The application of the monthly time step Pitman rainfall-runoff model to the Kafue River basin of Zambia
- Mwelwa, Elenestina Mutekenya
- Authors: Mwelwa, Elenestina Mutekenya
- Date: 2005
- Subjects: Kafue River (Zambia) , Kafue Flats (Zambia) , Floodplains -- Zambia , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6032 , http://hdl.handle.net/10962/d1006171 , Kafue River (Zambia) , Kafue Flats (Zambia) , Floodplains -- Zambia , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models
- Description: This thesis presents a discussion on the study undertaken in the application of the monthly time step Pitman rainfall-runoff model to the Kafue River basin. The study constituted one of the initial steps in the capacity building and expansion of the application of hydrologic models in the southern African region for water resources assessment, one of the core areas of the Southern African FRIEND project (Flow Regimes from International Experimental Network Data). The research process was undertaken in four major stages, each stage working towards achieving the research objectives. The first stage was the preparation of spatial data which included the selection and delineation of sub-catchments and inclusion of spatial features required to run the Pitman model and transferring the spatial data into SPATSIM. The second stage was the preparation of input data, mainly rainfall, streamflow, evaporation, and water abstraction data. This information was then imported into SPATSIM, which was able to assist in the further preparation of data by assessment of the input data quality, linking of observed flows and spatial interpolation of point rainfall data to average catchment rainfall in readiness for running and calibration of the model. The third stage was the running and calibration of the Pitman model. Use was made of both the automatic calibration facility, as well as manual calibration by means of the time series graph display and analysis facility of SPATSIM. Model calibration was used to obtain the best fit and an acceptable correlation between the simulated and the observed flows and to obtain simulation parameter sets for sub-catchments and regions within the Kafue catchment. The fourth stage was the analysis and evaluation of the model results. This included verification of results over different time periods and validation and testing of parameter transfers to other catchments. This stage also included the evaluation of SPATSIM as a tool for applying the model and as a database for the processing and storage of water resources data. The study’s output includes: A comprehensive database of hydrometeorological, physical catchment characteristics, landuse and water abstraction information for the Kafue basin; calibrated Pitman model parameters for the sub-catchments within the Kafue basin; recommendations for future work and data collection programmes for the application of the model. The study has also built capacity by facilitating training and exposure to rainfall-runoff models (specifically the Pitman model) and associated software, SPATSIM. In addition, the dissemination of the results of this study will serve as an effective way of raising awareness on the application of the Pitman model and the use of the SPATSIM software within Zambia and the region. The overall Pitman model results were found to be satisfactory and the calibrated model is able to reproduce the observed spatial and temporal variations in streamflow characteristics in the Kafue River basin.
- Full Text:
- Date Issued: 2005
- Authors: Mwelwa, Elenestina Mutekenya
- Date: 2005
- Subjects: Kafue River (Zambia) , Kafue Flats (Zambia) , Floodplains -- Zambia , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6032 , http://hdl.handle.net/10962/d1006171 , Kafue River (Zambia) , Kafue Flats (Zambia) , Floodplains -- Zambia , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models
- Description: This thesis presents a discussion on the study undertaken in the application of the monthly time step Pitman rainfall-runoff model to the Kafue River basin. The study constituted one of the initial steps in the capacity building and expansion of the application of hydrologic models in the southern African region for water resources assessment, one of the core areas of the Southern African FRIEND project (Flow Regimes from International Experimental Network Data). The research process was undertaken in four major stages, each stage working towards achieving the research objectives. The first stage was the preparation of spatial data which included the selection and delineation of sub-catchments and inclusion of spatial features required to run the Pitman model and transferring the spatial data into SPATSIM. The second stage was the preparation of input data, mainly rainfall, streamflow, evaporation, and water abstraction data. This information was then imported into SPATSIM, which was able to assist in the further preparation of data by assessment of the input data quality, linking of observed flows and spatial interpolation of point rainfall data to average catchment rainfall in readiness for running and calibration of the model. The third stage was the running and calibration of the Pitman model. Use was made of both the automatic calibration facility, as well as manual calibration by means of the time series graph display and analysis facility of SPATSIM. Model calibration was used to obtain the best fit and an acceptable correlation between the simulated and the observed flows and to obtain simulation parameter sets for sub-catchments and regions within the Kafue catchment. The fourth stage was the analysis and evaluation of the model results. This included verification of results over different time periods and validation and testing of parameter transfers to other catchments. This stage also included the evaluation of SPATSIM as a tool for applying the model and as a database for the processing and storage of water resources data. The study’s output includes: A comprehensive database of hydrometeorological, physical catchment characteristics, landuse and water abstraction information for the Kafue basin; calibrated Pitman model parameters for the sub-catchments within the Kafue basin; recommendations for future work and data collection programmes for the application of the model. The study has also built capacity by facilitating training and exposure to rainfall-runoff models (specifically the Pitman model) and associated software, SPATSIM. In addition, the dissemination of the results of this study will serve as an effective way of raising awareness on the application of the Pitman model and the use of the SPATSIM software within Zambia and the region. The overall Pitman model results were found to be satisfactory and the calibrated model is able to reproduce the observed spatial and temporal variations in streamflow characteristics in the Kafue River basin.
- Full Text:
- Date Issued: 2005
Revised parameter estimation methods for the Pitman monthly rainfall-runoff model
- Authors: Kapangaziwiri, Evison
- Date: 2008
- Subjects: Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models , Water supply -- South Africa , Water resources development -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6033 , http://hdl.handle.net/10962/d1006172 , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models , Water supply -- South Africa , Water resources development -- South Africa
- Description: In recent years, increased demands have been placed on hydrologists to find the most effective methods of making predictions of hydrologic variables in ungauged basins. A huge part of the southern African region is ungauged and, in gauged basins, the extent to which observed flows represent natural flows is unknown, given unquantified upstream activities. The need to exploit water resources for social and economic development, considered in the light of water scarcity forecasts for the region, makes the reliable quantification of water resources a priority. Contemporary approaches to the problem of hydrological prediction in ungauged basins in the region have relied heavily on calibration against a limited gauged streamflow database and somewhat subjective parameter regionalizations using areas of assumed hydrological similarity. The reliance of these approaches on limited historical records, often of dubious quality, introduces uncertainty in water resources decisions. Thus, it is necessary to develop methods of estimating model parameters that are less reliant on calibration. This thesis addresses the question of whether physical basin properties and the role they play in runoff generation processes can be used directly in the estimation of parameter values of the Pitman monthly rainfall-runoff model. A physically-based approach to estimating the soil moisture accounting and runoff parameters of a conceptual, monthly time-step rainfall-runoff model is proposed. The study investigates the physical meaning of the model parameters, establishes linkages between parameter values and basin physical properties and develops relationships and equations for estimating the parameters taking into account the spatial and temporal scales used in typical model applications. The estimationmethods are then tested in selected gauged basins in southern Africa and the results of model simulations evaluated against historical observed flows. The results of 71 basins chosen from the southern African region suggest that it is possible to directly estimate hydrologically relevant parameters for the Pitman model from physical basin attributes. For South Africa, the statistical and visual fit of the simulations using the revised parameters were at least as good as the current regional sets, albeit the parameter sets being different. In the other countries where no regionalized parameter sets currently exist, simulations were equally good. The availability, within the southern African region, of the appropriate physical basin data and the disparities in the spatial scales and the levels of detail of the data currently available were identified as potential sources of uncertainty. GIS and remote sensing technologies and a widespread use of this revised approach are expected to facilitate access to these data.
- Full Text:
- Date Issued: 2008
- Authors: Kapangaziwiri, Evison
- Date: 2008
- Subjects: Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models , Water supply -- South Africa , Water resources development -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6033 , http://hdl.handle.net/10962/d1006172 , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Hydrology -- Mathematical models , Water supply -- South Africa , Water resources development -- South Africa
- Description: In recent years, increased demands have been placed on hydrologists to find the most effective methods of making predictions of hydrologic variables in ungauged basins. A huge part of the southern African region is ungauged and, in gauged basins, the extent to which observed flows represent natural flows is unknown, given unquantified upstream activities. The need to exploit water resources for social and economic development, considered in the light of water scarcity forecasts for the region, makes the reliable quantification of water resources a priority. Contemporary approaches to the problem of hydrological prediction in ungauged basins in the region have relied heavily on calibration against a limited gauged streamflow database and somewhat subjective parameter regionalizations using areas of assumed hydrological similarity. The reliance of these approaches on limited historical records, often of dubious quality, introduces uncertainty in water resources decisions. Thus, it is necessary to develop methods of estimating model parameters that are less reliant on calibration. This thesis addresses the question of whether physical basin properties and the role they play in runoff generation processes can be used directly in the estimation of parameter values of the Pitman monthly rainfall-runoff model. A physically-based approach to estimating the soil moisture accounting and runoff parameters of a conceptual, monthly time-step rainfall-runoff model is proposed. The study investigates the physical meaning of the model parameters, establishes linkages between parameter values and basin physical properties and develops relationships and equations for estimating the parameters taking into account the spatial and temporal scales used in typical model applications. The estimationmethods are then tested in selected gauged basins in southern Africa and the results of model simulations evaluated against historical observed flows. The results of 71 basins chosen from the southern African region suggest that it is possible to directly estimate hydrologically relevant parameters for the Pitman model from physical basin attributes. For South Africa, the statistical and visual fit of the simulations using the revised parameters were at least as good as the current regional sets, albeit the parameter sets being different. In the other countries where no regionalized parameter sets currently exist, simulations were equally good. The availability, within the southern African region, of the appropriate physical basin data and the disparities in the spatial scales and the levels of detail of the data currently available were identified as potential sources of uncertainty. GIS and remote sensing technologies and a widespread use of this revised approach are expected to facilitate access to these data.
- Full Text:
- Date Issued: 2008
Quantification of water resources uncertainties in two sub-basins of the Limpopo River basin
- Authors: Oosthuizen, Nadia
- Date: 2018
- Subjects: Hydrologic models -- Limpopo River Watershed , Water-supply -- Limpopo River Watershed , Water-supply -- Management , Sustainable development , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Reservoirs -- Limpopo River Watershed
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/63267 , 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.
- Full Text:
- Date Issued: 2018
- Authors: Oosthuizen, Nadia
- Date: 2018
- Subjects: Hydrologic models -- Limpopo River Watershed , Water-supply -- Limpopo River Watershed , Water-supply -- Management , Sustainable development , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models , Reservoirs -- Limpopo River Watershed
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/63267 , 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.
- Full Text:
- Date Issued: 2018
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