MSc (Statistics) / Department of Statistics / Haulage trucks and cross border traders cross through Beitbridge border post from landlocked countries such as Zimbabwe and Zambia for the sake of trading. Because of global warming, South Africa has lately been experiencing extreme weather patterns in the form of very high temperatures and heavy rainfall. Evidently, in 2013 tra c could not cross the Limpopo River because water was owing above the bridge. For planning, its important to predict the likelihood of such events occurring in future. Extreme value models o er one way in which this can be achieved. This study identi es suitable distributions to model the annual maximum heights of Limpopo river at Beitbridge border post. Maximum likelihood method and the Bayesian approach are used for parameter estimation. The r -largest order statistics was also used in this dissertation. For goodness of t, the probability and quantile- quantile plots are used. Finally return levels are calculated from these distributions. The dissertation has revealed that the 100 year return level is 6.759 metres using the maximum likelihood and Bayesian approaches to estimate parameters. Empirical results show that the Fr echet class of distributions ts well the ood heights data at Beitbridge border post. The dissertation contributes positively by informing stakeholders about the socio- economic impacts that are brought by extreme flood heights for Limpopo river at Beitbridge border post

MURP / Department of Urban and Regional Planning / Disaster is posing serious threats to both human lives, infrastructure and the environment at large. Greater Tzaneen Municipality (GTM) is one of the many municipalities that suffer from flood related disasters. Lack of integration between Disaster Risk Reduction (DRR) and spatial planning has compounded the disaster risk situation in the municipality. This study sought to investigate the prospects of integrating spatial planning with disaster risk reduction in flood prone areas of GTM. The study is guided by three research objectives. First, the study sought to analyse spatial planning attributes that can be valorised for DRR in flood prone areas; Secondly, it sought to analyse spatial planning factors that define vulnerability attributes of households occupying flood prone areas. Finally, the study sought to perform a cluster analytical creation of a typology of households whose resilience to flooding could be enhanced through spatial planning. Twenty-five flood prone areas were analysed on the basis of four main flood vulnerability attributes. In order to identify such vulnerability attributes, the study borrowed critical insights from literatures on flood vulnerability, spatial planning and DRR. Such a critical review of literature was complemented by the use of pattern matching as a qualitative research instrument. Quantitative that was gathered using a structured observation checklist. Quantitative data generated was first subjected to various statistical tests that included Normality and Reliability Tests. Common measures of Normality test used included measures of skewness, kurtosis and the use of Normal Q-Q plots. To assess flood vulnerability, Hierarchical Cluster Analysis (HCA) was used. HCA was used to identify clusters of flood prone areas which had common characteristics in terms of the four main study constructs proposed by the study which included the physical/engineering, socio-economic, ecological/natural and political or governance conditions characterizing each area. HCA was then used to identify main clusters exhibiting similar characteristics and the associated level of vulnerability of such of communities occupying such clusters. Study results revealed 2 main clusters of flood prone areas whose differences lay in interactions that existed between the physical/engineering, socio-economic, ecological/natural and political or governance conditions characterizing each area. Such clusters depicted 2 levels of vulnerability that is high, and moderate. A number of opportunities and constraints were generated using the SWOT matrix strategy with the main results showing that spatial planning elements characterizing flood prone areas could be transformed into critical urban risk management options for DRR. This is because a spatial planning elements were found to have a direct influences on critical factors of DRR such as location of activities. The study concluded by recommending a number of spatial planning strategies that can be vaporized for DRR. Such strategies are systematically aligned to the unique vulnerability context conditions associated with the two flood vulnerability solution arrived at using HCA. / NRF