Ground water quality conformance to the World Health Organisation standards for drinking water was carried out and inferred to the health risks associated with use of such quality of water. Water samples were collected thrice a month, from nine boreholes, over a period of twelve months and analysed for physical, chemical and biological parameters. Chemical parameters were tested using UV-Vis photometry. Physical parameters were measured using HI9829 waterproof portable logging multi-parameter meter and biological parameters were determined using the Minimal Media ONRG-MUG test and the Membrane Filtration Method (MF). Results shows that total hardness and Fe concentration were above limit in 78% and 56% of the sampled boreholes, respectively. pH, EC, Ca, Cl, Fl, Mn, Mg and Turbidity were within the acceptable WHO limits. Of the sampled boreholes, 67% were not conforming to the Escherichia coli loads recommended for drinking water. Parametric correlations showed strong and significant correlations between chlorides and fluorides (r = 0.68; p < 0.05), Nitrates and Sulphates (r = 0.78; p < 0.05). There is need to treat borehole water to eliminate E. coli and reduce nitrates and total hardness. Furthermore, analysis and monitoring systems to determine temporal variability and health risks, respectively, needs to be put in place.

INTRODUCTION

Groundwater has emerged as a vital resource for domestic water supply, providing 25–40% of the world's drinking water (Margat & van der Gun 2013). In urban areas, a significant increase in groundwater use by 63.1% of the population has been reported between 1990 and 2010 (WHO & UNICEF 2014). The increase in ground water use mostly emanates from third world countries where outbreaks of water related diseases are prevalent (Gleick 2003; Sorenson et al. 2011; Bain et al. 2012; Onda et al. 2012). Lately, urban water utilities have resorted to groundwater exploration, development and use for two reasons. Firstly, there is need to cope with increasing population, rapid urbanisation, increasing affluence, accelerated rates of industrialisation, increasing per capita water demand (Rao et al. 2004). Secondly, the cost for drilling boreholes and wells is relatively affordable to the municipalities and private, in-situ self-supply residents (Rao et al. 2004; Foster et al. 2010).

Although ground water use has increased in urban areas, there are still challenges associated with its use as potable water. In urban environments, ground water is subject to temporal and spatial quality deterioration mainly due to pollution (Van Der Hoven et al. 2005; Schot & Pieber 2012). Ground water pollution is a subset of complex interactions between different legal or illegal land uses with rainfall, runoff and ground water recharge processes (Pionke & Urban 1985; Coulter et al. 2004; Lerner & Harris 2009).

Increasing population, serviced by old low capacity sanitation and reticulation facilities results in underground sewer burst which directly load faecal pathogens (eg Escherichia coli), pharmaceuticals, disinfectants, detergents and other persistent micro-pollutants to the ground water. Urban agriculture, landfills and waste tips may input high levels of nitrates or nitrite, ammonium, pesticides and sulphides through runoff, infiltration and seepage (Wakida & Lerner 2005). Industrial waste contributes heavy metals, poly-aromatic hydrocarbons among other pollutants.

Common health effects of groundwater pollution by heavy metals include high blood pressure, digestive problems, kidney damage and mental retardation from mercury and diarrhoea, nausea and death from Arsenic (Jarup 2003). Nitrates and nitrites, although their effects on human health is disputed (Addiscott 1996; Addiscott & Benjamin 2004; Addiscott 2005; Almasri 2007), it is strongly argued to cause infant methemoglobinemia and gastric cancer (Bruning-Fann & Kaneene 1993). These potential health risks can be fatal considering that physical, chemical and biological parameters are not usually tested for during acute water shortages. Furthermore, privately owned boreholes and wells are not mandatorily tested and most groundwater users regards groundwater to be pure.

The high level risk associated with groundwater use, is in a way, an indicator of information deficiency on the quality of the resource itself as well as lack of baseline data to base the development of a groundwater framework on. Therefore, this research may be a starting point towards informing local level policy makers about the groundwater quality and implications of its use as potable water. This may ultimately lead to the development of groundwater governance structures to control how groundwater is exploited and used. This status quo in Gweru city applies to all the other cities in Zimbabwe and most of countries in southern Africa. The correlations of groundwater parameters developed in this research may aid in identifying sustainable groundwater treatment options.

This research seeks to analyse the borehole water quality in Gweru city and assess the suitability of the water for domestic use using the World Health Organisation (WHO) guidelines for drinking water and analyse correlations between groundwater quality parameters.

SITE DESCRIPTION

Location and climate

The research was carried out in Gweru the fifth largest City in Zimbabwe, based on population. It is located at 19.4511 °S, 29.8302 °E and 285 km south-west of the Capital City Harare. The city covers about 26 113Ha of the Sanyati catchment. It is at an altitude of 1,420 above mean sea level. Gweru city lies in Natural Region IV and receives an average rainfall of 600 mm bordered by a minimum of 400 and a maximum of 850 mm (Mugandani et al. 2012). The area receives most of its rainfall in the tropical summer (October to March) with maximum average temperature of 28.3 °C and the winter is fairly cold with minimum average temperature of 8.7 °C (Vincent & Thomas 1960).

Soils and geology

The rocks consist of meta-sediments, felsic meta-volcanics, interbedded sediments, aeolian sands, grits sandstone, siltstone and Felsites rock formations (Figure 1). Most of the soils in the study area are related to the underlying rock. Two soil groups are common in the Gweru area, Regosols and Fersiallitic soils with the latter dominant. The former are deep sands with <10% silt and clay with very little to no reserves of weathered minerals (mainly Kalahari sands). Fersiallitic soils are mainly south of the city and have appreciable reserves of weatherable material, with moderately shallow to deep greyish brown sands or loamy sands over light reddish brown sandy loams formed on sandstones and quartzite of umkondo and to a lesser extent Permian formation (Nyamapfene 1991).
Figure 1

Underlying rocks in different sampling locations.

Figure 1

Underlying rocks in different sampling locations.

Population

The city of Gweru, like most of the cities in Zimbabwe, is experiencing rapid increases in population (Table 1); the population growth rate for 2002–2012 was 1.0 (ZimStat 2012). The population is housed in around 41,149 households in low, medium and high density residential areas. The population increase has surpassed the capacity of potable and wastewater treatment plants.

Table 1

Population increases for Gweru city and other major cities of Zimbabwe

  Population in census years
 
City 1982 1992 2002 2012 
Harare 656,011 1,189,103 1,435,784 1,468,767 
Bulawayo 413,814 621,742 676,650 655,675 
Mutare 69,621 131,367 170,466 188,245 
Gweru 78,918 128,037 140,806 158,233 
Masvingo 30,523 51,743 69,490 88,554 
  Population in census years
 
City 1982 1992 2002 2012 
Harare 656,011 1,189,103 1,435,784 1,468,767 
Bulawayo 413,814 621,742 676,650 655,675 
Mutare 69,621 131,367 170,466 188,245 
Gweru 78,918 128,037 140,806 158,233 
Masvingo 30,523 51,743 69,490 88,554 

Water reticulation system

Potable water in the city is supplied from three dams: Gwenoro (31.4 × 106 m3), White Waters (4.9 × 106 m3) and Amapongokwe (37.6 × 106 m3). Gwenhoro dam used to supply 93% of the city's water demand in 2002 and the supply capacity reduced by 10% in 2012. This is attributed to the change in catchment land uses, reduced rainfall amounts and increased groundwater abstraction in the upstream of the catchment including the city. There has been a decrease in the peak water levels in Gwenhoro dam (Table 2) which resulted in the decommissioning of the dam in October 2013. This further worsened the water scarcity situation and residents resorted to ground water for portable water. The city also tried to implement water rationing to cope with increasing demand and diminishing supply.

Table 2

Peak water levels for Gwenhoro and Whitewaters dams (2001–2013)

  Percentage full (%)
 
Dam 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 
Gwenhoro 100 97 59 75 68 54 48 64 71 81 60 56 18 
Whitewaters 100 99 61 89 97 93 92 88 96 99 100 98 97 
  Percentage full (%)
 
Dam 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 
Gwenhoro 100 97 59 75 68 54 48 64 71 81 60 56 18 
Whitewaters 100 99 61 89 97 93 92 88 96 99 100 98 97 

Zimbabwe's economy has been on the downward trend for the past two decades and performance of the city's water utilities has not been spared by the economic crisis. The city failed to repair breakdowns and to acquire chemicals for water treatment. The water scarcity situation resulted in a Cholera outbreak from October 2009 and lasted into March 2010. The outbreak claimed at least at least 4,000 lives.

Ground water abstraction

In response to the 2009–2010 Cholera crisis, Non-Governmental Organisations (NGO), private property owners and the city council drilled at least 200 emergency boreholes. By the end of 2010 at least 400 public and private boreholes were serving the city residences. Each borehole in the high density suburbs services an average of 100 households and at most 20 households in the medium and low density suburbs. The boreholes were sunk to an average depth of 40 m.

METHODOLOGY

Ground water sampling and chemical analysis

A total of 324 samples were collected from 9 boreholes located in nine residential areas (Figure 2) over a period of 12 months. The water samples were collected three times a month on an 8–10 days interval. Before sampling the borehole outlet was disinfected and water from the borehole was flushed out first to minimise contamination from the pipes (Sundaram et al. 2010; APHA 2012). Water samples were collected in labelled (source name and date) 500 ml collecting bottles and immediately put in cooler boxes with ice for immediate transport to the laboratory for ground water quality analyses. Samples for biological parameter analysis were collected in autoclaved opaque glass bottles. Poly-ethylene bottles used in collecting samples for physical and chemical analysis were soaked in phosphate-free detergent for 24 hours before they were thoroughly rinsed with distilled water and 5% nitric acid. On the site, bottles were rinsed three times with the borehole water. All the samples were kept at approximately 4 °C prior to analysis and were analysed for total hardness, fluorides, chlorides, iron, nitrates, magnesium, manganese, calcium, sulphates, potassium, total and faecal coliforms in the National Institute of Health Research (NIHR) Water Quality Laboratory. Chemical parameters were tested for using UV-Vis photometry. Turbidity, pH and electrical conductivity (EC) were measured on site using an HI9829 waterproof portable logging multi-parameter meter.
Figure 2

Map of Gweru indicating residential areas and sampled boreholes.

Figure 2

Map of Gweru indicating residential areas and sampled boreholes.

Coliform analysis

Total coliform, faecal coliforms and E. coli were tested for in the borehole water. The Minimal Media ONRG-MUG test was used to simultaneously detect total coliforms and E. coli load in sampled water. The presence and or absence of thermo-tolerant coliform (faecal coliform) populations was estimated using the Membrane Filtration Method (MF). The MF was carried out following USEPA Membrane Filtration Method 8047 (US-EPA 2012). A measured volume of water was filtered through a membrane composed of cellulose esters. The pore size was such that the organisms to be enumerated are retained on or near the surface of the membrane, which was placed, face upwards, on differential medium selective for the indicator organism sought. Volumes were chosen so that the number of colonies to be counted on the membrane would lie between 10 and 100. Membranes were incubated for 14 hours and at 37 °C to determine total coliforms and separate membranes were incubated for 4 hours at 30 °C, and then for 14 hours at 44.5 °C. Shiny yellow colonies were counted. To calculate coliform number the following formula was used: 
formula
1

Correlation between water quality parameters

A Pearson correlation test together with a two tailed significance test (p = 0.05) was carried out between water parameters. This was done to give preliminary options for ground water treatment and link the source and behaviour of the tested water parameters.

RESULTS

Turbidity, pH, electrical conductivity and total hardness

Turbidity values ranged from 0.013NTUs to 4.44NTUs. The highest turbidity value (4.44 NTUs) was recorded in Riverside residential area with the lowest (0.013 NTUs) recorded in Mkoba 11; a high density residential area. Borehole water pH ranged from 6.67 to 7.46 (Table 3). The lowest pH value was recorded in Mkoba 20 and the highest in Lundi Park residential area.

Table 3

Summary of ground water physical parameters measured in Gweru urban district

Location of Borehole pH Mean ± SD Turbidity (NTUs) Mean ± SD Conductivity (μScm−1Mean ± SD Total hardness (mgl−1Mean ± SD 
Senga 7.46 7.46 ± 0.32 0.097 0.097 ± 0.001 209 209 ± 91 575 575 ± 155 
Mambo 7.11 7.11 ± 0.11 1.250 1.25 ± 0.1 336 336 ± 103 381 381 ± 87 
Mkoba 13 6.99 6.99 ± 0.23 0.647 0.647 ± 0.03 249 249 ± 97 325 325 ± 77 
Mkoba 19 6.67 6.67 ± 0.28 2.017 2.017 ± 0.4 116 116 ± 23 222 222 ± 38 
Mkoba 20 7.06 7.06 ± 0.08 2.283 2.283 ± 0.03 152 152 ± 19 228 228 ± 56 
Mkoba 11 7.61 7.61 ± 0.41 0.013 0.013 ± 0.002 64.3 64.3 ± 0.9 106 106 ± 14 
Lundi Park 7.00 7 ± 0.13 0.043 0.043 ± 0.01 268 268 ± 88 261 261 ± 63 
Nashville 6.84 6.84 ± 0.26 0.040 0.04 ± 0.004 218 218 ± 72 498 498 ± 146 
Riverside 7.21 7.21 ± 0.28 4.440 4.44 ± 0.77 56.6 56.6 ± 13 114 114 ± 33 
WHO limits 6.5–9.2   1,380  200   
Location of Borehole pH Mean ± SD Turbidity (NTUs) Mean ± SD Conductivity (μScm−1Mean ± SD Total hardness (mgl−1Mean ± SD 
Senga 7.46 7.46 ± 0.32 0.097 0.097 ± 0.001 209 209 ± 91 575 575 ± 155 
Mambo 7.11 7.11 ± 0.11 1.250 1.25 ± 0.1 336 336 ± 103 381 381 ± 87 
Mkoba 13 6.99 6.99 ± 0.23 0.647 0.647 ± 0.03 249 249 ± 97 325 325 ± 77 
Mkoba 19 6.67 6.67 ± 0.28 2.017 2.017 ± 0.4 116 116 ± 23 222 222 ± 38 
Mkoba 20 7.06 7.06 ± 0.08 2.283 2.283 ± 0.03 152 152 ± 19 228 228 ± 56 
Mkoba 11 7.61 7.61 ± 0.41 0.013 0.013 ± 0.002 64.3 64.3 ± 0.9 106 106 ± 14 
Lundi Park 7.00 7 ± 0.13 0.043 0.043 ± 0.01 268 268 ± 88 261 261 ± 63 
Nashville 6.84 6.84 ± 0.26 0.040 0.04 ± 0.004 218 218 ± 72 498 498 ± 146 
Riverside 7.21 7.21 ± 0.28 4.440 4.44 ± 0.77 56.6 56.6 ± 13 114 114 ± 33 
WHO limits 6.5–9.2   1,380  200   

EC ranged from 56 to 336 μS cm−1. The maximum and minimum EC values were recorded in Mambo (336 μS cm−1) and Riverside (56.6 μS cm−1), respectively. Total hardness ranged from 106 to 575 mgl−1. Borehole water in Mkoba 11 and Riverside was classified as moderately hard (75–150 mg l−1), while in Mkoba 19, 20 and Lundi Park was found to be hard water with total hardness ranges of 150–300 mg l−1 and very hard water was found in Senga, Mambo, Mkoba 13 and Nashville boreholes (Table 4). Only 22% of the boreholes were within the WHO limit of water hardness. All the boreholes had water turbidity, pH and EC values within the WHO acceptable range.

Table 4

Ground water total hardness classes in Gweru City

Total hardness Class Borehole Location 
0–75 Soft None 
75–150 Moderately hard Mkoba11, Riverside 
150–300 Hard Mkoba19, 20 and Lundi Park 
>300 Very hard Senga, Mambo, Mkoba 13 and Nashville 
Total hardness Class Borehole Location 
0–75 Soft None 
75–150 Moderately hard Mkoba11, Riverside 
150–300 Hard Mkoba19, 20 and Lundi Park 
>300 Very hard Senga, Mambo, Mkoba 13 and Nashville 

Chemical parameters

Manganese, Sulphates, Potassium, Fluorides, Chlorides, calcium and Magnesium concentrations in all borehole locations were within the WHO limits. Only Iron concentrations were out of the recommended WHO limit in Mambo, Mkoba 20, Mkoba 19, Senga and Mkoba 13. Nitrates concentration ranged between 1.85 and 11 mg l−1 the WHO limits were surpassed in Mkoba 13 (Table 5).

Table 5

Summary of ground water chemical parameters

(a)
 
Borehole Location Manganese (mg l−1Mean ± SD Iron (mg l−1Mean ± SD Nitrates (mg l−1Mean ± SD Sulphates (mg l−1Mean ± SD 
Senga 0.03 0.03 ± 0.001 0.65 0.65 ± 0.25 4.17 4.17 ± 2.3 2.32 2.32 ± 0.3 
Mambo 0.02 0.02 ± 0.001 0.77 0.77 ± 0.32 1.85 1.85 ± 0.63 4.37 4.37 ± 0.8 
Mkoba 13 0.00 0.00 ± 0.000 0.61 0.61 ± 0.13 11.00 11.0 ± 3.6 19.33 19.33 ± 3.9 
Mkoba 19 0.01 0.01 ± 0.0001 0.41 0.41 ± 0.11 7.04 7.04 ± 2.9 1.33 1.33 ± 0.12 
Mkoba 20 0.00 – 0.54 0.54 ± 0.13 2.53 2.53 ± 0.8 0.03 0.03 ± 0.01 
Mkoba 11 0.00 – 0.14 0.14 ± 0.03 2.54 2.54 ± 0.93 0.33 0.33 ± 0.03 
Lundi Park 0.03 0.03 ± 0.002 0.27 0.27 ± 0.02 2.97 2.97 ± 0.89 3.00 3.00 ± 0.34 
Nashville 0.00 – 0.00 – 4.54 4.54 ± 1.64 0.00 – 
Riverside 0.00 – 0.17 0.17 ± 0.01 2.05 2.05 ± 0.77 0.02 0.02 ± 0.01 
WHO limit 0.1  0.3  10  400   
(b) 
Borehole Location Potassium (mg l−1Mean ± SD Fluorides (mg l−1Mean ± SD Chlorides (mg l−1Mean ± SD Calcium (mg l−1Mean ± SD Magnesium (mg l−1Mean ± SD 
Senga 2.47 2.47 ± 0.81 0.21 0.21 ± 0.08 0.44 0.44 ± 0.13 151 151 ± 23 41.00 41.00 ± 8.2 
Mambo 1.53 1.53 ± 0.33 1.42 1.42 ± 0.39 2.30 2.30 ± 0.73 171 171 ± 53 31.33 31.33 ± 13 
Mkoba 13 1.80 1.80 ± 0.26 0.35 0.35 ± 0.11 1.32 1.32 ± 0.38 131 131 ± 18 15.00 15.00 ± 5.8 
Mkoba 19 3.00 3.00 ± 0.43 0.20 0.20 ± 0.13 1.76 1.76 ± 0.68 128 128 ± 36 17.00 17.00 ± 10 
Mkoba 20 2.45 2.45 ± 0.75 0.13 0.13 ± 0.09 0.29 0.29 ± 0.18 108 108 ± 27 15.67 15.67 ± 5.4 
Mkoba 11 2.14 2.14 ± 0.18 0.20 0.20 ± 0.15 0.79 0.79 ± 0.29 25 25 ± 13 9.33 9.33 ± 4.31 
Lundi Park 4.10 4.10 ± 0.83 0.55 0.55 ± 0.21 0.50 0.50 ± 0.17 129 129 ± 19 20.33 20.33 ± 11 
Nashville 1.77 1.77 ± 0.11 0.29 0.29 ± 0.10 0.22 0.22 ± 0.09 133 133 ± 42 42.33 42.33 ± 14 
Riverside 1.85 1.85 ± 0.34 0.27 0.27 ± 0.18 0.10 0.10 ± 0.02 35 35 ± 12 12.67 12.67 ± 3.6 
WHO limit –  1.5  250  200  150   
(a)
 
Borehole Location Manganese (mg l−1Mean ± SD Iron (mg l−1Mean ± SD Nitrates (mg l−1Mean ± SD Sulphates (mg l−1Mean ± SD 
Senga 0.03 0.03 ± 0.001 0.65 0.65 ± 0.25 4.17 4.17 ± 2.3 2.32 2.32 ± 0.3 
Mambo 0.02 0.02 ± 0.001 0.77 0.77 ± 0.32 1.85 1.85 ± 0.63 4.37 4.37 ± 0.8 
Mkoba 13 0.00 0.00 ± 0.000 0.61 0.61 ± 0.13 11.00 11.0 ± 3.6 19.33 19.33 ± 3.9 
Mkoba 19 0.01 0.01 ± 0.0001 0.41 0.41 ± 0.11 7.04 7.04 ± 2.9 1.33 1.33 ± 0.12 
Mkoba 20 0.00 – 0.54 0.54 ± 0.13 2.53 2.53 ± 0.8 0.03 0.03 ± 0.01 
Mkoba 11 0.00 – 0.14 0.14 ± 0.03 2.54 2.54 ± 0.93 0.33 0.33 ± 0.03 
Lundi Park 0.03 0.03 ± 0.002 0.27 0.27 ± 0.02 2.97 2.97 ± 0.89 3.00 3.00 ± 0.34 
Nashville 0.00 – 0.00 – 4.54 4.54 ± 1.64 0.00 – 
Riverside 0.00 – 0.17 0.17 ± 0.01 2.05 2.05 ± 0.77 0.02 0.02 ± 0.01 
WHO limit 0.1  0.3  10  400   
(b) 
Borehole Location Potassium (mg l−1Mean ± SD Fluorides (mg l−1Mean ± SD Chlorides (mg l−1Mean ± SD Calcium (mg l−1Mean ± SD Magnesium (mg l−1Mean ± SD 
Senga 2.47 2.47 ± 0.81 0.21 0.21 ± 0.08 0.44 0.44 ± 0.13 151 151 ± 23 41.00 41.00 ± 8.2 
Mambo 1.53 1.53 ± 0.33 1.42 1.42 ± 0.39 2.30 2.30 ± 0.73 171 171 ± 53 31.33 31.33 ± 13 
Mkoba 13 1.80 1.80 ± 0.26 0.35 0.35 ± 0.11 1.32 1.32 ± 0.38 131 131 ± 18 15.00 15.00 ± 5.8 
Mkoba 19 3.00 3.00 ± 0.43 0.20 0.20 ± 0.13 1.76 1.76 ± 0.68 128 128 ± 36 17.00 17.00 ± 10 
Mkoba 20 2.45 2.45 ± 0.75 0.13 0.13 ± 0.09 0.29 0.29 ± 0.18 108 108 ± 27 15.67 15.67 ± 5.4 
Mkoba 11 2.14 2.14 ± 0.18 0.20 0.20 ± 0.15 0.79 0.79 ± 0.29 25 25 ± 13 9.33 9.33 ± 4.31 
Lundi Park 4.10 4.10 ± 0.83 0.55 0.55 ± 0.21 0.50 0.50 ± 0.17 129 129 ± 19 20.33 20.33 ± 11 
Nashville 1.77 1.77 ± 0.11 0.29 0.29 ± 0.10 0.22 0.22 ± 0.09 133 133 ± 42 42.33 42.33 ± 14 
Riverside 1.85 1.85 ± 0.34 0.27 0.27 ± 0.18 0.10 0.10 ± 0.02 35 35 ± 12 12.67 12.67 ± 3.6 
WHO limit –  1.5  250  200  150   

Biological parameters

Total coliform load ranged from 14 CFU 100 ml−1 to 167 CFU 100 ml−1 and E. coli load ranged from 0 to 23 CFU 100 ml−1. The highest faecal coliform load of 80 CFU 100 ml−1 was recorded in Riverside and no E. coli was recorded in Nashville (Table 7). The risk posed by faecal coliform load in borehole water was low in 56% of the boreholes. Thirty-three percent of the boreholes were on intermediate risk and only 1 borehole (11%) was at no risk (Table 6). A substantial 67% of the boreholes were not conforming to the WHO standards of 0 E. coli in potable water.

Table 6

Water quality risk assessment for faecal coliform load

Faecal coliform load Risk Ranking Location of Boreholes Proportion of Boreholes (%) 
No risk Nashvile 11 
1–10 Low Mambo, Mkoba 13, Mkoba 19, Mkoba 11, Lundi Park 56 
10–100 Intermediate Senga, Mkoba 20, Riverside 33 
100–1,000 High None 
>1,000 Very high None 
Faecal coliform load Risk Ranking Location of Boreholes Proportion of Boreholes (%) 
No risk Nashvile 11 
1–10 Low Mambo, Mkoba 13, Mkoba 19, Mkoba 11, Lundi Park 56 
10–100 Intermediate Senga, Mkoba 20, Riverside 33 
100–1,000 High None 
>1,000 Very high None 
Table 7

Total coliform, faecal coliform and E. coli load in borehole water

Borehole Location Total coliform load (CFU 100 ml−1) Faecal coliform load (CFU 100 ml−1E-coli load (CFU 100 ml−1
Senga 88 73 
Mambo 34 10 
Mkoba 13 16 
Mkoba 19 14 
Mkoba 20 81 68 14 
Mkoba 11 14 10 
Lundi Park 24 
Nashville 15 
Riverside 167 80 23 
Borehole Location Total coliform load (CFU 100 ml−1) Faecal coliform load (CFU 100 ml−1E-coli load (CFU 100 ml−1
Senga 88 73 
Mambo 34 10 
Mkoba 13 16 
Mkoba 19 14 
Mkoba 20 81 68 14 
Mkoba 11 14 10 
Lundi Park 24 
Nashville 15 
Riverside 167 80 23 

Correlations between ground water parameters

Total hardness had a strong and significant correlation with turbidity, Calcium, Chlorides, Magnesium and conductivity (Table 8). Conductivity was significantly correlated to Fluoride, Calcium and magnesium. Chlorides were significantly correlated to Fluorides (r = 0.68), Iron was correlated to Calcium and Chlorides, Nitrates were significantly correlated to Sulphates (r = 0.78).

Table 8

Correlation between measured borehole water parameters

Correlations   Mn pH Con TotHar Fl Cl Ca Fe SO4 Mg NO3 TC FC Turbidity 
Manganese Pearson Correlation               
Sig. (2-tailed)                
pH Pearson Correlation −0.005              
Sig. (2-tailed) 0.981               
Conductivity Pearson Correlation 0.342 −0.241             
Sig. (2-tailed) 0.081 0.226              
Total hardness Pearson Correlation 0.269 −0.086 0.642            
Sig. (2-tailed) 0.175 0.668 0.000             
Potassium Pearson Correlation 0.377 −0.232 0.023 −0.149           
Sig. (2-tailed) 0.052 0.245 0.911 0.459            
Fluoride Pearson Correlation 0.206 −0.059 0.708 0.192 −0.194          
Sig. (2-tailed) 0.302 0.770 0.000 0.337 0.333           
Chloride Pearson Correlation 0.122 −0.234 0.425 0.029 −0.160 0.653         
Sig. (2-tailed) 0.546 0.241 0.027 0.887 0.427 0.000          
Calcium Pearson Correlation 0.347 −0.436 0.824 0.731 0.091 0.464 0.425        
Sig. (2-tailed) 0.076 0.023 0.000 0.000 0.652 0.015 0.027         
Iron Pearson Correlation 0.292 0.004 0.525 0.327 −0.093 0.452 0.572 0.589       
Sig. (2-tailed) 0.140 0.986 0.005 0.096 0.644 0.018 0.002 0.001        
Sulphate Pearson Correlation −0.006 −0.134 0.436 0.143 −0.177 0.159 0.371 0.302 0.437      
Sig. (2-tailed) 0.977 0.504 0.023 0.477 0.377 0.430 0.057 0.126 0.023       
Magnesium Pearson Correlation 0.252 0.106 0.579 0.864 −0.231 0.296 −0.198 0.498 0.100 −0.067     
Sig. (2-tailed) 0.205 0.600 0.002 0.000 0.247 0.134 0.323 0.008 0.621 0.740      
Nitrate Pearson Correlation −0.106 −0.415 0.143 0.174 0.002 −0.234 0.268 0.288 0.206 0.780 −0.196    
Sig. (2-tailed) 0.600 0.031 0.478 0.385 0.994 0.240 0.176 0.146 0.303 0.000 0.327     
Total coliforms Pearson Correlation −0.072 0.262 −0.247 −0.145 −0.318 0.090 −0.139 −0.305 0.025 −0.121 0.027 −0.317   
Sig. (2-tailed) 0.721 0.186 0.214 0.472 0.106 0.655 0.488 0.121 0.903 0.547 0.895 0.107    
Faecal coliforms Pearson Correlation 0.189 0.415 −0.161 0.147 0.034 −0.267 −0.379 0.025 0.259 −0.194 0.201 −0.259 0.362  
Sig. (2-tailed) 0.346 0.031 0.423 0.465 0.866 0.179 0.052 0.901 0.193 0.333 0.314 0.192 0.063   
Turbidity Pearson Correlation −0.189 −0.150 −0.480 −0.518 −0.174 −0.079 −0.086 −0.371 −0.003 −0.212 −0.444 −0.197 0.682 0.160 
Sig. (2-tailed) 0.346 0.454 0.011 0.006 0.385 0.696 0.670 0.057 0.990 0.288 0.020 0.325 0.000 0.425 
Correlations   Mn pH Con TotHar Fl Cl Ca Fe SO4 Mg NO3 TC FC Turbidity 
Manganese Pearson Correlation               
Sig. (2-tailed)                
pH Pearson Correlation −0.005              
Sig. (2-tailed) 0.981               
Conductivity Pearson Correlation 0.342 −0.241             
Sig. (2-tailed) 0.081 0.226              
Total hardness Pearson Correlation 0.269 −0.086 0.642            
Sig. (2-tailed) 0.175 0.668 0.000             
Potassium Pearson Correlation 0.377 −0.232 0.023 −0.149           
Sig. (2-tailed) 0.052 0.245 0.911 0.459            
Fluoride Pearson Correlation 0.206 −0.059 0.708 0.192 −0.194          
Sig. (2-tailed) 0.302 0.770 0.000 0.337 0.333           
Chloride Pearson Correlation 0.122 −0.234 0.425 0.029 −0.160 0.653         
Sig. (2-tailed) 0.546 0.241 0.027 0.887 0.427 0.000          
Calcium Pearson Correlation 0.347 −0.436 0.824 0.731 0.091 0.464 0.425        
Sig. (2-tailed) 0.076 0.023 0.000 0.000 0.652 0.015 0.027         
Iron Pearson Correlation 0.292 0.004 0.525 0.327 −0.093 0.452 0.572 0.589       
Sig. (2-tailed) 0.140 0.986 0.005 0.096 0.644 0.018 0.002 0.001        
Sulphate Pearson Correlation −0.006 −0.134 0.436 0.143 −0.177 0.159 0.371 0.302 0.437      
Sig. (2-tailed) 0.977 0.504 0.023 0.477 0.377 0.430 0.057 0.126 0.023       
Magnesium Pearson Correlation 0.252 0.106 0.579 0.864 −0.231 0.296 −0.198 0.498 0.100 −0.067     
Sig. (2-tailed) 0.205 0.600 0.002 0.000 0.247 0.134 0.323 0.008 0.621 0.740      
Nitrate Pearson Correlation −0.106 −0.415 0.143 0.174 0.002 −0.234 0.268 0.288 0.206 0.780 −0.196    
Sig. (2-tailed) 0.600 0.031 0.478 0.385 0.994 0.240 0.176 0.146 0.303 0.000 0.327     
Total coliforms Pearson Correlation −0.072 0.262 −0.247 −0.145 −0.318 0.090 −0.139 −0.305 0.025 −0.121 0.027 −0.317   
Sig. (2-tailed) 0.721 0.186 0.214 0.472 0.106 0.655 0.488 0.121 0.903 0.547 0.895 0.107    
Faecal coliforms Pearson Correlation 0.189 0.415 −0.161 0.147 0.034 −0.267 −0.379 0.025 0.259 −0.194 0.201 −0.259 0.362  
Sig. (2-tailed) 0.346 0.031 0.423 0.465 0.866 0.179 0.052 0.901 0.193 0.333 0.314 0.192 0.063   
Turbidity Pearson Correlation −0.189 −0.150 −0.480 −0.518 −0.174 −0.079 −0.086 −0.371 −0.003 −0.212 −0.444 −0.197 0.682 0.160 
Sig. (2-tailed) 0.346 0.454 0.011 0.006 0.385 0.696 0.670 0.057 0.990 0.288 0.020 0.325 0.000 0.425 

DISCUSSION

Total water hardness above recommended limits is stated as a major etiological factor causing cardiovascular disorders, diabetes, reproductive failure, neural diseases, and renal dysfunction (Subba Rao 2006; Sengupta 2013). In Gweru, seventy-eight percent of surveyed boreholes had hard or very hard water which is a health risk to the consumers. In addition, hard water use in bathing and washing requires higher volumes of soap to lather compared to soft water (World Health Organization 2011). The source of water hardness are naturally occurring rocks, felsites and porphyries; rich in magnesium, calcium, sodium and potassium. The metal ions Mg2+ and Ca2+ weathered from the rocks are responsible for water hardness. The ions concentrations were significantly high and correlated to water hardness (Table 8). These findings reinstate the notion that of the 1 in 8 people who lack safe drinking water a substantial percentage consume hard water (WHO & UNICEF 2012).

To reduce the risk associated with hard water, users should consider boiling the water as a primary precaution to get rid of temporary hardness. For secondary treatment options, there is need to further understand the nature of hardness; whether it is temporary or permanent hardness.

The iron guidelines provided for by WHO are not based on the health risk but on the aesthetics of drinking water. Higher concentrations, as recorded in 56% of the sampled boreholes, are responsible for bad taste, discolouring of water, bad smell, corrosivity (World Health Organization 2011). High concentrations of Iron could be related to the geomorphology and geology of the area; felsites rocks rich in iron especially the mafic rocks which can be fine grained thus high solubility and concentrations in ground water. Although there are high concentrations of iron in the drinking water the pH level recorded is relatively high (Table 3), suggestive of the presence of the non-ferrous form (Fe3+). Non-ferrous form is not bioavailable and is not easily absorbed in the gastrointestinal (GI) tract (Hallberg & Hulthén 2000; Hurrell & Egli 2010; Merrill et al. 2010; Merrill et al. 2012). However, low absorbance is not a cushion to the unknown effects of high iron concentrations because there is a potion that will be added by the dietary food, increasing the daily intake of Iron. In addition, once the non-ferrous form is in the acidic digestive system it can be reduced to the ferrous iron (Aster 2007).

The city council should consider reducing the iron concentrations using the following methods: First, an inexpensive biosand filtration at house hold or at borehole catchment level; this method is reported by Karakochuk et al. (2015) and Murphy et al. (2010) to successfully remove 98–99% and 99% of iron from groundwater, respectively. Second, water storage prior to use, that is, giving water settling time so as to increase likelihood of Fe2+ conversion to Fe3+ (Murphy et al. 2010).

Nitrates concentrations higher than the recommended limits cause infant methemoglobinemia (Bruning-Fann & Kaneene 1993). Only one borehole did not conform to the WHO limits and is located in one of the oldest high density suburbs in the city. Sewer leakages in the area is likely to be responsible for high nitrates levels recorded. The sewer system has outlived its design lifespan and is servicing more people than its design capacity. The borehole water is susceptible to nitrate loads associated with underground and aboveground seepage of waste water into the ground water. In addition, complex interactions of aquifers and groundwater movement may be responsible for import of nitrates from agricultural lands in neighbouring areas (Wakida & Lerner 2005). For example, Mkoba 13 is surrounded by areas under intensive urban agriculture. The residence practice rain fed agriculture on open stands that are yet to be built on or areas left for strategic reasons by the municipality. The average area under agriculture per urban farmer is 0.5 ha (Rakodi 1995). Of the urban farmers in surrounding areas, 65% are reported to over apply fertilisers to maximise yields (Sammie et al. 2014).

The fluoride concentrations in all the sampled boreholes were within the WHO limits. However, the concentrations were below 0.5 mgl−1 which is reportedly the minimum required to protect people from dental problems (Ozsvath 2009). Generally, intake of 0.5–1.0 mgl−1 is considered beneficial to human health; in the production and maintenance of health bones (Ayoob & Gupta 2006; Chilton et al. 2006; Mohapatra et al. 2009). In South Africa, the South Africa Dental Association recommends consumption of water with fluoride concentration in the range of 0.7–1.5 mgl−1 to reduce level of tooth decay (SADA 2014). Concentrations of <0.5 mgl−1 increases the risk of dental caries (Ozsvath 2009). In Gweru urban, only 22% of the boreholes had fluoride concentrations above the lower safe limit. This is risky given that Zimbabwe like other African countries has not set low and high empirically tested threshold levels on which the extremes of fluoride concentrations can be a problem or cause dental fluorosis (NRC 2006).

Ground water, in most cases, contains high concentrations of fluoride which causes dental and skeletal fluorosis with such cases recorded in China (Guo et al. 2007; Gao et al. 2013), Sri Lanka and Ethiopia (Rango et al. 2012) among others. In this study, the low concentration of fluorides can be attributed to two factors. First, the neutral to alkaline pH of the water which prevent dissolution of fluorides (Subba Rao 2006). Second, high calcium content which may lead to formation of CaF2 (Subba Rao & John Devadas 2003). This is supported by the significant correlation between calcium and fluoride (p = 0.015).

Presents of coliform bacteria in water is used as an indicator of the general microbial conditions of the water and sub-groups may indicate the risks associated with use of such water. The risk posed to the Gweru residents by using ground water for portable purposes ranges from low to intermediate risk (Table 6). Most research done on water quality in Africa highlights the presence of coliform bacteria Total coliform bacteria indicates ‘All facultative anaerobic, gram-negative, non-spore-forming, oxidase-negative, rod-shaped bacteria that ferment lactose to acid and gas within 48 h at 35 °C or members of Enterobacteriaceae which are β-galactosidase positive’ (APHA 2012). They are common in the environment and are not explicitly harmful. Their presence however in drinking water indicates the probable occurrence of other pathogenic microbes (Cabral & Marques 2006). Faecal coliform is a subgroup of total coliform which is a thermo-tolerant bacteria that can grow at temperatures around 42 °C (Leclerc et al. 2001; APHA 2012).This subgroup is important in that most of the diseases causing bacteria e.g. vibrio cholerea and salmonella are spread in water contaminated with faecal matter (Grabow 1996).

Sixty-seven percent of the boreholes indicated presents of E. coli, which is consistently found in faeces of human beings and other animal (Tallon et al. 2005). E. coli is a subset of the thermotolerant coliforms with the enzyme β-glucuronidase and produce indole from tryptophan (Tallon et al. 2005). E. coli presents in sampled boreholes in Gweru is associated with pollution by sewage leaking into the groundwater. In addition, residents do their laundry including children nappies within 20 meter radius of the borehole. Safe laundry infrastructure was not included in the designs for ground water supply and can be a contributing factor to E. coli loads in the water. Although the presence of E. coli indicates faecal contamination and health risk, not all strains of E. coli cause diseases or pose a health risk, most E. coli are commensal bacteria of the GI tract (Salyers & Whitt 2002).

CONCLUSION

The research advances the need to carry out ground water quality tests in urban areas as a way of minimising the health risk associated use of groundwater. It was noted that 80% of the tested water quality parameters were within WHO guidelines for drinking water. Only Iron, nitrates, total hardness and E. coli load were above recommended limits set by WHO. Unless treated, it is very risky and not recommended for residents in Senga, Mkoba 20, Mambo, Mkoba 19, Riverside and Mkoba 13 to use borehole water for potable uses. It is therefore recommended that the city or households chlorinates the borehole water to reduce the health risk associated with E. coli. There exist strong and significant correlations between some water quality parameters, however, there are other parameters that were significantly correlated but with a weak correlation which suggest the possibility of their correlations to be strong if the analysis was carried out on short time/seasonal intervals.

Future research need to focus on heavy metal concentrations, temporal variability of ground water quality and seasonal correlations of water quality parameters.

REFERENCES

REFERENCES
Addiscott
T. M.
1996
Fertilizers and nitrate leaching
.
Issues in Environmental Science Technology
5
,
1
26
.
Addiscott
T. M.
2005
Nitrate in Fresh Water and Nitrous Oxide in the Atmosphere. In: Nitrate, Agriculture and Environment
(pp.
110
126
).
Addiscott
T. M.
Benjamin
N.
2004
Nitrate and human health
.
Soil Use and Management
20
(
2
),
98
104
.
http://doi.org/10.1111/j.1475-2743.2004.tb00344.x
.
Almasri
M. N.
2007
Nitrate contamination of groundwater: a conceptual management framework
.
Environmental Impact Assessment Review
27
(
3
),
220
242
.
http://doi.org/10.1016/j.eiar.2006.11.002
.
APHA
2012
Standard Methods for the Examination of Water and Wastewater. American Water Works Association/American Public Works Association/Water Environment Federation
.
Aster
J. C.
2007
The hematopoietic and lympoid system
. In:
Robbins Basic Pathology
8th edn
. (
Kumar
V.
Abbas
A. K.
Fausto
A.
Mitchell
R.
, eds).
Sauders Elsevier
,
Philadelphia
.
Ayoob
S.
Gupta
A. K.
2006
Fluoride in Drinking Water: A Review on the Status and Stress Effects
.
Critical Reviews in Environmental Science and Technology (Vol. 36). http://doi.org/10.1080/10643380600678112
.
Bain
R.
Gundry
S.
Wright
J.
Yang
H.
Pedley
S.
Bartram
J.
2012
Accounting for water quality in monitoring access to safe drinking-water as part of the Millennium Development Goals: lessons from five countries
.
Bulletin of the World Health Organization
.
90
,
228A
235A
.
http://doi.org/10.2471/BLT.11.094284
.
Bruning-Fann
C. S.
Kaneene
J. B.
1993
The effects of nitrate, nitrite and N-nitroso compounds on human health: a review
.
Veterinary and Human Toxicology
35
(
6
),
521
538
.
Cabral
J. P.
Marques
C.
2006
Faecal coliform bacteria in Febros River (northwest Portugal): temporal variation, correlation with water parameters, and species identification
.
Environmental Monitoring and Assessment
118
(
1–3
),
21
36
.
http://doi.org/10.1007/s10661-006-0771-8
.
Chilton
J.
Dahi
E.
Lennon
M.
Jackson
P.
2006
Fluoride in Drinking-water
.
World Health
.
Coulter
C. B.
Kolka
R. K.
Thompson
J. A.
2004
Water quality in agricultural, urban, and mixed land use watersheds1
.
Journal of the American Water Resources Association
40
(
6
),
1593
1601
.
http://doi.org/10.1111/j.1752-1688.2004.tb01608.x
.
Foster
S.
Hirata
R.
Misra
S.
Garduno
H.
2010
Urban Groundwater Use Policy-Balancing the Benefits and Risks in Developing Nations. GW-MATE Strategic Overview Series
.
Gao
X. B.
Zhang
F. C.
Wang
C.
Wang
Y. X.
2013
“Coexistence of High Fluoride Fresh and Saline Groundwaters in the Yuncheng Basin, Northern China.”
Procedia Earth and Planetary Science
7
,
280
83
.
doi:10.1016/j.proeps.2013.03.052
.
Gleick
P. H.
2003
The human right to water
.
Water Nepal
.
9-10
(
1–2
),
115
149
.
http://doi.org/10.3126/wn.v10i1.97
.
Grabow
W. O. K.
1996
Waterborne diseases: Update on water quality assessment and control
.
Water SA
22
(
2
),
193
202
.
Guo
Q.
Yanxin
W.
Teng
M.
Rui
M.
2007
Geochemical Processes Controlling the Elevated Fluoride Concentrations in Groundwaters of the Taiyuan Basin, Northern China
.
Journal of Geochemical Exploration
93
(
1
),
1
12
.
doi:10.1016/j.gexplo.2006.07.001
.
Hallberg
L.
Hulthén
L.
2000
Prediction of dietary iron absorption: an algorithm for calculating absorption and bioavailability of dietary iron
.
The American Journal of Clinical Nutrition
71
(
5
),
1147
1160
. .
Hurrell
R.
Egli
I.
2010
Iron bioavailability and dietary reference values 1–4
.
The American Journal of Clinical Nutrition
91
(
Suppl.
),
1461s
1467s
.
http://doi.org/10.3945/ajcn.2010.28674F.Am
.
Jarup
L.
2003
Hazards of heavy metal contamination
.
British Medical Bulletin
68
(
1
),
167
182
.
http://doi.org/10.1093/bmb/ldg032
.
Karakochuk
C. D.
Murphy
H. M.
Whitfield
K. C.
Barr
S. I.
Vercauteren
S. M.
Talukder
A.
Porter
K.
Kroeun
H.
Eath
M.
McLean
J.
Green
T. J.
2015
Elevated levels of iron in groundwater in Prey Veng province in Cambodia: a possible factor contributing to high iron stores in women
.
Journal of Water and Health
13
(
2
),
575
586
.
http://doi.org/10.2166/wh.2014.297
.
Leclerc
H.
Mossel
D. A.
Edberg
S. C.
Struijk
C. B.
2001
Advances in the bacteriology of the coliform group: their suitability as markers of microbial water safety
.
Annual Review of Microbiology
55
,
201
234
.
http://doi.org/10.1146/annurev.micro.55.1.201
.
Lerner
D. N.
Harris
B.
2009
The relationship between land use and groundwater resources and quality
.
Land Use Policy
26
(
SUPPL. 1
).
S265
S273
.
http://doi.org/10.1016/j.landusepol.2009.09.005
.
Margat
J.
van der Gun
J.
2013
Groundwater around the World : A Geographic Synopsis. CRC Press/Balkema
.
Merrill
R. D.
Labrique
A. B.
Shamim
A. A.
Schulze
K.
Christian
P.
Merrill
R. K.
West
K. P.
Jr.
2010
Elevated and variable groundwater iron in rural northwestern Bangladesh
.
Journal of Water and Health
8
(
4
),
818
825
.
http://doi.org/10.2166/wh.2010.144
.
Merrill
R. D.
Shamim
A. A.
Ali
H.
Jahan
N.
Labrique
A. B.
Christian
P.
West
K. P. J.
2012
Groundwater iron assessment and consumption by women in rural northwestern Bangladesh
.
International Journal for Vitamin and Nutrition Research. Internationale Zeitschrift Fur Vitamin- Und Ernahrungsforschung. Journal International de Vitaminologie et de Nutrition
82
(
1
),
5
14
.
http://doi.org/10.1024/0300-9831/a000089
.
Mohapatra
M.
Anand
S.
Mishra
B. K.
Giles
D. E.
Singh
P.
2009
Review of fluoride removal from drinking water
.
Journal of Environmental Management
91
(
1
),
67
77
.
http://doi.org/10.1016/j.jenvman.2009.08.015
.
Mugandani
R.
Wuta
M.
Makarau
A.
Chipindu
B.
Gweru
S. R.
Pleasant
M.
2012
Re-classification of the agro-ecological regions of Zimbabwe in conformity with climate variability and change
.
African Crop Science Journal
20
(
S2
),
361
369
.
Murphy
H. M.
McBean
E. A.
Farahbakhsh
K.
2010
A critical evaluation of two point-of-use water treatment technologies: can they provide water that meets WHO drinking water guidelines?
Journal of Water and Health
8
(
4
),
611
630
.
http://doi.org/10.2166/wh.2010.156
.
NRC
2006
Fluoride in drink water: a scientific review of EPA's standards
.
The National Academies Press
531
.
85
106
. .
Nyamapfene
K. W.
1991
The Soils of Zimbabwe. Harare: Nehanda Publishers
. .
Onda
K.
LoBuglio
J.
Bartram
J.
2012
Global access to safe water: accounting for water quality and the resulting impact on MDG progress
.
International Journal of Environmental Research and Public Health
.
9
(
3
),
880
894
.
http://doi.org/10.3390/ijerph9030880
.
Ozsvath
D. L.
2009
Fluoride and environmental health: a review
.
Reviews in Environmental Science and Biotechnology
8
(
1
),
59
79
.
http://doi.org/10.1007/s11157-008-9136-9
.
Pionke
H. B.
Urban
J. B.
1985
Effect of agricultural land use on ground-water quality in a small Pennsylvania watershed
.
Ground Water
23
(
1
),
68
80
.
http://doi.org/10.1111/j.1745-6584.1985.tb02781.x
.
Rakodi
C.
1995
The household strategies of the urban poor: coping with poverty and recession in Gweru, Zimbabwe
.
Habitat International
19
(
4
),
447
471
.
http://doi.org/10.1016/0197-3975(95)00039-I
.
Rango
T.
Kravchenko
J.
Atlaw
B.
McCornick
P. G.
Jeuland
M.
Merola
B.
Vengosh
A.
2012
Groundwater quality and its health impact: an assessment of dental fluorosis in rural inhabitants of the Main Ethiopian Rift
.
Environment International
43
(
1
),
37
47
.
http://doi.org/10.1016/j.envint.2012.03.002
.
Rao
S. V. N.
Bhallamudi
S. M.
Thandaveswara
B. S.
Mishra
G. C.
2004
Conjunctive use of surface and groundwater for coastal and deltaic systems
.
Journal of Water Resources Planning and Management
.
130
(
3
),
255
267
.
http://doi.org/10.1061/(ASCE)0733-9496(2004)
.
SADA
2014
SADA Endorses fluoridation
.
South African Dental Journal
69
(
1
),
4
.
Salyers
A. A.
Whitt
D. D.
2002
Bacterial Pathogenesis: A Molecular Approach
,
2nd edn
.
ASM Press
,
Washington, DC
.
Sammie
B.
Chitata
T.
Chagonda
I.
Zirebwa
F.
Gwazane
M.
2014
Dynamics of maize production practices in urban open field agriculture in Zimbabwe
.
International Journal of Agronomy and Agricultural Research
5
(
2
),
164
170
.
Schot
P. P.
Pieber
S. M.
2012
Spatial and temporal variations in shallow wetland groundwater quality
.
Journal of Hydrology
,
422–423
,
43
52
.
http://doi.org/10.1016/j.jhydrol.2011.12.023
.
Sengupta
P.
2013
Potential Health Impacts of Hard Water
.
International Journal of Preventive Medicine
4
(
8
),
866
875
.
Sorenson
S. B.
Morssink
C.
Campos
P. A.
2011
Safe access to safe water in low income countries: water fetching in current times
.
Social Science and Medicine
72
,
1522
1526
.
http://doi.org/10.1016/j.socscimed.2011.03.010
.
Subba Rao
N.
2006
Seasonal variation of groundwater quality in a part of Guntur District, Andhra Pradesh, India
.
Environmental Geology
49
(
3
),
413
429
.
http://doi.org/10.1007/s00254-005-0089-9
.
Subba Rao
N.
John Devadas
D.
2003
Fluoride incidence in groundwater in an area of Peninsular India
.
Environmental Geology
45
(
2
),
243
251
.
http://doi.org/10.1007/s00254-003-0873-3
.
Sundaram
B.
Feitz
J. A.
Caritat
D. P.
APlazinska
A.
Brodie
S. R.
Coram
J.
Ransley
T.
&
Geosicence Australia
2010
Groundweater Sampling and Analysis-A Field Guide
.
Tallon
P.
Magajna
B.
Lofranco
C.
Kam
T. L.
2005
Microbial indicators of faecal contamination in water: a current perspective
.
Water, Air, and Soil Pollution
166
(
1–4
),
139
166
.
http://doi.org/10.1007/s11270-005-7905-4
.
US-EPA
2012
Coliforms – Total, Fecal and E-Coli (No. DOC316.53.001224). Filtration
.
USA
.
Van Der Hoven
S. J.
Solomon
D. K.
Moline
G. R.
2005
Natural spatial and temporal variations in groundwater chemistry in fractured, sedimentary rocks: Scale and implications for solute transport
.
Applied Geochemistry
20
(
5
),
861
873
.
http://doi.org/10.1016/j.apgeochem.2004.11.013
.
Vincent
V.
Thomas
R. G.
1960
An Agricultural Survey of Southern Rhodesia: Part I: Agro-ecological Survey
.
Government Printers
,
Salisbury
.
Wakida
F. T.
Lerner
D. N.
2005
Non-agricultural sources of groundwater nitrate: a review and case study
.
Water Research
.
39
(
1
),
3
16
.
http://doi.org/10.1016/j.watres.2004.07.026
.
World Health Organization
2011
Hardness in Drinking-water: Background document for development of WHO Guidelines for Drinking-water Quality. World Health Organization
.
WHO and UNICEF
2012
Progress on drinking water and sanitation, 2012 update. Update
. .
WHO and UNICEF
2014
Progress on sanitation and drinking-water - 2014 update. … Monitoring Programme for water supply and sanitation…. http://doi.org/978.92.4.150724.0
.
ZimStat
2012
.
Zimbabwe National Census 2012 Report, Government of Zimbabwe, Harare. http://www.zimstat.co.zw/sites/default/files/img/National_Report.pdf
.