Modelling the relationship between flow and water quality in South African rivers
- Authors: Slaughter, Andrew Robert
- Date: 2011
- Subjects: Water quality -- Measurement -- South Africa Water quality -- Mathematical models -- South Africa Streamflow -- South Africa Stream measurements -- Mathematical models -- South Africa
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:6039 , http://hdl.handle.net/10962/d1006196
- Description: The National Water Act (Act 36 of 1998) provides for an ecological Reserve as the quantity (flow) and quality of water needed to protect aquatic ecosystems. While there are methods available to quantify the ecological Reserve in terms of flow, methods of linking flow to water quality are lacking. Therefore, the research presented in this thesis investigated various modelling techniques to estimate the effect of flow on water quality. The aims of the research presented in this thesis were: Aim 1: Can the relationship between flow and water quality be accurately represented by simple statistical models? Aim 2: Can relatively simple models accurately represent the relationship between flow and water quality? Aim 3: Can the effect of diffuse sources be omitted from a water quality model and still obtain realistic simulations, and if so under what conditions? Aim 4: Can models that solely use historical monitoring data, accurately represent the relationships between flow and water quality? In Chapter 3, simple Q-C regressions of flow and water quality were investigated using Department of Water Affairs (DWA) historical monitoring data. It was found that while flow versus salinity regressions gave good regression fits in many cases, the Q-C regression approach is limited. A mechanistic/statistical model that attempted to estimate the point and diffuse signatures of nutrients in response to flow was developed in Chapter 4 using DWA historical monitoring data. The model was verified as accurate in certain case studies using observed point loading information. In Chapter 5, statistical models that link land cover information to diffuse nutrient signatures in response to flow using DWA historical data were developed. While the model estimations are uncertain due to a lack of data, they do provide an estimation of the diffuse signature within catchments where there is flow and land cover information available. Chapter 6 investigates the extension of an existing mass-balance salinity model to estimate the effect of saline irrigation return flow on in-stream salinity. The model gave accurate salinity estimates for a low order stream with little or no irrigation within its catchment, and for a permanently flowing river within a catchment used extensively for irrigation. Chapter 7 investigated a modelling method to estimate the reaction coefficients involved in nitrification using only DWA historical monitoring data. Here, the model used flow information to estimate the residence time of nutrients within the studied river reaches. While the model obtained good estimations of nitrification for the data it was applied to, very few DWA data sets were suitable for the model. Chapter 8 investigated the ability of the in-stream model QUAL2K to estimate nutrient concentrations downstream of point and diffuse inputs of nutrients. It was found that the QUAL2K model can give accurate results in cases where point sources dominate the total nutrient inputs into a river. However, the QUAL2K simulations are too uncertain in cases where there are large diffuse source inputs of nutrients as the load of the diffuse inputs is difficult to measure in the field. This research highlights the problem of data scarcity in terms of temporal resolution as well as the range of constituents measured within DWA historical monitoring data for water quality. This thesis in addition argues that the approach of applying a number of models is preferable to applying one model to investigate the research aims, as particular models would be suited to particular circumstances, and the development of new models allowed the research aims of this thesis to be explored more thoroughly. It is also argued that simpler models that simulate a few key processes that explain the variation in observed data, are more suitable for implementing Integrated Water Resource Management (IWRM) than large comprehensive water quality models. From this research, it is clear that simple statistical models are not adequate for modelling the relationship between flow and water quality, however, relatively simple mechanistic models that simulate a limited number of processes and water quality variables, can provide accurate representations of this relationship. Under conditions where diffuse sources are not a major factor within a catchment, models that omit diffuse sources can obtain realistic simulations of the relationship between flow and water quality. Most of the models investigated in this thesis demonstrate that accurate simulations of the relationships between flow and water quality can be obtained using solely historical monitoring data.
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- Date Issued: 2011
The refinement of protective salinity guidelines for South African freshwater resources
- Authors: Slaughter, Andrew Robert
- Date: 2005
- Subjects: Water salinization -- South Africa Salinization -- Control -- South Africa Salinity -- South Africa Freshwater ecology -- South Africa Water resources development -- South Africa Caridina Caridina -- Effect of pollution
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:6031 , http://hdl.handle.net/10962/d1006170
- Description: South Africa is an arid country and its growing population is putting freshwater resources under increasing pressure. Natural salinization of freshwater systems is being exacerbated by anthropogenic influences. The National Water Act (No. 36 of 1998) stipulates the need for an ecological Reserve, that quantity and quality of freshwater needed to protect freshwater ecosystems while allowing sustainable use of freshwater resources. Water guidelines do exist in the form of the South African Water Quality Guidelines (DWAF, 1996) and more recently, Jooste and Rossouw (2002) compiled benchmark values for water quality variables marking the boundaries between ecological health classes in the 4-category classification system. Predominantly international toxicity data were used to compile the guidelines and the benchmark values. In addition, there is a paucity of chronic toxicity data nationally and internationally. This thesis showed that it is statistically possible to derive protective chronic endpoints for salinity from acute toxicity data through extrapolation. The Acute to Chronic Ratio (ACR), Two-Step Linear Regression (LRA) and Multi-Factor Probit Analysis (MPA) extrapolation methods were investigated to derive chronic toxicity data from acute toxicity data. The authors of LRA and MPA recommend associating a time independent LCx value in the range of LC₀¸₀₁ to LC₁₀ with a Predicted No Effect Concentration (PNOEC). In addition to published methods, this thesis studied the possibility of equating a time independent LC₅₀ value and subjected to a safety factor of 5 (LRA LC₅₀/5), to the PNOEC. Extrapolated chronic toxicity data where the toxicants are NaCl and Na₂SO₄ were derived for indigenous South African macroinvertebrates. NaCl and Na₂SO₄ are salts associated with salinisation in South Africa. In addition, a chronic salinity toxicity test protocol for an indigenous South African aquatic macroinvertebrate was designed and chronic toxicity test were performed using NaCl and Na₂SO₄ as toxicants. The experimental chronic toxicity data produced were used to validate results from the acute to chronic extrapolation methods. Extrapolated chronic toxicity data were inputted into Species Sensitivity Distribution curves, and concentrations that were predicted to protect 95 % of species (PC95) were compared to the sub-lethality benchmarks proposed by Jooste and Rossouw (2002) for NaCl and Na₂SO₄. This study concluded that the LRA LC₅₀/5 extrapolation method is the most protective and accurate and proposed that LRA replace the ACR method in future guideline development for inorganic salts.
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- Date Issued: 2005