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A CASE STUDY ON THE HISTORICAL WATER QUALITY

TRENDS PERTAINING TO THE JUKSKEI RIVER

IN THE GAUTENG PROVINCE, SOUTH AFRICA

JANAVI MELLISSA JARDINE-DA SILVA

MINOR DISSERTATION

Submitted in partial fulfilment of the requirements for the degree

MASTER OF SCIENCE (MSc) In

ENVIRONMENTAL MANAGEMENT

In the

FACULTY OF SCIENCE

At the

UNIVERSITY OF JOHANNESBURG

SUPERVISOR: Dr I.T. RAMPEDI

08th April 2016

ACKNOWLEDGEMENTS

I would like to extend a word of sincere thanks and appreciation to the following people in recognition of the meaningful role and support they have provided during the course of the Research Project.

 Dr I.T Rampedi, my Supervisor for his unwavering guidance, support, effort and encouragement throughout the project.

 The Department of Water Affairs (DWA) for supplying water quality data and monitoring information.

 Michiel Jonker from Ecotone Freshwater Consultants for his advice and allowing me to make use of his GIS and water quality assessment tools.

 My parents and brother for their support and encouragement and my husband, Richard for his support and encouragement during the entire research period.

ABSTRACT

Due to the geographical position of the Jukskei River in the built-up and densely populated landscape, it has been historically subject to many water quality problems, particularly of bacterial nature, as well as from other pollution sources. At one stage, between 1995 and 2005, this river was subject to increasing pH levels and variable concentrations of sulphates, potassium, phosphates and nitrates.

The potential for flooding and changes in water quality are expected to have a direct correlation to the changes in surface coverage of the built environment surrounding the Jukskei River. Major storm water management concerns have arisen in urban areas as a result of increased severity and frequency of flooding, with detrimental consequences for society and the environment.

There is therefore a dire need to constantly monitor water quality, as the pollution loads gathered in the Jukskei channel ultimately reach the Hartbeespoort Dam, which is already in a state of high eutrophication. In responding to these water management challenges, it is crucial to understand the relationship between land use change, rainfall trends and water quality, so that storm water runoff can be managed effectively and efficiently.

Data which was obtained from the Department of Water Affairs (DWA) for the 28 year period from 1986 to 2014, shows overall concentrations of pollutants for three sites (Site A, Site B and Site C) along the Jukskei River. This correlates inversely to the increases in average water flows at these sites. The increased water flow and increased urban land use coverage over the period may be responsible for the decrease in pollutant concentrations at these sites.

The reasons for the more marked decrease in pollutant concentrations at Site A than Site B may be that Site A is located downstream of Site B. This could be due to the increased incidence of development-related impermeable surfaces occurring in close proximity to Site B, whereas Site A is further from the urban edge. It appears that an increase in the area of impermeable surfaces over time is negatively correlated with pollutant concentrations. This would imply that increased impermeable surfaces provide increased flow into the Jukskei River and therefore allow for the dilution of pollutants entering this river. This negative correlation is expected to continue into the future and the dilution effect may possibly be enhanced with increased development of impermeable surfaces within Johannesburg, depending on other water quality inputs.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

TABLE OF CONTENTS

Table of Contents 1 INTRODUCTION ...... 6 1.1 INTRODUCTION AND BACKGROUND TO THE RESEARCH PROBLEM ...... 6 1.1.1 Statement of the Research Problem ...... 6 1.1.2 Research Aim and Objectives ...... 8 1.2 RESEARCH METHODOLOGY ...... 8 1.2.1 Stage 1 ...... 8 1.2.2 Stage 2 ...... 9 1.2.3 Stage 3 ...... 9 2 LITERATURE REVIEW ...... 10 2.1 INTRODUCTION ...... 10 2.1.1 Understanding the pollution context of the Jukskei River ...... 11 2.2 IMPACTS OF URBANISATION ON THE JUKSKEI RIVER ...... 12 2.2.1 Background on previous Jukskei River Water Quality Datasets ...... 14 3 DESCRIPTION OF THE STUDY AREA ...... 15 3.1 GENERAL BACKGROUND TO THE STUDY AREA ...... 15 3.2 LOCATION OF THE JUKSKEI RIVER ...... 15 3.3 GEOLOGY, SOIL AND TOPOGRAPHY ...... 16 3.4 NATURAL VEGETATION ...... 17 3.5 SOCIO-ECONOMIC FACTORS ...... 17 4 DATA COLLECTION AND METHODOLOGY ...... 19 4.1 INTRODUCTION ...... 19 4.1.1 Water Quality Guidelines and Standards ...... 19 4.1.2 Comparison of Various Standards ...... 19 4.2 DATA COLLECTION ...... 22 4.2.1 Geographical Position of Monitoring Sites ...... 22 4.3 CORRELATING HISTORICAL WATER QUALITY DATA WITH HISTORICAL LAND USE DATA ...... 23 4.4 CLIMATE ...... 28 4.4.1 Average Historical Rainfall Patterns within Gauteng ...... 28 5 RESULTS AND DISCUSSION ...... 30 5.1 INTRODUCTION ...... 30 5.1.1 Average Seasonal Flow Rates (DWA, 1986 to 2014) ...... 30 5.2 WATER QUALITY DATA ANALYSIS ...... 31 5.2.1 Analysis of Historical Water Quality (DWA - 1986 to 2014) ...... 31 5.2.2 Site A (DWA A21 90169), Site B (DWA A21 90189) and Site C (DWA A21 90191) Water Quality 32 5.3 ANALYSES OF PHYSICAL DETERMINANDS ...... 41 5.3.1 pH ...... 41 5.3.2 Electrical Conductivity ...... 43 5.3.3 Total Dissolved Solids/Dissolved Major Salts (TDS/DMS) ...... 46 5.4 ANALYSES OF CHEMICAL DETERMINANDS ...... 49

5.4.1 Ammonia (NH4) ...... 49 5.4.2 Chloride (Cl) ...... 51 5.4.3 Fluoride (F) ...... 54

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

5.4.4 Phosphate (PO4) ...... 56 5.4.5 Calcium (Ca) ...... 58 5.4.6 Magnesium (Mg) ...... 61 5.4.7 Potassium (K) ...... 63 5.4.8 Sodium (Na) ...... 65 5.4.9 Sulphate (SO4) ...... 67 5.4.10 Nitrate (NO3) ...... 69 6 CONCLUSIONS ...... 73 7 RECOMMENDATIONS ...... 75 7.1 RECOMMENDATIONS FOR PROPER LAND-USE MANAGEMENT...... 75 7.1.1 Potential for Future Studies ...... 75 8 REFERENCES ...... 77

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

LIST OF TABLES

Table 1: Typical water quality problems in South Africa (WRC, 1998) ...... 11 Table 2: Pollutants and their sources (After Armitage et al., 2013; Minton, 2002; Opher & Feidler, 2010; Schoeman et al., 2013) ...... 12 Table 3: Parameters typically assessed for the Jukskei River...... 14 Table 4: Comparison of water quality guidelines / standards (from Sheppard, 2013) ...... 21 Table 5: Fitness for use categories and colour coding (van Veelen, 2002) ...... 22 Table 6: Land-use/cover conversion (%), 1991-2001 (from Mubiwa & Annegarn, 2013)...... 26 Table 7: Land-use/cover conversion (%), 2001-2009 (From Mubiwa & Annegarn, 2013) ...... 26 Table 8: Land use percentage of total Gauteng land area (Mubiwa, 2013) ...... 27 Table 9: Seasonal water quality averages showing threshold exceedances in colour - Site A (DWA Monitoring point A21 90169) ...... 34 Table 10: Seasonal water quality averages showing threshold exceedances in colour - Site B (DWA Monitoring point A21 90189) ...... 36 Table 11: Seasonal water quality averages showing threshold exceedances in colour - Site C (DWA Monitoring point A21 90191) ...... 39

iii

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

LIST OF FIGURES

Figure 1: The position of the Jukskei River and its associated tributaries (Source: Olukunle et al., 2012) ...... 7 Figure 2: The Jukskei River drainage system (Wittman & Forstner, 1976) ...... 16 Figure 3: The Jukskei River in relation to Regions of Gauteng ...... 18 Figure 4: Google Earth aerial image showing Jukskei River monitoring points ...... 23 Figure 6: Gauteng urban development (1991-2001) derived from land cover/land use analysis of satellite images (from Mubiwa, 2013) ...... 24 Figure 7: Gauteng urban development (2001-2009) derived from land cover/land use analysis of satellite images (from Mubiwa, 2013) ...... 25 Figure 8: The ratio of land use coverage changes from 1991 to 2009 (from Mubiwa & Annegarn, 2013) ...... 27 Figure 9: Gauteng average rainfall from 1977 to 2009 (After Dyson, 2009) ...... 28 Figure 10: Average cubic metre flow rates at Site A ...... 30 Figure 11: Average cubic metre flow rates at Site B ...... 31 Figure 12: Average cubic metre flow rates at Site C ...... 31 Figure 13: Comparison of water quality for Site A (A21 90169) ...... 33 Figure 15: Comparison of water quality for Site C (A21 90191) ...... 38 Figure 16: pH at Site A ...... 41 Figure 17: pH at Site B ...... 42 Figure 18: pH at Site C ...... 42 Figure 19: pH Comparison of sites ...... 43 Figure 20: Electrical Conductivity at Site A ...... 44 Figure 21: Electrical Conductivity at Site B ...... 44 Figure 22: Electrical Conductivity at Site C ...... 45 Figure 23: Electrical Conductivity Comparison of sites ...... 46 Figure 24: TDS/DMS at Site A ...... 47 Figure 25: TDS/DMS at Site B ...... 47 Figure 26: TDS/DMS at Site C...... 48 Figure 27: TDS/DMS Comparison of sites ...... 49 Figure 28: Ammonia at Site A ...... 49 Figure 29: Ammonia at Site B ...... 50 Figure 30: Ammonia at Site C ...... 50 Figure 31: Ammonia comparison of sites ...... 51 Figure 32: Chloride at Site A ...... 52 Figure 33: Chloride at Site B ...... 52 Figure 34: Chloride at Site C ...... 53 Figure 35: Chloride comparison of sites ...... 53 Figure 36: Fluoride at Site A ...... 54 Figure 37: Fluoride at Site B ...... 54 Figure 38: Fluoride at Site C ...... 55 Figure 39: Fluoride comparison of sites ...... 56 Figure 40: Phosphate at Site A ...... 56 Figure 41: Phosphate at Site B ...... 57 Figure 42: Phosphate at Site C ...... 57 Figure 43: Phosphate comparison of sites ...... 58 Figure 44: Calcium at Site A ...... 59 Figure 45: Calcium at Site B ...... 59

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 46: Calcium at Site C ...... 60 Figure 47: Calcium comparison of sites ...... 60 Figure 48: Magnesium at Site A ...... 61 Figure 49: Magnesium at Site B ...... 61 Figure 50: Magnesium at Site C ...... 62 Figure 51: Magnesium comparison of sites ...... 62 Figure 52: Potassium at Site A ...... 63 Figure 53: Potassium at Site B ...... 63 Figure 54: Potassium at Site C ...... 64 Figure 55: Potassium comparison of sites ...... 65 Figure 56: Sodium at Site A ...... 65 Figure 57: Sodium at Site B ...... 66 Figure 58: Sodium at Site C ...... 66 Figure 59: Sodium comparison of sites ...... 67 Figure 60: Sulphate at Site A...... 67 Figure 61: Sulphate at Site B ...... 68 Figure 62: Sulphates at Site C ...... 68 Figure 63: Sulphate comparison of sites ...... 69 Figure 64: Nitrates at Site A ...... 70 Figure 65: Nitrates at Site B ...... 70 Figure 66: Nitrates at Site C ...... 71 Figure 67: Nitrates Comparison of sites ...... 72

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

1 INTRODUCTION

1.1 Introduction and Background to the Research Problem

South Africa is a semi-arid and water scarce country, experiencing low annual precipitation and high evaporation levels (Vetter, 2009). South Africa is also the 29th driest country out of 193 countries, as it had an estimated 1 110m3 of rainfall in 2005 and a limited spatial distribution of available water, thus creating a problem of water scarcity (Muller et al., 2009). Despite these limited freshwater resources, South African rivers are heavily polluted. It is also recognised that water quality deterioration is an equally important component of the problem (Zhulidov et al., 2001). In the Gauteng province, extremes in rainfall episodes lead to flooding from time to time due to heavy rainfall occurring over the province. Historically, most of these events occur during the summer period, for instance, between January and February in 1996 and February in 2000 (Dyson, 2009).

The problem of water pollution contributes to the water scarcity problem in that it prevents the cost- effective use of beneficial water sources for human consumption and agriculture (Zhulidov et al., 2001). This may have a negative impact on public health, which can have severe effects on the economy as a result of increasing water scarcity (Neswiswi, 2014). Also the degradation of water quality leads to water related diseases and reduced agricultural yield, thus to economic losses.

1.1.1 Statement of the Research Problem The quaternary catchment where the Jukskei River is found is A21C within the City of Johannesburg (CoJ). There are no other major rivers in the CoJ. However, the catchment of the Jukskei, Klip and Rietpsruit rivers have their headwaters in the CoJ (Burke & Bokako, 2004). The Jukskei is one of the main tributaries of the Crocodile (West) River Basin. This tributary is one of the largest of the three rivers draining the northern suburbs of the Witwatersrand and arises from an underground spring in the Bezuidenhout Valley, east of Johannesburg (Campbell, 1996). It traverses a range of urban settlements such as Alexandra Township, Buccleugh and Midrand. Before its confluence with the Crocodile River, it is joined by the Modderfontein, Braamfontein Spruit and Sandspruit, and then flows into the Hartbeespoort Dam. A large part of the river is flanked by informal settlements with no or limited access to municipal services (Campbell, 1996; GJCM, 2000). The Jukskei passes through the Alexandra Township – a severely overpopulated area – which creates pressure on the infrastructure and blocks sewers, causing frequent overflow of waste into the river (GJCM, 2000). The current population density in the floodplains of the Jukskei is over 1000 people per hectare. Plans to reduce densification of inhabitants are only expected to result in a 10% reduction over time (Kisembo, 2004). Moreover, the banks of this river are prone to overflowing, especially during the summer months when rainfall is heaviest. Areas mostly affected by bursting banks include Alexandra Township, especially those living in informal shacks that use the water for drinking, washing and cooking (Matowanyika, 2010). 6

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 1: The position of the Jukskei River and its associated tributaries (Source: Olukunle et al., 2012)

Due to the geographical position of the Jukskei in the built up and densely populated landscape (Figure 1), it has been historically subject to many water quality problems, particularly of bacterial nature, as well as from other pollution sources (Matowanyika, 2010; Olukunle et al., 2012; Taylor et al., 2005; Whitmann & Forstner, 1976). According to Huizenga and Harmse (2005), at one stage between 1995 and 2005 the Jukskei River was subject to increasing pH and variable concentrations of sulphates, potassium, phosphate and nitrate. These pollutant types were attributed to rapidly increasing population density in the Jukskei catchment area, especially within and near Alexandra Township (Huizenga & Harmse, 2005). In addition, flooding episodes along the Jukskei are problematic, especially within Alexandra, as many of the informal residents live below the flood line. This impacts the river through solid waste mismanagement, periodically exacerbating the risk of flooding (Muvhali, 2013). The potential for flooding and changes in water quality are expected to have a direct correlation to the changes in surface coverage of the built environment surrounding the Jukskei River. This is potentially more noticeable in areas of higher density. The flooding of these areas also contributes to erosion and blocking of certain areas along the river corridor (Muvhali, 2013). Major storm water management concerns have arisen in urban areas as a result of increased severity and frequency of flooding, with detrimental consequences for society and the environment (WRC, 2009; Braune, 2006).

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Water quality generally deteriorates with poorly planned urbanisation and the expansion of informal settlements (Stephenson, 1992). Water quality is also influenced by changes in other land uses and living standards (van Veelen, 1994; Wimberley, 1992; Wright et al., 1992), with areas having high density and low cost housing creating more pollution than areas with low density and high cost housing establishments. Although numerous water quality studies have been conducted in the past on the Jukskei River (Huizenga & Harmse, 2005; Olukunle et al., 2012; Sibali et al., 2008; Taylor et al., 2005; van Veelen, 2002; Walsh & Wepener, 2009; Wimberley & Coleman, 1993), there is still limited understanding on historical water quality trends on this channel and related impacts, especially since the year 1986 to the present. Hence, this case study has assessed water quality patterns and trends in the Jukskei river channel from 1986 till 2014. This assessment provides crucial information to the drafting and design of spatial development frameworks as well as environmental management frameworks for improved sustainability in municipal spatial planning aimed at reducing the destruction of natural resources and the severity of environmental disasters (Burke & Bokako, 2004).

1.1.2 Research Aim and Objectives The aim of this case study was to assess water quality patterns and trends in the Jukskei river channel from 1986 until 2014, a period of nearly 30 years. To achieve this aim, the following research objectives were addressed:

1. To analyse historical water quality trends of the Jukskei River at selected monitoring points. 2. To analyse the pattern of seasonal variations in pollutant loads within the Jukskei River. 3. To map changes in land use distribution (land use change) over the specified time period within the catchment, showing any changes in the surface area taken up by man-made structures or land features. 4. To compare water quality trends to Target Water Quality Guideline Ranges (TWQR) (DWAF, 1998) for domestic and agricultural use as well as aquatic ecosystems.

1.2 Research Methodology

In responding to the research problem and research objectives, the case study was undertaken in several stages, as elucidated below.

1.2.1 Stage 1 A desktop study was undertaken to gather applicable information regarding the relevant catchment area, nature of the prevailing drainage systems and overall catchment utilization with reference to water quality data obtained from the Department of Water Affairs (DWA, 2986 – 2014). Reference was made to Mucina and Rutherford (2006) and the National Spatial Biodiversity Assessment (Nel et al., 2004) in order to understand and describe the biophysical properties of the study area and the surrounding area.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

1.2.2 Stage 2 A historical water quality database for the study area was obtained from the Department of Water Affairs (DWA, 2015). The database is made up of monthly water quality data measured at certain sampling points once a month over a period of 28 years, and was subsequently converted into seasonal averages in order to reveal the pattern of seasonal variations. In addition, the study concentrated on the following parameters: Electrical Conductivity (EC), pH, Total Dissolved Solids (TDS), sulphate (SO4), chloride

(Cl), potassium (K), fluoride (F), phosphate (PO4), nitrogen (N), ammonia (NH4), calcium (Ca), magnesium (Mg), and sodium (Na). The monitoring sites included the sites numbered A21 90169 (Site A) and A21 90191 (Site B) (situated along the Jukskei River; Figure 1) as well as A21 90191 (The little Jukskei). These were numbered according to the DWA numbering system The data were treated as an annual average over this 28 year period and were analysed statistically to depict historical trends in water quality of the Jukskei River.

Furthermore, these historical water quality data were compared with historical rainfall data from various studies, the prime purpose being to explore possible correlation between these parameters.

1.2.3 Stage 3 The water quality data were also correlated to land use cover. In this instance, the downstream impacts associated with the various changes in spatial planning were assessed and related to overall changes in water quality.

To achieve these goals, historical land use map data were obtained as a result of consultation with the Land Cover data from Department of Environmental Affairs (DEA, 2015). This included information for each year from 1986 until 2014, and served as a basis for comparison of the water quality and flow regime of the sampling points within the Jukskei River, showing the relationship between water quality in the Jukskei River and the increase in land use coverage over time.

Water quality parameters that were assessed amongst others, included pH, total dissolved solids, and major cation and anion concentrations. Nutrient levels were not assessed in the available DWA monitoring results. The relationship between changes in spatial planning and pollutant levels in the water were determined using the methods mentioned below.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

2 LITERATURE REVIEW

2.1 Introduction

The Department of Water Affairs adopted the “Receiving Waters Quality Objectives Approach” for non- hazardous pollutants, and the “Pollution Prevention Approach” for hazardous pollutants in 1989 (DWAF, 1995). This means that the quality requirements of the receiving water body are set and the standards of compliance for wastewater are derived from those (van Veelen, 2002).

The resource quality objectives were taken one step further by giving it legal status in Section 13(1) (b) of the National Water Act (Act No. 36 of 1998). Resource quality is further defined in Section 1(1) (xix) as:

“The quality of all the aspects of a water resource including: - (a) The quantity, pattern, timing, water level and assurance of instream flow; (b) The water quality, including the physical, chemical and biological characteristics of the water; (c) The character and condition of the instream and riparian habitat; and (d) The characteristics, condition and distribution of the aquatic biota.” The resource quality objectives are dependent on the classification of a water resource as described in Section 13, which serves to protect the resource for basic human needs and the aquatic ecology. However, Part two and page 28 of the National Water Act (Act No. 36 of 1998) states clearly that “… a balance must be sought between the need to protect and sustain water resources on the one hand, and the need to develop and use them on the other”.

The objective is to ensure that the water resource is usable for the foreseeable future, and not to only ensure the protection of the water resource for conservation’s sake. The quality objectives as described above, hence, represent a set of parameters to keep the resource in a particular state (van Veelen, 2002).

In Table 1, typical water quality problems in South Africa are summarised, of which the most serious are the following (Department of Water Affairs and Forestry (DWAF), 1991): -

 Salination – from natural and anthropogenic causes. The natural source of salts both geological and the anthropogenic sources, including mining and industrial pollution.  Eutrophication – the result of increased levels of phosphate and nitrate in large water bodies. This originates from the effluent of waste water treatment works and agriculture.  Micropollutants – trace metals and organic compounds such as pesticides occur in rare instances.  Sedimentation – caused by widespread erosion.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 1: Typical water quality problems in South Africa (WRC, 1998) Source Quality Problems Surface Water Faecal pollution, colour and stability, salt concentrations, eutrophication. Ground Water Salinity, Fluoride, Sulphate and Chloride, Calcium and Magnesium, Iron and Manganese.

2.1.1 Understanding the pollution context of the Jukskei River The Jukskei River was characterised in the 1980’s as having low pH values (3 to 4), high sulphate concentrations and high concentrations of chloride, fluoride, sodium and nitrate (Huizenga & Harmse, 2005). Between the years 1987 and 1990, the Urban Renewal Plan was implemented in the Jukskei area with a view to reduce the pollution load. Thus, water reticulation systems, water-borne sewerage pipes, electrical reticulation and ablution facilities were provided to all dwelling units in Alexandra Township within the Jukskei catchment (Campbell, 1996). However, this plan might have attracted more residents into Alexandra and may in turn have caused increased urban runoff, possibly affecting the downstream water quality of the Jukskei River (Campbell, 1996). Furthermore, potential sources of water pollution along the Jukskei River include hazardous waste stemming from mining activities as well as manufacturing industries (Huizenga & Harmse, 2005). Moreover, the construction of impervious land surfaces across these urban, industrial and mining areas has a number of environmental impacts such as excess storm run-off. This is because conventional drainage systems generally focus on eliminating local flood events and mostly ignore the need to preserve or improve water quality (Armitage et al., 2013) Typically, such storm water runoff reaches the river, bringing with it pollutants and toxicants from neighbouring land uses, including industry or mining. These pollutants and their corresponding sources are represented in Table 2.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 2: Pollutants and their sources (After Armitage et al., 2013; Minton, 2002; Opher & Feidler, 2010; Schoeman et al., 2013) Pollutant Pollutants Sources Impacts Group Nutrients, Nitrogen & Phosphorus Domestic wastes, overloaded Excessive nutrients cause faecal sanitation systems, soil eutrophication. These nutrients bacteria, dumping, sewers or absence are commonly associated with viruses, of sewerage systems. algal blooms. This results in organic decreased biodiversity and matter. clarity. Sediments Suspended solids Erosion, construction, Increased turbidity, vegetation removal. sedimentation and smothering of aquatic biota. Organic P-, N- & Organic Vegetation, pollen, Increased nutrients and Material compounds atmospheric deposition. sediment. Hydrocarbon Heavy metals, oils, toxins, Vehicle emissions, industrial Public health risk. Creating s hydrocarbons, NOX, SO2. emissions, atmospheric contaminated recreational and deposition, pavements, spills, public areas. pavements, roads. Pollute downstream water and Pathogens Bacteria, viruses and Failing sewerage system, edible crops. protozoa animals. Decreased economic value of Metals Dissolved solids, Washing of clothes, vehicles. natural and public areas. chlorides, phosphates. Industrial leaks, galvanised construction materials. Toxic Dust, chlorides, S- Wind rain & groundwater. chemicals compounds, leachates. Agriculture and landscaping. Solids Dissolved solids, Burning of litter, wood & coal. Threat to wildlife and aesthetic sulphates, carbon, and appeal. particulate matter.

2.2 Impacts of Urbanisation on the Jukskei River

Major pollution sources from runoff emanate from developed areas, moving a wide variety of contaminants. The main variables affecting water pollution include climate conditions, maintenance policies, surrounding land use, percentage of permeable and impermeable areas, age and condition of vehicles as well as vehicle emissions (Prodanoff & Mascarenhas, 2010).

In the case of the Jukskei River, potential industrial polluters include the AECI Group explosives and Kelvin Power station (Huizenga & Harmse, 2005). These industries as well as others along the Modderfontein Spruit, at the confluence with the Jukskei River, have been attributed to the slightly lower

- 4- 3- - - pH and higher concentrations of F , SO2 , PO4 , NO3 and Cl .The impacts of the mining activities in the surrounding areas are possibly associated with high sulphate concentration and low pH values. The major cause of this is the oxidation of pyrite in mine waste in the presence of water, producing acidic water (Huizenga & Harmse, 2005).

The presence of high density informal settlements, especially near Alexandra Township, has been shown to cause increases in nutrient concentrations as well as sodium, chloride and potassium (Matowanyika, 2010). This can be attributed to the effluent escaping from these settlements due to the high density of shacks and poor solid waste management. As a result, urban runoff from this area is

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa. mixed with overflow stemming from portable toilets, leaking sewerage pipes, informal business operations and daily domestic cleaning detergent use (Campbell, 1996).

More concerning is the increased growth of impervious land surfaces and the associated risks of flooding during storm events. These factors are interfering with the natural ability of the river to attenuate floods and to store flood water. A reduction in this attenuation ability increases the velocity and the erosive power of flood waters, thus decreasing silt and sediment deposition between storm events and the peak runoff (WRC, 2014). Flooding and erosion affect water quality because the usual process of filtration of nutrients and impurities from runoff is hindered by the increased velocity of water entering the river. As such, the natural processes of diluting the wastes are hindered by man-made infrastructure and excess urban runoff leading to flooding. In highly populated areas with few open spaces, the water pollution may be diffuse or concentrated. It is difficult to evaluate the exact sources of diffuse pollution. At the same time, concentrated sources are also difficult to identify, as is the assessment of their water quality behaviour (Prodanoff & Mascarenhas, 2010). In order to manage the Jukskei’s catchment optimally, floodwaters should be allowed to slow down so that sediments can settle out, thereby maintaining water quality. This also improves the optimum functioning of riparian vegetation in the filtration of water entering the river (Prodanoff & Mascarenhas, 2010).

The urban form in Gauteng has been constantly changing over the 28 year period measured in this study, with various factors influencing the rate, extent and patterns of flow at different times (Mubiwa & Annegarn, 2013). During the decline of gold mining circa 1976, the land use shifted from mining to industrial and manufacturing and a service-based economy. This stimulated the rapid growth of residential suburbs and the decentralisation of commerce to peri-urban spaces. Randburg and Sandton also became new economic hubs (Mubiwa & Annegarn, 2013; Ovens et al., 2007; Sexwale, 2009; Visagie, 2008), thus changing the physical and economic profile. Many parts of Johannesburg have changed from predominantly peri-urban agricultural areas to major urban complexes (Mubiwa & Annegarn, 2013).

In view of these development-related pressures on the Jukskei River system, there is a dire need to constantly monitor its water quality, as the pollution loads gathered in this channel ultimately reach the Hartbeespoort Dam, which is already in a state of high eutrophication. Such eutrophication levels are detrimental to aquatic health and the future storage of water in South Africa (van Ginkel, 2011). In responding to these water management challenges, it is crucial to understand the relationship between land use change, rainfall trends and water quality, so that storm water runoff can be managed effectively and efficiently. Thus, the recommendations arising from this case study will shed light on optimal urban spatial planning and successful storm water management practices.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

2.2.1 Background on previous Jukskei River Water Quality Datasets Historically, the main chemical pollution emanating from the Jukskei was mostly made up of the following variables (Table 3). According to van Veelen (2002), who conducted an assessment of various datasets regarding the pollutants of concern, the following are of importance:

Table 3: Parameters typically assessed for the Jukskei River Parameter Type Constituents Physical Parameters Electrical Conductivity pH Turbidity Odour Colour Litter Chemical Oxygen Demand Sodium Adsorption Ratio Chemical Parameters Fluoride Ammonia Nitrate/Nitrite Sulphate Chlorine Phosphate Microbiological Parameters E. coli Feacal coliforms Chlorophyll-a (algae) Ecological Indicators Habitat integrity Biological indicators SASS (Macro-invertebrates) Fish (species diversity)

According to van Veelen (2002), the Jukskei River catchment has varied water quality from one sub- catchment to another. Each sub-catchment is affected differently due to varied inputs. Chemical pollution containing sulphates and fluoride emanate from the Modderfontein Industrial Area. Ammonia concentrations decreased as they moved away from the source point as a result of dilution and the natural breakdown of constituents. This study aims to assess only data provided by the Department of Water Affairs for the 28 year period. The efficacy of which can also be assessed.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

3 DESCRIPTION OF THE STUDY AREA

3.1 General Background to the Study Area

The region that is home to the Jukskei River is densely populated and the river is generally shallow and highly polluted (Campbell, 1996). The Jukskei River is contaminated with mine water amongst other contaminants such as untreated effluent, industrial waste, agricultural chemicals and hydrocarbon and chemical discharges (Burke & Bokako, 2004; Campbell, 1996; Huizenga, 2004; Matowanyika, 2010; Mawela, 2008; Neswiswi, 2014; Roux & Oelofse, 2010). The Jukskei River is an example of an urban catchment where many problems have arisen as a result of rapid urbanisation, mostly due to the development of the Alexandra Township.

Historically, the Alexandra area experienced a large influx of inhabitants during the period from 1945 to 1948. The lack of institutional services for sanitation and water management has placed immense stress on this system (Campbell, 1996). Over a number of years, many resettling policies have been implemented in the area to try to limit the number of people moving into the area (De Jager, 1990). However, people continue to move into Alexandra due to the high demand for affordable and low cost housing. Because of this, additional sources of pollution emanate from overflowing portable toilets, backyard businesses, washing of clothes along the river banks etc. (Campbell, 1996).

3.2 Location of the Jukskei River

The catchment area of the Jukskei River, which is approximately 77 650 hectares, drains a large portion of the Witwatersrand (Figure 2). It is within Johannesburg, with Midrand to the north, Roodepoort to the south, and Kempton Park to the east (Campbell, 1996).

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 2: The Jukskei River drainage system (Wittman & Forstner, 1976)

3.3 Geology, Soil and Topography

The geology of the Jukskei River catchment is made up of granite and gneiss (Huizenga & Harmse, 2005). The Witwatersrand Supergroup crops out along the Southern boundary and many other parts of the catchment. This forms various ridges such as the Linksfield ridge and Germiston ridge as well as the cliffs at Northcliff. At the confluence of the Jukskei River and the Modderfontein Spruit there is an eastern diabase dyke running in a north-south direction. To the north of the N3 freeway lies three syenite intrusions all running in a north-westerly direction. There are also two lineation cuts, one of which runs through the southern parts of Alexandra (van Veelen, 2002). Generally, Alexandra is underlain with highly weathered and decomposed rocks of Archaen granite, forming the Johannesburg/Pretoria Dome (Wimberley, 1992). This granite outcrops in the Jukskei riverbed and is of a medium to coarse textured pink or grey rock. The geology of the catchment does not play an important role in the drainage patterns (Figure 2) as the catchment is fairly geologically uniform (van Veelen, 2002).

The highest point of the river system is in Observatory, which reaches a height of 1808 mamsl. This catchment slopes to the north-west with the confluence of the Jukskei River with the Crocodile River at 1220 mamsl. The southern part of the catchment is made up of ridges to the south towards Northcliff

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa. and Florida Hills and steep ridges in Sandton giving way to rolling hills on the northern side of the river. The morphology of the Jukskei River is a classic example of a trellis drainage system. The highest point of the Jukskei is 1695 mamsl, with a height of 45 m across a length of 66 km, giving it an average slope of 7.3 m/km. The River is therefore steep and fast flowing (van Veelen, 2002). Due to the relatively steep slopes, none of the streams in the catchment meander and the streams run fairly straight. There are also not major obstacles or changes in geology to influence the course of the river (van Veelen, 2002).

3.4 Natural Vegetation

According to Mucina and Rutherford (2006), the natural vegetation types within the Jukskei catchment include the Egoli Granite Grassland covering the majority of the catchment, with an area to the south made up of Soweto Highveld Grassland and a small area to the east of Alexandra made up of Carletonville Dolomite Grassland.

The Egoli Granite Grassland is made up of undulating plains supporting tall, usually Hyperhenia hirta dominated grassland with some rocky outcrops supporting woody species. Only 3% of this veld type is conserved in statutory reserves, even though the veld type is considered endangered. Over two thirds of this vegetation type is transformed by cultivation, urbanisation, mining and dam building as well as roads and infrastructure (Mucina & Rutherford, 2006).

3.5 Socio-economic Factors

Johannesburg’s demographics indicate a large and ethnically diverse metropolitan area. It is the largest city in South Africa with a population of approximately 4.4 million people and a long history of local and international immigration. This population accounts for 32% of the Gauteng population and 8% of the country’s population. The growth continues to increase because the city attracts people from other provinces, other African states and elsewhere, who are looking for better economic opportunities (COJ, 2014b). The Jukskei River exists in Region E (represented in Figure 3) of the City of Joburg Metropolitan Municipality (COJ, 2015). According to the City of Joburg Integrated Development Plan (2014b), Region E is said to have 11.8% of the city’s population (COJ, 2015). Region E forms one of Joburg’s eastern boundaries. To the north of Region E is Region A; Midrand, to the west is Region B; Northcliff, Randburg, and Region F to the south; the inner city and Johannesburg South. In Region B, the land use varies from residential in the northwest and the west to industrial and manufacturing to the south and northeast. The majority of land use in Region E is made up of the Alexandra Township (COJ, 2015). The population estimate for the Alexandra Township is approximately 370 000 inhabitants, in the year 2000. Due to the highly dynamic nature of the influx and exodus of inhabitants, the figure has been estimated from anywhere between 180 000 to 750 000 inhabitants (CGMJ, 2000). Since this date, this number may have increased substantially.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 3: The Jukskei River in relation to Regions of Gauteng

Urban water management in the City of Johannesburg aims to improve water courses and water demand management. The two most important tributaries of the CoJ municipal area include the Jukskei River, draining towards the Hartbeespoort Dam and the Klipspruit River draining towards the Vaal Dam. Within the Jukskei River system, hotspots for pollution control intervention have been identified. These hotspots are those areas of the Jukskei flowing along poor communities (COJ, 2014a). It is thus evident that the area of most concern for the purposes of this study is within and surrounding the Alexandra Township, within Region E.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

4 DATA COLLECTION AND METHODOLOGY

4.1 Introduction

This section will provide a background on all relevant water quality guidelines and standards related to an explanation of the methodology selected for the current research. The water quality guidelines and standards are presented in section 4.1.2 and the methods are explained in section 4.2. The secondary purpose of the analysis is to evaluate the strength of the impact of land use on the quality of receiving waters. This will be looked at as a general trend of potentially increasing intensity of human activities for the Gauteng province and Johannesburg.

4.1.1 Water Quality Guidelines and Standards In order to understand the potential impacts on water quality the levels of pollutants must be assessed in terms of international and local standards. These guidelines or standards are important because they provide threshold values (for health and/or aesthetic purposes) pertaining to various concentrations of chemical and physical parameters measured (Sheppard, 2013). The term ‘water quality objective’ has traditionally referred only to the physical and chemical characteristics of waters, however, the water quality objectives can encompass a broader range of characteristics including flora and fauna, habitat, flow and physical condition (DEHP, 2014). These will not be discussed in this study, as the intention is to assess water quality patterns and not necessarily water quality objectives. However, compliance with these guidelines or standards aids in the regulation of the quality of water resources.

The WRC (2001) defines water quality as what is used to describe the microbiological, physical and chemical properties of water that determine its fitness for a specific use. The water quality that is for domestic purposes is not necessarily the same as for irrigation (DWA, 1996; WRC, 2011). Four main categories of uses include (DWA, 1996):

 Domestic  Agricultural  Industrial  Recreational

By comparing the physical and chemical properties of water, the extent of contamination of the water can be ascertained and its effect on human health can be established (Horner et al., 2011).

4.1.2 Comparison of Various Standards Recognised water quality guidelines and standards are required to evaluate the water quality data. As a result, a comparison of established water quality guidelines or standards will be used. Due to the fact that all chemical and physical parameters were not covered in each guideline, four additional water

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa. quality standards were compared. The effect on health is the most important factor for water quality. This is especially true for those living in shacks in the informal settlements of Alexandra, who are using the water along the banks for washing, drinking and cooking. As discussed in section 1.1.1 of this dissertation, the health implications of water quality are of great consequence (WHO, 2008) as this is the most direct impact of poor water quality. All other water quality standards are secondary to this from a health and economic perspective for the purposes of this study.

The standards that were used include the following:

 Total Water Quality Range Guidelines (TWQR) – Department of Water Affairs (DWA, 1996).  World Health Organisation (WHO): Guidelines for Drinking Water Quality Fourth Edition (WHO, 2011).  South African National Standard (SANS) 214:2011, Edition 1 (SABS, 2011).  South African National Standard (SANS) 241:200, Edition 6.1 (SABS, 2006).  The Council of the European Union (EU); 98/83/EC of 3 November 1998 on the quality of water intended for human consumption (EU, 1998).

The available physical and chemical parameter guidelines were compiled and listed in Table 4. The parameters in the table are separated into physical and chemical determinands. The physical determinands include pH, EC and TDS. The chemical determinands that were measured by DWA over the 28 year period include NH4, Cl, F, N, PO4, Ca, Mg, K, Na and SO4.These are determinands that dissolve in water and have a wide range of effects from toxicity to scale-forming (WRC, 2001).

In cases where both the health and aesthetic determinands were present; both were used to compare the levels as they were monitored. Where only the aesthetic guidelines have been provided, it may mean that insufficient quantities are present for their effect on human health. These guidelines combined provide a benchmark for the proper management of water determinand bodies by the relevant authorities (WHO, 2011).

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 4: Comparison of water quality guidelines / standards (from Sheppard, 2013) *The stars represent a lack of information for a specific parameter.

COMPARISON OF WATER QUALITY GUIDELINES AND THEIR ASSOCIATED THRESHOLD VALUES

WHO Guidelines SABS (2011) SABS (2006) EU 1998 4th Ed.

Physical Determinands Class I Class II 4.0 - pH 5 - 9.7 5.0 - 9.5 10.0 6.5 - 8.5 6.5 - 9.5 Electrical Conductivity 150 - (mS/m) <170 <150 370 * 250 Total Dissolved Solids 1000 - (mg/l) <1200 <1000 2400 <1000 *

Total Alkalinity

Chemical Aestheti Health Class I Class II Aestheti Health Threshol Formula Determinants c (mg/l) (mg/l) (mg/l) (mg/l) c (mg/l) (mg/l) d (mg/l)

Ammonia NH 4 <1.5 * 1.0 1.0 – 2.0 * * 0.5 200 - Chloride Cl - 300 * <200 600 250 * 250

Fluoride F - * 1.5 <1.0 1.0 - 1.5 * 1.5 1.5

Nitrate NO3- * 11 <10 10 - 20 * 50 50

Phosphate PO4 * * * * * * * 150 - Calcium Ca * * <150 300 * * *

Magnesium Mg * * <70 70 - 100 * * *

Potassium K * * <50 50 - 100 * NA * 200 - Sodium Na 200 * <200 400 200 * * 400 - Sulphate SO42- 250 500 <400 600 250 * 250

According to van Veelen (2004), the water quality guidelines developed for South Africa have been derived for fitness of use by categories and colour. These are summarised in Table 5 to colour code the values according to the categories of domestic, recreation, agriculture and aquatic ecosystems. For the purposes of this case study, only the variables that were monitored by DWA in their water quality monitoring programme from 1986 to 2014 were examined.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 5: Fitness for use categories and colour coding (van Veelen, 2002) User Variable Colour Category Blue Green Yellow Red Ideal Acceptable Tolerable Unacceptable Situation Situation Situation Situation Domestic Electrical Conductivity <70 70-150 150-370 >370 pH 6.0-9.0 4.5-6.0 4.0-4.5 4.0 Fluoride <1.0 1.0-1.5 1.5-3.5 >3.5 Nitrate <6.0 6.0-10.0 10.0-20.0 >20 Sulphate <200 200-400 400-600 >600 Recreation pH 6.5-8.5 5.0-6.5 <5.0 Agriculture Electrical Conductivity <40 40-90 90-540 >540 pH 6.5-8.4 <6.5 >8.4 Sulphate <200 200-300 300-500 >500 Fluoride <1.0 1.0-2.0 2.0-15.0 >15.0 Aquatic pH 6.5-8.5 5.0-6.5 4.0-5.0 <4.0 Ecosystems Ammonia <0.025 0.025-0.3 0.3-0.8 >8 Nitrite <0.06 0.06-0.25 0.25-5.0 >5.0

4.2 Data Collection

The water quality data were collected over a period of 28 years by the Department of Water Affairs (DWA) and were compiled into large datasets of monthly monitoring data. The data was originally available from 1972 until 2014; however, there were large gaps in available measured data during the period between 1972 and 1986. Therefore, in order to maximise accuracy when determining an average, the DWA data was only used from 1986 until 2014 to reflect the most consistent monitoring period. The DWA data only contain information about the physical and chemical determindands and no information regarding biological determinants. Because of this, the water quality patterns of Jukskei will not be addressed in terms of biological determinants such as faecal coliforms.

4.2.1 Geographical Position of Monitoring Sites The Department of Water Affairs (DWA) conducted water quality monitoring at numerous sites for differing periods of time at each site. However, the only sites with sufficient data to cover a 28 year period were the three sites named A21 90169; A21 90189 and A21 90191. These contained water quality data from 1973 up until 2014. However, the data from the period of 1973 until 1986 were relatively unreliable in that it contained many gaps with missing data. For this reason, only water quality data for the period of 1986 to 2014 was assessed in order to provide the most realistic representation of water quality. The positioning of these monitoring sites is shown in Figure 4.

For ease of reference in this case study, the monthly monitoring sites will be referred to as follows:

 A21 90169 will henceworth be referred to as Site A – co-ordinates = 25°53'43.80"S; 27°56'5.32"E.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

 A21 90189 will henceforth be referred to as Site B – co-ordinates = 25°57'15.98"S; 27°57'45.22"E.  A21 90191 will henceforth be referred to as Site C (shown here as Little Jukskei) – co- ordinates = 26° 4'5.92"S; 27°58'21.11"E.

Figure 4: Google Earth aerial image showing Jukskei River monitoring points

4.3 Correlating Historical Water Quality Data with Historical Land Use Data

The historical land use cover measured by Mubiwa and Annegarn (2013) from 1991 to 2001 and 2001 to 2009 can be used to give an overall pattern of the changes in land use over the 28 year period. Although the data do not encompass the entire 28 year period, it still provide a good indication of the land use changes over this period. The expansion of the urban/built up area is represented in red in both Figure 6 and Figure 7.

In Table 6 and Table 7, the continued urban development within Johannesburg and Pretoria was prominent during both periods shown in the tables. The change in land use has been highly dynamic within the region, and high levels of competition were experienced between many different land-use types (Mubiwa & Annegarn, 2013).

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 5: Gauteng urban development (1991-2001) derived from land cover/land use analysis of satellite images (from Mubiwa, 2013)

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 6: Gauteng urban development (2001-2009) derived from land cover/land use analysis of satellite images (from Mubiwa, 2013)

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

The urban land use between 1991 and 2001 has increased significantly, with approximately 25% of the bare area taken up and approximately 5% of the woodlands and grasslands converted to urban areas. The largest conversion from the period 1991 to 2001 was from woodland to grassland (Mubiwa & Annegarn, 2013).

Table 6: Land-use/cover conversion (%), 1991-2001 (from Mubiwa & Annegarn, 2013) Changed to Water Urban Mines Cultivated Grasslands Woodlands Wetlands Bare 2001 Changed from 1991 Water 88.78 1.40 0.06 0.12 6.77 1.48 0.44 0.41 Urban 0 99.99 0.06 0 0.1 0 0 Mines 0 0.02 99.97 0 0 0 0 0 Cultivated 0.01 0.11 0 99.13 0.66 0.05 0.02 0.01 Grasslands 0.21 4.79 0 0.3 84.90 4.65 0.78 4.35 Woodlands 0.32 5.15 0 0.16 69.65 17.02 4.87 2.81 Wetlands 0.23 2.98 0 0.06 56.57 5.61 32.80 1.72 Bare 0.33 24.62 0 0.22 46.03 3.28 0.41 25.06

The conversion to urban from woodlands was approximately 5% and from bare areas was just under 5%, making the changes during this time period much slower than those of the first period between 1991 and 2001. Changes from urban to other areas was recorded as zero (0). The trend during these periods of any changes including conversion from bare areas to grasslands and from woodlands to grasslands has slightly increased over the time period between 1991 and 2001.

The general trend regarding the expansion of impermeable surfaces and built up areas including urban areas and mines does not exceed 5% (Mubiwa & Annegarn, 2013). The changes in land use can be attributed to the stronger economic growth and population increases during the period of 2001 and 2009.

Table 7: Land-use/cover conversion (%), 2001-2009 (From Mubiwa & Annegarn, 2013) Changed to Water Urban Mines Cultivated Grasslands Woodlands Wetlands Bare 2009 Changed from 2001 Water 88.65 1.20 0.35 0.15 10.63 1.25 0.69 0.07 Urban 0 100 0 0 0 0 0 0 Mines 0.68 3.68 70.37 0.02 22.88 0.26 0.26 1.85 Cultivated 0.01 0.72 0 98.42 0.80 0.03 0.01 0.01 Grasslands 0.21 3.60 0.05 0.15 88.71 4.44 1.77 1.01 Woodlands 0.38 4.91 0.03 0.15 70.07 19.12 4.28 1.01 Wetlands 0.46 0.82 0 0.17 42.75 13.77 40.66 1.33 Bare 0.10 4.68 0.02 0.10 79.05 5.54 1.66 9.34

During the period of 1991 to 2001 small portions of mining to urban conversion were experienced in the Johannesburg CBD, where mining tailings were reclaimed and converted to industrial developments. Infill development continued into 2001 and 2009 with land use cover characterised by urbanisation.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Overall urban development from 1991 to 2001 changed by approximately 8% and from 2001 to 2009 by approximately 6% (Table 8).

Table 8: Land use percentage of total Gauteng land area (Mubiwa, 2013) Land Cover Class 1991 2001 2009 Hectares % Hectares % Hectares % Water 35 707.71 1.97 34 350.43 1.89 32 002.60 1.76 Urban (Built Up) 228 791.82 12.60 289 781.31 15.95 333 457.56 18.36 Mines 26 362.64 1.45 26 584.67 1.46 19 320.06 1.06 Cultivated 391 787.26 21.57 391 460.73 21.55 386 942.72 21.30 Grasslands 890 463.40 49.03 918 737.59 50.57 934 043.39 51.42 Woodlands 174 602.38 9.61 75 111.73 4.13 62 620.52 3.45 Wetlands 39 788.39 2.19 28 849.97 1.59 32 150.38 1.77 Bare 28 564.33 1.57 51 723.21 2.85 15 841.93 0.87

The growth patterns shown in Figure 5 and Figure 6 are concentrated within Johannesburg and Pretoria. The changes in land use over this period can be generally compared to the changes in water quality. These changes in land use do not fully encompass the period from 1986 to 2014, however, the general changes in land use indicate an increase in coverage of urban areas, thus increasing the percentage of impermeable surfaces within the Jukskei area and surrounds. The urban areas increased by 5.76% whereas the wetland areas decreased by 0.42%. This may create a situation where the landscape’s ability to attenuate floods and to absorb storm water events can be impaired, which can be exacerbated by a surface with decreasing permeability with the spread of urban areas.

Figure 7: The ratio of land use coverage changes from 1991 to 2009 (from Mubiwa & Annegarn, 2013)

It is evident from Figure 8 that the land use coverage in Gauteng changed over time with the apparent expansion of the urban areas in Gauteng. During this time the woodland land use coverage and the operational mines diminished. However, when looking at the maps of Gauteng in Figure 56 and Figure 67, the area representative of Johannesburg is predominantly made up of urban areas. These areas have expanded from 1991 to 2009, and this increase in urban coverage (shown in red) can be seen

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa. around the areas of concern to this study, including Midrand; Tembisa; outer edges of Randburg; Sandton; Alexandra; Woodmead and Lethabong.

4.4 Climate

4.4.1 Average Historical Rainfall Patterns within Gauteng The overall rainfall patterns in Gauteng were assessed using existing literature pertaining to the period of measurement. Dyson (2009) assessed the average rainfall patterns within Gauteng over a 32 year period between 1977 and 2009. Mackellar (2014) assessed the 50 year rainfall period between 1960 and 2010 throughout South Africa. This data, discussed here, will provide a basic comparative average of rainfall running concurrently, but over a portion of the entire 28 period. This is because these results do not run alongside the available water quality data recorded by DWA from 1986 to 2014 and do not correspond exactly. However, these data still provide an understanding of the rainfall trends and how they relate to water quality changes.

Dyson (2009) collated and assessed the Gauteng rainfall using data recorded over the 32 year period from 58 rainfall stations across Gauteng. Some data that were included ranged for shorter periods within this longer period.

Gauteng Average Rainfall 1977 - 2009 1200

1000

800

600

400

200

0 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 average

Early Summer Late Summer Total Linear (Total)

Figure 8: Gauteng average rainfall from 1977 to 2009 (After Dyson, 2009)

When combining the general rainfall patterns (Figure 9) with the overall changes over the period of 1991 to 2009, the slight increase in rainfall visible over the period of 1986 to 2014 is evident. The increase in conversion of land to urban uses with impermeable surfaces is also evident. The general increases in

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa. both rainfall and impermeable surfaces can contribute to a cumulative increase in storm water on impermeable surfaces over time.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

5 RESULTS AND DISCUSSION

5.1 Introduction

In order to fully understand the changes in water quality many factors have been taken into consideration, including: average rainfall patterns across Gauteng during the period, land use changes and average seasonal flow rates. The average seasonal flow rates were also measured at each monitoring site. The increase in flow rates in cubic metres will be compared to the changes in water quality at each site.

Each site will also be discussed with reference to the standards and guidelines discussed in section 4.1.2. They will then be compared to one another in terms of their changes in water quality.

5.1.1 Average Seasonal Flow Rates (DWA, 1986 to 2014) Average seasonal flow rates in cubic metres on all three sites (Figure 10, Figure 11 and Figure 12) show a pattern of significant increases in flow rates over time. These measurements were obtained from the Department of Water Affairs and taken over the full 28 year period. The peak flows may be as a result of urban development in the catchment area. This can be ascribed to the fact that large areas of land surface are being covered by impervious materials due to the apparent increase of urban development activities in the area (Botha, 2005). It can be noted that during the high flow period (summer) dilution is expected to take place (Campbell, 1996). It is expected that these increases over time may contribute to dilution of the chemical constituents of the water as it is evident in the results that the increased dilution occurs simultaneously with the decreases in concentrations. This will be compared to the average water quality patterns over the 28 year period.

A21 90169 Average Flow cubic metres 45.00 40.00 35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00

SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014 SUMMER 2015

Figure 9: Average cubic metre flow rates at Site A

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

A21 90189 Average flow cubic metres 200 180 160 140 120 100 80 60 40 20 0

Figure 10: Average cubic metre flow rates at Site B

A21 90191 Average flow cubic metres 3

2.5

1.5

0.5

0 WINTER2000 WINTER2001 WINTER2002 WINTER2003 WINTER2004 WINTER2005 WINTER2006 WINTER2007 WINTER2008 WINTER2009 WINTER2010 WINTER2011 WINTER2013 WINTER2014 WINTER2014 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998

Figure 11: Average cubic metre flow rates at Site C

5.2 Water Quality Data Analysis

5.2.1 Analysis of Historical Water Quality (DWA - 1986 to 2014) The water quality status assessment was based on the data obtained from the routine monitoring conducted by DWA at various sites along the Jukskei River. It is important to note that this is a high- level quantitative assessment of historical water quality of sections of the Jukskei River in the middle reaches of the river, just outside of the built up areas and downstream of most urban and commercial activities.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

According to van Veelen (2004), the Electrical Conductivity will generally be diluted by the time the Jukskei River meets the Crocodile River, and therefore the effect is much reduced. Although the quality of water is not ideal, there is no reason for environmental management concern. The pH values in the lower Jukskei River increased significantly since 1977.

The sulphates are a measure of the impact of mining activity within the system, and chlorides as well as nitrates indicate the agricultural impacts and discharge of sewage effluent and industrial impacts. The ammonia levels indicate toxicity and pH indicates mining impacts as well as natural variability (DWA, 2011).

Here the variations in water quality at each site are discussed in detail in an attempt to ascertain the differences between these sites, so as to quantify them and elucidate the reasons for their differences. The water quality threshold limits used were extracted from Table 4 and table Table 5 in section 4.1.2. These are the international standards and the South African Total Water Quality Range (DWA, 1996), respectively. The lowest limit for each element was used in all cases. This limit or standard used was from any of the standards where the limit expressed was lowest. This is in order to fully understand any limit exceedances.

5.2.2 Site A (DWA A21 90169), Site B (DWA A21 90189) and Site C (DWA A21 90191) Water Quality The water collected at Site A shows an overall change in quality (Table 9, Table 10 and Table 11; Figure 13, Figure 14 and Figure 15). The incremental increase in pH may be attributed to anthropogenic eutrophication in the study area (Dallas & Day, 1993). During the late 1980s and early 1990s, the fluoride, ammonia and nitrate levels showed an exceedance of guideline limits. Thereafter, the levels show a slow and steady decline in these values, with a spike in ammonia intermittently between 2006 and 2014. Changes in fluoride correlate with the changes in calcium concentrations as per results. This may suggest a common source for both. The exceedance limits are represented in Table 9, Table 10 and Table 11 as red blocks and those concentrations under the threshold limits of all or any of the guidelines represented in this study are represented in green.

The geological factors regarding the changes in water quality have not been assessed. Instead, the changes in concentration of certain water quality elements have been mainly assessed in terms of their relation to surrounding land uses. The potential sources are highly varied as the landscape is made up of many infrastructural as well as natural elements.

In addition, the flow rates over time will correlate directly with the water quality patterns per season over the 28 year period. The evident increase in flow rates may contribute to the dilution of water quality constituents.

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 12: Comparison of water quality for Site A (A21 90169)

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 9: Seasonal water quality averages showing threshold exceedances in colour - Site A (DWA Monitoring point A21 90169) DMS SEASON Cl Ca (TDS) EC F K Mg Na NH4 NO3 pH PO4 SO4 1986 SUMMER 89.97 76.73 762.33 87.73 2.14 15.33 21.57 95.93 10.10 28.47 6.82 0.72 278.87 1986 WINTER 89.19 76.51 788.14 113.53 2.62 17.89 17.47 111.73 7.82 30.12 7.26 1.57 257.37 1987 SUMMER 51.71 56.96 509.00 75.02 1.55 10.01 19.39 55.16 2.54 15.25 7.36 0.51 144.73 1987 WINTER 77.60 68.00 688.10 105.44 1.63 14.61 21.31 92.69 3.11 24.34 7.19 0.34 206.60 1988 SUMMER 59.10 56.80 501.00 77.37 1.69 10.62 18.93 56.65 2.67 19.63 6.94 0.31 155.10 1988 WINTER 71.88 65.41 637.38 98.05 2.35 13.77 20.16 79.76 4.74 23.00 7.16 1.43 178.39 1989 SUMMER 52.96 52.31 473.00 69.07 1.40 11.04 14.84 53.53 2.46 16.56 6.99 0.57 117.96 1989 WINTER 61.27 51.52 508.00 74.94 1.16 11.25 15.73 62.93 3.46 10.29 8.05 0.17 119.30 1990 SUMMER 51.51 42.96 403.86 59.26 1.12 10.43 11.86 50.10 2.81 7.77 8.19 0.20 105.33 1990 WINTER 89.46 59.63 602.25 76.39 1.14 14.36 19.45 80.13 2.61 11.23 7.85 0.89 161.81 1991 SUMMER 48.66 36.73 344.75 56.57 0.70 9.53 11.77 40.26 0.91 9.54 7.39 0.36 83.49 1991 WINTER 81.20 47.17 515.67 75.96 0.80 13.65 17.28 75.42 0.40 9.70 7.69 0.35 127.11 1992 SUMMER 62.47 38.15 422.00 62.71 0.69 12.79 11.97 62.45 0.69 6.34 7.77 0.21 90.08 1992 WINTER 66.96 37.01 451.49 65.42 0.69 14.54 12.74 71.57 0.37 7.59 7.63 0.41 92.11 1993 SUMMER 51.52 34.07 350.04 53.93 0.60 11.18 9.80 47.82 0.59 7.67 7.56 0.43 71.66 1993 WINTER 61.65 43.93 408.64 61.92 0.55 12.94 8.72 58.72 0.11 11.13 7.60 0.66 77.01 1994 SUMMER 51.75 47.37 403.00 60.23 0.67 10.95 12.49 46.59 0.94 11.22 7.79 0.28 84.94 1994 WINTER 68.57 48.40 457.00 65.68 0.71 13.60 10.63 62.88 0.77 10.66 7.97 0.39 82.24 1995 SUMMER 57.98 40.07 381.58 56.90 0.71 12.40 9.65 49.77 1.16 9.89 7.90 0.37 68.70 1995 WINTER 59.22 44.52 420.28 60.90 0.71 11.85 10.52 53.48 1.00 10.74 7.94 0.25 70.93 1996 SUMMER 49.62 44.37 386.42 55.70 0.77 10.76 12.13 42.98 0.46 9.07 7.77 0.86 80.06 1996 WINTER 64.66 54.95 489.71 70.40 0.66 11.80 14.26 56.74 2.31 10.81 8.03 0.44 88.95 1997 SUMMER 49.25 43.95 391.13 57.55 0.48 10.28 12.16 45.05 0.59 7.90 7.92 0.54 72.28 1997 WINTER 54.67 48.92 461.54 63.79 0.48 10.42 17.77 51.17 0.87 9.80 7.97 0.45 92.13 1998 SUMMER 48.86 39.59 387.56 56.51 0.47 10.00 13.10 46.68 0.39 8.43 7.97 0.47 74.03 1998 WINTER 62.15 37.82 428.92 61.10 0.44 11.95 12.80 63.00 0.14 8.71 7.98 0.53 76.45 1999 SUMMER 50.14 37.38 375.33 55.99 0.48 9.86 12.74 48.03 0.37 8.07 7.89 0.85 73.04 1999 WINTER 59.95 36.84 409.20 63.03 0.46 10.59 12.78 59.00 0.21 9.37 7.96 0.50 75.53 2000 SUMMER 49.50 38.05 364.22 56.64 0.42 9.29 12.08 44.96 0.16 6.96 7.79 0.66 69.33 2000 WINTER 56.85 48.23 427.34 64.90 0.32 9.99 13.97 48.11 0.30 8.01 7.97 0.41 71.27 2001 SUMMER 48.76 39.22 358.70 53.76 0.31 9.64 12.15 41.34 0.45 6.06 7.88 0.60 56.13 2001 WINTER 56.21 35.94 382.03 57.58 0.29 10.79 13.83 49.96 0.29 6.52 8.02 0.45 56.39 2002 SUMMER 44.94 33.01 337.31 51.94 0.31 9.59 13.23 39.11 0.16 6.46 8.04 0.40 52.18 2002 WINTER 45.66 31.52 333.16 55.49 0.26 9.68 10.04 44.48 0.20 6.44 8.06 0.27 43.56 2003 SUMMER 51.43 33.15 339.08 52.71 0.32 10.29 10.34 41.28 0.19 6.06 7.96 0.39 53.07 2003 WINTER 60.43 34.04 391.99 59.30 0.32 12.04 10.76 58.00 0.37 6.08 7.87 0.48 50.11 2004 SUMMER 49.37 36.12 343.71 50.46 0.33 9.92 9.63 44.68 0.04 4.49 7.63 0.35 48.72 2004 WINTER 54.26 37.97 382.22 57.86 0.31 10.69 10.84 53.21 0.13 5.81 7.66 0.14 53.18 2005 SUMMER 44.33 34.03 312.47 48.91 0.28 9.11 8.67 39.12 0.23 4.16 7.68 0.19 43.01 2005 WINTER 55.03 40.20 389.39 59.38 0.29 10.88 11.31 50.60 0.27 6.46 7.86 0.24 55.12 2006 SUMMER 52.68 41.24 368.77 56.89 0.28 10.28 10.83 43.51 0.52 6.48 7.74 0.57 54.09 2006 WINTER 58.85 45.78 415.65 59.22 0.30 11.03 11.86 49.34 0.79 6.23 7.81 1.06 53.05 2007 SUMMER 49.85 37.47 350.31 52.19 0.29 10.24 9.90 43.45 0.92 4.17 7.97 1.20 44.56 2007 WINTER 55.54 34.57 370.15 57.10 0.27 10.77 11.49 52.45 0.44 4.57 7.80 0.62 46.88 2008 SUMMER 50.99 39.04 369.41 55.26 0.30 9.04 12.42 44.70 0.43 4.26 7.78 0.84 56.57 2008 WINTER 60.67 37.92 385.87 58.68 0.28 9.66 14.19 51.69 0.69 6.12 7.88 0.60 57.94 2009 SUMMER 57.81 39.39 51.91 8.09 13.70 40.70 0.21 5.17 7.93 0.69 56.60 009 WINTER 60.16 37.35 391.47 57.99 0.31 9.09 14.10 52.16 0.15 4.94 7.83 0.26 53.34 2010 WINTER 53.75 39.11 56.52 8.02 13.53 44.11 0.19 5.56 7.88 0.34 54.27 2010 WINTER 60.28 41.72 417.83 59.11 0.31 8.53 15.14 46.47 0.23 6.54 7.68 0.33 61.26 34

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

DMS SEASON Cl Ca (TDS) EC F K Mg Na NH4 NO3 pH PO4 SO4 2011 SUMMER 49.78 40.21 380.22 53.97 0.28 8.62 15.41 43.14 0.21 5.09 7.78 0.33 57.01 2011 WINTER 55.31 41.18 408.08 56.38 0.40 8.57 15.83 48.76 0.10 6.44 7.80 0.30 57.88 2012 SUMMER 46.51 35.51 317.94 49.71 0.36 7.95 12.49 39.59 0.11 3.65 7.66 0.62 46.58 2012 WINTER 56.59 37.05 395.59 57.65 0.37 9.94 13.55 53.31 1.48 4.41 8.14 1.32 46.78 2013 SUMMER 49.57 34.51 351.46 52.50 0.32 8.04 11.63 44.99 1.19 5.05 8.13 0.84 44.17 2013 WINTER 51.75 34.73 382.97 56.81 0.32 9.42 12.82 52.66 1.14 5.18 8.22 0.38 52.84 2014 SUMMER 50.30 35.53 376.04 51.75 0.37 7.80 12.62 48.28 1.34 5.03 7.82 0.40 53.86 2014 WINTER 63.91 35.80 59.38 0.54 15.61 3.04 4.91 8.14 0.63 56.31

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 10: Seasonal water quality averages showing threshold exceedances in colour - Site B (DWA Monitoring point A21 90189) DMS SEASON Cl Ca (TDS) EC F K Mg Na NH4 NO3 pH PO4 SO4 SUMMER 1986 65,70 53,84 525,22 78,46 1,16 14,12 14,07 71,56 2,36 15,24 7,24 1,66 165,73 WINTER 1986 75,69 54,51 572,70 87,51 1,42 15,00 11,96 89,84 1,79 18,26 7,42 1,51 161,63 SUMMER 1987 52,25 46,50 429,56 65,04 1,11 10,61 13,71 55,94 1,25 12,39 7,27 0,93 114,81 WINTER 1987 72,44 55,03 573,64 86,12 1,10 13,90 16,49 83,28 1,93 17,28 7,34 1,63 151,26 SUMMER 1988 61,98 52,48 489,00 75,81 1,41 11,75 15,80 62,38 2,06 16,41 7,10 1,18 135,32 WINTER 1988 64,71 52,30 537,85 80,65 1,76 13,12 15,92 74,07 1,96 15,17 7,38 2,28 130,86 SUMMER 1989 51,04 44,22 423,50 65,53 1,20 11,06 12,28 53,45 0,91 12,41 7,08 1,00 94,75 WINTER 1989 64,45 51,12 525,27 71,77 1,30 12,21 15,12 69,66 2,64 12,39 7,92 0,93 124,43 SUMMER 1990 52,63 40,94 397,52 55,72 1,02 11,19 11,33 52,61 0,71 10,40 8,01 1,23 91,51 WINTER 1990 79,75 47,88 509,25 69,77 1,00 13,41 15,25 71,78 0,82 12,60 7,94 1,55 123,26 SUMMER 1991 60,97 39,19 395,68 54,38 0,88 11,97 11,97 52,14 0,25 10,92 7,73 1,20 90,09 WINTER 1991 79,68 42,51 482,97 72,50 0,64 13,86 15,18 71,89 0,17 9,14 7,90 0,40 102,67 SUMMER 1992 62,69 35,17 413,31 60,36 0,71 13,18 11,11 63,46 0,19 5,54 7,88 0,26 82,07 WINTER 1992 74,99 38,38 484,10 71,43 0,77 14,86 13,53 78,68 0,29 6,05 8,06 0,38 98,72 SUMMER 1993 47,18 32,45 334,31 50,67 0,59 10,90 9,34 45,79 0,45 5,07 8,00 0,33 63,35 WINTER 1993 63,18 43,58 426,46 62,94 0,52 12,83 8,99 64,17 0,19 8,75 7,82 0,67 77,96 SUMMER 1994 49,67 45,76 393,81 57,77 0,65 10,40 12,27 45,94 0,68 10,18 7,85 0,28 84,03 WINTER 1994 67,07 47,89 453,70 65,33 0,72 13,19 10,94 63,49 0,33 8,95 8,03 0,41 83,02 SUMMER 1995 57,21 39,94 379,56 56,40 0,68 12,02 9,82 50,94 0,67 8,77 7,99 0,36 67,75 WINTER 1995 62,30 45,67 434,32 63,28 0,69 11,79 11,30 56,88 0,64 9,86 7,95 0,26 75,96 SUMMER 1996 51,20 42,78 383,38 56,21 0,66 10,07 11,95 45,34 0,42 7,65 7,82 0,50 76,30 WINTER 1996 65,55 54,52 485,04 70,59 0,64 11,38 14,45 58,28 0,83 10,53 8,04 0,41 89,74 SUMMER 1997 47,42 43,47 386,28 56,30 0,50 9,82 12,54 44,24 0,46 7,27 8,04 0,41 72,74 WINTER 1997 54,46 47,41 452,69 63,72 0,46 10,30 16,86 52,11 0,32 8,79 8,02 0,32 86,71 SUMMER 1998 50,87 39,43 390,40 56,29 0,47 10,20 12,80 48,57 0,29 7,68 8,05 0,48 72,87 WINTER 1998 64,06 38,25 437,88 60,16 0,46 12,10 13,01 64,90 0,07 7,86 8,03 0,57 79,01 SUMMER 1999 49,20 35,50 357,54 53,19 0,44 9,51 11,86 46,41 0,19 6,36 7,91 0,65 65,61 WINTER 1999 60,46 36,40 409,36 62,42 0,44 10,38 13,04 59,07 0,13 8,10 7,99 0,52 73,21 SUMMER 2000 50,07 37,88 369,44 57,13 0,41 9,67 11,87 46,34 0,12 5,84 7,80 0,63 70,37 WINTER 2000 57,29 47,58 425,91 63,48 0,32 10,03 13,49 49,64 0,11 7,00 8,08 0,50 67,65 SUMMER 2001 48,90 38,29 351,09 53,08 0,32 9,34 12,02 41,76 0,09 4,78 7,91 0,43 56,12 WINTER 2001 57,95 36,00 394,15 58,64 0,29 10,79 14,96 52,45 0,11 6,30 8,13 0,50 57,77 SUMMER 2002 43,80 31,85 331,30 50,01 0,31 9,23 13,42 38,21 0,09 5,03 8,04 0,32 50,08 WINTER 2002 53,13 33,25 367,24 55,26 0,29 10,85 11,21 48,50 0,11 5,64 8,14 0,40 49,63 SUMMER 2003 48,00 32,79 322,47 51,75 0,31 9,57 10,03 39,21 0,06 4,58 8,02 0,31 48,33 WINTER 2003 61,27 33,84 400,77 59,07 0,33 11,94 10,91 60,24 0,15 5,05 7,97 0,56 52,43 SUMMER 2004 51,09 36,47 352,27 50,55 0,33 10,04 9,79 46,16 0,07 3,80 7,71 0,49 51,63 WINTER 2004 54,87 36,79 385,45 57,59 0,32 10,89 10,53 55,69 0,03 5,02 7,87 0,28 51,18 SUMMER 2005 43,12 32,45 311,42 47,68 0,30 8,97 8,15 40,16 0,28 3,56 7,70 0,28 42,67 WINTER 2005 58,78 37,79 388,71 59,48 0,28 10,98 10,55 54,81 0,13 5,73 7,94 0,39 48,82 SUMMER 2006 51,28 40,01 360,19 53,98 0,26 10,02 10,28 43,60 0,09 4,52 7,62 0,68 50,07 WINTER 2006 58,37 44,62 405,97 58,12 0,32 11,24 11,77 50,10 0,50 5,17 7,82 1,53 50,73 SUMMER 2007 50,18 34,99 338,25 51,02 0,30 10,01 10,10 44,24 0,15 4,02 7,97 0,99 42,78 WINTER 2007 54,14 31,22 357,49 55,18 0,27 10,99 11,54 51,06 0,22 4,38 7,87 0,80 46,91 SUMMER 2008 49,04 36,98 365,17 54,03 0,28 9,07 12,36 45,27 0,84 4,31 7,73 1,23 54,75 WINTER 2008 60,53 37,44 392,88 56,85 0,27 9,64 13,45 53,14 0,70 4,94 7,75 0,58 54,28 SUMMER 2009 51,57 36,13 48,83 8,27 11,94 41,55 0,18 5,97 7,82 0,76 49,87 WINTER 2009 60,85 36,51 57,39 9,37 13,15 52,24 0,19 6,60 7,85 0,53 54,65 SUMMER 2010 51,03 39,30 52,15 7,83 13,32 40,15 0,17 5,52 7,73 0,35 54,18 WINTER 2010 61,19 42,01 430,19 58,72 0,35 8,83 18,60 47,08 0,26 5,77 7,78 0,63 58,38 36

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

DMS SEASON Cl Ca (TDS) EC F K Mg Na NH4 NO3 pH PO4 SO4 SUMMER 2011 45,25 35,25 342,11 48,33 0,25 8,28 12,14 39,36 0,05 3,87 7,69 0,46 49,00 WINTER 2011 50,81 41,77 405,13 60,05 0,32 9,05 15,98 47,13 0,05 6,98 7,64 0,66 56,54 SUMMER 2012 43,34 34,28 350,46 49,19 0,36 8,59 11,69 42,29 0,03 4,26 7,60 0,95 43,95 WINTER 2012 52,03 35,77 393,19 58,66 0,35 9,75 13,08 53,53 1,44 4,71 8,01 1,99 46,46 SUMMER 2013 45,90 32,90 348,77 49,60 0,28 8,40 11,02 43,61 0,48 4,87 8,02 0,79 43,55 WINTER 2013 47,80 31,77 353,91 53,04 0,36 9,29 11,62 51,11 0,53 4,99 8,18 0,51 48,07 SUMMER 2014 43,81 32,55 328,96 46,29 0,47 7,15 11,39 44,44 0,34 4,93 7,73 0,58 48,61 WINTER 2014 54,37 34,06 57,45 0,35 15,05 0,78 7,16 7,90 1,31 53,76

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 13: Comparison of water quality for Site C (A21 90191)

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Table 11: Seasonal water quality averages showing threshold exceedances in colour - Site C (DWA Monitoring point A21 90191) DMS SEASON Ca Cl (TDS) EC F K Mg Na NH4 NO3 pH PO4 SO4 SUMMER 1986 25,25 18,55 177,00 31,50 0,29 3,13 9,15 11,30 0,10 0,46 8,15 0,04 23,85 WINTER 1986 32,68 22,70 240,20 34,43 0,23 3,47 11,92 18,54 0,06 0,43 8,20 0,02 25,66 SUMMER 1987 29,49 18,34 213,00 31,77 0,26 4,32 10,84 14,07 0,17 0,98 7,37 0,04 27,87 WINTER 1987 34,23 23,43 266,00 39,10 0,26 3,84 15,08 17,90 0,20 0,88 7,43 0,02 32,35 SUMMER 1988 31,14 20,35 232,95 34,57 0,27 3,93 12,62 15,02 0,15 0,93 7,37 0,03 29,46 WINTER 1988 33,02 21,70 273,00 39,46 0,40 3,07 16,76 17,10 0,14 1,08 7,55 0,10 31,08 SUMMER 1989 27,74 16,59 207,43 29,84 0,42 3,09 10,39 11,80 0,08 0,96 7,52 0,03 23,10 WINTER 1989 30,79 20,31 247,92 35,06 0,37 3,10 14,17 15,00 0,10 0,97 7,76 0,05 26,73 SUMMER 1990 24,04 15,97 186,71 26,37 0,27 3,80 8,93 12,74 0,15 0,93 8,13 0,03 19,77 WINTER 1990 32,70 25,05 268,00 34,47 0,27 2,83 15,33 17,00 0,10 0,94 8,25 0,02 25,05 SUMMER 1991 27,76 15,66 200,36 27,10 0,29 3,97 9,63 11,01 0,04 0,72 7,84 0,02 22,26 WINTER 1991 32,67 25,03 270,83 36,95 0,25 2,86 16,13 18,23 0,08 0,61 8,53 0,03 26,60 SUMMER 1992 28,73 16,34 211,00 31,19 0,34 4,19 10,19 12,53 0,11 0,43 8,30 0,02 17,81 WINTER 1992 35,78 26,07 308,00 43,90 0,31 5,60 15,95 24,92 0,08 0,36 9,18 0,04 34,25 SUMMER 1993 24,15 11,23 181,33 27,02 0,39 3,88 7,62 11,07 0,37 0,68 8,48 0,04 22,95 WINTER 1993 37,17 24,35 277,67 38,52 0,38 4,96 12,38 19,20 0,05 0,50 8,62 0,03 23,73 SUMMER 1994 32,53 15,67 238,86 33,36 0,35 3,73 10,67 13,83 0,06 0,85 7,89 0,03 32,46 WINTER 1994 36,33 21,63 301,43 39,44 0,40 3,87 17,34 18,94 0,05 1,08 8,54 0,03 34,41 SUMMER 1995 32,60 16,02 234,20 31,02 0,41 4,73 9,26 14,80 0,10 0,42 8,26 0,02 21,04 WINTER 1995 33,42 19,80 264,00 34,54 0,49 4,25 12,94 15,18 0,08 0,95 8,15 0,04 30,12 SUMMER 1996 26,28 15,72 205,33 30,53 0,22 4,46 9,37 12,68 0,06 0,79 8,03 0,08 28,75 WINTER 1996 38,21 22,71 306,00 42,16 0,25 4,31 16,20 18,64 0,21 1,76 8,48 0,04 31,53 SUMMER 1997 31,32 16,77 241,50 31,47 0,22 3,76 12,00 14,12 0,23 1,21 8,20 0,04 23,48 WINTER 1997 39,77 24,74 317,57 42,76 0,23 3,15 18,03 19,63 0,13 2,12 8,49 0,03 37,80 SUMMER 1998 29,96 18,86 246,00 33,76 0,23 3,53 12,02 15,60 0,06 1,39 8,30 0,02 26,50 WINTER 1998 30,64 19,77 252,23 35,43 0,22 3,57 12,40 16,85 0,06 1,29 8,26 0,02 28,12 SUMMER 1999 26,02 16,48 197,33 27,88 0,24 3,24 9,33 12,32 0,04 1,07 8,14 0,03 23,77 WINTER 1999 32,19 26,24 274,43 39,97 0,23 2,82 14,94 19,14 0,07 1,16 8,30 0,03 28,59 SUMMER 2000 32,77 23,36 254,90 38,16 0,21 3,78 10,93 18,78 0,07 1,74 8,06 0,14 35,25 WINTER 2000 38,00 26,98 298,26 42,77 0,22 3,11 14,53 18,79 0,12 1,52 8,37 0,04 31,54 SUMMER 2001 22,69 16,77 183,02 25,84 0,20 3,08 8,50 12,12 0,08 0,80 7,92 0,06 21,04 WINTER 2001 35,13 27,75 284,76 40,52 0,21 2,83 15,32 20,16 0,11 1,42 8,28 0,08 28,37 SUMMER 2002 24,87 17,68 205,20 29,64 0,20 3,47 10,64 13,54 0,11 0,87 7,95 0,04 21,53 WINTER 2002 33,89 29,19 275,43 39,90 0,20 3,37 14,65 16,99 0,08 1,41 8,32 0,05 24,95 SUMMER 2003 26,82 19,39 205,82 30,60 0,23 3,35 8,47 12,88 0,08 0,83 7,99 0,05 24,20 WINTER 2003 32,65 25,06 267,18 37,35 0,25 3,47 12,50 20,61 0,04 0,86 8,35 0,08 26,69 SUMMER 2004 32,42 24,37 242,42 35,38 0,27 4,30 10,67 18,31 0,06 0,66 7,89 0,06 22,21 WINTER 2004 36,60 31,50 296,82 42,63 0,24 3,08 15,67 21,53 0,05 0,95 8,16 0,05 25,81 SUMMER 2005 30,51 24,14 230,07 33,87 0,23 3,85 10,02 14,96 0,09 0,89 7,84 0,04 21,58 WINTER 2005 38,06 34,80 306,96 45,34 0,23 3,08 16,04 21,53 0,44 1,13 8,18 0,13 26,54 SUMMER 2006 37,56 30,92 276,02 42,28 0,23 4,24 12,41 19,47 0,07 1,13 7,98 0,05 34,70 WINTER 2006 37,94 34,87 299,46 42,99 0,23 3,11 15,59 21,05 0,07 1,37 8,22 0,07 29,57 SUMMER 2007 30,38 23,03 223,14 32,95 0,24 3,50 10,34 14,45 0,15 0,85 8,00 0,07 24,13 WINTER 2007 35,50 33,22 287,65 43,07 0,23 3,34 13,95 22,71 0,28 0,72 8,02 0,05 27,40 SUMMER 2008 32,55 28,04 256,86 37,10 0,22 3,76 11,20 19,19 0,80 1,05 7,93 0,17 27,06 WINTER 2008 33,58 32,02 268,29 41,54 0,19 3,11 15,12 19,60 0,29 1,33 7,95 0,07 31,66 SUMMER 2009 34,41 32,00 292,97 40,84 0,19 3,46 14,81 17,40 0,30 1,15 8,09 0,05 33,61 WINTER 2009 37,00 39,67 310,20 43,50 0,17 3,18 17,41 21,64 0,19 1,31 8,03 0,03 32,28 SUMMER 2010 36,17 34,00 41,72 3,57 14,02 18,79 0,53 1,87 8,08 0,08 33,47 WINTER 2010 34,90 38,14 319,88 41,54 0,26 3,11 15,76 19,40 0,07 1,46 7,84 0,03 32,25 39

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

DMS SEASON Ca Cl (TDS) EC F K Mg Na NH4 NO3 pH PO4 SO4 SUMMER 2011 30,85 29,76 258,38 34,16 0,18 3,22 13,27 15,49 0,25 1,32 8,10 0,02 26,63 WINTER 2001 32,62 31,80 261,98 38,73 0,28 3,22 15,43 18,91 0,03 1,83 7,89 0,01 29,60 SUMMER 2012 30,91 28,21 245,04 36,11 0,34 3,43 12,25 16,26 0,03 0,87 7,77 0,01 23,98 WINTER 2012 31,32 30,79 247,28 36,89 0,27 3,54 14,21 17,89 0,06 1,25 8,25 0,02 24,50 SUMMER 2013 30,00 27,29 245,11 33,72 0,28 3,50 11,92 16,30 0,11 1,06 8,16 0,02 21,06 WINTER 2013 31,86 29,62 272,38 38,89 0,27 3,74 15,76 20,32 0,21 1,45 8,35 0,03 25,39 SUMMER 2014 32,58 32,29 251,64 39,55 0,30 3,45 13,37 18,36 0,19 1,26 8,16 0,03 28,31 WINTER 2014 30,12 33,63 38,08 0,42 14,00 0,41 1,79 8,10 0,02 28,58

A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

5.3 Analyses of Physical Determinands

The physical determinands, which generally determine the aesthetic properties of the water include the following:

5.3.1 pH A change in pH (Figure 16, Figure 17 and Figure 18) may have severe effects on aquatic biota. However, it is important to note that some streams are naturally more acidic than others. Gradual reductions in pH may result in a change in aquatic biological community structure, with acid-tolerant organisms replacing less tolerant ones. The discharge of acid wastes into water containing bicarbonate alkalinity may release free carbon dioxide, which may be toxic to fish (DWAF, 1996a). The corrosivity, solubility and speciation of metal ions in water are all influenced by pH. The potential toxicity of ions is influenced by pH (DWAF, 1996b). Water with a high pH usually tastes bitter and/or soapy, and water with a low pH tastes sour (DWAF, 1996a). In the case of Site A and B of the Jukskei River, the pH is evidently increasing over time since 1986, although the increase in pH levels has remained within the prescribed limits of the various standards in the comparison below. Most indices suggest that pH values between 5.5 and 9.5 are not detrimental to human health. According to the Total Water Quality Range data of DWA (1996), there is no significant effect on health with a pH of between 6.0 and 9.0. This is because metal ions are unlikely to dissolve readily unless complexing ions or agents are present (DWA, 1996). Slight metal solubility begins to increase below pH 6, and amphoteric oxides may begin to dissolve above pH 8.5. This may slightly alter the taste of the water.

pH A21 90169 (Site A) 12.00 10.00 8.00 6.00 4.00 2.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

pH_Diss_Water SABS 2011 SABS 2006 LOWER SABS 2006 UPPER WHO 4th Ed LOWER WHO 4th Ed UPPER EU 1998 LOWER EU 1998 UPPER

Figure 14: pH at Site A

41 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

pH A21 90189 (Site B) 12 10 8 6 4 2 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

pH_Diss_Water SABS 2011 SABS 2006 LOWER SABS 2006 UPPER WHO 4th Ed LOWER WHO 4th Ed UPPER EU 1998 LOWER EU 1998 UPPER

Figure 15: pH at Site B

pH A21 90191 (Site C) 12 10 8 6 4 2 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

pH_Diss_Water SABS 2011 SABS 2006 LOWER SABS 2006 UPPER WHO 4th Ed LOWER WHO 4th Ed UPPER EU 1998 LOWER EU 1998 UPPER

Figure 16: pH at Site C

4.3.1.1. Comparison of pH levels at each site

Shown in Figure 19, in the combination of site pH, Site C falls within the reference conditions as set within the upper and lower limits for both international and local guidelines and standards. The pH of Site A shows an increase in pH measured in 1986 at 6.82 and in 2014, Site A was measured as having a pH of 8.14. The highest recorded pH on Site A was 8.22 during the winter of 2013. During 1986, the pH at Site B was measured at 7.24 and was measured in 2014 as having a pH of 7.90. The highest recorded pH on Site B was 8.18 during the winter of 2013.

42 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

The increase in pH over the 28 year period shows a spike during the period of 1990 to 1991. This increase in pH may adversely affect biota (Morrison et al., 2001). Increased pH can influence the toxicity of ammonia, making it more toxic at a pH of higher than 8.5.

pH 10.00 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

PH SITE A PH SITE B PH SITE C

Figure 17: pH Comparison of sites

5.3.2 Electrical Conductivity Electrical Conductivity (EC) (Figure 20, Figure 21 and Figure 22) is defined as a measure of the ability of water to conduct an electrical current (DWAF, 1996a), and it is due to the presence of dissolved ions in the water (DWAF, 1996). EC increases as the concentration of dissolved ions increases (most importantly calcium, magnesium, and bicarbonate) (Matowanyika, 2010). It is an indication of salination of water resources (DWA, 2011). EC is important for understanding other physical aspects of water quality, and is interdependent on TDS (Sheppard, 2013).

43 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Electrical Conductivity A21 90169 (Site A) 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 2010 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2011 2012 2013 2014 WINTER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER SUMMER

EC_Phys_Water SABS 2011 SABS 2006 SABS 2006 EU 1998

Figure 18: Electrical Conductivity at Site A

Electrical Conductivity A21 90189 (Site B) 400 350 300 250 200 150 100 50 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

EC_Phys_Water SABS 2011 SABS 2006 SABS 2006 EU 1998

Figure 19: Electrical Conductivity at Site B

44 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Electrical Conductivity A21 90191 (Site C) 400 350 300 250 200 150 100 50 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

EC_Phys_Water SABS 2011 SABS 2006 SABS 2006 EU 1998

Figure 20: Electrical Conductivity at Site C

5.3.2.1. Comparison of EC at each site

Above 70 mg/l and below 150 mg/l the water has a slightly saltier taste but is still well tolerated in terms of health and aesthetic factors. The combined monitoring results for EC along the Jukskei River (Figure 23) were recorded as having EC values at Site A ranging from 87.73 mg/l during 1986 to 59.38 mg/l during 2014, with the highest recorded EC being 113.53 mg/l during the winter of 1986. Site B showed the EC during 1986 as 78.46 mg/l and then at 57.45 mg/l during 2014, with the highest recorded values at 87.51 mg/l in the winter of 1986. This shows that the water quality ranges are well within the acceptable limits of the TWQR, under 150 mg/l, with most of the values under the 70 mg/l limit. This makes the health and aesthetic effects tolerable. In terms of irrigation waters, the majority of the values are within the 40-90 mg/l where a 95% relative yield of moderately salt-sensitive crops can be maintained by using low frequency irrigation.

45 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Electrical Conductivity Comparison of sites 120.00 100.00 80.00 60.00 40.00 20.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMEMR 1994 SUMEMR 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 21: Electrical Conductivity Comparison of sites

5.3.3 Total Dissolved Solids/Dissolved Major Salts (TDS/DMS) Plants and animals possess a wide range of physiological mechanisms to maintain balance of water and dissolved ions. Changes in concentration of TDS can affect the adaptations of individual species, community structure and microbial and ecological processes such as metabolism (Mwangi, 2014).

The rate of change and duration of change in TDS (Figure 24, Figure 25 and Figure 26) associated with seasonal fluctuations, has important synergistic effects with water temperature on the total community composition and functioning. Changes in TDS concentrations should not exceed 15% from the normal cycle of the water body, and the amplitude and frequency of natural cycles should not be changed (DWAF, 1996b). Potential sources of TDS are associated with the pulp and paper mill industries, where waste water is high in organic and inorganic material (Ferreira, 2008).

46 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Total Dissolved Solids A21 90169 (Site A) 3000.00 2500.00 2000.00 1500.00 1000.00 500.00 0.00 SINTER2009 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMEMR 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

DMS_Tot_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed

Figure 22: TDS/DMS at Site A

DMS (TDS) A21 90189 (Site B) 3000 2500 2000 1500 1000 500 0 WINTER2010 WINTER2011 WINTER2012 WINTER2013 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008

DMS_Tot_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed

Figure 23: TDS/DMS at Site B

47 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Total Dissolved Solids A21 90191 (Site C) 3000 2500 2000 1500 1000 500 0 WINTER2010 WINTER2001 WINTER2012 WINTER2013 WINTER2014 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009

DMS_Tot_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed

Figure 24: TDS/DMS at Site C

5.3.3.1. Comparison of DMS levels at each site

The DMS values along the Jukskei River (Figure 27) were recorded as being below the threshold limit values according to water quality guidelines. During the winter of 1986 the TDS at Site A reached the highest recorded levels of 788.14mg/l and the lowest recorded concentration, at 312.47mg/l during the summer period of 2005. On the other hand, the TDS at Site B where the highest concentration is 573.64 mg/l during winter 1987 and the lowest at 311.42 mg/l during summer 2005, having a relatively lower overall concentration when compared to Site A. The changes in concentrations show a potential source for Site A, downstream of Site B.

While these levels displayed decreasing concentrations of TDS over the period, the concentrations of the Little Jukskei River remained relatively uniform with a less pronounced decrease in concentrations. It experienced the highest recorded level of 317.57 mg/l during the winter of 1997 and the lowest at 183.02 mg/l during summer 2001.

The TDS at all sites do not exceed the threshold values of 1000 mg/l although the presence of high levels in drinking water may be objectionable for consumers (WHO, 2003). The water containing elevated levels of TDS most likely originated from natural sources, sewage, urban runoff and industrial wastewater (WHO, 2003).

48 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

DMS Comparison of sites 900.00 800.00 700.00 600.00 500.00 400.00 300.00 200.00 100.00 0.00 WINTER2009 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMEMR 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMEMR 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 25: TDS/DMS Comparison of sites

5.4 Analyses of Chemical Determinands

5.4.1 Ammonia (NH4) Ammonia is an indicator of toxicity (DWA, 1996). It contains the following applicable 0 – 1.0: No health or aesthetic effects; 1.0 – 2.0: Possibly taste or odour complaints; 2.0 – 10.0: Objectionable taste and odour, interferes with chlorine disinfection; >10.0: Danger of forming nitrates and severely interferes with chlorine disinfection (DWAF, 1996a). Free ammonia will become more toxic to aquatic biota at a pH of more than 8.5 (Ferreira, 2008). The main problem associated with the Jukskei River catchment has been the elevated levels of ammonia (Figure 28, Figure 29 and Figure 30), mostly related to leaking sewers and undesirable conditions in Alexandra (van Veelen, 2002).

Ammonia A21 90169 (Site A) 12.00 10.00 8.00 6.00 4.00 2.00 0.00 2010 WINTER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014 SUMMER

NH4_N_Diss_Water SABS 2011 SABS 2006 LOWER SABS 2006 UPPER EU 1998

Figure 26: Ammonia at Site A

49 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Ammonia A21 90189 (Site B) 3 2.5 2 1.5 1 0.5 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

NH4_N_Diss_Water SABS 2011 SABS 2006 LOWER SABS 2006 UPPER EU 1998

Figure 27: Ammonia at Site B

Ammonia A21 90191 (Site C) 2.5 2 1.5 1 0.5 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

NH4_N_Diss_Water SABS 2011 SABS 2006 LOWER SABS 2006 UPPER EU 1998

Figure 28: Ammonia at Site C

5.4.4.1. Comparison of ammonia at each site

The highest levels of ammonia, shown in Figure 31, recorded over the period at Site A were 10.10 mg/l during the summer of 1986 and lowest levels of 0.04 mg/l during the summer of 2004. This site experienced exceedance of the international and TWQR threshold limits during 1986. Thereafter, the site experienced a decrease in concentrations. Site B concentrations were measured at 2.64 mg/l during the winter of 1989 and at the lowest levels at 0.03 mg/l during the winter of 2003.

By contrast, the Little Jukskei River showed the highest concentration at 0.53 mg/l during the summer of 2010, and the lowest concentration at 0.03 mg/l during the summer of 2012. The threshold limit of

50 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

1.0 mg/l according to SABS 2006 is generally not exceeded, however, the highest levels across all sites observed during 1986 exceeded this limit. The ammonia is an indicator of toxicity (WRC, 2012). The potential sources of ammonia may originate from AECI and Alexandra, where the high organic content of the water results in high COD concentrations (van Veelen, 2002).

Ammonia Comparison of sites 12.00 10.00 8.00 6.00 4.00 2.00 0.00 SUMEMR 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1987 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 29: Ammonia comparison of sites

5.4.2 Chloride (Cl) The chloride concentrations shown in Figure 32, Figure 33 and Figure 34 are only detectable by taste in concentrations higher than 200 mg/l (van Veelen, 2002). Concentrations greater than 12 000 mg/l will cause unacceptably salty tastes. Chloride concentrations >2000mg/l may cause nausea, and >10 000 mg/l may cause vomiting (DWAF, 1996b). While increased corrosion can be caused by a concentration of 50mg/l, chloride concentrations >200mg/l may reduce the lifespan of domestic appliances (DWAF, 1996b). Sewage is a rich source of chloride, and may indicate high pollution of water by effluent. A natural, healthy river is usually in the range of 15-35mg/l (EPA, 2001).

51 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Chloride A21 90169 (Site A) 700.00 600.00 500.00 400.00 300.00 200.00 100.00 0.00 WINTER2010 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Cl_Diss_Water SABS 2011 SABS 2006 WHO 4th Ed EU 1998

Figure 30: Chloride at Site A

Chloride A21 90189 (Site B) 700 600 500 400 300 200 100 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Cl_Diss_Water SABS 2011 SABS 2006 WHO 4th Ed EU 1998

Figure 31: Chloride at Site B

52 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Chloride A21 90191 (Site C) 700 600 500 400 300 200 100 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Cl_Diss_Water SABS 2011 SABS 2006 WHO 4th Ed

Figure 32: Chloride at Site C

5.4.2.1. Comparison of chloride at each site

The monitoring results for chloride along the Jukskei River at all sites (Figure 35) were below threshold levels. The highest level recorded at Site A was 89.97 mg/l during the summer of 1986 and lowest level of 44.33 mg/l during the summer of 2005. Site B showed the chloride during 1990 as 79.75 mg/l and the lowest level of 43.12 mg/l during the summer of 2005. The highest recorded value at Site C was 39.67 mg/l in the winter of 2009 and the lowest at 11.23 mg/l during the summer of 1993.

The water quality ranges are well within the acceptable limits of the TWQR under 200 mg/l, with most of the values under the 70 mg/l limit. The concentration of chloride falls within the acceptable limits at all times at all three sites. The chloride may be an indicator of agricultural impacts, sewage effluent discharges and industrial impacts (WRC, 2012).

Chloride Comparison of sites 100.00 90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 SUMMER 1086 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 33: Chloride comparison of sites

53 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

5.4.3 Fluoride (F) Low concentrations of fluoride strengthen tooth enamel and bones in mammals (DWAF, 1996a). However, exposure over long periods may cause fluorosis of tooth enamel and bones (DWAF, 1996a) although exposure in low concentrations can protect against dental caries (WHO, 2011). Total fluoride daily exposure can vary depending on the inputs of that catchment and a range of different practices (WHO, 2011). The apparent source of an increase in fluoride during the 1980s is the Modderfontein Industrial Complex. This may have diluted as it moved further away from the source (Figure 36, Figure 37 and Figure 38). The element fluoride is found naturally in the environment due to fluoride- containing minerals (Sheppard, 2013).

Fluoride A21 90169 (Site A) 3.00 2.50 2.00 1.50 1.00 0.50 0.00 SUMER 2001 WINTER2009 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

F_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed EU 1998

Figure 34: Fluoride at Site A

Fluoride A21 90189 (Site B) 2 1.5 1 0.5 0 WINTER2010 WINTER2011 WINTER2012 WINTER2013 WINTER2014 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008

F_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed EU 1998

Figure 35: Fluoride at Site B

54 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Fluoride A21 90191 (Site C) 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 WINTER2010 WINTER2001 WINTER2012 WINTER2013 WINTER2014 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009

F_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed EU 1998

Figure 36: Fluoride at Site C

5.4.3.1. Comparison of fluoride at each site

The fluoride concentration (Figure 39) at Site A during the winter of 1986 was 2.62 mg/l at the highest and 0.26 mg/l at the lowest. The monitoring results at Site B range from 1.76 mg/l during the winter of 1988 to the lowest 0.25 mg/l during the summer of 2011. Therefore, the highest values for site A and B exceed the water quality threshold values. Consequently, the dilution of the fluoride level from 1986 onwards at these two sites has health and aesthetic effects that are well tolerated. The possible reason for this dilution may be the increased flow over the same time period.

Site C showed the fluoride during 1995 as 0.49mg/l and then at its lowest 0.17 mg/l during the winter of 2009. The fluoride concentrations are well within the acceptable threshold limits of 1.0 mg/l at Site C. Fluoride is necessary for hardening of dental enamel and increased resistance to attack on tooth enamel by bacteria (DWAF, 1996A).

Fluoride Comparison of sites 3.00 2.50 2.00 1.50 1.00 0.50 0.00 WINTER2012 WINTER2009 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

55 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Figure 37: Fluoride comparison of sites

5.4.4 Phosphate (PO4) Elevated phosphorus concentration (Figure 40, Figure 41 and Figure 42) limits the growth of aquatic plants and causes eutrophication (van Ginkel, 2011). Inorganic phosphorus concentrations of less than 5 mg/l are sufficiently low to reduce the likelihood of algal and other plant growth (DWAF, 1996a).

The phosphate levels are a meaningful determinant in the assessment of eutrophication (EPA, 2001). The EPA (2001) also recommends mandatory limits at 0.7 mg/l. Phosphate exists within a eutrophic state according to the Cary Institute of Ecosystem Sciences (2015), where results reading higher than 0.3 mg/l indicate pollution from fertiliser, sewage, industrial waste or detergents.

Phosphate A21 90169 (Site A) 1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00

Figure 38: Phosphate at Site A

56 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Phosphate A21 90189 (Site B) 2.5

1.5

0.5

Figure 39: Phosphate at Site B

Phosphate A21 90191 (Site C) 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0

Figure 40: Phosphate at Site C

5.4.3.1. Comparison of phosphate levels at each site

The phosphate at Site A (Figure 43) during the winter of 1986 were measured at 1.57 mg/l, and at its lowest were measured at 0.14 mg/l during the winter of 2004. The phosphate concentrations at Site B during the winter of 1988 were at their highest level of 2.28 mg/l, and their lowest level of 0.26 mg/l during the summer of 1992. This shows that sites A and B were within the range of eutrophic waters for the majority of the 28 year period, but, were shown to decrease over time during the first decade. The potential sources of phosphate at these sites may include the upstream source from Alexandra

57 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Township in the form of raw sewage, as well as domestic and animal waste (Matowanyika, 2010). The phosphate concentration patterns do not correlate with the other elements found at these two sites.

The monitoring results at Site C show a relatively consistent upwards concentration of phosphate over time, with the lowest at 0.01 mg/l and the highest level at 1.17 mg/l. These values are indicative of clean water (Cary Institute of Ecosystem Science, 2015). This may be due to the fact that this site does not occur near or downstream of Alexandra or a Waste Water Treatment Works (WWTW).

Phosphate Comparison of sites 2.50 2.00 1.50 1.00 0.50 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 41: Phosphate comparison of sites

5.4.5 Calcium (Ca) The recommended dietary intake range for humans is 500 to 1400 mg/day (DWAF, 1996b). Calcium is known to mitigate the toxicity of certain heavy metals. However, scaling is a side effect on household appliances such as kettles. High concentrations also impair the lathering of soap by the formation of insoluble calcium salts DWAF, 1996b).

The effect of calcium on personal hygiene, water distribution systems and water heating appliances can be summarised as follows: 32 to 80 mg/l cause increased scaling problems and impaired lathering of soap. Levels higher than 80 mg/l will cause severe scaling problems and lathering of soap will be severely impaired (DWAF, 1996b).

Water containing high concentrations of calcium (Figure 44, Figure 45 and Figure 46), magnesium and to a lesser extent other elements is considered hard water. This may precipitate out and form a dense coating of predominantly inorganic material such as sulphates of calcium and magnesium hydroxides (DWAF, 1996b).

58 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Calcium A21 90169 (Site A) 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014 SUMMER 1992

Ca_Diss_Water sabs 2006 SABS 2006

Figure 42: Calcium at Site A

Calcium A21 90189 (Site B) 350 300 250 200 150 100 50 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Calcium SABS 2006 SABS 2006

Figure 43: Calcium at Site B

59 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Calcium A21 90191 (Site C) 350 300 250 200 150 100 50 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Ca_Diss_Water sabs 2006 SABS 2006

Figure 44: Calcium at Site C

5.4.5.1. Comparison of calcium levels at each site

The highest concentration of calcium at Site A (Figure 47) was recorded at 76.73 mg/l during the summer of 1986, and the lowest at 31.52 mg/l during the winter of 2002. The highest concentrations of calcium at Site B were recorded during the winter of 1987 at 55.03 mg/l, and at the lowest level of 31.22 mg/l during the winter of 2002.

Site C showed the highest calcium concentration during the winter of 1997 was 39.77 mg/l, and at its lowest level during the winter of 2001 it was recorded at 22.69 mg/l. The water quality ranges at Site C are well within the acceptable international threshold limits under 150 mg/l, with most values around 50 mg/l for all three sites.

Calcium Comparison of sites 90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 45: Calcium comparison of sites

60 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

5.4.6 Magnesium (Mg) Magnesium (Figure 48, Figure 49 and Figure 50) is readily excreted by the kidneys, while excess magnesium uptake will result in diarrhoea. Magnesium may also results in scaling and inhibiting lathering of soap (DWAF, 1996b). Hardness caused by calcium and magnesium is usually indicated by precipitation of soap scum and the need for excess soap to achieve cleaning. Hardness is in excess of 500 mg/l of magnesium. According to international guidelines, the threshold limit of 70 mg/l is not exceeded in the monitoring results at all sites.

Magnesium A21 90169 (Site A) 120.00 100.00 80.00 60.00 40.00 20.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Mg_Diss_Water SABS 2006 SABS 2006

Figure 46: Magnesium at Site A

Magnesium A21 90189 (Site B) 120 100 80 60 40 20 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Mg_Diss_Water SABS 2006 SABS 2006

Figure 47: Magnesium at Site B

61 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Magnesium A21 90191 (Site C) 120 100 80 60 40 20 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Mg_Diss_Water SABS 2006 SABS 2006

Figure 48: Magnesium at Site C

5.4.6.1. Comparison of magnesium levels at each site

The concentrations for magnesium (Figure 51) are relatively consistent over the time period, with the highest level at 21.31mg/l during the winter of 1987 and during the summer of 2005 at the lowest level of 8.67 mg/l at Site A. With Site B ranging from the highest concentration during the winter of 1987 at 16.49mg/l to the lowest during the summer of 2005 at 8.15 mg/l. These two sites are relatively similar in their changes over time.

Site C remains consistent over time, besides the highest levels and lowest levels close together over the timeline, with the highest reading at 18.03 mg/l during the winter of 1997, and the lowest during the summer of 1993 at 7.62 mg/l. The changes in concentrations at Site C are erratic and unpredictable, whereas those of site A and B are similar and show a downward trend.

Magnesium Comparison of sites 25.00 20.00 15.00 10.00 5.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 49: Magnesium comparison of sites

62 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

5.4.7 Potassium (K) Potassium’s (Figure 52, Figure 53 and Figure 54) effect on aesthetics and human health from 0 to 50 mg/l does not exist. The concentrations of 50 to 100 mg/l will have no health effects in healthy adults (DWAF, 1996b).

The potassium concentrations between 100 and 400 mg/l will cause electrolyte disturbances in the body, and concentrations higher than 400 mg/l will cause a bitter taste, nausea, vomiting and irritation of the mucous membrane (DWAF, 1996b).

Potassium A21 90169 (Site A) 120.00 100.00 80.00 60.00 40.00 20.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

K_Diss_Water SABS 2006 SABS 2006

Figure 50: Potassium at Site A

Potassium A21 90189 (Site B) 120 100 80 60 40 20 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

K_Diss_Water SABS 2006 SABS 2006

Figure 51: Potassium at Site B

63 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Potassium A21 90191 (Site C) 120 100 80 60 40 20 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

K_Diss_Water SABS 2006 SABS 2006

Figure 52: Potassium at Site C

5.4.7.1. Comparison of potassium levels at each site

At Site A, the highest (Figure 55) potassium levels are at 21.31 mg/l during the winter of 1986 and below the threshold limit of 50 mg/l, while the lowest concentrations are during the summer of 2014 at 7.80mg/l. The monitoring results at Site B range from the highest concentrations of 15.00 mg/l during 1986 to 7.15 mg/l during the summer of 2014. At these two sites the water quality ranges are well within the acceptable threshold limits under 50 mg/l, with most of the values under the threshold value and decreasing over time.

At Site C, the levels do not dilute over time, rather, they stay consistent. The highest level was recorded at 5.60 mg/l during the winter of 1992 and the lowest at 2.82 mg/l during the winter of 1999. The potassium concentrations are well tolerated. The potential origins of potassium include mining and derelict sites, as well as urban areas (WRC, 2009).

64 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Potassium Comparison of sites 20.00 15.00 10.00 5.00 0.00 WINTER2001 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 53: Potassium comparison of sites

5.4.8 Sodium (Na) The taste threshold for sodium in water varies from 153 to 200 mg/l. These are generally associated with mining and derelict and abandoned mines as well as urban areas (WRC, 2009). Concentrations ranging from 200 to 400 mg/l will cause a slightly salty taste and is undesirable for a person on a strict diet (DWAF, 1996b).

A higher concentration of sodium chloride and an alkaline pH is a suitable environment for faecal coliforms, especially Enterococcus sp. (WHO, 2011). This may contribute to the elevated levels of faecal coliforms reported to be in the Jukskei River, as well as the elevated phosphate levels in this monitoring data (Figure 56, Figure 57 and Figure 58).

Sodium A 21 90169 (Site A) 500.00 400.00 300.00 200.00 100.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Na_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed

Figure 54: Sodium at Site A

65 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Sodium A21 90189 (Site B) 450 400 350 300 250 200 150 100 50 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Na_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed

Figure 55: Sodium at Site B

Sodium A21 90191 (Site C) 450 400 350 300 250 200 150 100 50 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Na_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed

Figure 56: Sodium at Site C

5.4.8.1. Comparison of sodium levels at each site

The concentrations of sodium (Figure 59) at Site A and B are at their highest during the winter of 1986, at 111.73mg/l and 89.84mg/l respectively. The lowest recorded levels at these two sites were 39.12 mg/l during the summer of 2005 and during the summer of 2003 at 39.21 mg/l, respectively.

Site C showed sodium concentration during the winter of 1992 as 24.92mg/l and then at 11.01 mg/l during the summer of 1991. These values do not show a pattern similar to that of sites A and B. Instead, this site shows consistent values over time, whereas the changes over time reflect a steady decrease in concentration over the 28 year period. This is mostly evident at Site A.

66 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

The pulp and paper mill effluent contains toxic substances such as soaps and sodium salts. These are relatively resistant to biodegradation (Owens, 1991). These inputs have been diluted over time.

Sodium Comparison of sites 120.00 100.00 80.00 60.00 40.00 20.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 57: Sodium comparison of sites

5.4.9 Sulphate (SO4) Sulphate concentrations in the Jukskei River are represented in Figure 60, Figure 61 and Figure 62. High sulphate concentrations exert acute health effects such as diarrhoea. Concentrations below 200 mg/l will have no aesthetic or health effects, while concentrations of 200 to 400 mg/l will cause diarrhoea for sensitive individuals. Concentrations of 400 to 600 mg/l will cause diarrhoea in most non-adapted individuals (DWAF, 1996b).

Sulphate A21 90169 (Site A) 700.00 600.00 500.00 400.00 300.00 200.00 100.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

SO4_Diss_Water SABS 2011 LOWER SABS 2011 UPPER SABS 2006 LOWER SABS 2006 UPPER WHO 4th Ed EU 1998

Figure 58: Sulphate at Site A

67 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Sulphate A21 90189 (Site B) 700 600 500 400 300 200 100 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

SO4_Diss_Water SABS 2011 LOWER SABS 2011 UPPER SABS 2006 LOWER SABS 2006 UPPER WHO 4th Ed EU 1998

Figure 59: Sulphate at Site B

Sulphate A21 90191 (Site C) 700 600 500 400 300 200 100 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

SO4_Diss_Water SABS 2011 LOWER SABS 2011 UPPER SABS 2006 LOWER SABS 2006 UPPER WHO 4th Ed EU 1998

Figure 60: Sulphates at Site C

5.4.9.1. Comparison of sulphate levels at each site

During the summer of 1986 the sulphate concentrations (Figure 63) at Site A show the highest levels at 27.87 mg/l and the lowest concentration during the winter of 2002 at 43.56 mg/l. This is lower than the 250 mg/l international limit and the TWQR limit of 300 mg/l for aesthetic and health effects. A decrease in sulphate is observed over time on both Site A and Site B. Site B showed 165.73 mg/l during the summer of 1986 and 42.67 mg/l during the summer of 2005. The changes in sulphate concentrations over time are more pronounced at Site B.

68 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

However, Site C shows consistent levels over the 28 year time period. Low sulphate values are known to exist in high sodium chloride waters, and usually have a pH higher than 8 (Sheppard, 2013). As with the Jukskei River at these sites, the sodium and chloride levels are relatively low and the pH values remain consistent at 8.

The monitoring results along the Little Jukskei River (Site C) were recorded with concentrations ranging from the highest of 35.25 mg/l during the summer of 2000 to 17.81 mg/l during the summer of 1992. These values are all lower than those of Site A and B.

Sulphate Comparison of sites 300.00 250.00 200.00 150.00 100.00 50.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 61: Sulphate comparison of sites

5.4.10 Nitrate (NO3) Nitrate concentrations for all three sites are represented in Figure 64, Figure 65 and Figure 66. Upon absorption, nitrite combines with haemoglobin to form methaemoglobin, incapable of carrying oxygen. This is called methaemoglobineamia (van Veelen, 2002). Reactions with secondary and tertiary amines and amides form nitrosamines, which are carcinogens. The range of nitrate/nitrite at 0 to 6 mg/l have no health effects. The 6 to 10 mg/l range is generally well tolerated. At concentrations ranging from 6mg/l to 10mg/l, methaemoglobinaemia may occur in infants (DWAF, 1998).

A concentration higher than 20 mg/l will cause irritation in the mucous membrane of adults (DWAF, 1996b). The conversion of nitrites to nitrates is an indication that nitrification and denitrification is taking place (Campbell, 1996). As more ammonia is converted to nitrates, an increase in nitrite concentration is observed and an equilibrium will form (Campbell, 1996).

69 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Nitrate A21 90169 (Site A) 60.00 50.00 40.00 30.00 20.00 10.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

NO3_NO2_N_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed EU 1998

Figure 62: Nitrates at Site A

Nitrate A21 90189 (Site B) 60 50 40 30 20 10 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

NO3_NO2_N_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed EU 1998

Figure 63: Nitrates at Site B

70 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Nitrate A21 90191 (Site C) 60 50 40 30 20 10 0 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

NO3_NO2_N_Diss_Water SABS 2011 SABS 2006 SABS 2006 WHO 4th Ed EU 1998

Figure 64: Nitrates at Site C

5.4.10.1. Comparison of nitrate levels as each site

The nitrate concentrations (Figure 67) at Site A during winter 1986 is 30.12mg/l and during summer 2012 at 3.65mg/l. The concentration at Site B during winter 1986 is highest at 18.26mg/l and at the lowest concentration of 3.56 during summer of 2005.

The nitrate values along the Little Jukskei River (Site C) were recorded with concentrations ranging from the highest 1.87 mg/l during the summer of 2010 to the lowest of 0.36 mg/l during the winter of 1992. This can be compared to the ammonia levels. When ammonia concentrations start to decline, the uptake of nitrate by plants is greater than the production of nitrates by the nitrification process, and a decrease in nitrate is observed. In all three sites, the nitrates decreased over time. Although the threshold limits are exceeded intermittently at both Sites A and B between 1986 and 1995, the Little Jukskei River is well below the threshold limits.

71 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

Nitrate Comparison of sites 35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00 SUMMER 1986 SUMMER 1987 SUMMER 1988 SUMMER 1989 SUMMER 1990 SUMMER 1991 SUMMER 1992 SUMMER 1993 SUMMER 1994 SUMMER 1995 SUMMER 1996 SUMMER 1997 SUMMER 1998 SUMMER 1999 SUMMER 2000 SUMMER 2001 SUMMER 2002 SUMMER 2003 SUMMER 2004 SUMMER 2005 SUMMER 2006 SUMMER 2007 SUMMER 2008 SUMMER 2009 SUMMER 2010 SUMMER 2011 SUMMER 2012 SUMMER 2013 SUMMER 2014

Site A Site B Site C

Figure 65: Nitrates Comparison of sites

72 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

6 CONCLUSIONS It is evident that a steady increase in rainfall has happened over the 28 year period from the analysed data. However, Site C, the Little Jukskei shows little change to the concentrations to pollutants over this time period. This could potentially be related to the slower rate of development around this area over the period.

When comparing the Site A and Site C to the overall rainfall patterns for Gauteng, the increase in hydrological flow rates at these sites show significantly higher increases over time than the increase in rainfall over a similar period. The difference in ratio of increases comparing rainfall and hydrological flow rates may be due to increased development impacts experienced in the surrounding landscape.

The increasing flow rates are seemingly responsible for improving water quality for both the physical or chemical determinants. This is evident in the simultaneous increase in flow rates and the drastic reduction in most pollutant levels at Site A and Site B between 1986 and 1993, thereafter remaining under all threshold guideline values for water quality while still experiencing a slow and steady decline.

The pollutant concentrations shown in Site C (Little Jukskei) are all under the threshold values for almost the entire 28 year period, excluding the pH during the winters between 1991 and 1994. The reason for this pattern is unclear. However, the pollutant concentrations remain at a consistent value relative to the other two sites.

Land use changes around sites A and B were shown in Figure 5 and Figure 66. From this pattern, it is evident that the land use changes between Midrand, Alexandra and Tembisa have expanded. This may have contributed to the changes in water quality due to increasing storm water inputs, with an increased development impact over the period surrounding Site A and Site B.

It was noted that the most drastic changes in concentration levels of the majority of pollutants are exhibited during 1986 and 2005. In general, most of the parameters were recorded at their highest

concentrations during 1986. Many of the lowest concentrations including F, EC, NO3, SO4, Cl and

TDS recorded were during 2005, these include Na, NO3, SO4, Cl, Ca, EC, Mg and TDS on some of the sites. The reasons for this are not clear and should be investigated in further detail. This can be carried out during future studies as potential research problems.

During the winter of 1986, the associated season flow rate experienced by Site A was 2.28 m3 and at

3 Site B was 3.74 m with TDS, PO4, SO4, Na, NH4 and K. The lower flow rates in cubic metres recorded at these sites may be linked to the elevated concentrations of these elements during this time period. The flow in cubic metres during this time was at its lowest level over the time period. The summer of

2005 experienced the lowest concentrations for Mg, EC, Na, Cl, SO4 and NO3. The flow rates in cubic metres were recorded much higher at Site A as 17.87 m3 and at Site B were measured at 9.71 m3.

73 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

The overall concentrations of pollutants for Site A and Site B were shown to decrease over time. This correlates inversely to the increases in average water flows at these sites. The increased flow and increased urban land use coverage over the period may be responsible for the decrease in pollutant concentrations at these sites. The reasons for the more pronounced decrease in concentrations at Site A than Site B may be that Site A is downstream of Site B. This could be due to the increased incidence of development of impermeable surfaces in close proximity to Site B, whereas Site A is further from the urban edge.

Furthermore, it can be noted that the changes in concentrations are more pronounced overall at Site

C than both other sites. This is with the exception of pH and PO4. Site C shows no correlation of the cubic metre flow rates to the changes in pollutant concentration. The changes to the flow patterns show an increase over time, whereas the pollutant concentrations remain relatively constant over time.

Whilst the data from the Department of Water Affairs is not exhaustive and does exclude important water quality constituents, the microbiological data including faecal coliforms would assist in providing a more holistic understanding of the current state of water quality within the Jukskei River. However, the aim for this study was to understand the impact of pollution sources emanating from outside of the river banks. These sources would be from industry, vehicle emmissions, construction erosion and agriculture or landscaping.

74 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

7 RECOMMENDATIONS

7.1 Recommendations for Proper Land-use Management

According to a study by Burke and Bokako (2004) on the optimisation of surface water quality monitoring within the City of Johannesburg, the monitoring of water quality has operated via a three pronged approach, namely; chemical tests, biological surveys and toxicity testing. This approach has improved the characterisation of discharges entering the water resources and is therefore recommended for future studies.

A successful surface water quality management programme requires a water quality management institution that is integrated, flexible, efficient, effective and responsive for it to be successfully implemented. The management of water quality spans too many disparate institutions and organisation, which do not take an integrated approach to water resource management. Therefore different aspects of water management must be consolidated.

The impact of urban land uses on river water quality that was demonstrated in this case study suggests that the known land-water relationship is important for town planning and environmental management in order for these professions to make better recommendations.

7.1.1 Potential for Future Studies Data of compounds associated with suspended particulate matter have considerably higher sampling uncertainties than soluble constituents. This can be caused by the high variability of a river’s reach. Analytical errors contribute significantly to overall uncertainty of river water quality (Rode & Suhr, 2006).

Future studies that may be of benefit may include the assessment of reliability of third party water quality data and collection techniques. There may be a need for more detailed water collection timetables. These may include the exact coordinates, time of year, time of day and position along cross sections of the river, whether within the riparian zone or channel.

More frequent monitoring and more representative samples of a given river cross-section may be required. This will achieve proper representation of spatial variations for a particular cross-sectional area, thus giving a more detailed exposition of specific water quality parameters (Rode & Suhr, 2006).

An assessment of potential pollution sources within the landscape, such as industrial areas and their specific constituents, as well as changes or expansion thereof should be beneficial to understanding the specific management requirements of the Jukskei River catchment. Here, the specific land uses and expected or potential pollutants that would typically emanate from these sources can be mapped and integrated into a Geographic Information System (GIS). Accordingly, information on the different pollutant sources can be traced back by following pollution load contributions in particular parts of the

75 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa. water network. This information can assist in identifying target areas for prevention and intervention strategies (Roux, 2010).

76 A case study on the historical water quality trends pertaining to the Jukskei River in the Gauteng province, South Africa.

8 REFERENCES Armitage, N., Vice, M., Fisher-Jeffes, L., Winter, K., Spiegel, A & J. Dunstan. 2013. Alternative technology for Storm water Management. The South African Guidelines for Sustainable Drainage Systems. Water Research Commission (WRC) Report no. TT 558/13.

Braune, M. 2006. Phase 2 Study: Generic Guidelines and BMPs for Flood and Erosion Control SRK Report 350137/2.

Burke. J & T. Bokako. 2004. Optimisation of surface water quality monitoring within the city of Johannesburg. Proceedings of the 2004 Water Institute of Southern Africa (WISA) Biennial Conference. Cape Town, South Africa, 2-6 May 2004.

Campbell, L. A. 1996. The waste assimilation capacity of a reach of the Jukskei River just downstream of Alexandra Township Johannesburg: Water Research Group. University of the Witwatersrand.

Cary Institute. www.caryinstitute.org. 2015. Changing Hudson Project. [ONLINE] Available at: http://www.caryinstitute.org/sites/default/files/public/downloads/curriculum- project/4A1_Phosphate_reading.pdf. [Accessed 15 September 15].

City of Joburg. 2014a. City of Johannesburg 2013/2014 Group Annual Report. Johannesburg, South Africa.

City of Joburg. 2014b. City of Johannesburg: 2012/16 Integrated Development Plan: 2013/14 Review. Available at Johannesburg, South Africa.

City of Joburg. www.joburg.org.za. 2015. Official website of the City of Johannesburg, 2015. [ONLINE] Available at: http://joburg.org.za/index.php?option=com_content&view=article&id=5502:jukskei- cleaned&catid=120&Itemid=201. [Accessed 16 July 2015].

Dallas, H. F & J. A. Day. 1993. The effect of water quality variables on riverine ecosystems: A review, WRC Report No TT61/39, Water Research Commission, Pretoria.

De Jager, T. 1990. A Town planners dream/nightmare?, Housing in South Africa, March 1990, 16-19.

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Department of Water Affairs (DWA). 2014. Historical Water Quality Measurements of the Jukskei River from 1979 to 2014. South Africa.

Department of Water Affairs and Forestry (DWAF). 1996a. South African Water Quality Guidelines. Volume 7: Aquatic Ecosystems. CSIR, Pretoria.

Department of Water Affairs and Forestry (DWAF). 1996b. South African Water Quality Guidelines (second edition). Volume 1: Domestic Use.

Department of Water Affairs and Forestry (DWAF). 1996c. South African Water Quality Guidelines (second edition). Volume 4: Agricultural Use: Irrigation.

Department of Water Affairs and Forestry (DWAF). 1991. Water quality management policies and strategies in the RSA. Department of Water Affairs and Forestry, Private Bag X313, Pretoria, Republic of South Africa.

Directorate Water Resource Classification. Department of Water Affairs (DWA). 2011. Classification of significant water resources in the Mokolo and Matlabas catchments: Limpopo Water Management Area (WMA) and Crocodile (West) and Marico WMA: Ecological Water Requirements Report. Report No: RDM/WMA 1.3/00/CON/CLA/0312.

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