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A cross-sectional epidemiological method was adopted to investigate the four main urban …

Biology Articles » Hydrobiology » Bacteriological assessment of urban water sources in Khamis Mushait Governorate, southwestern Saudi Arabia » Methods

- Bacteriological assessment of urban water sources in Khamis Mushait Governorate, southwestern Saudi Arabia

Study area, design, samples, and materials

The study area

The study was conducted in an urban zone of Khamis Mushait Governorate (about 43 km × 25 km centred at 18.3° N, 42.8° E [42], with a population of 497,000 [2007]), which covers about 1075 km2, with an elevation ranging from about 982 to 1946 m (mean 1464 m) above sea level, an average annual rainfall of 355 mm (range 160–450 mm), it has a two short rainy seasons, 70% of which occurs in March and May (ranges between 40–55 mm) and August and September (ranges between 36–62 mm) with about 300 mm/y and average minimum and maximum temperatures of 19.3 C and 29.70 C, respectively [17,5-7].


In this study, a cross-sectional epidemiological method was used to assess representative samples of the four main urban water sources (i.e. bottled, desalinated, surface, and well water; see Table 1) in Khamis Mushait Governorate, southwestern Saudi Arabia. These representative samples were examined between February and June 2007 to assess their bacteriological characteristics and suitability for potable purposes. Using a simple random sampling technique, a total of 95 drinking water samples were collected from bottled water, desalinated water, surface water, and groundwater (wells of different types).

Sampling and materials

Simple random sampling was the method chosen for this study. Geographical settings of both the surface water and wells were determined in advance via a digital satellite mapping processing technique (Erdas Map sheet, v.9 and Global Mapper Software, LLC v. 10) by using the Google Earth digital mapping engine (a paid copy of Google Earth pro™) to obtain an overview, to ease virtual navigation, and to refine the micro-geographic data when mapping the Khamis Mushait administrative area [49,5-7]. (Satellite images are aerial photographs and do not represent real time; they have an average high resolution age of several years and a spatial resolution of 25 m per pixel or even higher [15 m] in some areas) [42].

The network sampling method offered options that may have been more efficient for this study than classical sampling [50]. It employed good local knowledge, including of streets, in determining targeted water groups, their geographic distribution, and boundaries using Google Earth digital maps as a powerful platform in improving micro-sampling, processing, field manipulations and operations, tracking, allocation, and high-quality map creation. All of these elements supported the training of the research sampling team and helped in understanding the spatiotemporal relationship and geographic patterns between all entities. Composite maps of different types (i.e. hand drawn maps) were also used efficiently by the researcher and the field support team for the disk and ground phases.

For bottled water, sixteen brands (known to the local community) consisting of spring and purified bottled water types were purchased from different local supermarkets within Khamis Mushait Governorate and sampled. For desalinated water, 31 water samples were obtained from Ashiab (i.e. distributing points for the Khamis Mushait Governorate water desalination station), using the simple random sampling technique, from water trailers, houses, urban water networks, fish markets, and slaughterhouses. For surface water, 15 specimens were collected from the selected sites, the Tandaha dam reservoir and valleys around Khamis Mushait Governorate, using the simple random sampling technique. From wells, 33 water samples were also selected from the chosen geo-sites of different types of wells located around the study area, using the simple sampling technique. Planning of both the surface and groundwater samples was carried out, and the specimens were assessed using spatial techniques (i.e. network method) for the digital satellite map of Khamis Mushait Governorate, using the Google Earth mapping engine [42].

Samples from each brand of bottled water were kept in a screw capped 1.5-litre plastic container. Samples from desalinated, surface, and well water were collected under completely sterile conditions and placed in sterile, screw capped, 150-ml plastic bottles, taking into consideration the standard methods of both gathering and handling water samples. All specimens of desalinated, surface, and well water were sampled and dispatched daily, with a minimum delay, in an FWD Car (provided by King Khalid University to the author and his trained sampling team [E AlOtaibi, MSA Zaki A Ghorm, and N Alshahrani]) to the Medical Laboratory Technology Department, Khamis Mushait Community College. Most water quality constituents were determined within 2–6 hours of collection [3].

The bacteriological examination of water samples includes Most Probable Number (MPN) of presumptive coliforms, faecal coliforms, and faecal streptococci (MPN/100 ml water) using the Multiple Tube Fermentation Technique [3,26]. Suspected colonies of coliform groups were also identified on the basis of morphological, cultural, and biochemical characteristics [51,9]. Significant differences between each two means were evaluated using SPSS-PC Version 11 of the Student-T-Test [52].

Quality assurance procedures

Sampling strategy and design

Disk preparation phase

○ Adoption of a two-stage sampling scheme.

○ Careful planning and choice of representative sampling groups and sites according to the adopted network sampling technique, and determining certain criteria such as control sites where major sampling groups exist (i.e. surface water points, valleys, and wells), impact sites where contamination is expected, such as polygons, and outlets (e.g. treated water discharges site) to maximise understanding the quality of urban water sources, and with the least risk of missing the correct representative sampling groups and sites.

○ Attention paid to ensure inclusion in the sampling frame of all groups and locations (sites, roads, venues, and so on) via screening, browsing, and delineation from a satellite digital map of the Khamis Mushait Governorate zone, because local pre-knowledge was preferred with regard to accessibility, safety, and permission.

○ Approximation of the number of the target study population in each group and sampling location.

○ Determination of the proportional allocation of samples between different groups and locations.

○ Training of interviewers\sample collectors to follow and to use the sampling strategy and procedures.

○ Implementation of ways to boost participation rates in the screening and core interviews and sample collection.

○ Planning of logistic needs of timing, gathering, handling samples, and laboratory.

○ Producing sampling cards to be completed to record observations at scene (sample ID and data/information: date, time, temperature, group, locality, problems in the area, sketch map).

○ Selection of an appropriate major sampling method [52] (i.e. simple random sample; network sampling).

○ Planning of pilot visits to samples of each group in the field to review strategy.

During sampling phase

▪ Use simple random selection procedures when feasible to select representative samples of each location for each group.

▪ Gather water specimens from each sampled location with a probability proportional to the estimated total of the target population.

▪ Interview all eligible persons with regard to this site (as auxiliary data).

▪ Collect auxiliary data (on sampled site, it may affect the probability of selection)

▪ Transport and store samples away from sunlight or extreme heat.

During analysis phase

○ Perform standard analysis procedures.

○ Compare results and findings of each sample within each group with their auxiliary data and other associated characteristics written on sample card to verify and to make sure it belongs to the same group and sampled location; assess reasons for refusal if there are any and determine whether refusal is associated with selection biases or just handling, and report immediately.

○ Assess representativeness of the selected samples by comparing the data with other data.

○ Incorporate weights into the analyses to reflect unequal probabilities of selection, incomplete sampling frame, and rates of refusal samples.

○ Assess the need to use statistical programmes that incorporate the design effect of such a cross-sectional study.

○ Compare findings relating to the collected samples with expected results of the groups.

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