The further development, application and evaluation of a sediment yield model (WQSED) for catchment management in African catchments
- Authors: Gwapedza, David
- Date: 2021-04
- Subjects: Sedimentation and deposition -- South Africa , Sedimentation and deposition -- Zimbabwe , Watersheds -- South Africa , Watersheds -- Zimbabwe , Watershed management -- Africa , Water quality -- South Africa , Water quality -- Zimbabwe , Modified Universal Soil Loss Equation (MUSLE) , Water Quality and Sediment Model (WQSED) , Soil and Water Assessment Tool (SWAT)
- Language: English
- Type: thesis , text , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/178376 , vital:42934 , 10.21504/10962/178376
- Description: Erosion and sediment transport are natural catchment processes that play an essential role in ecosystem functioning by providing habitat for aquatic organisms and contributing to the health of wetlands. However, excessive erosion and sedimentation, mostly driven by anthropogenic activity, lead to ecosystem degradation, loss of agricultural land, water quality problems, reduced reservoir storage capacity and damage to physical infrastructure. It is reported that up to 25% of dams in South Africa have lost approximately 30% of their initial storage capacity to sedimentation. Therefore, excessive sedimentation transcends from an ecological problem to a health, livelihood and water security issue. Erosion and sedimentation occur at variable temporal and spatial scales; therefore, monitoring of these processes can be difficult and expensive. Regardless of all these prohibiting factors, information on erosion and sediment remains an urgent requirement for the sustainable management of catchments. Models have evolved as tools to replicate and simulate complex natural processes to understand and manage these systems. Several models have been developed globally to simulate erosion and sediment transport. However, these models are not always applicable in Africa because 1) the conditions under which they were developed are not as relevant for African catchments 2) they have high data requirements and cannot be applied with ease in our data-scarce African catchments 3) they are sometimes complicated, and there are little training available or potential users simply have no time to dedicate towards learning these models. To respond to the problems of erosion, sedimentation, water quality and unavailability of applicable models, the current research further develops, applies and evaluates an erosion and sediment transport model, the Water Quality and Sediment Model (WQSED), for integration within the existing water resources framework in South Africa and application for practical catchment management. The WQSED was developed to simulate daily suspended sediment loads that are vital for water quality and quantity assessments. The WQSED was developed based on the Modified Universal Soil Loss Equation (MUSLE), and the Pitman model is a primary hydrological model providing forcing data, although flow data from independent sources may be used to drive the WQSED model. The MUSLE was developed in the United States of America, and this research attempts to improve the applicability of the MUSLE by identifying key issues that may impede its performance. Assessments conducted within the current research can be divided into scale assessment and application and evaluation assessment. The scale assessment involved evaluating spatial and temporal scale issues associated with the MUSLE. Spatial scale assessments were conducted using analytical and mathematical assessments on a hypothetical catchment. Temporal scale issues were assessed in terms of the vegetation cover (C) factor within the Tsitsa River catchment in South Africa. Model application and evaluation involved applying and calibrating the model to simulate daily time-series sediment yield. The model was applied to calibrated and validated (split-sample validation) in two catchments in South Africa, two catchments in Zimbabwe and three catchments were selected from the USA and associated territories for further testing as continuous daily time-series observed sediment data could not be readily accessed for catchments in the Southern African region. The catchments where the model was calibrated and validated range in size from 50 km2 to 20 000 km2. Additionally, the model was applied to thirteen ‘ungauged’ catchments selected from across South Africa, where only long-term reservoir sedimentation rates were available to compare with long term model simulations converted to sediment yield rates. The additional thirteen catchments were selected from areas of different climatic, vegetation and soils conditions characterising South Africa and range in size from 30 km2 to 2 500 km2. The current research results are split into a) MUSLE scale dependency and b) WQSED testing and evaluation. Scale dependency testing showed that the MUSLE could be spatially scale-dependent, particularly when a lumped approach is used, resulting in simulations of up to 30% more sediment. Spatial scale dependence in the MUSLE was found to be related to the runoff and topographic factors used and how they are calculated. The current study resorted to adopting a reference grid in applying the MUSLE, followed by scaling up the outputs to the total catchment area. Using a reference grid resulted in a general avoidance of the problem of spatial scale. The adoption of a seasonal vegetation cover factor was shown to significantly account for temporal changes of vegetation cover within a year and reduce over-estimations in sediment output. The temporal scale evaluation demonstrated the uncertainties associated with using a fixed vegetation cover factor in a catchment with variable rainfall and runoff pattern. The WQSED model evaluation showed that the model could be calibrated and validated to provide consistent results. Satisfactory model evaluation statistics were obtained for most catchments to which the model was applied, based on general model evaluation guidelines (Nash Sutcliffe Efficiency and R2 > 0.5). The model also performed generally well compared to established models that had been previously applied in some of the study catchments. The highest sediment yields recorded per country were 153 t km-2 year-1 (Tsitsa River; South Africa), 90 t km-2 year-1 (Odzi River; Zimbabwe) and 340 t km-2 year-1 (Rio Tanama; Puerto Rico). The results also displayed consistent underestimations of peak sediment yield events, partly attributed to sediment emanating from gullies that are not explicitly accounted for in the WQSED model structure. Furthermore, the calibration process revealed that the WQSED storage model is generally challenging to calibrate. An alternative simpler version of the storage model was easier to calibrate, but the model may still be challenging to apply to catchments where calibration data are not available. The additional evaluation of the WQSED simulated sediment yield rates against observed reservoir sediment rates showed a broad range of differences between the simulated and observed sediment yield rates. Differences between WQSED simulated sediment and observed reservoir sediment ranges from a low of 30% to a high of > 40 times. The large differences were partly attributed to WQSED being limited to simulating suspended sediment from sheet and rill processes, whereas reservoir sediment is generated from more sources that include bedload, channel and gully processes. Nevertheless, the model simulations replicated some of the regional sediment yield patterns and are assumed to represent sheet and rill contributions to reservoir sediment in selected catchments. The outcome of this study is an improved WQSED model that has successfully undergone preliminary testing and evaluation. Therefore, the model is sufficiently complete to be used by independent researchers and water resources managers to simulate erosion and sediment transport. However, the model is best applicable to areas where some observed data or regional information are available to calibrate the storage components and constrain model outputs. The report on potential MUSLE scale dependencies is relevant globally to all studies applying the MUSLE model and, therefore, can improve MUSLE application in future studies. The WQSED model offers a relatively simple, effective and applicable tool that is set to provide information to enhance catchment, land and water resources management in catchments of Africa. , Thesis (PhD) -- Faculty of Science, Institute for Water Research, 2021
- Full Text:
- Authors: Gwapedza, David
- Date: 2021-04
- Subjects: Sedimentation and deposition -- South Africa , Sedimentation and deposition -- Zimbabwe , Watersheds -- South Africa , Watersheds -- Zimbabwe , Watershed management -- Africa , Water quality -- South Africa , Water quality -- Zimbabwe , Modified Universal Soil Loss Equation (MUSLE) , Water Quality and Sediment Model (WQSED) , Soil and Water Assessment Tool (SWAT)
- Language: English
- Type: thesis , text , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/178376 , vital:42934 , 10.21504/10962/178376
- Description: Erosion and sediment transport are natural catchment processes that play an essential role in ecosystem functioning by providing habitat for aquatic organisms and contributing to the health of wetlands. However, excessive erosion and sedimentation, mostly driven by anthropogenic activity, lead to ecosystem degradation, loss of agricultural land, water quality problems, reduced reservoir storage capacity and damage to physical infrastructure. It is reported that up to 25% of dams in South Africa have lost approximately 30% of their initial storage capacity to sedimentation. Therefore, excessive sedimentation transcends from an ecological problem to a health, livelihood and water security issue. Erosion and sedimentation occur at variable temporal and spatial scales; therefore, monitoring of these processes can be difficult and expensive. Regardless of all these prohibiting factors, information on erosion and sediment remains an urgent requirement for the sustainable management of catchments. Models have evolved as tools to replicate and simulate complex natural processes to understand and manage these systems. Several models have been developed globally to simulate erosion and sediment transport. However, these models are not always applicable in Africa because 1) the conditions under which they were developed are not as relevant for African catchments 2) they have high data requirements and cannot be applied with ease in our data-scarce African catchments 3) they are sometimes complicated, and there are little training available or potential users simply have no time to dedicate towards learning these models. To respond to the problems of erosion, sedimentation, water quality and unavailability of applicable models, the current research further develops, applies and evaluates an erosion and sediment transport model, the Water Quality and Sediment Model (WQSED), for integration within the existing water resources framework in South Africa and application for practical catchment management. The WQSED was developed to simulate daily suspended sediment loads that are vital for water quality and quantity assessments. The WQSED was developed based on the Modified Universal Soil Loss Equation (MUSLE), and the Pitman model is a primary hydrological model providing forcing data, although flow data from independent sources may be used to drive the WQSED model. The MUSLE was developed in the United States of America, and this research attempts to improve the applicability of the MUSLE by identifying key issues that may impede its performance. Assessments conducted within the current research can be divided into scale assessment and application and evaluation assessment. The scale assessment involved evaluating spatial and temporal scale issues associated with the MUSLE. Spatial scale assessments were conducted using analytical and mathematical assessments on a hypothetical catchment. Temporal scale issues were assessed in terms of the vegetation cover (C) factor within the Tsitsa River catchment in South Africa. Model application and evaluation involved applying and calibrating the model to simulate daily time-series sediment yield. The model was applied to calibrated and validated (split-sample validation) in two catchments in South Africa, two catchments in Zimbabwe and three catchments were selected from the USA and associated territories for further testing as continuous daily time-series observed sediment data could not be readily accessed for catchments in the Southern African region. The catchments where the model was calibrated and validated range in size from 50 km2 to 20 000 km2. Additionally, the model was applied to thirteen ‘ungauged’ catchments selected from across South Africa, where only long-term reservoir sedimentation rates were available to compare with long term model simulations converted to sediment yield rates. The additional thirteen catchments were selected from areas of different climatic, vegetation and soils conditions characterising South Africa and range in size from 30 km2 to 2 500 km2. The current research results are split into a) MUSLE scale dependency and b) WQSED testing and evaluation. Scale dependency testing showed that the MUSLE could be spatially scale-dependent, particularly when a lumped approach is used, resulting in simulations of up to 30% more sediment. Spatial scale dependence in the MUSLE was found to be related to the runoff and topographic factors used and how they are calculated. The current study resorted to adopting a reference grid in applying the MUSLE, followed by scaling up the outputs to the total catchment area. Using a reference grid resulted in a general avoidance of the problem of spatial scale. The adoption of a seasonal vegetation cover factor was shown to significantly account for temporal changes of vegetation cover within a year and reduce over-estimations in sediment output. The temporal scale evaluation demonstrated the uncertainties associated with using a fixed vegetation cover factor in a catchment with variable rainfall and runoff pattern. The WQSED model evaluation showed that the model could be calibrated and validated to provide consistent results. Satisfactory model evaluation statistics were obtained for most catchments to which the model was applied, based on general model evaluation guidelines (Nash Sutcliffe Efficiency and R2 > 0.5). The model also performed generally well compared to established models that had been previously applied in some of the study catchments. The highest sediment yields recorded per country were 153 t km-2 year-1 (Tsitsa River; South Africa), 90 t km-2 year-1 (Odzi River; Zimbabwe) and 340 t km-2 year-1 (Rio Tanama; Puerto Rico). The results also displayed consistent underestimations of peak sediment yield events, partly attributed to sediment emanating from gullies that are not explicitly accounted for in the WQSED model structure. Furthermore, the calibration process revealed that the WQSED storage model is generally challenging to calibrate. An alternative simpler version of the storage model was easier to calibrate, but the model may still be challenging to apply to catchments where calibration data are not available. The additional evaluation of the WQSED simulated sediment yield rates against observed reservoir sediment rates showed a broad range of differences between the simulated and observed sediment yield rates. Differences between WQSED simulated sediment and observed reservoir sediment ranges from a low of 30% to a high of > 40 times. The large differences were partly attributed to WQSED being limited to simulating suspended sediment from sheet and rill processes, whereas reservoir sediment is generated from more sources that include bedload, channel and gully processes. Nevertheless, the model simulations replicated some of the regional sediment yield patterns and are assumed to represent sheet and rill contributions to reservoir sediment in selected catchments. The outcome of this study is an improved WQSED model that has successfully undergone preliminary testing and evaluation. Therefore, the model is sufficiently complete to be used by independent researchers and water resources managers to simulate erosion and sediment transport. However, the model is best applicable to areas where some observed data or regional information are available to calibrate the storage components and constrain model outputs. The report on potential MUSLE scale dependencies is relevant globally to all studies applying the MUSLE model and, therefore, can improve MUSLE application in future studies. The WQSED model offers a relatively simple, effective and applicable tool that is set to provide information to enhance catchment, land and water resources management in catchments of Africa. , Thesis (PhD) -- Faculty of Science, Institute for Water Research, 2021
- Full Text:
Modelling water quality : complexity versus simplicity
- Authors: Jacobs, Haden
- Date: 2017
- Subjects: Water quality management -- Mathematical models , Water quality -- Measurement , Water quality biological assessment
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/4754 , vital:20721
- Description: Water quality management makes use of water quality models as decision making tools. Water quality management decisions need to be informed by information that is as reliable as possible. There are many situations where observational data are limited and therefore models or simulation methods have a significant role to play in providing some information that can be used to guide management decisions. Water quality modelling is the use of mathematical equations and statistics to represent the processes affecting water quality in the natural environment. Water quality data are expensive and difficult to obtain. Nutrient sampling requires a technician to obtain ‘grab samples’ which need to be kept at low temperatures and analysed in a laboratory. The laboratory analyses of nutrients is expensive and time consuming. The data required by water quality models are seldom available as complete datasets of sufficient length. This is especially true for ungauged regions, either in small rural catchments or even major rivers in developing countries. Water quality modelling requires simulated or observed water quantity data as water quality is affected by water quantity. Both the water quality modelling and water quantity modelling require data to simulate the required processes. Data are necessary for both model structure as well as model set up for calibration and validation. This study aimed to investigate the simulation of water quality in a low order stream with limited observed data using a relatively complex as well as a much simpler water quality model, represented by QUAL2K and an in-house developed Mass Balance Nutrient (MBN) model, respectively. The two models differ greatly in the approach adopted for water quality modelling, with QUAL2K being an instream water quality fate model and the MBN model being a catchment scale model that links water quantity and quality. The MBN model uses hydrological routines to simulate those components of the hydrological cycle that are expected to differ with respect to their water quality signatures (low flows, high flows, etc.). Incremental flows are broken down into flow fractions, and nutrient signatures are assigned to fractions to represent catchment nutrient load input. A linear regression linked to an urban runoff model was used to simulate water quality entering the river system from failing municipal infrastructure, which was found to be a highly variable source of nutrients within the system. A simple algal model was adapted from CE-QUAL-W2 to simulate nutrient assimilation by benthic algae. QUAL2K, an instream water quality fate model, proved unsuitable for modelling diffuse sources for a wide range of conditions and was data intensive when compared to the data requirements of the MBN model. QUAL2K did not simulate water quality accurately over a wide range of flow conditions and was found to be more suitable to simulating point sources. The MBN model did not provide accurate results in terms of the simulation of individual daily water quality values; however, the general trends and frequency characteristics of the simulations were satisfactory. Despite some uncertainties, the MBN model remains useful for extending data for catchments with limited observed water quality data. The MBN model was found to be more suitable for South African conditions than QUAL2K, given the data requirements of each model and water quality and flow data available from the Department of Water and Sanitation. The MBN model was found to be particularly useful by providing frequency distributions of water quality loads or concentrations using minimal data that can be related to the risks of exceeding management thresholds.
- Full Text:
- Authors: Jacobs, Haden
- Date: 2017
- Subjects: Water quality management -- Mathematical models , Water quality -- Measurement , Water quality biological assessment
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/4754 , vital:20721
- Description: Water quality management makes use of water quality models as decision making tools. Water quality management decisions need to be informed by information that is as reliable as possible. There are many situations where observational data are limited and therefore models or simulation methods have a significant role to play in providing some information that can be used to guide management decisions. Water quality modelling is the use of mathematical equations and statistics to represent the processes affecting water quality in the natural environment. Water quality data are expensive and difficult to obtain. Nutrient sampling requires a technician to obtain ‘grab samples’ which need to be kept at low temperatures and analysed in a laboratory. The laboratory analyses of nutrients is expensive and time consuming. The data required by water quality models are seldom available as complete datasets of sufficient length. This is especially true for ungauged regions, either in small rural catchments or even major rivers in developing countries. Water quality modelling requires simulated or observed water quantity data as water quality is affected by water quantity. Both the water quality modelling and water quantity modelling require data to simulate the required processes. Data are necessary for both model structure as well as model set up for calibration and validation. This study aimed to investigate the simulation of water quality in a low order stream with limited observed data using a relatively complex as well as a much simpler water quality model, represented by QUAL2K and an in-house developed Mass Balance Nutrient (MBN) model, respectively. The two models differ greatly in the approach adopted for water quality modelling, with QUAL2K being an instream water quality fate model and the MBN model being a catchment scale model that links water quantity and quality. The MBN model uses hydrological routines to simulate those components of the hydrological cycle that are expected to differ with respect to their water quality signatures (low flows, high flows, etc.). Incremental flows are broken down into flow fractions, and nutrient signatures are assigned to fractions to represent catchment nutrient load input. A linear regression linked to an urban runoff model was used to simulate water quality entering the river system from failing municipal infrastructure, which was found to be a highly variable source of nutrients within the system. A simple algal model was adapted from CE-QUAL-W2 to simulate nutrient assimilation by benthic algae. QUAL2K, an instream water quality fate model, proved unsuitable for modelling diffuse sources for a wide range of conditions and was data intensive when compared to the data requirements of the MBN model. QUAL2K did not simulate water quality accurately over a wide range of flow conditions and was found to be more suitable to simulating point sources. The MBN model did not provide accurate results in terms of the simulation of individual daily water quality values; however, the general trends and frequency characteristics of the simulations were satisfactory. Despite some uncertainties, the MBN model remains useful for extending data for catchments with limited observed water quality data. The MBN model was found to be more suitable for South African conditions than QUAL2K, given the data requirements of each model and water quality and flow data available from the Department of Water and Sanitation. The MBN model was found to be particularly useful by providing frequency distributions of water quality loads or concentrations using minimal data that can be related to the risks of exceeding management thresholds.
- Full Text:
Investigating integrated catchment management using a simple water quantity and quality model : a case study of the Crocodile River Catchment, South Africa
- Retief, Daniel Christoffel Hugo
- Authors: Retief, Daniel Christoffel Hugo
- Date: 2015
- Subjects: Watersheds -- South Africa -- Krokodilrivier (Mpumalanga) , Integrated water development -- South Africa -- Krokodilrivier (Mpumalanga) , Water quality management -- South Africa -- Krokodilrivier (Mpumalanga) , Water-supply -- South Africa -- Krokodilrivier (Mpumalanga) , Water quality -- Measurement
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6050 , http://hdl.handle.net/10962/d1017875
- Description: Internationally, water resources are facing increasing pressure due to over-exploitation and pollution. Integrated Water Resource Management (IWRM) has been accepted internationally as a paradigm for integrative and sustainable management of water resources. However, in practice, the implementation and success of IWRM policies has been hampered by the lack of availability of integrative decision support tools, especially within the context of limited resources and observed data. This is true for the Crocodile River Catchment (CRC), located within the Mpumalanga Province of South Africa. The catchment has been experiencing a decline in water quality as a result of the point source input of a cocktail of pollutants, which are discharged from industrial and municipal wastewater treatment plants, as well as diffuse source runoff and return flows from the extensive areas of irrigated agriculture and mining sites. The decline in water quality has profound implications for a range of stakeholders across the catchment including increased treatment costs and reduced crop yields. The combination of deteriorating water quality and the lack of understanding of the relationships between water quantity and quality for determining compliance/non-compliance in the CRC have resulted in collaboration between stakeholders, willing to work in a participatory and transparent manner to create an Integrated Water Quality Management Plan (IWQMP). This project aimed to model water quality, (combined water quality and quantity), to facilitate the IWQMP aiding in the understanding of the relationship between water quantity and quality in the CRC. A relatively simple water quality model (WQSAM) was used that receives inputs from established water quantity systems models, and was designed to be a water quality decision support tool for South African catchments. The model was applied to the CRC, achieving acceptable simulations of total dissolved solids (used as a surrogate for salinity) and nutrients (including orthophosphates, nitrates +nitrites and ammonium) for historical conditions. Validation results revealed that there is little consistency within the catchment, attributed to the non-stationary nature of water quality at many of the sites in the CRC. The analyses of the results using a number of representations including, seasonal load distributions, load duration curves and load flow plots, confirmed that the WQSAM model was able to capture the variability of relationships between water quantity and quality, provided that simulated hydrology was sufficiently accurate. The outputs produced by WQSAM was seen as useful for the CRC, with the Inkomati-Usuthu Catchment Management Agency (IUCMA) planning to operationalise the model in 2015. The ability of WQSAM to simulate water quality in data scarce catchments, with constituents that are appropriate for the needs of water resource management within South Africa, is highly beneficial.
- Full Text:
- Authors: Retief, Daniel Christoffel Hugo
- Date: 2015
- Subjects: Watersheds -- South Africa -- Krokodilrivier (Mpumalanga) , Integrated water development -- South Africa -- Krokodilrivier (Mpumalanga) , Water quality management -- South Africa -- Krokodilrivier (Mpumalanga) , Water-supply -- South Africa -- Krokodilrivier (Mpumalanga) , Water quality -- Measurement
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6050 , http://hdl.handle.net/10962/d1017875
- Description: Internationally, water resources are facing increasing pressure due to over-exploitation and pollution. Integrated Water Resource Management (IWRM) has been accepted internationally as a paradigm for integrative and sustainable management of water resources. However, in practice, the implementation and success of IWRM policies has been hampered by the lack of availability of integrative decision support tools, especially within the context of limited resources and observed data. This is true for the Crocodile River Catchment (CRC), located within the Mpumalanga Province of South Africa. The catchment has been experiencing a decline in water quality as a result of the point source input of a cocktail of pollutants, which are discharged from industrial and municipal wastewater treatment plants, as well as diffuse source runoff and return flows from the extensive areas of irrigated agriculture and mining sites. The decline in water quality has profound implications for a range of stakeholders across the catchment including increased treatment costs and reduced crop yields. The combination of deteriorating water quality and the lack of understanding of the relationships between water quantity and quality for determining compliance/non-compliance in the CRC have resulted in collaboration between stakeholders, willing to work in a participatory and transparent manner to create an Integrated Water Quality Management Plan (IWQMP). This project aimed to model water quality, (combined water quality and quantity), to facilitate the IWQMP aiding in the understanding of the relationship between water quantity and quality in the CRC. A relatively simple water quality model (WQSAM) was used that receives inputs from established water quantity systems models, and was designed to be a water quality decision support tool for South African catchments. The model was applied to the CRC, achieving acceptable simulations of total dissolved solids (used as a surrogate for salinity) and nutrients (including orthophosphates, nitrates +nitrites and ammonium) for historical conditions. Validation results revealed that there is little consistency within the catchment, attributed to the non-stationary nature of water quality at many of the sites in the CRC. The analyses of the results using a number of representations including, seasonal load distributions, load duration curves and load flow plots, confirmed that the WQSAM model was able to capture the variability of relationships between water quantity and quality, provided that simulated hydrology was sufficiently accurate. The outputs produced by WQSAM was seen as useful for the CRC, with the Inkomati-Usuthu Catchment Management Agency (IUCMA) planning to operationalise the model in 2015. The ability of WQSAM to simulate water quality in data scarce catchments, with constituents that are appropriate for the needs of water resource management within South Africa, is highly beneficial.
- Full Text:
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