- Title
- Quantification of water resources uncertainties in two sub-basins of the Limpopo River basin
- Creator
- Oosthuizen, Nadia
- ThesisAdvisor
- Hughes, D A (Denis A)
- ThesisAdvisor
- Kapangaziwiri, E
- ThesisAdvisor
- Mwenge Kahinda, J
- Subject
- Hydrologic models -- Limpopo River Watershed
- Subject
- Water-supply -- Limpopo River Watershed
- Subject
- Water-supply -- Management
- Subject
- Sustainable development
- Subject
- Rain and rainfall -- Mathematical models
- Subject
- Runoff -- Mathematical models
- Subject
- Reservoirs -- Limpopo River Watershed
- Date
- 2018
- Type
- text
- Type
- Thesis
- Type
- Masters
- Type
- MSc
- Identifier
- http://hdl.handle.net/10962/63267
- Identifier
- vital:28388
- Description
- The demand for water is rapidly growing, placing more strain on access to the resources and subsequently its management. For sustainable management, there is a need to accurately quantify the available water resources. Unfortunately, the data required for such assessments are frequently far from sufficient in terms of availability and quality, especially in southern Africa. In the absence of historical observed data, models are generally used to describe the different hydrological processes and generate data and information that will inform management and policy decision making. Ideally, any hydrological model should be based on a sound conceptual understanding of the processes in the basin and be backed by quantitative information for the parameterization of the model. Such data is however, often inadequate in many sub-basins necessitating the incorporation of the uncertainty related to the estimation process. Model parameter estimation and input data are significant sources of uncertainty that should be quantified. Also, in southern Africa water use data are unreliable because available databases consist of licensed information and actual use is generally unknown. In this study, the water resources of two sub-basins of the Limpopo River basin – the Mogalakwena in South Africa and the Shashe shared between Botswana and Zimbabwe – are estimated. The study assessed how uncertainties in the Pitman model parameterisation and input water use data affect the estimation of surface water resources of the selected sub-basins. Farm reservoirs and irrigated areas data from various sources were collected and used to run the Pitman model. Results indicate that the total model output uncertainty is higher for the Shashe sub-basin which is more data scarce than the Mogalakwena sub-basin. The study illustrates the importance of including uncertainty in the water resources assessment process to provide baseline data for decision making in resource management and planning. The study reviews existing information sources associated with the quantification of water balance components and gives an update of water resources of the sub-basin. The flows generated by the model at the outlet of the basin were between 22.6 Mm3 and 24.7 Mm3 per month when incorporating uncertainty to the main physical runoff generating parameters. The total predictive uncertainty of the model increased to between 22.2 Mm3 and 25.0 Mm3 when anthropogenic water use data such as small farm and large reservoirs and irrigation were included. The flows generated for Shashe was between 11.7 Mm3 and 14.5 Mm3 per month when incorporating uncertainty to the main physical runoff generating parameters. The predictive uncertainty of the model changed to 11.7 Mm3 and 17.7 Mm3 after the water use uncertainty was added. However, it is expected that the uncertainty could be reduced by using higher resolution remote sensing imagery.
- Format
- 128 pages, pdf
- Publisher
- Rhodes University, Faculty of Science, Institute for Water Research
- Language
- English
- Rights
- Oosthuizen, Nadia
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Collections
RU Institute for Water Research, including the Unilever Centre for Environmental Water Quality (IWR)
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