MESHWR / Department of Hydrology and Water Resources / This study dealt with the influence of climate variability on flood and drought cycles and implications on rainy season characteristics in Luvuvhu River Catchment (LRC) in Limpopo of South Africa. Extreme weather events resulting in hazards such as floods and droughts are becoming more frequent due to climate change. Extreme events affect rainy season characteristics and hence have an influence on water availability and agricultural production. Annual temperature was obtained from Water Research Commission for stations 0723485W, 0766628W and 0766898W from 1950-2013 were used to show/or confirm if there is climate variability in LRC. Daily rainfall data was obtained from SAWS for stations 0766596 9, 0766563 1, 0723485 6 and 0766715 5 were used to detect climate variability and determine the onset, duration and cessation of the rainy season. Streamflow data obtained from the Department of Water and Sanitation for stations A9H004, A9H012, and A9H001 for at least a period of 30 years for each station were used for climate variability detection and determination of flood and drought cycles. Influence of climate variability on floods and droughts and rainy season characteristic were determined in the area of study. Trends were evaluated for temperature, rainfall and streamflow data in the area of study using Mann Kendall (MK) and linear regression (LR) methods. MK and LR detected positive trends for temperature (maximum and minimum) and streamflow stations. MK and LR results of rainfall stations showed increasing trends for stations 0766596 9, and 0766563 1 whereas stations 0723485 6 and 0766715 5 showed decreasing trends. Standardized precipitation index (SPI) was used to determine floods and droughts cycles. SPI results have been classified either as moderately, severely and extremely dry or, moderately, very and extremely wet. This SPI analysis provides more details of dominance of distinctive dry or wet conditions for a rainy season at a particular station. Mean onset of rainfall varied from day 255 to 297, with 0766715 5 showing the earliest onset compared to the rest of the stations. Cessation of rainfall for most of the hydrological years was higher than the mean days of 88, 83 and 86 days in 0766596 9, 0766563 1 and 0723485 6 stations. Mean duration of rainfall varied from 102 to 128, with station 0766715 5 showing shortest duration of rainfall. The results of the study showed that the mean onset, duration and cessation were comparable for all stations except 0766715 5 which had lower values. The study also found that climate variability greatly affects onset, duration and cessation of rainfall during dry years. This led to late onset, early cessation and relatively short duration of the rainfall season. Communities within the catchment must be educated to practice activities such as conservation of indigenous plants, reduce carbon dioxide emissions.

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