Literatura académica sobre el tema "Mkomazi River"

It is still a challenge to provide spatially explicit predictions of climate parameters in African regions of complex relief, where meteorological information is scarce. Here we predict rainfall, temperature, and reference evapotranspiration (ETo) for the southern Mkomazi River Basin in Northeastern Tanzania, East Africa, by means of regression-based, digital elevation models (DEM) at 90 m spatial-resolution and geographic information systems (GIS) techniques. We mapped rainfall for the period 1964–2010. The models accounted for orographic factors which strongly influenced the spatial variability of rainfall in the region. According to orography, the area was divided into three zones for modelling rainfall: windward, leeward, and transition zone. Rainfall indicates high spatial and temporal variability dominated by equatorial East-African climate circulation systems. Maximum and minimum temperatures were modelled for the period 1989–1994, the models accounted only for the altitude gradient. Mean temperature was calculated by arithmetic mean of maximum and minimum temperatures maps in ArcGIS. ETo was estimated in ArcGIS following the method described by Hargreaves and Samani. The maps were made on a monthly basis for rainfall, ETo, and mean, maximum, and minimum temperatures. The obtained maps are useful for the purpose of agriculture, ecological, and water resources management.

Abstract. Water shortages are a chronic and severe problem in South Africa. Allocation of this limited water resources, environmental quality, and policies for sustainable water use are issues of increasing concern that require accurate and timely information to evolve strategies for dynamic natural resources management. Specifically, this paper is aimed to assist the planning, restoring and to rationally allocate the water resources in any river basin in resolving the current water stresses in many parts of South Africa, by using integrated knowledge from simulation and integrated river basin management approach. The developed system dynamic (SD) allocation system was used to investigates the extent to which the framework is ‘sustainable’ in the medium and long terms in evaluating existing and future water allocation among conflicting users at Mkomazi River Basin (MRB), KwaZulu-Natal Province, South Africa The invented SD framework confirms agricultural water use as the highest demand when compared with other users. The optimal sustainability performance index (0.25) of the system at 70% dependable flow shows an integrated scenario that combines rainfall variation with improved irrigation water use efficiency as a suitable framework plan. The study uses integrated knowledge from simulation and integrated river basin management approach as a feasible method to assist the planning, restoring and to rationally allocate the water resources in any river basin with similar attributes to the study area in resolving the current water stresses in many parts of the country. Water resources managers would find these tools beneficial in understanding the complex nature of water resources allocation and in determining priorities area which required prompt attention and intervention.

Submitted in fulfillment of the requirements of the Degree of Master of Technology: Civil Engineering, Durban University of Technology, 2014.
Streamflow modelling remains crucial to decision-making especially when it concerns planning and management of water resources systems in water-stressed regions. This study proposes a suitable method for streamflow modelling irrespective of the limited availability of historical datasets. Two data-driven modelling techniques were applied comparatively so as to achieve this aim. Genetic programming (GP), an evolutionary algorithm approach and a differential evolution (DE)-trained artificial neural network (ANN) were used for streamflow prediction in the upper Mkomazi River, South Africa. Historical records of streamflow and meteorological variables for a 19-year period (1994- 2012) were used for model development and also in the selection of predictor variables into the input vector space of the models. In both approaches, individual monthly predictive models were developed for each month of the year using a 1-year lead time. Two case studies were considered in development of the ANN models. Case study 1 involved the use of correlation analysis in selecting input variables as employed during GP model development, while the DE algorithm was used for training and optimizing the model parameters. However in case study 2, genetic programming was incorporated as a screening tool for determining the dimensionality of the ANN models, while the learning process was further fine-tuned by subjecting the DE algorithm to sensitivity analysis. Altogether, the performance of the three sets of predictive models were evaluated comparatively using three statistical measures namely, Mean Absolute Percent Error (MAPE), Root Mean-Squared Error (RMSE) and coefficient of determination (R2). Results showed better predictive performance by the GP models both during the training and validation phases when compared with the ANNs. Although the ANN models developed in case study 1 gave satisfactory results during the training phase, they were unable to extensively replicate those results during the validation phase. It was found that results from case study 1 were considerably influenced by the problems of overfitting and memorization, which are typical of ANNs when subjected to small amount of datasets. However, results from case study 2 showed great improvement across the three evaluation criteria, as the overfitting and memorization problems were significantly minimized, thus leading to improved accuracy in the predictions of the ANN models. It was concluded that the conjunctive use of the two evolutionary computation methods (GP and DE) can be used to improve the performance of artificial neural networks models, especially when availability of datasets is limited. In addition, the GP models can be deployed as predictive tools for the purpose of planning and management of water resources within the Mkomazi region and KwaZulu-Natal province as a whole.

The health and life expectancy of populations in developing countries is largely determined by the availability of good quality drinking water. Boreholes and springs generally provide water of better microbiological and physical quality than surface water sources, however, they may cause health and aesthetic problems due to chemical constituents dissolved out of the host rock. As part of a pilot study to assess the health-related quality of community water supplies, samples were taken from two Quaternary catchment areas in KwaZulu-Natal. The Umkomazi catchment area is located inland from Amanzimtoti, while the Umfolozi catchment area is located north-east of Ulundi. The geology in these areas is significantly different. The Umkomazi area is predominantly underlain by basement rocks of the Natal Structural and Metamorphic Province, while the Umfolozi area is underlain by sedimentary rocks of the Karoo Supergroup. Geographical information systems (GIS) were used to examine the influence of lithology, rainfall and landuse activities on groundwater quality. Major ion analysis of groundwater samples from the Umkomazi area revealed a linear relationship between borehole and spring concentrations. Dwyka Tillite was found to produce water with the highest concentrations of major ions, while Karoo dolerite produced water with the lowest concentrations of major ions. Samples from basement rocks and Natal Group contained intermediate concentrations of major ions. In the Umfolozi area Karoo dolerite samples showed the lowest concentrations of major ions, while the Vryheid Formation and Dwyka Tillite produced the highest borehole and spring concentrations, respectively. High salinity levels in sedimentary rocks may be due to marine influence during deposition. Piper diagrams show relative enrichment of major cations and anions and Stiff diagrams showed characteristic patterns. Fluoride is associated with siliceous basement rocks and related to calcium concentrations through the solubility of calcium fluoride. The trace metals, manganese, iron and zinc were found to cause significant aesthetic problems and possibly health problems in sensitive individuals. These constituents are derived from weathering of bedrock and possibly from the corrosion of metal pipes. There is an inverse relationship between mean annual rainfall (MAR) and electrical conductivity (EC), except near the coast where windblown salinity increases with rainfall. Nitrate, ammonium and E. Coli contamination are linked to landuse activities such as occurrence of human and animal excreta near the water source and the proximity of pit latrines. It is recommended that rural communities be educated about the nature and importance of groundwater quality.
Thesis (M.Sc.)-University of Natal, Durban, 1998.

In common with other natural systems, aquatic ecosystems provide a wealth of economically valuable services and long-term benefits to society. However, growing human populations, coupled with increased aspirations for improved quality of life, have lead to intense pressure on the world's finite freshwater resources. Frequently, particularly in developing countries, there are both perceived and genuine incompatibilities between ecological and societal needs for freshwater. Environmental Flow Assessment (EFA) is essentially a tool for water resources management and its ultimate goal should be the integration of ecological and societal systems. While other ecological components (i.e. biological and geomorphological) are equally important to EFA, this thesis investigates the role of the hydrological cycle and the hydrological regime in providing the ecosystem goods and services upon which society depends. Ecological and societal systems operate at different temporal, spatial and organisational scales and hydronomic zoning or sub-zoning is proposed as an appropriate water resources management technique for matching these different scales. A major component of this thesis is a review of the South African water resources management framework and, in particular, the role of the Reserve (comprising a basic human right to survival water as well as an ecological right of the aquatic resource to maintain ecological functioning) in facilitating ecologically sustainable water resources management. South African water resources management is in the early stages of water allocation reform and the Department of Water Affairs and Forestry has stated that "the water allocation process must allow for the sustainable use of water resources and must promote the efficient and non-wasteful use of water". Thus, new ways of approaching the compromise between ecological and societal needs for freshwater water are required. This thesis argues that this requires that the focus of freshwater ecosystems be extended beyond the aquatic resource, so that societal activities on the catchment are linked to the protection of instream flows. Streamflow variability plays a major role in structuring the habitat templates that sustain aquatic and riparian ecological functioning and has been associated with increased biodiversity. Biodiversity and societal well-being are interlinked. However, there is a need in EFA for knowledge of the most influential components of the streamflow regime in order that stakeholders may anticipate any change in ecosystem goods and services as a result of their disruption to the hydrological cycle. The identification of high information hydrological indicators for characterising highly variable streamflow regimes is useful to water resources management, particularly where thresholds of streamflow regime characteristics have ecological relevance. Several researchers have revisited the choice of hydrological indices in order to ascertain whether some indices explain more of the hydrological variability in different aspects of streamflow regimes than others. However, most of the research relating to hydrological indices has focused primarily on regions with temperate climates. In this thesis multivariate analysis is applied to a relatively large dataset of readily computed ecologically relevant hydrological indices (including the Indicators of Hydrological Alteration and the South African Desktop Reserve Model indices) extracted from long-term records of daily flows at 83 sites across South Africa. Principal Component Analysis is applied in order to highlight general patterns of intercorrelation, or redundancy, among the indices and to identify a minimum subset of hydrological indices which explain the majority of the variation among the indices of different components of the streamflow regimes found in South Africa. The results indicate the value of including several of the IHA indices in EFAs for South African rivers. Statistical analysis is meaningful only when calculated for a sufficiently long hydrological record, and in this thesis the length of record necessary to obtain consistent hydrological indices, with minimal influence of climatic variation, is investigated. The results provide a guide to the length of record required for analysis of the high information hydrological indices representing the main components of the streamflow regime, for different streamflow types. An ecosystem-based approach which recognises the hydrological connectivity of the catchment landscape in linking aquatic and terrestrial systems is proposed as a framework for ecologically sustainable water resources management. While this framework is intended to be generic, its potential for application in the South African Water Allocation Reform is illustrated with a case study for the Mkomazi Catchment in KwaZulu-Natal. Hydronomic sub-zoning, based on the way in which societal activities disrupt the natural hydrological processes, both off-stream and instream, is applied to assess the incompatibilities between societal and ecological freshwater needs. Reference hydrological, or pre-development, conditions in the Mkomazi Catchment are simulated using the ACRU agrohydrological model. Management targets, based on the statistical analysis of pre-development streamflow regimes, are defined to assess the degree of hydrological alteration in the high information hydrological indices of the Mkomazi Catchment as a result of different societal activities. Hydrological alteration from predevelopment conditions is assessed using the Range of Variability Approach. The results indicate that the proposed framework is useful to the formulation of stakeholder-based catchment management plans. Applying hydrological records (either observed or simulated) as an ecological resource is highly appropriate for assessing the variability that ecosystems need to maintain the biodiversity, ecological functioning and resilience that people and society desire.
Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2006.

AbstractThe impacts of climate change are already being felt, not only in terms of increase in temperature but also in respect of inadequate water availability. The Mkomazi River Basins (MRB) of the KwaZulu-Natal region, South Africa serves as major source of water and thus a mainstay of livelihood for millions of people living downstream. It is in this context that the study investigates water flows abstraction from headwaters to floodplains and how the water resources are been impacted by seasonal climate variability. Artificial Neural Network (ANN) pattern classifier was utilized for the seasonal classification and subsequence hydrological flow regime prediction between the upstream–downstream anomalies. The ANN input hydroclimatic data analysis results covering the period 2008–2015 provides a likelihood forecast of high, near-median, or low streamflow. The results show that monthly mean water yield range is 28.6–36.0 m3/s over the Basin with a coefficient of correlation (CC) values of 0.75 at the validation stage. The yearly flow regime exhibits considerable changes with different magnitudes and patterns of increase and decrease in the climatic variables. No doubt, added activities and processes such as land-use change and managerial policies in upstream areas affect the spatial and temporal distribution of available water resources to downstream regions. The study has evolved an artificial neuron system thinking from conjunctive streamflow prediction toward sustainable water allocation planning for medium- and long-term purposes.