Includes abstract. / Includes bibliographical references (p.127-131). / Global Circulation Models (GCMs) are the primary tool for simulating future climate changes. These models by necessity make use of various assumptions and simplifications due to computational constraints, and in so doing introduce biases and systematic error. Along with other sources of uncertainty regarding our understanding of the climate system and given the quasi-chaotic nature of the climate, climate projections differ between models whose climate simulation skill is poorly quantified. A new methodology is presented to assess the regional biases in GCMs and to, in part, compensate for some aspects of these biases. The study will focus on the Southern African region but could be replicated for other regions. Using Self-Organising Maps (SOMs), synoptic archetypal patterns are identified and the distribution and frequency of these patterns assessed. The use of synoptic archetypes to quantify model metrics presents a novel approach with many benefits over standard metrics, such as errors and means per variable. SOMs add a spatial and multi-variable dimension to the analysis as each metric is calculated based on its synoptic circulation pattern and associated to a set of atmospheric variables. Some persistent biases in the models are notable based on comparisons between the NCEP and GCM SOM node mapping, such as an overall cool bias in the models and a shift of the dominant high pressure cells and thus the westerly wave to the south. The weighting techniques provide insight into how much of the model bias is contributed by differences in synoptic frequency and what part is attributable to systematic biases in the models which result in a different mean state for a given synoptic process. The frequency correction enabled a correction of up to 25% of the difference between model and reanalysis data, but in most cases the change was far smaller than this. The differences in mean conditions remained the largest component of the bias. To correct for this the weighting was applied to the climate change anomaly (difference between future and control projections) per synoptic process to create a multi-model climate change component that is added to the NCEP baseline. This provides the most accurate depiction of future climate from the data provided. The models generally have different strengths, therefore the weighted multi-model solution allows models to give a greater contribution where they are skilful and less where they do not match the observed dynamics. Comparison of the magnitude of the climate change signal showed that winter states in the weighted multi-model composite had a smaller temperature increase and reduced rainfall compared to the unweighted results. In summer states there is greater warming and increased rainfall, especially over the oceans. This suggests the models are over estimating changes in temperature in winter and underestimating the increases in summer. Synoptic events are the primary driver of climate change impacts. Therefore errors in synoptic state will have a notable influence on the climate change projections and need to be fully considered in any climate change impact study. The use of the weighting technique helped to identify and reduce uncertainties in the climate change projections over Southern Africa.

Includes abstract. / Includes bibliographical references. / Lagrangian moisture source attribution model is developed in order to explore the regional moisture source dynamics of southern Africa. In particular, the model was developed in order to explore the role of the regional land surface as a source of moisture for regional precipitation. This work was prompted by previous studies suggesting that the land surface may play an important role in the regional climate system and particularly in the regional hydrological cycle. Existing moisture transport and source methodologies have a number of limitations.

Climate change studies are subject to high uncertainties partly resulting from data reliability. This study investigates the challenges of using statistical downscaled climate data to examine the likely impacts of climate change on maize growth in southern Africa in the context of these uncertainties.

Includes abstract. / Includes bibliographical references (leaves 215-241). / The study is focused on four study sites, two in the Western Cape, namely the Bruno section and Lake Michelle and two in southwestern Australia, namely Wambellup Swamp and Devil's Pool. These sites were chosen as they are well situated to investigate the complex interaction between Late Quaternary climate change, the influence of fluctuating sea levels and the impact of human interaction with the environments in question and provide a regional picture of these interactions.

Word processed copy. / Includes bibliographical references (p. 219-236). / This study investigated the causes, magnitude and selected socio-ecologlcal effects of soil degradation, with the ultimate goal of explaining and mapping the spatial and temporal variations of degradation in the dryland area of central Uganda.

Word processed copy. Includes bibliographical references (leaves 235-255).

Bibliography: leaves 182-189.

Includes bibliographical references (p. 111-119).

Includes bibliographical references (p. 263-309).

Includes abstract. / Includes bibliographical references (leaves 209-224). / This study examined whether sustainable tourism development could be achieved in the Lake Victoria shore region of southern Uganda, based on the physical environment indicators of sustainable tourism. This arose out of the observation that tourism in this region was developing in an unplanned manner which was likely to be environmentally destructive. The study was conducted as a cross-sectional descriptive survey involving an analytical research design. Its objectives include: to identify the spatial and temporal characteristics of the tourism sites; to assess their performance relative to the physical environment indicators of sustainable tourism; to examine the factors explaining the performance of the sites; and to develop a planning approach that will help attain sustainable tourism development. Data were collected using survey, non-survey and geo-spatial methods. The survey methods included interviews and questionnaires, which were administered to planning and environment officials, local residents and visitors selected using various sample methods. Documentary analysis, field observation, remote sensing and experimentation were among the nonsurvey and geo-spatial methods used. Data were analysed using qualitative and quantitative analysis techniques, which included documentary analysis, statistical techniques involving, chi square, data reduction, ANOVA, and correlation and regression analysis. Results indicate that lakeshore tourism sites are increasing in both number and size, which is gradually resulting in a clustered spatial patterning, especially in urban areas. Sites are receiving an increasing number of visitors, mainly nationals and day visitors. Apart from conservation areas, the contribution of the sites to nature conservation is concluded to be minimal and their management of solid and sewage waste, water quality and use intensity generally poor. Moreover, tourism planning and development control was found to either be limited or lacking, a situation that has resulted in unregulated tourism development. This poses a significant threat, not only to the fragile physical environment of the lakeshore region, but also to the future of lakeshore tourism itself. Analysis of the results show that there are significant relationships between spatial distribution of sites, their characteristics, site performance and factors explaining the performance and planning for sustainable tourism development in the region. Further analysis indicates that each of these variables may significantly predict planning, especially at site and local government level. Accordingly, a linear regression model-based planning approach is developed. This study explains how the model, when rooted in incremental planning theory, can be applied in order to plan for sustainable tourism in the lakeshore region. It highlights the variables and the sequence in which tourism planning efforts can be applied. The study concludes that, although this planning approach may not provide a panacea to the achievement of sustainable tourism development in the lakeshore region, it represents a valuable contribution towards the understanding of sustainable tourism planning. With the identification of critical tourism planning intervention points, the Lake Victoria shore region may be able to develop into a major tourism destination that is environmentally sustainable.