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How to cite this thesis

Surname, Initial(s). (2012) Title of the thesis or dissertation. PhD. (Chemistry)/ M.Sc. (Physics)/ M.A. (Philosophy)/M.Com. (Finance) etc. [Unpublished]: University of Johannesburg. Retrieved from: https://ujdigispace.uj.ac.za (Accessed: Date). SEASONAL EXPOSURE IN THE FORM OF PRECIPITATION AND ITS EFFECT ON WATER QUALITY FOR THE ROODEPLAAT DAM DRAINAGE BASIN: 2000 – 2009.

Nicole Janet LOMBERG

Minor Dissertation submitted in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE in ENVIRONMENTAL MANAGEMENT

Faculty of Science

University of Johannesburg

Supervisor: Prof. J.T. Harmse

December 2010

ABSTRACT

The main purpose of this study is to determine whether trends in rainfall patterns correlate to trends in water quality constituents for the Roodeplaat Dam Drainage Basin, thereby increasing the ‘dilution capacity’ potential of the aforementioned water system. The Roodeplaat Dam (reservoir) is a hypertrophic impoundment located approximately 20 kilometres north-east of Pretoria. The dam was originally designed for irrigational purposes and later became an important recreational site. In recent years it serves as an important source for Magalies Water, which represents a state-owned water board that currently supplies potable water to a large area north of Pretoria.

The Roodeplaat Dam catchment consists of three contributing rivers to the inflow of the impoundment, namely: The Pienaars River (located in the centre of the catchment), the Edendale Spruit (east of the catchment) and the Moreleta/Hartebees Spruit (west of the catchment). There are also two Water Care Works (Zeekoegat and Baviaanspoort) within the catchment, which supplement additional inputs of treated effluent discharges to the reservoir.

Temporal changes in selected physical, chemical and microbial constituents were analysed at established sampling points along each river, including a sample site located at the dam wall outlet. Such changes in water quality, in conjunction with rainfall patterns exhibited in the study area were analysed to determine whether an association exists between the two variables, and more specifically how rainfall impacts on water quality within the catchment which has a direct effect on the quality of the Roodeplaat Dam.

Data for rainfall and water quality were analysed over a 10 year period, from January 1999 to December 2009. Water quality sampling results were obtained from the Department of Water Affairs. Rainfall data for the same time period in question was obtained from the South African Weather Service. Results for both variables were projected graphically and collated to determine whether rainfall trends have an impact on concentrations of water quality constituents. Constituent concentrations were also compared at each sample site. To quantitatively justify graphical results, the author preformed Pearson’s and Spearman’s correlation analysis to establish whether rainfall and water quality concentrations displayed significant associations.

Results from graphical presentations and quantitative analyses identified that a correlation does exist between rainfall and water quality constituents, whereby an increase in rainfall tends to result in a decrease of water quality constituent concentrations. Microbial constituents contrasted to physical and chemical results, and displayed a strong positive correlation to rainfall. Rainfall therefore increases the ‘dilution capacity’ potential of the catchment, whereby the water system increases in its ability to receive and remove pollutants disposed in them by human induced land-use activities.

It was also found from the study that the strength and association between rainfall and water quality constituents is affected by external, anthropogenic variables which also exert an influence on the quality of water present in the Roodeplaat Catchment Area. This includes additional inputs from the Baviaanspoort, which is located along the Pienaars River. Results from the sample site located on this river displayed no relationship for many of the water quality constituents tested. It has also been highlighted from the study how the landscape has been severely altered by the rapid rate of human induced land use activities in the past decade. Further investigations need to incorporate the influences of natural phenomena, such as rainfall, together with influences exerted from anthropogenic activities. This will provide clearer information on the interdependent factors at play which compromise the dilution capacity potential of the Roodeplaat Catchment Area and subsequently the poor water quality status exhibited at the impoundment. Once such externalities are accounted for, it is recommended that a suitable management plan be conducted for the Roodeplaat Catchment Area that is based on scientific grounding and proactively mitigates the impacts exuded by land-use activities, thereby improving the status of the Roodeplaat impoundment.

ACKNOWLEDGEMENTS

It is with great sincerity and gratitude that I acknowledge the following persons and institutions for their significant contributions to the completion of this research study:

 Professor J.T. Harmse, my supervisor, for his invaluable contributions, provisions made and time spent on the review of my study. His manner of kindness, words of wisdom and open-door policy has been an incredible support system, not only through this process, but throughout my studies at the university.

 To all the staff members at the department who continuously give of themselves to the students and have made my time at the university a thoroughly enjoyable experience.

 The Department of Water Affairs and South African Weather Service for the supplement of raw data used in this study.

 To my incredible parents and brothers, who have supported me at every turn and encouraged me to fulfil my ambitions. Their unwavering faith and love for me has been such a vital piece of this puzzle. To all my family and friends for their support, I thank you.

 And finally, to my Heavenly Father, who has guided me through seasons of hardships and seasons of prosperity- who is always with me. Words could not justify my love or gratitude to Him.

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TABLE OF CONTENTS

ABSTRACT i ACKNOWLEDGEMENTS iii LIST OF FIGURES vi LIST OF TABLES vii ABBREVIATIONS USED xi 1. INTRODUCTION . 1 2. MOTIVATION FOR STUDY: PROBLEM STATEMENT AND OBJECTIVES 2 3. LITERATURE REVIEW 6 4. DESCRIPTION OF STUDY AREA 15 4.1 Location, Boundaries and Size 17 4.2 The Main Land-Use Activities in the Roodeplaat Dam Catchment Area that Impact on Water Quality 21 4.2.1 Land-use activities along the Pienaars River 23 4.2.2 Land-use activities along the Edendale Spruit. 24 4.2.3 Land-use activities along the Hartebees Spruit 25 4.2.4 Land-Uses Changes in the Roodeplaat Catchment Area. 25 5. WATER QUALITY AND WATER QUALITY CONSTITUENTS IN THE ROODEPLAAT DAM CATCHMENT AREA (2000-2009) 28 5.1 Physical Constituents 29 5.1.1 pH 29 5.1.2 Dissolved Major Solids (DMS) 29 5.2 Chemical Constituents 30

5.2.1 Inorganic Nitrogen (NH4) 30

5.2.2 Phosphates (PO4) 32

5.2.3 Sulphates (SO4) 35 5.2.4 Magnesium (Mg) 35 5.3 Microbial Constituents 36

5.3.1 E- Coli 37 6. DATA COLLECTION AND METHODOLOGY 40 6.1 Data collection and location of sample sites 40 6.2 Shortcomings of Data 42 6.3 Analysis of Data 43 7. RAINFALL OF THE ROODEPLAAT DAM 45 CATCHMENT AREA (2000-2009) 8. RESULTS AND DISCUSSION 46 8.1 Physical Constituents 46 8.1.1 pH 46 8.1.2 Dissolved Major Solids 48 8.2 Chemical Constituents 51 8.2.1 Inorganic Nitrogen 51 8.2.2 Phosphates 55 8.2.3 Sulphates 58 8.2.4 Magnesium 61 8.3 Microbial Constituents 65 8.3.1 E-Coli 65 8.4 Impact of Rainfall on water quality for the Roodeplaat Dam 69 Catchment area (2000-2009) 9. CONCLUSION 72 10. REFERENCE LIST 74

LIST OF FIGURES

Figure 1: Spatial Distribution of Mean Annual Precipitation across Southern Africa. 6 Figure 2: Distribution of Large Impoundments in South Africa. 8 Figure 3: Water Management Areas within South Africa. 15 Figure 4: Overview of the Crocodile (West) Marico Water Management Area. 16 Figure 5: Location of the study area within the Gauteng Province, South Africa. 17 Figure 6: Locality of Study Site. 18 Figure 7: Map of the Three Sub-Catchment Regions within the Roodeplaat Dam Catchment 20 Area. Figure 8: Land-use Activities within the Roodeplaat Catchment Area. 22 Figure 9: Changes in Land-Use Activities from 1997 to 2010 26 Figure 10: Roodeplaat Dam in December 2008. 33 Figure 11: Roodeplaat Dam in January 2009. 33 Figure 12: Fish deaths as a result of toxic cyanobacterial blooms. 34 Figure 13: Location of Sampling Points in Relation to Surrounding Land-use Activities. 41 Figure 14: Location of Sampling Points in Designated Study Area. 41 Figure 15: Location of Weather Station used in Study. 42 Figure 16: Interpolation of Incomplete Data Sets. 44 Figure 17: Results of Rainfall Tracking Over the Study Area (2000-2009). 45 Figure 18: Comparison of Sample Point concentrations of pH. 46 Figure 19: Results of pH and Rainfall Tracking at SP2. 47 Figure 20: Results of pH and Rainfall Tracking at SP4. 48 Figure 21: Results of DMS and Rainfall Tracking at Sample Point 3. 49 Figure 22: Results of DMS and Rainfall Tracking at Sample Point 2. 49 Figure 23: Comparison of Nitrate Concentrations at each of the Study Sample Points. 51 Figure 24: Inorganic Nitrogen and Rainfall Tracking at Sample Point 1. 53 Figure 25: Results of Inorganic Nitrogen and Rainfall Tracking at Sample Point 2. 54 Figure 26: Comparison of Phosphate Concentrations at each Sampling Point. 55 Figure 27: Results of Phosphate and Rainfall Tracking at Sample Point 1. 56 Figure 28: Phosphate and Rainfall Tracking at Sample Point 2. 57

Figure 29: Comparison of SO4 Concentrations at each of the Study Sample Points. 58 Figure 30: Results of Sulphate and Rainfall Tracking at Sample Point 1. 59 Figure 31: Results of Sulphate and Rainfall Tracking at Sample Point 3. 60 vi

Figure 32: Comparison of Magnesium Concentrations at each of the Study 62 Sample Points. Figure 33: Results of Magnesium and Rainfall Tracking at Sample Point 1. 63 Figure 34: Results of Magnesium and Rainfall Tracking at Sample Point 2. 64 Figure 35: Magnesium and Rainfall Tracking at Sample Point 3. 65 Figure 36: Comparison of E-coli Concentrations at each Sampling Point. 66 Figure 37: Results of E-Coli and Rainfall Tracking for Sample Point 1. 67 Figure 38: Results of E-Coli and Rainfall Tracking for Sample Point 2. 68 Figure 39: Results of E-Coli and Rainfall Tracking for Sample Point 3. 68

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LIST OF TABLES

Table 1: Extent of Failing Wastewater Treatment Capacity across South Africa. 9 Table 2: Trophic status as an indicator to assess the effects of Inorganic Nitrogen to an 31 Aquatic Ecosystem. Table 3: Aesthetic and Health Effects of Increased Magnesium Consumption. 36 Table 4: Effects of Faecal Coliforms in varying Concentrations to Human Health. 39 Table 5: Naming of Sample Points operated by DWAF. 40 Table 6: Correlation Co-efficient Values at all Four Sample Sites for DMS Concentrations. 50 Table 7: DWAF Water Quality Guidelines for Nitrates. 52 Table 8: SANS 241: 2005 Drinking Water Specifications. 52 Table 9: Vaal Barrage In-Stream Reservoir Guidelines for Nitrates. 52 Table 10: Vaal Barrage Reservoir In-Stream Water Quality Guidelines for Phosphates. 55

Table 11: Correlation Significance of PO4 and NH4 at each Sample Point. 57 Table 12: VBR In-Stream Water Quality Guidelines for Sulphates. 58 Table 13: SANS 241:2005 Drinking Water Specifications for Chemical Requirements- 58 Macro Determinants. Table 14: Vaal Barrage Reservoir In-Stream Water Quality Guidelines for E-Coli. 66

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ABBREVIATIONS USED

DWA Department of Water Affairs DWAF Department of Water Affairs and Forestry SP Sample Point SANS South African National Standards HSPF Hydrological Stimulation Program Fortran EFDC Environmental Fluid Dynamics Code WASP Water Quality Simulation Program EC Electrical Conductivity DMS Dissolved Major Solids

1. INTRODUCTION

According to van der Merwe-Botha (2009) consensus has been reached with regards to the vital role that water plays in human society. In addition to water being the primary source of livelihood and human health, it is also a fundamental input into all production in agriculture, industry and energy. Furthermore, water security is not only dependant on the adequate quantity, but also on the quality thereof.

South Africa is well cited throughout literature as being a ‘water-scarce’ country, with an average annual rainfall of 497mm in comparison with a world average annual rainfall of 860#mm (Mukheiber & Sparks, 2003; Fox & Rowntree, 2003). Only a narrow region along the south-eastern coastline receives adequate rainfall, whilst the majority of the interior and western part of the country is regarded as arid or semi-arid. However, attention is also being brought to the quality of existing water resources, particularly if there is limited availability of such resources as

Decisions regarding the allocation, distribution and strategic development of water resources by water management authorities, need to start asking pertinent questions about the fiscal value of water quality, particularly for a country like South Africa that already faces water shortages in the midst of growing economic and population demographics. According to van der Merwe-Botha (2009) decision makers, investors and researches share the view that the declining quality of water will have a negative impact on the South African economy, in both the short and long term.

According to van der Merwe-Botha (2009) wastewater quality has a direct impact on the system, in similar ways that pollution from agriculture, mining and other industries has an impact on South Africa’s water resources. In Gauteng, approximately 74 percent of the wastewater treatment works fail to comply with standards for two or more parameters in relation to effluent quality (van der Merwe-Botha, 2009). As in the case of the Roodeplaat Catchment basin, two domestic wastewater works (the Biviaanspoort and Zeekoegat) feed directly into the Roodeplaat Dam. This impoundment serves as an important source for Magalies Water, a state-owned water board that currently supplies potable water to a large area north of Pretoria.

Feeding substandard and polluted water into South Africa’s reservoirs and impoundments impacts on the quality of the receiving waters, creating trade-offs between the economic costs of maintaining wastewater works that do not have the ability to handle increased influent loads, and water quality of potable drinking water that receive treated effluents (van der Merwe, 2009).

The Roodeplaat Dam represents an important source of freshwater to the Gauteng Province. The catchment landscape has been greatly altered by the expansion of human activities. The Roodeplaat impoundment is well recognised for its exceedingly high levels of eutrophication and hypertrophic status.

As stated by van der Merwe-Botha (2009) such figures about South Africa’s water resource status demonstrates why water manager’s values and priorities are changing; from the constructions and development of dams (quantity) to good management and maintenance techniques. “Water resources management increasingly needs to focus on improving, in an equitable way, the security, safety and efficiency of existing facilities, while meeting environmental obligations and maintaining the usability of precious water supplies” (van der Merwe-Botha, 2009, p.10). This requires information on how water quality in the catchment is affected by different factors at play. Once such information is scientifically quantified, water managers can make effect decisions with regards to the protection of South Africa’s existing freshwater reserves.

2. MOTIVATION FOR STUDY: PROBLEM STATEMENT AND OBJECTIVES

Roodeplaat Dam represents a vital water resource that is utilised by a variety of different stakeholders (drinking water, recreational use and irrigational purposes). Water resource management is a crucial element in the allocation and use of South Africa’s water resources. Since management requires measurement, much more effort is needed to enhance and maintain water quality assessment, management and audits. The land-use activities and subsequent impacts that occur within the Roodeplaat Dam Basin are well documented (Pieterse & Toerien, 1978; Anne-Jones & Fred- Lee, 1984; Swanepoel, 1997; Oberholster & Ashton, 2008). However, in order to strengthen water quality assessments and overall management of the region, it is also important to identify how seasonal exposure, and in this case rainfall variability, contributes to the interdependent factors at play which impact on Roodeplaat’s declining water quality and hypertrophic status.

An important driver of water quality is the climate (van der Merwe-Botha, 2009). According to Turton (2008) dilution capacity is a term that refers to the ability of water bodies to receive and remove pollutants disposed in them through human activities. South Africa is already recognised as a ‘water scarce’ country due to the low average annual rainfall it experiences.

By establishing weather a relationship exists between precipitation and concentration of pollutants within the Roodeplaat Dam catchment, one can identify the extent to which the dilution capacity of the area is compromised. A weak dilution capacity means that all pollutants, including effluent streams, will have to be treated at an increasingly higher standard before being discharged into communal waters and impoundments (van der Merwe- Botha, 2009). The Baviaanspoort and Zeekoegat wastewater works already face operational challenges to treat increased loads with limited financial resources, poor operating and maintenance practices as well as lack of technical ability (DWAF, 1998). Deciphering temporal patterns and correlations of water quality constituents may also be useful for developing future monitoring strategies to track concentrations patterns and loads.

A comprehensive study examining the relationship between precipitation and its influence on water quality of the Roodeplaat drainage system over an extensive period has not been carried out. Thus, the aim of this study is to examine the spatial and temporal variations of selected water quality parameters over a long-term period, and to establish whether the seasonal influence of rainfall correlates to changes in water quality concentrations at the Roodeplaat Dam. Water inflow from the catchment area drains directly into the Roodeplaat Dam and therefore has an effect on the water quality thereof.

To achieve the goals of the study, the following objectives have been identified:  Identify the main land-use activities in the Roodeplaat Dam catchment area that impact on water quality. This will be achieved through the referencing of literature pertaining to the study area, site investigation as well as the analyses of maps of the study area.

 Select the most significant organic and inorganic water quality variables in response to the surrounding land-use activities. Using the Water Quality Guidelines established by DWAF in concordance with the land-use activities identified above, eight water quality parameters shall be selected to include physical, chemical and microbial constituents which impact on the water quality status of the Roodeplaat Dam catchment area.

 A set of sampling points will be selected from the available data provided by DWAF. The water quality data of samples collected at four sampling points on the Pienaars River, Hartebees Spruit, Edendale Spruit and inlet to the Roodeplaat Dam will be obtained from the Department of Water Affairs.

 Establish a trend analysis of the selected water quality variables for a mean monthly value over a 10 year period (1999-2009). Using the data provided by the Department of Water Affairs, a trend analysis of each water quality parameter will be established at each sampling point within the catchment area.

Water quality results will be interpreted and discussed, and recommendations will be made to highlight any negative impacts on the water quality at the sampling points. The results will be compared to the Water Quality Guidelines of DWAF for aquatic systems, domestic use and recreational use as well as the Vaal Barrage In-Stream Water Quality Guidelines. Results will also be compared to DWAF’s SANS 241: 2005 Drinking Water Specifications. Special emphasis will be given to those parameters which exceed these Water Quality Guidelines.

 Correlate the water quality monitoring data with annual rainfall data for the study area in the same time period to determine whether a relationship exists between rainfall variation and water quality impacts. Using data provided by the South African Weather Services for annual rainfall values, the author shall correlate trends in water quality parameters to annual precipitation loads to establish whether a relationship exists between the two variables.

In the following section, the status of water quality with regards to South Africa’s freshwater resources will be examined. Previous studies relating to seasonal exposure on water quality status will also be discussed.

3. LITERATURE REVIEW

As stated by Turton (2009, p.1) “water is a strategic natural resource which, by virtue of its fundamental physics and chemistry, is fugitive in nature”. This means that unlike any other resource (oil, coal etc), it is not a stock but rather a flux. The distribution of water is pre- determined by physical elements which combine to form the ‘hydrological cycle’. It is the hydrological cycle that establishes the spatial and temporal distribution of water across South Africa.

Figure 1: Spatial Distribution of Mean Annual Precipitation across Southern Africa (Turton, 2009, p.1).

From Figure 1 it can be seen that the spatial distribution of water across southern Africa is uneven, with a steep gradient from north to south and east to west. The result of this uneven distribution of precipitation leaves four of the most economically diverse countries- South Africa, Botswana, Namibia and Zimbabwe- all on the ‘wrong’ side of the global average of 860#mm per annum (Turton, 2009). South Africa has an average annual rainfall of approximately 497 mm (Mukheiber & Sparks, 2003; Fox & Rowntree, 2003; Nomquphu, 2005). Moreover, only nine percent of the rainfall reaches rivers, compared to the world average of 31 percent (DWAF, 1996; Oberholster & Ashton, 2008). Seven of South Africa’s nine provinces rely on water that is provided by inter-basin transfers. This reveals the intensity to which South Africa’s available resources are being used at present (van der Merwe-Botha, 2009).

Water scarcity represents the fundamental resource challenge in South Africa. However, as noted by Turton (2009) there is an uncharacteristic set of ‘risk’ drivers associated with water resource management in South Africa. This includes the geographic location of centres of development, whereby large cities such as Johannesburg and Pretoria are all located on, or very close to major watershed divides. This is a result of early industrial development, where mining dictated settlement patterns as opposed to water availability. According to Turton (2009, p.3) “this is totally at odds with the rest of the world, where most major centres of development are located on rivers, lakes or the seashore”. This driver of risk in itself promulgates the need to manage South Africa as a ‘transition’ from a non-sustainable extractive economic development industry (mining) into a sustainable industrial-based local economy, centred on existing cities (Turton, 2009).

As noted by Turton (2009) the way this challenge has been managed to date is through the development of hydraulic infrastructure, such as dams. Dams provide the high assurance of supply needed to support economic development within the region. Figure 2 depicts the distribution of large impoundments in South Africa. As very few natural lakes exist within South Africa, water impoundments and reservoirs represent the major sources of freshwater utilised by society. South Africa has over 497 large water impoundments, each with a capacity in excess of one million cubic metres, in addition to over 150, 000 smaller impoundments and farm dams (Oberholster & Ashton, 2008).

Figure 2: Distribution of Large Impoundments in South Africa (Capacity greater than one million cubic metres) (Oberholster & Ashton, 2008, p.2).

According to Harding (2010) South Africa faces an escalating water quality crisis, posed by the rapid decline of water quality of our dams. Approximately 35 percent of South Africa’s impounded water resources are seriously impaired (eutrophic to hypertrophic), with a further 20 to 30 percent which are incipiently problematical. “All of the major impoundments in the economic heartland of the country, Gauteng, are grossly impaired” (Harding, 2010, p.2). The declining water quality status of South Africa’s freshwater reserves is exacerbated by the increased demand for such resources to sustain an expanding population and economy. As noted by Oberholster & Ashton (2008) almost all of the country’s freshwater resources have now been fully allocated. It is forecasted that South Africa’s freshwater resources will be fully depleted and unable to meet the demands of people and industry by the year 2030 (National Committee on Climate Changes, 1998). As this transpires, less water will be left to support aquatic and associated eco-systems. As noted by Wallace et al. (2003) it is far more challenging to quantify the ‘value’ of water to ecosystem functioning. This in turn makes it extremely difficult for market-driven water managers to incorporate the values of ecosystem functioning into day-to-day water management techniques (Wallace et al., 2003).

Another driver of risk associated with water resource management in South Africa includes the management of effluent return flows. Given that centres of development are predominantly located on watersheds, the management of effluents becomes a critical issue to water quality. According to Turton (2009, p.5) “these major cities of development are located upstream of their water storage infrastructure, or crudely put, their sewage flows naturally into their drinking and industrial process-water”. This is the case for the Roodeplaat Dam catchment, with the Baviaanspoort water waste works situated upstream of the Roodeplaat impoundment on the Pienaars River.

Table 1 depicts the extent of failing wastewater treatment capacity across South Africa (Harding, 2010). Approximately 67 percent of Gauteng’s wastewater treatment facilities have non-compliant effluent flows. In the Free State and Northwest, approximately 99 percent and 100 percent of wastewater treatment facilities have non-compliant effluent respectively. The percentages of treatment works with flows that exceed design capacity are also substantial, with 84 percent of wastewater treatment works in Gauteng with flows that exceed facility design capacity. According to Mukheiber & Sparks (2003) it has been estimated that approximately R6 029 million may be required for the development of new major governmental waterworks during the next 25 years.

Table 1: Extent of Failing Wastewater Treatment Capacity across South Africa (Harding, 2010, p.2)

Eutrophication is the ecological term used to indicate the enrichment of water bodies with plant nutrients, primarily phosphorus and nitrogen, which consequently leads to the excessive growth of aquatic plants to levels that interfere with the desirable uses of the water body (Meyer & Rossouw, 1992; van Ginkel, 2002). During the eutrophication process, the water body accumulates nutrients and progressively alters its character from that of a deep water body (reservoir) to that of a wetland and, ultimately, to that of a terrestrial system (Walmsley, 2000). This subsequently leads to water quality deterioration, algal toxin production, oxygen depletion, clogging of water ways, disruption to the flocculation process in water treatment works and excessive loss of water through evapotranspiration (van Ginkel, 2002). This natural process has been significantly accelerated by human induced input activities, which in turn have accelerated the rate of enrichment, subsequently shortening the lifespan of water bodies (Walmsley, 2000). This is known as cultural eutrophication.

Sources of cultural eutrophication are classified as point and diffuse (non-point) sources. Point sources represent locations within the catchment of high nutrient concentrations (wastewater treatment works, livestock facilities) where effluent is discharged directly (via pipeline) into the receiving water body. Diffuse sources highlight multiple nutrient sources that are spread over a far wider area, whereby nutrients enter the water body through leaching and atmospheric deposition (Walmsley, 2000). According to Harding (2010) in most cases, particularly in the inland areas, cultural eutrophication is due to point source discharges of wastewater effluents.

As noted by Oberholster & Ashton (2008) until the 1980s, South Africa was recognised as one of the world-leaders with regards to eutrophication research. "Unfortunately, this advantage was lost because eutrophication management in South Africa focussed on the implementation of an inappropriately high phosphorus concentration (1mg/l) for all effluents discharged from sewage treatment plants to surface water systems” (Oberholster & Ashton, 2008). The result of this includes a significantly large proportion of South Africa’s freshwater impoundments being recognised as hypertrophic.

Hypertrophic impoundments, as in the case of the Roodeplaat Dam, are characterised by excessive levels of plant production that are governed by physical factors. Water Quality problems in such impoundments are continuous. As noted by Harding (2010), the problem of exposure to eutrophic water will be much more severe in rural areas where people have no choice but to drink whatever is directly obtainable from the river or waterhole. Eutrophication in the Roodeplaat Dam will be discussed in further detail in Section 5.2.

As noted by the Department of Water Affairs & Forestry (1998), in an effort to reduce eutrophication, management programmes have concentrated on reducing the total phosphorus load found within water bodies as phosphorus is considered to be the most manageable of nutrients. There are also verified and cost-effective removal measures which have been established with regards to the removal of phosphorus from wastewater. An effluent Standard of 1mg.1-1 ortho-phosphate was introduced on the 01 August 1980 by DWAF as a result thereof. The Standard was, however, only implemented in 1988 (DWAF, 1998).

A study was carried out by DWAF in 1998 to determine the extent to which the Baviaanspoort and Zeekoegat wastewater treatment facilities were complying with the Standard. The Baviaanspoort and Zeekoegat treatment facilities contribute approximately 70 percent of the phosphorus load to the Roodeplaat Dam (DWAF, 1998). Since 1988 when the Standard was implemented, the Baviaanspoort wastewater works had exceeded the Standard for some 50 percent of the time (DWAF, 1998). It was also found from the study that the Zeekoegat facility had exceeded the Standard approximately 77 percent of the time. According to van Ginkel (2002) the nutrient concentrations in the Roodeplaat Dam are of major concern. More stringent management strategies for eutrophication are needed as the 1 mg/l P-Standard has had minimal to no effect. “A constant increase in nutrients within the impoundment was apparent and symptoms of hyper-eutrophication are on-going” (van Ginkel, 2002, p.5).

Surrounding land-use activities in the Roodeplaat catchment area (point sources) have been recognised as the primary influential factor contributing to the poor water quality exhibited in the Roodeplaat Dam. However, very few studies have examined the combined effects of precipitation and land-use management practices on water quality at the regional or local scales.

Information on such combined factors affecting the water quality of the Roodeplaat impoundment is also necessary if trends are to be predicted and water management programmes applied. “In recognising that climate change impacts are a potential threat to the water related development goals of the country, substantial investments are required for water infrastructure and other water management strategies to be put in place” (Mukheiber & Sparks, 2003, p. 10).

There have been an abundance of studies conducted internationally to determine whether a correlation exists between rainfall/climate conditions and water quality. Tibby & Taylor (2007) conducted a study which analysed water quality monitoring data from three lakes in Western Victoria, Australia; namely: the Purrumbete, Colac and Bullen Merri. From the data collected over a 15 year time period, it was found that precipitation appeared to exert an influence on the water quality of these lakes.

Similar findings of correlation were exhibited by Chang (2004) who conducted a study on water quality impacts (specifically nitrogen loads) of climate change in south eastern Pennsylvania (Conestoga River Basin) for a period of 1970 to 1999. Based on the 21 year discharges of nitrogen from the Conestoga River, Chang (2004) noted a close association between annual loads of total nitrogen and annual precipitation. Nitrogen loads increased substantially with increasing precipitation. A bivariate linear regression suggested that the hydrological year’s (October- September) precipitation accounted for up to 75 percent of variation of annual nitrogen loads (p<0.05).

Shehane et al. (2005) conducted an assessment of microbial densities in an urbanised Florida watershed during a period of changing rainfall patterns to determine the role of climate change, coupled with urbanisation, in the declining water quality status of the catchment area. Concentrations of traditional and alternative faecal indicators were assessed by standard methods over a 24 month period. Changes indentified in faecal indicator densities and in faecal coliform sources during changing rainfall patterns suggested a strong role of precipitation on the sources and extent of microbial pollution within the urbanised Florida watershed (Shehane et al., 2005).

Schilling et al. (2009) conducted a similar study to Shehane et al. (2005) with regards to the temporal variations of E-coli concentrations in the Racoon River, Iowa, U.S.A. The Des Moines wastewater works is located on the Racoon River, which serves more than 400,000 people in central Iowa. Results from 2155 grab samples from 1997 to 2005 for E-coli analysis were examined for temporal variations. From the study, it was found that E-coli concentrations varied across years, seasons and flow conditions. As noted by Schilling et al. (2009, p.79) “Monthly concentrations exhibited clear seasonality with highest values in May through July”. Sinclair et al. (2009) observed similar results with regards to the temporal characteristics of faecal bacteria during the growing season from five sub-watersheds. It was found that faecal bacteria loads were greater during years with higher annual precipitation amounts.

Muhammad-Barzani et al. (2007) conducted a study to assess the hydrological properties and water quality of seven feeder rivers of the Tasik Chini, Pahang, Malaysia. The study was conducted in October and December 2004 and in February, March and April of 2005. Eleven water quality parameters were analysed based on in-situ and ex-situ analysis during these two season periods. A detailed physic-chemical study of the feeder river system during the wet and dry seasons revealed that the seven feeder systems showed varying seasonal fluctuations for various physical and chemical parameters. Water quality trends clearly identified that the majority of water quality constituents were higher in the wet season compared to the dry season (Muhammad-Barzani et al., 2007).

White et al. (2008) examined long term (20 years) data on water level, water quality and aquatic biota from four remote research areas in the Laurentian Great Lakes region in the USA. Through the use of correlation analysis, the study revealed significant correlations with water quality parameters and water level fluctuations in the research areas.

Liu et al. (2008) conducted research into the modelling of nutrient dynamics under critical flow conditions in three tributaries of St. Louis Bay in the USA. As noted by Liu et al. (2008) nitrogen dynamics were assessed for two designed critical flow conditions by integrating Hydrological Simulation Program Fortran (HSPF), Environmental Fluid Dynamics Code (EFDC) and Water Quality Analysis Simulation Program (WASP).

From the study it was found that nitrogen loads per unit flow volume were higher during the dry season. At the upstream tributaries, the computed total nitrogen concentrations were significantly higher for dry weather simulation than wet conditions, whereas at the near-bay tributary, there were no significant differences in total nitrogen load concentrations (Liu et al., 2008).

On a local scale, effects of seasonal exposure to various elements of water quality have also been examined in detail. Examples of this include a study conducted by Mzimela et al. (2003), who examined the seasonal variation of selected metals in sediments, water and tissues of the groovy mullet (Liza dumerelii) from the Mhlathuze Estuary in Richards Bay. The study revealed that metal constituents in both water and sediment were highest during December 1997, which coincided with extremely high freshwater inflow from the Mhlathuze River. Alternatively, metal concentrations were generally the lowest between April 1997 to June 1997, which coincided with reduced riverine runoff from the catchment of the Mhlathuze Estuary.

In the following sections, the challenges presented here, in relation to the declining water quality status of South Africa’s freshwater impoundments, will be related to the situation occurring at the Roodeplaat Dam. Many of the water quality challenges presented in this chapter are well recognised within the Roodeplaat Catchment area. In the following chapter, the description and characteristic of the study area, including a detailed examination of the land-use activities present in the Roodeplaat catchment area, will be discussed in detail.

4. DESCRIPTION OF STUDY AREA

South Africa is divided into 19 Water Management Areas in accordance with The Department of Water Affair’s1 Catchment Management Strategy. The designated boundaries of each Water Management Area are depicted in Figure 3. As can be seen from Figure 3, such boundaries do not correlate with administrative boundaries, but rather reflect the objective of the Department of Water Affairs to provide a framework of management of each Water Management Area, thereby ensuring consistency when responding to new water use licences, and informing existing water users (including authorities) on how the Department shall manage available resources within each area of concern (DWAF, 2004).

Figure 3: Water Management Areas within South Africa (DWAF, 2005, p.2).

The Roodeplaat Dam Catchment Area falls within the Crocodile West Marico Water Management Area (Numbered 3 in Figure 3). The natural mean runoff of the Crocodile West Marico Water Management area is approximately 855 million metres cubed per annum (DWAF, 2005).

1 The Department of Water Affairs and Forestry has since dropped the ‘Forestry’ section, but is still often cited as ‘DWAF’.

Approximately 75 percent of the total surface runoff from this Water Management Area flows down the Crocodile River (to which the Roodeplaat Catchment Area contributes). The remaining 25 percent is contributed by the Marico Catchment (20 percent) and the Upper Molopo Catchment (five percent). Rand Water, in conjunction with Magalies Water and Botshelo Water constitute the three water boards that supply water for the Crocodile Marico Water Management Area (DWAF, 2005).

According to the North West Provincial Government (2008) the water resources of the Crocodile West Marico Water Management Area support major economic activities within the Water Management Area, including a population of approximately 6, 7 million people (DWAF, 2005). As noted by DWAF (2005) more than half of the total water utilised in the Water Management Area comprises of urban, industrial and mining operations with approximately one-third utilised for irrigational purposes. The remainder of the water requirements are used for rural water supplies and power generation (DWAF, 2005). As stated by the North West Provincial Government (2008, p.3) “this area has the largest proportionate contribution to the national economy, generating almost a third of the Country’s Gross Domestic Product”

Figure 4: Overview of the Crocodile (West) Marico water management area (DWAF, 2005, p.10).

As can be seen in Figure 4, the Roodeplaat Dam is located in the south eastern portion of the Crocodile Marico Water Management Area and constitutes one of the major dams within the Apies/Pienaars sub-management area. Roodeplaat Dam (Reservoir) is a hypertrophic impoundment located approximately 20 kilometres north-east of Pretoria (Lee & Jones-Lee, 1984). Much controversy exists between the name of Pretoria within the Greater Metropolitan Area of Tshwane Municipality. For the purpose of this study, particularly to accommodate and integrate existing applicable scientific literature, “Pretoria” means the central city and larger urban area surrounding it. The Roodeplaat Dam was constructed in 1959. The dam was originally designed for irrigational purposes and later became an important recreational site. In recent years it serves as an important source for Magalies Water, which represents a state-owned water board that currently supplies potable water to a large area north of Pretoria.

4.1 Location, Boundaries and Size The study area is located in the Gauteng province as indicated in Figure 5. The Roodeplaat impoundment is situated approximately 24 kilometres north east of Pretoria. The reservoir has a net capacity of 41,9 × 10 6 m³ and covers an area of 396 hectares at full capacity, with a mean depth of 10,6 metres and a maximum depth of 43 metres (Steyn et al., 1976; Pieterse & Toerien, 1978).

Figure 5: Location of the study area within the Gauteng Province, South Africa (Adapted from Statistics South Africa, 2004).

The Roodeplaat catchment area extends over a region of 668 km² and is situated in an area of summer rainfall. According to Van Ginkel et al. (2007) approximately 29,4 % of the catchment area consists of urban development with 8,7% and 61,5% comprising of agricultural land and natural veld, respectively. The site is located within Sour Mixed Bushveld (Acocks, 1988) and Mixed Bushveld veld type (Low & Rebelo, 1996) which compromises part of the Savanna Biome.

According to Barnard (2000) the Roodeplaat Dam is located over three geological units. The first geological unit is located on the eastern and south eastern portion of the dam, which is underlain by the Rayton Formation of the Pretoria Group within the Transvaal Supergroup. The Lithology of this site is dominated by shale and quartzite. The second geological unit is located in the western section of the, which is underlain by the Rashoop Granophrye Suit of the Bushveld Complex. The lithology in this case is comprised of granodiorite. The last geological unit encompasses the northern section of the dam, which is underlain by the Pienaars River Complex. The subsequent lithology consists of foyaite, syenite and carbonatite (Barnard, 2000).

Figure 6: Locality of Study Site (DWA, 2007, p.7).

There are three river systems within the Roodeplaat Catchment area that contribute to the water flow of the impoundment. The Pienaars River represents the largest contributor to inflow, which drains the central part of the catchment (see Figure 7) and receives runoff from the Mamelodi Township as well as biologically treated sewage effluent from the Baviaanspoort sewage works (Bosman & Kempster, 1985; Pieterse & Rohrbeck, 1990). As seen in Figure 7, the Edendale Spruit which is situated to the east of the impoundment, drains agricultural land and grassland. The Moreleta/Hartebees Spruit system originates in an urban area of Pretoria and drains the suburban west part of the catchment, which bypasses an industrial area (Silverton). The area drained by each river system is 357 km², 161 km² and 129 km² for the Pienaars River, Hartebees Spruit and Edendale Spruit respectively (Bosman & Kempster, 1985). Another important inflow system into the Roodeplaat Dam to note includes the Zeekoegat Water Care Works, which was constructed and commissioned in 1991.

Figure 7: Map of the Three Sub-Catchment Regions within the Roodeplaat Dam Catchment Area (Adapted from Verheul, 2010, p.16).

The Roodeplaat impoundment is located within the Nokengtsa Taemane Local Municipality within the Metsweding District Municipality. The dam is also situated within the Gauteng Provincial Government Initiative, known as Dinokeng.

As noted by Gauteng Provincial Government (2007) such initiatives were established to highlight prime tourist destinations. Initiatives of such nature primarily focus on natural, cultural and historical attractions that are situated within the vicinity of Johannesburg and Pretoria. Various land-users surround the dam. This includes private corporations, government institutions as well as private land owners. The site is particularly attractive for a variety of aquatic sports such as canoeing, rowing and fishing amongst a variety of water sports.

4.2 The Main Land-Use Activities in the Roodeplaat Dam Catchment Area that Impact on Water Quality

As shown in Figure 8, land-use activities in the Roodeplaat catchment area have well been recognised as the primary influential factor contributing to the poor water quality exhibited in the Roodeplaat Dam. Such land-use activities reveal point-source locations, whereby the addition of phosphorus and nitrogen loads, including a variety of organic and inorganic dissolved constituents have not only contributed to the eutrophic level of this impoundment, but also its overall declining water quality status. It is also important to acknowledge non- point sources of water pollution that reach the impoundment and contribute to the declining status of the Roodeplaat Dam. As noted by Bosman & Kempster (1985, p.157) “ the water quality of the urban run-off is influenced not only by pollution occurring within the catchment, but also by the quality of water received across the catchment divide, as the major domestic source of water is obtained from the Vaal System”.

In the following section, the main land-use activities along each of the three river systems will be examined as well as and how such land-use activities contribute to the status of water quality that is received to the Roodeplaat impoundment.

Figure 8: Land-use Activities within the Roodeplaat Catchment Area (DWAF, 1998, p. 3).

4.2.1 Land-Use Activities along the Pienaars River

The Pienaars River drains the region north from Pretoria to the Waterberg Mountains near the town of Bela-Bela. This northerly flowing river system is also supplemented by water that is imported from the southerly situated Vaal River system to the Northern suburbs of Johannesburg, North of the Sub-Continental East-West striking drainage divide of the Witwatersrand. This water is mainly used for domestic and industrial water supplies prior to treatment and discharge (DWAF, 2005). The Pienaars River joins the Crocodile River just below the confluence of the Crocodile River and Elands River (DWAF, 2005).

As can be seen in Figure 8, there are a variety of land-use activities located on the banks of the Pienaars River. The Pienaars River flows in a northerly direction towards the Roodeplaat Dam. In the south of the Roodeplaat catchment area, the Pienaars River bypasses dryland and grassland area. However, further downstream, the amount and extent of anthropogenic land- use activities increases significantly towards the entry of the impoundment. There are two dominant land-use activities which affect the inflow of water to the Roodeplaat Dam. This is portrayed in Figure 8, whereby the Pienaars River flows directly through a large township area, known as the Mamelodi Township. The second includes the Baviaanspoort wastewater works located north of the Mamelodi Township.

According to Orton (2009) Mamelodi Township was founded in 1945, when the Pretoria City Council bought out portions of the Vlakfontein farm for the purpose of establishing a black township. Today Mamelodi represents an extensive area that is isolated from the Pretoria CBD. The township encompasses mainly low quality housing, coupled with informal settlement. Approximately one in every four households within the township does not possess piped water connections. This, in combination with poor refuse removal and ineffective ablution facilities, contributes to the increased annual loading of inorganic and organic constituents that enter the Pienaars River (Orton, 2009).

Flow from this river is also supplemented by significant discharges from treated domestic and industrial effluent. The Pienaars River receives treated sewage effluent from the Baviaanspoort wastewater treatment works. As seen in Figure 8, the Baviaanspoort treatment facility is located approximately 10 kilometres upstream of the Roodeplaat Dam on the eastern bank of the Pienaars River. The Baviaanspoort treatment works is designed and operated as a biological nutrient removal activated sludge plant (Esterhuyse and Bohmer, -1 2002) and has a 30 Ml .day capacity. This land-use activity is regarded as the principal nutrient source (phosphates) of the Roodeplaat impoundment (Pieterse & Toerien, 1978). The Baviaanspoort water care facility has also been subject to operational issues and subsequent breakdowns as a result of lack of maintenance and upgrading. This has lead to recurring incidents of untreated effluent that reaches the Roodeplaat Dam. According to DWAF (1998) data from a 1992 and 1995 report indicated that the Baviaanspoort and Zeekoegat sewage works contributed more than two thirds of the phosphorous load to the reservoir. Increased phosphate loads to the Roodeplaat Dam have been identified as the primary cause of extensive cyanobacterial blooms that covers most of the surface water as well as its hypertrophic status. The extensive eutrophication problem that is found within the Roodeplaat Dam will be discussed in section 8.

4.2.2 Land-Use Activities along the Edendale Spruit

As seen in Figure 8, the Edendale Spruit is situated to the east of the Roodeplaat impoundment. The Edendale Spruit runs through predominantly agricultural and grasslands, which constitute the main land-use activities that dominate this region. Agricultural activities along the Edendale Spruit include dryland cropping as well as a number of plantations located further north towards the inlet of the Roodeplaat Dam. As shown in Figure 8, woodlands dominate the northern region, upstream of the Edendale Spruit. Further downstream, the region comprises of grasslands. Nutrient enrichment of the Edendale Spruit through the use of fertilisers as well as the presence of plantations and livestock facilities, contributes towards the water quality of the Edendale Spruit (Swanepoel, 1997). Nutrient enrichment and the associated affects will be discussed in further detail in chapter 5.

4.2.3 Land-Use Activities along the Moreleta/ Hartebees Spruit

The Morelettaspruit/Hartebees Spruit system originates in an urban area of Pretoria and drains the suburban west part of the catchment, which bypasses an industrial area (Silverton). This area is characterised by the high concentration of urbanisation and continued expansion of Pretoria towards the east. According to Eco Assessments (2004) the increased scale of development in the upper catchment has contributed towards an increased runoff of storm water and consequently longer periods of water in the stream channel. As can be seen in Figure 8, the Hartebees Spruit also runs along the outskirts of the Mamelodi Township. Before reaching the inlet of the Roodeplaat Dam, the Hartebees Spruit also runs through an area of mixed agricultural land. Nutrient enrichment through surface runoff from the use of fertilisers and livestock feeds is also noted (Swanepoel, 1997). According to DWAF (1998) there is a piggery which is located further up the Hartebees Spruit, towards the inlet of the impoundment. It is therefore observed that a variety of land-use activities are at play which contributes towards the present water status of the Roodeplaat Reserve.

4.2.4 Land-Uses Changes in the Roodeplaat Catchment Area.

Figure 9 displays how land-use has changed in the study area over the past 12 years. In 1997, Swanepoel undertook a study to map the land-use activities that occur within the Roodeplaat Catchment Area. As seen in Figure 9 at ‘Current Land-Uses’, it is clear how the landscape has altered since then.

Region 1 constitutes the Hartebees Spruit sub-catchment. As seen from Figure 9, there has been a substantial increase of residential land-use activities that have spread southwards of the sub-catchment. Industrial land-use activities have also made a noteworthy increase over the past 12 years. It is also of importance to note how the sub-catchment is almost completely dominated by anthropogenic land-use activities with very little natural vegetation left.

Figure 9: Changes in Land-Use Activities from 1997 to 2010 (Adapted from Verheul, 2010, p 39).

Region 2 includes the Pienaars sub-catchment. The natural vegetation has substantially diminished upstream towards the dam inlet. Residential land-use has increased towards the west of the catchment. It can also be seen in Figure 9 that there has been expansion of industrial land-use activities into the Pienaars sub-catchment. Where natural vegetation dominated the south of the Pienaars sub-catchment, the area is now covered by agricultural small holdings.

Region 3 is identified as the Edendale Spruit sub-catchment. Previously, this area was regarded as having the smallest disruption of human land-use activities. This region was originally dominated by natural grasslands and vegetation. The amount of human induced invasion of land-use activities has severely altered the landscape of the study area. Residential land-use from the Pienaars sub-catchment (Mamelodi Township) has expanded into Region 3 considerably in the past 12 years. There has also been a commencement of industrial land-use activity right next to this expansion of residential area. From the land-use activities portrayed by Swanepoel in 1997, it is apparent how natural vegetation dominates the Edendale Spruit sub-catchment. The current situation displays a very different scenario. Natural landscape has given way to a significant increase in residential and small agricultural land-use activities. Only a narrow strip of natural vegetation is left. Region 4 includes the Roodeplaat dam and the Roodeplaat Nature Reserve. As can be seen in Figure 9, there has been a compromise of Roodeplaat Nature Reserve for small agricultural holdings.

5. WATER QUALITY AND WATER QUALITY CONSTITUENTS IN THE ROODEPLAAT DAM CATCHMENT AREA (2000-2009)

As noted by Taylor et al. (2007, p. 455) “Together with the increased demand on use of South Africa’s water resources, comes the eventual return of effluent water...to rivers, streams and impoundments”. Such returns, as seen from Baviaanspoort waterworks on the Pienaars River, in conjunction with diffuse charges (runoff from industry, agriculture and rural settlements) may alter the natural state of the receiving water body through addition of suspended solids as well as organic and chemical compounds. Such additions result in changes in nutrient status, turbidity and an overall alteration to the aquatic communities and eco-systems health of the water body, as in the case of the Roodeplaat Dam (Taylor et al., 2007).

According to the DWAF (1996c) the term water quality is used to delineate the physical, chemical, biological and aesthetic properties of water as to determine its fitness for a variety of uses which include domestic, recreational and aquatic eco-system use. The criteria used to quantify the fitness of water for each use will differ according to framework and guidelines established by the DWAF (e.g. SANS 241 drinking specifications of water). As noted by the DWAF (1996c) such guidelines are scientific and technical information which are provided for a particular water quality constituent.

For the purpose of this study, certain water quality constituents have been selected in accordance with the surrounding land-use activities to best evaluate the overall water quality of inflow to the Roodeplaat Dam. Changes in these water quality constituents impact on three main sectors of water usage, namely: domestic use, recreational use and the compromise to aquatic eco-system health. It is seldom possible to mitigate the effects of poor water quality to the same degree for domestic, recreational and aquatic eco-systems. As stated by the DWAF (1996c, p.9) “It is often possible to abstract and treat water of poor quality before it is used off-stream, but in the case of aquatic ecosystems it is seldom possible to mitigate the effects of poor water quality to the same degree”. Therefore prevention rather than mitigation of the effects of poor water quality should be given greater emphasis for aquatic ecosystems then would be the case for other water uses (DWAF, 1996c).

Poor water quality in this area is not only limited to effects on aquatic community structures and human health. As noted by the DWAF (2007) the Roodeplaat Dam is used for a variety of recreational activities. Rowing SA and Swimming SA utilise the dam for training purposes and international competitions. The impoundment is also used for a variety of water sports such as motorised boating and skiing. The effects of body contact in such cases to chemical and microbial constituents shall also be discussed in the following sections.

5.1 Physical Constituents In the following section, the two physical constituents that have been selected for the study will be discussed. 5.1.1 pH As described by the DWAF (1996c) pH is the value used to measure the concentration of hydrogen ion activity in a water sample. The equilibrium between H+ (alkalinity) and OH¯ (acidity) is influenced by reactions introduced into the aquatic ecosystem. Industrial activities, such as those located on the Moreletta/Hartebees Spruit, result in acidification of rivers and reservoirs. Acid mine drainage from the Silverton area may lead to the pH of receiving streams to drop below 2. pH may also vary diurnally and seasonally. In relation to diurnal fluctuations, rapid rates of photosynthesis (natural or due to eutrophication) result in high pH values. Seasonal variability is related to the hydrological cycle, whereby concentrations of organic acids are steadily lower during the rainy season. Ammonium ions are non toxic chemical compositions which constitute the main form in which nitrogen is assimilated by aquatic plants. However, at a higher pH (> 8), ammonium ions are converted

to highly toxic un-ionised ammonia (NH3). Gradual reductions in pH may also change the aquatic community structure, whereby acid tolerating organisms replace those that are less tolerant (DWAF, 1996c).

5.1.2 Dissolved Major Solids (DMS)

“Dissolved Major Solids is a measure of the quantity of all compounds in dissolved water” (DWAF, 1996c, p.108). DMS is directly proportional to Electrical Conductivity (EC) which is used to measure the concentrations of DMS within a water body. Natural waters contain varying quantities of DMS according to the underlying geological formations which come in contact with water systems.

Changes in the concentration of DMS may affect aquatic organisms at three levels which include:  Effects on and adaptations to individual aquatic species.  Effects to aquatic community structures.  Effects on microbial and ecological processes, which include rates of metabolism and nutrient cycling (DWAF, 1996c).

At low concentrations, DMS has a positive nutritional value to humans. However, intake of high concentrations lead to a variety of disorders in humans such as laxative effects in common cases, to effects on kidney function in rare cases. Body contact with water of high DMS concentrations may also give rise to excessive skin dryness and discomfort (DWAF, 1996a).

5.2 Chemical Constituents

5.2.1 Inorganic Nitrogen As noted by Manassaram et al. (2006) nitrate occurs naturally in soil containing nitrogen- fixing bacteria, decaying plants and animal manure. Other sources of nitrate include fertilisers used in agricultural activities (on the Edendale Spruit) as well as from human and animal waste discharged from sewage systems and livestock facilities (De Roos et al., 2003; Manassaram et al., 2006).

Inorganic nitrogen includes all major inorganic nitrogen components (NH4; NO2; NO3).

Ammonia (NH3) is a reduced form of inorganic nitrogen which exist as both dissolved ions or may be absorbed onto suspended material. As noted by the DWAF (1996c) inorganic nitrogen is primarily of concern as a result of its stimulatory effects on aquatic plant growth and algae to trigger the process of eutrophication within a water body. The active uptake of nitrates by algae and higher plants are directly affected by temperature, oxygen availability and the pH of the water body. Changes in the trophic status, in addition to growth of algae are used to assess the effects of nitrogen on aquatic eco-systems. The primary affect of increased nitrogen to an aquatic ecosystem includes the unrestricted growth of blue-green algae in the form of eutrophication.

The availability of phosphorus into the system is also of great importance, as phosphorus may modify the influence of inorganic nitrogen concentrations in the water body by fixing atmospheric nitrogen as compensation (DWAF, 1996c).

Table 2: Trophic status as an indicator to assess the effects of inorganic nitrogen to an aquatic ecosystem (DWAF, 1996c, p.84).

As can be seen in Table 2, the concentrations of average summer inorganic nitrogen concentrations determine the trophic status of a water body and the associated effects. The Roodeplaat Dam is classified as a hypertrophic impoundment. From Table 2 it is evident that hypertrophic conditions typify low levels of species diversity in conjunction with high growth of blue-green algae blooms of which certain species are toxic to man. Eutrophication shall be discussed in further detail in the following section.

An increased intake of NO2 in humans, particularly in infants, results in a condition known as methemoglobinemia. In such circumstances, nitrites combine with the oxygen carrying red blood pigment (haemoglobin), making it incapable of carrying oxygen through the body. Infants under three months are specifically at risk for this condition, which is commonly known as blue baby syndrome (Prakasa Rao & Puttanna, 2006).

According to Prakasa Rao & Puttanna (2006) NO2 in drinking water is associated with an array of health problems which include methemoglobinemia, cancer of the colon, rectum and other gastrointestinal cancers, vascular dementia as well as secretive functional disorders of the intestinal mucosa to name a few.

5.2.2 Phosphates (PO4) Phosphorus is considered to be the defining nutrient controlling the degree of eutrophication within an aquatic ecosystem (Twinch, 1986; Wiechers & Heynike, 1986; van Ginkel, 2002). Various forms of phosphorus in a water body are continually changing due to processes of decomposition and synthesis between organically bound forms and oxidising inorganic forms. The primary effect of phosphate loading to a water body includes increased stimulation of growth to aquatic plants. As previously mentioned, nitrogen loading has the same effect as with phosphorus in this case. However, phosphorus loading is acknowledged as the greater contributor to the process of eutrophication.

Elevated levels of phosphorus may occur from point-sources such as industrial and domestic effluents (Baviaanspoort and Zeekoegat wastewater works), as well as non-point sources, where by the increased phosphorus load is generated from surface and subsurface drainage. Non-point sources include urban runoff, atmospheric precipitation and particularly agricultural land where fertilisers have been used (along the Edendale Spruit) (DWAF 1996c).

Eutrophication refers to the enrichment of a water body with plant nutrients (particularly nitrates and phosphorus) which results in the overdevelopment of plant biomass, most commonly blue-green algae (Cyanobacterial blooms). As noted by Harding (2010, p.1) “ the process of nutrient enrichment towards problem (elevated) trophic states is slow and insidious, with problems often only becoming apparent a considerable time after onset of pollution”. Conservatively, approximately 35% of South Africa’s impounded water resources are seriously altered (eutrophic to hypertrophic) with a further 20 to 30% which are incipiently problematical (Harding, 2010).

As previously stated, the Roodeplaat impoundment is classified as a hypertrophic water body. This includes excessive levels of nutrient enrichment, whereby plant production is governed by physical factors and water quality problems are continuous (Walmsley, 2000).

Figure 10: Roodeplaat Dam in December 2008 (Craig, 2009, p.8).

Figure 11: Roodeplaat Dam in January 2009 (Craig, 2009, p.7).

As stated by Harding (2010) in most cases, and particularly for inland areas, the pollution contamination problems are point-source discharges of wastewater effluents. The two main point sources contributing to the phosphate load in the Roodeplaat Dam includes the Baviaanspoort and Zeekoegat wastewater works. As noted by DWAF (1998) there are also significant occurrences of toxic blue-green algae present in the Hartebees Spruit/ Morelettaspruit which indicate a nutrient source in this tributary of the reservoir. Non-point sources of phosphate include irrigated agricultural land-use activities (along the Edendale Spruit) or an informal settlement (Mamelodi Township).

According to an assessment done by DWAF (1998) the Biviaanspoort and Zeekoegat wastewater care works jointly contributed more than two thirds of the phosphorus load to the reservoir, with non-point sources contributing approximately 30% of the phosphate load. Therefore, phosphate loading to the Roodeplaat impoundment is dominated by point source pollution, which, according to the DWAF (1998), is likely to become increasingly more significant. According to van Ginkel (2002) the trophic status of the Roodeplaat Dam warrants the allocation of it as the top ten highest priority impoundments in relation to eutrophication management within South Africa. Van Ginkel (2002) further states that the impoundments that fall within the first 10 on the ranking list should be considered serious eutrophication and health hazards.

Eutrophication within the Roodeplaat impoundment presents an array of problems to the ecological functioning of the reservoir. This includes increased occurrence and intensity of algal blooms and toxic algae as seen in Figure 10 and 11. According to de Villiers & Thiart (2007) the most dramatic ramification of eutrophication in freshwater systems includes extensive kills of both invertebrates and fishes due to oxygen depletion related to the decomposition of excess organic matter produced. This is depicted in Figure 12. Toxin production by certain cyanobacterial blooms (e.g. Cylindrospermopsis, Microcystis aeruginosa) lead to a wide array of biological and human-health impacts (Havens, 2006). From an economical point of view, eutrophication is also associated with increased water treatment costs due to filter clogging in wastewater treatment plants, interference in recreational activities and loss of property values along the dam (Walmsley, 2000).

Figure 12: Fish deaths as a result of toxic cyanobacterial blooms (van Vuuren, 2008, p.15).

5.2.3 Sulphates (SO4) Sulphate constitutes the oxy-anion of sulphur in the +VI oxidation state, which forms salts with various cations such as magnesium, barium, lead, potassium, sodium and calcium. As noted by DWAF (1996a) sulphate is a common constituent of water which originates from the dissolution of mineral sulphates in rock and soils. Anthropogenic sources include discharge from acid mine wastes and other industrial processes which include textile mills, tanneries and processes using sulphuric acid.

According to DWAF (1996a) high concentrations of sulphate intake may result in diarrhoea. However, such effects are generally temporary and reversible as sulphate is rapidly excreted in the urine. From an aesthetic stand-point, sulphate imparts a bitter or salty taste when consumed.

5.2.4 Magnesium Magnesium is an alkaline earth metal which reacts with water and oxygen to form magnesium oxide and magnesium hydroxide. As stated by the DWAF (1996a) magnesium is responsible for the hardness of water. Solubility of magnesium is directly correlated to pH levels. Magnesium hydroxide is relatively soluble at pH 7; however, gradually becomes less soluble with an increase in pH.

From an aesthetic point of view, magnesium is bitter in taste which acts as a natural defence against the ingestion of harmful concentrations. As seen in Table 3, an excess of magnesium intake, particularly as a sulphate, will result in diarrhoea and scaling problems in plumbing works and heating elements.

Table 3: Aesthetic and Health Effects of Increased Magnesium Consumption (DWAF, 1996a, p. 99).

5.3 Microbial Constituents A wide range of pathogenic viruses, bacteria and protozoa are transmitted by water. When ingested orally, such pathogens can cause diseases such as gastroenteritis, hepatitis, typhoid fever, cholera, salmonellosis as well as a variety of ear, eye, nose and skin infections. Faecal pollution which carries such pathogens originate from excretory waste from humans and warm blooded animals, such as dogs, cats, poultry and rodents. Faecal matter finds its way into water systems through unsanitary practices, particularly in rural areas where many people do not have access to sanitary facilities and raw sewage is discharged into freshwater systems. Faecal matter is also found in sewage-polluted water and at sewage works, such as the Baviaanspoort (located on the Pienaars River). According to DWAF (1996a) there are a variety of physical, chemical and biological elements that play a role in the survival and removal of micro-organisms in a water body. Such factors include temperature, exposure to sunlight, pH, turbidity and nutrients. In some circumstances, micro-organisms may multiply in waters with suitable temperatures and sufficient nutrients.

5.3.1 E-Coli Escherichia coli (E-coli) is a highly specific indicator of faecal pollution which originates from the excretions of humans and warm-blooded animals. Therefore, the presence of E-coli is used to indicate the presence of pathogenic microorganisms in the form of faecal pollution (Boutilier et al., 2009). As previously mentioned, faecal pollution has significant effects to aquatic organisms and humans alike. Diseases such as gastroenteritis, salmonellosis, cholera and typhoid fever are associated with the consumption of faecal-polluted water which may result in death (particularly in infants). As noted by DWAF (1996a), the risk of infection correlates with the level of contamination to the water body and the amount of water consumed by an individual. Higher concentrations of faecal coliforms indicate a higher risk of contracting waterborne pathogens, even when small amount of water are consumed.

Sources of Faecal Coliforms within the Roodeplaat catchment arise from a number of land- use activities along the River inflows to the Roodeplaat Dam. These include faecal contamination from human and non-human faecal sources (Field & Samadpour, 2007). Human sources include the Baviaanspoort and Zeekoegat Sewage Works and rural settlements (Mamelodi Township) located on the Pienaars River, whilst non-human sources comprise of commercial agricultural activities such as piggery farms, located on the Hartebees Spruit/Moreleta Spruit. Mismanagement and discharge of untreated effluent by such surrounding land-use activities may have deleterious effects on the concentration of faecal contamination in the area. Inter-related problems, as with the case of eutrophication and unrestricted growth of algal blooms in the Roodeplaat impoundment clogs the filters at the Biviaanspoort treatment works, which results in more frequent of breakdowns and consequently, recurring incidents of untreated faecal pollution entering the reservoir (DWA, 2007).

The effectiveness of the Baviaanspoort and Zeekoegat wastewater treatment plants will also play a significant role with regards to the abundance of faecal coliforms that enter the Roodeplaat Dam. According to Momba and Sibewu (2009) uncontrolled sewage discharges in association with poorly managed wastewater treatment plants have been identified as the two major sources of water pollution in South Africa. The Zeekoegat and Baviaanspoort wastewater treatment plants are two of several plants that serve the City of Tshwane Metropolitan Municipality. Both plants drain into the Roodeplaat Reservoir.

Both plants use aeration and dispersion of liquid chlorine as its main source of disinfection (Momba & Sibewu, 2009). However, the main difference in design between Zeekoegat and Baviaanspoort lays in the design. Baviaanspoort is characterised by the lack of a division tank, the presence of a mechanical aeration system in the two biological reactors as well as a lack of sand filtration system for the final treated effluent.

In a study conducted by Dungeni & Momba (2010) the abundance of two pathogens, namely Cryptosporidium and Giardia spp. were tested in both the Zeekoegat and Biviaanspoort wastewater works. These pathogens are particularly dangerous as they can withstand normal disinfection processes (Dungeni & Momba 2010; Obi et al, 2008). Even after the treatment of influents, the cysts produced by the pathogens were still found in considerable concentrations in the final effluents of the Baviaanspoort. Zeekoegat was identified as having the highest removal of Giardia and Cryptosporidium (98.36% and 99.96% respectively). This was attributed to the rapid sand filtration process used for the final treated effluent, which aided in the physical removal of protozoan parasites from the water (Dungeni & Momba, 2010).

Other inter-related problems occurring at the Roodeplaat Dam may also effect the concentration of microbial coliforms present in the Impoundment. This includes processes of sedimentation, which is evident at the inlets of the dam as a result of activities upstream in the rivers (DWAF, 2007). According to a study conducted by Characklis et al. (2005) bacteria that attached to solid particles, in particular those dense, inorganic particles will settle out of the water column more rapid than those in free from. Microbial coliforms were also observed to survive longer within sediments than within the water column (Characklis et al., 2005). This was confirmed by Sinclair et al. (2009), whereby the loading of microbial contaminants was examined within the Thomas Brook Rural Watershed (Canada). From the study, it was found that processes of sediment transport and bacterial transport were linked as sediments constitute an important mode of transport for microbial constituents.

As stated previously, Roodeplaat Dam is a significant location in relation to recreational water activities. Body-contact recreational activities, such as swimming, water skiing and rowing increases exposure to faecal contamination and likelihood of adverse health outcomes which include gastrointestinal symptoms, eye infections, skin irritations, ear nose and throat infections and respiratory illnesses (Soller et al. 2010).

According to Anderson et al. (1998) the magnitude of effects of recreation on water quality remains poorly understood, however, swimming and other recreational activities whereby water is ingested are known to increase the risk of gastrointestinal illnesses.

Table 4: Effects of Faecal Coliforms in varying Concentrations to Human Health (DWAF, 1996a, p.79).

Roodeplaat Dam is a highly utilised impoundment for water sport activities. Ingestion of the smallest amount of E-coli may pose serious health effects when individuals come into contact with faecal polluted water. This is emphasised by an epidemiology study carried out by the United States Environmental Protection Agency (USEPA), which indicated that levels of E- coli in freshwater show a high correlation with occurrence of swimming related gastric illnesses (DWAF, 1996a).

6. DATA COLLECTION AND METHODOLOGY

6.1 Data collection and location of sample sites The Department of Water Affairs has collected and sampled water quality data within the study area for a number of years as part of their Water Quality Monitoring Programme for the Crocodile (West) and Marico Water Management Area. For the purpose of this study, four sampling points have been chosen from DWAF’s water quality monitoring sites that fall within the Roodeplaat catchment basin (as seen in Table 5). Water quality data at these four sampling points are collected on a fortnightly basis, returned to the lab and analysed by DWAF to provide a data.

The study will focus on water quality results obtained from DWAF at these four sampling sites, for the period of January 1999 to December 2009. Mean monthly averages for each water quality constituent at each sampling point will be derived from the raw data provided by DWAF.

Table 5: Naming of Sample Points operated by DWAF. Geographical Co- DWAF Sample Research Study Sample Description of Sample Point ordinates Points Points Latitude Longitude Pienaars River after A2H027 Sample Point (SP) 1 -25.6625 28.35139 Baviaanspoort Hartebees Spruit/Morelettaspruit A2H028 Sample Point (SP) 2 -25.6508 28.31944 Edendale Spruit A2H029 Sample Point (SP) 3 -25.6489 28.39194 Outlet of Roodeplaat at Dam A2R009 Sample Point (SP) 4 -25.622 28.373 Wall

Figure 13 and 14 depicts the location of sampling points within the demarcated study area. Figure 13 establishes the location of the study area and corresponding sampling points in relation to the Mamelodi Township and urbanised area of Pretoria. From Figure 13, it can be seen that the designated study area and location of sampling points are situated north-east of Pretoria and north of the Mamelodi Township. At a larger scale (Figure 14) the site of individual sampling points are highlighted. Sample Point (SP) 1 (A2H027) is located on the Pienaars River, upstream of the Baviaanspoort wastewater works. SP 2 (A2H028) is situated west of the demarcated study area, on the Hartebees Spruit.

SP3 (A2H029) is located on the Edendale Spruit, which is situated in the east of the study area. SP 4 (A2R009) is located towards the outlet of the Roodeplaat impoundment, on the dam wall.

Figure 13: Location of Sampling Points in Relation to Surrounding Land-use Activities (Adapted from DWAF, 2010, p.1).

Figure 14: Location of Sampling Points in Designated Study Area (Adapted from DWAF, 2010, p.1).

Rainfall data were also obtained from the South African Weather Service. Figure 15 highlights the location of the Baviaanspoort Water Care Works. An active weather station utilised by the South African Weather Service operates within the Baviaanspoort Water Care Works. Data from this station were provided by South Africa’s Weather Service and utilised in this study. The geographical co-ordinates of this weather station are noted in Figure 15. Total rainfall amounts for each month were recorded for the same time period of January 2000 to December 2009.

Figure 15: Location of Weather Station used in Study (Adapted from DWAF, 2010).

6.3 Shortcomings of Data The water quality data provided by DWAF contained multiple gaps and inconsistencies as a result of missing data for certain time periods or water quality parameters. The limited number of analysed variables by DWAF is also considered as a shortcoming in the database used for this study. Initially, the author wanted to include Electrical Conductivity (EC) in the research study. However, due to significant gaps in the data obtained, it was decided to omit this variable as results would not be scientifically justifiable. This was also the case for data obtained on E-coli at Sample Point 4.

For those cases where only a limited portion of the data was incomplete, completed the data set through interpolation of the data set. This is outlined in Figure 16. As can be seen in Figure 16, where values were absent in the table, existing data was graphed. A line was drawn to connect existing values. Interpolated values were read off the graph and thus the table completed.

Figure 16: Interpolation of Incomplete Data Sets.

It should also be noted that flow into the Roodeplaat impoundment is not solely dependent on rainfall alone. Water is added to the system through return flows from the Baviaanspoort and Zeekoegat wastewater works. However, for the purpose of the study, these aspects were not taken into consideration. This shortcoming may be regarded as a useful recommendation for future studies. By incorporating variations of rainfall and anthropogenic flows, better insight is gained as to how such variations of flows collectively affect water quality of the Roodeplaat Dam.

6.2 Analysis of Data Various chemical, physical and biological constituents of water quality were analysed. The data provided by DWAF were used to establish spatial and temporal variations for each water quality constituent at each of the four sampling points over a 10 year period time frame. Data provided by the South African Weather Service were also used to establish temporal variations in precipitation for the same time period in question.

Data from DWAF were converted to MS Excel format for statistical manipulation and analysis. A mean monthly average was derived for each parameter per locality. The data derived from the author’s statistical manipulation was then expressed graphically in the form of line graphs to visualise the spatial and temporal tendencies of each water quality parameter over the 10 year period.

Trends of specific constituents were also graphically compared at each locality to determine which sample sites had the highest concentrations of constituents over the time frame period. Water Quality Guidelines established by DWAF were also used to evaluate each constituent.

Data provided by the South African Weather Service were used to express temporal variations of precipitation in the form of line and bar graphs over the same time period under discussion. Graphs produced were then collated to those establishing the trend analyses of each water quality constituent to graphically express whether an association exists between rainfall and concentration of water quality constituents. Statistical analyses were also performed on the data set, through the use of Pearson’s and Spearman’s correlation analysis. Such manipulation was used to establish the strength of association between rainfall variation and concentration of water quality constituents.

According to the University of West England (2007) Pearson’s correlation is a measure of strength of a linear association between two variables. Such correlation analysis assumes that variables are normally distributed, where there is a linear relationship between the two data sets. In order to account for any ‘non-linear’ association between the variables, the author also performed Spearman’s Rank Correlation.

Using Spearman’s correlation, the author was able to transform non-parametric variables into linear ones by using the rank of the items rather than their actual values. Therefore, Spearman’s test does not depend on the assumption of an underlying bivariate normal distribution. Significance levels of 5% (1-tail) and 10 % (2-tail) were used for each analysis.

7. RAINFALL OF THE ROODEPLAAT DAM CATCHMENT AREA (2000-2009)

Figure 17 tracks rainfall values over the study period of 1999-2009. Rainfall data were collected by the South African Weather Service at the Baviaanspoort Water Care Works, which also constitutes as an active weather station.

Figure 17: Results of Rainfall Tracking Over the Study Area (2000-2009).

As seen from the Figure above, the Roodeplaat catchment area exhibits patterns of summer rainfall. Rainfall values are highest through the months of November- January. During the dry winter months (May- August), rainfall values are lowest. This pattern is continuous, with the exception of July 2002 and July 2007, which displayed uncharacteristic rainfall events during the dry, winter season. As seen in Figure 17, the months of September through to October, marks the onset of the wet season. It is also of interest to note that the two lowest values for the rainy season (A&B in Figure 17) occur previous to the two isolated events of increased rainfall values during the dry, winter months for 2002 and 2007. Summer rainfall values depicted at point A (October 2001 - April 2002) and B (October 2006 – April 2007) are therefore the lowest (<150# mm). The summer rainfall values exhibited in 2008 constitute the highest amount of rainfall received (>250#mm) during the study period. Excluding summer rainfall values exhibited in 2008, rainfall does not exceed 250#mm for the study area.

8. RESULTS AND DISCUSSION

8.1 Physical Constituents

8.1.1 pH Figure 18 depicts the pH at each sampling site. As can be seen from Figure 18, Sample Point (SP) 1 represents the lowest ranges of pH (between 7.4 and 8.2). pH at SP 1 is therefore not of concern, as ranges reflect recommended operational limits according to SANS 241: 2005 Drinking Water Specifications (DWAF, 2005). This is also the case for SP 2 and 3. Water at these locations are slightly more alkaline than SP 1, however, still fall within the recommended class 1 drinking specifications. Overall, pH within the Roodeplaat Catchment does not appear to be of concern as water exhibits neutrality to slightly alkaline dilutions.

Figure 18: Comparison of Sample Point concentrations of pH.

Figure 19 tracks rainfall and pH concentrations at SP 2. A clear seasonality of pH can be seen from Figure 19. This is justified through Pearson’s correlation, which detected an inverse relationship of -0.315 (correlation is significant at the 0.01 level). Spearman’s correlation exhibited a significant correlation of -0.438. Therefore, an increase in rainfall coincides with an increase in acidity. Alternatively, during the dry seasons (July-September) alkalinity at this SP increases. This may be a result of the increased dissolved mineral salts, which is also exhibited during the dry seasons. This will be discussed in further detail in Section 8.1.2.

Sample Point 1 did not appear to exhibit a distinct seasonality in pH (figure 18). No significant correlation was found in Pearson’s and Spearman’s correlation either (-0.076 & - 0.008 respectively). This may be the influence of Baviaanspoort, which regulates the pH of effluents. pH appears to be well under control at this sample point, with ranges between 7.4 and 8.2.

An increased input in dissolved salts into a system increases the alkalinity of water as a result thereof. This observation was also seen in the study which found a significant positive correlation between pH and DMS at SP 2 of 0.520. It is also of interest to note the significant positive relationship (0.413) between pH and SO4 at this site. Similar findings were also displayed at SP3, where there is an inverse relationship between rainfall and pH. This is justified through Spearmen’s correlation, which found a significant inverse relationship between rainfall and pH of -0.327

Figure 19: Results of pH and Rainfall Tracking at SP2.

As can be seen from Figure 18, pH is most alkaline at the Dam outlet of SP4. All nutrients and dissolved salts enter the dam from the study area’s catchment. There are also increased inputs of dissolved salts from Baviaanspoort and Zeekoegat waterworks as well as storm water runoff from land-use activities along the Hartebees Spruit. This may account for the increase alkalinity levels exhibited at this SP. It is also of interest to note how the relationship between rainfall and pH differs from SP 2 and 3 (as seen in Figure 20).

Figure 20: Results of pH and Rainfall Tracking at SP4.

Whilst a significant relationship between rainfall and pH is also found at this sampling point, the correlation reflects a positive relationship of 0.319 for Pearson’s and 0.466 for Spearman’s Correlation. Therefore, the alkalinity of the Sample Point increases with an increase in rainfall. This may occur as a result of the increased nutrients that are flushed away during the rainy season and subsequently enter the dam.

8.1.2 Dissolved Major Solids Dissolved Major Solids (DMS) concentrations were found to be highest at SP1, however all sample site concentrations were found to be within an acceptable limit, according to the SANS 241: Drinking Specifications (Class 1< 1000mg/l). There appeared to be an isolated event at SP, whereby DMS concentrations spiked to 1600 mg/l during May 2003. Overall for each sample site, DMS was found to be stabilised with little variance in concentration (typically below 500mg/l). According to the line graphs seen below, ranges of DMS tend to gravitate around 400mg/l for each sample site over the study time period. Therefore, from the study, DMS does not appear to be a constituent of concern.

From Figure 21, the inverse relationship between variation of rainfall and DMS concentrations is clearly notable. DMS concentrations at SP4 increase during the dry winter seasons. With an increase in rainfall for the wet season, concentrations of DMS decrease. This inverse relationship is also seen in Figure 22. The correlation displayed in Figure 21 and 22 are both validated by Table 6, which notes the correlation at each sample site.

Figure 21: Results of DMS and Rainfall Tracking at Sample Point 3.

Figure 22: Results of DMS and Rainfall Tracking at Sample Point 2.

As seen from Table 6, Pearson’s correlation shows a noteworthy inverse relationship of - 0.424 between rainfall and DMS. Spearman’s correlation displays an even greater correlation of -0.598. Therefore, as rainfall decreases at SP2, the concentration of DMS increases. As seen in Figure 22, this concentration ‘peak’ of DMS is highest during the study areas dry, winter months. When the Spring rains return, concentrations tend to decrease. As can be seen in Figure 22, there was a small peak of rainfall exhibited in July 2006. This peak coincided with a drop in DMS concentration. Thereafter DMS concentrations decreased throughout the duration of the rainy seasons to April 2007. Following on into 2007, there is an uncharacteristic, small peak of rainfall during the months of April – July and again a small amount of rainfall exhibited for the start of the spring rains. These ‘peaks’ in rainfall are correlated to dips in concentration levels of DMS and vice versa for the periods of low rainfall amounts.

Table 6: Correlation Co-efficient Values at all Four Sample Sites for DMS Concentrations

Similar findings of inverse correlations between rainfall and DMS are found at all four sample sites. As seen from Table 6, SP1 displays a noteworthy, inverse relationship between rainfall and DMS concentrations (-0.708) according to Spearman’s correlation. It is also noteworthy to consider the correlation exhibited between DMS and SO4 as well as DMS and E-coli. From Table 6, it appears that there is a highly positive correlation between DMS and

SO4. Therefore, an increase in DMS concentrations correlates to an increase in SO4 at all four sample sites. With regards to E-coli, a significant inverse relationship is apparent, particularly at SP2 (-0.568) for Spearman’s correlation. Thus, as DMS concentrations increase within the system, E-coli concentrations decrease. This notion shall be discussed in further detail in Section 8.3.

8.2 Chemical Constituents

8.2.1 Inorganic Nitrogen

Figure 23 compares Nitrate (NH4) concentrations across all four Sample Points (SP). As can

be seen from Figure 23, NH4 concentrations are substantially higher at SP1 than any other Sample Point. This is directly related to the effluent outputs discharged from the

Baviaanspoort wastewater works. SP4 represents the second highest concentration of NH4.

Concentrations at SP2 and SP3 are relatively low, apart from the isolated NH4 peak events seen at SP3.

Figure 23: Comparison of NH4 Concentrations at each of the Study Sample Points.

Table 7 indicates DWAF’s Water Quality Guidelines for nitrates. According to these

guidelines for domestic use, NH4 levels amongst all sample points comply with the <6.0 mg/l parameter, apart from two isolated events for SP1 in September- October 2004 and June

2007. This is affirmed in Table 8, where all NH4 concentrations at each sample point fall within the recommended Class I of SANS 241 Drinking Specifications, apart from the two isolated events seen at SP1. Table 9 indicates the In-stream Water Quality Guidelines used for the Vaal Barrage in relation to nitrate concentrations. According to these specifications, nitrate concentrations at the study location range from ideal to tolerable, with the two ‘spikes’ of NH4 seen at SP1 classified as unacceptable (> 6mg/l).

Table 7: DWAF Water Quality Guidelines for Nitrates (Adapted from DWAF, 1996). DWAF Water Quality Guidelines

Domestic Use < 6 mg/l

Recreational Use No Guideline Given

Aquatic Ecosystems < 0,5 mg/l

Table 8: SANS 241: 2005 Drinking Water Specifications (DWAF, 2005) SANS 241: 2005 Drinking Water Specifications

Class II

Determinand Unit Class I Class II Water consumption period, max.

Nitrate & Mg/l <10 10 ‐ 20 7 years Nitrite as (N)

Table 9: Vaal Barrage In-Stream Reservoir Guidelines for Nitrates (Rand Water, 2006). Vaal Barrage Reservoir In‐Stream Guidelines

Ideal Acceptable Tolerable Unacceptable

<0,5 (mg/l) 0.5‐3.0 (mg/l) 3.0‐6.0 (mg/l) > 6.0 (mg/l)

Figure 24 shows the trend of NH4 concentrations and rainfall over the study time period.

From the line graph of SP1, there is no evident correlation observed between NH4 concentrations and rainfall. This is confirmed through correlation analysis, which did not detect any significant correlation between the two variables (r =-0.047; rs= -0.60). This may

be the influence of Baviaanspoort, which distorts any natural correlation of NH4 and Rainfall through the release of treated effluents. Such additional inputs thus play a significant role in

the concentration of NH4 at SP1. There are two noteworthy events where NH4 concentrations increase substantially. As can be seen in Figure 24, peak concentration ‘spikes’ were exhibited in September-October 2004 and June 2005. These dates may coincide with operational failures or breakdowns that occurred at the Baviaanspoort sewage works. The

significant increase of NH4 concentrations coincide with a Report published by DWAF in October 2004 regarding fish kills observed in the Roodeplaat Dam.

A series of investigations found alarmingly high concentrations of certain water quality constituents, notably, unionised ammonia (NH3-N) and dissolved Zinc (Zn). From the report it was stated that “there had been problems with the discharge from the Baviaanspoort Water Care Works for the week or so prior to the fish killing taking place”. This event is clearly visible in Figure 24. Concentrations at SP1 also depict ‘spikes’, which translates to a high

amount of instability within NH4 concentrations at SP1.

Figure 24: Inorganic Nitrogen and Rainfall Tracking at Sample Point 1.

Figure 25 indicates the concentration of Rainfall and NH4 concentrations seen at SP2. Whilst Pearson and Spearman’s correlation establish that a relationship does exist between the two variables, the correlation is not as clear in Figure 24. This is justified through the level of significance rendered by Pearson’s and Spearman’s correlation. This included a weak, inverse correlation of -0.192 and -0.221 respectively. Again, these results may occur from a number of factors at play, which affect the concentrations of NH4 at SP2. This may include elements of storm water drainage or the quality of runoff from the urbanised area. It is also of

interest to note that strong, positive correlation that exists between NH4 and PO4 at this SP. According to Pearson’s and Spearman’s correlation, a correlation of 0.514 and 0.429 was identified respectively. Concentrations of NH4 do not appear to be of concern at this sample site.

Figure 25: Results of Inorganic Nitrogen and Rainfall Tracking at Sample Point 2.

Results of a significant relationship between NH4 concentration and rainfall were also not clear at SP3. However, as with the case of SP2, a positive relationship was exhibited between

NH4 and PO4. A 0.337 and 0.416 correlation co-efficient was found between the variables for Pearson’s and Spearman’s correlation, respectively.

This positive relationship identified between NH4 and PO4 has deleterious implications to the eutrophication process that is persisting in the Roodeplaat impoundment. Therefore, with an

increase in NH4 concentrations, there is a significant increase in PO4. These are the primary nutrients which influence the rate of algal growth and contribute towards the impoundments eutrophic status. Therefore, it is noteworthy to understand how these nutrients react. Significant correlations of this nature were also found at SP4; with a correlation of 0.199 for

Spearman’s analysis. An inverse relationship of -0.195 was also found between NH4 concentrations and rainfall at SP4.

8.2.2 Phosphates

Figure 26 depicts the comparison in concentrations of PO4 at each Sample Point.

Concentrations of PO4 are distinctly higher at SP 1 than any other Sample Point.

Concentrations of PO4 are lowest at SP2. It is also noteworthy to highlight the low concentrations found at SP3. SP3 is located in an area dominated by agricultural activities

and grasslands. Conventional notions would predict an elevated amount of PO4 concentrations. However, this is not the case at SP3. In fact, according to Rand Waters In- Stream Water Quality Guidelines (Table 10), the predominance of concentration levels are acceptable, with only a few isolated events that exceed this specification.

Figure 26: Comparison of Phosphate Concentrations at each Sampling Point.

Table 10: Vaal Barrage Reservoir In-Stream Water Quality Guidelines for Phosphates (Rand Water, 2006). Vaal Barrage Reservoir In‐Stream Water Quality Guidelines

Ideal Acceptable Tolerable Unacceptable

‐ <0,03 (mg/l) 0,03 – 0,05 >0,05 (mg/l)

Figure 27 tracks the concentration of PO4 and Rainfall at SP1. This figure reveals interesting results about the concentration of PO4 in the Pienaars River. According to the author’s

correlation analysis, there is no significant correlation observed between rainfall and PO4 at this site.

This is emphasised in Figure 27, where there is no apparent relationship seen (r = 0.151), however concentrations of PO4 vary significantly in space and time. This is a direct result of the inputs added by the Baviaanspoort. According to a study conducted by DWAF in 1998, data from 1992-1995 indicated that the Baviaanspoort and the Zeekoegat Waste Water Works jointly contributed more than two thirds of the phosphorus load to the impoundment, with non-point sources in the Pienaars River contributing approximately 30 percent of the phosphate load. This may justify the poor correlation seen between PO4 and Rainfall at this sample point.

Figure 27 identifies the Phosphate Standard implemented by DWAF, as a measure of effluent standard that Baviaanspoort must comply with. As seen in Figure 27, there are numerous incidents whereby Baviaanspoort has not been compliant with the Standard. Such ‘spikes’ of

PO4 has major repercussions to the rate of eutrophication within the Roodeplaat Dam.

Figure 27: Results of Phosphate and Rainfall Tracking at Sample Point 1.

Through analysis, it was seen that SP2 exhibited a noteworthy correlation between rainfall and PO4 concentrations. According to Spearman’s correlation, a positive relationship was exhibited between rainfall and PO4 at SP2. Therefore, as rainfall values increase, there is a comparable increase in PO4 concentrations.

This is shown in Figure 28. These results are different to those predicted, however, concentrations of PO4 are relatively low and these results may reflect the ‘flushing out’ of

PO4 from the urbanised area located. As rainfall events occur within the study area, PO4 is flushed out into the system through storm water drainage. No significant correlations were exhibited at SP 3 and 4 (r = -0.65; r = 0.003).

Figure 28: Phosphate and Rainfall Tracking at Sample Point 2.

There is also a strong positive correlation exhibited between PO4 and NH4 at each sampling site. Table 11 highlights the positive correlation identified between PO4 and NH4. The strongest relationship between PO4 and NH4 is seen at SP2. At the dam wall (SP1) this relationship is not as apparent.

Table 11: Correlation Significance of PO4 and NH4 at each Sample Point.

8.2.3. Sulphates

Figure 29 compares SO4 concentrations across Sample Points (SP). At all Sample Points, SO4 is well within the acceptable ranges. This is seen in Table 12 and Table 13. Therefore is can be established that sulphate concentrations are not of concern within the study area. From Figure 29, it can be seen that sulphate concentrations are highest at SP1 over the duration of the 10 year study period. Sulphate concentrations are lowest at SP3 which constitutes agricultural land, in contrast to the Hartebees Spruit (SP2) and Pienaars (SP1), with higher concentrations of SO4 as a result of the urbanised land use activities and infrastructure on those rivers.

Table 12: VBR In-Stream Water Quality Guidelines for Sulphates (Rand Water, 2006). Vaal Barrage Reservoir In-Stream Guidelines (mg/l) Ideal Acceptable Tolerable Unacceptable <20 (mg/l) 20 -100 (mg/l) 100-200 (mg/l) > 200 (mg/l)

Table 13: SANS 241:2005 Drinking Water Specifications for Chemical Requirements- Macro Determinants (DWAF, 2005).

Figure 29: Comparison of SO4 Concentrations at each of the Study Sample Points.

Figure 30 tracks sulphate and rainfall at SP1 for the historical time in question. From the line graph, the inverse relationship that exists between the two variables may be seen. It is important to note that for many of the line graphs, there is somewhat of a ‘lag’ effect between rainfall and constituents, particularly when rainfall reaches a ‘peak’ before water quality constituents to begin decreasing. This notion seems logical, as water must still runoff land before water reaches the river and begins to have a dilution effect on water constituents. As seen in October 2000 of Figure 30, an increase in rainfall coincides with a decrease in SO4.

This is also seen in December 2005, where SO4 concentrations decrease in correspondence with a rainfall event. This inverse relationship is confirmed through Pearson’s Correlation, which found a significant correlation of -0.299. Spearman’s correlation found a much stronger assimilation of -0.418.

Figure 30: Results of Sulphate and Rainfall Tracking at Sample Point 1.

It is also of interest to note the correlation between SO4, E-coli and DMS. Correlation figures

discussed in section 8.1.2 for DMS and SO4 concentrations are emphasised again here.

According to Spearman’s correlation, there is a strong positive relationship between SO4 and DMS (r = 0.607). This is also seen for Pearson’s (0.334) however, not as strong. As with

DMS, SO4 displays a negative correlation to E-coli. According to Pearson’s correlation at SP1, an inverse relationship exists of -0.326 for sulphate concentration and E-coli.

Rainfall is not the only factor at play when determining chemical constituent concentrations at the Sample Point. It is important to also consider the additional inputs by Baviaanspoort and how such influents have an effect on the water chemistry.

The inverse relationship between rainfall and SO4 is not as apparent at SP2. According to

Pearson’s correlation, there is no significant relationship between rainfall and SO4. Spearman’s correlation, however, shows a significant inverse correlation of -0.281 between rainfall and SO4 at SP2. Other correlations of interest at this SP include SO4 and DMS (0.708)

as well as SO4 and E-coli (-0.209).

Figure 31: Results of Sulphate and Rainfall Tracking at Sample Point 3.

Figure 31 represents the lowest concentration of SO4 at any sampling point. The relationship

present at SP3 reflects a positive relationship between SO4 and rainfall (r = 0.223 rs = 0.281).

This is seen in Figure 31, whereby concentrations of SO4 decrease during the dry winter

months. Once rainfall increases again, concentrations of SO4 tend to increase in response. As

previously mentioned, SO4 concentrations are lowest at this SP. Therefore the increase of SO4

seen in Figure 31 as rainfall increases, may be a result of surface runoff, whereby SO4 is flushed into the Edendale Spruit system.

Pearson’s correlation found a positive relationship of 0.223 at SP4. Correlation was also found through Spearman’s correlation, which revealed a significant positive correlation of

0.281. As seen at the other Sample Points, SO4 exhibited a significant positive correlation to DMS and E-coli of 0.357 and 0.228 respectively.

SO4 at the dam wall did not reveal a significant relationship according to Spearman’s and Pearson’s correlation. This may be due to additional inputs of water from the wastewater works and the quality of runoff from storm water drainage along the Hartebees Spruit that plays a role in the concentration of SO4 at the dam outlet. SP4 also represents the second highest concentration of SO4 of the four sampling points. However, SO4 at this SP is still well within the recommended concentrations as seen in Table 12 & 13, and is therefore not of main concern in terms of water quality management.

8.2.3 Magnesium Magnesium (Mg) is a macro-nutrient that is needed by humans and animals alike. Magnesium also relates to the ‘hardness’ of water, where increased concentrations make water aesthetically displeasing as it is bitter in taste. Sources of magnesium include inputs from fertiliser and cattle feeds. This is seen in Figure 32, whereby the highest concentration of Mg is found at SP3. Land-use activities along the Edendale Spruit are dominated by dryland cropping, mixed agriculture and grasslands. The second highest concentration of Mg is found at SP2, followed by SP1. Concentrations of Mg are lowest at the Dam Wall. As mentioned in Section 5.2.4, the solubility of magnesium is directly related correlated to pH; whereby it becomes gradually less soluble with an increase in pH. This may account for the low concentrations of Mg exhibited at SP4.

Figure 32: Comparison of Magnesium Concentrations at each of the Study Sample Points.

Figure 33 tracks magnesium and rainfall concentrations at SP1. As can be seen in Figure 33, the correlation between rainfall and Mg concentrations is not as apparent. This was confirmed through Pearson’s and Spearman’s correlation analysis, which found no significant

relationship between rainfall and Mg concentrations at SP1 (r = 0.058; rs = 0.002). The relationship between rainfall and Mg concentrations may be affected by the additional inputs from the Baviaanspoort, which regulates the concentration of Mg in their effluent outputs to the Roodeplaat dam. Baviaanspoort may remove magnesium to soften the water and improve its quality for domestic use. Therefore, rainfall is not the dominant factor at play which affects Mg concentrations at this Sample Point, but rather the amount and quality of effluents released by Baviaanspoort. According to the SANS 241:2005 Drinking Water Specifications (Table 13), concentrations of Mg at all sampling points are well within the acceptable drinking class (<70mg/l) and is therefore not of concern.

Figure 33: Results of Magnesium and Rainfall Tracking at Sample Point 1.

As can be seen in Figure 34, the inverse relationship between rainfall and Mg concentrations is more clearly defined at SP2 than at SP1. During the dry, winter season when rainfall values are low, concentrations of Mg tend to ‘peak’. Alternatively, when rainfall events increase in the October months, there is a sharp decline in Mg concentrations. The sharpest decline of Mg occurs roughly in December-January, when rainfall values are at the highest. SP2 is also the second highest concentration of Mg. Industries add magnesium to plastics and other materials as a fire protection measure or filter. This may be the reason as to why the Hartebees Spruit constitutes the second highest concentration of Mg.

The inverse relationship demonstrated in Figure 34 is justified through the correlation analysis. According to Pearson’s correlation, Mg revealed a strong, inverse relationship of -0.467. Spearman’s correlation highlighted a stronger relationship of -0.623. It is also noteworthy to highlight the inverse relationship found between PO4 (-0.212) and E-coli

(-0.207) at SP2. Mg also revealed a strong positive correlation to SO4 (0.655) and DMS (0.970).

Figure 34: Results of Magnesium and Rainfall Tracking at Sample Point 2.

SP 3 represents the highest concentration of Mg at any Sampling Point. From Figure 35, one can identify the inverse relationship that exists between Rainfall and Mg at this site. As rainfall increases, the concentration of Mg decreases. From October 2002 to January 2003, there is an increase in rainfall and decrease in Mg concentrations. Then a decrease in rainfall is noted, which is subsequently followed by an increase in Mg concentrations (see Figure 35). The results from Figure 35 are confirmed through analyses, which found a significant relationship of -0.423 for Pearson’s and -0.383 for Spearman’s correlation.

Figure 35: Magnesium and Rainfall Tracking at Sample Point 3.

Similar findings were evident at SP4. Pearson’s correlation found a significant inverse relationship of -0.255 at SP4. It is also of interest to note the inverse correlation exhibited between Mg and pH at this Sample Point. Pearson’s correlation revealed a significance of -0.215. This highlights the fact that Mg gradually becomes less soluble with an increase in pH. A strong correlation was also found between Mg and DMS of 0.503 at SP4. Overall, magnesium concentrations at this Sample Point do not seem to be of concern (below 20mg/l). Ranges are well within acceptable limits, were the water at the SP4 is in fact quite soft.

8.3 Microbial Constituents

8.3.1 E-coli Figure 36 illustrates the concentration of E-coli at Sample Points 1, 2 and 3. E-coli concentrations were not included for SP4 as there were significant inconsistencies and gaps in the data provided which would not provide an accurate description of the study area. As can be seen from Figure 36, SP1 exhibits the greatest concentration of E-coli over time.

However, there is an isolated event in August 2006 at SP3, where E-coli concentrations exceed the specifications of <200 counts/100ml (Table 13). Excluding this event, E-coli concentrations do not exceed the tolerable limit specified in the Vaal Barrage Reservoir In- Stream Water Quality Guidelines (Table 14).

Figure 36: Comparison of E-coli Concentrations at each Sampling Point.

Table 14: Vaal Barrage Reservoir In-Stream Water Quality Guidelines for E-Coli (Rand Water, 2006). Vaal Barrage Reservoir In‐Stream Water Quality Guidelines

Ideal Acceptable Tolerable Unacceptable

‐ < 126 (counts/100ml) 100 – 200 (counts/100ml) >200 (counts/100ml)

E-coli is of particular interest in this study, as the findings of this constituent contrasted to those identified for physical and chemical water quality constituents. As seen in the figures below, unlike many of the inverse relationships observed between rainfall and water quality constituents in previous sections; E-coli exhibits a positive correlation to rainfall variation. Therefore, as water values increase, so does the concentration of E-coli colonies at each sample points. At SP1 (Figure 37), E-coli trends show significant variance. This is contrasted to SP3 (Figure 39) which is far more stabilised. The positive correlation identified at all three sample sites is confirmed through analyses. At SP1 (Figure 37) Pearson’s correlation revealed a significant positive relationship of 0.239. Spearman’s analysis yielded an even greater significance of 0.424.

As seen in Figure 37, E-coli concentrations were lower during the winter months, when rainfall values were correspondingly low. Similar results were also identified at SP2. This is validated through analysis which found a positive significance of 0.207 and 0.673 for Pearson’s and Spearman’s correlation respectively. At SP3, Spearman’s correlation recognised a significant positive correlation of 0.477 between rainfall and E-coli concentrations. E-coli represents an foreign bacterium that spreads through a system via water as its driving medium. E-coli also attaches itself to sediments and solid particles in a water body. Water therefore ‘flushes’ the microbial constituent throughout the system. This notion of ‘flushing’ is more prominent after episodes of rainfall. The results identified for microbial constituents at each sampling point correspond to those exhibited by Sinclair et al. (2009); Schilling et al. (2009) and Shehane et al. (2005) in Section 3; who all recognised that faecal bacteria loads were greater during years with higher annual precipitation.

Figure 37: Results of E-Coli and Rainfall Tracking for Sample Point 1.

Figure 38: Results of E-Coli and Rainfall Tracking for Sample Point 2.

Figure 39: Results of E-Coli and Rainfall Tracking for Sample Point 3.

8.4 Impact of Rainfall on Water Quality for the Roodeplaat Dam Catchment Area (2000-2009) From the results given above, it is clear that a correlation exists between rainfall and water quality constituents. The strength and association between rainfall and constituents is affected by external, anthropogenic variables which also exert an influence on the quality of water present in the Roodeplaat Catchment Area. This includes additional inputs from the Baviaanspoort. This is evident at SP 1 for each water quality constituent, where the effluent inputs added distorted the inherent relationship between rainfall and concentration of constituents. This includes the ability of Baviaanspoort to remove certain constituents, operational breakdowns at the facility and sheer volume of water that is added to the Roodeplaat catchment system. Therefore, it is essential to note that rainfall is one of many variables at play, which function as an interdependent whole to exert an influence on water quality constituents. Where anthropogenic influences outweigh seasonality (as seen for inorganic nitrogen and phosphates), the association between rainfall and constituents are less apparent. From the results produced above, it is clear that an inverse relationship exists between rainfall and the concentration of water quality constituents. This notion conforms to the ‘dilution capacity’, whereby rainfall (and an increase thereof) plays an essential role in diluting constituent concentrations in a water body.

E-coli is also of particular interest, as unlike physical and chemical constituents, E-coli exhibited a strong positive relationship to rainfall. This was evident at all three of the sample points and confirmed through literature produced in Section 3. Therefore, as rainfall values increase, so does the concentration of E-coli colonies within a water body.

It was also revealed from the study that certain water quality constituents have a significant association. This was seen for nitrates and phosphates, which exposed a strong positive correlation between the two chemical constituents. This notion has serious implications to the eutrophication problem seen at the Roodeplaat Dam. Other positive associations included a correlation between SO4 and DMS amongst many others. Understanding how water quality constituents respond to rainfall and one another provides a pathway of resource quality management within the Roodeplaat Catchment area that is based on scientific grounding and highlights the fact that a water system (in this case the Roodeplaat Dam) is an interdependent system.

There are a variety of factors at play. No one factor/influence works in isolation. By understanding how rainfall affects water quality constituents, we can better manage those anthropogenic influences which are in our control.

The aim of the study was to examine the spatial and temporal variations of selected water quality parameters over a long-term period, and to establish whether seasonal exposure in the form of rainfall variation, correlates to changes in water quality concentrations within the catchment area. From the results identified above, it is evident that an association does in fact exist between rainfall and concentration of water quality parameters in the study area.

An increase in rainfall, therefore, increases the ‘dilution capacity’ potential of the Roodeplaat drainage basin; in that an increase in rainfall tends to result in a decrease of water quality constituents. In this way, the water system of the Roodeplaat catchment area increases in its natural ability to receive and remove pollutants disposed in them by human induced land-use activities. This is seen for a variety of physical and chemical constituents.

Whilst the study establishes an inverse relationship between rainfall and water quality pollutant concentrations, it is lead to conclude that this finding is highly pressured by the growing expansion of anthropogenic land-use activities in the area. Within the past decade the landscape has altered quite significantly. Human land-use activities have nearly wiped out all the natural land and vegetation within the Roodeplaat Catchment. As a result of this rapid growth and expansion of human infrastructure and development, the ‘dilution capacity’ of the catchment area is compromised. According to van der Merwe-Botha (2009) this consequently means that all pollutants, including effluent streams, will need to be treated at increasingly higher standards before being discharged into communal waters and impoundments.

The problem we face in response to this is that the water infrastructure within this area cannot adequately deal with such impacts to the Roodeplaat catchment. The current infrastructure is unable to handle the pressure of increased inflows from the Baviaanspoort and Zeekoegat Water Care Works. This is intensified by human utilisation of land in the study area. This is seen in the results, where a correlation between the two variables is present, however this relationship is skewed and less direct (significant) due to the association of land-use activities to water quality concentrations.

This raises a suggestion further research and recommendations. In the study, the author has focussed on how natural phenomenon, such as rainfall, impacts on water quality parameters. This establishes how contributing rivers in the watershed contribute towards the dilution potential of the catchment and consequently to the Roodeplaat Dam. Further investigations should incorporate such notions, together with the influences of anthropogenic activities. This will provide clearer information on the interdependent factors at play which are compromising the dilution capacity potential of the Roodeplaat catchment area. Climate change is an additional factor which may be of interest to explore.

Further research is also required on ways to improve the infrastructure of the area, with particular focus on the additional inflows from the Baviaanspoort and Zeekoegat Water Care Works. Once these externalities are accounted for on a scientific basis, a proper management plan can be conducted for the Roodeplaat Catchment Area that will limit the impacts of land- use activities have on the area.

9. CONCLUSION

Roodeplaat Dam represents a strategic source of freshwater supply to the economic heartland of Gauteng. Water quality deterioration has been a continuous cause of concern within this catchment area and reflects the inability of decision makers to install policy into practice. In order to effectively manage the finite freshwater resources South Africa has, it is crucial to acknowledge two defining paradigms of any system. The first emphasises the fact that measurement equals management. The second notion is that any system, including that seen within the Roodeplaat Catchment, is interdependent. No system works in isolation. Through measurement, we are able to understand how various factors like precipitation effect water quality. We are also able to understand how different factors interact and subsequently impact on water quality. This notion translates into effective decision making, trend forecasting and ultimately better water management plans.

The overall objective of this study was to determine whether a correlation exists between rainfall and water quality constituents for the Roodeplaat Dam catchment area. The physical, chemical and microbiological water quality parameters were examined at four sampling sites situated in the Roodeplaat catchment over a 10 year period, from 1999 to 2009. Results of pH revealed a negative correlation at SP 2 and 4, with a positive correlation exhibited at SP3. No correlation was evident at SP1. For Dissolved Major Solids, an inverse relationship between rainfall and constituent concentrations was evident at all four sample sites. Nitrates and phosphates revealed a less direct correlation to rainfall. An inverse relationship was seen at SP 2 and 4 for nitrates, and a positive relationship at SP2 for phosphates. No apparent relationship was evident at SP1 for either water quality parameters. This may be the influence of additional inputs from the Baviaanspoort at SP1. From the study it was also revealed that nitrates and phosphates display a strong positive correlation to one another. This was also seen for sulphates and dissolved major solids, which displayed a strong positive correlation to one another. A negative relationship was also evident between sulphates and E-coli. Magnesium concentrations displayed a significant inverse relationship to rainfall at SP 2, 3 and 4. No correlation was evident at SP1.

E-coli displayed a significantly positive correlation to rainfall at all three sample sites utilised in the study. E-coli attach itself to sediments and solid particles in a water body. Rainfall therefore ‘flushes’ the microbial constituent through the system. This may account for the positive relationship exhibited between rainfall and E-coli in the study.

These results are correspondent to the ‘dilution capacity’ potential of the Roodeplaat catchment; whereby rainfall plays an essential role in diluting constituent concentrations in a water body and increases the ability of the water body to receive and remove pollutants disposed in them through anthropogenic land-use activities. However, the study also revealed that the ‘dilution capacity’ of the Roodeplaat catchment is compromised by the growing expansion of land-use activities in the area. Correlations at SP1, where additional inputs are added by the Baviaanspoort Water Care Works, were significantly distorted or displayed no correlation at all. Relationships between rainfall and water quality constituents at other sample sites revealed weak to medium correlations. As the landscape of the catchment progressively changes, land-use activities represent the primary influential factor impacting on water quality of the Roodeplaat catchment area. Natural vegetation that was mapped by Swanepoel (1997) has given way to a rapid increase of residential, industrial and small agricultural holdings in the catchment.

Pressures to the ‘dilution capacity’ of the catchment will inevitably require higher standards of water treatment to the inflow of water to the Roodeplaat Dam. The current infrastructure cannot already deal with the additional inputs to the Roodeplaat dam. This is seen through operational breakdowns, poor maintenance upkeep and outdated treatment techniques.

This study highlights an important challenge that water investment managers face in South Africa. Past practices have emphasised the construction of hydrological infrastructure to account for water scarcity within the country. Emphasis is now shifting to the ‘value’ of our existing freshwater systems and the quality of water to account for scarcity. Understanding how water quality constituents respond to rainfall and one another provides a pathway of resource quality management that is based on scientific grounding. Such findings, in association with data provided on the expansion of land-use activities within the Roodeplaat catchment, provide the necessary information water managers require to formulate effective management plans.

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