Submitted in fulfilment of the requirements of the Degree of Doctor of Engineering, Durban University of Technology, 2017. / Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area. / D

MESHWR / Department of Hydrology and Water Resources / Irrigation uses the largest amount of water, estimating to 60 % of the total consumption in South Africa. For this reason, the efficient and reasonable use of water by irrigators is of paramount importance. Thus, this study was carried out to assess the suitability of Wetting Front Detectors (WFDs) in improving water management. The study involved an on-farm survey; field installations; testing of WFD technology on selected plots within the scheme; identification of the crops grown; documentation of the current water supply and documentation of the challenges faced by farmers in relation to irrigation. These were carried out to identify the ideal situations in the scheme. Irrigation scheduling helps farmers to know when to irrigate and amount of water required supplying for crop need. The study presented WFD, as a means of improving irrigation efficiency. The WFD is a simple tool that helps farmers to identify what is occurring around the root zone. Four plots with a representative farmer in each of the plot were identified in four Blocks (Block 1 farmer 1, Block 1 farmer 2; Block 2 farmer 1; Block 3 farmer 1 and Block 4 farmer 1). On-farm experiment of the WFD was carried out. However, with Block 4 farmer 1, insufficient data was collected due to absence of LongStop equipment. This also involved field installation, observation and measurements of the LongStops (LSs) and FullStops (FSs) WFDs at placement depth of 30 cm, 45 cm and 60 cm. The efficiency of an irrigation system depends on different performance indicators including Irrigation Efficiency (IE), Conveyance Efficiency (CE), Application Efficiency (AE), Storage Efficiency (SE), Distribution Uniformity (DU) and Coefficient uniformity (CU). In this study, attention was focused only on DU; CU and SE, as represented by water moisture availability. All the DU for all plots in blocks were below the standard DU of furrow, which is 65%. Farmer 2, in Block 1, had a higher DU and CU, which were 60% and 68%, respectively- considered closer to the standard DU value. For the other farmers, their DU and CU prior to irrigation were very low, which indicated that there was uneven distribution of water in these plots. The poor DU in Block 1 farmer 1, indicated by the uneven infiltrated water, resulted in excessive watering. Analysing the WFD showed that farmers were performed well in all the Blocks, except for farmer 1 in Block 1. Average soil moisture content result indicated high water loss through deep percolation. The highest volumes of water recorded before and after irrigation were 131 ml and 159 ml, respectively, for LS90 placed at a depth of 90 cm in Block 2 farmer 1. High volumes of water were collected in Block 1 farmer 2, Block 2 farmer 1 and Block 3 farmer 1 before and after irrigation. The result showed that, the more placement depth down the soil profile, the more accumulation of water in the LSs. Therefore, it was recommended that farmers continue to use the WFD as a tool for irrigation efficiency. However, there is need for improvement and capacity building in using the tool.

MENVSC / Department of Geography and Geo-Information Sciences / Agricultural abandonment is a challenge in areas of South Africa more especially in rural areas. The study employs both qualitative and quantitative methods of in sampling and collection and analysis. It adopted a case cross-sectional study design. This design is a case study in nature, hence this study compared the active and none active farmers in identifying the causes and effects of the phenomenon studied. Comparatively, the study sought to find out if there are factors influencing farm abandonment and its consequences in Tshiombo village. The study was based on field surveys allowing for observation and with respect to agricultural abandonment. In addition to observation open ended questions together with questionnaires were administered to extension officers. The data collected from open ended questions and questionnaires was recorded and subjected to descriptive analysis. Several factors have been identified influencing farm abandonment. The challenges ranges from needs prioritization, infrastructure and capacity. It was recommended that government should reinstate its support to small scale farmers prioritize the maintenance of irrigation canals. The prioritisation of agriculture will attract many into agricultural practice with the aim of reducing poverty and starvation in rural communities. / NRF