This paper discusses raw water quality results for the raw water from Bospoort dam in South Africa. A time series analysis was conducted for various parameters over a prolonged period of time. It was revealed that apart from conductivity, hardness, and high coliform counts, most parameters were below their recommended threshold levels for the greatest part of the study period.

Background

The South African constitution states that everyone has a right to have access to an environment that is not harmful to their health or well-being. This includes a constant supply of clean and safe drinking water. In order to fulfil this constitutional right, it is imperative to carry out continuous monitoring of water at different stages of the water supply system so that real data can be obtained about the state of water quality in the environment. Management interventions can then be made to maintain or improve water quality.

Magalies Water is a state-owned entity providing a wide range of related water and sanitation services in South Africa, and operates in four provinces that include Gauteng, Limpopo, North West and Mpumalanga. It obtains a significant fraction of its raw water from the Bospoort Dam, a gravity and earth-fill type dam on the Hex River, which is a tributary of the Elands River, a part of the Crocodile River (Limpopo) basin. It is located near Rustenburg, North West, South Africa. The reservoir mainly provides water for irrigation purposes, municipal water supply and industrial uses.

Magalies Water recognises the critical role played by the monitoring of water quality and therefore carries out continuous measurement and collection of various water quality data. This data was handed over to the authors for analysis, which has culminated into the production of this paper.

Key water quality parameters

The major water quality parameters that have been analysed include pH, conductivity and dissolved solids, turbidity and colour, total coliforms, Escherichia coli (E. coli), hardness, alkalinity, precipitation potential, chlorophyll and organic carbon.

pH

The term pH (Jonnalagadda & Mgere 2001) describes the extent to which water is acidic or basic (alkaline). The pH scale ranges from 0 to 14. Water that is neutral has a pH of 7; water that is acidic has a pH less than 7 and water that is basic has a pH higher than 7. Very acidic or very basic water can be corrosive and can also interfere with water treatment process efficiency. pH is an important treated water quality parameter mainly due to the fact that (among other reasons), potable water should be non-corrosive.

Conductivity and dissolved solids

Conductivity is a measure of the ease with which water transmits an electric current. Conductivity is due to, and is therefore an indicator of the presence of inorganic dissolved solids in the water such as chlorides, nitrates, sulphates and phosphate ions (ions that carry a negative charge), or sodium, magnesium, calcium, iron and aluminium ions (ions that carry a positive charge). Potable water should possess these substances in controlled amounts, as excess proportions can affect the taste and colour of water, and may be responsible for more adverse health effects such as reducing the oxygen carrying capacity of blood, or lowering blood sugar levels.

Turbidity and colour

Turbidity is a measure of water clarity or the extent to which colloidal substances in water decrease the passage of light through the water (Juntunen et al. 2012). Colloidal substances are chemically reactive suspended substances that cannot be removed by filtration and may include clay, silt, algae, plankton, microbes, and other substances. Colour in water may be caused by the presence of minerals such as iron and manganese or by substances of vegetable origin such as algae and weeds. Colour tests indicate the efficiency of the water treatment system. Potable water should be colourless and non-turbid.

Total coliforms and E. coli

It is difficult, time-consuming, expensive and impractical to monitor drinking water for every possible microbial pathogen (disease-causing) bacteria, viruses, or protozoans that might occur with contamination (Reddy & Lee 2012; Onda et al. 2012; Bartram et al. 2014). A more viable approach is the detection of organisms normally present in the faeces of man and other warm-blooded animals, as indicators of faecal pollution, as well as of the efficiency of water treatment and disinfection. The most commonly tested faecal bacteria indicators are total coliforms, faecal coliforms, E. coli, faecal streptococci, and enterococci. All members of the total coliform group can occur in human faeces, but some can also be present in animal manure, soil, and in other places outside the human body. E. coli is a single species of faecal coliform bacteria that is specific to faecal material from humans and other warm-blooded animals. Its identification implies the presence of hazardous disease causing organisms.

Hardness and alkalinity

Hardness is a measure of the amount of divalent salts, or positively charged ions, particularly calcium (Ca2+) and magnesium (Mg2+), in water. Total hardness is the sum of the concentrations of Ca2+ and Mg2+, expressed in ppm (mg/l) calcium carbonate. Calcium carbonate hardness is a general term that indicates the total amount of divalent salts present, although it does not specify which salts are causing water hardness. Hard water is generally not harmful to human health but wastes soap and forms scale precipitates upon heating (Kumar & Puri 2012; Sengupta 2013).

Alkalinity, on the other hand, is a measure of the capacity of water to neutralize acids. Alkaline compounds in the water such as bicarbonates, carbonates, hydroxides and phosphates lower the acidity of the water. Alkalinity, like hardness, is reported as milligrams per litre of calcium carbonate (mg/l CaCO3), and owing to this fact, hardness and alkalinity are often confused. However, alkalinity measures negative ions (carbonates and bicarbonates) while hardness measures positive ions (calcium and magnesium), and sometimes these values can differ greatly. If limestone (calcium carbonate) is the cause of hardness and alkalinity, these values will be similar or identical. However, if sodium bicarbonate (NaHCO3) is responsible for high alkalinity, it is possible for water to have high alkalinity and low hardness.

Precipitation potential

Measured in milligrams per litre of calcium carbonate, this parameter indicates the level of corrosivity of the water (Randtke 2011). A negative potential indicates that the water is corrosive i.e. can dissolve the metal of the pipeline. A positive potential indicates that calcium carbonate can be precipitated from the water and deposited into the pipeline. This action can have the advantage of protecting the pipeline through lining, but can, if in excess, reduce the hydraulic capacity of the pipeline, hence the establishment of a limit.

Chlorophyll

A pigment in plants that enables photosynthesis to take place. The concentration of Chlorophyll is a convenient indicator of the amount of algae in the water. Too much algae can cause undesirable tastes and odours, clog filters, consume chlorine and can lead to the production of undesirable disinfection by-products. All of this can increase the cost of treating water for domestic use.

Organic carbon

This parameter measures the amount of organic matter in the water (Toming et al. 2016). Too much organic matter will attract undesirable microorganisms that will grow in pipelines.

Other parameters

Temperature can affect parameters such as pH, precipitation potential, as well as the concentration of various dissolved solids.

Metals such as potassium and sodium exist in low concentrations in raw water. Zinc, chromium, aluminium, iron, copper, cobalt and manganese, were found to exist in trace concentrations. These concentrations are desirable for human health. Health hazards attributed to these elements are minimal and moreover, the body can get rid of them easily. However, high concentrations of these metals are known to be deleterious to human health.

Other parameters, whose health hazards can only be realised when consumed in high concentrations (which concentrations rarely occur in drinking water) include: sulphates, nitrates, ammonium, fluorides and phosphates (Thi Minh Hanh et al. 2011; Yan et al. 2015; Liu & Chan 2016). Their concentrations were found to be sufficiently and consistently low for the period under consideration. Unfortunately, for most of these parameters, a thorough analysis could not be carried out, owing to little and/or missing data.

To facilitate the understanding of the results, each graph has been drawn with a linear trend line in order to demonstrate the general trend in the variation of data for the period under consideration. An alarm level (the maximum recommended concentration of a parameter) has also been included in the graphs (in a red colour), to show the deviation of the data values from the limit.

pH

The pH, as can be observed in Figure 1, fluctuates between 7.35 and 9.35, and is shown to bear a very small increase over time, which indicates slightly increasing alkalinity of the raw water. With a linear trend line whose slope is 0.3%, and without any anomalous deviations, this observation can be safely neglected. The variation of the pH is similar to that of the raw water from Vaalkop dam (see Section 1.1). While there is no cause for concern, it is important to study the catchment in order to understand the causes of this trend.
Figure 1

Variation of pH.

Figure 1

Variation of pH.

Close modal

Variation of conductivity and dissolved solids

Figure 2 shows that the conductivity of the water is high, surpassing the alarm level for over 65% of the period under consideration. It fluctuates between 50 and 235 mS/m. As was observed in the raw water quality results for Vaalkop dam (Section 1.2) although the results in Figure 2 generally imply a declining trend in conductivity, the very low coefficient of determination could suggest that the declining trend cannot be confirmed. What is certain, however, is that conductivity is not increasing over time. Moreover, while it is an indicator of the dissolved solid content of the water, it can be seen in Figures 3 and 4 that all dissolved solids, with the exception of chlorides, were found to have concentrations that were consistently and significantly lower than their recommended alarm levels. However, despite various missing data intervals, the values were generally decreasing over time. For example, sodium and sulphate values were less than 75% of the alarm level, while potassium was found to be less than 40% of the alarm level. Furthermore, the concentration of chlorides was below the alarm limit after July 2009, and reveals a declining trend thereafter. Other dissolved solids are discussed as nutrients in Section 2.8, with similar results. This observation requires further verification.
Figure 2

Variation of conductivity.

Figure 2

Variation of conductivity.

Close modal
Figure 3

Variation of calcium and magnesium.

Figure 3

Variation of calcium and magnesium.

Close modal
Figure 4

Variation of solids.

Figure 4

Variation of solids.

Close modal

Hardness and alkalinity

Figure 5 reveals that the hardness of Bospoort raw water is above the recommended alarm limit for at least 50% of the study period. Thus, water from Bospoort is harder than water from Vaalkop. It can be seen from Figure 3, that the concentration of causative agents, calcium and magnesium, is also higher in Bospoort than in Vaalkop. A declining trend is revealed, but cannot be confirmed due to data gaps.
Figure 5

Variation of hardness.

Figure 5

Variation of hardness.

Close modal
Figure 6 shows alkalinity values appearing lower than their respective alarm level, and despite missing data, a slight increasing alkalinity trend is revealed, which is in agreement with the slight pH rise noted in Figure 1.
Figure 6

Variation of alkalinity.

Figure 6

Variation of alkalinity.

Close modal

Precipitation potential

The precipitation potential (Figure 7) of Vaalkop water was mainly positive with a few scattered periods when it was negative. Thus, the water is not corrosive, although it can be hard. Available data suggests that the alarm level was exceeded on at least 50% of the study period, which could explain why in Section 2.3 and Figure 2.5, the water is excessively hard. A trend could not be accurately established due to gaps existing in the available data.
Figure 7

Precipitation potential of Vaalkop water.

Figure 7

Precipitation potential of Vaalkop water.

Close modal

Colour

Colour levels were found to vary between 16 and 149 mg/l Pt, which is generally higher than the concentration for Vaalkop dam, and generally falling below the alarm level (Figure 8). The linear trend line depicts a slight decrease in colour over time. However, an interesting observation is the sharp unprecedented increase in colour during the month of December 2008. It is not immediately clear what triggered this sharp increase.
Figure 8

Variation of colour.

Figure 8

Variation of colour.

Close modal

Turbidity

Turbidity levels were found to vary between 1 and 23 NTU (Figure 9), generally higher than those of Vaalkop, and generally falling below the alarm level. The linear trend line depicts a very slight decrease in turbidity over time, which can be safely neglected. There was a sharp unprecedented increase in turbidity at the beginning and end of 2008.
Figure 9

Variation of turbidity.

Figure 9

Variation of turbidity.

Close modal

Total coliform count

Studying Figure 10, the total coliform count was approximately 10–30% of the alarm level for the entire study period, except for two unprecedented instances in May 2011 and April 2012.
Figure 10

Variation of total coliforms.

Figure 10

Variation of total coliforms.

Close modal

E. coli count

From Figure 11, it can be observed that the E. coli count was well below the alarm level for the most part of the study period. This implies that with regard to coliform count, Bospoort dam has a better water quality than Vaalkop. However, there were isolated cases of excessively high E. coli counts, which are observed at the beginning of 2009, 2011 and 2012. This can be attributed to the summer rainfall that carries runoff polluted with wastewater.
Figure 11

Variation of E. coli.

Figure 11

Variation of E. coli.

Close modal

Organic carbon

The dissolved organic carbon content (Figure 12) appears to be below the limit for part of the time, but establishment of the trend is not possible due to large missing data.
Figure 12

Variation of organic carbon.

Figure 12

Variation of organic carbon.

Close modal

Nutrients

As can be observed in Figure 13, with respect to their impact on human health as dissolved inorganic solids, ammonium and nitrates generally fell below the recommended alarm levels for human health for the entire six years of the study period, and only exceeded the alarm levels in one case. However, phosphates fell above their alarm levels for the majority of the study period, while nitrites exceeded their limit on at least three occasions. An accurate establishment of their trend is complicated by missing data.
Figure 13

Variation of nutrients.

Figure 13

Variation of nutrients.

Close modal

Chlorophyll

Chlorophyll values were consistently below their recommended values for the entire study period (Figure 14), except for January 2009, implying a low algal concentration in the water. These findings, though, are not conclusive due to several gaps in the available data.
Figure 14

Variation of chlorophyll.

Figure 14

Variation of chlorophyll.

Close modal

Conclusions

  • (i) In general terms, the pH, colour, turbidity, dissolved solids, alkalinity, precipitation potential, chlorophyll and organic carbon were found to be within acceptable limits.

  • (ii) The hardness of the water was found excessive.

  • (iii) The conductivity of the water is high, surpassing the alarm level for approximately 65% of the period under consideration, even though the causative dissolved solids are appreciably below their alarm levels.

  • (iv) The total coliform and E. coli counts were significantly lower than for Vaalkop dam, with a few isolated incidents of sharp increases in the counts.

Recommendations

  • (i) A further investigation, requiring more data, is required to explain the contradiction between high conductivity and low dissolved solid concentration.

  • (ii) It is important to investigate the events that led to the E. coli count increase at the beginning of 2009, 2011 and 2012.

Bartram
J.
Brocklehurst
C.
Fisher
M. B.
Luyendijk
R.
Hossain
R.
Wardlaw
T.
Gordon
B.
2014
Global monitoring of water supply and sanitation: history, methods and future challenges
.
Int. J. Environ. Res. Public Health
11
,
8137
8165
.
Jonnalagadda
S. B.
Mgere
G.
2001
Water quality of the Odzi river in the eastern high lands of Zimbabwe
.
Water Res.
35
(
10
),
2371
2376
.
pmid:11394770
doi: 10.1016/s0043-1354(00)00533-9.
Juntunen
P.
Liukkonen
M.
Pelo
M.
Lehtola
M. J.
Hiltunen
Y.
2012
Modelling of water quality: an application to a water treatment process
.
Applied Computational Intelligence and Soft Computing
.
doi:10.1155/2012/846321.
Kumar
M.
Puri
A.
2012
A review of permissible limits of drinking water
.
Indian Journal of Occupational and Environmental Medicine
16
(
1
),
40
44
.
http://doi.org/10.4103/0019-5278.99696
.
Randtke
S.
2011
Chapter 13: Precipitation, coprecipitation and precipitative softening
. In:
Water Quality and Treatment: A Handbook on Drinking Water
, 6th edn. (
Edzwald
J. K.
, ed.).
American Water Works Association
,
Denver
,
Colorado
;
McGraw-Hill, New York, New York
.
Reddy
K. D. H.
Lee
S. M.
2012
Water pollution and treatment technologies
.
J. Environ. Anal. Toxicol.
2
,
e103
.
doi:10.4172/2161-0525.1000e103.
Sengupta
P.
2013
Potential health impacts of hard water
.
International Journal of Preventive Medicine
4
(
8
),
866
875
.
Thi Minh Hanh
P.
Sthiannopkao
S.
The Ba
D.
Kim
K.
2011
Development of Water Quality Indexes to Identify Pollutants in Vietnam's Surface Water
.
Journal of Environmental Engineering
137
(
4
),
273
283
.
Toming
K.
Kutser
T.
Tuvikene
L.
Viik
M.
Noges
T.
2016
Dissolved organic carbon and its potential predictors in eutrophic lakes
.
Water Research
102
.
doi:10.1016/j.watres.2016.06.012.