approach for mitigating the adverse effects of cold weather on masonry construction in early fall periods through the application of nano-alumina (NA) and nano-silica (NS) in mortar joints. The assessment criteria were based on the fresh properties, hardened properties and microstructural features of mortar mixtures and mechanical behaviour of concrete masonry prisms at early and later ages. Various test results show that NS can be successfully used to minimize the adverse effects of cold temperature on mortar joints by speeding up the hydration of cement, shortening the setting time, and increasing the strength up to 72 h.

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This study investigates the control of atmospheric circulation patterns on rainfall incidence in Spain. The main objective of the research is to evaluate a range of statistical synoptic approaches with the aim of identifying the scheme that best models circulation to association. Spatial patterns of rainfall in Spain are first investigated using Principal Components Analysis and Cluster Analysis. Distinct precipitation affinity groups emerge that display covariant rainfall behaviour and reflect differences in latitude, the influence of topography and distance from the synoptic feature responsible for rainfall. The method allows seasonal redefinition of boundaries and the investigation of the effect of climate change. In total 24 synoptic models are investigated. The best performing models (a daily weather type model and a monthly airflow index model) use standardized data and the 500hPa contour surface. Some of the problems associated with non-stationarity are attempted by modifying models using kinematic information. Adjustments to the models (inclusion of frontal information and stochastic modelling) can improve results on a sub-regional scale. Effective models are then used to empirically downscale from General Circulation Model (GCM) scenarios obtained from the Canadian Centre for Climate Modelling and Analysis. The downscaling procedure is of limited use due to errors in GCM output but results suggest strongly increasing anticyclonicity in the Iberian area and a decrease in rainfall in many areas. There are uncertainties associated with regional scale climate change estimation using current empirical methods, nevertheless as GCM output inevitably becomes more accurate the scope for detailed regional assessment will improve

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