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:
Phenolic compounds in water and the implications for rapid detection of indicator micro-organisms using ß-D-Galactosidase and ß-D-Glucuronidase
- Authors: Abboo, Sagaran
- Date: 2009
- Subjects: Water -- Purification -- Biological treatment , Pollutants -- Biodegradation , Phenol , Organic water pollutants , Water quality biological assessment , Water -- Pollution
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:3978 , http://hdl.handle.net/10962/d1004037 , Water -- Purification -- Biological treatment , Pollutants -- Biodegradation , Phenol , Organic water pollutants , Water quality biological assessment , Water -- Pollution
- Description: Faecal contamination in water is detected using appropriate microbial models such as total coliforms, faecal coliforms and E. coli. Βeta-D-Galactosidase (β-GAL) and Beta-D-glucuronidase (β-GUD) are two marker enzymes that are used to test for the presence of total coliforms and E. coli in water samples, respectively. Various assay methods have been developed using chromogenic and fluorogenic substrates. In this study, the chromogenic substrates chlorophenol red β-D-galactopyranoside (CPRG) for β-GAL and p-nitrophenyl-β-D-galactopyranoside (PNPG) for β-GUD were used. Potential problems associated with this approach include interference from other organisms present in the environment (e.g. plants, algae and other bacteria), as well as the presence of certain chemicals, such as phenolic compounds in water. Phenolic compounds are present in the aquatic environment due to their extensive industrial applications. The USA Enviromental Protection Agency (EPA) lists 11 Priority Pollutant Phenols (PPP) due to their high level of toxicity. This study investigated the interfering effects of the eleven PPP found in water on the enzyme activities of both the β-GAL and β-GUD enzyme assays. The presence of these PPP in the β-GAL and β-GUD enzyme assays showed that over and underestimation of activity may occur due to inhibition or activation of these enzymes. Three types of inhibition to enzyme activities were identified from double reciprocal Lineweaver-Burk plots. The inhibition constants (Ki) were determined for all inhibitory phenolic compounds from appropriate secondary plots. Furthermore, this study presented a validated reverse phase high performance liquid chromatography (RP-HPLC) method, developed for the simultaneous detection, separation and determination of all eleven phenolic compounds found in the environment. This method demonstrated good linearity, reproducibility, accuracy and sensitivity. Environmental water samples were collected from rivers, streams, industrial sites and wastewater treatment plant effluent. These samples were extracted and concentrated using a solid phase extraction (SPE) procedure prior to analysis employing the newly developed HPLC method in this study. Seasonal variations on the presence of the PPP in the environment were observed at certain collection sites. The concentrations found were between 0.033 μg/ml for 2,4-dinitrophenol in a running stream to 0.890 mg/ml for pentachlorophenol from an tannery industrial site. These concentrations of phenolic compounds found in these environments were able to interfere with the β-GAL and β-GUD enzyme assays.
- Full Text:
- Authors: Abboo, Sagaran
- Date: 2009
- Subjects: Water -- Purification -- Biological treatment , Pollutants -- Biodegradation , Phenol , Organic water pollutants , Water quality biological assessment , Water -- Pollution
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:3978 , http://hdl.handle.net/10962/d1004037 , Water -- Purification -- Biological treatment , Pollutants -- Biodegradation , Phenol , Organic water pollutants , Water quality biological assessment , Water -- Pollution
- Description: Faecal contamination in water is detected using appropriate microbial models such as total coliforms, faecal coliforms and E. coli. Βeta-D-Galactosidase (β-GAL) and Beta-D-glucuronidase (β-GUD) are two marker enzymes that are used to test for the presence of total coliforms and E. coli in water samples, respectively. Various assay methods have been developed using chromogenic and fluorogenic substrates. In this study, the chromogenic substrates chlorophenol red β-D-galactopyranoside (CPRG) for β-GAL and p-nitrophenyl-β-D-galactopyranoside (PNPG) for β-GUD were used. Potential problems associated with this approach include interference from other organisms present in the environment (e.g. plants, algae and other bacteria), as well as the presence of certain chemicals, such as phenolic compounds in water. Phenolic compounds are present in the aquatic environment due to their extensive industrial applications. The USA Enviromental Protection Agency (EPA) lists 11 Priority Pollutant Phenols (PPP) due to their high level of toxicity. This study investigated the interfering effects of the eleven PPP found in water on the enzyme activities of both the β-GAL and β-GUD enzyme assays. The presence of these PPP in the β-GAL and β-GUD enzyme assays showed that over and underestimation of activity may occur due to inhibition or activation of these enzymes. Three types of inhibition to enzyme activities were identified from double reciprocal Lineweaver-Burk plots. The inhibition constants (Ki) were determined for all inhibitory phenolic compounds from appropriate secondary plots. Furthermore, this study presented a validated reverse phase high performance liquid chromatography (RP-HPLC) method, developed for the simultaneous detection, separation and determination of all eleven phenolic compounds found in the environment. This method demonstrated good linearity, reproducibility, accuracy and sensitivity. Environmental water samples were collected from rivers, streams, industrial sites and wastewater treatment plant effluent. These samples were extracted and concentrated using a solid phase extraction (SPE) procedure prior to analysis employing the newly developed HPLC method in this study. Seasonal variations on the presence of the PPP in the environment were observed at certain collection sites. The concentrations found were between 0.033 μg/ml for 2,4-dinitrophenol in a running stream to 0.890 mg/ml for pentachlorophenol from an tannery industrial site. These concentrations of phenolic compounds found in these environments were able to interfere with the β-GAL and β-GUD enzyme assays.
- Full Text:
The role of acute toxicity data for South African freshwater macroinvertebrates in the derivation of water quality guidelines for salinity
- Authors: Browne, Samantha
- Date: 2005
- Subjects: Water-supply -- South Africa , Water quality management -- South Africa , Aquatic ecology -- South Africa , Ecosystem management -- South Africa , Freshwater invertebrates -- South Africa -- Ecology , Water -- Toxicology -- South Africa , Water quality biological assessment
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4742 , http://hdl.handle.net/10962/d1006173 , Water-supply -- South Africa , Water quality management -- South Africa , Aquatic ecology -- South Africa , Ecosystem management -- South Africa , Freshwater invertebrates -- South Africa -- Ecology , Water -- Toxicology -- South Africa , Water quality biological assessment
- Description: Water resources are under ever-increasing pressure to meet the demands of various water users both nationally and internationally. The process of anthropogenically-induced salinisation serves to exacerbate this pressure by limiting the quantity and quality of water available for future use. Water quality guidelines provide the numerical goals which water resource managers can use to adequately manage and protect aquatic ecosystems. Various methods which have been developed and used internationally to derive such guidelines are discussed. Acute toxicity tests were conducted using two inorganic salts, NaCl and Na₂SO₄. Field collected, indigenous, freshwater macroinvertebrates were used as tests organisms. Data generated from these tests contributed to the expansion of the currently limited toxicological database of response data for indigenous organisms and the suitability of using such organisms for future testing was discussed. Salt sensitivities of indigenous freshwater invertebrates were compared those of species sourced from an international toxicological database and were found to have similar ranges of tolerances to NaCl and Na₂SO₄. Species sensitivity distributions (SSDs), a method of data extrapolation, were derived using different types of toxicological data, and hence different guideline values or protective concentrations were derived. These concentrations were equated to boundary values for South Africa’s ecological Reserve categories, which are used to describe degrees of health for aquatic ecosystems. Provisional results suggest that using only acute toxicity data in guideline derivation provides ecosystem protection that is under-protective. Chronic toxicity data, which include endpoints other than mortality, provide the most realistic environmental protection but lack data confidence due to small sample sizes (acute tests are more readily conducted than chronic tests). The potential contribution of sub-chronic data to guideline derivation is highlighted as these data are more readily extrapolated to chronic endpoints than acute data and sub-chronic tests are not as complex and demanding to conduct as chronic tests.
- Full Text:
- Authors: Browne, Samantha
- Date: 2005
- Subjects: Water-supply -- South Africa , Water quality management -- South Africa , Aquatic ecology -- South Africa , Ecosystem management -- South Africa , Freshwater invertebrates -- South Africa -- Ecology , Water -- Toxicology -- South Africa , Water quality biological assessment
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:4742 , http://hdl.handle.net/10962/d1006173 , Water-supply -- South Africa , Water quality management -- South Africa , Aquatic ecology -- South Africa , Ecosystem management -- South Africa , Freshwater invertebrates -- South Africa -- Ecology , Water -- Toxicology -- South Africa , Water quality biological assessment
- Description: Water resources are under ever-increasing pressure to meet the demands of various water users both nationally and internationally. The process of anthropogenically-induced salinisation serves to exacerbate this pressure by limiting the quantity and quality of water available for future use. Water quality guidelines provide the numerical goals which water resource managers can use to adequately manage and protect aquatic ecosystems. Various methods which have been developed and used internationally to derive such guidelines are discussed. Acute toxicity tests were conducted using two inorganic salts, NaCl and Na₂SO₄. Field collected, indigenous, freshwater macroinvertebrates were used as tests organisms. Data generated from these tests contributed to the expansion of the currently limited toxicological database of response data for indigenous organisms and the suitability of using such organisms for future testing was discussed. Salt sensitivities of indigenous freshwater invertebrates were compared those of species sourced from an international toxicological database and were found to have similar ranges of tolerances to NaCl and Na₂SO₄. Species sensitivity distributions (SSDs), a method of data extrapolation, were derived using different types of toxicological data, and hence different guideline values or protective concentrations were derived. These concentrations were equated to boundary values for South Africa’s ecological Reserve categories, which are used to describe degrees of health for aquatic ecosystems. Provisional results suggest that using only acute toxicity data in guideline derivation provides ecosystem protection that is under-protective. Chronic toxicity data, which include endpoints other than mortality, provide the most realistic environmental protection but lack data confidence due to small sample sizes (acute tests are more readily conducted than chronic tests). The potential contribution of sub-chronic data to guideline derivation is highlighted as these data are more readily extrapolated to chronic endpoints than acute data and sub-chronic tests are not as complex and demanding to conduct as chronic tests.
- Full Text:
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