Hydrological modelling under limited data availability : a case study of Umdloti River, South Africa

Abstract

Due to the water scarcity in South Africa, new strategies in management planning are needed in order to sustain water resources. The increase of population and economic growth in South Africa has a negative effect on the water resources. Therefore, it should be well managed. The main concerns of the sustainability of water resources are hydropower, irrigation for agriculture, domestic and industries. Hence, the use of integrated water resources management in a single system which is built up by a river basin will help in water resources. This study was focused on water management issues: some of the principal causes of water shortages in UMdloti River are discussed. The current situation of water supply and demand at present is discussed. It also addressed some essential elements of reasonable, cooperative and sustainable water resources management solutions. Many developing countries are characterized as there is limited data availability, water scarcity and decrease of water levels in the dams. The eThekwini municipality is also having similar problems. Water resources have been modelled under this limited data using the hydrological modelling techniques by assessing the streamflow and observed data. The aim of the study was to address the issue of water management how water supply sources can be sustained to be manageable to meet the population growth demand considering the capacity of Hazelmere Dam demand downstream of the dam. Hydrological models, simulation, and decision making support systems were used to achieve all the research objectives. Hazelmere Dam has been modelled so that it can be used efficiently for the benefit of all users downstream of the dam for their economic and ecological benefits. Monthly reservoir inflow data for Hazelmere Dam was obtained from the Department of Water Affairs, South Africa. The nature of data is streamflow volume in mega liter (Ml) recorded for every month of the year. This was converted to mega cubic meter (Mm3) for use in the analysis herein. A period spanning 19 years of data (1994 – 2013) was used for the analysis. Six parametric probability distribution models were developed for estimating the monthly streamflow at Hazelmere Dam. These probability distribution functions include; Normal, Log-Normal (LN), Pearson III, Log-Pearson type III (LP3), Gumbel extreme value type1 (EVI) and Log-Gumbel (LG). It was observed that UMdloti River is smaller when compared with other rivers within the KwaZulu-Natal Province which could make it difficult to implement integrated water resources management. The hydro-meteorological data collected also has some limitations. The meteorological stations are far away to one another and this would make it difficult to attach their readings with the corresponding water basin. The comparison between the observed and simulated streamflow indicated that there was a good agreement between the observed and simulated discharge. Even though, the performance of the model was satisfactory, yet, it should not be generalized equally for all purposes. The erosion on the study area must be addressed by the stakeholders. It must be minimized in order to sustain the water resources of the UMdloti River. Erosion has a bad impact on the environment because it causes environmental degradation as well. Further investigations are recommended that account for the geological characteristics and the source of the base flow to make sure the rate of groundwater is sufficient for any future developments. Harnessing more energy from existing water sources within the frontier of the country is important in capacitating the South African Government’s commitment to reduction of the country’s greenhouse gas emissions and transition to a low-carbon economy while meeting a national target of 3,725 megawatts by 2030. This study also aimed to determine the amount of energy that can be generated from Hazelmere Dam on the uMdloti River, South Africa. Behavioral analyses of the Hazelmere reservoir were performed using plausible scenarios. Feasible alternative reservoir operation models were formulated and investigated to determine the best operating policy and power system configuration. This study determines the amounts of monthly and total annual energy that can be generated from Hazelmere reservoir based on turbines efficiencies of 75%, 85% and 90%. Optimization models were formulated to maximize hydropower generation within the constraints of existing abstractions, hydrological and system constraints. Differential evolution (DE) optimization method was adopted to resolve the optimization models. The methodology was applied for an operating season. The optimization models were formulated to maximize hydropower generation while keeping within the limits of existing irrigation demands. Differential evolution algorithm was employed to search feasible solution space for the best policy. Reservoir behavioural analysis was conducted to inspect the feasibility of generating hydropower from the Hazelmere reservoir under normal flow conditions. Optimization models were formulated to maximize hydropower generation from the dam. DE was employed to resolve the formulated models within the confines of the system constraints. It was found that 527.51 MWH of annual energy may be generated from the dam without system failure. Storage was maintained above critical levels while the reservoir supplied the full demands on the dam throughout the operating period indicating that the system yield is sufficient and there is no immediate need to augment the system.