An assessment protocol for water quality integrity and management of the Nyl River Wetland System

By

Richard Greenfield

Submitted in fulfilment of the requirements for the degree

PHILOSOPHIAE DOCTOR

In Aquatic Health

In the DEPARTMENT OF ZOOLOGY

University of Johannesburg

Promoter: Professor J.H.J. van Vuren University of Johannesburg Co-Promoter Professor V. Wepener University of Johannesburg

October 2004

Acknowledgments

There are many people who helped me in the completion of this research project ranging from those who helped with fieldwork, those who helped with funding to those who gave me moral support. I appreciate all the help that they provided and would like to thank them all for their time and patience.

The staff and students at the University of Johannesburg have been a great help and their input has been invaluable. A special word of thanks must be extended to Professors Johan van Vuren and Victor Wepener. Thank you for all your support and advice; I really appreciate it.

A word of thanks must be extended to Dr. Wynand Vlok, Clayton Cook and Support Chavalala for the valuable help they provided on field sampling trips. Sampling trips with you guys were great; it is hard to say you are working when you are having that much fun at the same time.

I would also like to extend a word of thanks to Dr Steve Mitchell and the Water Research Commission for funding the project.

A final word of thanks must be extended to my family and friends, without their understanding and patience this project would have been much tougher. Thank you for all the motivation provided when things went off track.

If I have forgotten anybody I apologise and thank you.

i Abstract

The Nyl River floodplain is one of the jewels in the arid Limpopo Province. The conservation and protection thereof is thus vitally important. The Nyl River Floodplain is an ephemeral floodplain and the largest of its type in South Africa. The wetland is a Ramsar site and provides habitat for a number of endangered species of birds and animals. The aims of this project were to (1) assess the water and sediment quality in the Nyl River system, (2) to determine baseline levels of pollution, (3) to develop a rapid wetland assessment protocol for biomonitoring and (4) to provide a framework for wetland management.

Eighteen sites in the Groot Nyl and Klein Nyl rivers, as well as in some of the larger tributaries were selected. Water and sediment were sampled and analyzed to determine metal and nutrient levels. Bacterial analysis also took place at five of the sites along the course of the system. The results obtained from the water analysis indicate that bacterial levels in the system are cause for concern.

Although metal levels in the water and the sediment are higher than Target Water Quality and Sediment Guideline Ranges, the metal levels remained relatively constant throughout the system. The metal levels indicated that they pose no potential threat to the system. The comparison between the present and historical ecological state indicated that nutrient levels are increasing in the system. The levels of toxic ammonia did not increase and thus the water quality in the system can thus be classified as fair.

The sequential extraction of the sediment indicated that the majority of the metals in the sediment are not readily bioavailable. They were released by the fourth and fifth fractions and will only become available in the presence of strong reducing or oxidizing agents. Organic contaminant levels were also analysed in the sediment. The results indicated traces of PCB’s (Poly-chlorinated Biphenyls) and pyrethroids (Cypermethrin), but concentrations were too low to quantify.

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The third aim of the project was to develop a Wetland Assessment Protocol. A draft version of the protocol was developed using a modified version of the South

African Scoring System version 5 (SASS5). Due to the lack of biotopes in the system, the vegetation biotope was chose as sampling habitat. Aquatic invertebrates were collected and a total score was given to each sampling site. The total site rating was determined using a combination of the SASS5 scoring system, a newly developed habitat assessment system and a human impact assessment system, The Wetland assessment protocol identified changes in water quality, but more refinement is required on a system with a greater pollution gradient.

The fourth aim of the project was to set up a draft framework for wetland management. The framework is based on the National Estuary Programme of the USEPA. It has been interpreted and adapted for use in wetlands, in a similar way to which USEPA ecological risk assessment guidelines have been adapted for the South African scenario.

This research project was thus able to (1) provide baseline values for the Nyl River System, (2) to produce a first draft of a Wetland Assessment Protocol and (3) provide a framework for wetland management. It is envisaged that the information in this thesis will provide useful information in the protection and management of the Nyl River.

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Opsomming

Die Nylrivier vloedvlakte is een van die juwele van die droë Limpopoprovinsie. Die bewaring en beskerming daarvan is dus baie belangrik. Die Nylrivier- vloedvlakte is ‘n efemerale vleiland en die grootste van sy soort in Suid Afrika. Die vleiland is ‘n Ramsar gebied en verskaf habitats vir verskeie bedreigde voël- en dier-spesies. Die doelwitte van hierdie projek was (1) om die water en sediment kwaliteit van die Nylrivier stelsel te assesseer, (2) om basisvlakke van besoedeling te bepaal, (3) om ‘n vinnige vleiland assesseringsprotokol vir biomonitering te ontwikkel en (4) om ‘n raamwerk vir vleilandbestuur op te stel.

Agtien lokaliteite in die Groot- en Klein Nylriviere, sowel as in vyf van die groter sytakke, was as monsterneemingspunte gekies. Water en sediment was versamel en vir metaal en nutrient-inhoud geanaliseer. Bakteriële analises is ook by vyf van die lokaliteite gedoen. Die resultate van die bakteriële analise het aangedui dat bakterie-vlakke in die water moontlike probleme kan skep.

Alhoewel metaal-vlakke in die water en sediment hoër as die teiken water- kwaliteit en sediment-gids-waardes was, het hulle relatief konstant deur die loop van die stelsel gebly. Die metaalvlakke het daarop aan gedui dat dit geen moontlike gevaar vir die stelsel inhou nie. Dit word ondersteun deur die lae vlakke van toksisiteit wat deur die uitvloeisel toksisiteits-gebaseerde toetse uitgewys is. ‘n Vergelyking tussen die huidige- en historiese ekologiese toestande van die water in die stelsel dui aan dat die nutriënt-lading in die water besig is om te styg. Die vlakke van toksiese ammoniak het nie gestyg nie en dus kan die water as van goeie kwaliteit beskou word.

Sekwensiële ekstraksie van die sediment het aangedui dat die meerderheid van die metale hierin nie biologies beskikbaar is nie. Die metale is in die vierde en vyfde fraksies vrygestel en sal dus slegs in die teenwoordigheid van sterk reduserende en oksiderende agente beskikbaar word. Organiese

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besoedelingstof vlakke van die sediment was ook geanaliseer. Die resultate van hierdie analises dui die teenwoordigheid van Poligechlorineerde Bifenole (PCB’s) en Pyretroïdes (Cypermethrin) aan, maar in konsentrasies te laag om te kwantifiseer.

Die derde doelwit van die projek was om ‘n Vleiland assesseringsprotokol te ontwikkel. ’n Konsep-weergawe van die protokol was ontwikkel deur van ‘n gemodifiseerde weergawe van die akwatiese invertebraatindeks-protokol (SASS5) gebruik te maak. As gevolg van die lae biotoopverskeidenheid in die vleiland, is die plantbiotoop as monsternemings-habitat gekies. Akwatiese invertebrate was versamel om ‘n waarde aan die verskillende lokaliteite toe te ken. Hierdie punt was bepaal deur van ‘n kombinasie van die SASS5 punte- stelsel, ‘n nuut ontwikkelde habitatsassesserings stelsel en ‘n menslike impak assesseringstelsel gebruik te maak. Die Vleilandassesserings-protokol het verskille in waterkwaliteit aangedui, maar verfyning is nodig in ‘n stelsel met ‘n groter besoedelingshelling.

Die vierde doelwit van die projek was om ’n konsep-raamwerk vir bestuur van vleilande optestel. Hierdie raamwerk is op die USEPA Nasionale Strandmeer- Program gebaseer. Dit is geïnterpreteer en aangepas vir gebruik in vleilande, in ‘n soortgelyke wyse as die USEPA Ekologiese risiko analisegids vir Suid Afrikaanse aanwending aangepas is.

Hierdie navorsingsprojek het dus (1) inligting oor basisvlakke van besoedeling in die Nylrivier-stelsel verskaf, (2) ‘n Vleiland assesserings-protokol ontwikkel en (3) ’n bestuurs-raamwerk vir vleilande daargestel. Daar word beoog dat die inligting in hierdie tesis as ‘n bruikbare instrument in die bestuur en bewaring van die Nylrivier gebruik kan word.

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Table of Contents

List of Figures Ix List of Tables Xvi Chapter 1: Introduction 1 References 10 Chapter 2: Locality Description 13 2.1 General 14 2.2 Site Description 18 2.3 References 40 Chapter 3: Materials and Methods 41 3.1 Introduction 42 3.2 Practical applications 45 3.3 Water 46 3.4 Sediments 52 3.5 Statistical Methods 57 3.6 References 59 Chapter 4: Water quality: Results and Discussion 61 4.1 Historical data 62 4.2 Water parameters 87 4.3 Inorganic constituents 99 4.4. Total metal concentrations in the water samples 107 4.5 Bacteriology 137 4.6 Toxicity Testing 145 4.7 Integrated water quality 150 4.8 Present ecological state of the system 154 4.9 Conclusion 159 4.10 Reference 161 Chapter 5: Sediment: Results and Discussion 168

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5.1 Introduction 169 5.2 Aluminium 172 5.3 Chromium 176 5.4 Manganese 180 5.5 Zinc 182 5.6 Copper 185 5.7 Arsenic 187 5.8 Cadmium 190 5.9 Lead 192 5.10 Metal summary 196 5.11 References 197 Chapter 6: Organic contaminants in sediment 199 6.1 Polychlorinated biphenyls 200 6.2 Pyrethroids 201 6.3 Results and Discussion 202 6.4 References 205 Chapter 7: Wetland Assessment Protocol 207 7.1 Biological assemblages 210 7.2 Wetland Classification 212 7.3 Wetland selection 213 7.4 Sampling Methods Selection 214 7.5 Data Analysis and Matrix Determination 216 7.6 Result Reporting 223 7.7 Case Study 223 7.8 References 229 Chapter 8: Wetland Management Framework 231 8.1 Rationale Behind Framework 232 8.2 Develop Monitoring Objectives and Performance Criteria 245 8.3 Establish Testable Hypotheses and Select Statistical Methods 249 8.4 Select analytical Methods and Alternative Sampling 252

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8.5 Evaluation Monitoring Programme Performance 258 8.6 Design and Implement Data Management Plan 262 8.7 Communicate Programme Results 265 8.8 Example of the application of the [NRFBMP]: implementation of 268 bacterial and nutrient contamination monitoring. 8.9 References 274 Chapter 9: Conclusions and Recommendations 275 9.1 References 282

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List of Figures

Chapter 1: Introduction 1 Chapter 2: Locality descriptions 13 Figure 2.1: Map of the Waterberg catchment indicating the river system and 17 the sample point. (Adapted from Higgins and Rogers, 1983). Figure 2.2: Metallogenic map of the Modimolle area (Ehlers and Du Toit, 19 1999). Figure 2.3: Simplified Acocks veld types of the study area. (Midgely et al, 20 1994). Figure 2.4: Klein Nyl Oog (KNO)(February 2002). 30 Figure 2.5: Groot Nyl Oog (GNO) (February 2002). 30 Figure 2.6: Koh I Noor (KIN)(April 2001). 31 Figure 2.7:Dla Dla (February 2002). 31 Figure 2.8: Abba (February 2002). 32 Figure 2.9: Donkerpoort Dam below dam wall (DPD)(April 2001). 32 Figure 2.10: Nylstroom Sewage Treatment Works (STW)(April 2001). 33 Figure 2.11: Effluent discharge pipe leading onto the banks of the Klein Nyl 33 River (November 2002). Figure 2.12: Jasper (April 2001). 34 Figure 2.13: Hessie se Water (HSW)(August 2002). 34 Figure 2.14: Olifants Spruit (April 2001). 35 Figure 2.15: Nylvley Nature Reserve (April 2001). 35 Figure 2.16: Bad se Loop (BSL)(April 2001). 36 Figure 2.17: Mosdene (April 2001). 36 Figure 2.18: Tobias Oog (TO)(April 2001). 37 Figure 2.19: Tobias Mine (TM)(April 2001). 37 Figure 2.20: Tobias station (TS)(April 2001). 38 Figure 2.21:Haakdoring (April 2001). 38 Figure 2.22: Moorddrift (April 2001). 39

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Chapter 3: Materials and Methods 41 Figure 3.1: Flow diagram of sampled components and analysis conducted. 44 Figure 3.2: Flow diagram for Tessier sequential extraction (Coetzee, 1993). 53 Chapter 4: Water quality: Results and discussion 61 Figure 4.1: Graphical representation of historical data on a temporal scale. 65 pH, conductivity and TDS at Klein Nyl River at Nylstroon/Modimolle (KNN). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.2: Graphical representation of historical data on a temporal scale. 66 Chloride, sulphate and nitrite-nitrate at Klein Nyl River at Nylstroon/Modimolle (KNN). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.3: Graphical representation of historical data on a temporal scale. 67 Orthophosphate at Klein Nyl River at Nylstroon/Modimolle (KNN). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.4: Graphical representation of historical data on a temporal scale. 68 pH, conductivity and TDS at Donkerpoort Dam (DPD). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.5: Graphical representation of historical data on a temporal scale. 69 Chloride, sulphate and nitrite-nitrate at Donkerpoort Dam (DPD). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.6: Graphical representation of historical data on a temporal scale. 70 Orthophosphate at Donkerpoort Dam (DPD). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.7: Graphical representation of historical data on a temporal scale. 71 pH, conductivity and TDS at Hessie se Water (HSW). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.8: Graphical representation of historical data on a temporal scale. 72

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Chloride, sulphate and nitrite-nitrate at Hessie se Water (HSW). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.9: Graphical representation of historical data on a temporal scale. 73 Orthophosphate at Hessie se Water (HSW). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.10: Graphical representation of historical data on a temporal scale. 74 pH, conductivity and TDS at Olifants Spruit. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.11: Graphical representation of historical data on a temporal scale. 75 Chloride, sulphate and nitrite-nitrate at Olifants Spruit. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.12: Graphical representation of historical data on a temporal scale. 76 Orthophosphate at Olifants Spruit. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.13: Graphical representation of historical data on a temporal scale. 77 pH, conductivity and TDS at Nylsvley at Deelkraal. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.14: Graphical representation of historical data on a temporal scale. 78 Chloride, sulphate and nitrite-nitrate at Nylsvley at Deelkraal. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.15: Graphical representation of historical data on a temporal scale. 79 Orthophosphate at Nylsvley at Deelkraal. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.16: Graphical representation of historical data on a temporal scale. 80 pH, conductivity and TDS at Bad se Loop (BSL). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.17: Graphical representation of historical data on a temporal scale. 81 Chloride, sulphate and nitrite-nitrate at Bad se Loop (BSL). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.18: Graphical representation of historical data on a temporal scale. 82

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Orthophosphate at Bad se Loop (BSL). A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.19: Graphical representation of historical data on a temporal scale. 83 pH, conductivity and TDS at Tobias Spruit. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.20: Graphical representation of historical data on a temporal scale. 84 Chloride, sulphate and nitrite-nitrate at Tobias Spruit. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.21: Graphical representation of historical data on a temporal scale. 85 Orthophosphate at Tobias Spruit. A polygonal trend line is superimposed on the data to indicate any trends present. Figure 4.22: Graph indicating mean oxygen concentration level fluctuations 93 in the Klein Nyl River as it flows from the source through the Nyl River Floodplain. Figure 4.23: Graph indicating the increase in EC through the Klein Nyl 96 River during August 2001. The light grey bars indicate the points where water from the tributaries mix with the water from Nyl River. Levels given for the tributaries are average EC readings from the different sites in the tributaries. Figures 4.24 (A-F): Spatial and temporal representations of total aluminium 127 (mg/l) concentrations recorded in the water. Figures 4.25 (A-F): Spatial and temporal representations of total chromium 128 (mg/l) concentrations recorded in the water. Figures 4.26 (A-F): Spatial and temporal representations of total 129 manganese (mg/l) concentrations recorded in the water. Figures 4.27 (A-F): Spatial and temporal representations of total iron (mg/l) 130 concentrations recorded in the water. Figures 4.28 (A-F): Spatial and temporal representations of total copper 131 (mg/l) concentrations recorded in the water. Figures 4.29 (A-F): Spatial and temporal representations of total zinc (mg/l) 132

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concentrations recorded in the water. Figures 4.30 (A-F): Spatial and temporal representations of total arsenic 133 (mg/l) concentrations recorded in the water. Figures 4.31 (A-F): Spatial and temporal representations of total cadmium 134 (mg/l) concentrations recorded in the water. Figures 4.32 (A-F): Spatial and temporal representations of total lead (mg/l) 135 concentrations recorded in the water. Figures 4.33 (A-F): Spatial and temporal representations of total selenium 136 (mg/l) concentrations recorded in the water. Figures 4.34: Spatial and temporal representation of total coliform (A), 144 faecal coliform (B) and Heterotrophic (C) counts in the Nyl River System. Figure 4.35 (A-D): Principle component plot of spatial similarities of water in 153 the system. Chapter 5: Sediments results and discussion 168 Figure 5.1: Aluminium concentrations (mg/kg) in the different fractions 174 during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.2: Chromium concentrations (mg/kg) in the different fractions 178 during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.3: Manganese concentrations (mg/kg) in the different fractions 181 during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.4: Zinc concentrations (mg/kg) in the different fractions during the 183 different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.5: Copper concentrations (mg/kg) in the different fractions during 186 the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.6: Arsenic concentrations (mg/kg) in the different fractions during 188

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the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.7: Cadmium concentrations (mg/kg) in the different fractions 191 during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figure 5.8: Lead concentrations (mg/kg) in the different fractions during the 193 different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002. Figures 5.9 A-D. Fraction percentages of mean metal concentrations. 195 Chapter 6: Organic contaminants in sediment 199 Chapter 7: Development of a Wetland Assessment Protocol 207 Figure 7.1: Ecosystem influences on biological integrity. (Adapted from Karr 209 et al., 1986). Figure 7.2 SASS5 score sheet used for primary data collection (Dickens 215 and Graham, 2002). Figure 7.3: WBI Data Sheet. 222 Figure 7.4: Flow diagram of sampled components and analysis conducted. 224 Figure 7.5 (A-D): Principle component analysis of Nylsvley water quality for 225 (A)August 2001, (B)November 2001, (C)March 2002 and (D)July 2002 with the calculated WBI superimposed onto it. Chapter 8: Wetland Management Framework 231 Figure 8.1 Conceptual framework for monitoring programme design. 239 Figure 8.2 Individual steps involved in designing each component of the 240 NRFBMP. Figure 8.3 Conceptual framework for monitoring programme design 246 indicating the development of Monitoring objectives and performance criteria. Figure 8.4 Conceptual framework for monitoring programme design 250 indicating the establishment of a testable hypothesis and statistical method selection.

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Figure 8.5 Conceptual framework for monitoring programme design 253 indicating alternate sampling designs and analytical methods. Figure 8.6 Description of various sampling designs. 255 Figure 8.7 Conceptual framework for monitoring programme design 260 indicating monitoring performance evaluation. Figure 8.8 Conceptual framework for monitoring programme design 263 indicating design and implementation of data management plan. Figure 8.9 Conceptual framework for monitoring programme design 265 indicating program result communication. Figure 8.10 Example of monitoring reports from Chesapeake Bay and 267 Santa Monica Bay. Figure 8.11: Conceptual framework of the biomonitoring programme into 269 which the management of contaminant should be incorporated. Figure 8.12: Developmental and refining stage in designing a monitoring 270 program for potential variables of concern in the system. Figure 8.13: Incorporation of the identified potential coliform contamination 272 in the system into the biomonitoring framework. Figure 8.14: Incorporation of the identified nutrient enrichment into the 273 framework. Chapter 9: Conclusion and Recommendations 275

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List of Tables

Chapter 1: Introduction 1 Table1.1: List of some of the studies conducted on the Nyl River 3 Floodplain. Table 1.2: Table of wetland functions and conservation concerns. 4 (Kupchella and Hyland, 1993). Table 1.3 List of rare and endangered birds found breeding in the Nylsvley 7 Nature Reserve. (Haskins and Kruger, 1997). Chapter 2: Locality Description. 13 Table 2.1: GPS co-ordinates of the 18 localities. 15 Chapter 3 Materials and Methods. 41 Table 3.1: Table of localities and associated sampling strategy. 43 Table 3.2: Table of APHA methods used for the determination of water 47 macro variables. Table 3.3: Pesticide derivatives analysed in sediments to determine 56 pesticide concentrations in sediment. Table 3.4 Interpretation of angles between the lines in correlation bi-plots 58 of chemical variables for PCA for the water quality data. Chapter 4: Water quality: Results and Discussion. 61 Table 4.1: List of gauging stations used to determine reference conditions 63 and number of samples used. Table 4.2: Water quality ranges for historical sites indicating two time 86 periods and temporal changes in variables. Table 4.3: Water quality ranges for the Nyl River System. 87 Table 4.4: pH values in the Nyl River System during the study period. 89 Table 4.5: Dissolved oxygen concentrations (mg/l) during the study period. 91 Table 4.6: Percentage oxygen saturation (%) during the study period. 92 Table 4.7: EC values for the sampling sites for the period April 2001 to 95 March 2003.

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Table 4.8: TDS values for the sampling sites for the period April 2001 to 97 March 2003. Table 4.9: Water temperatures measured during the study period. 98

Table 4.10: Water classification according to CaCO3 concentrations in 99 mg/l.

Table 4.11: Measured CaCO3 concentrations in mg/l 99 Table 4.12: Recorded chloride levels at the sampling sites during the study 101 periods. Table4.13: Nitrate concentrations at the different sampling sites 103 Table 4.14: Nitrite concentrations at the sampling sites 103 Table 4.15: Sulphate levels in the Nyl River System. 105 Table 4.16: Orthophosphate levels in the Nyl river system. 107 Table 4.17: List of TWQR’s (DWAF, 1996a) 107 Table 4.18: Table of the elements scanned using an ICP-MS. 109 Table 4.19: Guideline values for metal content in aquatic ecosystems. 110 Table 4.20: Table of summary statistics for metal concentrations in water 111 (mg/l). Table 4.21: Table of the effects of total coliforms on human health (DWAF, 139 1996c) Table 4.22: Table of effects of faecal coliforms to humans (DWAF,1996c). 141 Table 4.23: Table of effects of heterotrophic bacteria to human health 142 (DWAF, 1996c) Table 4.24: Table of advantages and disadvantages to toxicity testing 145 (Muller and Palmer, 2002). Table 4.25: Recorded mortality percentages during WET testing. 147 Table 4.26: Table of LC 50 values obtained during the study. 149 Table 4.27: Class Assessment Descriptions 154 Table 4.28: Relationship between water temperature, pH and un-ionized 155 ammonia (Bath et al, 1999b). Table 4.29: Nutrient assessment using the un-ionized ammonia 156

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concentration to assign assessment classes for rivers (Bath et al., 1999b). Table 4.30: Assessment of nutrient status based on N:P ratio using only 156 orthophosphate data (Bath et al., 1999b). Table 4.31 Resultant classes assigned to sites analysed 157 Table 4.32: System variable assessment for total dissolved solids (TDS) 158 (Bath et al., 1999b) Table 4.33: Present ecological state for the assessment of pH in rivers 158 (Bath et al, 1999b) Table 4.34: Present ecological state of the sites in the Nyl River system 159 Chapter 5: Sediment Results and Discussion 168 Table 5.1: Table of the different fractions extracted during the sequential 171 extraction process, their binding sites and the remobilisation thereof. (Adapted from Coetzee, 1993) Table 5.2: Table of potential problem metals, ICP-MS detection limits and 172 SQG levels in mg/kg Chapter 6: Organic Contaminants in Sediment 199 Table 6.1: Pesticide derivatives analysed in sediments to determine 203 pesticide concentrations in sediment. Table 6.2: Table of results obtained indicating spatial and temporal 204 distributions of POP’s in the Nyl River system. Chapter 7: Development of a Wetland Assessment Protocol 207 Table 7.1: Table of advantages and disadvantages in using aquatic macro- 211 invertebrates as bio-indicators of wetland integrity. (USEPA, 2002b) Table 7.2: Invertebrate sampling list with relative sensitivities according to 217 the SASS5 score sheet (Adapted from Dickens and Graham, 2002). Table 7.3: Habitat Quality Rating based on percentage vegetation cover 219 Table 7.4: Land Usage Rating Score 220 Table7.5: Table of WBI scores calculated during study period. 225 Chapter 8: Wetland Management Framework 231 Table 8.1: Impacts on the floodplain environment of the Nyl River System. 248

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Table 8.2: Examples of monitoring program objectives and associated 251 questions. Chapter 9: Conclusion and Recommendations 275

xix Chapter 1: Introduction

CHAPTER 1: Introduction

1 Chapter 1: Introduction

Chapter 1: Introduction

Wetlands form a vitally important part of river systems around the world. They perform vital functions that help maintain the quality and quantity of fresh water in many regions. Bellamy (1993) stated that the continued destruction of wetlands by drainage, exploitation and pollution is the worst act of environmental vandalism being committed. It is for this reason that the conservation of wetlands is imperative.

Before one can analyse wetlands and develop means to conserve them it is important to know what a wetland is. The Ramsar Convention defines wetlands as areas of marsh, fen, peatland or water whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh brackish or salt, including areas of marine water the depth of which does not exceed six meters. These areas include riparian and coastal zones (Cowan, 1999). This definition is very broad and thus almost any body of water can be termed as a wetland. The U.S Fish and Wildlife Services (1979) go on to define wetlands as lands transitional between terrestrial and aquatic systems where the water table is usually at or near the surface or the land is covered by shallow water. For purposes of this classification wetlands must have one or more of the following three attributes: (1) at least periodically, the land supports predominantly hydrophytes; (2) the substrate is predominantly undrained hydric soil; and (3) the substrate is non-soil and is saturated with water or covered by shallow water at some time during the growing season of the year (U.S. Fish and Wildlife Services, 1979). Merritt (1994) describes wetlands as any habitat characterised by standing water or a saturated soil for a large part of the year, considering lakes, pond, fen, salt marshes, wet meadows and estuaries, ditches and streams as wetlands.

These three definitions cover a variety of habitats and water bodies and the definitions are thus too broad for the scope of this study. For the purposes of this study wetlands are thus defined as floodplain areas along the course of the main

2 Chapter 1: Introduction channel of the stream, which undergo a temporary/ephemeral flooding period.

With an understanding of what a wetland is, in the scope of the study, one can now look at the functions of the wetlands and in so doing understand the importance of the Nyl River Floodplain. Table 1.2 lists the functions of wetlands and the concerns involved in the conservation thereof.

A large amount of work has been done on the Nyl River Floodplain with respect to its hydrology and its value as a conservation and agricultural asset, but very little has been done with respect to water quality. Table 1.1 indicates some of the studies conducted on the Nyl River Floodplain and the surrounding areas.

Greenfield (2001) concluded in his study of the Nyl River Floodplain that the system was contaminated with heavy metals. The study however didn’t include the whole system and thus could not depict an accurate account of the heavy metal levels in the entire system. This study takes the entire system into account incorporating both the sources of the Groot and Klein Nyl rivers and the Tobias Spruit, Hessie se Water, Bad se Loop and the Olifants Spruit. The majority of the work conducted on the Nyl River Floodplain revolves around the possible effects of hydrological changes to the flow regime by the Centre for Water in the Environment at the University of the Witwatersrand (see cited work of Rogers in Table 1.1).

3 Chapter 1: Introduction

Table1.1: List of some of the studies conducted on the Nyl River Floodplain. Authors Title Higgins, S.I. and Rodgers, K.H. 1993 The Nyl River Floodplain: Situation Report and Preliminary Statement of Impacts of the Proposed Olifants Spruit Dam. Rogers, K.H. and Higgins, S.I. 1993 The Nyl River Floodplain as a functional unit of the landscape: Preliminary synthesis and future research. Haskins, C. and Kruger, J. 1997 Information sheet for the site designated to the List of Wetlands of International Importance especially as waterfowl habitat. Petrie, S.A. and Rodgers, K.H. 1997 Ecology, nutrient reserve dynamics and movements of white faced ducks in South Africa. Duthie, A. and Tarboton, W. 2001 Nylsvley- A Conservation Imperative – Article on the Nyl Floodplain. Jooste, A. and Polling, L, 2000 Aftermath of simultaneous toxic spills in the Klein Nyl River, Northern Province, South Africa. Booij-Liewes, M. and Roge rs, K.H. 2002 Vegetation change in response to disturbance on the Nyl River Floodplain. James, C., Rogers, K.H. and Birkhead, A. The hydrological and Hydraulic study of the Nyl 2002. River Floodplain. Greenfield, 2001. Bioaccumulation of selected metals in water, sediment and selected tissues of Oreochromis mossambicus and Clarias gariepinus in the Nyl River System and Nylsvley

Table 1.2: Table of wetland functions and conservation concerns. (Kupchella and

4 Chapter 1: Introduction

Hyland, 1993). Wetland Function How Wetlands Perform Conservation Concern. Function Flood storage Some wetlands store and Fill or dredging of wetlands slowly release flood waters reduces their flood storage capacity Flood conveyance Some wetlands serve as If flood flows are blocked by floodway areas by conveying fills, dikes or other structures, flood flows from upstream to increased flood heights and downstream points velocities result, causing damage to adjacent upstream and downstream areas. Erosion control/wave barriers Wetland vegetation, with Removal of vegetation massive roots and rhizome increases erosion and reduced systems, binds and protects capacity to moderate wave soils. Vegetation also act as intensity wave barriers. Sediment control Wetland vegetation binds soil Destruction of wetland particles and retards the topographic contours or movement of sediment in vegetation decreases wetland slowly flowing waters. capacity to filter surface runoff and act as sediment traps. Pollution control Wetlands act as settling ponds Destruction of wetland and remove nutrients and contours and vegetation other pollutants by filtering and decreases natural pollution causing chemical breakdown control capacity. of pollutants. Fish and wildlife habitat Wetlands provide water, food Fills, dredging, damming and supply and nesting and resting other alterations destroy and areas. damage flora and fauna and decrease productivity. Recreation Wetlands provide scenery, Fill, dredging or other wild areas, habitat, wildlife and int erference with wetland water for recreational use. causes loss of area for boating, swimming, bird watching, hunting and fishing. Water supply (surface) Some wetlands store Fills or dredging cause floodwater, reducing the timing accelerated runoff and and amount of surface runoff. increased pollution. Aquifer recharge Some wetlands store water Fills or drainage may destroy and release it slowly to aquifer recharge capability, groundwater deposits. thereby reducing base flow to streams.

The benefits of wetlands are not always recognised and result in pollution, poor management and destruction of these areas. Holdgate (1993) wrote that wetlands have been treated with such hostility by many human societies over so many years that there conservation seems almost counter cultural. Wetlands can either have direct or indirect benefits to humans. Direct benefits can be noted as

5 Chapter 1: Introduction having direct advantages to man such as crop or pasture production and recreational significance (Rennies Wetland Project Booklet 2). Indirect benefits do not require the use of the wetland to realize the benefits thereof. These indirect benefits include ground water recharge, flood senescence and water purification (Rennies Wetland Project Booklet 1).

The National Water Act (NWA, 1998) states that the nation’s water resources are to be protected, used, developed, conserved, managed and controlled in ways that take many factors into account, such as:

1. Meeting basic human needs, and those of future generations. 2. Promoting equitable access to water. 3. Promoting the efficient, sustainable and beneficial use of water in the public interest. 4. Provide for growing demand for water use. 5. Protecting aquatic and associated ecosystems and their biological diversity. 6. Reducing and preventing pollution and degradation of water resources. 7. Meeting national obligations. 8. Managing floods and droughts.

Wetlands can prove to be crucial in the Governments’ attempts to attain the goals of the Water Act with respect to all eight points. Management plans are thus imperative if these jewels are to be protected.

Before a practical and workable management plan can be designed one must ascertain baseline contamination values for the floodplain and surrounding tributaries. Because of its Ramsar status, Nylsvley is classified as a wetland of international importance and part is managed as a nature reserve. A management plan for the nature reserve has been set up with goals and objectives but these do not include monitoring the water quality in the system.

6 Chapter 1: Introduction

The management plan looks at the Nylsvley Nature Reserve as the main conservation concern with the catchment not playing any role in the conservation effort. The management plan makes use of the following operating principles: controlled sustainable use, environmental education, rehabilitation, maintenance of system integrity with respect to species diversity, promotion of ecotourism, linking development to resource potential, maintaining aesthetic quality and subscription to all treaties to which South Africa is party (Haskins and Kruger, 1997). Little is however done to monitor the water quality of the water entering the floodplain.

The Nyl River floodplain is of great importance as it helps filter and purify water in this part of the Limpopo Province. The South African Push Pull Project (2003) stated that the Limpopo Province is the poorest and the most arid province in the country. The floodplain is situated in the semi-arid savannah region and the preservation of any water is of great value. The wetland also helps in ground water recharge and thus makes water more available to the farmers in the area throughout the year. The recharge of the ground water supplies also helps prevent water loss via evaporation. The conservation of such an environmental treasure is made even more important due to the habitat it provides to rare and endangered species of flora and fauna.

The Nyl River floodplain serves as the breeding grounds and wintering grounds for a variety of birds. Tarboton (1987) listed some 412 species of birds found in the wetland with water bird numbers reaching approximately 80 000 in wet years. Table 1.3 lists some of the rare and endangered species found in the Nylsvley Nature Reserve.

7 Chapter 1: Introduction

Table 1.3 List of rare and endangered birds found breeding in the Nylsvley Nature Reserve. (Haskins and Kruger, 1997). Species Common name Butroides rufiventris Rufousbellied Heron Ixobrychus minutes Little Bittern Ixobychus sturmii Dwarf Bittern Botaurus stellaris Bittern Nettapus auritus Pygmy Goose Porzana pusilla Baillon’s Crake Aenigmatolimnas marginalis Striped Crake Ciconia nigra Black Stork

The Wetland also provides habitat for some 17 species of fish (Kleynhans, 1991) and 132 species of herpetofauna (23 species of lizard, 1 amphisbaenid, 17 frogs and 29 snakes) (Jacobsen, 1991).

The lack of a suitable biomonitoring tool may play a role in the lack of monitoring taking place in the system. There are many bio-monitoring protocols available for the assessment of river system quality but there isn’t a protocol developed for wetlands. The variable nature of wetlands and the many different kinds of wetlands, make it difficult to develop a protocol suitable for all wetland types.

The main aim of this project was to develop a biomonitoring framework program for the Nyl River Floodplain.

The objectives of the project were thus: 1. To provide baseline data on the levels of metals and nutrients in the water of the Nyl River Floodplain and some of the Nyl Rivers larger tributaries. 2. To provide a baseline assessment of inorganic and organic contaminant levels in the sediment of the Nyl River Floodplain.

8 Chapter 1: Introduction

3. To develop a Wetland Assessment Protocol (WAP) for the assessment of floodplain biological integrity using the Nyl River Floodplain as a model. 4. To develop an integrated comprehensive biomonitoring framework for the Nyl River Floodplain.

The WAP will also help in assessing similar wetland although the end product from this project will only be a starting block. With further work on other systems it is hoped that the WAP will make a contribution to the conservation of these vitally important areas in the arid Limpopo Province. It is also hoped that the results can help shed some light as to the dwindling numbers of water fowl observed in the Floodplain over the past couple of years.

This thesis is separated into different chapters dealing with different topics. The breakdown of the different chapters is as follows: Chapter 2: Locality description · Provides and outline of site location, surrounding activities, possible causes for concern and locality vegetation cover. Chapter 3: Materials and methods · Provides the methods used for sample analysis, chemicals and apparatus required. Chapter 4: Water results and discussion. · Provides all the results to do with water analysis and the discussion thereof. This chapter covers historical data, nutrient levels, bacterial levels, metal concentrations, toxicity testing and the present ecological state of the water in the system. Chapter 5: Sediment results and discussion · Provides the results from the sequential extraction of metals from the sediment samples, and a discussion thereof. Chapter 6: Organic contaminants in sediment · Provides the results obtained from the study of organic compounds in the sediment.

9 Chapter 1: Introduction

Chapter 7: Wetland assessment protocol · Provides the framework for a wetland assessment protocol using aquatic invertebrates as indicators of water quality monitoring. Chapter 8: Nyl River Floodplain Biomonitoring protocol. · Provides the framework for a biomonitoring protocol to help in the development of a management plan for the Nyl River Floodplain. Chapter 9: Conclusions and recommendations. · Provides the conclusion from the this study and provides some recommendations as the way forward in protecting this valuable treasure of the Limpopo Province.

10 Chapter 1: Introduction

References BELLAMY, D.J. (1993). Introduction. [In] Wetlands in Danger, ed. P. DUGAN. Oxford University Press. New York. pp. 187. BOOIJ-LIEWES, M. and ROGERS, K.H. 2002 Vegetation change in response to disturbance on the Nyl River Floodplain. Center for Water in the Environment, University of the Witwatersrand COWAN, G.I. (1999). Introduction. Biota of South African Wetlands in relation to the Ramsar Convention. Department of Environmental Affairs and Tourism. Pretoria. pp. 100. DUTHIE, A. and TARBOTON, W. 2001 Nylsvley- A Conservation Imperative – Article on the Nyl Floodplain. Wildlife and Environment Society of South Africa. GREENFIELD, R. (2001). Bioaccumulation of selected metals in water, sediment and selected fish tissues of Oreochromis mossambicus and Clarias gariepinus in the Nyl River System and Nylsvley. Unpublished MSc Dissertation, University of the North, Sovenga, South Africa. HASKINS, C. and KRUGER, J. 1997 Information sheet for the site designated to the List of Wetlands of International Importance especially as waterfowl habitat. Chief Directorate Environmental Affairs, Pietersburg. South Africa. http://www.ngo.grida.no/soesa/nsoesa/resource/wetland/nylsvley_ris.htm HIGGINS, S.I. and ROGERS, K.H. (1993). The Nyl River Floodplain: Situation Report and Preliminary Statement of Impacts of the Proposed Olifants Spruit Dam. Report No 3/93. Center for Water in the Environment, University of the Witwatersrand. HOLDGATE, M.W. (1993). Forward. [In]. Wetlands in Danger, ed. P. DUGAN. Oxford University Press, New York. pp. 187. JACOBSEN, N.G.H. (1991). The influence of the periodic flooding of the Nyl River Floodplain on amphibians, reptiles and mammals. Report to the Chief Director of Nature and Environmental Conservation, Transvaal Provincial Administration, Pretoria. JAMES, C., ROGERS, K.H. and BIRKHEAD, A. (2002). The Hydrological and Hydraulic study of the Nyl River Floodplain. Center for Water in the Environment, University of the Witwatersrand JOOSTE, A. and POLLING, L., (2000). Aftermath of simultaneous toxic spills in the Klein Nyl River, Northern Province, South Africa. South African Journal of Aquatic Science, 25 (1/2): 1-7. KLEYNHANS, C.J. (1991). The Nyl Floodplain: its ichthyofauna and conservation status. Report to the Chief Director of Nature and Environmental Conservation, Transvaal Provincial Administration, Pretoria. KUPCHELLA, C.E. and HYLAND, M.C. (1993). Environmental Science: Living with the system of nature. Prentice-Hall International, Inc. pp. 579. MERRITT, A. (1994). Wetlands, Industry and Wildlife: A manual of principles and practices. Hindson Print Limited. Newcastle. pp. 175. NWA (1998). National Water Act 36 of 1998, Government Printers, Pretoria. PETRIE, S.A. and ROGERS, K.H. (1997). Ecology, nutrient reserve dynamics and movements of white-faced ducks in South Africa. Department of Environmental Affairs and Tourism. Pretoria. South African Wetland

11 Chapter 1: Introduction

Conservation Programme Report Series. pp 107. PUSH PULL PROJECT (2003). “Push Pull “ Strategies for Management of Stemborers in South Africa. South African Push Pull Activities. http://southafrica.push-pull.net/limpopo.html. RENNIES WETLAND PROJECT booklet 1: Wetlands and People. http://psyberggate.com/wetfix/home.htm RENNIES WETLAND PROJECT booklet 2: What is a Wetland? http://psyberggate.com/wetfix/home.htm ROGERS, K.H. and HIGGINS, S.I. (1993). The Nyl River Floodplain as a functional unit of the landscape: Preliminary synthesis and future research. Report No 1/93. Center for Water in the Environment, University of the Witwatersrand. TARBOTON, W.R. (1987). The Nyl Floodplain. Fauna and Flora 45. U.S. Fish and Wildlife Services (1979). Wetland definitions http://wetlands.fws.gov/definition.htm

12 Chapter 2: Locality Description

Chapter 2: Locality Description

13 Chapter 2: Locality Description

Chapter 2: Locality Description.

2.1: General The study area falls within the Waterberg catchment area. It follows the course of both the Klein and Groot Nyl Rivers, from their sources to their confluence and then the course of the Nyl River to Moorddrift Dam near Mokopane (Potgietersrus). The Nyl River flows through or is impacted on by the towns of Modimolle (Nylstroom) and Moogkopong (Naboomspruit).

To gain a better idea of the system and the possible impacts on the Nyl River Floodplain it is important to have some knowledge of the catchment area as well as the anthropogenic activities that occur there. The Waterberg catchment is 600 to 800 km2 in size and has a mean annual rainfall of approximately 623 mm (Higgins and Rodgers, 1993). The Klein Nyl River is dammed at Donkerpoort, and most of the stream reserve is provided by the Groot Nyl River and the Olifants Spruit. Precipitation, ground water storage and water abstraction are the main factors influencing the flow of water to the floodplain (Haskins and Kruger, 1997).

During the study 18 localities were selected from an extensive desktop study of the 1:250 000 2428 Modimolle (Chief Directorate, 2001a) and 1: 50 000 topographic map series of South Africa (Chief Directorate, 2001b-f). The sites were chosen to be evenly distributed throughout the system, thereby providing representative sample points in the Nyl River, the Nyl River floodplain and some of the tributaries with more permanent flow throughout the season. These sites were selected so that possible point sources of pollution could be identified.

The position of the localities were recorded using a Geographical Positioning System (GPS) and the co-ordinates were tabulated. Table 2.1 indicates the GPS co-ordinates of the 18 localities.

14 Chapter 2: Locality Description

Table 2.1: GPS co-ordinates of the 18 localities. Locality Southern co-ordinate Eastern co-ordinate Klein Nyl Oog (KNO) 24° 42’ 967” 28° 14’ 542” Groot Nyl Oog (GNO) 24° 46’ 959” 28° 15’ 270” ABBA 24° 40’ 800” 28°16’ 746” Donkerpoort Dam (DPD) 24° 40’ 542” 28° 20’ 019” Dla Dla 24° 45’ 645” 28° 20’ 757” Nylstroom/Modimolle Sewage 24° 42’ 335” 28° 25’ 747” Treatment Works (STW) Jasper 24° 42’ 536” 28° 28’ 786” Hessie se Water (HSW) 24° 39’ 948” 28° 28’ 408” Olifants Spruit 24° 39’ 214” 28° 28’ 589” Tobias Oog (TO) 24° 28’ 995” 28° 35’ 933” Tobias Mine (TM) 24° 28’ 323” 28° 40’ 886” Tobias station (TS) 24° 27’ 504” 28° 45’ 080” Bad se Loop (BSL) 24° 34’ 442” 28° 28’ 687” Mosdene 24° 33’ 950” 28° 45’ 850” Haakdoring 24° 25’ 804” 28° 54’ 711” Moorddrift 24° 15’ 175” 28° 58’ 521” Koh I Noor (KIN) 24° 38’ 812” 28° 17’ 813” Nylsvley 24° 38’ 960” 28° 41’ 445”

Figure 2.1 indicates the 18 localities selected in the system.

The Nyl River flows in a northeasterly direction from Modimolle in the west to Mokopane in the east. At Mokopane the river changes course northwards and is renamed the Makgalakwena River. The Makgalakwena then flows into the Limpopo River. The Nyl River and floodplain are subjected to various potential impacts via anthropogenic activities such as mining and farming as well as the associated problems caused by formal and informal settlements. According to the Mookgopong (Anon, 2003a) and Mokopane (Anon, 2003b) tourism bureau the farming activities that take place include both agriculture and live stock. Crops such as maize, groundnuts, tobacco, citrus, cotton, millet, wheat, rice and

15 Chapter 2: Locality Description sunflowers are planted in the fertile soil of the Waterberg catchment area. Cattle are also farmed extensively in the rich grazing provided by the floodplain. Around the sources of the Klein Nyl Rivers and the Groot Nyl River game farming takes place on a large scale with a large number of privately owned game farms (Anon, 2003c). The mining of tin, chrome and fluorspar also takes place in the area between Mookgopong and Mokopane. The Waterberg catchment is characterised by it richness in minerals with 545 known mineral deposits (Anon, 2003d) Figure 2.2 indicates the different mineral deposits.

The lithology of the area indicated on the 1: 250 000 metallogenic series map of Nylstroom (Figure 2.2) shows that the study area has three distinct regions namely a sedimentary rock region and two igneous rock regions (Ehlers and Du Toit, 1999). The sedimentary region is located in the area surrounding Modimolle and stretches from the sources of the Groot and Klein Nyl Rivers to a point just before Mookgopong. This region is characterised by arenite and arenite with subordinate argillite dominance. The sites that fall in the system before the site called Jasper fall within a manganese ore field.

The second region is dominated by gabbro (iron dominant) igneous rocks. This region stretches from the south western side of Mookgopong to near the site Haakdoring (H). This region falls within the Springbok flats coal fields. East of this region is a section made up of granite and granitoid rocks. This stretch is near the Tobias Spruit. The rocks are extremely rich in minerals namely magnesium, fluorspar, silica (glass sand), tin, silver, dimension stone (quartzite and granite dominant) and lead.

16 Chapter 2: Locality Description

Legend: A:(KNO) B: Abba C:(KIN) D:(DPD) E:(GNO) F: Dla Dla G:(STW) H:Jasper I:(HSW) J:Olifants Spruit K:Nylsvley L:BSL M:Mosdene N:TO O:TM P:TS Q:Haakdoring R:Moorddrift

Figure 2.1: Map of the Waterberg catchment indicating the river system and sample points. (Adapted from Higgins and Rogers, 1993).

17 Chapter 2: Locality Description

The third region is also very mineral rich. This region stretches from the site on the farm Haakdoring to the end of the study area at Moorddift Dairy. This region is dominated by pyroxenite and gabbronorite igneous rocks. Minerals in this region include tin, vanadium, iron, nickel, chromium, platinum and copper.

2.2: Site Description All vegetation descriptions in this chapter were done in collaboration with Antonio De Castro, botanical collaborator/consultant in the project. An asterisk before a plant name indicates that it is exotic. Figure 2.3 illustrates that the entire study area is homogeneous, and falls within the tropical bush and savannah veld type (Midgely et al., 1994).

Klein Nyl Source (KNO)

The Klein Nyl River springs from the source north west of Modimolle. The site is located approximately 100 m from where it bubbles out of the ground. The water flows though a small patch of ferns and into a small impoundment on the farm Vaalkop 405. The farm is a cattle farm with few impacts apart from the effects of the cattle. The site is located in the impoundment. Figure 2.4 indicates the site and some of the surrounding vegetation.

18 Chapter 2: Locality Description

Arenite Arenite with Subordinate argillite dominance Gabbro igneous rocks Gabbronorite Pyroxenite Granite and granitoid rocks

Figure 2.2: Metallogenic map of the Modimolle area (Ehlers and Du Toit, 1999).

19 Chapter 2: Locality Description

Figure 2.3: Simplified Acocks veld types of the study area. (Midgely et al., 1994).

20 Chapter 2: Locality Description

This dam is situated at relatively high altitude on a small first order stream vegetated by dense marsh vegetation that is in good condition and comprises a high diversity of indigenous hydrophytic grasses and sedges. The margins of the dam itself are dominated by emergent species such as Typha capensis and Cyperus spp. Floating leaved aquatic species such as Nymphaea capensis and Nymphoides indica form numerous stands in deeper water. Few alien invasive species occur, though *Paspalum urvillei is common and conspicuous along the upper margins of the wetland marsh communities.

Groot Nyl Source (GNO)

This site is located at a point where the secondary road crosses the Groot Nyl for the first time. The source of the river is approximately 500 m up stream and is situated on the cattle farm Groot Nyls Oog 447. Figure 2.5 is a photograph of the GNO site taken in April 2001.

This sampling site is situated in the upper reaches of a first order stream at relatively high altitude. The broad floodplain is vegetated by indigenous grass and sedge dominated marsh that is highly diverse and in good condition. The closed woodland fringing the floodplain is dominated by species such as Acacia karoo and Rhus lancea.

Koh I Noor.(KIN)

The KIN site is situated on a private game farm below a waterfall. This stream is a tributary of the Klein Nyl River and flows into the Donkerpoort Dam. The private game farm is situated on the farm Nooigedacht 404. Figure 2.6 indicates the pool that was sampled.

This site is situated in the upper reaches of a mountain stream. The riparian closed woodland is in good condition and comprises a relatively high diversity of

21 Chapter 2: Locality Description tree species. Common and conspicuous species include Combretum erythrophyllum, Celtis africana and A. karoo. The herbaceous vegetation of the riparian and narrow floodplain habitats is dominated by indigenous, hydrophytic grasses and sedges. Some two hundred meters below the site the riparian habitats of this stream have been invaded by large stands of the aggressively invasive tree *Populus canescens.

Dla Dla

This locality is situated on the farm Sussensvale approximately 500m upstream from where the Groot Nyl River flows beneath the R101. The farm has some ploughed lands but is also being used for the production of chickens. During the study the owner constructed a fish dam below the flood line of the river which could have possible disastrous effects during periods of floods. Figure 2.7 indicates the site. Factors such as ploughing, sedimentation and encroachment by alien species has significantly altered the vegetation at this site.

The riparian vegetation consists of secondary closed wood or forest completely dominated by *Eucalyptus spp. Only small patches of indigenous riparian marsh and grassland remain. These patches are dominated by indigenous hydrophytic grasses and sedges such as Phragmites australis, Miscanthus capensis, Ischaemum fasiculatum, Kyllinga spp. and *Cyperus spp.

ABBA

This site (Figure 2.8) is located on the road that runs past the Donkerpoort Dam below the ABBA game ranch on the farm Vaalkop 405. On the eastern side of the site there is a private game ranch and on the western side maize is being cultivated. Both of these activities could have possible deleterious effects on the water quality of the Klein Nyl River.

22 Chapter 2: Locality Description

The vegetation of the site consists of secondary plant communities dominated by indigenous pioneer species such as T. capensis and alien invasive species such as *Sesbania punicea and *Eucalyptus spp.”

Donkerpoort Dam (DPD).

This site (Figure 2.9) is situated on the Klein Nyl River below the Donkerpoort Dam approximately 100m upstream from the point where the Klein Nyl flows beneath the secondary road that leads to the dam. It is situated on the farm Donkerpoort 406. A possible impact to this site is the damming effect caused by the presence of a weir.

The riparian and floodplain vegetation consists of marsh vegetation dominated by indigenous grasses and sedges. Some alien invasive species, e.g. *P. urvillei and *Paspalum dilatatum are common, but not dominant in these communities. The riparian and floodplain habitats have also been heavily encroached by Eucalyptus spp., which are the dominant trees, and *S. punicea which is the dominant shrub.

Nylstroom Sewage Treatment Works (STW)

This locality (Figure 2.10) is situated below the point where the STW releases its effluent into the Klein Nyl River. The surrounding land use is cattle grazing, but the site is characterised by an abundance of alien invasive trees (mainly Eucalyptus spp.). The stream at this site is sterile in appearance with a lack of both marginal and aquatic vegetation. One disturbing fact about this site is the presence of a large pipe leading from the STW that releases sewage sludge onto the land in times of need. Figure 2.11 illustrates the pipe and dried sludge that remains on the ground.

The vegetation at this site is indicative of severely disturbed riparian habitat that

23 Chapter 2: Locality Description has been affected by anthropogenic factors such as poor water quality, altered hydrological patterns, overgrazing and trampling. Only a few indigenous riaparian trees, such as A.karoo, remain. The vegetation of the site is secondary Eucalyptus woodland, and the herbaceous layer consits mostly of indigenous pioneer sedges and grasses with a high percentage of alien hebaceous species also occuring.

Jasper

Jasper (Figure 2.12) is situated at the point where the secondary road which leads to the Jasper train station crosses the Nyl River. It is situated approximately 1.5 km downstream of the confluence of the Groot and Klein Nyl Rivers. The site is on a cattle farm and is impacted on by the cattle as well as the effluent arising from the STW and the informal settlement Phagameng.

The riparian vegetation at this site consists of A. karoo dominated closed woodland. The dominance of P. australis on the active-channel banks indicates possible altered hydrological patterns. Persicaria spp. are also a common and conspicuous component of the active channel banks, where they form dense stands in places. The floodplain vegetation is dominated by indigenous hydrophytic grasses and sedges, though some alien invasive species such as *P. dilatatum, *P. urvillei and *Aster squamatus are common and conspicuous.

Hessie se Water (HSW)

This site (Figure 2.13) is located at the bridge where Hessie se Water flows beneath the old N1 to Mookgopong. It is a tributary of the Olifants Spruit.

The active-channel banks are dominated by the indigenous pioneer species P. australis, and have also been encroached by alien invasive willow trees (*Salix babylonica). Patches of indigenous grass and sedge dominated marshes still

24 Chapter 2: Locality Description occur within riparian and floodplain habitats. These patches are characterised by the robust grass *Miscanthus junceus.

Olifants Spruit

This site (Figure 2.14) is in one of the main tributaries of the Olifants Spruit. The site is on a cattle farm that is not farmed intensively. The Olifants Spruit has its confluence with the Nyl River about 1 km downstream of the site at Jasper.

The indigenous riparian woodland at this site, characterised by species such as A. karoo and C. erythrophyllum has been heavily encroached by alien invasive trees and shrubs such as *Melia azedarach and *S. punicea. The active-channel banks are dominated by the indigenous pioneer species P. australis and T. capensis. Small patches of indigenous marsh vegetation dominated by sedges and grasses still occur within the riparian and floodplain habitats.

Nylsvley Nature Reserve (Nylsvley)

This site is located in the middle of the wetland. It is in the main channel and .is characterised by the vegetation. The floodplain is unique in the fact that it is the only place in South Africa where the wild rice Oryza longistaminata grows (Gibbs et al. 1991). The nature reserve also provides valuable breeding ground for the endangered Roan antelope (Hippotragus equinus) and numerous waterfowl species. In all there are 23 red data bird species found in the wetland (Tarboton, 1987). The system is extremely variable in nature with water levels determining the site characteristics. Figure 2.15 indicates the wetland under flooded conditions The active-channel is situated in a large floodplain vegetated with dense and highly productive, healthy marsh vegetation, dominated by the hydrophytic grass O. longistaminata. This uniform marsh is punctuated by ‘islands’ formed by dense reedbeds of Phragmites mauritianus. Though dense and highly

25 Chapter 2: Locality Description productive, the vegetation of these floodplain habitats contains a relatively low plant diversity comprising mostly of indigenous grasses and sedges. The active- channel itself provides habitat for rooted and submerged or floating leaved species such as Lagarosiphon sp. and Potamogeton thunbergii. The edge of the floodplain is characterised by closed woodland dominated by Acacia tortilis and Acacia nilotica.

Bad se Loop (BSL)

The Bad se Loop site (Figure 2.16) is situated at the bridge where Bad se loop flows under the old N1 (R101) north between Modimolle and Mookgopong.

The vegetation of this site is in good condition and consists of closed riparian woodland characterised by species such as A. karoo, R. lancea, Ziziphus mucronata and Rhus pyroides. Depostional bars within the channel are vegetated by indigenous hydrophytic grasses and sedges such as P. australes, Cynodon dactylon, Hemarthria altissima and Paspalum spp.

Mosdene.

This site (Figure 2.17) is situated on the western side of the R519, which leads to Roedtan. It is on the farm Mosdene, which is a private nature reserve and heritage site. Mosdene is known for its avifaunal diversity. In 1997 the owner removed the remaining cattle from the land (Haskins and Kruger, 1997).

The active-channel is situated in a large floodplain vegetated with dense and highly productive, healthy marsh vegetation, dominated by the hydrophytic grass O. longistaminata. This uniform marsh is punctuated by ‘islands’ of A. tortilis and A. nilotica closed woodland situated on slightly elevated areas that are less exposed to flooding. Though dense and highly productive, the vegetation of these floodplain habitats contains a relatively low plant diversity comprising

26 Chapter 2: Locality Description mostly of indigenous grasses and sedges. The active-channel itself provides habitat for rooted and submerged or floating leaved species such as Lagarosiphon sp. and P. thunbergii. The edge of the floodplain is characterised by closed woodland dominated by A. tortilis and A. nilotica. The actual sampling site is situated adjacent to a road where the vegetation has been somewhat degraded by the altering of hydrological patterns, and contains a higher percentage of indigenous pioneer species.

Tobias Eye (TO)

The Tobias eye site (Figure 2.18) is situated approximately 500m from the source of the Tobias Spruit, on the farm Rietfontein 513. The river flows through grazing before it reaches the site.

The riparian woodland at this site is dominated by species such as A. karoo and R. lancea. More open areas within the riparian and floodplain habitats are dominated by indigenous grass and sedge dominated marsh vegetation. Large parts of the riparian and floodplain habitats have been invaded by dense stands of *P. canescens. The alien invasive grass *P. urvillei is also common and conspicuous.

Tobias Mine (TM)

The Tobias Mine (TM) site (Figure 2.19) is situated in one of the tributaries of the Tobias Spruit. It is situated at the point where the tributary runs under the R520 and just below the water storage dam belonging to the fluorspar mine. The stream flows into the Tobias Spruit approximately 5 km downstream.

The riparian vegetation of this site consists of dense riparian woodland characterised by species such as C. erythrophyllum, R. lancea and A. karoo. The active channel banks are dominated by pioneer reeds (Phragmites spp.).

27 Chapter 2: Locality Description

Tobias Station (TS).

The Tobias station site (Figure 2.20) is located where the Tobias Spruit flows under the N1 north, close to the turn off for the Tobias train station.

The riparian vegetation of this site consists of A. karoo dominated closed woodland. The dense herbaceous layer is dominated by terrestrial and hydrophytic grasses such as Hyparrhenia spp., Sporobolus pyramidalis and Cymbopogon spp.

Haakdoring

The Haakdoring site (Figure 2.21) is situated in a dam on the farm Haakdoring. The farm practices intensive cattle farming. It is below the eastern side of the secondary road that transverses the floodplain.

The active-channel is situated in a large floodplain vegetated with dense and highly productive, healthy marsh vegetation, dominated by the hydrophytic grass O. longistaminata. Though dense and highly productive, the vegetation of these floodplain habitats contains a relatively low plant diversity comprising mostly of indigenous grasses and sedges. The active-channel itself provides habitat for rooted and submerged or floating leaved species such as Lagarosiphon sp. and P. thunbergii. Pools of open water within the floodplain support marginal vegetation characterised by dense stands of sedges such as Cyperus spp. and Schoenoplectus spp. The edge of the floodplain is characterised by closed woodland dominated by A. tortilis and A. nilotica. The actual sampling site is situated adjacent to a large berm that has significantly altered hydrological patterns (especially flooding regimes) and lead to the creation of numerous pools of open water.

28 Chapter 2: Locality Description

Moorddrift

The Moorddrift site (Figure 2.22) is located in a storage dam on the Moorddrift dairy farm. The surrounding land use was previously cattle grazing, but has now been converted into its natural state for the purpose of game farming.

This sampling site is situated in a large farm dam. Rooted, submerged or floating leaved aquatic plants occur throughout the majority of the water surface of the dam. These species include P. thunbergii, Potamogeton sp. Lagarosiphon sp. and Myriophyllum sp. The marginal vegetation is dominated by hydrophytic, emergent sedges such as Cyperus spp. and Schoenoplectus spp. Above this zone of emergents, the seasonally flooded areas are dominated by hydrophytic grasses. The margins of the floodplain are vegetated by closed woodland dominated by A. tortilis and A. nilotica.

29 Chapter 2: Locality Description

Figure 2.4: Klein Nyl Oog (KNO)(February 2002)

Figure 2.5: Groot Nyl Oog (GNO)(February 2002)

30 Chapter 2: Locality Description

Figure 2.6: Koh I Noor (KIN) (April 2001)

Figure 2.7: Dla Dla (February 2002)

31 Chapter 2: Locality Description

Figure 2.8: Abba (February 2002)

Figure 2.9: Donkerpoort Dam below dam wall (DPD) (April 2001)

32 Chapter 2: Locality Description

Figure 2.10: Nylstroom Sewage Treatment Works (STW) (April 2001)

Figure 2.11: Effluent discharge pipe leading onto the banks of the Klein Nyl River (November 2002)

33 Chapter 2: Locality Description

Figure 2.12: Jasper (April 2001)

Figure 2.13: Hessie se Water (HSW) (August 2002)

34 Chapter 2: Locality Description

Figure 2.14: Olifants Spruit (April 2001)

Figure 2.15: Nylsvley Nature Reserve (April 2001)

35 Chapter 2: Locality Description

Figure 2.16: Bad se Loop (BSL) (April 2001)

Figure 2.17: Mosdene (April 2001)

36 Chapter 2: Locality Description

Figure 2.18: Tobias Oog (TO) (April 2001)

Figure 2.19: Tobias Mine (TM) (April 2001)

37 Chapter 2: Locality Description

Figure 2.20: Tobias Station (TS) (April 2001)

Figure 2.21: Haakdoring (April 2001)

38 Chapter 2: Locality Description

Figure 2.22: Moorddrift (April 2001)

39 Chapter 2: Locality Description

2.3: References

ANON .(2003a) Lets Go -South Africa- Nylstroom (Modimolle) http://www.letsgo.com/SAF/08-NorthernProvince-21 ANON. (2003b). Routes Travel Info Portal: Mokopane. http://www.routes.co.za/lp/mokopane ANON (May 2003c). Routes Travel Info Portal: Mookgopong. http://www.routes.co.za/lp/mookgopong ANON (2003d). Explanation of the metallogenic map sheet 2428. http://www.geoscience.org.za/whatsnew/nylstroom.htm CHIEF DIRECTORATE, SURVEYS AND MAPPING. (2001a). 1:250 000 Topographic map of South Africa. 2428 Modimolle. 5th Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LAND USE. (2001b). 1:50 000 sheet of South Africa. 2428CB Nylstroom. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LAND USE. (2001c). 1:50 000 sheet of South Africa. 2428 CD Warmbaths. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LAND USE. (2001d). 1:50 000 sheet of South Africa. 2428 DA Naboomspruit 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LAND USE. (2001e). 1:50 000 sheet of South Africa. 2428 BD Haakdoring. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LAND USE. (2001f). 1:50 000 sheet of South Africa. 2428 DB Crecy. 3rd Edition. Government Printer, Mowbray. EHLERS, D.L. and DU TOIT, M.C. (1999). 1: 250 000 Metallogenic series map, 2428 Nylstroom. Council for Geoscience, Pretoria. GIBBS, R., WATSON, L., KOEKAMOER, M., SMOOK, N.P., ANDERSON, H.M. and DALLWITZ, M.J. (1991). Grasses of Southern Africa. Memoirs of the Botanical Survey of South Africa No.58. HASKINS, C. and KRUGER, J. (1997). Nylsvley Nature Reserve, South Africa, information sheet for the site designated to the List of wetlands of international importance especially as waterfowl habitat. Chief Directorate of Environmental Affairs, Polokwane. pp 32. HIGGINS, S.I. and ROGES, K.H. (1993). The Nyl River floodplain: situation report and preliminary statement of impacts of the proposed Olifants Spruit Dam. Center for Water in the Environment Report No. 03/93. University of the Witwatersrand, Johannesburg. MIDGELY, D.C., PITMAN, W.V. and MIDDLETON, B.J. (1994). Surface water resources of South Africa. Book of maps. Vol 1. WRC Report no. 289/1.2/94 TARBOTON, W.R. (1987). The Nyl River floodplain. Fauna & Flora 45.

Personal Communications

A. de Castro. De Castro and Brits, Expert Botanist Collaborator.

40 Chapter 3: Materials and Methods

Chapter 3: Materials and Methods

41 Chapter 3: Materials and Methods

Chapter 3 Materials and Methods.

3.1: Introduction

In order to undertake a baseline study of this nature one must design the study approach to address the aims and objectives set out. These factors must encompass as large a field as possible looking at both natural and anthropogenic components. The natural factors influencing a system of this nature are variable and not much can be done to eliminate them. These factors include natural decreases in the water quality due to the concentration effect caused by evaporation and lack of rain. It is however easier to assess the unnatural or anthropogenic influences in the system and to assess the effects that these factors have on the overall integrity of the system. It was thus decided to concentrate on the human impacts on the system with respect to pollution, and to develop a system for the assessment of system integrity using some of the biotic components found therein.

The sampling design of this study can be divided into 2 sections namely in situ field sampling and laboratory based bioassays and analyses.

Before the study was undertaken an extensive desktop study was conducted using the 1: 50 000 map series of South Africa (Chief Directorate Surveying and Landuse, 2001a-e) and the 1: 250 000 topographical map of South Africa (Chief Directorate Surveys and Mapping, 2001f). This study assessed the entire system and sampling sites were selected on the basis of where in the system they were located and the surrounding possible impacts. Accessibility was also taken into account. For the purpose of this study 18 localities were chosen throughout the Waterberg catchment. A reconnaissance trip to the area took place to assess the accessibility of the localities and the degree of permanence of water at the sites. This trip also involved making contact with all the interested and affected parties (landowners and the Department of Environmental Affairs and Tourism, Limpopo

42 Chapter 3: Materials and Methods

Province). The GPS coordinates were also recorded at each site using the Garmin 12 Map GPS Unit. Refer to Chapter 2 for a general description of the sampling localities.

The sampling strategy to be undertaken at each locality was selected. Table 3.1 indicates the localities and the samples that were collected.

Table 3.1: Table of localities and associated sampling strategy. Sites in tributaries are shaded in light grey Locality Water Sediment Aquatic Bacteria Toxicity Pesticides Invertebrates Testing KNO · · · · KIN · · · GNO · · · Dla Dla · · · · DPD · · · · · Abba · · · · Jasper · · · · · · STW · · · · Olifants · · · · · Spruit HSW · · · Nylsvley · · · · · · BSL · · · TO · · · TM · · · TS · · · Mosdene · · · · Haakdoring · · · · Moorddrift · · · · ·

The sampling can be divided into two categories namely the biotic (invertebrates) and abiotic (water and sediment) components. The functioning of the wetland system makes the analysis of both water and sediment imperative. The analysis of the water samples indicates if the filtration processes of the wetland are functioning properly and if the wetlands capacity to function well has been exceeded or not. This however gives an indication of what is happening in the system at the present moment. The analysis of the sediment indicates what has settled out during the filtration process and thus gives and indication of contamination that may have occurred in the periods between sample trips. This

43 Chapter 3: Materials and Methods thus gives an integrated spatial and temporal indication of the systems functioning and integrity. Figure 3.1 provides a brief overview of the different processes that the different samples were subjected to.

SAMPLES

BIOTIC ABIOTIC

FACTORS FACTORS

WATER SEDIMENT

AQUATIC INVERTEBRATES SEQUENTIAL PESTICIDES EXTRACTION

METALS NUTRIENTS TOXICITY AND MACRO- TESTING VARIABLES

Figure 3.1: Flow diagram of sampled components and analysis conducted

3.2: Practical applications 3.2.1 Field work Field sampling trips were conducted between March 2001 and March 2003. These trips took place on a quarterly basis and incorporated the sampling of water, sediment and aquatic invertebrates.

44 Chapter 3: Materials and Methods

Water samples were collected in 500ml plastic bottles. Three bottles were collected for different analyses. The water in one bottle was not treated and used for further analysis of macro variables and organic constituents. The water in the second bottle was treated with 5ml nitric acid to preserve the metal content in the water. Once the water samples were collected they were placed on ice until they could be frozen. Once frozen the water samples were returned to the laboratory for further analysis. A further 2l of water was taken in plastic sample bottles for toxicity testing back at the Rand Afrikaans University (RAU) Aquarium facility. These samples were also frozen until the testing could take place in the RAU environmental control facilities in the aquarium.

In situ water parameters were also recorded at each locality. These were taken using a variety of Eutech instruments. The water parameters recorded were O2 (concentration and percentage saturation), pH, total dissolved solids (TDS), conductivity and temperature. The oxygen concentrations (mg/l) and percentage saturation were determined using the Eutech Cyberscan DO 300 oxygen meter, the pH was determined using the Eutech Cyberscan pH 300 meter and the conductivity and TDS were determined using the Eutech Cyberscan con 410 conductivity and TDS Combination meter. All three meters contained built in thermometers. The meters were calibrated according to the instruction manuals with standards provided by Selectech. The pH meter underwent a 3 point calibration using the 4, 7 and 10 pH standards. The conductivity meter was calibrated to 1413 mS/cm standard and the TDS calibration standard was the 300 ppm standard. The oxygen meter was calibrated according to altitude and air saturation (van Vuren et al., 1994).

The sediment samples were taken from the upper 5cm of the substrate and placed in 350 ml plastic honey jars. The samples were then placed on ice until freezing could take place back at the base camp. Once frozen the samples were returned to the laboratory for further analysis.

45 Chapter 3: Materials and Methods

Aquatic invertebrates were sampled in the field using a modified SASS protocol. The methods used will be explained in Chapter 7 on the development of a wetland assessment protocol (Dickens and Graham, 2002).

Bacteriological samples were also collected in sterilised 250ml glass bottle with plastic lids. These samples were placed on ice and returned to the laboratory for immediate analysis.

3.2.2. Laboratory work.

In the laboratory the different samples were analysed for the required variables. Prior to analysis all glassware and plastic containers was washed according to the protocol prescribed by Giesy and Wiener (1977). The pre-washed containers were placed in a phosphate free soap bath for 24 hours containing a 2% concentration of Contrad soap (Merck). They were then removed, rinsed with distilled water and placed in a 2% HCl acid (Merck) bath for 24 hours. The glassware and plastic containers were then rinsed with distilled water and placed on drying racks and allowed to air dry. The clean containers were then placed on racks for storage until needed.

3.3: Water

3.3.1.1 Metal Analysis Water samples were analysed at Waterlab in Pretoria for metal concentrations, nutrients and inorganic constituents and bacterial counts. The acidified water samples were analysed for metals using Inductively Coupled Plasma Mass Spectrophotometry (ICP-MS). These samples from each sampling trip underwent a scan and were analysed for 70 elements.

46 Chapter 3: Materials and Methods

3.3.1.2 Nutrients and macro variables The non-acidified water samples collect were defrosted and then analysed using the standard methods prescribed by the American Public Health Association (APHA, 1998). The following macro variable levels were determined: chloride, sulphates, ortho-phosphates, nitrites, nitrates and fluorides. Table 3.2 indicates the macro variable and the APHA methods used in analysis.

Table 3.2: Table of APHA methods used for the determination of water macro variables. Macro Variable APHA Method Chlorides 4500-Cl B. Argentometric Method 2- Sulphates 4500-SO4 E. Turbidimetric Method Fluorides 4500-F- C. Ion-Selective Electrode Method Ortho-phosphates 4500-P D. Stannous Chloride Method - Nitrates 4500-NO3 H. Automated Hygrazine Reduction Method - Nitrites 4500-NO2 B. Colometric Method

3.3.1.3 Bacterial counts

Prior to sampling the bottles were sterilised. The clean glass bottles were sterilised in an autoclave with a 1% sodium thiosulphate solution. Heterotrophic plate counts, faecal coliform and total coliform counts were then carried out on the samples according to standardised methods (APHA, 1998). The different counts were done by culturing the bacteria present on the appropriate agar based medium in an incubator and then the developed colonies were counted and expressed as standard plate counts per ml.

3.3.1.4. Toxicity testing.

47 Chapter 3: Materials and Methods

The use of toxicity testing is important in the assessment of water throughout a system. The tests indicate the response of living material to the total effect of actual and potential disruptions in water, and thus complement the chemical analysis in monitoring harmful chemicals in water (Blaise et al., 1988). The chemical analysis of water indicates what constituents/contaminants the water is composed of and if they pose a potential problem in the water to aquatic organisms. It does not however give an indication to the cumulative effects of the constituents/ contaminants to organisms inhabiting the water. The use of toxicity testing can give an indication of these cumulative effects on the organisms placed in the water (Slabbert et al., 1998). It was thus decided to subject the water to acute toxicity testing using both the water flea, Daphnia pulex, and the guppy, Poecillia reticulata, as test organisms. Exotic test organisms were used so as to stick to standard protocols.

Toxicity tests were carried out in an environmental room at the RAU Aquarium. These tests were carried out according to the guideline set out by the Institute for Water Quality Studies (IWQS, 1998).

3.3.1.4a Daphnia culturing.

The D. pulex was cultured in a separate environmental room to the one in which the toxicity testing took place. The culture was kept at a temperature of approximately 20 °C. A photoperiod of 16 hours daylight was also maintained. Daphnia cultures were kept in 3l glass beakers in a reconstituted medium to promote culture growth. The culture was refreshed every 3 weeks to keep daphnid densities in the media down to promote reproduction.

The Daphnia-media was made up according to method 3001 001 of the Acute Toxicity Assessment Methods Manual (Truter, 1994). The medium used was

48 Chapter 3: Materials and Methods moderately hard, reconstituted water. It was made up by placing 1l of stock reagent into 19l of double distilled water and the medium was then aerated for 24 hours before use. New medium was made up weekly. The stock reagent was prepared by dissolving 2.59g NaHCO3, 1.2g CaSO4.2H2O, 0.08g KCl and 2.46g

MgSO4.7H2O in 1l of deionised water in a volumetric flask. The medium was then aerated and 2500 ml medium then added to a 3000ml glass beaker and 5 ml of food was added before the transfer of D. pulex took place.

The feeding of the Daphnid culture is very important and fresh food was made up weekly. The Daphnia food is a suspension of trout pellets, alfalfa and brewers yeast. Food was made up as follows: 6.3g of trout pellets, 2.6g of dried yeast and 0.5g of alfalfa was added to 1l of warm deionised water. The food was left to stand for approximately 15 minutes to allow the pellets to soften and then placed on a magnetic stirrer for about 2 hours. This allowed the particles to go into suspension. The food was then placed in the fridge over night and the following morning the top 500ml was poured off into a 500ml volumetric flask leaving solid particles behind in the preparation beaker. The food was kept in the fridge. The daphnids were fed three times a week on Mondays, Tuesdays and Fridays. The food was left to reach room temperature before it was introduced into the cultures. 5 ml of food was pipetted into each culture beaker. 3.3.1.4b Guppy culture.

Guppies were bought from a fish farm near Polokwane (Pietersburg) and held in the aquarium for less than a week before being used. The guppies used in the tests were between 1 and 2 weeks old.

3.3.1.4cTest Media

The tests were carried out according to the guidelines set out by the IWQS for

49 Chapter 3: Materials and Methods both guppies and D. pulex (IWQS, 1998). Both diluents used in the tests were moderately hard reconstituted water, where the daphnia culture medium was used for the daphnid tests and guppy medium was used for the guppy tests. The preparation of the Daphnia medium preparation was described in Section 3.3.1.4a.

3.3.1.4d Guppy Test Medium.

The preparation of the guppy medium was done according to method 3001 002 in the Acute Toxicity test methods manual (IWQS, 1998). Four stock solutions of reconstituted moderately hard water were prepared using milli-Q water. The four stock solutions were prepared in 1l volumetric flasks and contained: 11.76g

CaCl2.2H2O, 4.93g MgSO4.7H2O, 2.59g NaHCO3 and 0.23g KCl. An aliquot (250 ml) of each of these four stock solutions was then added to a container containing 19l of deionised water and aerated over night to allow stabilisation of the medium and for the medium to attain the required room temperature of 21 ºC.

3.3.1.4e Toxicity Test Protocol.

Acute screening toxicity tests were performed on all the water samples collected at the different localities. These tests were carried out every three months for a period of a year as part of the water monitoring programme. For the daphnids the 48-hour acute static screening tests were used and for the guppy the 96 hour acute static screening tests were performed. Rand (1995) describes a screening test as a short test usually in the early stages of a programme to establish the potential of an effluent or chemical to elicit an adverse effect. All tests were carried out in duplicate for confirmation of mortality rates (Truter, 1994).

The effluent or stream water tested was defrosted and left to reach room temperature before testing took place. Daphnid tests were carried out in 40ml glass beakers and guppy tests in 600ml glass beakers. Tests were conducted at

50 Chapter 3: Materials and Methods both the 100 percent and 50 percent dilution levels. All dilutions were made with reconstituted water. Medium controls were run for both tests to monitor the medium toxicity. As these were acute tests the feeding of organisms was not necessary during the test period.

In the case of the daphnid tests 40ml of stream water was used in the 100 percent test and for the 50 percent test 20ml stream water and 20ml of medium were added to 40ml glass beakers. The water quality variables (i.e. O2 saturation, O2 concentration, pH, conductivity and total dissolved solids) were then recorded using the Eutech range of water quality meters before the D. pulex were added. Five individuals, which were approximately one day old were added to each beaker. The water quality was monitored every day and mortalities noted. The cumulative mortalities, after the completion of the tests, were then analysed using the Spearman Karber method and the 50% mortality concentration (LC50) was determined (Truter, 1994).

In the case of the guppy test 400ml of stream water was used in the 100 percent test. For the 50 percent test 200ml of stream water was added to 200ml of guppy medium. Water quality parameters were recorded as described for the D.pulex test. Five guppies (week old) were placed in each beaker and their mortalities were recorded daily. The mortalities were also analysed using the Spearman Karber method to determine the LC50.

3.4: Sediments.

3.4.1 Sequential extraction In the laboratory the sediment samples underwent a process of sequential extraction. It was decided to use a five fraction extraction, which identifies the non-residual metal concentrations among the three basic operationally- defined host fractions (Ngiam and Lim, 2000). The process followed was modified from the process set out by Tessier et al. (1979). The process involves subjecting the

51 Chapter 3: Materials and Methods sediment samples to chemicals of decreasing pH and increasing oxidising strength, to remove the operationally defined host fractions corresponding to the exchangeable, carbonate, reducible and organic/sulphide phases (Ngiam and Lim, 2000). Sediment samples were dried in an oven at 60ºC. Approximately 1g of dry sample was placed in a 50ml nalgene polyethylene centrifuge tube before it underwent extraction. Figure 3.2 gives a brief outline of the process followed during the extraction process.

52 Chapter 3: Materials and Methods

SAMPLE 1g

1M MgCl, pH = 7

SUPERNATANT FRACTION 1

RESIDUE

1M NaOHC/HOAC. pH =5.0

SUPERNATANT FRACTION 2

RESIDUE

0.04M NH2OH.HCl in 25% (v/v)HOAC

SUPERNATANT FRACTION 3

RESIDUE

30% H2O2. pH =2 with HNO3

SUPERNATANT FRACTION 4

RESIDUE ACID ATTACK FRACTION 5 HF + HClO + HNO 4 3

Figure 3.2: Flow diagram for Tessier sequential extraction (Coetzee, 1993)

53 Chapter 3: Materials and Methods

The five fractions removed were: 1: The exchangeable fraction, 2: The fraction bound to carbonates, 3: The fraction bound to iron and manganese oxides, 4: The fraction bound to organic matter, 5: The residual or inert fraction.

3.4.1.1. Extraction process.

Once in the centrifuge tube the 1g of sediment was subjected to different digestive processes. For first fraction was subjected to a 1M magnesium chloride solution. This was made up by dissolving 23.793g of magnesium chloride (Merck) in 250ml of deionised water. The pH was then adjusted to 7 using NaOH and 8ml was then added to each sample and left at room temperature for one hour. The samples were then centrifuged at 3000 rpm for 30 minutes before the supernatant was removed and placed in amber glass bottles. The extraction was then diluted to 50ml.

The residue then underwent further extraction with 8ml of a 1M sodium acetate/acetic acid buffer to pH 5 for five hours at room temperature. The sodium acetate/acetic acid buffer was made up by dissolving 20.5g of sodium acetate (BDH Lab Reagents) in 250ml deionised water, buffered to pH 5 with acetic acid (Associate Chemical Enterprises). The samples were then centrifuged at 3000 rpm for 30 minutes and the supernatant was removed and placed in amber glass bottles and made up to a volume of 50ml

The residue then underwent the 3rd extraction under mild reducing conditions. 20ml of a 0.4M hydroxyl amine hydrochloride in 25%(v/v) acetic acid was added to the residue and incubated in a warm bath for 6 hours at 96 ± 3ºC. The hydroxyl amine hydrochloride solution was prepared by dissolving 6.949g of

54 Chapter 3: Materials and Methods hydroxyl ammonium chloride (Saarchem) in 25%(v/v) acetic acid to a volume of 250ml. The reduced samples were then centrifuged at 3000 rpm for 30 minutes and the supernatant was placed in amber glass bottles and made up to a volume of 50ml.

The residue underwent the 4th reduction. The reducing agent in this fraction was a nitric acid/ hydrogen peroxide solution. 3ml of a 0.02M nitric acid (Saarchem) and 5ml 30% (v/v) hydrogen peroxide (Saarchem) were added to each sample. The mixture was then heated in a warm bath at 85 ± 2 °C for 3 hours. Once cool, 5ml of 3.2 M ammonium acetate (26.6656g of ammonium acetate in 100ml 20% (v/v) nitric acid ) was added to the samples and left to stand for an hour before the samples were centrifuged at 3000 rpm for 30 min. The supernatant was then removed and placed in amber glass bottles and made up to a volume of 50ml.

The 5th fraction was then extracted from the residue. This was achieved by digesting the residue with a 5:1 mixture of hydrofluoric acid (Merck) and perchloric acid (Saarchem). The samples were placed in a warm bath at 96 ±3°C for 3 hours and then left to cool. They were centrifuged at 3000rpm for 30 minutes and the extract removed and placed in plastic falcon tubes. The extract was made up to a volume of 50ml.

All samples were then analysed for metal content using standard ICP-MS techniques.

3.4.2 Organic toxicants

Due to the various farming activities in the area (Chapter 2), the decision was made to analyse sediment samples to indicate what pesticides are present in the system, with an eye on further analysis of potential problem toxicants in tissues of organisms found in the system.

55 Chapter 3: Materials and Methods

Sediment samples from five localities along the system were analysed for the presence of five main groups of organic compounds. These localities were analysed under both high and low flow conditions during 2002. Table 3.3 indicates the five main groups analysed and the derivatives in these groups. A total of 55 derivatives were scanned.

Table 3.3: Pesticide derivatives analysed in sediments to determine pesticide concentrations in sediment.

Carbamates Organochlorine Organophosphorus Pyrethroids PCB’s pesticides pesticides & Triazines

Aldicarb Alpha-BHC Dichlorvos Lambda - 2,4-Dichlorobiphenyl Cyhalothrin (PCB-8) Carbofuran Beta-BHC Phosdrin Permethrin 2,3,3- Trichlorobiphenyl (PCB-20) Carbaryl Gamma-BHC Diazinon Cypermethrin 2,4,4- (Lindane) trichlorobiphenyl (PCB-28) Methomyl Delta -BHC Chlorpyrifos-methyl Deltamethrin 2,2’,5,5’- tetrachlorobiphenyl (PCB-52) Oxamyl Heptachlor Chlorpyrifos- ethyl Esfenvalerate 2,2’,4,5,5’- pentachlorobiphenyl (PCB-101) 3-Hydroxycarbofuran Aldrin Malathion 2,3’,4,4’,5- pentachlorobiphenyl (118) Aldicarbofuran Epoxide Bromophos-methyl 2,2’,3,4,4’,5’ hexachlorobiphenyl (PCB-138) Aldicarbsulfoxide Endosulfan-I Parathion 2,2’,4,4’,5,5’- hexachlorobiphenyl (PCB-153) Methiocarb 4,4-DDE Carbophenothion 2,2’,3’,4,4’,5,5’- heptachlorobiphenyl (PCB-180) Propoxur Dieldrin Atrazine Endrin Simazine Endosulfan-II Terbuthylazine DDD Clorothalonil Endrin aldahyde 4,4-DDT Endosulfan sulphate Endrin ketone metoxychlor

56 Chapter 3: Materials and Methods

The sediment samples were analysed at the SANAS accredited laboratory, Testing and Conformity Services (Pty) Ltd, an affiliate of the SABS. The single determination was carried out using test method AP0 27 A: Method for the determination of OC and OP pesticides, Triazines, Pyrethroids, PCB’s and Carbamates in sediment.

3.5: Statistical Methods.

All data underwent statistical analysis with one of the following statistical analysis computer packages: Microsoft Excel, Graphpad Prism, PRIMER 5 and SPSS version 11. General statistics used include the calculation of means, maximum values, minimum values, standard deviations, percentiles and significant differences (P<0.05).

The ordination method, Principal Component Analysis (PCA), was used to elucidate dissimilarities between sites and flow periods in the water quality data. The PCA technique is widely applied to ecological studies and provides a global interpretation of environmental variables: physical, chemical, physiographical, morphometrical or climatological. PCA allows for the extraction of the general directions of variation of environmental variables. These complex gradients relate to the geomorphological processes of fluvial systems, influence of human activities and mineralisation processes of autochthonous and allochthonous energy sources.

Water quality data from the selected sites were subjected to PCA. All water quality values, with the exception of those of pH, were transformed (Y = Log(X+1)). Principal component analysis was carried out on the correlation matrix of the variables, being final components unrotated. The scaling method used, required that the angles between the lines (chemical variables) be interpreted as a measure of their correlation as depicted in Table 3.4. The distance between the sampling sites is a measure of their similarity (based on

57 Chapter 3: Materials and Methods standardised Euclidean distance).

The first axis of the plot (PC1) indicates the variability between the different sites using the variables causing the most variability. The second axis (PC2) indicates the variability using variables that don’t figure as strongly on the first axis. The difference in plot position indicates that the sites situated close together are similar in nature (Clark and Warwick, 1994, Clark and Gorley, 1994).

Table 3.4 Interpretation of angles between the lines in correlation bi-plots of chemical variables for PCA for the water quality data. ANGLE (qº) CORRELATION

0

Primer software was used to superimpose the biotic index scores on the complex multivariate water quality PCA ordination. The magnitude of the contribution of the particular biotic index value is represented as symbols of differing size.

58 Chapter 3: Materials and Methods

3.6: References

APHA (1998). Standard Methods for the Examination of Water and Wastewater, 20th Edition. United Book Press, Baltimore, Maryland. pp 4-67 – 4-179. BLAISE ,C., SERGY, G., WELLS, P., BERMINGHAM, N and COILLIE, R.V. (1988). Biological testing - development, application, and trends in Canadian environmental protection laboratories. Toxicity Assessment 3: 385-406. CHIEF DIRECTORATE, SURVEYS AND LANDUSE. (2001a). 1:50 000 sheet of South Africa. 2428CB Nylstroom. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LANDUSE. (2001b). 1:50 000 sheet of South Africa. 2428 CD Warmbaths. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LANDUSE. (2001c). 1:50 000 sheet of South Africa. 2428 DA Naboomspruit 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LANDUSE. (2001d). 1:50 000 sheet of South Africa. 2428 BD Haakdoring. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND LANDUSE. (2001e). 1:50 000 sheet of South Africa. 2428 DB Crecy. 3rd Edition. Government Printer, Mowbray. CHIEF DIRECTORATE, SURVEYS AND MAPPING. (2001f). 1:250 000 Topographic map of South Africa. 2428 Modimolle. 5th Edition. Government Printer, Mowbray. CLARKE, K.R. and GORLEY, R.N. (1994). PRIMER v5: user Manual/Tutorial. Plymouth Marine Laboratory, Natural Environment Research Council, UK. pp 91. CLARKE, K.R. and WARWICK, R.M. (1994). Change in Marine Communities: an approach to statistical analysis and interpretation. Plymouth Marine Laboratory, Natural Environment Research Council, UK. pp 144. COETZEE, P.P. (1993). Determination and speciation of heavy metals in sediments of the Hartebeespoort Dam by sequential chemical extraction. Water SA 19 (4): 291-301. DICKENS, D.W.S. and GRAHAM, P.M. (2002). The South African Scoring System (SASS) version 5 Rapid Bioassessment Method for Rivers. African Journal of Aquatic Science 27: 1-10. GIESY, J.P. and WIENER, J.G. (1977). Frequency distribution of trace metal concentrations in five freshwater fishes. Transactions of the American Fisheries Society 106: 393-403. IWQS (1998). Methods Manual: Method 3001 002 acute toxicity assessment using Poecillia reticulata. pp 14 NGIAM, L. and LIM, P. (2001). Speciation patterns of heavy metals in tropical estuarine anoxic and oxidized sediments by different sequential extraction schemes. The Science of the Total Environment 275 (1-3): 53-61. RAND, G.M., WELLS, P.G. and McCARTY, L.S. (1995). Introduction to aquatic toxicology. In: G.M. Rand (ed.) Fundamentals of aquatic toxicology: effects, environmental fate and risk assessment. Taylor and Francis, United States. pp 3-66. SLABBERT, J.L., OOSTHUIZEN, J., VENTER, E.A., HILL, E., DU PREEZ, M.

59 Chapter 3: Materials and Methods

and PRETORIUS, P.J. (1998). Development of guidelines for toxicity bioassaying of drinking and environmental waters in South Africa. Water Research Commission Report Number 358/1/98. Water Research Commission, Pretoria. pp 101. TESSIER,A. CAMPBELL, P.G.C. and BISON, M. (1979). Sequential extraction procedure for speciation of particulate trace metals. Analytical Chemistry 51: 844-851. TRUTER, E. 1994. Methods for estimating chronic toxicity of a chemical or water sample to the Cladoceran Daphnia pulex. IWQS Report number N0000/00/OEQ/1394. VAN VUREN, J.H.J., DU PREEZ, H.H. and DEACON, A.R. (1994). Effects of pollutants on the physiology of fish in the Olifants River (Eastern Transvaal). Water Research Commission Report Number 350/1/94. Water Research Commission, Pretoria. pp 214.

60 Chapter 4: Water Quality Results and Discussion

CHAPTER 4: Water quality: Results and Discussion

61 Chapter 4: Water Quality Results and Discussion

CHAPTER 4: Water quality: Results and Discussion.

The analysis of the water in the wetland is vitally important as it forms the life’s blood of the system. It provides habitat for most of the organisms involved in the system, both terrestrial and aquatic. Many of the invertebrates in the systems depend on the hydrosphere for all or part of their life cycle. The chemical characteristics of the water indicate the level of contamination in the system. This is important as it provides vital information on the suitability of the systems’ water for both animal and human consumption and the provision of a suitable living medium for aquatic organisms.

The water in the system was analysed for the following chemical and physical parameters: inorganic constituents, organic constituents, raw water toxicity, bacterial counts and total metal concentrations. These analyses form a suite of tests that are carried out on the water to provide a holistic indication of the levels of contamination and the suitability of the water for the many users involved.

4.1: Historical data

Reference conditions for the Nyl River system were determined using the method of Bath et al., (1999a). This method is for the determination of reference conditions for water quality variables in the Reserve determination process. This method of reference condition determination has been developed to account for 1) the influence of point and diffuse sources, 2) the lack of consistent spatial and temporal data, and 3) natural changes in quality along the length of a river (Bath et al., 1999a). Historical data were obtained from the Water Quality on Disc database (DWAF, 1999). The sites selected comprised of existing gauging stations from the only available historical database. The sites covered the main river and the more important tributaries. The data used was selected between the dates 1972 to September 1999. Data from gauging stations at 7 localities were used to obtain a representative reference condition or desired state for the Nyl

62 Chapter 4: Water Quality Results and Discussion

River system. The seven localities used are listed in Table 4.1 together with their gauging station reference numbers. These stations differ from the sites used in the rest of the study but provide useful historical data.

Table 4.1: List of gauging stations used to determine reference conditions and number of samples used. Station Name Station Total Sample Sample number Sample size size size period period one two (after (before onset of trend) trend) Klein Nyl at A6H006Q01 178 48 130 Nylstroom (KNN) Donkerpoort Dam A6r003Q01 63 31 32 (DPD) Hessie se Water A6H019Q01 113 51 62 (HSW) Olifants Spruit A6H012Q01 221 76 145 Nylsvley at Deelkraal A6H002Q01 47 9 38 Bad se Loop (BSL) A6H010Q01 214 50 164 Tobias Spruit A6H023Q01 25 19 6

From the figures obtained (Figures 4.1-4.21) two time periods were determined. These time periods were determined visually from the graphs judging from the visible onset of an increase in the trend of the particular concentration/level. These periods were generally from February 1972 to January 1984 and from February 1984 to September 1999.

These reference conditions cannot be used in a full reserve determination as they are calculated for a single period and not monthly as one would conduct for a full reserve determination. They are however suitable to act as a guideline for comparisons of sampled data and to denote changes in the overall status of the system.

The trend lines obtained indicate that the water quality of the system has

63 Chapter 4: Water Quality Results and Discussion deteriorated over the last 20 years. This is true for most of the variables at most of the sites. There are however a few exceptions. These trend lines are indicated in Figures 4.1 to 4.21. The positive trend indicates an increase in the level/concentration of the specific variable, where a negative trend indicates a decrease in the variable level/concentration. These temporal changes can be caused by a number of factors.

64 Chapter 4: Water Quality Results and Discussion

9

8

7

6

5 pH 4

3

2

1

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 pH Poly. (pH)

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5

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 Date Conductivity Poly. (Conductivity)

120

100

80

60

40 Total Dissolved Solids (mg/l)

20

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 TDS Poly. (TDS)

Figure 4.1: Graphical representation of historical data on a temporal scale. pH, conductivity and TDS at Klein Nyl River at Nylstroom/Modimolle (KNN). A polygonal trend line is superimposed on the data to indicate any trends present.

65 Chapter 4: Water Quality Results and Discussion

25

20

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10 Chloride concentration (mg/l)

5

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 Chloride Poly. (Chloride)

14

12

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6

4 Sulphate concentration (mg/l)

2

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 Sulphates Poly. (Sulphates)

0.14

0.12

0.1

0.08

0.06

0.04 Nitrite and Nitrate concentration (mg/l) 0.02

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 Nitrites and Nitrates Poly. (Nitrites and Nitrates)

Figure 4.2: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Klein Nyl River at Nylstroom/Modimolle (KNN). A polygonal trend line is superimposed on the data to indicate any trends present.

66 Chapter 4: Water Quality Results and Discussion

0.14

0.12

0.1

0.08

0.06

0.04 Orthophosphate concentration (mg/l)

0.02

0

30/11/198318/04/198406/03/198510/04/198508/01/198712/02/198719/03/198726/11/198721/01/198825/02/198831/03/198812/05/198816/06/198821/07/198825/08/198827/10/198823/02/198906/04/198917/05/198922/06/198920/07/198931/08/198929/03/199024/05/199028/06/199024/01/199128/02/199111/04/199116/05/199113/06/199106/08/199109/09/1991 Orthophosphate Poly. (Orthophosphate)

Figure 4.3: Graphical representation of historical data on a temporal scale. Orthophosphate at Klein Nyl River at Nylstroom/Modimolle (KNN). A polygonal trend line is superimposed on the data to indicate any trends present.

67 Chapter 4: Water Quality Results and Discussion

9

8

7

6

5 pH 4

3

2

1

0

06/04/197606/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 pH Poly. (pH)

14

12

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6 Conductivity (ms/m)

4

2

0

06/04/197606/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 conductivity Poly. (conductivity)

120

100

80

60

40 Total Dissolved Solids (mg/l)

20

0

06/04/197606/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 TDS Poly. (TDS)

Figure 4.4: Graphical representation of historical data on a temporal scale. pH, Conductivity and TDS at Donkerpoort Dam (DPD). A polygonal trend line is superimposed on the data to indicate any trends present.

68 Chapter 4: Water Quality Results and Discussion

14

12

10

8

6

4 Chloride concentration (mg/l)

2

0

06/04/197606/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 Chloride Poly. (Chloride)

18

16

14

12

10

8

6 Sulphate concentration (mg/l) 4

2

0

06/04/197606/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 Sulphate Poly. (Sulphate)

0.7

0.6

0.5

0.4

0.3

0.2

Nitrite-Nitrate concentration (mg/l) 0.1

0

06/04/1976-0.106/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 Nitrite-Nitrate Poly. (Nitrite-Nitrate)

Figure 4.5: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Donkerpoort Dam (DPD). A polygonal trend line is superimposed on the data to indicate any trends present.

69 Chapter 4: Water Quality Results and Discussion

0.06

0.05

0.04

0.03

0.02 Orthophosphate concentration (mg/l) 0.01

0

06/04/197606/04/197606/04/197606/05/198008/07/198017/09/198003/12/198004/03/198127/05/198114/07/198108/09/198124/11/198123/02/198220/04/198215/06/198208/09/198222/12/198228/09/198301/02/198428/03/198429/05/198428/08/198430/10/198429/01/198526/03/198528/05/198501/08/198501/10/198528/01/198625/03/1986 Orthophosphate Poly. (Orthophosphate)

Figure 4.6: Graphical representation of historical data on a temporal scale. Orthophosphate at Donkerpoort Dam (DPD). A polygonal trend line is superimposed on the data to indicate any trends present.

70 Chapter 4: Water Quality Results and Discussion

9

8

7

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5 pH 4

3

2

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0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 pH Poly. (pH)

16

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6 Conductivity (ms/m)

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2

0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 Conductivity Poly. (Conductivity)

100

90

80

70

60

50

40

30 Total Dissolved Solids (mg/l)

20

10

0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 TDS Poly. (TDS)

Figure 4.7: Graphical representation of historical data on a temporal scale. pH, Conductivity and TDS at Hessie se Water (HSW). A polygonal trend line is superimposed on the data to indicate any trends present.

71 Chapter 4: Water Quality Results and Discussion

12

10

8

6

4 Chloride concentration (mg/l)

2

0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 Chloride Poly. (Chloride)

14

12

10

8

6

4 Sulphate concentration (mg/l)

2

0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 Sulphate Poly. (Sulphate)

0.3

0.25

0.2

0.15

0.1 Nitite-Nitrate concentration (mg/l)

0.05

0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 Nitrite-Nitrate Poly. (Nitrite-Nitrate)

Figure 4.8: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Hessie se Water (HSW). A polygonal trend line is superimposed on the data to indicate any trends present.

72 Chapter 4: Water Quality Results and Discussion

0.8

0.7

0.6

0.5

0.4

0.3

0.2 Orthophosphate concentration (mg/l)

0.1

0 05/12/1977 09/01/1978 13/02/1978 03/04/1978 15/05/1978 19/06/1978 24/07/1978 28/08/1978 04/10/1978 08/11/1978 20/12/1978 02/05/1979 06/06/1979 14/11/1979 19/12/1979 30/01/1980 06/03/1980 09/04/1980 14/05/1980 18/06/1980 23/07/1980 27/08/1980 01/10/1980 05/11/1980 24/12/1980 28/01/1981 04/03/1981 12/08/1981 19/05/1982 22/12/1982 29/10/1997 11/03/1998 29/07/1998 28/10/1998 03/02/1999 23/06/1999 Orthophosphate Poly. (Orthophosphate)

Figure 4.9: Graphical representation of historical data on a temporal scale. Orthophosphate at Hessie se Water (HSW). A polygonal trend line is superimposed on the data to indicate any trends present.

73 Chapter 4: Water Quality Results and Discussion

10

9

8

7

6

5 pH

4

3

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0 14/02/1972 08/03/1976 24/05/1976 09/08/1976 22/11/1976 14/02/1977 09/05/1977 01/08/1977 18/10/1977 02/01/1978 10/04/1978 26/06/1978 20/09/1978 06/12/1978 16/05/1979 22/08/1979 28/11/1979 20/02/1980 14/05/1980 30/07/1980 22/10/1980 04/02/1981 12/08/1981 19/01/1983 28/11/1984 24/12/1985 26/02/1987 25/02/1988 26/01/1989 28/12/1989 25/04/1991 01/03/1993 27/02/1995 22/04/1996 12/06/1997 13/05/1998 15/04/1999 pH Poly. (pH)

20

18

16

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8 Conductivity (ms/m) 6

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0 14/02/1972 08/03/1976 24/05/1976 09/08/1976 22/11/1976 14/02/1977 09/05/1977 01/08/1977 18/10/1977 02/01/1978 10/04/1978 26/06/1978 20/09/1978 06/12/1978 16/05/1979 22/08/1979 28/11/1979 20/02/1980 14/05/1980 30/07/1980 22/10/1980 04/02/1981 12/08/1981 19/01/1983 28/11/1984 24/12/1985 26/02/1987 25/02/1988 26/01/1989 28/12/1989 25/04/1991 01/03/1993 27/02/1995 22/04/1996 12/06/1997 13/05/1998 15/04/1999 Conductivity Poly. (Conductivity)

160

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120

100

80

60

Total Dissolved Solids (mg/l) 40

20

0

14/02/197215/03/197607/06/197606/09/197627/12/197628/03/197727/06/197719/09/197712/12/197713/03/197819/06/197820/09/197813/12/197806/06/197919/09/197902/01/198026/03/198025/06/198024/09/198014/01/198124/06/198108/09/198228/11/198429/01/198630/04/198702/06/198801/06/198928/06/199030/10/199128/03/199429/01/199625/03/199716/04/199815/04/1999 TDS Poly. (TDS)

Figure 4.10: Graphical representation of historical data on a temporal scale. pH, Conductivity and TDS at Olifants Spruit. A polygonal trend line is superimposed on the data to indicate any trends present.

74 Chapter 4: Water Quality Results and Discussion

35

30

25

20

15

10 Chloride concentration (mg/l)

5

0 14/02/1972 08/03/1976 24/05/1976 09/08/1976 22/11/1976 14/02/1977 09/05/1977 01/08/1977 18/10/1977 02/01/1978 10/04/1978 26/06/1978 20/09/1978 06/12/1978 16/05/1979 22/08/1979 28/11/1979 20/02/1980 14/05/1980 30/07/1980 22/10/1980 04/02/1981 12/08/1981 19/01/1983 28/11/1984 24/12/1985 26/02/1987 25/02/1988 26/01/1989 28/12/1989 25/04/1991 01/03/1993 27/02/1995 22/04/1996 12/06/1997 13/05/1998 15/04/1999 Chloride Poly. (Chloride)

14

12

10

8

6

4 Sulphate concentration (mg/l)

2

0 14/02/1972 08/03/1976 24/05/1976 09/08/1976 22/11/1976 14/02/1977 09/05/1977 01/08/1977 18/10/1977 02/01/1978 10/04/1978 26/06/1978 20/09/1978 06/12/1978 16/05/1979 22/08/1979 28/11/1979 20/02/1980 14/05/1980 30/07/1980 22/10/1980 04/02/1981 12/08/1981 19/01/1983 28/11/1984 24/12/1985 26/02/1987 25/02/1988 26/01/1989 28/12/1989 25/04/1991 01/03/1993 27/02/1995 22/04/1996 12/06/1997 13/05/1998 15/04/1999 Sulphate Poly. (Sulphate)

0.4

0.35

0.3

0.25

0.2

0.15

0.1 Nitrite and Nitrate concentration (mg/l)

0.05

0

14/02/197215/03/197607/06/197606/09/197627/12/197628/03/197727/06/197719/09/197712/12/197713/03/197819/06/197820/09/197813/12/197806/06/197919/09/197902/01/198026/03/198025/06/198024/09/198014/01/198124/06/198108/09/198228/11/198429/01/198630/04/198702/06/198801/06/198928/06/199030/10/199128/03/199429/01/199625/03/199716/04/199815/04/1999 Nitrite-Nitrate Poly. (Nitrite-Nitrate)

Figure 4.11: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Olifants Spruit. A polygonal trend line is superimposed on the data to indicate any trends present.

75 Chapter 4: Water Quality Results and Discussion

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2 Orthophosphate concentration (mg/l)

0.1

0

14/02/197215/03/197607/06/197606/09/197627/12/197628/03/197727/06/197719/09/197712/12/197713/03/197819/06/197820/09/197813/12/197806/06/197919/09/197902/01/198026/03/198025/06/198024/09/198014/01/198124/06/198108/09/198228/11/198429/01/198630/04/198702/06/198801/06/198928/06/199030/10/199128/03/199429/01/199625/03/199716/04/199815/04/1999 Orthophosphate Poly. (Orthophosphate)

Figure 4.12: Graphical representation of historical data on a temporal scale. Orthophosphate at Olifants Spruit. A polygonal trend line is superimposed on the data to indicate any trends present.

76 Chapter 4: Water Quality Results and Discussion

12

10

8

6 pH

4

2

0 14/02/1972 02/02/1976 15/03/1976 27/04/1976 07/06/1976 20/07/1976 30/08/1976 11/10/1976 22/11/1976 03/01/1977 14/02/1977 28/03/1977 16/05/1977 27/06/1977 22/08/1977 03/10/1977 14/11/1977 09/01/1978 10/04/1978 07/11/1979 11/06/1980 04/03/1981 09/09/1981 13/04/1983 30/03/1988 28/09/1988 26/04/1989 26/04/1990 24/04/1991 23/12/1991 28/03/1994 13/11/1996 05/05/1997 29/10/1997 15/04/1998 09/12/1998 07/07/1999 pH Poly. (pH) 30

25

20

15

Conductivity (ms/m) 10

5

0 14/02/1972 02/02/1976 15/03/1976 27/04/1976 07/06/1976 20/07/1976 30/08/1976 11/10/1976 22/11/1976 03/01/1977 14/02/1977 28/03/1977 16/05/1977 27/06/1977 22/08/1977 03/10/1977 14/11/1977 09/01/1978 10/04/1978 07/11/1979 11/06/1980 04/03/1981 09/09/1981 13/04/1983 30/03/1988 28/09/1988 26/04/1989 26/04/1990 24/04/1991 23/12/1991 28/03/1994 13/11/1996 05/05/1997 29/10/1997 15/04/1998 09/12/1998 07/07/1999 Conductivity Poly. (Conductivity)

250

200

150

100 Total Dissolved Solids (mg/l)

50

0

14/02/197209/02/197629/03/197617/05/197605/07/197623/08/197611/10/197629/11/197617/01/197707/03/197702/05/197720/06/197722/08/197711/10/197728/11/197728/02/197807/02/197907/05/198004/03/198125/11/198129/01/198729/06/198822/02/198929/11/198924/04/199128/01/199225/03/199612/02/199727/08/199710/03/199809/12/199804/08/1999 TDS Poly. (TDS)

Figure 4.13: Graphical representation of historical data on a temporal scale. pH, Conductivity and TDS at Nylsvley at Deelkraal. A polygonal trend line is superimposed on the data to indicate any trends present.

77 Chapter 4: Water Quality Results and Discussion

14

12

10

8

6

4 Chloride concentration (mg/l)

2

0 14/02/1972 02/02/1976 15/03/1976 27/04/1976 07/06/1976 20/07/1976 30/08/1976 11/10/1976 22/11/1976 03/01/1977 14/02/1977 28/03/1977 16/05/1977 27/06/1977 22/08/1977 03/10/1977 14/11/1977 09/01/1978 10/04/1978 07/11/1979 11/06/1980 04/03/1981 09/09/1981 13/04/1983 30/03/1988 28/09/1988 26/04/1989 26/04/1990 24/04/1991 23/12/1991 28/03/1994 13/11/1996 05/05/1997 29/10/1997 15/04/1998 09/12/1998 07/07/1999 Chloride Poly. (Chloride) 18

16

14

12

10

8

6 Sulphate concentration (mg/l) 4

2

0 14/02/1972 02/02/1976 15/03/1976 27/04/1976 07/06/1976 20/07/1976 30/08/1976 11/10/1976 22/11/1976 03/01/1977 14/02/1977 28/03/1977 16/05/1977 27/06/1977 22/08/1977 03/10/1977 14/11/1977 09/01/1978 10/04/1978 07/11/1979 11/06/1980 04/03/1981 09/09/1981 13/04/1983 30/03/1988 28/09/1988 26/04/1989 26/04/1990 24/04/1991 23/12/1991 28/03/1994 13/11/1996 05/05/1997 29/10/1997 15/04/1998 09/12/1998 07/07/1999 Sulphates Poly. (Sulphates)

0.8

0.7

0.6

0.5

0.4

0.3

0.2 Nitrite-Nitrate concentration (mg/l)

0.1

0 14/02/1972 02/02/1976 15/03/1976 27/04/1976 07/06/1976 20/07/1976 30/08/1976 11/10/1976 22/11/1976 03/01/1977 14/02/1977 28/03/1977 16/05/1977 27/06/1977 22/08/1977 03/10/1977 14/11/1977 09/01/1978 10/04/1978 07/11/1979 11/06/1980 04/03/1981 09/09/1981 13/04/1983 30/03/1988 28/09/1988 26/04/1989 26/04/1990 24/04/1991 23/12/1991 28/03/1994 13/11/1996 05/05/1997 29/10/1997 15/04/1998 09/12/1998 07/07/1999 Nitrite-Nitrate Poly. (Nitrite-Nitrate)

Figure 4.14: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Nylsvley at Deelkraal. A polygonal trend line is superimposed on the data to indicate any trends present.

78 Chapter 4: Water Quality Results and Discussion

0.25

0.2

0.15

0.1

Orthophosphate concentration (mg/l) 0.05

0

14/02/197209/02/197629/03/197617/05/197605/07/197623/08/197611/10/197629/11/197617/01/197707/03/197702/05/197720/06/197722/08/197711/10/197728/11/197728/02/197807/02/197907/05/198004/03/198125/11/198129/01/198729/06/198822/02/198929/11/198924/04/199128/01/199225/03/199612/02/199727/08/199710/03/199809/12/199804/08/1999 Orthophosphate Poly. (Orthophosphate)

Figure 4.15: Graphical representation of historical data on a temporal scale. Orthophosphate at Nylsvley at Deelkraal. A polygonal trend line is superimposed on the data to indicate any trends present.

79 Chapter 4: Water Quality Results and Discussion

30

25

20

15

Conductivity (ms/m) 10

5

0

1975/11/111976/08/0317/05/197626/07/19761976/01/111977/10/0121/03/197730/05/197715/08/197725/10/19771978/02/0122/01/198018/08/198027/10/19801981/12/0113/07/198123/02/198329/02/198427/03/198529/01/198627/11/19861987/01/1028/07/198829/06/198928/06/199027/06/19911992/01/0726/04/199328/02/199417/07/199518/09/199627/08/199729/07/199815/04/1999 Conductivity Poly. (Conductivity) 200

180

160

140

120

100

80

60 Total Dissovled Solids (mg/l)

40

20

0

1975/11/111976/08/0317/05/197626/07/19761976/01/111977/10/0121/03/197730/05/197715/08/197725/10/19771978/02/0122/01/198018/08/198027/10/19801981/12/0113/07/198123/02/198329/02/198427/03/198529/01/198627/11/19861987/01/1028/07/198829/06/198928/06/199027/06/19911992/01/0726/04/199328/02/199417/07/199518/09/199627/08/199729/07/199815/04/1999 TDS Poly. (TDS)

Figure 4.16: Graphical representation of historical data on a temporal scale. pH, Conductivity and TDS at Bad se Loop (BSL). A polygonal trend line is superimposed on the data to indicate any trends present.

80 Chapter 4: Water Quality Results and Discussion

40

35

30

25

20

15

Chloride concentration (mg/l) 10

5

0

1975/11/111976/08/0317/05/197626/07/19761976/01/111977/10/0121/03/197730/05/197715/08/197725/10/19771978/02/0122/01/198018/08/198027/10/19801981/12/0113/07/198123/02/198329/02/198427/03/198529/01/198627/11/19861987/01/1028/07/198829/06/198928/06/199027/06/19911992/01/0726/04/199328/02/199417/07/199518/09/199627/08/199729/07/199815/04/1999 Chloride Poly. (Chloride)

40

35

30

25

20

15

Sulphate concentration (mg/l) 10

5

0

1975/11/111976/08/0317/05/197626/07/19761976/01/111977/10/0121/03/197730/05/197715/08/197725/10/19771978/02/0122/01/198018/08/198027/10/19801981/12/0113/07/198123/02/198329/02/198427/03/198529/01/198627/11/19861987/01/1028/07/198829/06/198928/06/199027/06/19911992/01/0726/04/199328/02/199417/07/199518/09/199627/08/199729/07/199815/04/1999 Sulphates Poly. (Sulphates)

12

10

8

6

4 Nitrate-nitrite concentration (mg/l) 2

0

1975/11/111976/08/0317/05/197626/07/19761976/01/111977/10/0121/03/197730/05/197715/08/197725/10/19771978/02/0122/01/198018/08/198027/10/19801981/12/0113/07/198123/02/198329/02/198427/03/198529/01/198627/11/19861987/01/1028/07/198829/06/198928/06/199027/06/19911992/01/0726/04/199328/02/199417/07/199518/09/199627/08/199729/07/199815/04/1999 Date Nitrate-nitrite Poly. (Nitrate-nitrite)

Figure 417: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Bad se Loop (BSL). A polygonal trend line is superimposed on the data to indicate any trends present.

81 Chapter 4: Water Quality Results and Discussion

0.16

0.14

0.12

0.1

0.08

0.06

0.04 Orthophosphate concentration (mg/l)

0.02

0

1975/11/111976/08/0317/05/197626/07/19761976/01/111977/10/0121/03/197730/05/197715/08/197725/10/19771978/02/0122/01/198018/08/198027/10/19801981/12/0113/07/198123/02/198329/02/198427/03/198529/01/198627/11/19861987/01/1028/07/198829/06/198928/06/199027/06/19911992/01/0726/04/199328/02/199417/07/199518/09/199627/08/199729/07/199815/04/1999 Orthophosphate Poly. (Orthophosphate)

Figure 4.18: Graphical representation of historical data on a temporal scale. Orthophosphate at Bad se Loop (BSL). A polygonal trend line is superimposed on the data to indicate any trends present.

82 Chapter 4: Water Quality Results and Discussion

9

8

7

6

5 pH 4

3

2

1

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985 pH Poly. (pH) 35

30

25

20

15 Conductivity (ms/m)

10

5

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985 Conductivity Poly. (Conductivity)

200

180

160

140

120

100

80

60 Total Dissolved Solids (mg/l)

40

20

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985 TDS Poly. (TDS)

Figure 4.19: Graphical representation of historical data on a temporal scale. pH, Conductivity and TDS at Tobias Spruit. A polygonal trend line is superimposed on the data to indicate any trends present.

83 Chapter 4: Water Quality Results and Discussion

25

20

15

10 Chloride concentration (mg/l)

5

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985 Chloride Poly. (Chloride) 25

20

15

10 Sulphate concentration (mg/l)

5

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985 Sulphate Poly. (Sulphate)

0.2

0.18

0.16

0.14

0.12

0.1

0.08

0.06

Nitrite-Nitrate concentration (mg/l) 0.04

0.02

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985 Nitrite-Nitrate Poly. (Nitrite-Nitrate)

Figure 4.20: Graphical representation of historical data on a temporal scale. Chloride, sulphate and nitrite-nitrate at Tobias Spruit. A polygonal trend line is superimposed on the data to indicate any trends present.

84 Chapter 4: Water Quality Results and Discussion

0.05

0.045

0.04

0.035

0.03

0.025

0.02

0.015 Orthophosphate concentration 0.01

0.005

0

09/01/197823/01/197806/02/197806/03/197820/03/197810/04/197824/04/197808/05/197822/05/197805/06/197819/06/197803/07/197817/07/197828/11/197919/12/197916/01/198030/01/198013/02/198027/02/198012/03/198026/03/198009/04/198023/04/198024/12/198014/01/198128/01/198111/02/198125/02/198111/03/198125/12/1985

Orthophosphate Poly. (Orthophosphate)

Figure 4.21: Graphical representation of historical data on a temporal scale. Orthophosphate at Tobias Spruit. A polygonal trend line is superimposed on the data to indicate any trends present.

As mentioned in Chapter 2 various activities take place around these sites and increased farming and mining activities over the last 20 years may have lead to these changes occurring. The variables that indicated negative trends or decreases in concentrations are the conductivity and TDS at the source of the Klein Nyl River and in the Olifants Spruit.

The reference conditions for the sites were then calculated using the medians of the data for the first time period. Three percentile values were determined for each site with the 50th percentile giving the median concentration/levels for the system and the 25th and 75th percentiles indicating a suitable operating range to act as guideline values. Table 4.3 shows these values and thus the guideline ranges for the water in the system. It is important to remember that these values are just a guideline for water quality in the system in the period from 1972 to 1984 and are thus not pristine conditions for the system but any deviations from these ranges denote deterioration in the systems integrity. In the case of Nylsvley at Deelkraal the data set was small so the first time period was taken from October 1983 to January 1988.

85 Chapter 4: Water Quality Results and Discussion

Table 4.2: Water quality ranges for historical sites indicating two time periods and temporal changes in variables.

pH EC TDS Cl SO4 NO2-NO3 PO4

Klein Nyl River at Nylstroom (KNN) 25th p period 1 6.53 71.75 49.00 3.08 0.68 0.02 0.00 median period 1 6.90 87.00 64.00 4.40 1.85 0.03 0.01 75th p period 1 7.10 137.50 103.00 6.63 4.80 0.05 0.02 25th p period 2 7.33 75 51 5.8 3.9 0.03 0.01 median period 2 7.54 82.3 58 7.5 4.8 0.04 0.01 75th p period 2 7.67 99.69 70 10 6.5 0.05 0.02 Donkerpoort Dam (DPD) 25th p period 1 6.03 45.00 35.00 2.60 0.01 0.00 median period 1 6.44 49.00 39.00 3.70 0.03 0.01 75th p period 1 6.72 59.00 44.00 6.40 0.05 0.01 25th p period 2 6.44 55.15 43.25 5.00 0.03 0.01 median period 2 6.75 72.00 46.50 5.35 0.08 0.01 75th p period 2 6.99 79.50 48.75 6.68 0.24 0.02

Hessie Se Water (HSW) 25th p period 1 6.14 34.25 24.00 2.00 1.20 0.01 0.01 median period 1 6.60 39.00 30.00 2.30 2.30 0.02 0.01 75th p period 1 6.80 42.00 35.00 2.90 4.45 0.02 0.01 25th p period 2 7.22 41.05 38.35 5.03 4.00 0.04 0.01 median period 2 7.45 52.75 49.00 10.00 4.52 0.04 0.02 75th p period 2 7.59 63.08 52.00 10.00 5.80 0.04 0.03

Olifants Spruit 25th p period 1 6.52 56.00 42.00 1.80 0.70 0.01 0.01 median period 1 6.89 64.00 49.00 2.60 1.90 0.02 0.01 75th p period 1 7.11 72.25 55.00 3.60 5.15 0.03 0.01 25th p period 2 6.87 56.40 36.00 4.30 3.40 0.03 0.01 median period 2 7.41 60.10 41.00 5.70 4.40 0.04 0.01 75th p period 2 7.56 64.00 45.00 8.25 6.00 0.07 0.02 Nylsvley 25th p period 1 6.79 101.50 64.50 7.15 4.13 0.02 0.03 median period 1 7.00 113.00 77.00 7.30 4.85 0.03 0.05 75th p period 1 7.15 126.50 92.00 7.65 5.58 0.04 0.05 25th p period 2 6.78 93.25 61.25 9.80 1.90 0.02 0.01 median period 2 7.09 114.50 67.00 11.50 3.60 0.03 0.02 75th p period 2 7.57 125.50 80.00 14.00 5.00 0.04 0.04 Bad se Loop 25th p period 1 6.42 72.25 53.25 3.10 3.10 0.11 0.01 median period 1 6.67 86.00 58.00 5.10 5.60 0.35 0.01 75th p period 1 6.97 99.25 66.75 6.60 7.30 0.56 0.02 25th p period 1 7.32 170.75 121.25 9.80 7.18 0.55 0.01 median period 2 7.66 199.75 135.00 12.00 10.15 2.47 0.02 75th p period 1 7.92 216.00 143.00 15.53 12.67 4.12 0.02 Tobias 25th p period 1 6.55 149.50 106.50 8.75 1.70 0.02 0.00 median period 1 6.94 179.00 124.00 11.90 2.95 0.04 0.01

86 Chapter 4: Water Quality Results and Discussion

75th p period 1 7.29 182.50 139.00 14.55 8.43 0.10 0.02 25th p period 2 7.00 112.78 123.00 15.00 5.00 0.20 0.20 median period 2 7.07 272.50 160.00 25.87 5.00 0.20 0.20 75th p period 2 7.17 318.00 170.75 29.00 5.00 0.20 0.20 The results in Table 4.2 indicate that at most of the sites the medians for period two show increased levels/concentrations when compared to those of period one. These indicate an overall deterioration of the water quality in the system over the past 20 years. The 25th and 75th percentiles provide a guideline range from which one can compare present conditions. These indicate conditions close to the natural state of the river system. Table 4.3 indicates the preferred water quality ranges from the Nyl River system based on data from the gauging weirs. The conductivity and TDS at the source of the Klein Nyl’s Eye (KNN) indicates a different trend and thus the data from period two has been used instead of the values from period one. The same trend is present at Olifants Spruit and at the site Nylsvley at Deelkraal.

Table 4.3: Water quality ranges for the Nyl River System. pH Ec Tds Cl SO4 NO2-NO3 PO4 KNN Lower Limit 7.33 75 51 5.8 3.9 0.03 0.01 Upper Limit 7.67 99.69 70 10 6.5 0.05 0.02 DPD Lower Limit 6.03 45.00 35.00 2.60 0.01 0.00 Upper Limit 6.72 59.00 44.00 6.40 0.05 0.01 HSW Lower Limit 7.22 41.05 38.35 5.03 4.00 0.04 0.01 Upper Limit 7.59 63.08 52.00 10.00 5.80 0.04 0.03 Olifants Spruit Lower Limit 6.87 56.40 36.00 4.30 3.40 0.03 0.01 Upper Limit 7.56 64.00 45.00 8.25 6.00 0.07 0.02 Nylsvley Lower Limit 6.79 93.25 61.25 7.15 4.13 0.02 0.03 Upper Limit 7.15 125.5 80.00 7.65 5.58 0.04 0.05 Bad se Loop Lower Limit 7.32 170.75 121.25 9.80 7.18 0.55 0.01 Upper Limit 7.92 216.00 143.00 15.53 12.67 4.12 0.02 Tobias Lower Limit 6.55 149.50 106.50 8.75 1.70 0.02 0.00 Upper Limit 7.29 182.50 139.00 14.55 8.43 0.10 0.02

4.2: Water parameters

As mentioned in Chapter 3 water was sampled at the different localities

87 Chapter 4: Water Quality Results and Discussion quarterly from April 2001 to March 2003. The following parameters were determined in situ at the different localities. Dissolved oxygen (O2) concentration and percentage saturation, pH, electrical conductivity (Ec) and total dissolved solids. The Department of Water Affairs and Forestry has set out a list of guideline values with which to compare element levels in a water body and to assess if they are toxic or not. These guideline values form a target water quality range (TWQR). If the levels fall below the TWQR organisms can become susceptible to disease. If the concentrations exceed the upper limit of the TWQR then the elements become toxic to the aquatic organisms (Du Preez et al., 1997). The effect of the different parameters is explained under the different subheadings. pH pH is a measure of the hydrogen ion (H+) activity in water. As the concentration of H+ ions increases in water the pH value decreases making the water more acidic (DWAF, 1996a). pH is regulated by the carbonate- + bicarbonate cycle consisting of H2CO3- ? H2O+CO2 ? 2H +CO3- ? + - H +HCO3 (Polling, 1999). pH fluctuations may occur either naturally or by anthropogenic activities.

Natural fluctuations can either occur diurnally or seasonally. Diurnal fluctuations are caused by the changes in the carbonate- bicarbonate levels due to the actions of photosynthesis in productive systems. Extreme rates of photosynthesis can result in high pH values in still standing eutrophied waters. Seasonal variations are caused by the hydrological cycle (DWAF, 1996a).

Artificial changes brought on by anthropogenic activities take place in 3 ways: (1) low pH point source from industries, (2) mine drainage, which is almost always acidic, and (3) acidic precipitation brought on by the presence of air borne pollution. During the burning processes of coal and combustion engines

SO2 and NO2 are released into the atmosphere. These gasses bind with the water in the atmosphere to form a sulphuric or nitric acid compound which

88 Chapter 4: Water Quality Results and Discussion leads to acid rain (DWAF, 1996a). The acid rain interferes with the nutrient availability. pH plays an important role in physio-chemical and biological processes in water (Train, 1979). Depending on the number of free H+ ions, cations and anions are released or bonded to other ions in the water making them more or less toxic to aquatic organisms. An example of this is the influence pH can have on the reproductive rates of fish. This was indicated by Tucker and Robinson (1990) in Channel catfish. They noted that disturbances in respiration, osmoregulation and blood pH/acid-base balance result from exposure to low water pH levels.

This caused reduced growth, reproduction and disease resistance. “Acid rain” can cause situations that will negatively influence egg production and hatching time of fish eggs (Mount, 1973, Nelson, 1982). Egg production can also be negatively influenced for example some species of fish show signs of embryonic deformities (Lee and Germing, 1980, Peterson et al., 1976). The pH of the water can also have a role in the release of toxic substances from sediments (DWAF, 1996a), which is important in wetland systems as they act as sediment traps. Table 4.4: pH values in the Nyl River System during the study period. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality pH Apr-01 Aug-01 Nov-01 Mar-02 Jul-02 Nov-02 Mar-03 KIN 5.89 7.76 5.7 N/A 7.14 N/A N/A KNO 5.91 8.39 6.62 5.52 7.33 6.5 N/A Abba 6.21 7.56 6.55 6.64 6.43 6.57 6.57 DPD 6.11 7.51 6.8 6.68 6.45 N/A 6.85 GNO 6.06 7.36 6.45 5.61 5.88 7.1 N/A DlaDla 6.41 7.07 6.66 6.34 6.72 6.8 N/A STW 7.2 7.66 N/A 7.14 7.34 7.31 N/A Jasper 6.29 8.81 6.67 6.86 7.16 7.39 6.75 HSW 6.33 7.02 6.94 6.61 6.43 7.35 N/A Olifants Spruit 6.3 7.31 6.79 6.58 6.64 7.08 6.28 Nylsvley 7.04 7.31 6.78 6.92 7.56 6.8 7.62 BSL 6.2 7.5 7.05 7.56 7.31 7.4 N/A TO 6.45 7.35 7.02 6.9 7.44 7.2 N/A TM 6.72 7.13 7 7.18 7.01 7.29 N/A TS 6.87 N/W 6.73 7.69 N/W N/A N/A

89 Chapter 4: Water Quality Results and Discussion

Mosdene 6.72 6.92 6.75 6.38 N/W N/A N/A Haakdoring 6.9 8.47 6.6 8.26 7.29 N/A N/W Moorddrif 9.56 9.5 8.94 7.97 7.52 N/A 7.59 The pH of the water in the system (Table 4.4) for the most part falls within the target water quality range (TWQR) (DWAF, 1996a). Less than 25% of the readings showed values less than the lower TWQR limit of 6.5 pH units. Less than five percent of the readings fell outside the upper limit of 9 pH units. The TWQR of 6.5-9 is set out for Aquaculture (DWAF, 1996b). A maximum value of 9.52 pH units was measured at the site located at the Moorddrift Dairy during sampling in April 2001. The minimum value of 5.52 pH units was recorded at the source of the Klein Nyl River (KNO) during March 2002. The increased pH levels at the Haakdoring and Moorddrift site can be attributed to the eutrophication of the water. Increased nutrient loads at these sites cause increased rates of photosysnthesis which leads to a increase in pH levels (ELC, 2003). Both sites are dammed areas situated at the lower end of the Nyl River Floodplain and would thus provided good points for nutrient deposition and eutrophication. This increase could be an effect of commercial cattle farming.

Oxygen

Dissolved oxygen concentrations are probably the most important abiotic factors for aquatic organisms (Davies and Day, 1998). Dissolved oxygen enters the aquatic environment by one of two methods. The first is the dissolving of atmospheric oxygen into the water via surface interface interactions. The second is via the photosynthetic interactions of aquatic plants (DWAF, 1996a). Concentrations fluctuate diurnally due to the metabolic processes of photosynthesis and respiration (Davies and Day, 1998). Oxygen concentration levels are usually lowest just before dawn and increase during the day, peaking in the afternoon. The amount of oxygen that can dissolve in a water body is dependant on certain factors such as temperature, aeration rates from the atmosphere, air pressure and salinity (Davies and Day, 1998). Oxygen concentrations in a water body can be influenced by the following

90 Chapter 4: Water Quality Results and Discussion factors: (1) organism respiration rates, (2) the presence of organic matter and (3) the resuspension of anoxic sediments either via dredging or natural flooding (DWAF, 1996a). In wetland systems the presence of oxidisable organic matter (detritus) and the rates of photosynthesis and respiration are important factors in the oxygen concentrations in water. These factors can have an influence on the oxygen levels and thus affect the presence of high life in the system. Organic matter will settle out in the system due to a drop in the velocity of the water in the system. This is part of the normal functioning of wetlands as previously discussed in Chapter 1.

Table 4.5: Dissolved oxygen concentrations (mg/l) during the study period. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality Dissolved Oxygen (mg/l) 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul 02-Nov 03-Mar KIN 8.1 7.78 8.67 N/A 8.64 N/A N/A KNO 5.4 8.48 6.96 4.04 8 5.23 N/A Abba 7.3 6.53 6.96 7 5.44 0.13 0.13 DPD 7.6 8.38 8.84 8.13 8.45 N/A 6.36 GNO 6.2 7.31 7.22 8.68 8.26 7.34 N/A DlaDla 7.9 9.03 8.39 9.2 6.89 6.54 N/A STW 7.5 8.3 N/A 8.07 5.18 N/A N/A Jasper 7.9 10.75 5.95 8.35 7.75 4.96 2.04 HSW 6 8.85 6.71 7.16 8.74 1.5 N/A Olifants 6.7 6.93 8.75 8.97 5.68 4.64 6.86 Spruit Nylsvley 6.7 6.11 5.41 2.23 7.11 1.15 3.3 BSL 6.4 8.42 8.37 8.82 8.03 7.1 N/A TO 7.2 7.55 8.42 7.74 6.89 5.69 N/A TM 4.7 2.1 7.95 6.71 4 3.24 N/A TS 5.96 N/W 8.14 8.15 N/W N/A N/A Mosdene 0.4 3.6 1.48 0 N/W N/A N/A Haakdoring 6 9.75 0.33 7.65 3.4 N/A N/W Moorddrift 10.1 7.36 5.9 8.74 8.63 N/A 8.84

91 Chapter 4: Water Quality Results and Discussion

Table 4.6: Percentage oxygen saturation (%) during the study period. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality Dissolved O2 (% Saturation) 1-Apr 1-Aug 1-Nov 2-Mar 2-Jul 2-Nov 3-Mar KIN 99 70.4 90.8 N/A 79.4 N/A N/A KNO 69 102 77.1 50 75.4 67.3 N/A Abba 91 73 75.5 87 68.4 1.8 1.8 DPD 96 83 95.6 100.2 85.8 N/A 83.5 GNO 82 78.9 80.2 108.1 75.6 96.6 N/A DlaDla 104 92.2 90.5 109.4 72.1 80.4 N/A STW 96 79.2 N/A 100.5 N/A 59.3 N/A Jasper 98 113 63.8 104 71.8 55.6 3.75 HSW 79 78.1 70.6 88 83.1 20 N/A Olifants 91 71.2 93.5 108.6 66.8 52.8 82 Spruit Nylsvley 74 55.7 62.6 27.6 89.4 14.1 45.3 BSL 81 87 92.3 107.9 81.9 90.5 N/A TO 87 75.6 89 95.8 75.9 74.6 N/A TM 61 21.4 86.1 82.9 36.1 41 N/A TS 71 N/W 90 96.4 N/W N/A N/A Mosdene 6 31.7 16.7 0 N/W N/A N/A Haakdoring 77 101.7 3.5 117.7 32.8 N/A N/W Moorddrift 139 82.1 69.2 102.6 90 N/A 117.8

Tables 4.5 and 4.6 indicate results obtained from the in situ O2 determinations. The results varied both spatially and temporally with no clear trends. The maximum O2 concentration was recorded during the August 2001 survey at Jasper. The site had an O2 concentration of 10.75mg/l. The minimum value recorded was at Mosdene in March 2002. A spatial trend is only observed if the temporal data for each site is averaged (Figure 4.22).

92 Chapter 4: Water Quality Results and Discussion

10.00 8.00 6.00 4.00 2.00 0.00

KNO Abba DPD STW Oxygen concentration (mg/l) Jasper Nylsvley Mosdene Moorddrift Haakdoring

Figure 4.22: Graph indicating mean oxygen concentration level fluctuations in the Klein Nyl River as it flows from the source through the Nyl River Floodplain.

Figure 4.22 indicates the mean oxygen concentrations at the different sites along the course of the Klein Nyl River, past the confluence of the Groot and Klein Nyl Rivers, and along the course of the Nyl River. The graph clearly indicates that the oxygen levels decrease as the water flows through the wetland. This can be attributed to the increased levels of organic matter and the break down thereof. A more detailed explanation will be provided later in this chapter. The oxygen saturation (Table 4.6) indicated slightly different results with the maximum value being 139% at Moorddrift in April 2001. The minimum value was once again found at Mosdene in March 2002. The values at Mosdene in March 2002 can be attributed in part to an oily layer that was found floating on the surface of the sampling site. This layer inhibited the transfer of oxygen from the atmosphere into the water. The oxygen levels fluctuated greatly and thus it makes it difficult to list all the sites that fell outside the TWQR for aquatic ecosystems. The TWQR for oxygen saturation indicate that levels below 60% are sublethal to aquatic organisms and below 40% are lethal. The sampling site located at Mosdene consistently provided oxygen saturation readings below the lethal TWQR of 40%, with many of the

93 Chapter 4: Water Quality Results and Discussion other sites displaying sub lethal oxygen levels.

Electrical Conductivity (EC) and Total Dissolved Solids (TDS)

Electrical conductivity is the measure of a body of water’s ability to conduct an electrical current (DWAF, 1996a). It is closely related to the waters TDS (DWAF, 1996a). Conductivity is usually the parameter of choice to measure as it is easier to measure than TDS. TDS is derived from the conductivity by multiplying the conductivity (mS/m) by a factor of 6.5. This gives an approximate TDS value in mg/l (Kempster and van Vliet, 1991).

A water body’s EC is a result of the presence of ions in the form of carbonates, bicarbonates, sulphates, nitrates, sodium, potassium, calcium and magnesium. Organic compounds dissolve in water but do not affect the EC of the water (Davies and Day, 1998). Natural waters contain varying quantities of TDS and their conductivities thus also vary. These solids enter the water column via a number of routes namely: (1) the mechanical weathering of rocks, (2) evaporation and (3) rainfall (Davies and Day, 1998)

TDS concentrations can increase due to anthropogenic activities. These can be either from direct input of effluents from industrial processes, or from surface runoff from urban, industrial or cultivated areas. Increased TDS concentrations affect metabolic processes of organisms and the fate and impact of other chemical constituents in the aquatic environment (DWAF, 1996a).

Changes in TDS concentration can affect organisms on the following levels: (1) effects on, and adaptations of individual species, (2) effects on community structure, and (3) effects on microbial and ecological processes such as metabolic rates and nutrient cycling (Dallas et al., 1998).

Little is known about the tolerance levels of aquatic organisms to changes in

94 Chapter 4: Water Quality Results and Discussion

TDS concentrations but the following generalizations can be made. Rate of change and duration are more important than absolute TDS changes, especially in systems where organisms are not adapted to fluctuations in TDS. Juvenile stages appear more sensitive to changes in TDS concentration. Synergistic and antagonistic effect usually appear as secondary effects of TDS concentration changes (metals may become more toxic), and organisms adapted to low salinities are generally more sensitive to changes in TDS concentrations (Dallas et al., 1998).

Table 4.7: EC values for the sampling sites for the period April 2001 to March

2003. N/A: not available, N/W: no water. Light grey cells indicate tributaries.

Locality Electrical Conductivity (mS/cm) 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul 02-Nov 03-Mar KIN 19.3 26.1 18.1 N/A 49.9 N/A N/A KNO 8.17 47.2 24.6 14.48 46.6 17.3 N/A Abba 45.5 44.2 62.2 48.9 67.8 73.2 73.2 DPD 48.5 47.1 53.5 55.7 91.4 N/A 134.7 GNO 16.99 16.2 16.57 25.8 40.6 26.1 N/A DlaDla 35.2 36.8 39.6 30.3 72.5 54.1 N/A STW 233 206 N/A 150.4 287 685 N/A Jasper 132.3 151.9 151.5 165.7 229 503 163 HSW 60.8 61 73.5 63.9 51.4 141.3 N/A Olifants 53.6 52.4 29.9 57.1 86.2 60.3 42 Spruit Nylsvley 98.1 120 59 156.3 190.1 358 130.5 BSL 167 236 47.7 162.8 242 238 N/A TO 92.6 102.2 51.2 80 128.4 118.5 N/A TM 306 346 70.7 239 322 35.8 N/A TS 375 N/W 137 292 N/W N/A N/A Mosdene 94.9 152.2 121 224 N/W N/A N/A Haakdoring 325 361 196.7 215 468 N/A N/W Moorddrift 179.5 218 232 166 163.7 N/A 311

The results in Table 4.7 indicate that the conductivities at the sites range between 8.17mS/cm and 685mS/cm. Figure 4.9 indicates that at points where the EC readings decrease a dilution of the main stream occurs and where increases occur the tributaries are adding to the contamination. The results also indicate that the STW has an effect on the increase of the conductivity of

95 Chapter 4: Water Quality Results and Discussion the Nyl River. The Tobias Spruit also has a deleterious effect on the water quality of the Nyl River. The highest conductivity reading (685ms/cm) was recorded at the Sewage Treatment Works in November 2002. The EC reading is higher than the 635ms/cm recorded by Polling (1999) in the polluted Selati River. Polling (1999) reported that the conductivity of 635ms/cm was almost acceptable and the conductivity reading at the STW can thus be deemed to be unacceptable. This however is an isolated incident with the median conductivity for the system being 91.4ms/cm, which is acceptable. The conductivity values obtained in the lower reaches of the study area do not conform to the TWQR guideline values as they differ by more than 15% from the normal EC (DWAF, 1996a).

Tobias Spruit 400 350 300 Dla Dla BSL 250 200 Olifants Spruit 150 100 KiN 50 0 conductivity (us/cm)

KIN KNO Abba DPD STW Jasper Nylsvley Mosdene Moorddrift Haakdoring

Figure 4.23: Graph indicating the increase in EC through the Klein Nyl River during August 2001. The light grey bars indicate the points where water from the tributaries mix with the water from Nyl River. Levels given for the tributaries are average EC readings from the different sites in the tributaries.

Table 4.8: TDS values for the sampling sites for the period April 2001 to

96 Chapter 4: Water Quality Results and Discussion

March 2003. N/A: not available, N/W: no water. Light grey cells indicate tributaries.

Locality Total Dissolved Solids (mg/l) 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul 02-Nov 03-Mar KIN 10.2 13 N/A N/A 24.2 N/A N/A KNO 15.84 24.1 12.4 7.18 23.3 8.5 N/A Abba 23.7 22.2 31.4 24.7 40.8 36.6 36.6 DPD 25.1 23.2 26.8 26.7 45.8 N/A 67.2 GNO 8.93 8.05 8.25 13.1 19.9 16.2 N/A DlaDla 18.5 18.9 19.8 14.8 38.4 27.1 N/A STW 118 104 N/A 75.5 152 342 N/A Jasper 69.6 76.1 74.9 83.3 116 251 81.6 HSW 30.1 30.6 36.7 32.3 51.7 70.2 N/A Olifants 27.8 26.3 15 28.1 44 29.7 21.1 Spruit Nylsvley 51 59.9 29.5 73.7 97.5 178 65.3 BSL 83 118 23.9 82.4 117 120 N/A TO 48.3 50.1 25.8 41.5 59.6 59.1 N/A TM 159 174 35.5 111 161 178 N/A TS 190 N/W 69.5 144 N/W N/A N/A Mosdene 49 74.8 60.6 112 N/W N/A N/A Haakdoring 170 183 96.8 109 235 N/A N/W Moorddrift 93.3 109 116 82.8 81.8 N/A 157

Table 4.8 gives the TDS values for the system. These values correspond to the EC levels, showing the same increase or decrease in trends. The TWQR for TDS state that the levels should not change by more than 15% of normal conditions for that time of year (DWAF, 1996a). These levels do increase by more than 15% if one compares the levels obtained during the same time periods for 2001 and 2002. One must take into account the difference in stream flow due to the poor rainy season experienced during 2002, which resulted in decreased water volume during the periods of low flow. The maximum concentration recorded of 342mg/l was recorded at the STW during November 2002. The minimum concentration of TDS (7.13mg/l) was recorded at the source of the Klein Nyl River in March 2002. The good rains during the 2001- 2002 season were responsible for diluting the TDS concentrations in the system. Conversely the poor 2002-2003 rainy season can be a contributing factor to the increased TDS concentrations recorded in the November 2002 sampling period.

97 Chapter 4: Water Quality Results and Discussion

Temperature

The water temperature (Table 4.9) in the system ranged between 8.3ºC at KIN during the winter month of July 2002 and 31.3ºC at Moorddrift Dam during March 2003. These drastic temperature changes can be attributed to the season but the high water temperature can also be attributed to the lack of water circulation in water overgrown with aquatic vegetation. The mean water temperature during the winter months is 13.1ºC and during summer 22.6ºC.

Table 4.9: Water temperatures measured during the study period. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality Temperature (°C) 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul 02-Nov 03-Mar KIN 16.4 14.7 18 N/A 8.3 N/A N/A KNO 19.9 19.6 21 28.7 12.7 26.6 N/A Abba 17.8 15.7 19.9 25.7 14.3 27.4 27.4 DPD 18.9 15.2 21.8 26.5 15 N/A 27 GNO 19.8 19 19.1 23.9 10.9 26.5 N/A DlaDla 21.5 14.5 19.6 23.9 8.8 25.2 N/A STW 18.4 11.7 N/A 27.3 13.2 22 N/A Jasper 17 14.7 20.7 23.9 5.9 21.1 27 HSW 19.7 10.1 19.5 24.8 6.2 21.7 N/A Olifants 20.4 13.3 19.5 25 12 21.7 23.7 Spruit Nylsvley 20.7 10.9 22.9 25.9 11.9 26.1 28.3 BSL 17.4 17.2 19.7 26.6 12.5 27 N/A TO 16.1 12.1 18.6 26.6 12.9 29 N/A TM 19 16.4 19 27.3 10.8 25.2 N/A TS 20.2 N/W 20.3 23.9 N/W N/A N/A Mosdene 17 8 21.5 21.6 N/W N/A N/A Haakdoring 22.6 15.8 20.9 25.8 16.8 N/A N/W Moorddrift 22.3 14.9 24.6 23.5 14.7 N/A 31.3

98 Chapter 4: Water Quality Results and Discussion

4.3: Inorganic constituents

Total alkalinity and water hardness.

Total alkalinity is the measure of all bases dissolved in a water body (Polling, 1999). It is directly involved in the buffering capacity of a water body and is closely related to water hardness. Water hardness is determined by the

CaCO3 concentrations in the water (DWAF, 1996b). Hardness plays a role in the toxicity of certain metals. Carbonates and bicarbonates have a dampening effect on the toxicity of certain metals (Train, 1979). As a general rule the toxicity of metals decreases as the hardness or CaCO3 concentrations increases (Bell, 1976). A total alkalinity range of between 20 and 100mg/l is optimal for primary and secondary production in aquatic ecosystems (Stickney, 1979). Water can be classified into four main classes according to its CaCO3 concentrations. Table 4.10 indicates these classes and the CaCO3 concentration ranges associated with each class.

Table 4.10: Water classification according to CaCO3 concentrations in mg/l.

Classification CaCO3 concentration range (mg/l) Soft water < 60 Medium water 60-119 Hard water 120-179 Very hard water >180

Table 4.11: Measured CaCO3 concentrations in mg/l N/A: not available, N/W: no water. Light grey cells indicate tributaries.

Locality Total alkalinity CaCO3 (mg/l) 1-Apr 1-Aug 1-Nov 2-Mar 2-Jul KIN 2.6 5 N/A 20 15 KNO 1.4 5 15 20 <5 Abba 15.2 10 15 30 20 DPD 13 25 25 25 40 GNO 0.6 <5 10 60 20 Dla Dla 10 10 20 15 15 STW 60.8 65 55 35 70 Jasper 46.8 35 85 40 <5 HSW 25.4 20 35 35 30

99 Chapter 4: Water Quality Results and Discussion

Table 4.11 cont: Olifants Spruit 18.6 15 25 20 <5 Nylsvley 36.2 25 65 30 35 BSL 56 25 45 15 50 TO 30.4 30 35 25 40 TM 99.2 105 85 20 120 TS 124 N/W 105 70 N/W Mosdene 56.4 55 60 35 N/W Haakdoring 122.4 140 100 85 225 Moorddrift 91.8 90 85 95 65

The results indicate (Table 4.11) that for the most part the water is soft with a median value of 35mg/l. A maximum concentration of 225mg/l was recorded at Haakdoring in July 2002 and the minimum concentration of 0.6 mg/l recorded at source of the Groot Nyl River in April 2002. The average total alkalinity concentrations for the 2001 and 2002 sampling periods were both 45mg/l. The soft nature of the water can change the speciation of the metals in the water and thus, potentially lead to the increased toxicity of metals found in the system.

Chlorides

Chlorides are considered one of the major inorganic anions in water after carbonates and sulphates (Hutchinson, 1975). Although there is no TWQR available for chlorides, Ayers and Wescott (1985) considered chloride concentrations of 60mg/l safe for agricultural use and values up to 100mg/l safe for livestock, game animals and industrial use. Aucamp and Viviers (1990) considered 250mg/l to be the maximum limit safe for potable water sources.

Chlorides are a product of the binding action of chlorine to most elements. Chlorine is used widely as a bleaching agent in industry and for water purification. Chlorides are relatively non-toxic to organisms with an effective excretion mechanism. To organisms without an effective excretion mechanism

100 Chapter 4: Water Quality Results and Discussion for example plants, chlorides can prove to be toxic (Kempster et al.,1980). Chloride may enter the aquatic environment via irrigation runoff, industrial processes and sewage effluent (DWAF, 1996b). Chlorides interact with metals to enhance and accelerate the oxidation processes.

Table 4.12: Recorded chloride levels at the sampling sites during the study periods. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality Cl- concentration (mg/l) 1-Apr 1-Aug 1-Nov 2-Mar 2-Jul KIN 3.33 <5 N/A <5 10 KNO N/A <5 <5 <5 6 Abba N/A 20 <5 <5 12 DPD N/A <5 <5 <5 11 GNO 2.9 <5 5 <5 10 Dla Dla N/A 16 <5 <5 7 STW 25.63 17 20 <5 37 Jasper 13.07 20 15 9 613 HSW 4.01 <5 <5 6 11 Olifants Spruit N/A 14 <5 10 608 Nylsvley 10.15 16 11 <5 34 BSL 11.61 15 11 <5 26 TO 5.62 6 6 <5 14 TM 25.87 29 15 <5 29 TS 25.15 N/W 16 9 N/W Mosdene 5.24 31 11 6 N/W Haakdoring 18.29 <5 <5 6 41 Moorddrift 8.01 9 <5 12 12

Nitrates and Nitrites

Nitrates and nitrites are two inorganic constituents that are interlinked. Nitrites are the intermediate in the nitrogen cycle where ammonia is broken down by the process of nitrification to form nitrites and then once again broken down to form nitrates. This is done by the action of two bacteria (Nitromonas spp and Nitrobacter spp.) under aerobic conditions. Under anaerobic conditions nitrates are oxidised to form nitrites by a number of species of common

101 Chapter 4: Water Quality Results and Discussion facultative anaerobic bacteria, which use nitrite as an exogenous terminal electron acceptor during the oxidation of organic compounds.

The basic equation for these reactions is as follows.

Nitromonas spp. and Nitrobacter spp.

+ - - NH4 NO2 NO3

Common facultative anaerobic bacteria

The processes of nitrification, denitrification and active uptake of nitrates by algae and higher plants are regulated by temperature and pH. Some of the bacteria used in these processes are affected by cold temperatures. High levels of nitrates impact on the eutrophication of a water body (DWAF, 1996b). Ammonia and thus nitrates and nitrites are indicative of contamination by organic industrial effluents, runoff from farming activities and by far the biggest providers of ammonia into a system are sewage effluent and intensive animal culturing e.g. dairy farming (Davies and Day, 1998). High levels of nitrites are indicative of organic contamination and therefore lead to the contamination of fish flesh by metals and bacteria such as E.coli. Nitrites are more toxic than nitrates to aquatic organisms and their rate of uptake is influenced by temperature, pH and chloride concentrations (DWAF, 1996b). Nitrates are usually more stable than nitrites and are more abundant in aquatic ecosystems (DWAF, 1996a).

102 Chapter 4: Water Quality Results and Discussion

Table4.13: Nitrate concentrations at the different sampling sites N/A: not available, N/W: no water. Light grey cells indicate tributaries.

Locality Nitrates (mg NO3-N/l) 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul KIN N/A <0.2 N/W <0.2 <0.2 KNO N/A <0.2 <0.2 <0.2 0.3 Abba 0.08 <0.2 <0.2 <0.2 <0.2 DPD N/A <0.2 <0.2 <0.2 <0.2 GNO N/A <0.2 <0.2 <0.2 <0.2 Dla Dla 1.47 0.7 0.2 <0.2 0.5 STW 1.32 <0.2 0.2 <0.2 3.3 Jasper N/A <0.2 0.2 <0.2 <0.2 HSW N/A <0.2 <0.2 <0.2 <0.2 Olifants Spruit 0.08 <0.2 <0.2 0.5 <0.2 Nylsvley N/A <0.2 0.2 <0.2 <0.2 BSL 14.53 8 2.7 <0.2 6.8 TO N/A <0.2 0.2 <0.2 <0.2 TM N/A <0.2 <0.2 0.2 0.2 TS N/A N/W <0.2 0.2 N/W Mosdene N/A <0.2 <0.2 <0.2 N/W Haakdoring N/A <0.2 <0.2 <0.2 <0.2 Moorddrift N/A <0.2 0.2 <0.2 <0.2

Table 4.14: Nitrite concentrations at the sampling sites N/A: not available, N/W: no water. Light grey cells indicate tributaries.

Locality Nitrite (mg No2-N/l) 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul KIN N/A <0.1 <0.1 <0.1 <0.1 KNO N/A <0.1 <0.1 <0.1 <0.1 Abba N/A <0.1 <0.1 <0.1 <0.1 DPD N/A <0.1 <0.1 <0.1 <0.1 GNO N/A <0.1 <0.1 <0.1 <0.1 Dla Dla N/A <0.1 <0.1 <0.1 <0.1 STW N/A <0.1 0.3 <0.1 <0.1 Jasper N/A <0.1 <0.1 <0.1 <0.1 HSW N/A <0.1 <0.1 <0.1 <0.1 Olifants Spruit N/A <0.1 <0.1 <0.1 <0.1 Nylsvley N/A <0.1 <0.1 <0.1 <0.1 BSL N/A <0.1 <0.1 <0.1 <0.1 TO N/A <0.1 <0.1 <0.1 <0.1 TM N/A <0.1 <0.1 <0.1 <0.1 TS N/A N/A N/W <0.1 N/W Mosdene N/A <0.1 <0.1 <0.1 N/W Haakdoring N/A <0.1 <0.1 <0.1 <0.1 Moorddrift N/A <0.1 <0.1 <0.1 <0.1

Table 4.13 indicates the nitrate concentrations recorded at the different localities during the study period.

103 Chapter 4: Water Quality Results and Discussion

The site at BSL had the highest nitrate concentration recorded of

14.53mgNO3-N/l during April 2001. BSL also consistently showed the highest nitrate concentrations through out the study period. The average nitrate concentration for the system (Excluding the increased results from the BSL) was 0.56mgNO3-N/l although most of the sites indicated results of

<0.2mgNO3-N/l. The sites at the sewage treatment works and at Dla Dla were the other sites that indicated results of more than 0.2mgNO3-N/l. The DWAF guidelines for aquaculture indicates that a nitrate concentration of less than

5mgNO3-N/l signifies that the water is unimpacted. This holds true for most of the sites with the site at BSL being the only site that shows signs of any impact (DWAF, 1996b).

The nitrite concentrations in the system (Table 4.14) were all very low. No reading of above 0.1mgNO2-N/l was recorded at any of the sites along the course of the study area. The TWQR for nitrite in aquaculture lies between

0.06 and 0.25mgNo2-N/l. This range is considered safe for many warm water fish species (DWAF, 1996b). A comparison of the recorded results and the TWQR would indicate that nitrites are not impacting on the organisms in the system.

Sulphates

Sulphates are the oxy-anions of sulphur in the +IV oxidation state (DWAF, 1996c). They are non-toxic to humans and animals but can become so at extremely high concentrations. They are slightly less toxic to plants than chlorides (Kempster et al., 1980).

104 Chapter 4: Water Quality Results and Discussion

Table 4.15: Sulphate levels in the Nyl River System. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality Sulphates mg/l 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul KIN 0.33 <5 <5 <5 <5 KNO N/A <5 <5 <5 18 Abba 0.31 <5 <5 <5 <5 DPD 0.62 <5 <5 <5 <5 GNO N/A <5 <5 <5 <5 Dla Dla N/A <5 <5 <5 <5 STW 10.76 <5 <5 <5 17 Jasper 2.43 <5 <5 <5 363 HSW 0.25 <5 <5 <5 <5 Olifants Spruit 0.55 <5 <5 <5 520 Nylsvley 0.44 <5 <5 <5 <5 BSL 8.93 <5 <5 <5 9 TO 1.4 <5 <5 5 <5 TM 6.43 <5 <5 <5 <5 TS 3.03 N/A <5 6 N/W Mosdene N/A <5 5 <5 N/W Haakdoring 0.19 <5 <5 5 <5 Moorddrift N/A <5 <5 13 <5

The sulphate levels in the system (Table 4.15) are typical of surface water, i.e. 5mg/l (DWAF, 1996d). Most of the readings are less than 5mg/l. The majority of the readings recorded during all sampling months other than April 2001 are <5mg/l due to the minimum detection limits on the apparatus used during analysis. The readings could however be somewhat closer to those found in April 2001. A maximum value of 520mg/l was recorded at Olifants Spruit in July 2002 with a minimum value recorded at Haakdoring (0.19mg/l) during April 2001. Most of the sulphate levels recorded are within the TWQR of between 0 and 200mg/l set out for domestic consumption. No TWQR is available for aquatic ecosystems and so the TWQR for domestic use has been used as suitable for the organisms. Jasper and Olifants Spruit were the only two sites that had readings that fell outside these guideline values with

105 Chapter 4: Water Quality Results and Discussion readings of 363 and 520mg/l respectively. These readings were recorded in July 2002. These values however are below the median guideline value prescribed by Kempster et al. in 1980 of 1400mg/l.

Phosphates.

Phosphates can be either inorganic or organic in nature. They are measured as orthophosphates, total dissolved phosphorus or total inorganic phosphate. Orthophosphate is the only form of phosphorus that is immediately available for aquatic biota. It can be transformed into an available form via natural processes (DWAF, 1996a). Phosphates are essential to a wide variety of aquatic organisms. In animals they play a vital role in the building of nucleic acids and the storage and use of energy in cells. Plants readily utilise it in unimpacted waters by converting it into cell structures in the process of photosynthesis. Phosphates enter the water in one of two ways, either naturally or by anthropogenic activities.

Naturally they enter the water body by the weathering of rocks and the decomposition of organic matter. Anthropogenic activities that release phosphates into the water include domestic and industrial effluents (point source), atmospheric precipitation, urban run off and drainage from agricultural activities (non- point source) (Dallas and Day, 1993).

106 Chapter 4: Water Quality Results and Discussion

Table 4.16: Orthophosphate levels in the Nyl river system. N/A: not available, N/W: no water. Light grey cells indicate tributaries. Locality Orthophosphates mg/l 01-Apr 01-Aug 01-Nov 02-Mar 02-Jul KIN N/A <0.2 <0.2 <0.2 <0.2 KNO N/A <0.2 <0.2 <0.2 <0.2 Abba N/A <0.2 <0.2 <0.2 <0.2 DPD N/A <0.2 <0.2 <0.2 <0.2 GNO N/A <0.2 <0.2 <0.2 <0.2 Dla Dla N/A <0.2 <0.2 <0.2 <0.2 STW 4.54 <0.2 0.4 <0.2 2.2 Jasper N/A <0.2 <0.2 <0.2 <0.2 HSW N/A <0.2 <0.2 <0.2 <0.2 Olifants N/A <0.2 <0.2 <0.2 <0.2 Spruit Nylsvley N/A <0.2 <0.2 <0.2 <0.2 BSL N/A <0.2 <0.2 <0.2 <0.2 TO N/A <0.2 <0.2 <0.2 <0.2 TM N/A <0.2 <0.2 <0.2 <0.2 TS N/A N/W <0.2 <0.2 N/W Mosdene N/A <0.2 <0.2 <0.2 N/W Haakdoring N/A <0.2 <0.2 <0.2 <0.2 Moorddrift N/A <0.2 <0.2 <0.2 <0.2

The TWQR for phosphates is listed in table 4.17. Different ranges have been set out for different levels of nutrient loads in a water body. Table 4.17: List of TWQR’s (DWAF, 1996a) Average Summer Inorganic Phosphorus Effects Concentration (µg/l) Oligotrophic conditions; usually moderate levels of species <5 diversity; low productivity with rapid nutrient cycling; no nuisance growth of aquatic plants or blue green algae Mesotrophic conditions; usually high levels of species diversity; usually productive systems; nuisance growth of 5 – 25 aquatic plants and blue green algal blooms; algal blooms usually non toxic Eutrophic conditions; usually low levels of specie diversity; usually highly productive systems, with nuisance growth of 25- 250 aquatic plants and blooms of blue green algae; algal blooms may include species which are toxic to man, livestock and wildlife. Hypertrophic conditions; usually very low levels of species diversity; usually very highly productive system; nuisance >250 growth of aquatic plants and blooms of blue green algae, often including species which are toxic to man, livestock and wildlife.

Table 4.16 indicates the phosphate levels determined in the Nyl River System.

107 Chapter 4: Water Quality Results and Discussion

The maximum value recorded (4540mg/l) was recorded at the STW outflow. This would indicate that the effluent has extremely high phosphate values and the system would thus be hypertrophic in nature. Only one other reading higher than 200mg/l was recorded at the STW. The rest of the readings were less than 200mg/l which would indicate that the entire system is eutrophic, and susceptible to algal blooms and increased aquatic macrophyte growth.

4.4: Total metal concentrations in water samples.

All living organisms need a certain amount of trace elements for effective and proper metabolic functioning (Galvin,1996). The functions of these elements can be varied and include: (1) the role played in physiological processes, (2) their requirement for respiration and gonadal development and (3) their role as an integral part of protein and enzymatic systems (Heath, 1987). Natural waters contain these elements at low concentrations and an increase in the concentrations can lead to an increase in the accumulation by the aquatic organisms (Nussey et al., 1999). Metal levels in water can be either toxic, or non-toxic to aquatic organisms, depending on the metal, concentration and whether the element is an essential element or not. The presence of heavy metals in water becomes harmful when the concentrations present rise above that of the background concentrations found in water and sediment.

Metals enter the natural surface water systems either naturally or via anthropogenic activities. Natural processes include chemical geological weathering and decomposition of biotic matter. Metal concentrations can also be increased by anthropogenic activities such as industrial pollution, agriculture and mining. Industrial pollution is usually point source in nature where as agriculture and mining activities act as diffuse sources of metal contamination (Heath and Claassen, 1999). Mining and industrial effluent are usually the major sources of increased metal concentrations in rivers. There are two factors that contribute to the damaging effect of metals as environmental pollutants namely (1) the inadequacy of biological degradation

108 Chapter 4: Water Quality Results and Discussion of inert metals and (2) the trend of metals to accumulate and largely remain in the aquatic environment (Robinson and Avenant-Oldewage, 1997).

Metals entering fresh water systems could undergo various changes before temporary or final stability is reached. In aqueous solutions metal ions can be complexed with water (hydrated) or associated with organic or inorganic matter through the process of adsorbtion, chemical combination or complex formation (Förstner and Muller, 1973). The ambient water quality determines the actions of these processes, for example a low pH causes some metals (e.g. aluminium) to become more toxic. The species of the metal occurring in the water plays an important role in the bioavailability and toxicity of that metal. The formation of complexes greatly reduces the toxicity of the free metal ion. The final toxicity of the metal is further influenced by the interactions between the pollutant, the developmental stage of the aquatic organism and the interspecies variations in susceptibility to metals (Hellawell, 1986). Table 4.18: Table of the elements scanned using an ICP-MS. Element symbol Li Cr Rb I Ga Pr Yb B Mn Sr W Ge Nd Lu Na Fe Zr Tl Y Sm Hf Mg Co Mo Pb Ru Eu Ta Al Ni Ba Hg Rh Gd Re Si Cu Pd Bi Nb Tb Os K Zn Ag U Te Dy Ir Ca As Cd Be Cs Ho Pt Ti Se Sn P La Er Au V Br Sb Sc Ce Tm Th

From this list of the analysed elements (Table4.18) comparisons were made to the TWQR for aquatic ecosystems. Due to the complex nature of the interactions of metals in water and organisms TWQR’s for most of the elements are not available at this time. Those elements that exceeded the existing TWQR’s will be discussed in this chapter.

Table 4.19 lists the metals for which TWQR’s exist and the specified guideline

109 Chapter 4: Water Quality Results and Discussion values. Ranges are taken from two different sources (1) the DWAF Water Quality Guidelines for Aquatic ecosystems and (2) the CCME Canadian Water Quality Guidelines, where discrepancies occur the lowest value has been used for comparison.

Table 4.19: Guideline values for metal content in aquatic ecosystems.

DWAF 1996a CCME, 1992 (Canadian (Water Quality Water Quality Element Guidelines for Guidelines)

Aquatic Ecosystems)

Al =10mg/l 0.1 mg/l As =10 0.05

=0.25 moderately hard Cd 0.8 water Cr =7 0.002

=0.3 moderately hard Cu 0.002 water Pb =0.5 0.001 Mn 180 Hg =0.04 0.001 Se =2 0.001 Zn =2 0.03

Ten of the 70 elements analysed indicated values above the guideline values set out by DWAF. These elements are listed in Table 4.20, as well as the summary statistics. The statistics are calculated for the sites grouped together each sampling period and not for each individual site. It is however important to note that these are total metal concentrations and not the dissolved concentration. It also does not differentiate between the more toxic species of the metals e.g. total chromium and not chromium VI.

110 Chapter 4: Water Quality Results and Discussion

Table 4.20: Table of summary statistics for metal concentrations in water

(mg/l). TWQR values are indicated below the metals name.

Aug-01 Nov-01 Mar-02 Jul-02 Average 779.83 1047.33 228.50 16.17 Stdev ± 253.19 ± 552.73 ±119.17 ± 28.81 Aluminium 25th percentile 681.25 639.00 171.00 0.00 =10mg/l 75th percentile 945.25 1343.75 257.75 19.50 Maximum 1144.00 2089.00 598.00 97.00 Minimum 0.00 313.00 0.00 0.00 Average 403.72 42.56 41.78 0.00 Stdev ± 1119.29 ± 12.46 ± 10.64 ± 0.00 Chromium 25th percentile 0.00 33.25 43.00 0.00 =7 75th percentile 11.75 47.75 45.75 0.00 Maximum 3679.00 71.00 48.00 0.00 Minimum 0.00 26.00 0.00 0.00 Average 243.83 111.11 407.11 63.67 Stdev ± 682.97 ± 91.93 ± 1164.78 ± 98.58 Manganese 25th percentile 5.25 49.50 52.75 11.25 180 75th percentile 25.00 136.00 185.75 57.50 Maximum 2882.00 343.00 5047.00 348.00 Minimum 0.00 29.00 0.00 0.00 Average 1578.94 3053.56 2815.17 376.17

Iron Stdev ± 3709.14 ± 1988.45 ± 4425.11 ± 548.40 25th percentile 0.00 1780.25 1061.75 120.00

75th percentile 216.25 3758.25 2540.75 389.00 Maximum 13310.00 9306.00 19901.00 2321.00 Minimum 0.00 852.00 0.00 0.00 Average 21.06 53.67 3.17 1.17 Copper Stdev ± 42.28 ± 168.79 ± 1.50 ± 1.34 =0.3 25th percentile 4.25 7.50 2.25 0.00 moderately 75th percentile 9.00 18.75 3.75 1.75 hard water Maximum 151.00 729.00 7.00 4.00 Minimum 0.00 4.00 0.00 0.00 Average 520.50 438.33 111.94 1.28 Stdev ± 496.10 ± 264.28 ± 28.50 ± 5.42 Zinc 25th percentile 114.25 189.50 112.25 0.00 =2 75th percentile 1037.00 692.25 121.75 0.00 Maximum 1350.00 871.00 130.00 23.00 Minimum 0.00 132.00 0.00 0.00 Average 25.22 8.17 1.22 0.78 Stdev ± 23.50 ± 6.65 ± 1.06 ± 1.35 Arsenic 25th percentile 11.25 3.25 0.25 0.00 =10 75th percentile 25.00 10.75 2.00 1.50 Maximum 79.00 25.00 4.00 4.00 Minimum 0.00 1.00 0.00 0.00

111 Chapter 4: Water Quality Results and Discussion

Table 4.20 cont: Average 3.94 2.00 6.17 2.39 Stdev ± 2.44 ± 1.41 ± 2.57 ± 2.00 Selenium 25th percentile 3.00 1.00 5.00 1.00 =2 75th percentile 4.75 3.00 7.00 3.00 Maximum 10.00 5.00 11.00 7.00 Minimum 0.00 0.00 0.00 0.00 Average 21.33 0.00 0.00 0.00 Cadmium Stdev ± 5.39 ± 0.00 ± 0.00 ± 0.00 =0.25 25th percentile 22.00 0.00 0.00 0.00 moderately 75th percentile 23.00 0.00 0.00 0.00 hard water Maximum 24.00 0.00 0.00 0.00 Minimum 0.00 0.00 0.00 0.00 Average 38.11 72.06 7.22 2.06 Stdev ± 19.75 ± 32.40 ± 2.05 ± 0.87 Lead 25th percentile 26.75 47.50 7.00 2.00 =0.5 75th percentile 48.25 82.50 8.00 2.75 Maximum 89.00 175.00 10.00 3.00 Minimum 0.00 43.00 0.00 0.00

Aluminium

Aluminium is a metal that is strongly dependent on pH. In the soluble state it forms the highly toxic hexahydrate form. Developmental stage and organism species determines the toxicity of aluminium. It can have the following possible deleterious effects on organisms, (1) interference with osmotic and ionic balance, (2) respiratory defects as a result of coagulation of mucous on the gills, (3) interference with the functioning of calcium regulating proteins, and (4) calcium metabolism in the brain and other organs (DWAF, 1996a). Aluminium toxicity increases as the water pH decreases (Savory and Wills, 1991). Possible sources of aluminium are industrial effluents and aluminium is used as a flocculent in the purification of drinking water (Kempster et al., 1980).

Aluminium concentrations (Figures 4.24 A-F) ranged between 2089mg/l at the source of the TO during November 2001 to a lowest recorded value of 18mg/l, at the source of the Groot Nyl River (GNO), in July 2002. Various

112 Chapter 4: Water Quality Results and Discussion readings below detection limits were recorded during July 2002 with July 2002 having lower readings than the other sampling months. November 2001 had the highest recorded aluminium concentrations. Although aluminium concentrations were high they are much lower than aluminium levels recorded in the upper catchment of the Olifants River during the autumn of 1994. A comparison of the levels (2089mg/l as opposed to 43 680mg/l) indicates that the levels are almost one twentieth of those found in the upper catchment of the Olifants River (Van Vuren et al., 1999). Average aluminium levels recorded during the low flow period between August and November 2001 (913.58mg/l) were also found to be lower than the average low flow level (8840mg/l) found in unfiltered water by Greenfield (2001) during a previous study on Nyl River. Figures 4.24 A-F indicate that all the aluminium concentrations recorded were above the TWQR of 10mg/l for aquatic ecosystems.

Chromium

Chromium is a relatively scarce metal that can occur in several states. Chromium VI is the most toxic state. It is the highly oxidized state of chromium and is highly soluable at all pH ranges. Chromium II and III are the more reduced states of the chromium ion and are seen to be less toxic. In aquatic environments chromous compounds tend to be oxidized to chromic forms, whilst chromium VI can be reduced to form chromium III by heat and the presence of organic matter and reducing agents. Chromium exists in natural waters in three oxidation states. These are however difficult to distinguish due to inter-conversion reactions. The presence of oxydizable organic matter and iron (II) salts encourages reduction to lower and less toxic oxidation states (DWAF, 1996a). Water hardness has a significant effect on the toxicity. Chromium (III) becomes more toxic in soft water (CCME, 1992). The toxicity of fish and invertebrates to chromium is comparable in soft water. Phytoplankton has been shown to be more sensitive to chromium than are fish. According to the Canadian Water Quality Guidelines (CCME, 1992) the

113 Chapter 4: Water Quality Results and Discussion total chromium concentration in water should not exceed 200mg/l.

From the data indicated in Table 4.20 it can be seen that chromium levels ranged between 3679mg/l, at Nylsvley in August 2001, to 26mg/l, at Donkerpoort Dam in November 2001. Various sites throughout the study period however did have readings below detection limits. Although August 2001 had the highest recorded chromium levels it was only at seven of the 18 sampled localities. Chromium levels were however recorded at all eighteen localities during the November 2001 and March 2002 surveys. These levels were however all below the TWQR, for aquatic ecosystems, for both chromium (VI)(70mg/l) and (III)(120mg/l). Chromium levels only seemed to be alarmingly high (3679mg/l) during August 2001.These results are clearly illustrated in figures 4.25 A-F.

Manganese

Manganese is an essential element in animals and plants (Health and Welfare Canada, 1980). Manganese is a functional component in nitrate assimilation and an essential catalyst of numerous enzyme systems in animals, plants and bacteria (DWAF, 1996a). In vertebrates manganese deficiencies can lead to skeletal deformities and a reduction in reproduction processes. High concentrations are toxic and can lead to disturbances in various pathways such as the central nervous system caused by the inhibition of dopamine formation (DWAF, 1996a).

External sources of manganese into the environments include (1) the steel industry and the production of dry cell batteries, (2) the fertilizer industry, (3) the chemical industry and (4) acid mine drainage. Dissolved manganese concentrations are influenced by redox potential, dissolved oxygen, pH and organic matter. In surface waters divalent manganese (Mn2+) is rapidly oxidized to insoluble manganese dioxide (MnO2), which settles out of the water column (DWAF, 1996a).

114 Chapter 4: Water Quality Results and Discussion

In well oxygenated waters manganese levels are lower than in waters with low dissolved oxygen concentrations. This is because most soluble manganese compounds are rapidly oxidised and precipitate out (Galvin, 1996). As the pH in the system decreases the toxicity of manganese increases, as the manganese becomes more prevalent in its ionic state (Wang, 1987). In natural fresh water the manganese concentration rarely exceeds concentrations of 1000mg/l (Hellawell, 1986).

Manganese levels (Figures 4.26 (A-F)) ranged between 5047mg/l, at Mosdene in March 2002, and 3mg/l, at Olifants Spruit in August 2001. For the most part manganese levels were higher during November 2001 and March 2002 (high flow period) than in August 2001 and July 2002 (low flow period). This would indicate that manganese levels are higher during the rainy season and that the increased water flow released manganese that has precipitated out during periods of low to no flow. The average manganese concentrations for the different sampling months (Table 4.20) would indicate this not to be the case, but high concentrations at Mosdene (2882mg/l) and at (TM) (639mg/l) have skewed the August 2001 average concentrations. The same applies for the Mosdene reading (5047mg/l) during November 2001. Figures 4.26 (A-F) illustrate the localities that indicated readings above the TWQR (180mg/l). These readings show no clear trend as to increases and decreases in manganese concentrations, although Mosdene, Jasper, Nylsvley, Abba, KNO and (TM) indicate the sites with high levels of manganese compared to the TWQR for aquatic ecosystems.

Iron

115 Chapter 4: Water Quality Results and Discussion

On the basis of limited toxicity and bioavailability iron is classified as a non- critical element. Two common oxidation states are found in water namely: divalent ferrous iron (Fe2+) and trivalent ferric iron (Fe3+) (DWAF, 1996a). Iron is present in natural waters in varying quantities depending on the geological makeup of the specific region (Train, 1979). Iron originates in natural waters via rock dissolution and via the anthropogenic activities of steel production and other industrial waste waters (Galvin, 1996). The main source of iron entering the study area through human activities is via effluent from sewage treatment works (DWAF, 1996a). Iron is readily oxidized and at high concentrations may lead to oxygen depletion in the water (Dallas and Day, 1993). In natural fresh waters total iron is found at levels between 500- 50000mg/l (WHO, 1993). In surface waters iron is generally in the trivalent form ranging between 100 and 300mg/l, this is due to the precipitation of

Fe(OH)3 at pH 7.5 and lower. Divalent salts start to precipitate out at pH 6 and lower (Galvin, 1996). In organic rich waters, such as waters in wetlands, divalent iron and the organic matter form stable Fe2+-organic matter complexes, which cause serious problems in the subsequent treatment of these waters (Galvin and Mellado, 1993).

Iron is an essential element and is required in respiratory enzymes of all organisms. It makes up the basic component of the haeme containing respiratory pigment (haemoglobin), and is present in cytochromes and several redox enzymes. (DWAF, 1996a; Galvin, 1996).

Gills, liver and kidneys are the main accumulation points for iron (Nussey et al., 1999). One of the main toxic actions of iron is that it precipitates on the gill surface causing increased mucous production and suffocation (Muniz and Leivestad, 1980).

Iron concentrations (Figures 4.27 (A-F)) ranged between 19901mg/l, at Mosdene in March 2002, and 110mg/l, at Jasper in July 2002. The averages in table 4.20 for iron indicate that iron levels are higher during November 2001

116 Chapter 4: Water Quality Results and Discussion

(3053.4mg/l) and March 2002 (2815.2mg/l)(High flow periods) than in August 2001 (1578.9mg/l) and July 2002 (376.2mg/l)(low flow periods). The maximum concentration of total iron recorded (19900mg/l) falls within the range indicated by Galvin (1996), of between 500 and 50000mg/l, for nature fresh water. Figures 4.27 (A-F) illustrate the high levels of iron in the water and the non-uniform nature of the peaks obtained in the water sampled.

Copper

Copper is a common environmental metal and is found in the Cu+, Cu2+ and Cu3+ oxidation states. It is an essential metal in cellular metabolism, but is also potentially highly toxic to fish (Grosell et al., 1997). The toxicity of copper in water is largely attributed to mono-valent (Cu+) and CuOH+, which is present in small quantities in fresh water. Divalent (Cu2+) ions are rarely found in the loose form in water as they bind rapidly to inorganic and organic substances and can be adsorbed to particulate matter (Robinson and Avenant-Oldewage, 1997)

Copper dissociates in acidic conditions to the Cu2+ form and thus the toxicity of copper increases as the pH decreases (Benedetti et al., 1989). In alkaline conditions it tends to precipitate out of water (Grosell et al., 1997). Toxicity of copper increases in water when (1) there is a reduction in water hardness, (2) there is a decrease in dissolved oxygen concentrations, and (3) it acts synergistically with other elements found in the water column (DWAF, 1996a, Benedetti et al., 1989, EIFAC, 1978).

The toxicity of copper is greater in the presence of zinc than it is as a single toxicant (Scheinberg, 1991). Copper toxicity decreases with an increase in alkalinity. The presence of certain compounds, such as sodium nitrate, sodium nitrite and calcium, can also increase the toxicity of copper to fish (DWAF, 1996a).

117 Chapter 4: Water Quality Results and Discussion

Copper enters the environment through the oxidation of sediment, but heavy increases are due to anthropogenic activities. The main routes of copper into the environment with respect to this study are: (1) sewage treatment effluent, (2) aquatic algaecides, (3) the runoff from fungicides and pesticides from agricultural land use, and (4) the manufacturing and use of fertilizers (Kotze et al., 1999, Nussey et al., 1999). Copper compounds such as copper sulphate are effective in the treatment of water to eliminate algae and micro-organisms such as E. coli. This action is made possible by the copper obstructing the micro-organisms membrane wall preventing oxygen uptake. Moderate levels of copper in the water can have negative effects on fish (Galvin, 1996).

Copper is an essential element that aids in bone formation, maintenance of myelin and the synthesis of haemoglobin (Nussey et al., 1999). Its accumulation has a specific pattern of uptake namely liver > gills > skin and muscle (Kotze et al., 1999). Copper accumulation takes place across the gills and through the digestion of food and sediment. In the food chain, tolerant plants and invertebrates may accumulate copper posing a risk to organisms higher up in the food chain. About half the ingested copper is excreted in the faeces (Scheinberg, 1991). In comparable ecosystems water plants accumulate up to three times more copper than terrestrial plants.

The copper concentrations ranged between 729mg/l, at Jasper during November 2001, and below detection limits, at both the sources of the Groot and Klein Nyl Rivers during July 2002. Table 4.20 indicates that August 2001 and November 2001 have higher copper concentrations than March and July 2002. This would indicate that the copper concentrations are not season related but rather temporally. Figures 4.28 (A-F) illustrates that all recorded concentrations of copper were above the TWQR of 0.3mg/l. The recorded copper levels in the system were all high but one must remember that they were read in unfiltered water samples.

Zinc

118 Chapter 4: Water Quality Results and Discussion

Zinc is an essential micronutrient for all organisms because it forms the active site for various metaloenzymes (DWAF, 1996a). It is also essential for life (Sola and Duran, 1994). Zinc occurs in water in two oxidation states namely: as the metal and as a divalent zinc ion (Zn2+). It is the divalent form in water that is toxic to fish and aquatic organisms (DWAF, 1996a). Zinc in waters is usually low being detected as inorganic, ionic or colloidal compounds. In this way the mean values of zinc in surface waters are usually lower than 10mg/l (Galvin, 1996). Zinc chloride and zinc sulphates in water react with dissolved carbon dioxide yielding hydroxides and carbonates which are adsorbed onto sediments and muds of river beds or lakes (Galvin, 1996).

Zinc has an antagonistic and toxic effect in the uptake of cadmium. It helps in the synthesis of metallothionines, which bind to cadmium ions to detoxify them (Kargin and Çoèun, 1999). According to Kargin and Çoèun (1999) Zn2+ ions may inhibit the uptake of cadmium by the gills but increases the movement of cadmium to the internal organs. The antagonistic effect of zinc arises due to the competition between Zn and Cd for protein binding sites.

Gills are usually the first organs to be affected by metal pollution due to their direct contact with the water (Hogstrand et al., 1994). Zinc causes death to the fish as it destroys the gill tissue. Acute increases in water borne Zn2+ concentrations impairs branchial calcium influx. This causes hypocalcaemia by inhibiting Ca2+ transporting ATPase in baso-lateral membranes of chloride cells. Zinc is essential for maintaining structure and functioning of cell membranes. It binds to the plasma and internal membranes to stabilize them (Viarengo, 1988). It also plays a role in biological functions such as enzyme activity, nucleic acid metabolism, protein synthesis and hormone activity (Ohnesorge and Wilhelm, 1991).

Zinc shows the greatest bioconcentration factor in skin and bone although the liver, gills and kidney also accumulate it to a considerable extent (Heath,

119 Chapter 4: Water Quality Results and Discussion

1987). The LC50 value for zinc is higher in warm water than in cold water but fish are more sensitive to zinc at cold temperatures. At increased temperatures there is an increased concentration of zinc in the gills (Rattner and Heath, 1995). Water hardness also plays a role in zinc toxicity. As the water hardness increases the zinc uptake rate across the gills decreases thus reducing zinc caused mortality in fish. Toxicity also increases as the quantity of dissolved oxygen decreases (Rattner and Heath, 1995). Copper increases zinc toxicity in soft water and prolonged exposure can cause liver necrosis (DWAF, 1996a).

Zinc concentrations (Figures 4.29 (A-F)) ranged between 1350mg/l, at Mosdene in August 2002, and 23mg/l at KIN in July 2003. Average zinc concentrations were higher during August 2002 and November 2002 than those recorded in March 2003 and July 2003. This would indicate that the good rainy season experienced at the end of 2002 had a flushing effect on the system. All zinc concentrations recorded were above the TWQR of 2mg/l. Table 4.20 indicates the summary statistics for zinc in the water of the Nyl River system. The statistics for July 2003 indicate average zinc concentrations below the TWQR, Figures 4.29 (A-F) illustrate the spatial and temporal fluctuations in zinc concentrations and their deviation from the TWQR.

Arsenic

Arsenic is a metalloid element (Rodriguez et al., 2003). It is an analyte of high concern to the scientific community due to its toxic properties (Pizzaro et al., 2003). Arsenic is widely distributed as a trace constituent in rocks and soils, natural waters and organisms. It can be mobilized mainly by weathering and microbial activities (Garcia-Sanchez and Alvarez-Ayuso, 2003). Arsenic may enter the natural environment via either point source or diffuse sources (Carbonell et al., 1998). Anthropogenic activities that can lead to an increase in arsenic levels include (1) agricultural use of pesticides and fertilizers, (2) mining wastes, (3) industrial processes and (4) mineral debris (Rodriguez et

120 Chapter 4: Water Quality Results and Discussion al., 2003; Garcia-Sanchez and Alvarez-Ayuso, 2003).

Arsenic concentrations found in natural waters range from less than 0.5mg/l to more than 5000mg/l (Huang et al., 2003). Arsenic has effects on the functioning of the central nervous system, genotoxicity and cell disruption (Rodriguez et al., 2003). Arsenic is also carcinogenic, mutagenic and teratogenic (Newman and McIntosh, 1991). Arsenic, although toxic, can also play a role in the conversion of methionine to its metabolites taurine, labile methyl and possibly the polyamines (Rodriguez et al., 2003). Arsenical compounds may also be used to treat trypanosomiasis. In fish arsenical compounds can have effects on fish embryos causing skeletal malformations at concentrations as low as 250mg/l (Newman and McIntosh, 1991).

Arsenic concentrations (Figures 4.29 (A-F)) ranged between 79mg/l, at Mosdene in August 2002, and below detection limits at various localities. The average arsenic concentrations (Table 4.20) indicate that August 2002 had the highest average concentration of 25.22mg/l. This average concentration is higher than the TWQR of 10mg/l for aquatic ecosystems. The other localities all had average concentrations below the TWQR. Results indicate that August 2002 and November 2002 had significantly higher average arsenic concentrations than March 2003 and July 2003. This could be attributed to the flushing effect that the good rainy season had on the March and July sampling period. Arsenic concentrations approximately five times greater than the TWQR were experienced at four localities during August 2002. The sites KIN and KNO are situated at the source of the Klein Nyl River and these high concentrations could be attributed to natural arsenic levels. The sites situated at the Nylstroom/Modimolle Sewage Treatment Works and Mosdene may be seen as point sources of arsenic pollution. Figures 4.30 (A-F) illustrate the spatial and temporal arsenic levels throughout the study area and their deviations from the TWQR.

Cadmium

121 Chapter 4: Water Quality Results and Discussion

Cadmium is a non-essential volatile trace element. In natural waters it occurs primarily as a divalent ion (Cd2+), cadmium chloride and cadmium carbonate. Cadmium enters the environment via a number of anthropogenic activities. The ones most prevalent to this system are via (1) Sewage sludge, (2) Fertilizers and (3) Pesticides (DWAF, 1996a).

Cadmium toxicity increases as temperature increases due to the suppression of calcium ions by the cadmium ions. Cadmium suppresses ventilation in catfish but causes elevation in gill ventilation in most other fish species. Cadmium precipitates in hard waters (Rattner and Heath, 1995). As pH decreases the toxicity of cadmium increases, due to the fact that cadmium is highly soluble in acidified waters (DWAF, 1996a).

Cadmium accumulation takes place in the kidneys, liver, gastro-intestinal tract and gills. It does not accumulate in muscle tissue. It can be excreted via the faeces of organisms (Spry and Wiener, 1991). The toxic effects of cadmium are worsened by the fact that it has a long half-life. This means that it stays in the tissues for a long time after accumulation thus making it available for longer periods of time to prospective predators (WHO, 1992).

Cadmium causes decreased growth rates and can have negative effects on embryonic development (Newman and McIntosh, 1991). Cadmium has various physiological effects, and can cause anaemia due to the destruction of red blood cells. It also causes a disturbance in renal functioning by obstructing the renal tubes. It can cause hypocalcaemia, which is the destruction of skeletal bones (Larsson et al., 1994). Another physiological effect of cadmium is the interruption of ionic balance by altering the permeability of cell membranes. It affects the passive movement and active transport processes by inhibiting Na and K ATPases. This toxicant also displaces the beneficial metals from their active binding sites of enzymes and binds to the deactivating site on the molecule (Viarengo, 1985).

122 Chapter 4: Water Quality Results and Discussion

Fish can survive and accumulate high levels of cadmium in the liver. The cadmium is immobilized to a non-toxic form by the formation of Cd-thionien complex (Carpene et al., 1987). Bioavailability of cadmium to benthic organisms is limited by its strong adsorption to environmental components such as sediment and organic matter (Sanders et al., 1999).

Cadmium concentrations (Figures 4.31 (A-F)) during August 2002 ranged between 24mg/l, at Abba and HSW, and 21mg/l, at GNO and KIN. The site located at TS had a zero reading as it was dry. All the readings obtained for August 2002 were above the TWQR (0.25mg/l) for aquatic ecosystems. This however is no cause for concern as the cadmium levels are very similar throughout the system with the average for the system being 21.3mg/l ± 2.6mg/l and the sources of the Groot and Klein Nyls Rivers having concentrations of 21mg/l and 22mg/l respectively. Figures 4.31 (A-F) illustrate the uniformity of cadmium concentrations recorded during August 2002, and the lack of readings for the other sampling months.

Lead

Lead is a ubiquitous non-essential trace element (Ewers and Schlipkoter, 1991). It exists in several oxidation states namely, Pb, Pb+, Pb2+ and Pb4+. Divalent lead (Pb2+) is the most toxic form and is bio-accumulated by aquatic organisms. It enters the environment via a number of different ways namely: (1) Combustion of fossil fuels, (2) Industrial and municipal waste, (3) Precipitation fall out and (4) Street runoff (DWAF, 1996a; Manahan, 1993).

Lead pollution is localized near points of discharge due to its low solubility. The bioavailability of Pb2+ increases as pH decreases. An increase in water hardness decreases the toxicity of lead. Lead toxicity increases with decreased dissolved oxygen in the water. The toxicity of lead is also dependent on the life stage of the organism and the presence of organic material (Hellawell, 1986). In South African surface waters lead is usually

123 Chapter 4: Water Quality Results and Discussion particulate in form and this results in a decreased bioavailability to fish (Seymore et al., 1995). Uptake of lead usually takes place across the gills (Coetzee, 1996). Animal exposure experiments have shown that lead is a renal and vascular poison (Browning, 1961). Lead poisoning in the wild have been said to be the cause of central nervous disorders, motor abnormalities and blindness (Ewers and Schlipkoter, 1991). Low levels of lead affect fish by causing the formation of a thin film of mucous over the gills and subsequently the entire body. Death of the fish is then caused by suffocation. Lead does not appear to bio magnify through the food web (DWAF, 1996a).

Lead concentrations ranged between 175mg/l, at the STW in November 2002, and 2mg/l at various sites during July 2003. August and November 2002 indicate average lead concentrations higher than those recorded during March and July 2003. This can be attributed to the good rainy season experienced and the resultant increased street runoff. Lead levels in 2002 were significantly higher than those recorded in 2003. All lead concentrations recorded were far above the TWQR (0.5mg/l) for aquatic ecosystems. The increased levels experienced (Figures 4.32A-F) in November 2002 can be attributed to the washing effect of run off from the roads around the urban areas as well as the old and new N1 north. Although runoff increased the lead levels in the water the sources of the Groot and Klein Nyl Rivers as well as the tributaries indicate relatively high natural lead concentrations.

Selenium

Selenium is a metalloid element similar to sulphur. It occurs in many forms but the tetravalent form is the most common form found. Small quantities are essential to animals and bacteria to help in the functioning of certain enzymatic systems (DWAF, 1996a). Selenium has not been recognised as an essential element for plants (Cao et al., 2001). Selenium occurs naturally in various rock types. It may enter the water body by mechanical & chemical weathering of the rocks and by the deposition of organic compounds from

124 Chapter 4: Water Quality Results and Discussion decaying plant matter (DWAF, 1996a). In natural waters selenium usually occurs in nanogram quantities. The organic form of selenium is more toxic than the inorganic form (Newman and McIntosh, 1991). Selenium is an important element to ecotoxicologists due to its protective effects it has on the toxicity of certain heavy metals such as mercury and cadmium (Bhattacharya et al., 2003).

Selenium levels can also enter the environment via anthropogenic activities. These activities include industrial activities and agricultural activities (Liu et al., 1987). Industrial activities that lead to increased selenium levels in the environment include (1) the paint industry, (2) the food processing industry, (3) the steel industry, (4) the pesticide manufacturing industry and (5) the combustion of fossil fuels during the smelting process and the operation of coal fired power plants (DWAF, 1996a; Bhattacharya et al., 2003).

Selenium is a very toxic element to cells when it occurs over critical levels (Cao et al., 2001). Its toxicity to fish is directly related to water temperature. pH decreases in the water column decrease the toxicity of selenium. This is because it becomes less soluble as the pH decreases and hence pH has little effect on selenium toxicity (DWAF, 1996a). Toxic effects of selenium include changes in feeding behaviour, skeletal anomalies in offspring, decreases growth rates and eventually death (DWAF, 1996a, Newman and McIntosh, 1991). Selenium however at the right levels can increase an animal’s resistance to some diseases and cancers (Cao et al., 2001).

Selenium concentrations (Figures 4.33 A-F) ranged between 11mg/l, at BSL in March 2003, and below detection limits, at various sites throughout the system. The summary statistics (Table 4.20) indicate that November 2002 had the lowest average selenium levels (2mg/l) and that March 2003 (6.17mg/l) had the highest. During the August 2002 and March 2003 sampling months most of the sites had selenium concentrations above the TWQR value of 2mg/l. Mosdene, DPD and Abba showed selenium concentrations below the

125 Chapter 4: Water Quality Results and Discussion

TWQR during August 2002 and no site indicated (Figures 4.33 A-F) values below the TWQR for March 2003. Average concentrations equal to of slightly higher were recorded during November and July (2mg/l and 2.3mg/l respectively). This would indicate that selenium levels during these months were acceptable. The higher levels experienced during August and March could be attributed to a few factors. These factors could be (1) increased use of pesticides in agricultural activities, (2) increased combustion of fossil fuels in informal settlements during winter months and (3) increased weathering of the surrounding geology.

126 Chapter 4: Water Quality Results and Discussion

A B

1500 1500 August 2001 August 2001 November 2001 July 2002 1000 1000 March 2002 November 2001 July 2002 March 2002 500 500 Al concentration (ug/l) Al concentration (ug/l) TWQR 0 TWQR 0

KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

1000 1000 August 2001 August 2001 November 2001 November 2001 March 2002 March 2002

500 July 2002 500 July 2002

Al concentration (ug/l) TWQR 0 Al concentration (ug/l) TWQR 0

STW JASPER HSW OLIFANT SPRUIT NYLSVLEY BSL Locality Locality

E F

3000 2000 August 2001 August 2001 2500 November 2001 November 2001 1500 2000 March 2002 March 2002 July 2002 July 2002 1500 1000

1000 500 500 Al concentration (ug/l) Al concentration (ug/l)

TWQR 0 TWQR 0 TO TM TS MOSDENE HAAKDORING MOORDDRIFT Locality Locality

Figures 4.24 (A-F): Spatial and temporal representations of total aluminium (mg/l) concentrations recorded in the water.

127 Chapter 4: Water Quality Results and Discussion

A B

4000 50 3000 August 2001 August 2001 2000 November 2001 40 November 2001 50 March 2002 March 2002 40 July 2002 30 July 2002 30 20 20 TWQR 10 TWQR 10 Cr concentration (ug/l) Cr concentration (ug/l) 0 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

75 4000 August 2001 3000 August 2001 November 2001 2000 November 2001 100 50 March 2002 March 2002 July 2002 July 2002

50 25

TWQR Cr concentration (ug/l) Cr concentration (ug/l) 0 0 STW JASPER HSW OLIFANTS SPRUIT NYLSVLEY BSL Locality Locality

E F

300 50 250 August 2001 August 2001 200 150 November 2001 November 2001 50 March 2002 March 2002 July 2002 July 2002 25 25 TWQR TWQR Cr concentration (ug/l) Cr concentration (ug/l) 0 0 TO TM TS MOSDENE HAAKDORINGMOORDDRIFT Locality Locality

Figures 4.25 (A-F): Spatial and temporal representations of total chromium concentrations (mg/l) recorded in the water.

128 Chapter 4: Water Quality Results and Discussion

A B

500 200 August 2001 TWQR August 2001 November 2001 November 2001 150 350 March 2002 March 2002 July 2002 July 2002 200 100 TWQR 150 100 50

Mn concentration (ug/l) 50 Mn concentration (ug/l) 0 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

400 350 August 2001 August 2001 November 2001 300 November 2001 300 March 2002 250 March 2002 July 2002 200 July 2002 200 200 TWQR TWQR

100 100 Mn concentration (ug/l) Mn concentration (ug/l) 0 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

700 5500 August 2001 5000 August 2001 600 4500 November 2001 4000 November 2001 500 3500 March 2002 3000 March 2002 400 2500 July 2002 2000 July 2002 200 300 TWQR 250 200 TWQR 100 150 100

Mn concentration (ug/l) Mn concentration (ug/l) 50 0 0 TO TM TS MOSDENE HAAKDORING MOORDDRIFT Locality Locality

Figures 4.26 (A-F): Spatial and temporal representations of total manganese (mg/l) concentrations recorded in the water.

129 Chapter 4: Water Quality Results and Discussion

A B

15000 3000 August 2001 August 2001 12500 November 2001 November 2001 10000 March 2002 2000 March 2002 7500 July 2002 July 2002 5000 4000 1000 3000 2000 Fe concentration (ug/l) Fe concentration (ug/l) 1000 0 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

7500 10000 August 2001 August 2001 November 2001 November 2001 7500 5000 March 2002 March 2002 July 2002 July 2002 5000

2500 2500 Fe concentration (ug/l) Fe concentration (ug/l) 0 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

3000 20000 August 2001 17500 August 2001 November 2001 15000 November 2001 2000 March 2002 12500 March 2002 July 2002 10000 July 2002 5000 4000 1000 3000 2000 Fe concentration (ug/l) Fe concentration (ug/l) 1000 0 0 TO TM TS MOSDENE HAAKDORING MOORDDRIFT Locality Locality

Figures 4.27 (A-F): Spatial and temporal representations of total iron concentrations (mg/l) recorded in the water.

130 Chapter 4: Water Quality Results and Discussion

A B

120 20.0 August 2001 August 2001 110 17.5 100 November 2001 15.0 November 2001 90 March 2002 March 2002 80 12.5 25 July 2002 10.0 July 2002 20 5 15 4 10 3 8 6 2 4 Cu concentration (ug/l) 2 Cu concentration (ug/l) 1 TWQR 0 TWQR 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

800 200 600 August 2001 180 August 2001 400 November 2001 160 November 2001 15 March 2002 140 March 2002 12 July 2002 45 July 2002 35 9 25 6 15 5 4 3 3

Cu concentration (ug/l) Cu concentration (ug/l) 2 1 TWQR 0 TWQR 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

25.0 30 22.5 August 2001 25 August 2001 20.0 November 2001 20 November 2001 15 15 March 2002 10 March 2002 12 July 2002 5 July 2002 4 9 3 6 2 3 1 Cu concentration (ug/l) Cu concentration (ug/l) TWQR 0 TWQR 0 TO TM TS MOSDENE HAAKDORINGMOORDDRIFT Locality Locality

Figures 4.28 (A-F): Spatial and temporal representations of total copper concentrations (mg/l) recorded in the water.

131 Chapter 4: Water Quality Results and Discussion

A B 1100 20 1000 August 2001 August 2001 900 November 2001 November 2001 800 March 2002 March 2002 400 July 2002 July 2002 250 10 100 30 20

Zn concentration (ug/l) 10 Zn concentration (ug/l) TWQR TWQR 0 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

800 160 August 2001 150 August 2001 750 November 2001 140 November 2001 March 2002 45 March 2002 July 2002 July 2002 700 30 15 15 10 5.0

5

Zn concentration (ug/l) Zn concentration (ug/l) 2.5 TWQR TWQR 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

30 30 August 2001 August 2001 November 2001 November 2001

20 March 2002 20 March 2002 July 2002 July 2002

10 10

Zn concentration (ug/l) TWQR Zn concentration (ug/l) TWQR 0 0 TO TM TS MOSDENE HAAKDORINGMOORDDRIFT Locality Locality

Figures 4.29 (A-F): Spatial and temporal representations of total zinc concentrations (mg/l) recorded in the water.

132 Chapter 4: Water Quality Results and Discussion

A B

70 15 August 2001 August 2001 60 November 2001 November 2001 50 March 2002 TWQR March 2002 40 July 2002 July 2002 25 20 15 5 TWQR

As concentration (ug/l) 5 As concentration (ug/l) 0 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

70 20 August 2001 August 2001 60 November 2001 November 2001 15 50 March 2002 March 2002 40 July 2002 July 2002 15 TWQR

TWQR 5 5 As concentration (ug/l) As concentration (ug/l) 0 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

20 80 August 2001 August 2001 70 November 2001 November 2001 15 March 2002 60 March 2002 July 2002 50 July 2002 TWQR 25 20 15 5 TWQR

As concentration (ug/l) As concentration (ug/l) 5 0 0 TO TM TS MOSDENE HAAKDORINGMOORDDRIFT Locality Locality

Figures 4.30 (A-F): Spatial and temporal representations of total arsenic concentrations (mg/l) recorded in the water.

133 Chapter 4: Water Quality Results and Discussion

A B

30 30 August 2001 August 2001 25 November 2001 November 2001

20 March 2002 20 March 2002 July 2002 July 2002 15

10 10

5 Cd concentration (ug/l) Cd concentration (ug/l) TWQR 0 TWQR 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

30 30 August 2001 August 2001 November 2001 November 2001 March 2002 March 2002 20 20 July 2002 July 2002

10 10 Cd concentration (ug/l) Cd concentration (ug/l) TWQR 0 TWQR 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

30 30 August 2001 August 2001 November 2001 November 2001 20 March 2002 20 March 2002 July 2002 July 2002

10 10 Cd concentration (ug/l) Cd concentration (ug/l) TWQR 0 TWQR 0 TO TM TS MOSDENE HAAKDORING MOORDDRIFT Locality Locality

Figures 4.31 (A-F): Spatial and temporal representations of total cadmium concentrations (mg/l) recorded in the water.

134 Chapter 4: Water Quality Results and Discussion

A B

90 60 August 2001 August 2001 80 50 November 2001 November 2001 70 March 2002 40 March 2002 60 July 2002 July 2002 60 10 50 40 30 8 20 6 5 4 4 3

Pb concentration (ug/l) 2 Pb concentration (ug/l) 2 1 TWQR 0 TWQR 0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

180 120 170 August 2001 August 2001 160 110 150 November 2001 100 November 2001 140 88 70 March 2002 March 2002 60 July 2002 58 July 2002 50 40 28 30 8 8 6 6 4 4 Pb concentration (ug/l) 2 Pb concentration (ug/l) 2 TWQR 0 TWQR 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

100 90 90 August 2001 August 2001 80 November 2001 60 November 2001 70 60 March 2002 March 2002 50 July 2002 30 July 2002 10 10 8 8 6 6 4 4

Pb concentration (ug/l) 2 Pb concentration (ug/l) 2 TWQR 0 TWQR 0 TO TM TS MOSDENE HAAKDORINGMOORDDRIFT Locality Locality

Figures 4.32 (A-F): Spatial and temporal representations of total lead concentrations (mg/l) recorded in the water.

135 Chapter 4: Water Quality Results and Discussion

A B

10.0 7.5 August 2001 August 2001 November 2001 November 2001 7.5 March 2002 5.0 March 2002 July 2002 July 2002 5.0

2.5 2.5 TWQR TWQR Se concentration (ug/l) Se concentration (ug/l) 0.0 0.0 KIN KNO ABBA DPD GNO DLA DLA Locality Locality

C D

10.0 15 August 2001 August 2001 November 2001 November 2001 7.5 March 2002 10 March 2002 July 2002 July 2002 5.0

5 2.5 TWQR TWQR Se concentration (ug/l) Se concentration (ug/l) 0.0 0 STW JASPER HSW OLIFANTS SPRUITNYLSVLEY BSL Locality Locality

E F

10.0 7.5 August 2001 August 2001 November 2001 November 2001 7.5 March 2002 5.0 March 2002 July 2002 July 2002 5.0

2.5 2.5 TWQR TWQR Se concentration (ug/l) Se concentration (ug/l) 0.0 0.0 TO TM TS MOSDENE HAAKDORINGMOORDDRIFT Locality Locality

Figures 4.33 (A-F): Spatial and temporal representations of total selenium concentrations (mgl) recorded in the water.

136 Chapter 4: Water Quality Results and Discussion

4.5: Bacteriology

Bacteria

One of the functions of a wetland is water filtration. Suspended organic matter and bacteria settle out in a wetland due to the action of gravity on the particles in the slow moving water. Bacteria and pathogens enter the system via leaking sewer lines, sewage effluents and direct input from developing urban and rural areas (Vega et al., 2003), as well as from farm animals.

Bacterial contamination is of great concern as the bacteria and pathogens can contaminate ground water supplies. This is of importance as ground water supplies are the main source of potable water supplies for the future (Vrhovsek et al., 1996). Rodgers et al., (2003) stated that an important but often overlooked aspect of bacterial contamination of water courses is faecal contamination from organic matter via agricultural run off. Faecal coliforms are abundant in the faeces of warm-blooded animals and their presence indicates the potential risk to humans of faecal contamination, bacteria and viral agents. Bacterial water quality in rivers and wetlands is thus essential in planning policy decisions and providing an indication of the health risk posed by faecal contamination (Wilkinson et al., 1995).

A study by Mvungi et al. (2003) on the impact of home industries on water quality concluded that improper waste management practices, sewage overflows and pollutant runoff increased the contaminant and bacterial content of tributaries draining urban areas in Harare. This fact is evident in the results obtained in this study.

The results indicate that the Nylstroom/Modimolle STW has an effect on the bacterial content of the system. From Figures 4.34 (A-C) it is evident that bacterial content of the water increases once the water flows past the STW. Another source of bacteria in the system can be attributed to agricultural run

137 Chapter 4: Water Quality Results and Discussion off from the many cattle farms in the area, as well as run off from the informal settlement of Phagameng.

Total coliforms.

Total coliform counts indicate an increase in number of colonies per 100ml (N/100ml) between Donkerpoort Dam (DPD) and the sewage treatment works (STW) (Figure 4.34 A). This trend is most visible during the April 2001 sampling period, with counts increasing from 35N/100ml to 77000N/ml. The levels then slowly decrease as the water moves through the wetland to the site at Mosdene where the bacterial levels rise sharply once gain. This would indicate that there is a point source of bacterial contamination entering the system upstream from the site. This trend holds true for four of the five sampling periods with March 2002 indicating a different trend. The total coliform decrease experienced between the STW and Nylsvley during the sampling months of April 2001, August 2001, November 2001 and July 2002 can be attributed to one or more of the following factors, (1) dilution factor due to an influx of water from the tributaries HSW and the Olifants Spruit, (2) bacterial breakdown/die off due to changes in water chemistry, (3) bacterial die off due to water temperature changes, and (4) the settling action exerted on bacterial particles bound to particulate organic matter and sediments as the water moves slowly through the wetland system (An et al., 2002; Zaccone et al., 2002, Maul and Cooper, 2000). The increases in total coliform concentrations can be attributed to (1) point sources of contamination e.g. STW and increased run off from cattle farms in the area, (2) increased agricultural run off from precipitation and (3) resuspension of sediments bound to microbes during periods of increased flow (Interlandi and Crockett, 2003; Jagalsa, 1997; An et al., 2002). Fisher et al., (2000) concluded in their study of the Oconee River in Georgia that total coliform number increased with rainfall events but decreased more rapidly in grazed watersheds.

138 Chapter 4: Water Quality Results and Discussion

Table 4.21: Table of the effects of total coliforms on human health (DWAF, 1996c) Total coliforms (counts/100ml) Effects TWQR (0-5) Negligible risk of microbial infection Indicative of inadequate treatment, post contamination or after growth in the water distribution system. Risk of 5-100 infectious disease transmission with continuous exposure and a slight risk with occasional exposure. Indicative of poor treatment, post treatment contamination or definite after growth in the water distribution >100 system. Significant and increasing risk of infectious disease transmission.

Table 4.21 indicates the guideline ranges set out by DWAF for drinking water or domestic use. The results indicate that the total coliform count falls within the lower two classes and that the risk for microbial infection if water from both Mosdene and the STW are ingested is significant and increasing. The other three sites indicate a high risk of infection if water is ingested.

Faecal coliforms

Faecal coliform counts followed similar trends to those of the total coliforms. This is logical as they form part of the total coliform count. Sources of faecal contamination to the system could be attributed to (1) runoff from developed and developing urban areas, (2) agricultural runoff from both cattle and chicken farms as well as from wilderness areas such as game reserves, and (3) sewage effluents. High numbers of coliform bacteria from wilderness areas could account for variation in coliform levels when water quality is otherwise

139 Chapter 4: Water Quality Results and Discussion good (Fisher et al., 2000).

The decreases illustrated in Figure 4.34 B can be attributed to the binding of the microbes to particulate organic matter and sediment particles, and the subsequent settling of the bacteria into the sediment layers of the wetland (Fisher et al., 2000, An et al., 2002). The faecal coliforms however indicated different trends during August 2001, November 2001 and March 2002 with peaks in the trend line occurring at Jasper and not at the STW as is the case with the April sampling period. Studies by Maul and Cooper (2000) and by Newman et al. (2000) showed that standing water and wetlands decrease faecal coliform counts. Faecal coliform counts were all above the recommended TWQR for drinking water (DWAF, 1996c) of 0counts/ 100ml. A maximum faecal coliform count was recorded at the STW in April 2001 of 37500counts/100ml. Faecal coliform guideline values for aquatic ecosystems are not available.

Table 4.22 indicates the DWAF guidelines for domestic use of water. These ranges indicate the different effects that water contaminated with faecal coliforms could have on humans. The water at all of the sites falls outside of the TWQR of 0 counts/100 ml range and pose varying risks to human health from slight risks to significant and increasing risks. Jasper is the site that indicated the highest faecal contamination.

Heterotrophic bacteria are recognised as an important component of the planktonic community contributing significantly to the regulation of the flux of organic matter. They are also a critical link in the microbial loop, which starts with the production of dissolved organic matter and ends with the oxidation to

CO2 (Zaccone et al., 2002). Heterotrophic plate counts are used to test the general microbial quality of the water. They do not represent the total bacterial population present. They do however indicate the efficacy of the water treatment process and indicate if the treatment process is adequate or not (DWAF, 1996c).

140 Chapter 4: Water Quality Results and Discussion

Table 4.22: Table of effects of faecal coliforms to humans (DWAF,1996c).

Faecal coliforms (counts/100ml) Effects

TWQR 0 Negligible risk of microbial infection Slight risk of microbial infection with

0-10 continuous exposure; negligible risk with occasional exposure

Risk of infectious disease transmission with continuous 10-20 exposure; slight risk with occasional exposure. Significant and increasing risk of infectious disease transmission. As >20 faecal coliform levels increase, the amount of water ingested required causing infection decreases.

Heterotrophic Plate Counts

Heterotrophic plate counts of between 100-1000counts/ml indicate that the water has undergone inadequate treatment, post treatment contamination or after growth in the water. There is a slight risk of microbial infection (DWAF, 1996c). The primary role of heterotrophic bacteria is classified as the decomposition and mineralization of dissolved and particulate organic nitrogen. Significant heterotrophic utilization of dissolved inorganic nitrogen would have profound effects on the fluxes of nitrogen and carbon in the water column (Allen et al., 2002). Heterotrophic bacteria include species from many bacterial genera such as the nitrifying bacteria Nitrosomonas, Nitrobacter, and the denitrifying bacteria (Sakai et al., 1997).

Heterotrophic plate counts indicated a different trend (Figure 4.34 C) to that of

141 Chapter 4: Water Quality Results and Discussion the coliform bacteria. All sampling periods indicate the steady increase in bacteria numbers from DPD to Jasper and then the trend lines form a plateau. Heterotrophic plate counts also exceeded the TWQR of 0-100counts/ml except at the DPD site. All the plate counts fell between the ranges of 100- 1000counts/ml. As mentioned earlier in this section, this would indicate that the water entering the system as effluent is not being treated properly. This would also indicate that the water in the system would pose a slight risk to human health. The plateau that is visible in the trend line could indicate a normal trend in wetlands as heterotrophic bacteria play a vital role in the filtration/purification of water. The bacteria help in the reduction of nutrient loads in the water column by oxidising toxic ammonia to nitrites, nitrates and finally nitrogen which is released into the atmosphere (Kupchella and Hyland, 1993).

Table 4.23: Table of effects of heterotrophic bacteria to human health (DWAF, 1996c) Heterotrophic plate count (Counts Effects per ml) TWQR (0-100) Negligible risk of microbial infection Indicative of inadequate treatment, post contamination or after growth in 100-1000 the water distribution system. Slight risk of microbial infection Indicative of poor treatment, post treatment contamination or definite >1000 after growth in the water distribution system. Increased risk of infectious disease transmission.

Table 4.23 indicates the effects of differing heterotrophic bacteria ranges to human health. The water in the system falls within the 100-1000counts/ml range and thus poses a slight risk of microbial infection to humans.

142 Chapter 4: Water Quality Results and Discussion

Due to the nature of the system and the functions of wetlands it could be said that high heterotrophic bacterial content in the water is not a major problem to the system. With the purification process/function of wetlands one would expect to have a relatively high heterotrophic plate count due to the presence of the bacteria needed to complete the different nutrient cycles, and organic matter break down. A high count however could indicate the contamination of the system with nutrients from agricultural activities. The concerning bacterial counts in the system are the high faecal and total coliform counts. These indicate that the system is definitely being contaminated by sewage effluent and agricultural run off from the different farms either game farms or cattle farms.

143 Chapter 4: Water Quality Results and Discussion

A

78000

77000

76000

2100 1600 1100 600 350

300

250

200

Total Coliform Counts / 100ml 150

100

50

TWQR 0 DPD STW JASPER NYLSVLEY MOSDENE Locality 01-Apr 01-Aug 01-Nov Mar-02 02-Jul

B

38000

37500

37000 650

550

450 50

25 Faecal coliform counts /100ml

TWQR DPD STW JASPER NYLSVLEY MOSDENE Locality

01-Apr 01-Aug 01-Nov Mar-02 02-Jul

C

800

700

600

500

400

300

200 Heterotrophic Plate count /ml

TWQR

0 DPD STW JASPER NYLSVLEY MOSDENE Locality 01-Apr 01-Aug 01-Nov Mar-02 02-Jul Figures 4.34: Spatial and temporal representation of total coliform (A), faecal coliform (B) and Heterotrophic (C) counts in the Nyl River System.

144 Chapter 4: Water Quality Results and Discussion

4.6: Toxicity testing

Pollution of the environment means the contamination of soil, air and water. As water is essential for life, its pollution will not only endanger aquatic life, but also terrestrial organisms, including man (Kfir, 1981). Living material responds to the total effect of actual and potential disruptions in the water and therefore, the use of biological toxicity testing has become an important approach to complement chemical analysis to monitor and control harmful chemicals in water (Blaise et al., 1988). Bioassays are used to determine the potential of substances to cause environmental harm, and are sometimes able to elicit responses at concentrations below chemical detection limits (Muller and Palmer, 2002). Bioassays have both advantages and disadvantages and these are listed in Table 4.24.

Table 4.24: Table of advantages and disadvantages to toxicity testing (Muller and Palmer, 2002). Advantages Disadvantages A holistic approach, integrating Tests do not indicate which stressors effects of all stressors (especially are causing the observed effects. useful for investigating whole effluent). Tests can be simple and cost Tests can be too simple and result in effective environmentally unsound answers The effect on the selected Not all organisms, exposures and organism(s) is (are) observed at the end-points can be tested exposure(s) tested Tests are normally carried out under Field conditions are different from controlled laboratory conditions laboratory conditions and extrapolating results from laboratory to field is associated with its own set of complications

145 Chapter 4: Water Quality Results and Discussion

An objective of the standard toxicity test is to assess whether the measured treatment of one end-point is significantly different from the measured end- point in another treatment, usually a control (Denton and Norberg-King, 1996). The aims of toxicity testing are therefore the ability of the test to detect either acute or chronic toxicity of an effluent (Chapman et al., 1996).

The results discussed in this section are reported as LC50 values of the raw water (viz. whole effluent) tested. The results were obtained by calculating the LC50 using the trimmed Spearman Karber test. During the tests the mortalities and various parameters were recorded. During the tests the pH, conductivity, TDS, temperature and oxygen levels were monitored. For the tests to be validated the test conditions were monitored according to the International Standards Organisation (ISO), Institute for Water Quality Studies (IWQS) and the Organisation for Economic Change and Development (OECD) guidelines for static testing (OECD, 1992; Truter,1994, ISO, 1996 IWQS, 1998;). · These guidelines require the test conditions to conform to the following regulations: · Constant conditions must be maintained as far as possible throughout the test. · Dissolved oxygen concentrations should not dip below the 60% saturation level throughout the duration of the test. · The mortality of control organism should not exceed 10%. · The proportion of control organisms showing abnormal behaviour should not exceed 10% of the total number of organisms in the control medium. · Organisms should be healthy with mortalities in holding tanks kept down to a minimum From the results obtained the test conditions conformed to the required test condition specified by the OECD and ISO. Zero mortality was experienced under control conditions. The temperature of the test conditions did not differ by more the 0.5 degrees during the tests and the oxygen concentrations

146 Chapter 4: Water Quality Results and Discussion remained more or less above the 80% saturation level. Table 4.26 indicates the LC50 values that were obtained during both the D. pulex and P. reticulata tests. The results will be discussed according to the different sampling months. Table 4.25 indicates the mortalities recorded during the toxicity testing. A mortality level higher than 20 percent indicates that the water was toxic to the organisms (Slabbert et al., 1998). Mortalities during the August 2001 testing were high with most localities experiencing higher than 20 percent death rate in fish. This however is strange as the LC50 values could not be determined and would indicate that mortalities were caused by an external factor.

Table 4.25: Recorded mortality percentages during Whole Effluent Toxicity testing. Empty block indicate no water present.

Locality Daphnid mortalities P.reticulata mortalities Aug-01 Nov-01 Mar-02 Jul-02 Aug-01 Nov-01 Mar-02 Jul-02 KIN 0 40 80 20 KNO 0 0 0 0 20 0 0 GNO 0 40 0 0 0 20 0 Dladla 0 0 0 0 0 20 40 40 DPD 0 0 0 0 20 0 40 40 STW 0 0 0 0 80 0 40 40 Jasper 40 0 0 0 20 20 0 HSW 0 20 0 0 20 0 20 20 Olifants Spruit 0 20 0 0 60 0 20 20 Nylsvley 0 0 0 0 80 0 0 Mosdene 0 0 20 40 100 0 20 40 BSL 0 20 0 0 80 0 0 Haakdoring 0 0 0 0 40 0 40 40 Moorddrift 0 0 0 0 80 0 0 TO 0 0 0 0 100 0 0 TM 60 40 0 20 100 0 40 0 TS 20 0 0 20 20 20 Abba 0 0 0 0 60 20 0

The daphnid test for August 2001 produced no LC50 values during the tests. This is simply due to the lack of mortality experienced with not enough Daphnia dying to allow Spearman Karber to calculate the LC50 value. The guppy test produced LC50 values ranging between 73.49 percent, at the

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Tobias mine site (TM), and 100 percent at Mosdene and BSL. The confidence limits of these tests are not reliable. Moorddrift, STW, KIN and Nylsvley were the other sites that produced LC50 values but once again the values were not reliable.

From the samples from November 2001, March 2002 and July 2002 no LC50 values could be calculated due to lack of mortalities in both the Daphnia and guppy tests. The only site during November 2001 where an LC50 value was calculable was TM. The LC50 value was 100 percent, but it was not statistically reliable. The only site where an LC50 value was calculable was Moorddrift during July 2002. The LC50 value was calculated at 84.9 percent.

The results from the whole battery of toxicity tests would indicate that the water is relatively non toxic to aquatic organisms during three of the four sampling periods. The water posed little potential threat to maintaining aquatic life during November 2001, March 2002 and July 2002. The water during August 2001 could be considered toxic to the organisms.

148 Chapter 4: Water Quality Results and Discussion

Table 4.26: Table of LC 50 values obtained during the study. Daphnia (Daphnia pulex) Guppy (Poecillia reticulata) Locality LC50 Confidence limits Locality LC 50 Confidence limits Aug-01 Moorddrift 77.11% Not 95% reliable STW 74.3% Not 95% reliable Mosdene 100% Not 95% reliable All sites Not available trim too TM 73.49% Not 95% reliable large BSL 100% Not 95% reliable KIN 82.03% Not 95% reliable Nylsvley 82.03% Not 95% reliable Rest of the Not available trim too sites large Nov-01 TM 100% Not 95% reliable All sites Not available trim too large Rest of sites. Not available trim too large

Mar-02 All sites Not available trim too All sites Not available trim to large large Jul-02 All sites Not available trim too Moorddrift 84.9% large Rest of sites Not available trim too large

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4.7: Integrated water quality

For the integrated water quality analyses, localities were compared to one another based on all water quality variables with the exception of bacteria and toxicity test results. The data was analysed using PRIMER 5 statistics program. The data underwent a principle component analysis (PCA) with the results being plotted on graphs. The PCA’s were conducted for each of the four sampling periods. Data was normalised to give a better comparison between the different localities.

August 2001

Eigen values calculated indicate that 46.8 percent of the variation can be explained by the first two of the components calculated. Principle component one indicates that chromium, manganese, iron, copper, chlorides and oxygen saturation and concentration are causing the variation in water qualities. Principle component two indicates that aluminium, selenium, alkalinity, conductivity and TDS are causing the variability in the water.

This would indicate that the above mentioned variables play a vital role in the system‘s health, and that they are important stressors in the system to be monitored. Figure 4.35 A illustrates the two components plotted on a graph. The X axis depicts the principle component one and the Y axis principle component two. The sites grouped close together indicate water with similar qualities. In Figure 4.35 A the sites grouped together are all situated before the STW at Nylstroom/Modimolle and would thus indicate that the STW has an effect on the water downstream.

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November 2001

The calculated Eigen values indicate that 41.6 percent of the variation can be explained by the first two principle components. Principle component one indicates that the variation in the water is caused by the water parameters and the alkalinity. In component two the metals chromium, iron, zinc, arsenic, and lead are primarily responsible for the variation. Alkalinity also is one of the causes of variation. Figure 4.35 B indicates the graphical representation of the similarities between the sites based on water quality. No definitive grouping was identified, with GNO and DPD are the only sites that show any similarity in the water body.

March 2002

The Eigen values calculated indicate that 43.9 percent of the variation is explained by the first two principle components. In principle component one the aluminium, chromium, lead, chloride, sulphate, pH, conductivity, and TDS are responsible for the spatial variation in the water. In principle component two manganese, iron, zinc, chloride and oxygen saturation and concentration can account for the variation in the water. Figure 4.35 C indicates the spatial graphical representation of the first two principle components. From the figure a group emerges of localities with similar water qualities. This can be due to an increase in water volume or stability in the water column due to less water entering the system via precipitation.

July 2002

The calculated Eigen values indicate that 40.7 percent of the variation in the water quality is explained in the first two components of the principle component analysis. The first component indicates that the water parameters such as (oxygen, pH, Ec, TDS, Nitrates, Nitrites, Sulphates and Orthophosphates) and alkalinity account for the variation in the water. In

151 Chapter 4: Water Quality Results and Discussion principle component two the metals aluminium, manganese, selenium and lead as well as the chlorides and sulphates account for variation in the water. Figure 4.35 D indicates the grouping of the sites with similar water qualities.

A comparison of the graphs (Figures 4.35 A-D) indicates that the site groupings on each graph are similar during three of the four sampling months (August 2001, March 2002 and July 2002) with many of the sites in these groups corresponding. The fourth sampling period (November 2001) is the period that differs. This can be attributed to a change in water stability due to an influx of water from runoff and the associated influx of contaminants. The precipitation causing the influx could also be changing the water chemistry with the associated dilution effect of the addition of large amounts of fresh water to the system. The sites excluded from the grouping are BSl, Haakdoring, Jasper, HSW, TS and Moorddrift.

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A B August 2001 November 2001

C D March 2002 July 2002

Figure 4.35 (A-D): Principle component plot of spatial similarities of water in the system.

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4.8: Present ecological state of the system.

Historical data from the gauging stations that were used to determine the reference condition were obtained from DWAF and used to determine the present ecological state of the system. This data was analyzed using the method set out by Bath et al. (1999b) for the determination of the present ecological status of the system. This method is used in the resource directed measures for a reserve determination. The purpose of this assessment is not to carry out a water quality reserve determination but rather determining the present water quality status based on the changes that have occurred in the system over the last 20 years. Changes determined include the parameters pH, TDS and conductivity as well as nutrients (N:P ratios and ammonia concentrations). The results were then compared to the reference conditions determined in the beginning of this chapter. Table 4.27 indicates the ecological status description of each class assessment.

Table 4.27: Class Assessment Descriptions Class assessment Description A Un-impacted/ pristine B Few modifications C Moderately modified D Largely modified E Greatly modified F

4.8.1 Nutrients

Ammonia

Ammonia is the toxic nitrogen based compound in an aquatic environment. It is present in air soil and water and in large amounts in decomposing organic matter. Ammonia is a common pollutant in water and contributes greatly to

154 Chapter 4: Water Quality Results and Discussion eutrophication in a system (DWAF, 1996a). External sources of un-ionised ammonia include (1) fish farm effluents, (2) sewage discharges, (3) atmospheric deposition of ammonia from the combustion of coal and (4) the biological degradation of manure. Increases in temperature and pH increase the proportion of toxic un-ionized ammonia in solution and hence increase its toxicity to aquatic organisms (DWAF, 1996a).

The ammonia levels at the gauging stations were determined using the water temperature, ammonium levels and Table 4.28. The ammonium concentration was multiplied by the factor given in Table 4.28, for the corresponding water temperature and pH, and divided by 100 to give the proportion of un-ionized ammonia in the water. This concentration was then compared to Table 4.29 and assigned a letter depicting the class range that the water fell in. Table 4.29 gives the different class ratings, ammonia ranges and impact status of a water body.

Table 4.28: Relationship between water temperature, pH and un-ionized ammonia (Bath et al, 1999b). PH Water Temperature in Degrees Celsius 10 15 20 25 30 6.5 0.06 0.09 0.12 0.18 0.25 7 0.18 0.27 0.39 0.56 0.79 7.5 0.58 0.85 1.2 1.7 2.4 8 1.8 2.6 3.8 5.3 7.3 8.5 5.5 7.9 11 15 20

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Table 4.29: Nutrient assessment using the un-ionized ammonia concentration to assign assessment classes for rivers (Bath et al., 1999b). General Assessment Ammonia (un-ionized) classes classes concentration (expressed as mg-

N/l as NH3) Un-impacted A <0.007 B <0.015 Moderately C <0.030 impacted D <0.070 Highly impacted E <0.100 system F >0.100

Nitrogen: Phosphorus (N: P) Ratio

The N:P ratio is the ratio of total inorganic nitrogen (TIN) to orthophosphates (SP). This ratio is determined by calculating the median TIN for the system and the median SP concentrations. These concentrations are then compared to each other to provide a ratio. This ratio is then used along with the SP concentration and Table 4.30 to assign nutrient status classes.

Table 4.30: Assessment of nutrient status based on N:P ratio using only orthophosphate data (Bath et al., 1999b). Total inorganic Nitrogen to Soluble Phosphate Ratio <10:1 >10:1&<20:1 >20:1&<30:1 >30:1 Orthophosphate <0.01 C B A A concentration <0.05 D C B A (expressed in <0.07 E/F D C B mg-P/l) <0.1 F E/F D C >0.1 F F E/F D/E

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Table 4.31 Resultant classes assigned to sites analyzed Historical Present state state Present state

Un-ionised N:P N:P Ammonium. KNO C F A DPD C HSW C F A Olifants Spruit D F A Nylsvley D BSl A F A Tobias Spruit D

The results indicated in Table 4.31 show that although the system was moderately impacted twenty years ago the nutrient levels have increased to a highly impacted state. The present day ammonia levels would however indicate that although the system has been impacted by water nitrification the toxic levels are as un-impacted and the water is thus not harmful to the aquatic organisms.

4.8.2 System variables

For the purpose of this study the TDS and pH were assessed. For TDS the sites were classified using the following method: The median reference condition (RC) was calculated using the data collected earlier on in this chapter (Section 4.1 Historical Data). The median TDS value was also calculated for the present study from March 2001 to March 2003. These values were then substituted into the following equation:

% difference [TDS] = ((TDS median – TDS median RC)/ TDS median RC)*100

Table 4.32 was then used with the percentage difference to assign a class rating to each site. These were then compared to the reference condition to depict the ecological status of the system.

157 Chapter 4: Water Quality Results and Discussion

Reference conditions were calculated for pH previously in this chapter (Section 4.1 Historical Data). These conditions were then compared to the present pH conditions to assign assessment class ratings. For pH the percentage variation was calculated using the following formula:

% pH = ((pH median – pH median RC)/ pH median RC)*100

Assessment classes were then assigned using Table 4. 33.

Table 4.32: System variable assessment for total dissolved solids (TDS) (Bath et al., 1999b) TDS The median TDS concentration Assessment class should not differ from the upstream Reference Condition (RC) by greater than: A 15 percent B 20 percent C 30 percent D 40 percent E and F > 40 percent

Table 4.33: Present ecological state for the assessment of pH in rivers (Bath et al, 1999b) PH:The median pH value should not differ Assessment class from the upstream reference condition (RC) by greater than: A < ± 5 percent B ± 7 percent C ± 10 percent D ± 12 percent E and F > ± 12 percent

158 Chapter 4: Water Quality Results and Discussion

Table 4.34 indicates the results of the present ecological state of the system in comparison to reference conditions. The reference conditions were assigned an assessment class rating A as they are the considered to be pristine or un-impacted conditions. Table 4.27 indicates the state of the system according to the class ratings.

From the results indicated in Table 4.34 it can be concluded that the pH of the system has not changed over the last twenty years. The only site indicating moderate impact is BSL. TDS assessment class ratings indicate that the system is being impacted and the salt levels in the system are increasing. These increases are taking place in the Olifants Spruit, Tobias Spruit and in the Bad se Loop. The TDS values at Nylsvley are un-impacted which would indicate the system health and effective functioning of the wetland.

Table 4.34: Present ecological state of the sites in the Nyl River system

Reference condition (R/C) pH TDS KNO A A A DPD A A A HSW A A B Olifants Spruit A A E Nylsvley A A A BSL A C F Tobias Spruit A A F

4.9: Conclusion

The results discussed in this chapter point to the conclusion that the water in the Nyl river system poses little cause for concern with respect to pollutant contamination. The system variables indicate that most of the variables fall within the target water quality ranges set out in the DWAF guidelines. The results indicate that the water is soft to medium in nature with a relatively neutral pH. The oxygen concentrations dip in the wetland sites, but this can be attributed to the vegetation in the system and the breakdown of organic

159 Chapter 4: Water Quality Results and Discussion matter. Metals in the system are at relatively high levels but this is constant from the source to the last site monitored. This would indicate that they are from natural sources and that there are few point sources of metal entry into the system. Toxicity tests showed that the water is generally suitable for sustaining aquatic life. Nutrient ratios (N:P) indicate that there is an influx of nutrients into the system. This influx is having an effect on the system with the eutrophication of the system. The increased nutrient levels can however be controlled with mechanical removal of reeds after the growing season . This however is not a major concern as the levels of toxic ammonia indicate that the system is un-impacted. The input of organic matter and bacteria however posses a potential threat to animal and human health alike. The bacteria counts indicate that faecal coliform, total coliform and heterotrophic plate counts are higher than the TWQR. These bacteria are entering the system via sewage effluents and agricultural runoff. The results indicate that the Nylstroom/Modimolle Sewage Treatment Works is the major contaminator of the system, but runoff from agricultural lands and developing urban settlements are also contributing to the bacterial contamination in the system.

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4.10: References

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Research 37: 1737-1748. INTERNATIONAL STANDARD ORGANISATION (ISO), (1996). Water quality- Determination of the acute lethal toxicity of substances to a freshwater fish [Brachydanio rerio Hamilton-Buchanan (Teleostei, Cyprinidae)] Part 1: Static method, Second edition. ISO 7346-1:1996(E). pp 11. IWQS 1998. Methods Manual: Method 3001 002 acute toxicity assessment using Poecillia reticulata. pp 14. JAGALSA, P. (1997). Stormwater runoff from typical developed and developing South African urban developments: definitely not for swimming. Water Science and Technology 35: 133-140. KARGIN, F. and ÇOèUN, N.Y. (1999). Metal interactions during accumulation and elimination of zinc and cadmium in tissues of the freshwater fish Tilapia nilotica. Bulletin of Environmental Contamination and Toxicology 63: 511-519 KEMPSTER, P.L. and VAN VLIET, H.R. (1991). Water quality fitness for use curves for domestic water. Draft internal report, Hydrobiological Research Institute, Department of Water Affairs and Forestry, Pretoria, South Africa. KEMPSTER, P.L., HATTINGH, W.A.J. and VAN VLIET, H.R. (1980). Summarized water quality criteria. Department of Water Affairs and Environmental Conservation, Hydrological Research Institute. Technical Report No TR 108. pp 45. KFIR, R. (1981). The detection and assay of potential carcinogens and toxicants in water by tissue culture techniques. Unpublished PhD thesis, University of Pretoria. KOTZE, P., DU PREEZ, H.H. and VAN VUREN, J.H.J. (1999). Bioaccumulation of copper and zinc in Oreochromis mossambicus and Clarias gariepinus, from the Olifants River, Mpumalanga, South Africa. Water SA 25(1): 99-110. KUPCHELLA, C.E. and HYLAND, M.C. (1993). Environmental Science: Living within the System of Nature 3rd ed. Prentice Hall International Ltd. London. pp 579. LARSSON, A., BENATSSON, B.E. and SVANBERG, O. (1976). Some haematological and biochemical effects of cadmium on fish. In: LOCKWOOD, A.P.M. (ed.) Effects of pollutants on aquatic organisms. Cambridge University Press, London pp. 193. LEE, R.M. and GERMING, S.D. (1980). Survival and reproductive performance of the desert pupfish, Cyprinidon nevadensis (Eigenmann and Eigenmann) in acid water. Journal of Fish Biology 17: 507 LIU, D.L., YANG,Y.P., HU, M.H., HARRISON, P.J. and PRICE, N.M. (1987). Selenium content of marine food chain organisms from the coast of China. Marine Environmental Research 22: 151-165. MANAHAN, S.E. (1993). Fundamentals of environmental chemistry. Lewis Publishers, Boca Raton. pp. 417-437. MAUL, J.D. and COOPER, C.M. (2000). Water quality of seasonally flooded agricultural fields in Mississippi, USA. Agriculture, Ecosystems and Environment 81: 171-178. MOUNT, D.I. (1973). Chronic effects of low pH on fathead minnow survival, growth and reproduction. Water Research 7: 987 - 993

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MULLER, W.J. and PALMER, C.G. (2002). The use of Daphnia spp. and indigenous river invertebrates in whole effluent toxicity testing in the Vaal catchment. WRC Report No 815/1/02. pp. 57. MUNIZ, I.P. and LEIVESTAD, H. (1980). Toxic effects of aluminium on the brown trout, Salmo trutto. pp 320-321. In: D.DRABLOS & A. TOLLEN [ed.] Ecological impact of acid precipitation. SNSF Project, Norway. MVUNGI, A., HRANOVA, R.K. and LOVE, D. (2003). Impact of home industries on the water quality in a tributary of the Marimba River, Harare: implications for urban management. Physics and Chemistry of the Earth 28: 1131-1137. NELSON, J.A. (1982). Physiological observations on developing rainbow trout, Salmo gairdneri (Richardson), exposed to low pH and varied calcium iron concentrations. Journal of Fish Biology 20: 359 NEWMAN, J.M., CLAUSEN, J.C. and NEAFSEY, J.A. (2000). Seasonal performance of a wetland constructed to process dairy milkhouse wastewater in Connecticut. Ecological Engineering 14: 181-198. NEWMAN, M.C. and MCINTOSH, A.W. (1991). Metal Ecotoxicology: Concepts and Applications. Lewis Publishing, Michigan. pp. 399. NUSSEY, G., VAN VUREN, J.H.J. and DU PREEZ, H.H. (1999). Bioaccumulation of Al, Cu, Fe and Zn in the tissues of the moggel from Witbank Dam, upper Olifants River catchment (Mpumalanga). South African Journal of Wildlife Research 29(4): 129-144. OHNESORGE, F.K. and WILHELM, M. (1991). Zinc In: E. MERIAN (ed.). Metals and their compounds in the environment: Occurrence, analysis and biological relevance. pp. 1438. ORGANISATION FOR ECONOMIC CHANGE AND DEVELOPMENT (OECD), (1992). Guideline for testing of chemicals: fish acute toxicity test 203. pp 9. PETERSON, R.H., DAYE, P.G., LACROIX, G.L. and GARSIDE, E.T. (1976). Reproduction in fish experiencing acid and metal stress. In: JOHNSON, R.E. (ed), Acid Rain and Fisheries. American Fisheries Society, Bethesda, Md. pp. 177. PIZZARO, I., GOMEZ, M., CAMARA, C. and PALACIOS, M.A. (2003). Arsenic speciation in environmental and biological samples Extraction and stability studies. Analytica Chimica Acta 495: 85-98. POLLING, L. (1999). Ecological aspects of the Ga-Selati River System, Northern Province, Republic of South Africa. Unpublished PhD. Thesis, University of the North, Pietersburg, South Africa. pp 312. RATTNER, B.A. and HEATH, A.G. (1995). Environmental factors affecting contaminant toxicity in aquatic and terrestrial vertebrates. In D.J. HOFFMAN, B.A. RATTNER, G.A. BURTON. Jr. and J.CAIRNS Jr. [ed.]. Handbook of ecotoxicology. Lewis Publishers. Boca Raton. ROBINSON, J. and AVENANT- OLDEWAGE, A. (1997). Chromium, copper, iron and manganese bioaccumulation in some organs and tissues of Oreochromis mossambicus from the lower Olifants River, inside the Kruger National Park. Water SA. 23(4): 387-404. RODGERS, P., SOULSBY, C., HUNTER, C. and PETRY, J. (2003). Spatial and temporal quality of a lowland agricultural stream in northeast Scotland. The

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Science of the Total Environment 314-316: 289-302. RODRIGUEZ, V.M., JIMENEZ-CAPDEVILLE, M.E., and GIORDANO, M. (2003). The effects of arsenic exposure on the nervous system. Toxicology Letters 145: 1-18. SAKAI, K., NAKAMURA, K., WAKAYAMA, M. and MORIGUCHI, M. (1997). Change in nitrite conversion direction from oxidation to reduction in heterotrophic bacteria depending on the aeration conditions. Journal of Fermentation and Bioengineering 84 (1): 47-52. SANDERS, M.J., DU PREEZ, H.H. and VAN VUREN J.H.J. (1999). Monitoring cadmium and zinc contamination in fresh water systems with the use of the fresh water crab, Potamanautius warrenii. Water SA. 25 (1): 91-98. SAVORY, J. and WILLS, M.R. (1991). Aluminium In: E. MERIAN (ed.). Metals and their components in the environment: Occurrence, analysis and biological relevance. pp. 1438. SCHEINBERG, I.H. (1991). Copper In: E. MERIAN [ed.]. Metals and their compounds in the environment: Occurrence, analysis and biological relevance. pp. 1438. SEYMORE, T., DU PREEZ, H.H. and VAN VUREN, J.H.J. (1995). Manganese, lead and strontium bioaccumulation in the tissues of the yellow fish, Barbus marequensis from the lower Olifants River, Eastern Transvaal. Water SA 21 (2): 159-171. SOLA, M. and DURAN, M. (1994). El zinc y los enzimas: Importancia y studio mediante modelos. Quimica e Industria 42 (7). pp 24-28. In: GALVIN, R.M. (1996). Occurrence of metals in waters: An overview. Water SA 22 (1): 7-18. SPRY, D. and WIENER, J.G. (1991). Metal bioavailability and toxicity to fish in low alkalinity lakes: A critical review. Environmental Pollution 71(2-4): 243-304. SLABBERT, J.L., OOSTHUIZEN, J., VENTER, E.A., HILL, E., DU PREEZ, M. and PRETORIUS, P.J. (1998). Development of guidelines for toxicity bioassaying of drinking and environmental waters in South Africa. Water Research Commission Report Number 358/1/98. Water Research Commission, Pretoria. pp 101. STICKNEY, R.R. (1979). Principles of warm water aquaculture. Interscience Publication, John Wiley and Sons Inc. New York, USA. TRAIN, R.E. (1979). Quality criteria for water. US Environmental Protection Agency, Washington DC. Castle House Publications. pp 256. TRUTER, E. (1994). Methods for estimating chronic toxicity of a chemical or water sample to the Cladoceran Daphnia pulex. IWQS Report number N0000/00/OEQ/1394. TUCKER, C.S. and ROBINSON, E.H. 1990. Channel catfish farming handbook. Van Nostrand Reinhold, New York: 454pp. VAN VUREN, J.H.J., DU PREEZ, H.H., WEPENER, V., ADENDORFF, A., BARNHOORN, I.E.J., COETZEE, L., KOTZE, P. and NUSSEY, G. (1999).Lethal and Sublethal Effects of Metals on the Physiology of Fish: An Experimental Approach with Monitoring Support. Water Research Commission Report Number 608/1/99. VEGA, E., LESIKAR, B. and PILLAI, S.D. (2003). Transport and survival of

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bacterial and viral tracers through submerged-flow constructed wetland and sand filter system. Bioresource Technology 89: 49-56. VIARENGO, A. (1985) Biochemical effects of trace metals. Marine Pollution Bulletin 16 (4): 153-158. VRHOVSEK, D., KUKANJA, V. and BULC, T. (1996). Constructed wetland (CW) for industrial waste water treatment. Water Research 30 (10). pp 2287-2292. WANG, W. (1987). Factors affecting metal toxicity to (and accumulation by) aquatic organisms-Overview. Environment International 13: 437-457. WHO (World Health Organization) (1992). Cadmium-environmental aspects. World Health Organization, Geneva pp. 156. WILKINSON, J., JENKINS, A., WYER, M. and KAY, D. (1995). Modelling faecal coliform dynamics in streams and rivers. Water Research 29 (3): 847-855. WORLD HEALTH ORGANIZATION (WHO) (1993). Guideline for drinking water quality (2nd edn.) Vol 1. Geneva (Switzerland). ZACCONE, R., CARUSO, G. and CALI, C. (2002). Heterotrophic bacteria in the northern Adriatic Sea: seasonal changes and ectoenzyme profile. Marine Environmental Research 54: 1-19.

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CHAPTER 5:

Sediments: Results and Discussion

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CHAPTER 5: Sediments: Results and Discussion 5.1: Introduction

From the myriad of literature available it is possible to conclude that metals have a high toxicity and worldwide distribution in the aquatic environment. They are also known to accumulate in sediments (Klavins et al., 1998). Data concerning environmental effects of chemicals clearly indicate the accelerated and negative effects of the dispersal of metals and metalloids in the environment by anthropogenic activities, and the changes made to global chemical cycles (Mester et al., 1998). The study of sediments in wetlands is important as wetlands act as natural filters for water in a system and thus act as a sink for contaminated suspended particles in the water column. Sediments also provide an indication of potential contamination on a temporal scale. The analysis of water indicates the contamination status at present where as sediment can provide information on the systems contamination history (Shine, 2004). Wetlands can also act as a source of increased contaminant levels in a water body during periods of increased water flow by remobilizing the settled particles and thus the resuspension of the contaminants in the water. These sediments are transported downstream and affect the ecosystems of the river downstream as well as flooded wetlands (Ulbrich et al., 1997). The mobilisation of sediments by water flow allows contaminants to penetrate deep into wetlands by flood waters (Ulbrich et al., 1997). It is thus important to assess the sediment quality throughout the system.

Contaminants bind to the sediment particles (Buykx et al., 2002). These contaminants can be either metallic in nature or originate from chemical compounds released into the system via a number of anthropogenic activities. This chapter deals with the metal and metalloid contamination of sediments with sediment contamination by pesticides discussed in the next chapter (Chapter 6).

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Metals in a system can originate from either natural or anthropogenic sources. These metals may be present in several geochemical phases that act as reservoirs or sinks of trace metals in the environment (Li et al., 1995). These phases include the broad categories: exchangeable, specifically adsorbed, carbonate, Fe-Mn oxides, organic matter and mineral lattice (Li et al., 1995) it is thus recognised that the quantification of the chemical forms of metals in the sediment is essential for estimating the mobility and bioavailability of metals in the environment (Leschber et al., 1985, Li et al., 1995). Van Ryssen et al. (1999) noted in an article on the mobilization potential of trace metals in aquatic sediments that in anoxic sediments the exchangeable and carbonate fractions are negligible for all elements, except Mn, where as 50-90% of metals are bound to the residual fraction (Van Ryssen et al., 1999)

It is generally recognised that information about the physico-chemical forms of elements is necessary to understand their environmental behaviour such as mobility and bioavailability (Tack and Verloo, 1995). To this end the sediment samples collected from the 18 localities throughout the system were subjected to a five point sequential extraction. The sequential extraction of metals from solid media is a common tool used in the analysis of environmental geochemistry (Sutherland and Tack, 2003). This process uses different reducing and oxidising agents to remove each fraction of the bound metals in the sample to allow for the evaluation of the total metal content available for uptake by organisms or bioavailability. The extraction method is comprehensively described in Chapter 3 and this chapter will thus only report the results obtained from the analysis and a discussion thereof.

As mentioned earlier the samples underwent a five point extraction. The five fractions extracted are listed in Table 5.1 with a brief explanation of the remobilisation of metal ions from each fraction.

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Table 5.1: Table of the different fractions extracted during the sequential extraction process, their binding sites and the remobilisation thereof. (Adapted from Coetzee, 1993) Fraction Binding Site Remobilization

Changes in ionic composition of Weakly absorbed metals, water would strongly influence particularly those absorbed absorption-desorption and ion Exchangeable Fraction to the surface of sediment exchange processes of metal ions particles. with the major constituents of sediments. Trace metals co- Lowering the water pH will remobilise Bound to carbonates precipitated with carbonates these trace metals. Fe and Mg oxides present Trace metals are remobilized due to in sediments as concretions Bound to manganese and iron reduction of Fe(III) and Mn(IV) under are excellent substrates oxides anoxic conditions and their with large surface areas for subsequent dissolution. trace metals to absorb to Organic matter such as detritus, living organisms Trace metals may be released under and coatings on mineral Bound to organic matter oxidising conditions during the particles bind trace metals degradation of these substances. through complexation and bioaccumulation processes. Residual fractions are the trace metals bonded These metals are not likely to be Residual or inert fraction strongly to the crystal remobilised under normal structure of the minerals environmental conditions comprising the sediment.

After the sequential extraction process the samples were subjected to an ICP-MS analysis and the results were then statistically analysed using the SPSS statistical analysis software. From the scan performed, metals that corresponded to those found to be potential problems from the water scan performed earlier (Chapter 4 Water Results and Discussion) are discussed in more detail. Table 5.2 indicates these metals, the detection limits of the ICP-MS, and the sediment quality guideline (SQG) levels used to determine if the concentrations reported

171 Chapter5: Sediment:-Results and Discussion are toxic to aquatic life (EPA, 1999). Table 5.2: Table of potential problem metals, ICP-MS detection limits and Sediment Quality Guideline levels in mg/kg. Metal ICP-MS Detection limit (mg/kg) SQG (mg/kg) Aluminium 0.000112 Chromium 0.000008 81-370 Copper 0.000062 34-270 Cadmium 0.000014 1.2-9.6 Zinc 0.000028 150-410 Manganese 0.000008 Lead 0.000022 46.7-218 Arsenic 0.000002 8.2-70 Sediment Guideline levels give a range determined by the Effect Range-Low (ERL) and the Effect Range Median (ERM) (EPA, 1999).

The results in this chapter will be discussed on a metal for metal basis. The results reported cover a comparison of the different fractions of the sequential extraction between the different sampling months as well as the fractions within the sampling months. Maximum concentrations will also be reported.

5.2: Aluminium

The increased bioavailability of aluminium in sediments comes about by the remobilization of sediment particles by increased water flow and agitation in conjunction with decrease in pH (Buykx et al., 2002). This increased bioavailability can have various physiological effects on the organisms in the system. These potential negative physiological effects have been discussed in Chapter 4 and will thus not be discussed in this chapter.

Figures 5.1 A-D indicate the various aluminium concentrations observed at each locality during the different sampling periods for each fraction. The

172 Chapter5: Sediment:-Results and Discussion concentrations recorded indicate that the majority of the aluminium in the sediment is partitioned into the 4th and 5th fractions. This would indicate that the aluminium in the sediment is not very bioavailable and will only be released in the presence of a strong reducing agent or if the pH in the system were to decrease.

Figure 5.1 A indicates the aluminium concentrations during the August 2001 sampling period. The localities situated at Nylsvley, Haakdoring and Moorddrift had the highest concentrations of aluminium with concentrations of 25938.12mg/kg, 17787.95mg/kg and 24757.47mg/kg respectively.

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Figure 5.1: Aluminium concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

174 Chapter5: Sediment:-Results and Discussion

No significant differences were found between the mean aluminium concentrations in fraction 4. Significant differences (P<0.05) were however noted between the following fractions: · Fraction 1 and fraction 3 · Fraction 1 and fraction 5 · Fraction 2 and fraction 3 · Fraction 2 and fraction 5. A comparison between fraction 1 and 2 indicated no significant difference.

Figure 5.1 B indicates the aluminium concentrations during the November 2001 sampling period. The figure indicates that fraction 5 once again had the highest concentrations of aluminium with the highest concentrations being found at Nylsvley, Haakdoring, the sewage treatment works (STW) and Tobias station (T.S). Maximum aluminium concentrations of 23951.68mg/kg, 16692.37mg/kg, 11751.84mg/kg and 12390.49mg/kg were recorded respectively. The statistical analysis of the November 2001 sampling period indicates that all mean fraction concentrations were significantly different with a few exceptions. The difference between fraction 1 and 2 and fraction 3 and 4 were not significantly different with p values being greater than 0.05.

Figure 5.1 C indicates the aluminium concentrations recorded during the March 2002 sampling period. Abba, Tobias mine (TM), Haakdoring and Moorddrift had the highest aluminium concentrations with concentrations of 17182.31mg/kg, 14677.73mg/kg, 16162.49mg/kg and 14090.91mg/kg respectively. Significant differences (P<0.05) between fraction means in the system were recorded between the following fractions: · Fraction 1 and fraction 3 · Fraction 2 and fraction 3 · Fraction 1 and fraction 5 · Fraction 2 and fraction 5

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Figure 5.1 D indicates the aluminium concentrations for the July 2002 sampling period. Maximum concentrations were found in fraction 5 and were found at Haakdoring, Moorddrift and Nylsvley. These sites had aluminium concentrations of 17822.93mg/kg, 15160,46mg/kg and 15225.94mg/kg respectively. Significant differences were recorded between the following fractions: · Fraction 1 and fraction 3 · Fraction 1 and fraction 4 · Fraction 1 and fraction 5 · Fraction 2 and fraction 3 · Fraction 2 and fraction 4 · Fraction 2 and fraction 5 · Fraction 3 and fraction 4 · Fraction 3 and fraction 5

No significant differences were found between the mean aluminium concentrations for fractions 1, 2, 4 and 5 when the fractions for each month were compared to each other. The comparison between the fraction 3 concentrations for March and July were however significantly different.

The results indicate that the majority of the aluminium is concentrated in the 5th or inert fraction. This would indicate that the majority of the aluminium extracted from the sediment is from a lattice or detrital origin and can be taken as from a natural source (Jain, 2004).

5.3: Chromium.

Chromium is a relatively scarce metal that occurs in several states. The most toxic of these states is the chromium VI or hexavalent state. The physiological effects of chromium on aquatic organisms vary. These physiological effects have been discussed in Chapter 4 and will thus not be discussed again.

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Fytianos and Lourantou (2004) observed in their study of sediment from Lake Volvi and Koronia in Northern Greece, that chromium is primarily distributed in the reducible (Fe/Mn oxide), residual and oxidizable fractions. They found that metals bound to these different fractions have different potentials for remobilization and for uptake by biota (Fytianos and Lourantou, 2004).

Figure 5.2 indicates the chromium concentrations found in the samples collected during the different sampling months. The graphs illustrate during the different months the chromium is released in the different fractions. Chromium is predominantly remobilized in the oxidizable (F4) and inert fractions (F5). During the August 2001, November 2001 and March 2002 sampling period the observed partitioning of chromium concentrations is primarily in fractions F4 and F5 During the July sampling the majority of the chromium is found in the 5th fraction.

Figure 5.2 A indicates chromium concentrations throughout the system during the August 2001 sampling period. Fraction F4 had the highest chromium concentration. The maximum concentration recorded was 244.5129mg/kg at Mosdene. BSL, Nylsvley, Haakdoring and Moorddrift also had high concentrations of chromium in fraction F4. A comparison of mean chromium concentrations showed significant differences between fractions 1&3, 1&5, 2&3 and 2&5 with P values less than 0.05.

Figure 5.2 B indicates the chromium concentrations recorded during the November 2001 sampling period. The results indicate that the chromium concentrations are highest in fractions 4 and 5. The highest chromium concentrations were recorded at Nylsvley, T.S, Mosdene and Haakdoring. Concentrations were 34.82428mg/kg, 37.47542mg/kg, 50.98731mg/kg and 41.76947mg/kg respectively. Significant differences (P<0.05) in mean chromium concentrations were recorded between fractions 1&2, 1&3, 1&4, 1&5, 2&3, 2&4 and 2&5.

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Figure 5.2: Chromium concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

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Figure 5.2 C indicates chromium concentrations recorded during the March 2002 sampling period. The results indicate that the majority of the chromium is partitioned into fractions F3, F4 and F5. The maximum concentrations recorded were at Haakdoring (F4) of 58.32133mg/kg, Abba (F4) of 34.44767mg/kg and at Mosdene (F5) 45.16986mg/kg.

Figure 5.2 D indicates chromium concentrations recorded during the July 2002 sampling period. The results indicate that the majority of the chromium is partitioned in fraction F5. The maximum concentration observed was observed at Haakdoring (78.3164mg/kg). Abba, STW, Jasper, HSW, Olifants Spruit and Nylsvley also indicated elevated chromium levels compared to the other sites. Significant differences (P<0.05) in mean chromium concentrations were observed between the following fractions 1&3, 1&4, 1&5, 2&3, 2&4 and 3&5.

In the comparison between the different fractions and the months sampled, fraction F4 and F5 indicated no significant differences (P>0.05) between August 2001, November 2001, March 2002 and July 2002. Fraction 3 indicated a significant difference in mean chromium concentration between March 2002 and July 2002. Fraction F1 indicated significant differences between August 2001 & July 2002 but no significant differences between August 2001 and March 2002 and July 2002, and November 2001 and March 2002 and July 2002, but not between August 2001 and November 2001. Fraction 2 indicated significant differences between August 2001 and November 2001, August 2001 and March 2002, November 2001 and March 2002 and November 2001 and July 2002. The highest chromium concentrations recorded all fell within the Sediment Quality Guideline Range of 81 – 370mg/kg (EPA, 1999). The majority of the chromium concentrations were below the lower limit of 81 mg/kg or ERL (effect range low) (EPA, 1999).

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5.4: Manganese

Manganese is an essential element (Health and Welfare Canada, 1980). It is a functional component in nitrate assimilation and is used as a catalyst in many enzymatic systems in both plants and animals (DWAF, 1996). Manganese is readily oxidizable and settles out of the water column as MnO2 (DWAF, 1996). For an overview of the physiological effects of manganese on aquatic organisms refer to Chapter 4.

Figure 5.3 indicates the manganese concentrations recorded during the sampling period in the system. The results indicate that the third fraction had the highest concentrations on manganese during the sampling period.

Figure 5.3 A indicates the manganese concentrations recorded during the August 2001 sampling period. One notable spike is visible on the graph at Mosdene. The fractions F3 and F4 spike with manganese concentrations of 1742.529mg/kg and 791.1142mg/kg respectively. No significant differences in mean manganese concentrations were found between the different fractions for August 2001.

Figure 5.3 B indicates manganese concentrations recorded during the November 2001 sampling period. Notable spike in the third fraction occur at GNO and T.S with concentrations of 1112.466mg/kg and 1904.166mg/kg respectively. No significant differences were found between the fractions for the November 2001 sampling period.

Fraction 5.3 C indicates the manganese concentrations recorded during the March 2002 sampling period. Fraction F3 indicated the greatest partition of manganese. Abba had the highest manganese concentration with all five fractions indicating increased levels of manganese. T. Mine and Jasper showed higher concentrations of manganese in fraction one (105.3879mg/kg

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F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

Figure 5.3. Manganese concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

181 Chapter5: Sediment:-Results and Discussion and 135.5336mg/kg) and HSW recorded high concentrations in fraction one and two (130.9786mg/kg and 141.4849mg/kg). The increased concentrations in fraction one and two indicate manganese that is readily available and that could cause a potential threat to the system. No significant differences in mean manganese concentration were found between the different fractions for March 2002.

Figure 5.3 D indicates manganese concentrations recorded during the July 2002 sampling period. Fraction F3 indicated the highest concentrations with Jasper, BSL and Haakdoring having concentrations of 2237.896mg/kg, 1518.569mg/kg and1316.884mg/kg respectively. No significant differences were recorded in mean manganese concentration between fractions for July 2002.

No significant differences were also recorded between corresponding fractions of each sampling month.

5.5: Zinc

Zinc is an essential micronutrient for all organisms. It forms the active site for various metaloenzymes (DWAF, 1996). The physiological effects of zinc on organisms have been discussed in the previous chapter, so for an overview of the physiological effects refer to Chapter 4.

Figure 5.4 illustrates the zinc concentrations in the system during the sampling period.

Figure 5.4 A indicates zinc concentrations recorded during the August 2001 sampling period. The results indicate that the majority of the zinc is partitioned into fractions F4 and F5.

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5000 200 0 0 KIN BSL KIN KNO Abba DPD GNO STW HSW T Eye KNO Abba DPD GNO STW HSW BSL T Eye Jasper Nylsvley T.Mine Jasper Nylsvley T.Mine DLA DLA T Station Mosdene DLA DLA T Station Mosdene Haakdoring Moorddrift Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

C D

5000 1200 4500 1000 4000 3500 800 3000

Conc (mg/kg) 2500 Conc (mg/kg) 600 2000 400 1500 1000 200

500 0 0

KIN KNO Abba DPD GNO STW HSW BSL KIN KNO Abba DPD GNO STW HSW BSL Jasper T Eye T.Mine Jasper T Eye T.Mine DLA DLA Nylsvley T Station Mosdene DLA DLA Nylsvley T Station Mosdene Haakdoring Moorddrift Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

Figure 5.4: Zinc concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

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Mosdene exhibited the highest concentration of zinc (1031.88mg/kg). Fraction 4 at Abba and Mosdene exhibited zinc concentrations higher than the Sediment Quality Guideline (SQG) for aquatic ecosystems (EPA, 1999) of 150-410mg/kg. No significant differences were found between the mean zinc concentrations for the different fractions during August 2001.

Figure 5.4 B indicates the zinc concentrations recorded in the system during the November 2001 sampling period. The highest zinc concentrations recorded were in the residual or inert fraction (Fraction 5) at KIN (24461.8mg/kg). Fraction 2 KIN (6090.918 mg/kg), fraction 1 at Jasper (2000.789mg/kg) and fraction 4 at Jasper (1959.353mg/kg) were the other fractions that exhibited Zn concentrations higher than the SQG range. No significant differences were recorded for the mean zinc concentrations for the different fractions.

Figure 5.4 C indicates the zinc concentrations recorded throughout the system for the March 2002 sampling period. Fraction 3 at HSW and fraction 4 at T. Eye exhibited the highest zinc concentrations of 4608.765mg/kg and 1371.047mg/kg respectively. All the other zinc concentrations recorded were below the SQG. Significant differences (P<0.05) were found between fractions 2&3, 2&5 and 3&5.

Figure 5.4 D indicates the zinc concentrations recorded during the July 2002 sampling period. All sites and fractions indicate increased zinc concentrations for each of the five fractions. The highest concentrations were recorded at KNO (fraction 2, 1043.751mg/kg), Nylsvley (fraction 2, 824.1389mg/kg), GNO (fraction 5, 642.0671mg/kg) and Olifants Spruit (fraction 2, 554.6227mg/kg). These four sites had zinc concentrations greater than the SQG. Three of these sites indicated these high concentrations in the readily available fraction 2 (ions bound to carbonates). No significant differences were found between the mean zinc concentrations in the different fractions. Fraction 4 and 5 indicated no significant differences in the mean zinc concentrations during the different sampling months. In fraction 3 significant

184 Chapter5: Sediment:-Results and Discussion differences (p<0.05) were found between August 2001 & July 2002, August 2001 & March 2002, November 2001 & July 2002 and March 2002 & July 2002. Fraction 2 indicated significant differences between August 2001 & March 2002 and fraction 1 between August 2001 & July 2002.

5.6: Copper

Copper is a common environmental metal. It is essential in cellular metabolism but at high concentrations it can be highly toxic to fish (Grosell et al., 1997). Copper is generally remobilized with acid-base ion exchange and oxidation mechanism (Gomez Ariza et al., 2000).

Figure 5.5 illustrates the copper concentrations observed in the system during the sampling period. Copper concentrations recorded all generally fell below or at the lower end of the SQG range (34-270mg/kg) with one exception. An excessively high copper concentration (786.533mg/kg) was recorded at the source of the Klein Nyl River (KNO) during July 2002 (Figure 5.5 D). This level was found in the second fraction, which would indicate that copper is readily available. The site is however situated on a farm about 50 m from the source of the Klein Nyl River so it can be assumed the levels come from natural sources.

Figure 5.5 A illustrates the copper concentrations recorded during August 2001. The results indicate that the majority of the copper is found in fractions 3, 4 and 5. The maximum concentration recorded was in fraction 4 at Mosdene (64.3368mg/kg). Mosdene also recorded the highest concentrations in fraction 3 (30.9564mg/kg) and fraction 5 (26.5269mg/kg). Significant differences were found in copper concentrations between fractions 1&5 and 2&5.

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A B

70 40

35 60

30 50 25 40 Conc (mg/kg) Conc (mg/kg) 20 30 15

20 10

10 5

0 0 KIN KIN KNO Abba DPD GNO STW HSW BSL T Eye KNO Abba DPD GNO STW HSW BSL T Eye Jasper Nylsvley T.Mine Jasper Nylsvley T.Mine DLA DLA T Station Mosdene DLA DLA T Station Mosdene Haakdoring Moorddrift Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

C D

70 800

700 60

600 50 500 40 Conc (mg/kg) Conc (mg/kg) 400 30 300

20 200

10 100

0 0 KIN KIN KNO Abba DPD GNO STW HSW BSL KNO Abba DPD GNO STW HSW BSL T Eye Jasper T Eye T.Mine Jasper Nylsvley T.Mine DLADLA Nylsvley T Station Mosdene DLA DLA T Station Mosdene Haakdoring Moorddrift Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

Figure 5.5: Copper concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

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Figure 5.5 B indicates the copper concentrations in the system for November 2001 sampling period. Fractions 3, 4 and 5 exhibited the highest concentrations with T.S having the highest concentration of 36.86751mg/kg. Significant differences were found between fractions 1, 2 & 3 and fraction 5 as well as between fraction 2&4.

Figure 5.5 C indicates the copper concentrations recorded during the March 2002 sampling period. The majority of the copper is partitioned into fractions 3, 4, and 5. A maximum concentration was recorded at BSL in fraction 4 (62.1038mg/kg). Significant differences were recorded between fractions 1&5, 2&3 and 2&5.

Figure 5.5 D indicates the copper concentrations recorded during the July 2002 sampling period. As mentioned earlier KNO had a spike with copper levels higher than all the other sites. No significant differences were found in mean copper concentrations between the fractions in the system.

A comparison between the corresponding fractions from each sampling month indicated that fraction 3 was the only fraction that exhibited significant differences. Significant differences in mean copper concentration were between November 2001&July 2002 and March 2002 and July 2002.

5.7: Arsenic

Arsenic is a highly toxic metalloid element (Rodrigues et al., 2003, Pizzaro et al., 2003). It is widely distributed as a trace element in rocks and soils and is mainly mobilized by microbial activities (Garcia-Sanchez and Alvarez-Ayuso, 2003). The physiological effects of arsenic on aquatic organisms have been discussed in the previous chapter (Chapter 4) and will thus not be referred to in this chapter.

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A B

60 9

8

50 7 40 6 5 Conc (mg/kg) 30 Conc (mg/kg) 4

20 3

2 10 1

0 0 KIN KNO DPD GNO BSL Abba STW Jasper HSW T Eye T.Mine KIN KNO Abba DPD GNO STW HSW BSL Nylsvley T Station Jasper TEye T.Mine DLA DLA Mosdene Moorddrift DLA DLA Nylsvley T Station Mosdene Haakdoring Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

C - D

14 30

12 25

10 20 8 Conc (mg/kg) Conc (mg/kg) 15 6 10 4 5 2

0 0

KIN KIN KNO Abba DPD GNO STW BSL KNO Abba DPD GNO STW HSW BSL T Eye Jasper HSW T Eye T.Mine Jasper Nylsvley T.Mine Nylsvley T Station Mosdene DLA DLA T Station Mosdene DLA DLA Moorddrift Haakdoring Moorddrift Haakdoring Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

Figure 5.6: Arsenic concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

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Figure 5.6 indicates the arsenic concentrations in the system during the sampling period. The graphs indicate that most of the arsenic is concentrated in the residual or inert fraction (fraction 5).

Figure 5.6 A indicates arsenic concentrations in the system during the August 2001 sampling period. The highest concentrations were recorded at Jasper (57.0031mg/kg) and TO (58.25977mg/kg). The results indicate that arsenic concentrations from the different fractions fell within the SQG of between 8.2 and 70 mg/kg. Significant differences in mean arsenic concentrations were found between fractions 1, 2, 3 and fraction 5.

Figure 5.6 B indicates arsenic concentrations recorded in the system during the November 2001 sampling period. The graphs indicate that the majority of the arsenic is partitioned into the fifth fraction. The results indicate that arsenic concentrations ranged between 0.181436mg/kg (Olifants Spruit) and 8.835832mg/kg (TO). This range falls within or below the ERL of the SQG range. Fractions 1, 2, 3 and 4 indicated a significant difference in mean arsenic concentration from fraction 5.

Fraction 5.6 C indicates arsenic concentrations during the March 2002 sampling period. The results indicate that the majority of the arsenic is once again partitioned in the residual fraction. The maximum concentration observed however was observed in the fourth fraction at TO (12.75781mg/kg). All concentrations occurred toward or below the lower end of the SQG range of between 8.2 and 70mg/kg. Significant differences were found in mean arsenic concentrations between fractions 1, 2 3 and fraction 5 respectively.

Figure 5.6 D indicates the arsenic concentrations recorded during the July 2002 sampling period. The majority of the arsenic is partitioned in the fifth fraction. A spike on the graph at TO can be observed with a maximum concentration of 28.77561mg/kg. No significant differences were observed for July 2002 between

189 Chapter5: Sediment:-Results and Discussion the fractions.

Fraction 1 and 5 were the only fractions to show significant differences between sampling months. Fraction 1 indicated a difference in mean arsenic concentration for August 2001 and July 2002. Fraction 5 indicated a significant difference in mean arsenic concentration between November 2001 and March 2002.

5.8: Cadmium

Cadmium is a non-essential trace element that enters the environment via anthropogenic activities such as sewage sludge, fertilizers and pesticides (DWAF, 1996). Cadmium adsorbs strongly to sediments and organic matter (Sanders et al., 1999). The physiological effects such as decreased growth rates and negative effects on embryonic development (Newman and McIntosh, 1991) have been discussed in Chapter 4 and will thus not be discussed here.

Figure 5.7 indicates the cadmium concentrations recorded during the sampling period.

Figure 5.7 A indicates the cadmium concentrations determined for the system during August 2001. The maximum concentration recorded was in fraction 5 of 0.373014mg/kg. Cadmium concentrations ranged between 0.000014mg/kg and 0.373014mg/kg. Significant differences (P<0.05) were only noted in mean cadmium concentrations between fractions for fraction 3 and 4.

Figure 5.7 B indicates the cadmium concentrations recorded during the November 2001 sampling period. The maximum concentration recorded was at Olifants Spruit in fraction 1 (1.032342mg/kg). This would indicate that the cadmium is readily available. Significant differences were recorded between fractions 2&4 and 3&4.

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A B

0.4 1.2

0.35 1 0.3 0.8 0.25

Conc (mg/kg) 0.2 Conc (mg/kg) 0.6 0.15 0.4 0.1 0.2 0.05

0 0 KIN BSL KNO Abba DPD GNO STW HSW T Eye KIN BSL Jasper Nylsvley T.Mine KNO Abba DPD GNO STW HSW T Eye DLA DLA T Station Mosdene Jasper Nylsvley T.Mine Haakdoring Moorddrift DLA DLA T Station Mosdene Moorddrift Olifants Spruit Haakdoring Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

C D

3 0.45 0.4 2.5 0.35 2 0.3 0.25 Conc (mg/kg) 1.5 Conc (mg/kg) 0.2

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0 0 KIN BSL KIN KNO Abba DPD GNO STW HSW BSL KNO Abba DPD GNO STW HSW T Eye Jasper T Eye T.Mine Jasper Nylsvley T.Mine Nylsvley T Station Mosdene DLA DLA T Station Mosdene DLA DLA Haakdoring Moorddrift Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

Figure 5.7: Cadmium concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

191 Chapter5: Sediment:-Results and Discussion

Figures 5.7 C and D indicate cadmium concentrations recorded during the March 2002 and July 2002 sampling periods. 2 distinct peaks can be seen on the graphs. In figure 5.7 C the maximum concentration recorded, was recorded in fraction 3 at TO (2.514241mg/kg). In figure 5.7 D the maximum concentration of 0.422359mg/kg was recorded for fraction 4 at TM. No significant differences were recorded in mean cadmium concentrations between fractions.

The maximum cadmium concentration of 2.514241mg/kg recorded during sampling fell within the SQG and thus cadmium poses little potential threat to the organisms in the system. No significant differences were recorded between corresponding fractions for each month with the exception of fraction 4. Significant differences were recorded between November 2001& and March 2002 and November 2001 and July 2002.

5.9: Lead

Lead is a non-essential trace element (Ewers and Schlipkoter, 1991). The toxicity of lead is dependent on life stage of the organism and the presence of organic material (Hellawell, 1986). A variety of physico-chemical factors lead to increased toxicity. Physiological effects caused by lead toxicity have been discussed in Chapter 4 and will thus not be discussed.

Figure 5.8 indicates lead concentrations determined in the system during the sampling period. The results indicate that the majority of the lead is partitioned in fractions 3, 4 and 5.

Figure 5.8 A indicates lead concentrations recorded during the August 2001 sampling period. The majority of the lead is partitioned in the fifth fraction. Maximum lead concentrations were recorded at TM (1226.425mg/kg) and Olifants Spruit (1118.408mg/kg). Significant differences were found in mean lead concentrations of lead between fractions 1&5, 2&5, 3&5 and 4&5.

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A B

1400 40

35 1200

30 1000 25 800 Conc (mg/kg) Conc (mg/kg) 20 600 15 400 10

200 5

0 0 KIN BSL KNO Abba DPD GNO STW HSW T Eye KIN Jasper Nylsvley T.Mine KNO Abba DPD GNO STW HSW BSL T Eye DLA DLA T Station Mosdene Moorddrift Jasper Nylsvley T.Mine Haakdoring DLA DLA T Station Mosdene Olifants Spruit Haakdoring Moorddrift Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

C D

40 45 35 40

35 30 30 25 25 Conc (mg/kg) 20 Conc (mg/kg) 20 15 15

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0 0

KIN KNO DPD GNO BSL KIN KNO DPD GNO BSL Abba STW Jasper HSW T Eye T.Mine Abba STW Jasper HSW T Eye T.Mine DLA DLA Nylsvley T Station Mosdene DLA DLA Nylsvley T Station Mosdene Haakdoring Moorddrift Haakdoring Moorddrift Olifants Spruit Olifants Spruit F1 F2 F3 F4 F5 F1 F2 F3 F4 F5

Figure 5.8: Lead concentrations (mg/kg) in the different fractions during the different sampling months. A: August 2001, B: November 2001, C: March 2002 and D: July 2002.

193 Chapter5: Sediment:-Results and Discussion

Figure 5.8 B indicates lead concentrations recorded during the No vember 2001 sampling period. The lead is partitioned primarily in fractions 3, 4 and 5. The maximum concentration was recorded at Nylsvley in fraction 3 (37,89936mg/kg). Significant differences were recorded between fractions 1&2, 1&3, 1&4, 1&5, 2&3, 2&4 and 2&5.

Figure 5.8 C indicates lead concentrations recorded during the March 2002 sampling period. The majority of the lead is partitioned in fractions 3, 4 and 5. The maximum lead concentrations were recorded at BSL, TM, Mosdene and Haakdoring. The maximum values were all in fraction 3 and were 36.2352mg/kg, 38.08004mg/kg, 30.92636mg/kg and 23.71075mg/kg respectively. Significant differences were recorded between fractions 1&3, 1&4, 1&5, 2&3, 2&4 and 2&5.

Figure 5.8 D indicates the lead concentrations recorded for the system during July 2002. The majority of the lead is partitioned in fraction 3. Maximum concentrations were recorded at BSL (44,19074mg/kg) and KNO (Fraction 2, 26,05897mg/kg). Significant differences were recorded between fractions 1&3, 1&4 and 1&5.

No significant differences were noted in mean lead concentrations between corresponding fractions for fraction 2 and 3 from August 2001 to July 2002. In fraction 1 significant differences were recorded between August 2001 & March 2001, August 2001 & July 2002, November 2001 & March 2001 and November 2001 & July 2002. In fraction 5 significant differences were recorded between August 2001 & November 2001, March 2002 & July 2002, November 2001 & March 2002 and November 2001 & July 2002

All lead concentrations fell within the SQG range except for fraction 5 in August 2001. This is little cause for concern as fraction 5 is the residual/inert fraction and the lead would thus be from natural sources.

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A B

August 2001 November 2001

100% 100% 90% 80% 80% 70% 60% 60% Fraction 5 Fraction 5 Fraction 4 50% Fraction 3 Fraction 4 Fraction 2 Fraction 1 Fraction 3 40% 40%

Partition percentage partition percentage Fraction 2 30% Fraction 1 20% 20% 10% 0% 0% Al mg/kg Cr mg/kg Mn mg/kg Zn mg/kg Cu mg/kg As mg/kg Cd mg/kg Pb mg/kg Al mg/kg Cr mg/kg Mn mg/kg Zn mg/kg Cu mg/kg As mg/kg Cd mg/kg Pb mg/kg

C D

March 2002 July 2002

100% 100% 90% 80% 80% 70% 60% 60% Fraction 5 Fraction 5 Fraction 4 Fraction 4 50% Fraction 3 Fraction 3 Fraction 2 Fraction 2 Fraction 1 Fraction 1 40% 40%

Partition percentage Partition percentage 30% 20% 20% 10% 0% 0% Al mg/kg Cr mg/kg Mn mg/kg Zn mg/kg Cu mg/kg As mg/kg Cd mg/kg Pb mg/kg Al mg/kg Cr mg/kg Mn mg/kg Zn mg/kg Cu mg/kg As mg/kg Cd mg/kg Pb mg/kg

Figures 5.9 A-D. Fraction percentages of mean metal concentrations.

195 Chapter5: Sediment:-Results and Discussion

5.10: Metal summary

The results clearly indicate the metals do not appear to be a problem in the system. Figures 5.9 A-D indicate a stacked graph of the percentage makeup of the different fractions for the different metals. The graphs indicate that the majority of the metals are partitioned into fractions 3, 4 and 5. Indications are that the metals generally are not very bioavailable. This would indicate that metals from the sediments pose little to no potential threat to the organisms in the system. This would also imply that most of the metals in the system are from a natural source.

The results also indicate that all metal concentrations fell within the lower end of the Sediment Quality Guideline Range. These will thus have little or no effect on the organisms in the system. Zinc was the only metal that had concentrations greater than the guideline value. This is however little cause for concern as they were recorded in the residual or inert fraction (Fraction 5). This would imply that they are natural concentrations in the sediment.

It may thus be concluded that the bioavailability of metals may be related to chemical form in sediment structure and not total concentration (Tüzen, 2003).

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5.11: References.

BUYKX, S.E.J., VAN DEN HOOP, M.A.G.T. and LOCH, J.P.G. (2002). Dissolution kinetics of heavy metals in Dutch carbonate and sulphide-rich freshwater sediments. Journal of Environmental Quality 31: 573-580. COETZEE, P. (1993). Determination and speciation of heavy metals in sediments of the Hartbeespoort Dam by sequential chemical extraction. Water SA 19 (4): 291-300. DEPARTMENT OF WATER AFFAIRS AND FORESTRY (DWAF). (1996). South African Water Quality Guideline volume 7: Aquatic ecosystems. pp 159. Environmental Protection Agency (EPA). (1999). Sediment Quality Guidelines developed for the national status and trends program. Report number 6/12/99. http://www.epa.gov/waterscience/cs/pubs.htm (May 2004). EWERS, U. and SCHLIPKOTER, H.W. (1991). Lead In: E. MERIAN [ed.]. Metals and their compounds in the environment, Occurrence, analysis and biological relevance. pp. 1438. FYTIANOS, K. and LOURANTOU, A. (2004). Speciation of elements in sediment samples collected at lakes Volvi and Koronia, N. Greece. Environment International 30: 11-17. GARCIA -SANCHEZ, A. and ALVAREZ-AYUSO, E. (2003). Arsenic in soils and water and its relation to geology and mining activities (Salamanca Province, Spain). Journal of Geological Exploration 80: 69-79. GOMEZ ARIZA, J.L., GIRÁLDEZ, I., SÁNCHEZ-RODAS, D. and MORALES,E. (2000). Comparison of the feasibility of three extraction procedures for trace metal partitioning in sediments from south west Spain. The Science of the Total Environment 246: 271-283. GROSELL, M.H., HOGSTRAND, C. and WOOD, C.M. (1997). Copper uptake and turnover in both copper acclimated and non-acclimated rainbow trout (Oncorhynchus mykiss). Aquatic Toxicology 38: 257-276. HEALTH AND WELFARE CANADA, (1980). Guidelines for Canadian drinking water quality 1978. Supporting documentation. Supply and services Canada, Hull. HELLAWELL, J.M. (1986). Biological indicators of freshwater pollution and environmental management. Elsevier Applied Science Publishers Ltd., London pp. 546. JAIN, C.K. (2004). Metal fractionation study on bed sediments of River Yamuna, India. Water Research 38: 569-578. KLAVINS, M., RODINOV, V. and VERESKUNS, G. (1998). Metal and organochlorine compounds in fish from Latvian lakes. Bulletin of Environmental Contamination and Toxicology 60: 538-545. LESCHBER, R., DAVIS, R.D. and L’HERMITE, P. (1985). Chemical methods for assessing Bio-available metals in sludge and soils. Elsevier, London, 96 pp. LI, X., COLES, B.J., RAMSEY, M.H. and THORNTON, I. (1995). Sequential extraction of soils for multielement analysis by ICP-AES. Chemical Geology 124: 109-123. MESTER, Z., CREMISINI, C., GHIARA, E. and MORABITO, R. (1998).

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Comparison of two sequential extraction procedures for metal fractionation in sediment samples. Analytica Chimica Acta 359: 133-142. NEWMAN, M.C. and MCINTOSH, A.W. (1991). Metal Ecotoxicology: Concepts and Applications. Lewis Publishing, Michigan. pp 399. PIZZARO, I., GOMEZ, M., CAMARA, C. and PALACIOS, M.A. (2003). Arsenic speciation in environmental and biological samples Extraction and stability studies. Analytica Chimica Acta 495: 85-98. RODRIGUEZ, V.M., JIMENEZ-CAPDEVILLE, M.E., and GIORDANO, M. (2003). The effects of arsenic exposure on the nervous system. Toxicology letters 145: 1-18. SANDERS, M.J., DU PREEZ, H.H. and VAN VUREN J.H.J. (1999). Monitoring Cadmium and zinc contamination in fresh water systems with the use of the fresh water crab, Potamanautius warrenii. Water S.A. 25 (1): 91-98. SHINE, J. (2004). Biogeochemical control of heavy metal speciation and bioavailability in contaminated marine sediments. http://es.epa.gov/ncer/early/proj/earcar5.html SUTHERLAND, R.A. and TACK, F.M.G. (2003). Fractionation of Cu, Pb and Zn in certified reference soils SRM 2710 and SRM 2711 using the optimized BCR sequential extraction procedure. Advances in Environmental Research 8: 37- 50. TACK, F.M.G. and VERLOO, M.G. (1995). Chemical speciation and fractionation in soil and sediment heavy metal analysis: a review. International Journal of Environmental Analytical Chemistry 59: 225-238. TÜZEN, M. (2003). Determination of trace metals in the River Yesilirmak sediments in Tokat, Turkey using sequential extraction procedure. Microchemical Journal 74: 105-110. ULBRICH, K., MARSULA, R., JELTSCH, F., HOFMANN, H. and WISSEL, C. (1997). Modelling the ecological impact of contaminated river sediments on wetlands. Ecological Modelling 94: 221-230. VAN RYSSEN, R., LEERMAAKERS, M. and BAEYENS, W. (1999). The mobilisation potential of trace metals in aquatic sediments as a tool for sediment quality classification. Environmental Science and Policy 2: 75-86.

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Chapter 6:

Organic Contaminants in Sediment

199 Chapter 6: Organic Contaminants in Sediment

Chapter 6: Organic Contaminants in Sediment

Persistent organic pollutants (POP’s) are chemicals that may persist for long periods of time in the environment (Suchan et al., 2004). POP’s include polychlorinated biphenyls (PCB’s), polychlorinated dibenzo p-dioxins (PCDD’s), dibenzo furans (PCDF’s), polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCP’s). POP’s have been cause for concern since the 1960’s (Nowell et al., 1999). Due to their toxicity, persistence, tendency to accumulate in biota and their adverse effects on wildlife, the use of the majority of organochlorine pesticides was banned in the USA (Sapozhnikova et al., 2004).

6.1: Polychlorinated biphenyls

PCB’s are categorized as members of the group of ubiquitous, persistent, lipophilic, bio accumulative, highly toxic micro contaminants in the global environment (Falandysz et al., 2004). Due to their lipophilic nature they are persistent and are chemically prone to long range transport through the atmosphere and along the course of river systems (Suchan et al., 2004). Their lipophilic nature also allows them to accumulate in ecosystems.

PCB’s are primarily industrial in origin but due to their physical and chemical properties they mimic organochlorine pesticides (Sapozhnikova et al., 2004). PCBs are a group of halogenated aromatic compounds, which consist of a large group of 209 congeners (Storelli et al., 2004, Kimbrough, 1995). PCB’s have a long half-life and their presence in the environment is cause for concern relating to human health and toxicity in animals (Gallant et al, 2000).

In the aquatic environment fish are exposed to hydrophobic organic compounds (HOCs) both via direct contact with water and via the food uptake routes (Burreau et al., 2004). Uptake from water takes place over the gill membranes

200 Chapter 6: Organic Contaminants in Sediment and in food over the membranes in the gastro-intestinal tract. PCBs have various adverse physiological effects on aquatic organisms, which include development, reproduction and behaviour (Oliver, 1985; Ferraro et al., 1991). They also have a carcinogenetic and mutagenic effect on organisms (Suchan et al., 2004). As PCBs bio-magnify in the food chain the contamination of a system by PCBs can have negative effects on humans as well. Exposure to PCBs can lead to non-Hodgkin lymphoma, serious intellectual impairment in newborns, lymphatic/haematological malignancies and breast cancer in humans (Zuccato et al., 1999).

6.2: Pyrethoids

Synthetic pyrethroids are amongst the most potent and effective insecticides available, and account for more than 30% of the worlds market in insecticides (Philip and Rajasree, 1996). Synthetic pyrethroids such as Cypermethrin are being used increasingly due to their low toxicity in mammals, non-persistence and efficiency (Moore and Waring, 2001). Their efficiency and non-persistence lends them to be a good pesticide to use although they a highly toxic to fish (Coats and O’Donnel-Jeffery, 1979). They are used extensively in agriculture; in households and low doses are used in aquaculture as an effective insecticide on the ectoparasite Argulus spp. (Das & Mukherjee, 2003; Adhikari et al., 2004).

Cypermethrin is a neurotoxin and is highly toxic to fish, aquatic and terrestrial invertebrates and some beneficial arthropods such as shrimps and lobsters (Polat et al., 2002). The toxicity is due to the organisms inability to degrade and metabolise pyrethroids (David et al., 2004). They are also known to induce alterations in carbohydrate metabolism (Philip et al., 1995). The hypersensitivity of fish to this group of toxicants is partially due to differences in species specific pyrethroid metabolism and increased sensitivity of the piscine nervous system (Moore and Waring, 2001). The main route of uptake of pyrethroids in fish is via the gills (Adhikari et al., 2004). Pyrethroids, like cypermethrin, have also a

201 Chapter 6: Organic Contaminants in Sediment negative effect on the reproduction rates of some fish species. Studies by Moore and Waring (2001) indicate that the pyrethroids inhibit olfactory detection of the male reproductive priming pheromone from female Atlantic salmon. The pheromone is considered to be involved in the synchronisation of spawning between the sexes and thus pyrethroids negatively affects the spawning and reproduction of salmon.

6.3: Results and Discussion

The extent of pesticide contamination in the Nyl River system is not yet known. Sediment samples were analysed at the SANAS accredited laboratory, Testing and Conformity Services (Pty) Ltd, an affiliate of the SABS for a qualitative analysis. Samples from KNO, Jasper, Nylsvley, Olifants Spruit and Moorddrift were analysed. Both high flow (March 2002) and low flow (July 2002) conditions were analysed for 55 derivatives of pesticides from the main classes of organic contamination. Samples were analysed for organophosphates, organochlorides, PCB’s and triazines, carbamates and pyrethroids. Table 6.1 indicates the different pesticide sub groups and derivatives analysed.

The results obtained indicate that pesticides pose no potential threat to the system. Of the 55 contaminants, only four were found above detection limits. These derivatives (PCB 118, 101 and 52 and the pyrethroid, cypermethrin) were all below 12 mg/kg, which are concentrations too low to accurately quantify. Table 6.2 indicates the results obtained and the detection limits of the different organic compounds.

On a spatial scale the detected Organic compounds are present in the area between Nylstroom/Modimolle and before the start of the floodplain and Nylsvley. On a temporal scale the results indicate that the organic compounds in the system accumulate in the sediments during the low flow periods and are then remobilised and transported into the wetland itself during the high flow season.

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Table 6.1: Pesticide derivatives analysed in sediments to determine pesticide concentrations in sediment. Carbamates Organochlorine Organophosphorus Pyrethroids PCB’s pesticides pesticides & Triazines Aldicarb Alpha-BHC Dichlorvos Lambda- 2,4-Dichlorobiphenyl Cyhalothrin (PCB-8) Carbofuran Beta-BHC Phosdrin Permethrin 2,3,3-Trichlorobiphenyl (PCB-20) Carbaryl Gamma-BHC Diazinon Cypermethrin 2,4,4-trichlorobiphenyl (Lidane) (PCB-28) Methomyl Delta-BHC Chlorpyrifos-methyl Deltamethrin 2,2’,5,5’- tetrachlorobiphenyl (PCB-52) Oxamyl Heptachlor Chlorpyrifos- ethyl Esfenvalerate 2,2’,4,5,5’- pentachlorobiphenyl (PCB-101) 3-Hydroxycarbofuran Aldrin Malathion 2,3’,4,4’,5- pentachlorobiphenyl (118) Aldicarbofuran Epoxide Bromophos-methyl 2,2’,3,4,4’,5’ hexachlorobiphenyl (PCB-138) Aldicarbsulfoxide Endosulfan-I Parathion 2,2’,4,4’,5,5’- hexachlorobiphenyl (PCB-153) Methiocarb 4,4-DDE Carbophenothion 2,2’,3’,4,4’,5,5’- heptachlorobiphenyl (PCB-180) Propoxur Dieldrin Atrazine Endrin Simazine Endosulfan-II Terbuthylazine DDD Clorothalonil Endrin aldahyde 4,4-DDT Endosulfan sulphate Endrin ketone metoxychlor

These results indicate that POP’s are present in the system but the results are not conclusive, as data from sediments may not be representative of biota concentrations and cannot give information on contamination patterns in the upper levels of the food chain (Binelli and Provini, 2003). Further analysis on tissues from organisms in the system is recommended to ascertain the true extent of the pesticide contamination in the Nyl River System.

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Table 6.2: Table of results obtained indicating spatial and temporal distributions of POP’s in the Nyl River system. Sample PCB 52 PCB 118 PCB 101 Cypermethrin residue residue residue in residue in in mg/kg in mg/kg mg/kg mg/kg Detection 2 mg/kg 2 mg/kg 2 mg/kg 2 mg/kg Limit Jasper <12 mg/kg July 2002 Nylsvley <12 mg/kg March 2002 Olifants <12 <12 Spruit mg/kg mg/kg July 2002

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6.4: References.

ADHIKARI, S., SARKAR, B., CHATTERJEE, A., MAHAPATRA, C.T. and AYYAPPAN, S. (2004). Effects of cypermethrin and carbofuran on certain haematological parameters and prediction of their recovery in a freshwater teleost, Labeo rohita (Hamilton). Ecotoxicology and Environmental Safety 58. pp 220-226. BINELLI, A. and PROVINI, A. (2003). The PCB pollution of Lake Iseo (N.Italy) and the role of biomagnification in the pelagic food web. Chemosphere 53. pp 143-151. BURREAU, S. ZEBUHR, Y. BROMAN, D. and ISHAQ, R. (2004). Biomagnification of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) studied in pike (Esox lucius), perch (Perca fluviatilis) and roach (Rutilus rutilus) from the Baltic Sea. Chemosphere 55. pp 1043- 1052. COATS, J.R. and O’DONNEL-JEFFERY, N.L. (1979). Toxicity of four synthetic pyrethroid insecticides to rainbow trout. Bulletin of Environmental Contamination and Toxicology 23. pp 250. DAS, B.K. and MUKHERJEE, S.C. (2003). Toxicity of cypermethrin in Labeo rohita fingerlings: biochemical, enzymatic and haematological consequences. Comparative Biochemistry and Physiology (C) 134. pp 109-121. DAVID, M., MUSHIGERI, S.B., SHIVAKUMAR, R. and PHILIP, G.H. (2004). Response of Cyprinus carpio (Linn) to sublethal concentration of cypermethrin: alterations in protein metabolic profiles. Chemosphere 56. pp 347-352. FALANDYSZ, J., WYRZYKOWSKA, B., WARZOCHA, J., BARSKA, I., GARBACIK-WESOLOWSKA, A. and SZEFER, P. (2004). Organochlorine pesticides and PCBs in perch Perca fluviatilis from the Odra/Oder River Estuary, Baltic Sea. Food Chemistry 87. pp 17-23. FERRARO, S.P., LEE II, H., SMITH, L.M., OZRETICH, R.J. and SPECHT, D.T. (1991). Accumulation factors for eleven polychlorinated biphenyl congeners. Bulletin of Environmental Contamination and Toxicology 46. pp 276-283. GALLANT, T.L., SINGH, A. and CHU, I. (2000). PCB 118 induces ultrastructural alterations in the rat liver. Toxicology 145. pp 127-134. KIMBROUGH, R.D. (1995). Polychlorinated biphenyls (PCBs) and human health: an update. CRC Critical Revision of Toxicology 25. pp 133-163. MOORE, A. and WARING, C.P. (2001). The effects of a synthetic pyrethroid pesticide on some aspects of reproduction in Atlantic salmon (Salmo salar L.). Aquatic Toxicology 52. pp 1-12. NOWELL, L.H., CAPEL, P.D. and DILEANIS, P.D. (1999). Pesticides in stream sediment and aquatic biota: distribution, trends, and governing factors. Lewis Publishers, Boca Raton, FL. OLIVER, B.G. and NIIMI, A.J. (1985). Bioconcentration factors of some halogenated organics for the rainbow trout: limitations in their use for prediction of environmental residues. Environmental Science Technology 19. pp 842-849. PHILIP, G.H. and RAJASREE, B.H. (1996). Action of cypermethrin on tissue

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transamination during nitrogen metabolism in Cyprinus carpio. Ecotoxicology and Environmental Safety 34. pp 174-179. PHILIP, G.H., REDDY, P.M. and SRIDEVI, G. (1995). Cypermethrin-induced in vivo alterations in the carbohydrate metabolism of freshwater fish, Labeo rohita. Ecotoxicology and Environmental Safety 38. pp 173-178. POLAT, H., ERKOÇ, F.Ü., VIRAN, R. and KOÇAK, O. (2002). Investigation of acute toxicity of beta-cypermethrin on guppies Poecilia reticulata. Chemosphere 49. pp 39-44. SAPOZHNIKOVA, Y., BAWARDI, O. and SCHLENK, D. (2004). Pesticides and PCBs in sediments and fish from the Salton Sea, California, USA. Chemosphere 55. pp 797-809. STORELLI, M.M., STORELLI, A., D’ADDABBO, R., BARONE, G. and MARCOTRIGIANO, G.O. (2004). Polichlorinated biphenyl residues in deep- sea fish from Mediterranean Sea. Environment International 30. pp 343-349. SUCHAN, P., PULKRABOVÁ, J., HAJŠLOVÁ, J. and KOCOUREK, V. (2004). Pressurized liquid extraction in determination of polychlorinated biphenyls and organochlorine pesticides in fish samples. Analytica Chimica Acta 520 (1-2). pp 193-200. ZUCCATO, E., CALVARESE, S., MARIANI, G., MANGIAPAN, S., GRASSO, P., GUZZI, A. and FANELLI, R. (1999). Level sources and toxicity of polychlorinated biphenyls in the Italian diet. Chemosphere 38 (12). pp 2753- 2765.

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Chapter 7:

Development of a Wetland Assessment Protocol

207 Chapter 7: Development of a wetland assessment protocol.

Chapter 7: Development of a Wetland Assessment Protocol

Biological assessments evaluate the health of a water body by directly measuring the condition of one or more of its taxonomic assemblages (e.g. plants, macro- invertebrates, etc.) and supporting chemical and physical attributes. A major premise of bio-assessments is that biotic communities of plants and animals will reflect the health of the water body in which they live. Changes will occur in floral and faunal community structure, diversity, organism health and trophic structure after damage from anthropogenic activities has occurred (USEPA, 2002a)

In wetlands minimal human activities will cause little effect to the biotic communities (Karr and Dudley, 1981). These communities are usually very resilient and will recover quite quickly. Biological integrity can be regarded as the ability to “support and maintain a balanced adaptive community of organisms having a species composition, diversity and functional organisation comparable to that of natural habitats within a region” (Karr and Dudley, 1981).

When the interaction of wetland plants and animals with their environment is disrupted many of the functions provided by the wetlands are lost or diminished (USEPA, 2002a). The most direct and cost effective way to evaluate the integrity of a wetland is to directly measure the attributes of the floral and faunal communities that inhabit the wetland. Chemical endpoints are not suitable for evaluating wetlands as there are too many of chemical endpoints to monitor and many studies are limited by financial and staff resource constraints (USEPA, 2002a).

Stream based bio-assessment programs have found that bio-assessment programs are less expensive than many chemical based assessment programs (Yoder and Rankin, 1995).

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There are many other factors that affect a system or which could be monitored to assess the biological integrity of a system. These factors are illustrated in Figure 7.1.

Figure 7.1: Ecosystem influences on biological integrity. (Adapted from Karr et al., 1986).

Bio-assessments can help prioritise where to follow up with additional monitoring, diagnosis of causes of degradation and assist in informed management decision making in the protection and rehabilitation of wetlands.

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Bio-assessments are based on the premise that the biotic communities will reflect the integrity of the wetland system. Decreases in community structure, abundance and diversity are sure signs of damage to the system. Bio- assessment methods developed for streams and rivers can be and have been adapted for use in the monitoring of wetlands, lakes, estuaries and terrestrial systems (USEPA, 1998, Karr and Chu, 1999).

The development of a wetland assessment protocol involves the following six stages of development: Selection of the biological assemblage to monitor. Classification of the wetland. Selection of wetlands across a human disturbance gradient to monitor. Sampling of chemical and physical characteristics to use in result validation. Data analysis. Result reporting.

The rest of this chapter will be discussed under these six headings with the aim of providing a framework for wetland assessment in the Limpopo Province.

7.1: Biological Assemblages

A variety of biological assemblages can be used to assess the integrity of wetland systems. These assemblages include fish, plants, macro-invertebrates, algae and amphibians. Each of these assemblages has their own pitfalls and merits. During the sampling phase of this study both fish and aquatic invertebrates were sampled. For the purpose of this assessment system macro- invertebrates were the assemblage of choice, due to the nature of the water in the wetland and the ephemeral nature of the stream fish were difficult to sample thus making aquatic invertebrates the next best choice.

There are many reasons for the use of macro-invertebrates, the least of which is

210 Chapter 7: Development of a wetland assessment protocol. that they have successfully been used in the monitoring of river and stream integrity in South Africa. Table 7.1 indicates the advantages and disadvantages of using Macro-invertebrates as bio-indicators of system integrity.

Table 7.1: Table of advantages and disadvantages in using aquatic macro- invertebrates as bio-indicators of wetland integrity. (USEPA, 2002b) Advantages and disadvantages of using invertebrates for biological analysis of wetlands Advantages Disadvantages Invertebrates can be expected to respond to a Because it is likely that multiple stressors are wide array of stresses to wetlands, such as present, it may not be possible to pinpoint the pollutants in water and bottom sediments, precise cause of a negative change in the nutrient enrichment, increased turbidity, loss or composition of invertebrates. However, data simplification of vegetation, siltation, rearing of from major sources of human disturbance, e.g., bait or game fish, input of storm water or water and sediment chemistry, the nearby wastewater runoff, introductions of exotic wetland landscape features, sources of species, or alterations of the landscape around hydrologic alteration, and other disturbance the wetland. factors cam be assessed in relation to the invertebrate data to see which factors have the greatest effects. Life cycles of weeks to months allow integrated Information on short-term, pulse impairments responses to both chronic and episodic (using algae, zooplankton) or more long-term pollution, whereas algae recover rapidly from impairments (using macrophytes, vertebrates) acute sources, and vertebrates and or more landscape-level (using birds, macrophytes may take longer to respond to amphibians) impairment may be desired. chronic pollution. Toxicological/laboratory based information is Toxicological response data may not be extensive. Invertebrates are used for a large available for all invertebrates; data for some variety of experimental approaches. wetlands species are less extensive than for stream species. There is an extensive history of analysis of Using invertebrates to assess the condition of aquatic invertebrates in biological monitoring wetlands is now under development in several approaches for streams. States and organizations. Invertebrates are used for testing Tissue contaminant analyses are always bioaccumulation of contaminants to analyze costly. This is true for tissue analysis of any effects of pollutants in food webs. group of organisms: vertebrate, invertebrate, or plant. Invertebrates are important in food webs of Aquatic invertebrates tend not to be valued by fish, salamanders, birds, waterfowl, and the public as much as fish, amphibians, turtles, predatory invertebrates. or birds. However, citizens do respond to invertebrates. Many invertebrates are ubiquitous in standing Invertebrate composition will differ in different water habitats. wetland classes, as will other groups of organisms (plants, birds) that might be used to assess wetlands.

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Table 7.1 cont:

Many invertebrates are tightly linked to wetland Some invertebrates migrate in from other water conditions, completing their life cycles within bodies; these taxa are not as tightly linked to the wetlands. They are exposed to site-specific the conditions in the specific wetland. conditions. Many invertebrates depend on diverse wetland Loss of invertebrates may be a secondary vegetation, some depend on particular types of effect from the loss of wetland vegetation, e.g., vegetation for reproduction. from herbicide treatments. Vegetation loss is an impairment. Invertebrates have short and long life cycles Many complete their life cycle within a year, and they integrate stresses to wetlands often they are not as "long-lived" as birds, within a 1-year time frame. amphibians or perennial vegetation. Invertebrates can be easily sampled with . Picking invertebrate samples is labor - standardized methods intensive. Invertebrates can be sampled once during the Invertebrate composition of wetlands often year, if the best index period is selected for varies within the seasons of the yearly cycle. optimal development of invertebrates. Invertebrates mature at different times. This necessitates selecting an "index period" for sampling once, or alternatively, sampling more than once in the season. Invertebrates can be identified using available Expertise is required to perform identifications taxonomic keys within labs of the entities doing of invertebrates. Some may choose to contract the monitoring. Staff help develop out some or all the identifications. There is a biomonitoring programs. cost involved. High numbers of taxa and individual counts Large numbers of taxa and individual counts permits the use of statistical ordination make the sample processing more labor techniques that might be more difficult with just intensive than other groups. Adequate training a few species, e.g. with amphibians. and staff time are required. More lab time is needed than for some other groups of organisms. Citizens can be trained to identify wetlands Citizen monitoring requires training to learn invertebrates and become interested and many invertebrates in a short time, a structured involved in wetlands assessment. Citizens are program, and a commitment by volunteers and excited to see the richness of wetland local governments; citizens may tend to invertebrates. underrate high quality wetlands.

7.2: Wetland Classification

The classification of wetlands is of great importance in assessing wetlands and in being able to draw comparisons to other similar wetlands. The monitoring system must be validated in a number of different wetlands and it is important to compare similar systems with differing levels of anthropogenic impacts. One of the ways to simplify the evaluation of wetlands is to classify the wetlands and only compare wetlands within the same class (USEPA, 2002a)

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There are many definitions of wetlands which are broad in nature and thus classification of the system a necessity. The overall goal of classification is to reduce the variability within classes caused by differences in natural condition related to factors such as geology, hydrology and climate (USEPA, 2002c). For the purposes of developing bio-assessment methods, the goal is to establish classes of wetlands that have similar biological communities and the same expected response to similar human disturbances (USEPA, 2002a)

On a broad scale wetlands can be divided into the following categories: (1) swamps and marshes, (2) lakes, (3) estuaries, (4) marine, (5) riverine and (6) artificial wetlands. These classes can further be divided into permanent and seasonal classes with respect to duration of flow/ inundation (Frazier, 1999).

The protocol described in this chapter is specifically for ephemeral, riverine floodplains. The Nyl River Floodplain served as test site for the wetland assessment protocol.

7.3: Wetland Selection

After wetland classification it is important to select sampling sites along a disturbance gradient. These sites are used to document how the biological assemblage responds to differing levels of human disturbance (USEPA, 2002d). The disturbance gradient used is not important, but rather the sites should be selected from minimally disturbed to severely disturbed. In selecting the sampling sites one should not become preoccupied with the disturbance gradient, as it is impossible to take every way that humans can disturb a wetland into account, but the gradient must be estimated sufficiently enough to allow for calibration of selected matrices (Karr and Chu, 1999). The expected disturbances should also be defined and described to allow for sufficient sampling at either end of the disturbance gradient (USEPA, 2002a).

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7.4: Sampling Method Selection

The sampling method selected was a modification on the method used in the South African Scoring System version 5 (SASS5). The system has successfully been modified by Thirion (2000) for use in impoundments or deep water. The SASS system was modified by using artificial substrates to make sampling of deep localities easier and to allow for anaerobic conditions during summer periods in impoundments. The sampling method should be simple and not require the services of highly trained personnel. In the SASS5 protocol three habitats are sampled namely stones, vegetation and sand/grave l/mud. These biotopes cover the range of in-stream habitats available and thus allow for representative sampling of the entire reach of the sampling site. Due to the lack of biotope variation in wetlands, it was decided that the vegetation biotope was the most suitable biotope to sample, as it contains a larger diversity of organisms. This biotope is important in the system and provides the necessary refugia and food sources for the macro invertebrates to colonise. Aquatic macro- invertebrates were sampled using a 30 cm by 30 cm 1000 micron nylon mesh net. Approximately five meters of marginal vegetation, submerged vegetation or a mixture of both was sampled, by sweeping the net through the vegetation to brush the macro-invertebrates into the net. The invertebrates were then transferred into a photographic tray or similar sort of vessel for on site identification. (Adapted from Dickens and Graham, 2002).The organisms were identified and recorded on a SASS 5 score sheet. Identification of organisms was aided using Aquatic invertebrates of South African Rivers: Illustrations (Gerber and Gabriel, 2002b). Figure 7.2 illustrates the score sheet used during the data collection phase of the protocol. The sampler will need the following equipment which is relatively inexpensive and easily obtainable: Waders*, Sampling Net, A3 photo tray or similar container, sample bottles*, forceps*, preservation solution*, data sheets and Aquatic Macro-invertebrate identification field guide. The items marked with an asterisk are optional. Samples can be identified either in the laboratory or in the field.

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SASS Version 5 Score Sheet Taxon S Veg GSM Tot Taxon S Veg GSM Tot Taxon S Veg GSM Tot PORFERA 5 HEMIPTERA DIPTERA Date: / / 200 COELENTERATA 1 Belostomatidae 3 Athericidae 10 TURBELLARIA 3 Corixidae 3 Blepharoceridae 15 Collector: ANNELIDA Gerridae 5 Ceratopogonidae 5 Oligocheata 1 Hydrometridae 6 Chiromonidae 2 Grid Reference: WGS-84 Cape Date Leeches 3 Naucoridae 7 Culicidae 1 CRUSTACEA Nepidae 3 Dixidae 10 S: " ' , E: " ' . Amphipoda 13 Notonectidae 3 Empididae 6 Potamonautidae 3 Pleidae 4 Ephydridae 3 Site Code: Atyidae 8 Veliidae/M…veliidae 5 Muscidae 1 River:……………………………. Palaemonidae 10 MEGALOPTERA Psychodidae 1 Site Description:……………………. HYDRACARINA 8 Corydalidae 8 Simulidae 5 Weather Condition:…………………… PLECOPTERA Sialidae 6 Syrphidae* 1 Notonemouridae 14 TRICHOPTERA Tabanidae 5 Temp:……… pH:………… Perlidae 12 Dipseudopsidae 10 Tipulidae 5 DO:…………mg/lCond:………ms/m EPHEMEROPTERA Ecnomidae 8 GASTROPODA Baetidae 1sp 4 Hydropsychidae 1sp 4 Ancylidae 6 Biotopes Sampled: Baetidae 2sp 6 Hydropsychidae 2sp 6 Bulinidae* 3 SIC………… Time………. minutes Baetidae >2 sp 12 Hydropsychidae >2sp 12 Hydrobiidae* 3 SOOC…….. Time………. minutes Caenidae 6 Philopotamidae 10 Lymnaeidae* 3 Average size of stones…………….cm Ephemeridae 15 Polycentropodidae 12 Physidae* 3 Bedrock…………….. Heptageniidae 13 Psychomyiidae/Xiphocen 8 Planorbidae* 3 Aquatic veg'n………. Dom. Sp………… Leptophlebiidae 9 Case Caddis: Thiaridae* 3 MvegIC Dom. Sp………… Oligoneuridae 15 Barbarochthonidae SWC 13 Viviparidae* ST 5 MvegOC Dom. Sp………… Polymitarcyidae 10 Calamoceratidae ST 11 PELECYPODA Gravel………….. Prosopistomatidae 15 Glossosomatidae 11 Corbiculidae 5 Sand…………….. Teloganodidae SWC 12 Hydroptilidae 6 Sphaeriidae 3 Mud………………. Tricorythidae 9 Hydrosalpingidae 15 Unionidae 6 Hand picking/ visual observation………….. ODONATA Lepidostomatidae 10 SASS Score Flow : Low/ Medium/ High Calopterygidae 10 Leptoceridae 6 No. of Taxa Turbidity : Low/ Medium/ High Chlorocyphidae 10 Petrothrincidae SWC 11 ASPT Riperian Land Use: Chlorolestidae 8 Pisuliidae 10 Coenagrionidae 4 Sericostomatidae SWC 13 Sample collection efforts exceeds method?..... Lestidae 8 COLEOPTERA Disturbances in the river: eg. Sandwinning, Platycnemidae 10 Dytiscidae* 5 cattle drinking point, floods etc. Protoneuridae 8 Elmidae/Dryopidae* 8 Other biota including juveniles: Aeshnidae 8 Gyrinidae* 5 Corduliidae 8 Haliplidae* 5 Observations: eg. Smell and colour of water Gomphidae 6 Helodidae* 12 Comments: petroleum, dead fish, etc. Libellulidae 4 Hydraenidae* 8 LEPIDOPTERA Hydrophilidae* 5 Pyralidae 12 Limnichidae 10 Psephenidae 10 Figure 7.2 SASS5 score sheet used for primary data collection (Dickens and Graham, 2002).

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7.5: Data Analysis and Matrix Determination.

The determination of a single matrix for the evaluation of wetland integrity is difficult due to the uniqueness of the floral and faunal assemblages as well as the ecological processes (Wissinger 1999). It is also unrealistic to expect to find a single index of wetland integrity for all wetlands, due to the wide variation in wetlands from a geographical, hydrological, wetland class and biological aspects (USEPA, 2002d). According to Gemes and Helgen (1999) the monitoring of a number of assemblages increases the power of wetland bio-assessments. It is for this reason that a multi pronged approach was decided upon for the assessment of the Nyl River Floodplain. The three prongs of the index were Aquatic Macro-invertebrates, Habitat Quality Rating and a Land Usage Rating. The scores obtained from the three prongs were then aggregated to provide a Wetland Biological Index Score or WBI.

Aquatic Macro-invertebrates.

The invertebrate families chosen to act as indicator species for the monitoring were selected according to two criteria. The first criterion used was the determination of the families present in the system during sampling periods. Two high flow and two low flow periods were sampled using the SASS5 method of sampling and data collection (Dickens and Graham, 2002). The families identified in the vegetation biotope were then placed on a list and checked for compliance to the second criterion. For the second criterion the listed families were checked for habitat preference in the Aquatic Invertebrates of South Africa Field Guide (Gerber and Gabriel, 2002a). Only those families found on both lists were then used as indicator families for the WBI.

Table 7.2 indicates the invertebrate families chosen to act as indicator families in the Nyl River Floodplain System. The relative sensitivities obtained for and use in SASS5 was used to obtain the invertebrate score.

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Table 7.2: Invertebrate sampling list with relative sensitivities according to the SASS5 score sheet (Adapted from Dickens and Graham, 2002). Taxon Sensitivity Presence Potaminautidae 3 Atydae 8 Hydrachnellae 8 Baetidae 4 Chlorocyphidae 10 Chlorolestidae 8 Coenagrionidae 4 Lestidae 8 Aeshnidae 8 Belostomatidae 3 Corixidae 3 Gerridae 5 Naucoridae 7 Nepidae 3 Notonectidae 3 Pleidae 4 Veliidae 5 Leptoceridae 6 Dytiscidae 5 Gyrinidae 5 Helodidae 12 Chironomidae 2 Culicidae 1 Simulidae 5 Lymnaeidae 3 Physidae 3 Planorbidae 3 Dixidae 13 Leeches 3 Hydrophilidae 5 Lepistomatidae 10 Pisuliidae 10 Planerians 3 Oligochaetes 1 Elmidae 8 Total A

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Habitat Quality Rating

Habitat quality plays an important role in the monitoring of macro-invertebrates. Sites with a more diverse habitat will have a greater diversity of invertebrates, but this may not indicate the water quality in which they live (Pennak, 1978). It is thus important to negate the effects of habitat on the score obtained in the final WBI. For this reason a simple table of weighted questions was set up. Answers to five questions were assigned a value between 1 and 5 with the habitat rating score being calculated by adding the values together. Table 7.3 indicates the list of questions relating to habitat quality. Invertebrate community structures improve with an improvement in habitat quality. Weighted values were thus assigned to percentage bank cover, percentage aquatic vegetation and percentage fringing/ leafy vegetation. The weighted scores assigned fall within the following categories: 0-20% 1 21-40% 2 41-60% 3 61-80% 4 81-100% 5 These scores allow the sampler to rate the habitat with a high score denoting a good habitat quality and a low score denoting a poor habitat quality, or lack of habitat. The habitat quality rating is divided into five questions giving the habitat a score out of 25 in the end. The questions are simple but provide the relevant information as to habitat suitability for the presence of aquatic macro- invertebrates. The five questions are: Percentage right bank cover? Percentage left bank cover? Percentage submerged aquatic vegetation? Percentage right bank cover fringing/Leafy? Percentage left bank cover fringing/Leafy? For the sampler to assess the habitat quality he/she should have an

218 Chapter 7: Development of a wetland assessment protocol. understanding of the relevant definitions.

Left or Right: the left or right hand side of the channel is determined according to the direction of flow of the river. This means that if you stand facing the same direction as to the river flow, the left bank will be on your left side and the right bank will be on your right side. Percentage Bank Cover: defines the percentage of the bank that is covered by vegetation in comparison to bare ground. Percentage Aquatic Vegetation: is defined as the amount of submerged or floating vegetation cover in comparison to open water and bare substrate. Percentage Fringing Vegetation: this refers to the percentage of the bank cover that is herbaceous and leafy in nature hanging in or submerged in water. This type of plant cover provides better cover and more food source for the organisms than reeds, sedges and grasses do.

The habitat rating could be subjective but the broad nature of the differential percentage classes erases some of the subjectivity involved in the assessment process.

Table 7.3: Habitat Quality Rating based on percentage vegetation cover Habitat Quality Rating 0-20% 21-40% 41-60% 61-80% 81-100% % Left Bank Cover 1 2 3 4 5 % Right Bank Cover 1 2 3 4 5 % Aquatic Vegetation 1 2 3 4 5 % Left Bank Fringing 1 2 3 4 5 Vegetation % Right Bank Fringing 1 2 3 4 5 Vegetation Total B

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Land Usage Rating.

Different anthropogenic land use activities can cause a decline in the macro- invertebrate community. These land use practises can vary from mining activities, both agricultural and livestock farming activities and the construction of unnatural barriers (roads, impoundments, dams etc.). The land uses at the sites were assigned a weighted score between 0 and 3. Table 7.4 indicates the land use practises and the weighted score assigned to each practise.

Scores assigned to each activity were chosen randomly with the activity having a large impact scoring a zero and if the activity is not present the activity scores a three. The different activities were rated from sever to none. A high Land Use Rating score indicates a site with little observed impact and with a low rating score having a high level of anthropogenic impact. The maximum Land Use Rating obtainable for a site is a score of 15.

Table 7.4: Land Usage Rating Score Land Use Rating Severe Moderate Minimal None Mining 0 1 2 3 Agriculture 0 1 2 3 Livestock 0 1 2 3 Urban 0 1 2 3 Other 0 1 2 3 Total C

Wetland Biological Index Score.

The three scores obtained were then placed in the following simple equation to establish the WBI.

220 Chapter 7: Development of a wetland assessment protocol.

WBI=A-B+C

Where: A is the Invertebrate score B is the Habitat Quality Rating C is the Land Use Rating.

Due to the increases made on invertebrate scores by a high habitat rating it was decided to subtract the Habitat Quality Rating from the score to negate the habitats’ role in the invertebrate score. The land usage plays a role in the decline in invertebrate community structure so a high score means little impacts from land usage and thus plays a role in the integrity of the site. Figure 7.3 illustrates the score sheet developed for use in the wetland biological index.

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Date__/___/20__ Site:______Sampler:______

Taxon Sensitivity Presence Taxon Sensitivity Presence Habitat Quality Rating (HQR) 0-20 21-40 41-60 61-80 81-100 CRUSTACEA COLEOPTERA Potaminautidae 3 Dytiscidae 5 % Left Bank 1 2 3 4 5 Atydae 8 Gyrinidae 5 Cover Hydrachnellae 8 Elmidae 8 % Right Bank EPHEMEROPTERA Hydrophilidae 5 1 2 3 4 5 Cover Baetidae 4 Helodidae 12 ODONATA DIPTERA % Aquatic 1 2 3 4 5 Chlorocyphidae 10 Chironomidae 2 Vegetation Chlorolestidae 8 Culicidae 1 % Left Bank Coenagrionidae 4 Dixidae 13 1 2 3 4 5 Lestidae 8 Simulidae 5 Fringing Aeshnidae 8 GASTROPODA HEMIPTERA Lymnaeidae 3 % Right Bank 1 2 3 4 5 Belostomatidae 3 Physidae 3 Fringing Corixidae 3 Planorbidae 3 Gerridae 5 ANNELIDA B Naucoridae 7 Oligochaetes 1 Land Use Rating Nepidae 3 Leeches 3 Severe Moderate Minimal None Notonectidae 3 Mining 0 1 2 3 0 1 2 3 Pleidae 4 Planerians 3 Agriculture Livestock 0 1 2 3 Veliidae 5 Urban 0 1 2 3 CASED CADDIS: Other 0 1 2 3 Leptoceridae 6 A C WBI = A - B + C A B C WBI

Figure 7.3: WBI Data Sheet

222 Chapter 7: Development of a wetland assessment protocol.

7.6: Result Reporting.

The results obtained from the data sheets can then be reported with reference to weighted invertebrate scores, habitat quality and land use. The wetland integrity can also be reported with the WBI able to relate water quality of the system. The WBI does however not specify the cause of the disturbance in the invertebrate community structure but does flag the system as to whether it is being impacted or not, thereby allowing for management decisions to be made. Interpretation of the results should take into account that the seasons play a role in the invertebrate community structure and that WBI values may decrease during periods of low flow and extreme high flow. The system has as yet not been calibrated and compared to other wetland systems similar in nature so reference (maximum) WBI values cannot be stated at this point in time.

7.7: Case study

The Nyl River Floodplain was chosen as the wetland for this study. Six localities were chosen along the course of the Klein Nyl River with three sites inside the wetland itself and three sites in the river before it flows into the wetland. The six localities selected were Abba, DPD, Jasper, Nylsvley, Haakdoring and Moorddrift. (For the positioning of these localities refer to Figure 2.1 in Chapter 2). As mentioned earlier in this chapter the WBI has specifically been developed for this type of system namely ephemeral riverine floodplains. The localities were situated along a pollution/impact gradient so as to provide the necessary information as to whether the WBI could indicate the effects of human impacts on the invertebrate community structure.

Invertebrates from the six localities were sampled using the protocol described in the previous sections and the organisms were identified. The habitat was rated as well as the surrounding land uses. Water and sediment samples were also collected and analysed back in the laboratory. These data were used as a

223 Chapter 7: Development of a wetland assessment protocol. measuring stick against which the wetland assessment protocol could be evaluated.

Figure 7.4 indicates the different processes that the samples from the different localities were subjected to.

SAMPLES

BIOTIC ABIOTIC

FACTORS FACTORS

WATER SEDIMENT

AQUATIC INVERTEBRATES SEQUENTIAL PESTICIDES EXTRACTION

METALS NUTRIENTS TOXICITY AND MACRO- TESTING VARIABLES

Figure 7.4: Flow diagram of sampled components and analysis conducted.

Table 7.5 indicates the scores obtained at the different localities during the four sampling periods.

224 Chapter 7: Development of a wetland assessment protocol.

Table7.5: Table of WBI scores calculated during study period. Wetland Biological Integrity Index August November March July 2002 2001 2001 2002 Abba 88 43 53 DPD 33 62 58 Jasper 15 35 16 Nylsvley 37 42 29 42 Haakdoring 57 14 33 57 Moorddrift 37 43 54 52

A. B.

C. D.

Figure 7.5 (A-D): Principle component analysis of Nylsvley water quality for (A)August 2001, (B)November 2001, (C)March 2002 and (D)July 2002 with the calculated WBI superimposed onto it.

225 Chapter 7: Development of a wetland assessment protocol.

The results were then compared to those obtained for the water analysis for the same period. The comparisons were made by superimposing the WBI scores onto the Principle Component Analysis Plots of the water quality at each locality. Figures 7.5 (A-D) illustrate the superimposed WBI scores on the PCR plots with the bubbles of similar size indicating water with similar WBI scores and water qualities.

The results discussed in Chapter 4 indicate that for the most part the water in the Nyl River system is of a suitable quality. The water does however have bacterial contamination at the sites analysed. The results from the WBI indicate these trends that bacterial contamination is also affecting the aquatic invertebrate communities.

In Figure 7.5 (A) the bubble superimposed onto the site at Haakdoring indicates that the WBI score at this site is high in relation to the other scores. The size of bubbles at Moorddrift, Nylsvley and DPD indicate that the invertebrate communities are similar. The large angles between Moorddrift, DPD and Nylsvley indicate that the water quality at these sites is not similar, but the variable/s causing dissimilarity in the water quality is not affecting the invertebrate communities adversely, in relation to one another. The larger bubble at Haakdoring indicates a higher WBI score and thus a healthier invertebrate community. This can be attributed to a lack of cattle in the area and the larger volume of water present during the dry conditions experienced throughout the system. No bubble values at Jasper and Abba are due to a lack of data so the WBI could not be applied at these sites.

In Figure 7.5 (B) the bubble sizes at the sites indicate that the water quality at Abba and DPD are of a better quality and more suitable for sustaining aquatic invertebrates. The increased water flow due to precipitation has led to a decrease in water quality due to increased runoff from farmlands. The small bubble values at both Jasper and Haakdoring indicate poor invertebrate

226 Chapter 7: Development of a wetland assessment protocol. community structure and would thus indicate a decrease in water quality. The water quality data in Chapter 4 mirrors this fact with both sites having similar water qualities. The bubble sizes at Nylsvley and Moorddrift indicate that the invertebrate communities at these sites are similar in nature and would indicate that the effects of the contamination at Jasper and Haakdoring have less of an effect on the water quality, or that the water quality at these sites is improving. The poor invertebrate community structure can in all probability be as a result of bacterial contamination in the form of coliform bacteria. This figure indicates clearly that the sites situated before Nylstroom/Modimolle have better invertebrate community structure and that Nylstroom/Modimolle has an effect on the system. The acute angles (refer to Chapter 3.5) between the plotted sites of DPD, Nylsvley and Abba indicate that these sites have similar water qualities.

In Figure 7.5 (C) the invertebrate communities appear to be similar in nature based on the similar sized bubble plots. The acute angles between the water qualities at five of the six sites indicate that the water quality is also very similar in nature. Moorddrift is the outlier with respect to water quality and invertebrate community structure indicates that the water leaving the floodplain is of a better quality than that of the water in the Klein Nyl River and of that entering the floodplain. This would indicate that the floodplain is functioning correctly by slowing down the water movement and removing possible contaminants from the water. March 2002 is at the end of the high flow period and the water moves quicker than during dry months so possible contaminants are being spread throughout the system thereby resulting in the system displaying similar water quality at all the localities. The size of the WBI bubbles as well as the WBI score indicates that the invertebrate community structures are similar in relation to the similar water qualities.

In Figure 7.5 (D) Jasper is the only site with a small bubble size, which would indicate that the invertebrate community at this site is under the influence of a stressor. Four of the other five sites namely: Haakdoring, Moorddrift, DPD and

227 Chapter 7: Development of a wetland assessment protocol.

Abba have similar bubble sizes indicating similar invertebrate community structures. The Nylsvley bubble size is slightly smaller than the other bubble sizes, which indicates the effects of the water from the contaminated Jasper site with a large degree of system recovery with respect to the water quality due to the increased WBI score.

The WBI indicates that throughout all sampling periods, increased levels of disturbance cause the WBI scores to decrease. The clearest indication of this is the sampling done during July 2002, with the WBI score indicating that the Jasper site is contaminated with sewage effluents, and this is reflected by the invertebrate community structure.

The results of the WBI indicate that the WBI scores reflect stressors to the system although more sampling and refinement is necessary before this index can be used as a tool to evaluate the integrity of ephemeral, floodplain wetland health. Ephemeral wetland systems with greater pollution gradients need to be monitored using this tool to validate its efficacy. The nature of the water quality in the Nyl River Floodplain is such that it has few contaminants thus making it not a very good system to calibrate an index of this nature. The water quality (Chapter 4) indicates that bacterial contamination is the only cause for concern in the system. the metal concentrations in the water are consistent at all localities and are from a natural source. Nutrification of the water in the system also is not having an effect on the water in the system. Calibration and refinements such as the addition or subtraction of invertebrate families can only take place once the Wetland Assessment Protocol has been tested on a number of systems and over a greater time frame.

228 Chapter 7: Development of a wetland assessment protocol.

7.8: References

DICKENS, D.W.S. and GRAHAM, P.M. (2002). The South African Scoring System (SASS) version 5 Rapid Bioassessment Method for Rivers. African Journal of Aquatic Science 27: 1-10. FRAZIER, S. (1999). Ramsar Sites Overview: A Synopsis of the World’s Wetlands of International Importance. Wetlands International. pp 42. GEMES, M.C. and HELGEN, J.C. (1999). Indexes of Biotic Integrity (IBI) for Wetlands . Vegetation and invertebrates IBI’s. Final Report to U.S.EPA. Assistance #CD 995515-01. Minnesota Pollution Control Agency, Environmental Outcomes Division. GERBER, A. and GABRIEL, M.J.M. (2002a). Aquatic Invertebrates of South African Rivers: Field Guide (1st ed.). Institute for Water Quality Studies. Department of Water Affairs and Forestry, Pretoria. pp 150. GERBER, A. and GABRIEL, M.J.M. (2002b). Aquatic Invertebrates of South African Rivers: Illustrations (1st ed.). Institute for Water Quality Studies. Department of Water Affairs and Forestry, Pretoria. KARR, J.R. and CHU, E.W. (1999). Restoring Life in Running Waters: Better Biological Monitoring. Washington, D.C.: Island Press. Pp 220. KARR, J.R. and DUDLEY, D.R. (1981). Ecological perspective on water quality goals. Environmental Management 5: 55-68. KARR, J.R., FAUSCH, K.D., ANGERMEIER, P.L., YANT, P.R. and SCHLOSSER, I.J. (1986). Assessment of Biological Integrity in Running Waters. A method and its rationale. Illinois Natural History Survey Special Publication 5. PENNAK, R.W. (1978). Freshwater invertebrates of the United States (2 nd ed). John Wiley and Sons, New York. pp 803. THIRION, C. (2000). A new biomonitoring protocol to determine the ecological health of impoundments using artificial substrates. African Journal of Aquatic Science 25 (1). pp 123-133. UNITED STATES ENVIRONMENTAL PROTECTION AGENCY (USEPA) (1998). Lake and Reservoir Bioassessment and Biocriteria: Technical Guidance Document. Office of Water, Washington D.C. EPA 841-B-98-007. UNITED STATES ENVIRONMENTAL PROTECTION AGENCY (USEPA) (2002a). Methods for Evaluating Wetland Condition: # 1 introduction to Wetland Biological Assessment. Office of Water, Washington, D.C. EPA 822- R-02-014. pp 35. UNITED STATES ENVIRONMENTAL PROTECTION AGENCY (USEPA) (2002b). Methods for Evaluating Wetland Condition: #9 Developing an invertebrate Index of Biological Integrity for Wetlands. Office of Water, Washington, D.C. EPA 822-R-02-019. pp 50. UNITED STATES ENVIRONMENTAL PROTECTION AGENCY (USEPA) (2002c). Methods for Evaluating Wetland Condition: #7 Wetland Classification. Office of Water, Washington, D.C. EPA 822-R-02-017. pp 35. UNITED STATES ENVIRONMENTAL PROTECTION AGENCY (USEPA) (2002d). Methods for Evaluating Wetland Condition: #6 Developing Metrics

229 Chapter 7: Development of a wetland assessment protocol.

and Indexes of Biological Integrity. Office of Water, Washington, D.C. EPA 822-R-02-016. pp 38. WISSINGER, S.A. (1999). Ecology of Wetland Invertebrates: Synthesis and Applications for Conservation and Management. In: BATZER, D.P., RADER, R.B. and WISSINGER, S.A. (eds.). Invertebrates in Freshwater Wetlands of North America: Ecology and Management. John Wiley, New York. pp 1043- 1086. YODER, C.O. and RANKIN, E.T. (1995). Biological criteria program development and implementation in Ohio. In: DAVIES, W.S., and SIMON, T.P., Eds. Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Boca Raton, FL: CRC Press. pp 109-144.

230 Chapter 8: Wetland Management Framework

Chapter 8:

Wetland Management Framework.

231 Chapter 8: Wetland Management Framework

Chapter 8: Wetland Management Framework. 8.1: Rationale behind the Framework 8.1.1 Introduction The protection of the South African wetland environments is protected by a number of legislative Acts. The most relevant legislation is the implementation of biomonitoring in the wetland environment, and is as follows:

Pollution Legislation

The National Water Act (Act 36 of 1998) recognises the protection of water quality resources and that it is necessary to ensure sustainability of the nation’s water resources in the interest of all water users. It also recognises that the ultimate aim of water resource management is to achieve the sustainable use of water for the benefit of all users. Part 4 of the act deals with pollution prevention in particular in situations where water pollution occurs due to activities on land. The person who owns, occupies or controls the land is responsible for taking measures to prevent pollution of the water courses. The management and policing of these acts falls under the auspices of a Catchment Management Agency.

Water resource management legislation

The National Water Act (Act 36 of 1998) came into effect on 1 October 1998. The central departure of the Act is the concept of resource use being dependent on resource protection, and the recognition that the water quality should be extended to resource quality and includes the quantity and quality of the water itself, the geomorphological structure of the system, biota, and the associated riparian biota. As far as water quality is concerned, resource use involves using resources both to supply water that is “fit for use” by various categories of users, and to transport and absorb wastes, particularly using the natural biotic capacity to process organic wastes. However, the question arises as to how much waste

232 Chapter 8: Wetland Management Framework the ecosystem can absorb or process before ecosystem damage occurs. It is thus important to develop a management forum for the protection of wetlands in South Africa. Such a management forum should make it a priority to develop a Comprehensive Conservation and Management Plan for each catchment or possibly each Ramsar Site. It should also establish requirements to monitor the effectiveness of actions taken pursuant to the plan.

At present there are no legal requirements or directives that make provision for the inclusion of biomonitoring programmes in Wetland management. This document provides guidance on the design, implementation, and evaluation of a Wetland monitoring programme. The design of the programme is based on the National Estuary Programme (USEPA, 1992) and it has been interpreted and adapted for use in the Nyl River Floodplain in a similar manner to which Murray and Claassen (1999) evaluated the USEPA ecological risk assessment guidelines.

The intended audience are the members of the environmental management sections (i.e. the Safety, Health and Environment departments of companies associated with activities in the Modimolle, Mookgopong and Mokopane districts, the Department of Environmental Affairs and Tourism, Limpopo Province, and local municipalities) as well as other interest groups (local rate payers association, local wildlife organisations and Ornithological Clubs). The purpose of this document is to identify the steps involved in developing and implementing a monitoring programme for the Nyl River Floodplain. Given the large number of participants in the project and the diversity of technical backgrounds, it is also intended to provide a technical basis for discussions on the development of monitoring programme components, and the allocation of sampling effort. Some of the issues addressed in this document are:

· What is the role of monitoring in the Nyl River Floodplain?

233 Chapter 8: Wetland Management Framework

· Why monitoring programmes are necessary and what are examples of goals and objectives? · What criteria should be used to select components of the monitoring programme, and what should drive the decision-making process? · What is the importance of historical data, and how can ongoing monitoring programmes be incorporated into a Nyl River biomonitoring programme?

The key technical and programmatic aspects associated with each of these issues are described. This document also includes several examples.

Data management, effective data analysis, and the communication of monitoring programme results to a wide range of audiences at several technical levels are also essential for the success of the biomonitoring programme and this document discusses data management strategies to contribute towards achieving this goal.

The purpose of this chapter is aimed at providing a framework, which could be used to set up a management forum tasked with preparing a management plan and accompanying monitoring programme to ensure the ecological integrity of the Nyl River Floodplain and surrounds. This management forum has the responsibility to implement a four-phased programme:

· Phase 1 - The Planning Initiative. The planning phase is intended to build the management framework for identifying and solving problems and defining the steps in the decision-making processes. · Phase II - Characterisation and Problem Definition. The goal of the system characterisation is to gather and summarise the existing knowledge concerning the state of the wetland as well as the physical, chemical, and biological factors focusing on identifying existing and potential problems and exploring probable causes of such problems. Such cause-effect linkages between human activities and environmental changes provide the public and decision makers with the information

234 Chapter 8: Wetland Management Framework

necessary to develop priorities, set management strategies, and devise mitigating measures. However, information gaps do exist. Additional sampling and a subsequent monitoring programme can fill such information gaps.

· Phase III - Development of a Comprehensive Conservation and Management Plan (CCMP). The CCMP is a major product of the Nylsvley floodplain programme. It is developed by a management conference to summarize findings, identify and prioritise problems, determine environmental quality goals and objectives, identify action plans and compliance schedules for pollution control and resource management, and to ensure that designated uses of the wetland are protected.

· Phase IV - CCMP Implementation. All the interested parties should establish a committee to co-ordinate the implementation of the CCMP. The development of a monitoring programme to evaluate the effectiveness of actions specified in the CCMP is a required task of the management conference.

The four phases of the Nyl River Floodplain Biomonitoring Program (NRFBMP) should be viewed as sequential steps, where one phase cannot be initiated before the previous phase is completed. On the contrary, participants should be encouraged to proceed with the four phases simultaneously as often as possible. For example, early results of characterisation (Phase II) may indicate obvious management actions that can be taken (Phase IV) prior to completion of the CCMP (Phase III). In these cases, implementation actions should proceed.

Environmental sampling is required in Phases II and IV of the biomonitoring programme. The studies conducted in Phase II are focused on filling identified data gaps, providing baseline data on point and non-point loadings of pollutants, and developing estimates of the degree of spatial and temporal variability.

235 Chapter 8: Wetland Management Framework

Sampling is conducted in Phase IV of the biomonitoring programme as part of a long -term environmental monitoring strategy.

Environmental monitoring that is conducted during Phase IV is considered to be different from the sampling that is conducted during Phase II. Monitoring involves repeated sampling over time. For example, short-term sampling may be conducted in Phase II to collect specific information on the concentration, distribution, and variability of chemical contaminants in sediments. The goal of the corresponding sampling that is conducted during Phase IV monitoring is that comprehensive environmental monitoring programme components and to allocate sampling efforts accordingly. It will also be necessary to carefully plan and co-ordinate monitoring efforts and among individual monitoring components and other pre-existing monitoring programmes to determine interactions and streamline monitoring efforts. A third distinction between environmental sampling and monitoring is the need to periodically analyse the monitoring programme results and modify the level of sampling effort to maximise programme effectiveness.

8.1.2 Recommended Monitoring Procedures

Outlined below is a systems approach to the design of the NRFBMP that incorporates existing information and that will ensure the collection, analysis and reporting of adequate information to meet the goals of individual monitoring programmes. A systems design approach places emphasis on the optimum design of the overall monitoring programme. The essential elements are the assessment of trade-offs between individual aspects of the monitoring programme and the use of feedback mechanism to modify individual monitoring components based on periodic assessments of overall programme performance. This approach is well suited for design problems that involve complex, highly variable systems, such as the Nyl River Floodplain, and that involve a large number of investigators that must interact

236 Chapter 8: Wetland Management Framework as a group to produce the product.

The plan for implementing this approach to designing the monitoring programme is shown in Figure 8.1. It involves the specification of monitoring objectives into clearly defined monitoring activities, and the use of feedback mechanisms to refine the objectives and adjust the sampling effort.

The overall objective of monitoring undertaken during Phase IV of the NRFBMP programme will be to measure the effectiveness of management actions implemented as part of the CCMP. Meeting this broad programme objective will require the specification of individual, highly interrelated monitoring objectives. Examples of individual monitoring objectives (shown in Figure 8.1 as Objectives 1 through n) include: to determine the response of key water quality variables to management actions, to determine trends in sediment contaminant concentrations; and to evaluate the persistence of metals in the tissue of fish, birds and aquatic invertebrates.

Each monitoring objective represents a separate component of the overall biomonitoring programme. The individual steps involved in designing each component of the monitoring programme are shown in Figure 8.2

· Step 1. Develop Monitoring Objectives and Performance Criteria. Clear objectives and corresponding performance criteria must be developed for each component of the monitoring programme. Performance criteria specify the level of change or trend that the monitoring programme must be able to detect. For example the monitoring programme needs to assess the temporal and spatial metal bioaccumulation patterns in fish tissues and changes in Indices of Biotic Integrity (IBI) scores. Therefore, the corresponding objectives and performance criterion for the bioaccumulation component of biomonitoring programme would be to detect long- term

237 Chapter 8: Wetland Management Framework changes in metal concentrations in fish tissue in excess of permissible levels for human consumption.

238 Chapter 8: Wetland Management Framework

Public

concern Modelling Research Legislation

DEVELOP / REFINE MONITORING OBJECTIVES Objective 2 Objective 3 Objective n

Refine monitoring objectives

EVALUATE / ASSESS PROGRAMME

COMMUNICATE MONITORING RESULTS / REDIRECT MANAGEMENT PROGRAMME Figure 8.1 Conceptual framework for monitoring programme design

· Step 2. Establish Testable Hypotheses and Select Statistical Methods. The study objectives must be translated into statistically testable hypotheses; for example, no spatial trend exists in metal bioaccumulation in fish. Establishing testable hypotheses ensures that the result of the monitoring programme will be unambiguous and that the objectives of the programme can be met. The establishment of testable hypotheses also guides the development of statistical strategies for determining sample locations and times as well as the selection of statistical tests that will be used to analyse the resulting data.

239 Chapter 8: Wetland Management Framework

Develop monitoring objectives, performance criteria

Establish testable hypothesis and select statistical methods

Rethink Select analytical methods monitoring and study alternative sampling designs approach

Evaluate expected monitoring programme performance

Is the No monitoring programme adequate?

YES

Design and implement data management plan Figure 8.2 Individual steps involved in designing each component of the NRFBMP

· Step 3. Select Analytical Methods and Alternative Sampling Designs. Detailed specifications for each monitoring variable (measurable endpoint) of the monitoring programme must be developed. These include: field sampling and laboratory procedures, and QA/QC procedures. Additionally, alternative sampling designs that specify the number and location of stations must be devised for input to the next step in the designs that specify the number and location of stations must be devised for input to the next step in the design process.

· Step 4. Evaluate Expected Monitoring Programme Performance. It is essential to evaluate the expected performance of the initial sampling design to determine the minimum difference that can be detected over time or between locations. Without this evaluation there is a risk of collecting and analysing too few samples to detect statistically significant temporal or spatial 240 Chapter 8: Wetland Management Framework trends or of analysing an excessive number of samples (with associated high costs). As indicated by the feedback loop shown in Figure 8.1, the results of this evaluation are used to identify modifications to the initial design in order to increase monitoring programme effectiveness. Information from this evaluation will also be used to assess the ability of monitoring components to provide information used to modify the management plan.

· Step 5. Design and Implement Data Management Plan. The development of a data management system is an essential task that is often overlooked in the design of monitoring programmes. The data management system should be operational prior to implementation of the monitoring programme. Data analysis methods and a timetable for analysing the data, assessing CCMP implementation progress results should be specified. The results of the performance assessment are used to refine programme objectives.

These individual steps in the monitoring design process shown in Figures 8.1 and 8.2 are described in Sections 8.2 through 8.6.

Peer review of the monitoring programme is recommended to evaluate and assess programme design. Critical review by technical experts without a vested interest in the programme will ensure that the monitoring objectives are meaningful and that the monitoring strategy adequately addresses these objectives with the most appropriate methods. This review should take place after the initial developments of specific objectives and performance criteria and as part of the periodic reviews that are conducted to evaluate the success of the monitoring programme.

Overall programme performance must be assessed at periodic intervals, and the results should be used to refine monitoring programme objectives and methodologies. The original monitoring design must remain open to modification. The monitoring programme should take advantage of new information and innovative sampling approaches as they are developed, and the link between modelling and monitoring efforts should be fully exploited. The results of the monitoring programme

241 Chapter 8: Wetland Management Framework should be used to refine and modify conceptual and mathematical models of the system, and modelling results should be used to guide changes in individual monitoring programme components, variables monitored, the frequency of sampling, and overall monitoring strategies. It is essential that the new information, from both independent research and the monitoring programme results are integrated into the monitoring programme.

8.1.3 Monitoring Programme Management

In order for a monitoring programme to succeed there are a number of management issues related to the design, implementation, and maintenance of the NRFBMP that must be addressed early by a management conference. These include setting the timetable for the design and implementation process, assigning responsibilities for coordinating the design effort, and planning for the long-term success of the monitoring programme.

Timetable for the Design and Implementation of the NRFBMP

The development of a monitoring programme should be a consensus building effort among the parties involved in order to finalise the initial design plans. In addition to the decisions regarding the basic sampling strategy, agreement is required on numerous interrelated issues, such as sampling protocols, appropriate quality assurance/quality control methodology, and the selection of an information management system.

Planning for the monitoring programme should be initiated during the first year of the management forum. Milestones for the monitoring programme effort should be clearly stated in the management forum agreement (a three to five year action plan for CCMP completion that is negotiated shortly after a management forum is convened). Development of the monitoring programme should be given a high priority by the management forum after it is convened. It is important to begin early planning of the monitoring programme plan must accompany the CCMP that is

242 Chapter 8: Wetland Management Framework submitted to the interested parties for approval. The monitoring plan must contain the following elements that are described in this document:

· Definition of programme objectives and performance criteria (parameter values needed to guide management decisions). · Identification of testable hypotheses. · Detailed specifications for each monitoring variable, including sampling locations and frequency, field sampling procedures, field and laboratory analytical procedures, quality assurance and control procedures. · Specification of the data management system and statistical tests that will be used to analyse the monitoring data. · Description of the expected performance of the initial sampling design (i.e., the minimum difference that can be detected in measured variables over time and between locations). · Plan and timetable for analysing data and assessing programme performance.

8.1.4 Management Tasks for Developing the Monitoring Programme

The first management task in developing the monitoring programme should be the establishment of an organisation or committee, similar to the proposed Catchment Management Authorities (CMA) of DWAF to develop the monitoring programme. This Implementation Committee (IC) is one of three committees that make up the overall management forum. The other two committees are the Management Committee and a general public advisory committee. Membership in the monitoring subcommittee should not be limited to IC members but should include representatives from provincial and local agencies, universities, industry, environmental groups and others currently conducting monitoring or planning monitoring programmes within the wetland or surrounding waters.

The subcommittee should be charged with the following tasks:

243 Chapter 8: Wetland Management Framework · Define the goals and objectives of the monitoring programme. · Propose an initial design that includes recommendations for sampling and analytical protocols, data management system specifications, quality assurance guidelines, data reporting requirements and cost estimates. · Coordinate the activities of the numerous interested and participating agencies and develop interagency agreements that will promote the monitoring effort. · Identify funding mechanisms and opportunities to contain costs.

As discussed in Section 8.1.2, the process of developing a comprehensive monitoring programme must begin with a clear statement of the objectives. The explicit statement of objectives, and options for obtaining these objectives, is necessary as a starting point for describing the problem areas in the Nyl River Floodplain and developing the consensus among interested agencies and other parties that is essential to the success of monitoring effort.

The primary goals of the monitoring programme will be to measure the success of the CCMP and to provide information that can be used to redirect and refocus to development. However, it will also be the responsibility of this subcommittee to develop secondary goals and programme objectives that will be used to focus the sampling effort.

These objectives could include: continued characterisation of spatial and temporal patterns of change in water quality, sediment and biological resources of the floodplain; development of a permanent record of significant natural and human- caused changes in environmental indicators in the floodplain over time, and support for research activities through the availability of consistent, scientifically valid data. The presence of developing these objectives is described in Section 8.2.

244 Chapter 8: Wetland Management Framework 8.2: Develop Monitoring Objectives and Performance Criteria

The overall objective of the NRFBMP is to assist in determining the effectiveness of the implementation of the CCMP. However, this overall objective may encompass several specific monitoring objectives. The identification of these specific objectives begins during system characterisation. The characterisation process identifies concerns and formulates a series of corresponding management issues. During characterisation, conceptual and predictive models are developed and research results are evaluated to provide a basic understanding of important physical, chemical and biological processes in ephemeral wetlands. This information is used in the design of the monitoring programme to specify a set of variables and ecological processes that can be used to detect changes in the wetland in response to management issues. During characterisation, conceptual and predictive models are developed and research results are evaluated to provide a basic understanding of important physical, chemical and biological processes in the Nyl River Floodplain. This information is used in the design of the monitoring programme to specify a set of variables and ecological processes that can be used to detect changes in the wetland in response to management actions.

245 Chapter 8: Wetland Management Framework

Public concern Modeling Research Legislation Develop monitoring objectives, performance

criteria

DEVELOP / REFINE MONITORING OBJECTIVES

Figure 8.3 Conceptual framework for monitoring programme design indicating the development of Monitoring objectives and performance criteria.

Regardless of the scope of the proposed monitoring programme, it is essential to develop explicit statements of the monitoring objectives as well as to establish performance criteria with which to measure monitoring programme success.

A unique approach for identifying concerns and ecological problems is to construct a matrix, shown in Table 8.1, which identifies Valued Ecosystem Components (VEC’s) and sources of perturbation. This matrix also summarizes the understanding of the relative importance of each perturbation on a single ecosystem component. By way of an example one source of perturbation and affected ecosystem components is indicated in Table 8.1. It must be stated that this is only an example since the characterisation of the system would be one of the functions of the management forum. The effects of each identified source of perturbation (e.g., sewage effluent 246 Chapter 8: Wetland Management Framework discharge) on all identified resources (VEC’s) are summarised along a single row. Similarly, each column summarizes the existing knowledge of the impacts on a single resource caused by the complete range of identified sources of perturbation.

This matrix summarizes existing information on the resources of the Nyl River Floodplain and potential impacts in an easily accessible manner. The process of developing this matrix also provides an effective tool for building consensus among the wide range of interested parties in the wetland program on the relative priority of monitoring objectives and the different components of proposed monitoring programs.

Simple conceptual and predictive models developed in the characterisation process may also be used to summarize the physical, chemical, geological and biological status of the wetland and identify the factors controlling spatial and temporal changes. Finally, it is necessary to quantify the identified ecological relationships. Existing data should be analysed to evaluate the strength and direction of identified relationships and to determine the magnitude of uncertainty associated with the existing information. The products of the characterisation process should include the identification of the primary management issues. These management issues are used for development of the CCMP. The CCMP sets environmental quality goals and management objectives for the floodplain and specifies actions for achieving these objectives. The monitoring program is designed to verify the predicted results and evaluate the effectiveness of the CCMP implementation, and to recommend corrective actions. When insufficient information is available for floodplain characterization and\or information gaps occur additional sampling and analysis should be undertaken to fill these gaps.

247 Chapter 8: Wetland Management Framework Table 8.1: Impacts on the floodplain environment of the of the Nyl River System.

Valued

Ecosystem

Components

getation

Sources of

Perturbation

Wetland Phytoplankton Zooplankton Riperian Vegetation Marginal vegetation Aquatic ve Aquatic invertebrates Pelagic Fish Demersal Fish Fish Eggs & Larvae Aquatic Birds Human Health All Flow Regime Disturbances Blooms\ Invasions Ecological Interactions Wastewater outfalls Sewage Effluent 3 3 3 1 1 1 3 3 3 2 4 4 3 Discharges Rivers\Storm Runoff Sport Fishing Habitat Loss\Mod. Chemical Spills All

KEY Potential importance Understanding Controlling Major Moderate Some High Moderate Low 1 2 3 4

8.2.2 Performance Criteria

The establishment of programme requirements, i.e., performance criteria, in terms of the level of precision and accuracy that is necessary to make decisions regarding the success of monitoring effort will define the expectation of the monitoring programme. Issues that must be addressed include: 1) What level of detail will be necessary to

248 Chapter 8: Wetland Management Framework make decisions regarding the success of the CCMP? 2) What level of differences must be detected in the monitoring programme to initiate modifications in the design and implementation of the monitoring programme? This concept of explicit stating performance criteria is the cornerstone of the systems design approach that is described below. The explicit statement of the monitoring programme requirements provides a basis for evaluating expected and actual monitoring programme performance (Section 8.5). Evaluation of the effectiveness of alternate monitoring designs also provides a basis for discussion of alternate monitoring approaches and sampling layouts.

8.3: Establish Testable Hypotheses and Select Statistical Methods

Table 8.2 provides examples of monitoring that are common to many NEP monitoring programmes. The range of corresponding questions provides some idea of the breadth of monitoring issues that are encompassed in the monitoring objectives.

In designing the monitoring programme, these broad objectives must be focused to identify specific monitoring variables and corresponding activities.

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Establish testable hypotheses and select statistical methods

Figure 8.4 Conceptual framework for monitoring programme design indicating the establishment of a testable hypothesis and statistical method selection.

8.3.1 Establish Testable Hypotheses

The questions identified in Table 8.2 give rise to a number of alternative scientific hypotheses. For, example, questions regarding the water quality component of a monitoring programme and hypoxia can lead to several hypotheses regarding the response of dissolved oxygen concentrations in the water column. An example of a hypothesis is:

· Metal reduction strategies will result in decreased bioaccumulation in fish throughout the floodplain.

250 Chapter 8: Wetland Management Framework Table 8.2: Examples of monitoring program objectives and associated questions. Objective Questions Document response of water variables to · Are nutrient reduction strategies management actions effective? · Is the risk of hypoxia reduced? · Is there a decrease in phytoplankton biomass? · Is light transmittance affected? · Is fish community structure affected? Characterise spatial and temporal patterns · What is the risk of consuming fish in bioaccumulation products from within the floodplain? · Are there trends in fish contaminant concentrations? · Do toxic hot spots exist and what are the influences on bioaccumulation? · What is the relationship between sediment concentrations of contaminants and observed tissue concentrations? · What is the relative contribution of different sources of pollutants? Monitor the status of the ecosystem · What are the trends in selected indicators? · What are the consequences of the physiological, morphological and molecular changes on which indicators are based on organism survival and population health? · What is the status of indigenous species?

It is clear that the monitoring programme must be designed to address a wide range of alternative hypotheses. The recommended procedure for ensuring that sufficient information and the right type of information is developed in the monitoring programme is to specify, prior to the collection of any samples, the statistical model that will be used to analyse the resulting monitoring data, and to specify testable (null) hypotheses.

8.3.2 Selection of Statistical Methods

The statistical tests that will be used to analyse the resulting data must be specified for each hypothesis developed. The applicability of univariate, multivariate, parametric and nonparametric methods must be carefully evaluated. However, it is essential to involve the statisticians responsible for the analysis of the data in both 251 Chapter 8: Wetland Management Framework the development of testable hypotheses and the selection of analytical methods. The statistical software that will be used to analyse the data should also be identified at this step in the design process.

8.4: Select analytical methods and alternative sampling designs

The goal of this step in the design process detailed monitoring programme specifications. In addition to the statistical methods, these specifications include the field collection and laboratory analysis methods for individual monitoring variables, and the appropriate quality assurance/quality control procedures. Alternative sampling layouts including numbers and location of sampling points, sample frequency, and the level of sample replication should also be developed. This information will then be used in the next step (see Section 8.5) to evaluate expected monitoring programme performance and to select the most efficient sampling layout among the alternatives.

8.4.1 Selection of Field and Laboratory Methods

The purpose of selecting field and laboratory methods at this stage of the design process is to ensure: the feasibility of using the selected methods in conjunction with the proposed level of sampling effort; that any data used to evaluate expected monitoring performance, a crucial step in the design process, are directly comparable with data that would be collected in the proposed monitoring effort; and, that standardised methods are used.

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Select analytical methods and alternative sampling design

Figure 8.5 Conceptual framework for monitoring programme design indicating alternate sampling designs and analytical methods.

Standardised protocols or performance criteria should be developed to ensure that the data collected by the different groups participating in the NRFBMP are directly comparable. In the development of alternative sampling layouts, considerations should be given to the trade-offs between the benefits of a comprehensive monitoring effort and available funding. In general, support for biomonitoring programmes are limited both in the amount of funding available annually and the duration of funding. Consideration should be given to both limiting the scope of monitoring efforts and making the most efficient use of ongoing monitoring programmes in the floodplain.

Ideally, the scope of the programme should be adequate to meet all identified

253 Chapter 8: Wetland Management Framework monitoring objectives. Where the funding is not available to meet all the objectives, however, the individual monitoring components should be prioritised on the basis of the relative importance of related management issues and the availability of existing information. Generally, emphasis should be placed on focusing monitoring efforts in order to attain the level of precision necessary to evaluate the effectiveness of individual management actions, rather than implementing a comprehensive monitoring programme that lacks the ability to detect the level of changes expected over time.

Given the large variability generally associated with environmental samples, and the limit of funding, alternate sampling strategies should be investigated. Through design optimisation, the sampling effort can be distributed spatially and temporally in such a way as to maximize the amount of information obtained within the area sampled. The strategy behind most sample design optimisations is either to minimise the detectable difference or trend. The strategy adopted will depend upon the specific situation for each monitoring programme. In either case, the goal is to obtain the maximum amount of information per rand spent.

The choice of a sampling design depends on several factors including the objectives of the monitoring programme, the type of data that are required to test the null hypothesis, the underlying assumptions of statistical tests, and the spatial and temporal distribution of the monitoring parameters. These factors can affect both the validity of the test results and the efficiency of the monitoring programme (cost to obtain a given level of detection). A brief summary of the common sampling designs is presented in Figure 8.6

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Figure 8.6 Description of various sampling designs.

The most basic method of collecting monitoring data is simple random sampling. With this design, samples are selected randomly and with equal probability. While this method is easy to implement, there are a variety of sampling designs that can be more efficient. Such designs will produce estimates with smaller standard errors for the same sampling effort, or require fewer samples to obtain the same standard errors as would be obtained with simple random sampling.

One such design is systematic sampling. In systematic sampling, sample units are selected at fixed intervals in space or time, usually with a random start. There are many variations of systematic sampling; however, they all share some common advantages and disadvantages. The even coverage obtained with systematic sampling tends to ensure that each sample, on average, is more representative of

255 Chapter 8: Wetland Management Framework the population as a whole than a simple random sample. Therefore, such samples arise that lead to bias or increased variance if there is an underlying pattern or periodicity in the population over space or time, which is common with environmental data. In addition, it can be difficult to obtain a valid estimate of the standard error if the data cannot be assumed to be distributed randomly.

Another design often used is stratified sampling. By dividing the study area into non- overlapping homogeneous strata it is possible to optimise the sampling effort in several ways. First, the samples can be allocated to the different strata in proportion to the size of the strata and the variability within the strata, and in inverse proportion to the cost of sampling in those strata. This method will ensure that the minimum variance will be obtained for a given cost. Other criteria, such as the ecologic importance of strata and the parameters being measured, can also be taken into account when allocating sampling effort. Stratified sampling also allows the use of the best sampling designs within strata to further increase the sampling efficiency. Stratified sampling works well in a tiered approach because it allows monitoring performance assessment and design modification to be made on a stratum-by- stratum basis. Stratified sampling also yields estimates for each stratum, providing information that better represents the area being sampled, and is therefore more ecologically meaningful. As an example, two strata may each have a significant trend for a given parameter, but the trends may be in opposite directions. If the data were combined (such as in systematic sampling), the trends might cancel each other out and result in a conclusion of no significant trend. Because stratified sampling ensures that some samples will be taken from each other stratum, over the entire study area, it helps to ensure that the overall estimate will be more representative on average than one obtained from a simple random sample. This advantage of stratified sampling will be realized even if optimal allocation is not used and the strata are defined arbitrarily with respect to the parameters of interest. In general, if the variability within individual strata is less than the overall variability in all combined strata, the standard errors obtained with stratified sampling will be less than those obtained from systematic sampling, which would be less than those obtained from simple random sampling.

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Multistage sampling is another cost effective method of allocating sampling effort over large areas. In this design, large primary sampling units are composed of smaller secondary units. For large-scale studies, third stage units may also be used. Within each of the selected first stage units, one or more second stage units are selected. In addition to increased sampling efficiency, this method allows intensive sampling to be done only at the second stage, while parameters that are inexpensive to measure can be obtained for the first units. This provides some level of monitoring over a wide area, and if problem areas are detected, the distribution of second stage units can be reallocated. The information collected from the first units can be used to implement variable probability sampling at the second stage to further increase the sampling efficiency.

8.4.3 Existing Monitoring Programmes

A monitoring strategy that incorporates ongoing monitoring programmes or elements from these programmes can significantly reduce the cost of the monitoring effort. Existing compliance and resource monitoring programmes may produce data that can completely satisfy, or augment, the spatial and temporal coverage required by the NRFBMP. Additionally, by adopting sampling and analytical methods of ongoing monitoring programmes as standard protocols for NRFBMP components, data from these existing monitoring may be used in evaluating the effectiveness of the CCMP.

An inventory and evaluation of existing monitoring programmes within the floodplain and surrounding areas should be conducted in order to assess their usefulness and applicability in evaluating the effectiveness of the CCMP. Key tasks of this assessment process include:

· Identification of existing and planned programmes as well as special projects that may contribute data useful in evaluating the effectiveness of the CCMP.

257 Chapter 8: Wetland Management Framework · Determination of whether the NRFBMP objectives could be cost-effectively met by incorporating sampling and analytical methodologies from existing monitoring programmes.

Specific monitoring variables, statistical and analytical methods selected will depend upon the stated objectives and action plans outlined in the CCMP, and specific hypotheses to be tested in the monitoring programme. Therefore techniques from existing monitoring programmes may not necessarily be adopted.

8.5: Evaluation Monitoring Programme Performance

Although often overlooked and neglected, the evaluation of monitoring programme performance is potentially the most important step in the design and review process. The performance evaluation motivates the development of explicit statements of programme objectives as well as the specification of performance criteria during the design phase. During the course of the monitoring effort, performance evaluations provide a systemic procedure for measuring success in terms of the ability to meet programme goals. The periodic evaluation process also identifies the need to modify sampling design and methods.

Evaluation procedures are essential because the information developed in the monitoring programmes must be sufficiently precise and scientifically defensive. The monitoring programmes will provide the primary source of information that will be used to evaluate the success of the CCMP. This information will be used as a basis for determining the efficiency of selected management strategies and the accuracy of model predictions upon which many management decisions have been based. The monitoring programme will also provide quantitative information that will guide decisions regarding needed modifications to the management plan.

Additionally, the cost of the NRFBMP will probably be substantial. In order to protect this investment, it is essential to assess expected performance prior to collecting the first samples. This performance information will provide the basis for determining the

258 Chapter 8: Wetland Management Framework feasibility of proposed sampling strategies, selecting the most effective monitoring components and variables, and optimising the overall monitoring effort.

The two types of performance evaluations are shown in Figure 8.7. The first is the evaluation of the expected performance of individual components of the monitoring programme (e.g., the evaluation of trends in toxic chemical accumulation in sediments). The first evaluation takes place during the design phase. The second type of performance evaluation is the assessment of overall programme performance. This assessment takes place after the monitoring programme has been implemented (e.g., after the first full year of data have been collected). The objective is to determine if the overall goals of the programme are being met by the individual monitoring components and if adding, deleting or expanding the scope of individual monitoring components should modify the programme. The essential feature of both types of evaluation is the existence of a feedback loop that provides the pathway for modifying the system's design based on monitoring programme performance.

The establishment of performance criteria (e.g., the ability to detect a change in metal bioaccumulation in fish exceeding permissible levels over a period of five years) is a fundamental part of developing monitoring objectives. As indicated in Section 8.2., these performance criteria represent the level of change that must be detected in order to make management decisions regarding the effectiveness of the CCMP.

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Rethink monitoring study approach

Evaluate expected monitoring programme performance

Is the No monitoring programme adequate?

YES

Figure 8.7 Conceptual framework for monitoring programme design indicating monitoring performance evaluation. It is these performance criteria that will be used to evaluate the applicability of individual components of the monitoring programme. The specification of sampling methods for proposed monitoring programme components described in Step 3 (Section 8.4) includes the development of alternate sampling strategies, including the monitoring variables/indicators and the level of sampling effort (number of sampling stations and sample replicates). The goal of the performance assessment is to evaluate the effectiveness of these alternative sampling designs in terms of the established performance criteria. The results will provide the basis for determining the relative benefits of individual monitoring components and selecting the final monitoring design.

The questions that will be addressed in these analyses are:

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· Can the proposed sampling effort meet the needs of the monitoring programme as defined in the performance criteria associated with the stated objectives?

· How can the proposed programme be modified to ensure that these objectives are met?

As indicated by the feedback loop shown in Figure 8.7, this is an iterative process. Proposed sampling designs are evaluated and modified, if necessary, to meet the overall objectives. The tools for conducting these analyses are described in Section 8.5.3.

8.5.2 Evaluate Overall Programme Performance

The overall performance of the monitoring programme should be evaluated at periodic intervals. Initially, this evaluation should take place at the conclusion of the first year of sampling. This evaluation should compare the results with expected monitoring performance, and a list of required modifications should be prepared. Opportunities for streamlining the programme should be identified, and the performance criteria should be reviewed and revised, if necessary, for subsequent evaluations.

8.5.3 Statistical Power Analysis Methods

The primary tool for conducting these analyses is statistical power analysis. Statistical power analysis provides an evaluation of the ability to detect statistically significant differences in a measured monitoring variable. The importance of these analyses can be seen in the examination of the possible outcomes associated with testing the null hypothesis (e.g., HO: sampling location has no effect on observed sediment contaminant concentrations).

261 Chapter 8: Wetland Management Framework 8.6: Design and Implement Data Management Plan

Data management and data analysis, two key components of the monitoring study that are often overlooked in the design of monitoring programmes, are as important to the success of the monitoring effort as the collection and laboratory analysis of field data. Moreover, the cost of effective data management/data analysis can be substantial. Approximately 20 percent of the budget allocated for the monitoring programme should be reserved for data management and data analysis activities. Failure to plan for these costs can result in the loss of information due to inadequate data preservation and limited analysis of the monitoring data that are collected.

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Design and implement data management plan

Figure 8.8 Conceptual framework for monitoring programme design indicating design and implementation of data management plan.

The need to assimilate and integrate historical information, as well as planned monitoring efforts, should drive the development of a data management strategy. Failure to plan for data management can result in the loss of the information due to inadequate data preservation.

The development of a data management strategy must consider the following questions:

· Where will the data go? · How will these data be stored? · Who will maintain the data-base?

263 Chapter 8: Wetland Management Framework · How will data be checked and loaded into the data-base? · How accessible will the data be? · How will statistical, graphical, and report generating tools be available ? · How much will it cost?

A computer system will be essential for the management of the data collected by the wetland monitoring programmes. It should be operational prior to implementation of the monitoring programme and should have the following attributes:

· Centralized storage of raw data. · Easy access and use. · Quality assurance procedures. · Linkage to graphical, statistical and report generation routines. · Long-term availability and flexibility.

An additional feature of a centralised data management approach is the ability to designate a system administrator who has responsibility for system documentation and data quality assurance.

8.6.2 Data Analysis

As indicated in Section 8.5., an essential element of the monitoring plan will be the specification of a timetable for analysing the data and assessing monitoring programme performance. The assessment of monitoring programme performance should be used to refine monitoring programme objectives and modifying individual monitoring programme elements to satisfy these objectives. Initially, monitoring programme evaluations should be conducted after the first year of data collection. Subsequent interim evaluations should be conducted at two or three intervals. The primary purpose of other data analysis activities will be to test the hypotheses developed in Step 2 of the design process (see Section 8.3.). Additional goals are to summarise the data, generate new hypotheses, and evaluate the uncertainty associated with the measurements and conclusions. Additional analyses should be 264 Chapter 8: Wetland Management Framework designed to produce information for use by groups with diverse technical backgrounds.

A wide range of statistical and graphical tools is readily available for use in meeting these goals. Recently, there has been an increased interest in the development of Geographical Information Systems applications for geographical analysis and information display.

8.7: Communicate Programme Results

Public concern Modelling Research Legislation

COMMUNICATE MONITORING RESULTS / REDIRECT MANAGEMENT PROGRAMME

Figure 8.9 Conceptual framework for monitoring programme design indicating program result communication.

265 Chapter 8: Wetland Management Framework One of the primary goals of the monitoring programme information that can be used to redirect and reinforce the CCMP. To achieve this goal, emphasis should be placed on distributing the data that are collected in the wetland monitoring programmes. The data collected by individual investigators should be made readily available to the scientific community for comparative studies that relate information from different components of the programme. Section 8.6. discusses the need for the development and implementation of an effective data management strategy. Emphasis should also be placed on the analysis of these data.

The dissemination of the recorded monitoring data is not a sufficient mechanism for communicating results. Statistical analysis of the monitoring data is essential, and graphical and written summaries should be produced for agency managers charged with implementing the CCMP. The results must be effectively communicated to an audience with a wide range of technical backgrounds and interests.

Figure 8.9 shows two feedback loops associated with the evaluation of monitoring data. One provides direct feedback of analytical results that are used to modify and refine the monitoring programme to increase efficiency (see Section 8.5.). The other provides feedback to three basic factors that influence the design, development and refinement of monitoring programme objectives: public concerns, legislation, modelling, and research. Data analyses must provide information that addresses the needs of programme managers, scientific fraternity and the public.

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Figure 8.10 Example of monitoring reports from Chesapeake Bay and Santa Monica Bay.

Graphical and written summaries should be produced that demonstrate the results of individual components of the monitoring programme as well as the relationships between monitoring activities. Examples of monitoring reports from Chesapeake Bay and Santa Monica Bay is presented in Figure 8.10. These summaries should

267 Chapter 8: Wetland Management Framework serve as tools to effectively communicate information on the effectiveness of the actions taken by the wetland programme. Demonstration materials that summarise programme results should be produced for use in newsletters, workshops, poster sessions, and public forums. The results of the monitoring effort should also be made available to scientific community, and use of monitoring data should be encouraged. Data analysis should be conducted to test for trends, test and generate new hypotheses, evaluate the uncertainties association with the data, to identify the source of these certainties. These analyses should serve as a basis for extending existing knowledge of wetlands, making refinements to conceptual and numerical models of the system developed in the characterisation phase of the programme, and identifying new research. Collectively the analytical results should provide the necessary information for redirecting and refocusing the CCMP.

8.8: Example of the application of the [NRFBMP]: implementation of bacterial and nutrient contamination monitoring.

The results indicated that coliform bacteria concentrations and nutrient enrichment of the system pose a potential threat to the system. The development of a monitoring plan is thus required to monitor and manage these two problems in the system. Figure 8.11 indicates the framework within which the two potential problems could be incorporated.

The first stage involves developing the monitoring objectives of the program. Two objectives for the management and monitoring of the Nyl River Floodplain would be the detection of spatial and temporal changes in bacterial content in the floodplain and the detection of improvement or deterioration of the system with regard to nutrient levels over time.

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Public

concern Modelling Research Legislation

DEVELOP / REFINE MONITORING OBJECTIVES Objective 2 Objective 3 Objective n

Refine monitoring objectives

EVALUATE / ASSESS PROGRAMME PERFORMANCE

COMMUNICATE MONITORING RESULTS / REDIRECT MANAGEMENT PROGRAMME

Figure 8.11: Conceptual framework of the biomonitoring programme into which the management of contaminants should be incorporated.

The Nyl River Floodplain biomonitoring programme consists of various components of which the development and refining of existing plans is vitally important. Figure 8.12: indicates the developmental and refining stage in designing a monitoring program for potential variables of concern in the system.

The results have indicated two variables of concern in the system, which would be incorporated into this conceptual framework as follows. Figure 8.13 indicates the

269 Chapter 8: Wetland Management Framework incorporation of the potential coliform contamination in the system into the biomonitoring framework. Figure 8.14 indicates the incorporation of the nutrient enrichment into the framework.

Develop monitoring objectives, performance criteria

Establish testable hypothesis and select statistical methods

Rethink Select analytical methods monitoring and study alternative sampling designs approach

Evaluate expected monitoring programme performance

Is the No monitoring programme adequate?

YES

Design and implement data management Figure 8.12: Developmental and refining stageplan in designing a monitoring program for potential variables of concern in the system

The first stage requires the formulation of a suitable monitoring objective. In both instances the objective would be to determine the temporal and spatial trends in bacterial and nutrient enrichment in the Nyl River system. The second stage involves the establishment of a testable hypothesis and the selection of the statistical methods to be used. The results from the present study indicate that the Nylstroom Sewage Treatment Works (NSTW) has an effect on the bacterial content in the system, especially the faecal coliform content. The hypothesis would thus be that the bacterial concentrations released in the Nyl River System originate from the NSTW. The present study also indicated that the system is enriched by nutrients and thus

270 Chapter 8: Wetland Management Framework the working hypothesis would be that the increased nutrients are a result of faecal contamination from intensive cattle farming activities. The third stage of the framework involves the selection of the analytical methods to use. These selections include the development of field and laboratory practices, site selection and determination of the number of sampling sites for efficient system analysis.

The monitoring design will involve a before-after control-impact (BACI) sampling design. Representative sites above the NSTW, where effluents are released into the stream, and then sites downstream from NSTW will be selected. The frequency of sampling is very important and monthly sampling is recommended. The analysis would involve determination of faecal coliform bacteria, total coliform bacteria and heterotrophic plate counts. The results then must be statistically analysed to determine spatial and temporal trends in bacterial levels.

Bimonthly sampling of nutrients in the system would provide vital information with respect to nutrient enrichment. The choice of variables to analyses is important with orthophosphates, total phosphates, nitrates, nitrites and ammonium concentrations providing the necessary information for system status analysis. Data analysis would involve applying the methods of Bath et al. (1999a and b) for the determination of water quality reference conditions and determination of present ecological state. The fourth stage of the framework involves evaluating expected monitoring performance. This stage helps to evaluate the experimental design to determine the minimum detection limits of the monitoring program. Without this stage the risk exists of analysing too few or too many samples for accurate system evaluation without providing accurate spatial and temporal trends.

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Determine spatial and temporal trends in bacterial levels in the system

The NSTW has an effect on the bacterial levels in the system.

Rethink Sample site selection and monitoring analysis of faecal coliforms, study total coliforms and approach heterotrophic bacteria

Does the present monitoring program provide the necessary data?

Is the No monitoring programme adequate?

YES

Design and implement data management

Figure 8.13: Incorporation of the identified potential coliform contamination in the system into the biomonitoring framework.

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Determine spatial and temporal trends in nutrient levels in the system

The farming operations have an effect on nutrient levels in the system

Sample site selection and analysis Rethink of nitrates, nitrites, ammonium, monitoring phosphates and total phosphates. study Determine present ecological state, approach and reference conditions

Does the present monitoring program provide the necessary data?

Is the No monitoring programme adequate?

YES

De sign and implement data management

Figure 8.14: Incorporation of the identified nutrient enrichment into the framework.

The fifth stage is to design and implement a data management plan, which will allow for the dissemination of data to interested and affected parties as well as to the relevant management organisations to allow for effective corrective decision making.

By incorporating all the potential problems into the framework as the different objectives of the management plan, one can effectively manage these problems and thus help to conserve and protect the wetland.

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8.9: References Murray, K. and Claassen, M. (1999). An interpretation and evaluation of the US Environmental Protection Agency ecological risk assessment guidelines. Water SA 25 (4). pp 513-518. US EPA (1992). Monitoring Guidance for the National Estuary Program. EPA/842/B-92/004, Washington DC.

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Chapter 9:

Conclusions and Recommendations

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Chapter 9: Conclusions and Recommendations

The results from the water analysis give a comprehensive summary of the water quality in the Nyl River System. Of the many variables and parameters analysed the bacteriological study indicated most cause for concern. Total coliform and faecal coliform counts increased along the course of the river and into the wetland. The faecal coliform counts increased from the point were the Nylstroom/Modimolle Sewage Treatment Works releases its effluent into the Klein Nyl River. This increase in faecal coliform content can have deleterious effects on the system as well as the people who rely on the water in the system. There are three possible causes for the increase in faecal coliform content along the course of the Nyl River namely: 1. The Nylstroom/Modimolle Sewage Treatment Works is unable to cope with the volume of effluent that passes trough it. This is evident from Figure 2.8 (Chapter 2), which clearly shows a pipe leading into the field along the banks of the Klein Nyl River. This could results in raw sewage leaching into the river and the subsequent contamination thereof. 2. The second possible cause for the increase in faecal coliform content in the river is run off from the surrounding informal settlements such as Phagameng. Insufficient municipal services could have an effect in the quantity of bacteria entering the system during the rainy season. 3. The third possible cause for the increased faecal coliform content in the system can be attributed to increased run off from agricultural land. The surrounding areas contain a large number of live stock farmlands including cattle, pigs, chickens, game and crocodiles. Run off during the rainy season could cause an increase of faecal coliform bacteria in the system.

Although there is little one can do about the increase of livestock farming in the surrounding areas it is possible to address the other two points of contamination. The Nylstroom/Modimolle Sewage Treatment works needs to be upgraded to cope with the volumes of sewage received and possibly to make provision for

276 Chapter 9: Conclusions and recommendations any further expansion of Nylstroom/Modimolle. The incorporation of the informal settlements into the sewage network would also decrease the run off of bacteria entering the system. Although parts of the settlements may have been incorporated already, personal observation indicated that the pipelines are in a poor state and blockages in the system cause spills of raw sewage. Maintenance of these systems is also vitally important.

The floodplain helps in the purification of the water in the river system and aids in decreasing coliform counts. Continual contamination of the system however eventually exceeds the systems’ ability to cope with the bacterial levels and process them, leading to health risk problems further down stream. Increased levels of coliform bacteria in the wetland could also lead to the contamination of ground water supplies.

Toxicity tests done on the water in the system indicate that the water is suitable for sustaining aquatic life. The acute static screening toxicity tests on P.reticulata and D. pulex indicated low mortalities and thus indicate that the water is of a fair quality.

The ICP-MS analysis of the whole water samples indicated that there are heavy metal concentrations above the TWQR set out by the Department of Water Affairs and Forestry (DWAF, 1996). These metals however occur naturally in the system with the metal levels in the water remaining relatively constant from the source of the Klein and Groot Nyl Rivers to the furthest sampling site at Moorddrift. The physical water quality parameters such as the conductivity, oxygen content and pH also indicated little cause for concern. These factors together with the metal concentrations show that the water is of a fair quality. A comparison of reference condition (Bath et al., 1999a) and the present ecological state (Bath et al., 1999b) of the system indicates that although the nutrient levels in the system are on the increase, they pose little cause for concern, as the levels of toxic ammonia are still low. All these chemical constituents would

277 Chapter 9: Conclusions and recommendations indicate that the system is relatively un-impacted although the relatively non toxic nutrient levels indicate otherwise.

The analysis of metals in the sediment indicates that they pose little cause for concern in the system. The sequential extraction sediment analysis indicated that the majority of the metals in the system are partitioned in the 3rd to 5th fractions. This indicates that the majority of the metals are not readily bio available. The metals will become more available with a decrease in water pH with remobilisation being aided in the presence of strong reducing agents. The analysis of pesticide levels in the sediment indicated that they pose little threat to the system. The levels determined were inadequate to quantify but traces of the pyrethroid, Cypermethrin, and polychlorinated biphenyls (PCB’s) were detected. Due to the persistent nature of the organic compounds further analysis into the accumulation of organics in fish tissue is recommended.

The results from the water and sediment analysis indicate that the system is not polluted. This would also indicate that the ability of the wetland to purify and filter water has not yet been compromised. Wetlands are natural filters and can help in providing a clean source of water to people for consumption. The high bacterial content detracts from this and thus needs attention. The wetland also helps in ground water recharge and it is thus vital to preserve this jewel in the Limpopo Province.

The results would also indicate that the decrease in bird numbers seen throughout the system and in the Nylsvley Nature Reserve is caused by some other anomaly. The water in the system provides suitable habitat for waterfowl and the fish and invertebrates that they feed on. Further monitoring of the system is necessary but at this stage one would have to investigate other reasons for decreases in migratory bird numbers visiting the wetland. Some possible reasons for this could be: 1. The increased number of artificial wetlands being constructed around

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Africa to help in the water purification process and for their aesthetic value. 2. Increased air traffic along migratory routes as world travel becomes easier and cheaper. 3. Increased predation due to food shortages in many African countries. 4. Changes in the world’s climate due to global warming could also be having an effect on the migratory patterns of birds. 5. Changes in rainfall patterns and thus flooding regimes of wetlands could also have an effect on the availability of the necessary food needed to sustain breeding and rearing of chicks.

Nylsvley is a dynamic and variable system, which undergoes cyclic changes. Although no data was collected on flow rates, flooding regimes and the general hydrology in the floodplain it was noticeable during the sampling phase of the study how flooding differed on a temporal scale. Changes in rainfall lead to the wetland experiencing flooding at different times in the year. Varying rainfall levels also lead to differing flood levels. This affects the productivity of the wetland and thus the availability of habitat and food stocks. The cyclic nature of the flooding from year to year could also be mirrored by migratory birds, thus in years with less rainfall the number of bird will also decrease. The construction of artificial barriers such as roads and impoundments has also changed the hydrology of the system. These barriers have helped change the nature of the system providing new habitats and destroying others. The construction of impoundments upstream has also changed the flooding period and the wetland only fills up with water long after the rain has started falling.

The Wetland Assessment Protocol is the first step in developing a useful tool in the rapid assessment of the countries’ wetlands. The WAP cannot be seen as the be all and end all in the monitoring of a system but will help in determining if the system is under threat from an external source. The WAP should be used in conjunction with a series of monitoring protocols to obtain the best possible

279 Chapter 9: Conclusions and recommendations results.

The WAP has been developed to be relatively non invasive to the system but also to be rapid, simple and cost effective. The protocol does not need to be carried out by highly educated people and a layman may be trained to identify the invertebrates quite easily. At this stage the protocol still has to be tested on various systems. Due to the unique nature of the Nyl River Floodplain, the system should be tested in other ephemeral floodplain systems. The WAP should also be tested in a system with a larger pollution gradient. The relative un- impacted nature of the Nyl River System doesn’t lend itself to the calibration of a bio-monitoring tool. The protocol does however have the ability to identify the sites that are under more pressure than others.

Recommendations for further studies: Although this study provides a comprehensive study of the water and sediment quality in the Nyl River Floodplain and answers many questions as to the state of the wetland it also asks more questions like: 1. What percentage of the bacterial contamination is from run off and what percentage comes from the Sewage Treatment Works? 2. What is the source of the nutrient enrichment? 3. To what extent has the observed change in flow regime influenced the productivity and efficiency in function of the Nyl River System? 4. Why are observed bird numbers dropping?

These new questions provide more scope for further study into the management and conservation of the Nyl River Floodplain.

The conservation of the Nyl River Floodplain relies on the development of an effective realistic management plan. Chapter 8 presents the framework for such a management plan and this study lays down the groundwork in providing a base line from which to work. Reliable baseline values now exist to act as a reference

280 Chapter 9: Conclusions and recommendations for further comparative studies. These baseline values can be incorporated into the framework to provide the necessary management plan needed to protect this important wetland in the dry Limpopo Province. Section 8.8 in chapter 8 provides an example of how potential problems could be incorporated into the management framework.

It would also be advisable to implement a quarterly monitoring program using some of the biomonitoring tools such as the WAP, Integrated Habitat

Assessment (IHAS), SASS5, the Riparian Vegetation Index (RVI) and other IBI’s (Indices of biotic integrity). The use of the WAP along with the other bio- monitoring tools will also help in validating the data provided by the protocol. It is pointless to analyse a wetland without analysing the water entering the wetland and as such all these biomonitoring tools can be useful. Although most of the tools have been developed for riverine systems, observed changes in scores can help in assessing and reporting changes in the WAP score. The results obtained during the development of WAP indicate the protocols’ potential but more data is needed before the protocol can be incorporated as a viable tool in water quality monitoring. The WAP should also be validated in other wetlands with a greater pollution gradient. An annual screening toxicity test could provide vital information as to the suitability of the aquatic environment for sustaining aquatic life. The implementation of such a management plan is vital if the wetland is to survive and maintain its status as a wetland of international importance.

281 Chapter 9: Conclusions and recommendations

9.1: Reference

DEPARTMENT OF WATER AFFAIRS AND FORESTRY (DWAF). (1996). South African Water Quality Guideline volume 7: Aquatic ecosystems. pp 159. BATH, A., JOOSTE, S., HOHLS, B., MACKAY H., ASHTON, P. and PALMER, C. (1999a). Part one of appendix x: determination of reference conditions for water quality variables. Unpublished Report, Institute for Water Quality Studies, Pretoria. BATH, A., JOOSTE, S., HOHLS, B., MACKAY, H., ASHTON, P. and PALMER, C. (1999b). Part two of appendix x: determination of present ecological statues: water quality . Unpublished Report, Institute for Water Quality Studies, Pretoria.

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