The development potential of Kwazulu-Natal aquifers for rural water supply
- Authors: King, Georgina
- Date: 1997
- Subjects: Aquifers -- South Africa -- KwaZulu-Natal , Water-supply, Rural -- South Africa -- KwaZulu-Natal , Hydrology -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4938 , http://hdl.handle.net/10962/d1005550 , Aquifers -- South Africa -- KwaZulu-Natal , Water-supply, Rural -- South Africa -- KwaZulu-Natal , Hydrology -- South Africa
- Description: The supply of water to 'disadvantaged' areas of KwaZulu-Natal has in the past received low priority. Local government is now faced with supplying water to large, sometimes dispersed, rural populations. Groundwater has been utilised informally as a water supply for some years, but the impetus provided by the Department of Water Affairs and Forestry's White Paper has compelled those responsible for water supply to seriously consider groundwater as a sustainable option. The development potential or success of groundwater in its role as a reliable water supply is dependent on acceptance of the resource by the communities, appropriate level of service, yield sustainability and safe quality. Apart from the social aspects, the yield and groundwater quality characteristics of the aquifers under consideration must be used to determine the best hydrogeological features to target during exploration. A total of 993 borehole records, from a recent government drought relief programme, were used to compare the yield, water quality and best geophysical exploration and drilling techniques of the main hydrolithologies in rural KwaZulu-Natal. The results of comparative analysis shows that the competent rocks of the Natal Group and Natal Metamorphic Province and the karstic Uloa Formation of the Maputaland Group have the best overall potential for water supply. The unconsolidated sediments of the Maputaland Group also have good potential, but have some salinity problems. The Karoo Supergroup sediments and volcanics have moderate potential, with the argillaceous rocks having the worst potential of the Karoo rocks. The contacts between the Ecca Group shales and sandstone have the best potential of the Karoo Supergroup sedimentary hydrolithologies. Fractures clearly enhance the groundwater potential of most hydrolithologies, with fractured Dwyka Group tillites rated as having one of the best development potentials of all the hydrogeological targets in KwaZulu-Natal, despite the hydrolithology's poor water-bearing characteristics. Dolerite contacts with sedimentary rocks are commonly targeted features in groundwater development. However, the results from this research showed that, apart from the Natal Group's contact with dolerite, these targets have poor development potential. In general, contacts between different hydro lithologies. Health related quality was found to be adversely affected in argillaceous hydrolithologies, such as the majority of Karoo rocks which had high levels of sodium and chloride and Natal Metamorphic Province schists which had elevated sodium, chloride and fluoride. Crystalline and arenaceous hydrolithologies generally exhibited good quality groundwater. A comparison between the different geophysical methods for each target feature indicates that there are appropriate methods to use to detect anomalies related to water-bearing features. The large number of dry boreholes drilled in locations with recorded geophysical anomalies can be either a function of the water-bearing characteristics of the formation, human error or background noise. The cost of using the different geophysical methods vary considerably. The order of increasing cost is magnetics, VLF, EM-34, electrical resistivity profiling followed by vertical electrical sounding. Drilling has a large influence on the development potential of certain aquifers due to the high costs involved. Most of the secondary aquifers will require percussion drilling which is the cheapest method of drilling commonly used. Some very unstable formations within fractured or highly weathered rock may need ODEX drilling to enable drilling to advance. ODEX drilling in these conditions is very costly and can double the cost of drilling compared to air percussion. The unconsolidated sediments of the Maputaland Group can only be drilled by mud rotary or ODEX techniques. The relative costs of these two methods arer very similar with ODEX being slightly cheaper. Because of the high expense of drilling in the sands it is recommended that alternative sources, possibly from shallow hand-dug wells, be considered as appropriate methods of accessing groundwater. The aspects of groundwater yield and quality of aquifers, appropriate geophysical siting and drilling methods, together with social considerations will all contribute to the success of groundwater development in rural KwaZulu-Natal.
- Full Text:
- Date Issued: 1997
- Authors: King, Georgina
- Date: 1997
- Subjects: Aquifers -- South Africa -- KwaZulu-Natal , Water-supply, Rural -- South Africa -- KwaZulu-Natal , Hydrology -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4938 , http://hdl.handle.net/10962/d1005550 , Aquifers -- South Africa -- KwaZulu-Natal , Water-supply, Rural -- South Africa -- KwaZulu-Natal , Hydrology -- South Africa
- Description: The supply of water to 'disadvantaged' areas of KwaZulu-Natal has in the past received low priority. Local government is now faced with supplying water to large, sometimes dispersed, rural populations. Groundwater has been utilised informally as a water supply for some years, but the impetus provided by the Department of Water Affairs and Forestry's White Paper has compelled those responsible for water supply to seriously consider groundwater as a sustainable option. The development potential or success of groundwater in its role as a reliable water supply is dependent on acceptance of the resource by the communities, appropriate level of service, yield sustainability and safe quality. Apart from the social aspects, the yield and groundwater quality characteristics of the aquifers under consideration must be used to determine the best hydrogeological features to target during exploration. A total of 993 borehole records, from a recent government drought relief programme, were used to compare the yield, water quality and best geophysical exploration and drilling techniques of the main hydrolithologies in rural KwaZulu-Natal. The results of comparative analysis shows that the competent rocks of the Natal Group and Natal Metamorphic Province and the karstic Uloa Formation of the Maputaland Group have the best overall potential for water supply. The unconsolidated sediments of the Maputaland Group also have good potential, but have some salinity problems. The Karoo Supergroup sediments and volcanics have moderate potential, with the argillaceous rocks having the worst potential of the Karoo rocks. The contacts between the Ecca Group shales and sandstone have the best potential of the Karoo Supergroup sedimentary hydrolithologies. Fractures clearly enhance the groundwater potential of most hydrolithologies, with fractured Dwyka Group tillites rated as having one of the best development potentials of all the hydrogeological targets in KwaZulu-Natal, despite the hydrolithology's poor water-bearing characteristics. Dolerite contacts with sedimentary rocks are commonly targeted features in groundwater development. However, the results from this research showed that, apart from the Natal Group's contact with dolerite, these targets have poor development potential. In general, contacts between different hydro lithologies. Health related quality was found to be adversely affected in argillaceous hydrolithologies, such as the majority of Karoo rocks which had high levels of sodium and chloride and Natal Metamorphic Province schists which had elevated sodium, chloride and fluoride. Crystalline and arenaceous hydrolithologies generally exhibited good quality groundwater. A comparison between the different geophysical methods for each target feature indicates that there are appropriate methods to use to detect anomalies related to water-bearing features. The large number of dry boreholes drilled in locations with recorded geophysical anomalies can be either a function of the water-bearing characteristics of the formation, human error or background noise. The cost of using the different geophysical methods vary considerably. The order of increasing cost is magnetics, VLF, EM-34, electrical resistivity profiling followed by vertical electrical sounding. Drilling has a large influence on the development potential of certain aquifers due to the high costs involved. Most of the secondary aquifers will require percussion drilling which is the cheapest method of drilling commonly used. Some very unstable formations within fractured or highly weathered rock may need ODEX drilling to enable drilling to advance. ODEX drilling in these conditions is very costly and can double the cost of drilling compared to air percussion. The unconsolidated sediments of the Maputaland Group can only be drilled by mud rotary or ODEX techniques. The relative costs of these two methods arer very similar with ODEX being slightly cheaper. Because of the high expense of drilling in the sands it is recommended that alternative sources, possibly from shallow hand-dug wells, be considered as appropriate methods of accessing groundwater. The aspects of groundwater yield and quality of aquifers, appropriate geophysical siting and drilling methods, together with social considerations will all contribute to the success of groundwater development in rural KwaZulu-Natal.
- Full Text:
- Date Issued: 1997
Evaluating uncertainty in water resources estimation in Southern Africa : a case study of South Africa
- Authors: Sawunyama, Tendai
- Date: 2009
- Subjects: Water supply -- South Africa , Water supply -- Africa, Southern , Hydrology -- South Africa , Hydrology -- Africa, Southern , Hydrologic models , Hydrology research -- South Africa , Hydrology research -- Africa, Southern , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:6035 , http://hdl.handle.net/10962/d1006176
- Description: Hydrological models are widely used tools in water resources estimation, but they are simple representations of reality and are frequently based on inadequate input data and uncertainties in parameter values. Data observation networks are expensive to establish and maintain and often beyond the resources of most developing countries. Consequently, measurements are difficult to obtain and observation networks in many countries are shrinking, hence obtaining representative observations in space and time remains a challenge. This study presents some guidelines on the identification, quantification and reduction of sources of uncertainty in water resources estimation in southern Africa, a data scarce region. The analyses are based on example sub-basins drawn from South Africa and the application of the Pitman hydrological model. While it has always been recognised that estimates of water resources availability for the region are subject to possible errors, the quantification of these uncertainties has never been explicitly incorporated into the methods used in the region. The motivation for this study was therefore to contribute to the future development of a revised framework for water resources estimation that does include uncertainty. The focus was on uncertainties associated with climate input data, parameter estimation (and recognizing the uncertainty due model structure deficiencies) methods and water use data. In addition to variance based measures of uncertainty, this study also used a reservoir yield based statistic to evaluate model output uncertainty, which represents an integrated measure of flow regime variations and one that can be more easily understood by water resources managers. Through a sensitivity analysis approach, the results of the individual contribution of each source of uncertainty suggest regional differences and that clear statements about which source of uncertainty is likely to dominate are not generally possible. Parameter sensitivity analysis was used in identifying parameters which are important withinspecific sub-basins and therefore those to focus on in uncertainty analysis. The study used a simple framework for evaluating the combined contribution of uncertainty sources to model outputs that is consistent with the model limitations and data available, and that allows direct quantitative comparison between model outputs obtained by using different sources of information and methods within Spatial and Time Series Information Modelling (SPATSIM) software. The results from combining the sources of uncertainties showed that parameter uncertainty dominates the contribution to model output uncertainty. However, in some parts of the country especially those with complex topography, which tend to experience high rainfall spatial variability, rainfall uncertainty is equally dominant, while the contributions of evaporation and water use data uncertainty are relatively small. While the results of this study are encouraging, the weaknesses of the methods used to quantify uncertainty (especially subjectivity involved in evaluating parameter uncertainty) should not be neglected and require further evaluations. An effort to reduce data and parameter uncertainty shows that this can only be achieved if data access at appropriate scale and quality improves. Perhaps the focus should be on maintaining existing networks and concentrating research efforts on making the most out of the emerging data products derived from remote sensing platforms. While this study presents some initial guidelines for evaluating uncertainty in South Africa, there is need to overcome several constraints which are related to data availability and accuracy, the models used and the capacity or willingness to adopt new methods that incorporate uncertainty. The study has provided a starting point for the development of new approaches to modelling water resources in the region that include uncertain estimates.
- Full Text:
- Date Issued: 2009
- Authors: Sawunyama, Tendai
- Date: 2009
- Subjects: Water supply -- South Africa , Water supply -- Africa, Southern , Hydrology -- South Africa , Hydrology -- Africa, Southern , Hydrologic models , Hydrology research -- South Africa , Hydrology research -- Africa, Southern , Rain and rainfall -- Mathematical models , Runoff -- Mathematical models
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:6035 , http://hdl.handle.net/10962/d1006176
- Description: Hydrological models are widely used tools in water resources estimation, but they are simple representations of reality and are frequently based on inadequate input data and uncertainties in parameter values. Data observation networks are expensive to establish and maintain and often beyond the resources of most developing countries. Consequently, measurements are difficult to obtain and observation networks in many countries are shrinking, hence obtaining representative observations in space and time remains a challenge. This study presents some guidelines on the identification, quantification and reduction of sources of uncertainty in water resources estimation in southern Africa, a data scarce region. The analyses are based on example sub-basins drawn from South Africa and the application of the Pitman hydrological model. While it has always been recognised that estimates of water resources availability for the region are subject to possible errors, the quantification of these uncertainties has never been explicitly incorporated into the methods used in the region. The motivation for this study was therefore to contribute to the future development of a revised framework for water resources estimation that does include uncertainty. The focus was on uncertainties associated with climate input data, parameter estimation (and recognizing the uncertainty due model structure deficiencies) methods and water use data. In addition to variance based measures of uncertainty, this study also used a reservoir yield based statistic to evaluate model output uncertainty, which represents an integrated measure of flow regime variations and one that can be more easily understood by water resources managers. Through a sensitivity analysis approach, the results of the individual contribution of each source of uncertainty suggest regional differences and that clear statements about which source of uncertainty is likely to dominate are not generally possible. Parameter sensitivity analysis was used in identifying parameters which are important withinspecific sub-basins and therefore those to focus on in uncertainty analysis. The study used a simple framework for evaluating the combined contribution of uncertainty sources to model outputs that is consistent with the model limitations and data available, and that allows direct quantitative comparison between model outputs obtained by using different sources of information and methods within Spatial and Time Series Information Modelling (SPATSIM) software. The results from combining the sources of uncertainties showed that parameter uncertainty dominates the contribution to model output uncertainty. However, in some parts of the country especially those with complex topography, which tend to experience high rainfall spatial variability, rainfall uncertainty is equally dominant, while the contributions of evaporation and water use data uncertainty are relatively small. While the results of this study are encouraging, the weaknesses of the methods used to quantify uncertainty (especially subjectivity involved in evaluating parameter uncertainty) should not be neglected and require further evaluations. An effort to reduce data and parameter uncertainty shows that this can only be achieved if data access at appropriate scale and quality improves. Perhaps the focus should be on maintaining existing networks and concentrating research efforts on making the most out of the emerging data products derived from remote sensing platforms. While this study presents some initial guidelines for evaluating uncertainty in South Africa, there is need to overcome several constraints which are related to data availability and accuracy, the models used and the capacity or willingness to adopt new methods that incorporate uncertainty. The study has provided a starting point for the development of new approaches to modelling water resources in the region that include uncertain estimates.
- Full Text:
- Date Issued: 2009
Effects of digital elevation model data resolution on hydrological modelling using SWAT: a case study of the Swartkops river catchment
- Authors: Loni, Litha
- Date: 2025-04
- Subjects: Digital elevation models -- South Africa , Hydrology -- South Africa , Water-supply -- South Africa
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/75987 , vital:80104
- Description: Digital Elevation Models (DEMs) are widely used as input to model hydrological processes. Using the appropriate resolution of DEMs is critical in producing accurate simulations of hydrological processes using hydrological models such as the Soil and Water Assessment Tool (SWAT) model. As a result of the availability of DEMs in recent decades and land use/cover (LULC) change impacts on hydrological regimes, the aim of this study was to investigate the effect of DEM data resolution on SWAT model performance for analysing the hydrological response to LULC changes in the Swartkops River catchment. This included using the SWAT model to analyse runoff conditions in the catchment. The main objectives of the study were: (1) to generate LULC maps and analyse LULC changes using Multi-Temporal Landsat TM and OLI images from 1990 to 2022 within the Swartkops catchment using IDRISI Terrset and ArcMap 10.7; (2) to assess the influence of different DEM data resolutions on SWAT model performance via the quantification of model results; and (3) to utilise the SWAT model with optimal performance to analyse the impact of LULC change on the hydrological response (i.e., runoff generation) of the Swartkops catchment using ArcSWAT. To do this, 1990 and 2022 Landsat images were acquired, pre-processed, and classified using supervised image classification via the Maximum Likelihood algorithm. Idrisi Terrset software was used process the Landsat images by generating natural colour composite images which were then used to sample training sites. A stratified random sampling approach was employed which produced spectral signature files which were the basis for employing the Maximum Likelihood classifier to classify the images. Classified images were exported to ArcMap 10.7 where they underwent classification accuracy assessments. An error matrix approach was implemented, and the accuracy of the maps was assessed using the producer’s, user’s, overall and Kappa accuracy. Thereafter, LULC changes were quantified using ArcMap 10.7 by determining the area difference of each LULC type between 1990 and 2022. The SWAT models for the different resolution DEMs (i.e., 20m, 30m, and 90m) were set up on ArcSWAT, and the Swartkops catchment was delineated, subdivided into Hydrological Response Units, and run by inserting all the relevant input data such as LULC data (i.e., 1990, and 2022 classified maps), topographic data (i.e., the DEMs), soil data (i.e., FAO map), and weather data. Statistical evaluations for the performance rating of the models were conducted and incorporated the use of statistical parameters such as Nash-Sutcliffe Efficiency (NSE), Percentage of Bias (PBIAS), Coefficient of determination ((R2), and RMSE-Observation standard deviation ratio (RSR) for assessing the performance of each SWAT model. The model producing the most satisfactory performance was used to compute runoff conditions for the Swartkops catchment. Computations were conducted using the Soil Conservation Service (SCS) curve number method. Fieldwork, which incorporated measuring iii runoff for different LULC types using Gerlach troughs at hillslope scale, was conducted to validate the results of the SWAT model. Results indicated that the 1990 and 2022 LULC maps had an overall accuracy of 87.11% and 94.89%, respectively which was highly satisfactory. The Kappa statistics reflected similar results where the 1990 map had a value of 0.84 while the 2022 map had a value of 0.94, indicating high statistical agreement between the classified maps and the reference data. The study also found that bare areas exuberated the greatest area change with a decline of 9.49%, while built-up areas manifested the highest increase of 5.97% from 1990 to 2022. Agricultural land increased by 4.79% in conjunction with a slight increase of 0.44% by green vegetation while water declined by 1.71%. To determine the ideal DEM to analyse hydrological response, the LULC maps in conjunction with other input data were inserted into the SWAT model to assess model performance. It was found that the 30m produced satisfactory model performance (NSE = 0.49 at calibration and 0.67 at validation) and was eligible to assess runoff conditions as a function of LULC change. Other statistics indicated satisfactory model performance at calibration (PBIAS = 48.80, R2 = 0.51, RSR = 1.02) and validation stage (PBIAS = -38.1, R2 = 0.47, RSR = 1.08). The 90m DEM possessed the poorest model performance (NSE = 0.18 at calibration and 0.35 at validation) followed by the 20m DEM (NSE = 0.41 at calibration and 0.32 at validation). Runoff simulations using the 30m SWAT model showed that surface runoff was highest in areas where there were built-up areas. Built-up areas and bare areas yielded 36% of the total surface runoff individually, while vegetation produced only 28% in 1990. Similar readings were obtained for 2022, which included agricultural land that produced 29% of the surface runoff. Runoff volume measured at hillslope scale was highest in bare areas (6.6 L) and built-up areas (9.3 L). Therefore, this study shows that the resolution of DEMs must concur with the relevant scale of the study to produce optimal results. Additionally, this study showed that a change in LULC heavily affects the amount of surface runoff generated, which has several implications in terms of flooding. Therefore, this study is useful as it will inform sustainable catchment management decisions, and water resource management, and enhance our understanding of the relationships between DEM spatial resolution, LULC change, SWAT modelling, and water quantity calculations. , Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2025
- Full Text:
- Date Issued: 2025-04
- Authors: Loni, Litha
- Date: 2025-04
- Subjects: Digital elevation models -- South Africa , Hydrology -- South Africa , Water-supply -- South Africa
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/75987 , vital:80104
- Description: Digital Elevation Models (DEMs) are widely used as input to model hydrological processes. Using the appropriate resolution of DEMs is critical in producing accurate simulations of hydrological processes using hydrological models such as the Soil and Water Assessment Tool (SWAT) model. As a result of the availability of DEMs in recent decades and land use/cover (LULC) change impacts on hydrological regimes, the aim of this study was to investigate the effect of DEM data resolution on SWAT model performance for analysing the hydrological response to LULC changes in the Swartkops River catchment. This included using the SWAT model to analyse runoff conditions in the catchment. The main objectives of the study were: (1) to generate LULC maps and analyse LULC changes using Multi-Temporal Landsat TM and OLI images from 1990 to 2022 within the Swartkops catchment using IDRISI Terrset and ArcMap 10.7; (2) to assess the influence of different DEM data resolutions on SWAT model performance via the quantification of model results; and (3) to utilise the SWAT model with optimal performance to analyse the impact of LULC change on the hydrological response (i.e., runoff generation) of the Swartkops catchment using ArcSWAT. To do this, 1990 and 2022 Landsat images were acquired, pre-processed, and classified using supervised image classification via the Maximum Likelihood algorithm. Idrisi Terrset software was used process the Landsat images by generating natural colour composite images which were then used to sample training sites. A stratified random sampling approach was employed which produced spectral signature files which were the basis for employing the Maximum Likelihood classifier to classify the images. Classified images were exported to ArcMap 10.7 where they underwent classification accuracy assessments. An error matrix approach was implemented, and the accuracy of the maps was assessed using the producer’s, user’s, overall and Kappa accuracy. Thereafter, LULC changes were quantified using ArcMap 10.7 by determining the area difference of each LULC type between 1990 and 2022. The SWAT models for the different resolution DEMs (i.e., 20m, 30m, and 90m) were set up on ArcSWAT, and the Swartkops catchment was delineated, subdivided into Hydrological Response Units, and run by inserting all the relevant input data such as LULC data (i.e., 1990, and 2022 classified maps), topographic data (i.e., the DEMs), soil data (i.e., FAO map), and weather data. Statistical evaluations for the performance rating of the models were conducted and incorporated the use of statistical parameters such as Nash-Sutcliffe Efficiency (NSE), Percentage of Bias (PBIAS), Coefficient of determination ((R2), and RMSE-Observation standard deviation ratio (RSR) for assessing the performance of each SWAT model. The model producing the most satisfactory performance was used to compute runoff conditions for the Swartkops catchment. Computations were conducted using the Soil Conservation Service (SCS) curve number method. Fieldwork, which incorporated measuring iii runoff for different LULC types using Gerlach troughs at hillslope scale, was conducted to validate the results of the SWAT model. Results indicated that the 1990 and 2022 LULC maps had an overall accuracy of 87.11% and 94.89%, respectively which was highly satisfactory. The Kappa statistics reflected similar results where the 1990 map had a value of 0.84 while the 2022 map had a value of 0.94, indicating high statistical agreement between the classified maps and the reference data. The study also found that bare areas exuberated the greatest area change with a decline of 9.49%, while built-up areas manifested the highest increase of 5.97% from 1990 to 2022. Agricultural land increased by 4.79% in conjunction with a slight increase of 0.44% by green vegetation while water declined by 1.71%. To determine the ideal DEM to analyse hydrological response, the LULC maps in conjunction with other input data were inserted into the SWAT model to assess model performance. It was found that the 30m produced satisfactory model performance (NSE = 0.49 at calibration and 0.67 at validation) and was eligible to assess runoff conditions as a function of LULC change. Other statistics indicated satisfactory model performance at calibration (PBIAS = 48.80, R2 = 0.51, RSR = 1.02) and validation stage (PBIAS = -38.1, R2 = 0.47, RSR = 1.08). The 90m DEM possessed the poorest model performance (NSE = 0.18 at calibration and 0.35 at validation) followed by the 20m DEM (NSE = 0.41 at calibration and 0.32 at validation). Runoff simulations using the 30m SWAT model showed that surface runoff was highest in areas where there were built-up areas. Built-up areas and bare areas yielded 36% of the total surface runoff individually, while vegetation produced only 28% in 1990. Similar readings were obtained for 2022, which included agricultural land that produced 29% of the surface runoff. Runoff volume measured at hillslope scale was highest in bare areas (6.6 L) and built-up areas (9.3 L). Therefore, this study shows that the resolution of DEMs must concur with the relevant scale of the study to produce optimal results. Additionally, this study showed that a change in LULC heavily affects the amount of surface runoff generated, which has several implications in terms of flooding. Therefore, this study is useful as it will inform sustainable catchment management decisions, and water resource management, and enhance our understanding of the relationships between DEM spatial resolution, LULC change, SWAT modelling, and water quantity calculations. , Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2025
- Full Text:
- Date Issued: 2025-04
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