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Original article
12 (
8
); 2104-2110
doi:
10.1016/j.arabjc.2015.01.001

Evaluation of the suitability of surface water from Riyadh Mainstream Saudi Arabia for a variety of uses

 Department of Agricultural Engineering, College of Food and Agricultural Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia
Received: , Accepted: ,
© The Author(s) 2019
Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Peer review under responsibility of King Saud University.

Abstract

An evaluation of the suitability of surface water for different uses from the mainstream running through Riyadh, Saudi Arabia, was conducted using three indices namely: water quality index (WQI), percentage of sodium (%Na) and Nemerow’s pollution index (NPI). The water samples were collected on monthly basis from June 2009 to March 2010 from 10 sites. The WQI was calculated based on different water standards for different uses. Excellent water has WQI value of 50–100, where WQI is calculated based on 29 parameters. The permissible range of %Na in water used for irrigation purpose should be between 40% and 60%. On the other hand, if 0 < NPI < 1.0, then the water is regarded as being in a good condition. In this study, WQI ranged from 34 to 513 with an average of 282, thereby indicating mild pollution at some sites. The %Na value ranged between 19 and 66, with an average value of 46 indicating that the water is suitable for irrigation at most of the sites. The NPI ranged between 1 and 11 with an average value of 5, which indicates that water in most of the sites is in a good condition. It is recommended that surface water from these sites should not be used for human activities. The formulas used to calculate the water quality indices are easy to use thus providing a valuable tool for the accurate monitoring of water pollution.

Keywords

Water quality index
Percentage of sodium
Nemerow’s pollution index
Irrigation
1

1 Introduction

The surface water quality in a region largely depends on the nature and extent of the industrial, agricultural and other anthropogenic activities which exist within the catchments (Banejad and Olyaie, 2011). The control of water quality has become very important in maintaining the sustainability of water resources. However, the main cause of water pollution is human activities (Ashraf et al., 2010). Two sources of water pollution can be recognized, namely point sources and non-point sources. Point sources discharge pollutants at specific locations (e.g. landfills and industrial wastes) through inlets into surface water, while non-point sources (e.g. acid rain, agriculture, construction and domestic pollutants) cannot be traced to a single discharge (Ashraf et al., 2010). The water quality directly affects virtually all water uses (Najah et al., 2009); for example, fish survival, agricultural usage, including irrigation and livestock watering are affected by the physical, chemical, biological, and microbiological conditions existing in a watercourses (Najah et al., 2009).

Saudi Arabia is located within an extremely arid region where the average rainfall is low and the availability of surface water is very limited. This surface water is the result of rainfall that floods and flows into a mainstream running through Riyadh, Saudi Arabia, for short distance. This available surface water is an important resource for Saudi Arabia due to its good quality (Al-Motairi, 2001), although, due to discharges of domestic and industrial wastewaters, the quality of this surface water is deteriorating rapidly (Chiang et al., 2001). There is a possibility of water to be contaminated with persistent organic pollutants (POPs) due to their extensive occurrence, long-term persistence and transportation, robust resistance, high bioaccumulation, and potential impacts on ecosystems. Hexachlorocyclohexanes (HCHs), dichlorodiphenyltrichloroethane (DDT), and polychlorinated biphenyls (PCBs) are frequently found in the environment and their restricted application helps to keep the water away from contamination. Water quality mainly depends on the source, location and the intended uses of the water. There are many different physical, biological, and chemical parameters as well as water quality criteria (i.e. standards) that can be used to measure water quality and, therefore, there is no single correct answer to the question – ‘what is water quality’ (UNEP GEMS/Water Programme, 2007). Water quality may be assessed in a variety of ways, for example in relation to the quality of water needed for drinking water or the quality of water needed to sustain agricultural activities (Srebotnjak et al., 2012). Irrigation with poor quality waters may bring undesirable elements to the soil in excessive quantities thereby affecting its fertility (Nishanthiny et al., 2010). As a result of these and other issues, the evaluation of water quantity and quality is essential for the development of civilization and to establish database for planning future water resources development strategies. In order to assess water quality for different uses, a variety of indices are used, although the water quality index (WQI) is one of the most effective tools to monitor the surface as well as groundwater pollution and can be used efficiently in the implementation of water quality upgrading programmes (Alam and Pathak, 2010). The objective of an index is to turn multifaceted water quality data into simple information that is both comprehensible and useable by the public. The WQI was first formulated by Horton (1965) and subsequently used by several workers for the quality assessment of different water resources (Ramakrishanaiah et al., 2009; Samantray et al., 2009; Yadav et al., 2010). This study focuses on the evaluation of surface water for its suitability for a range of purposes; the evaluation being based on WQI, %Na and Nemerow’s pollution index.

2

2 Materials and methods

2.1

2.1 Study area

The mainstream running through Riyadh, Saudi Arabia, is located in the Wadi Hanifa area in the Nejd region of central Saudi Arabia. The stream runs for a length of 120 km from north to south, cutting through the capital city, Riyadh. Several towns and villages lie along the stream. It extends from north of Al Uyaynah to south of Al-Hair city. Industrial effluents as well as domestic sewage/wastes are disposed into it, either with partial or no pretreatment and hence, increasing concentration of different kinds of pollutants reaches this watercourse. The watershed area of the stream is estimated to be about 4400 km2 and the mainstream flood-channel is located slightly east of the centre of the catchment area and flows northwest to southeast. The source of the water in the main channel of the stream is seasonal rainfall.

2.2

2.2 Sampling procedure

Water samples from the specified locations were collected during June, July, August, September, October, November and December of the year 2009 and during January, February and March of the year 2010. The water samples were taken according to standard method (APHA, 1992.). Samples were collected from the number of distribution sites and selection of the sample was performed depending on stream characteristics, study objectives, availability of equipment, and few other required factors. The integrated sample was taken from top to bottom in the middle of the main channel of the stream and from side to side at mid-depth, preferably they were taken at various points of equal distance across the stream. After that, the samples were transferred to the laboratory of Saudi Berkefeled Filters Co., in Riyadh for the chemical analysis. All chemical analyses were achieved according to standard methods (APHA, 1992). Table 1 shows the area code, sampling area, description of area and, northing and easting of sampling area.

Table 1 Area code, sampling area, description of area, northing and easting of sampling area.
Area code Sampling area Description of area Northing Easting
SW1C Arriyadh North diversion channel- down stream of confluence of proposed channel and DNC 2724103.251 669451.238
SW12a Arriyadh Underneath King Fahad expressway, bridge upstream of bioremediation 2721476.628 672518.914
SW8A Al Masane Manfuha complex 2720071.397 675685.708
SW8C Al Masane Below STP discharge near bridge 2718369.409 675859.770
SW23 Al Masane Batha channel before meeting the main stream 2716538.376 676839.277
SW14 Al Masane At inlet of culvert Batha channel in the stream 2716278.544 676631.335
SW20 Al Masane 100 m downstream of culvert immediately downstream of confluence of existing channel and a tributary from the Batha channel 2716194.470 676823.123
SW8g Al Masoriyah 150 m downstream of Tannery 2713161.808 6786648.795
SW10b Al Hair Al Hair bridge 2697973.000 685465.000
SW11b Near Al Hair Lake Al Hair lake 2696646.000 693373.000

2.3

2.3 Calculation of water quality indices

2.3.1

2.3.1 Water quality index (WQI)

The WQI was calculated as follows:

(1)
WQI = ∑ q i × W i ∑ W i

The quality rating scale for each parameter qi was calculated by using this expression

(2)
q i = 100 × V n V s where Vn is actual amount of nth parameter and Vs is permissible limits of corresponding parameter as listed in Table 2. Relative weight (Wi) was calculated by a value inversely proportional to the permissible limits of the corresponding parameter as follows:
(3)
W i = 1 V s
Table 2 Water quality parameters used in calculating WQI.
No. Parameters Unit Permissible limits Water classification Water use Source
1 PH – 8.5 Surface water Drinking Akoteyon et al. (2011)
2 Conductivity μS /cm 1000 Surface water Akoteyon et al. (2011)
3 TDS mg/L 1000 Drinking WHO (1993)
4 Suspended solids mg/L 100 Drinking Alam and Pathak (2010)
5 Dissolved oxygen mg/L 10 Unpolluted waters Joseph and Jacob (2010)
6 BOD mg/L 5 Unpolluted natural waters http://www.dnr.mo.gov/env/esp/waterquality-parameters.htm
7 COD mg/L 15 Uncontaminated source water Chiang et al. (2001)
8 Total organic carbon mg/L 2 Uncontaminated source water Chiang et al. (2001)
9 Alkalinity mg/L 200 Typical surface waters SWRP (2011)
10 Bicarbonate mg/L 250 Surface water WHO (1996)
11 Calcium mg/L 100 Surface water WHO (1996)
12 Chloride mg/L 250 Drinking Yogendra and Puttaiah (2008)
13 Magnesium mg/L 50 WHO (1996)
14 Nitrate mg/L 45 Drinking Yogendra and Puttaiah (2008)
15 Potassium
16 Sodium mg/L 250 Surface water Drinking Akoteyon et al. (2011)
17 Sulphate mg/L 250 WHO (1996)
18 Ammonium mg/L 20 http://www.water-chemistry.in/2008/08/ammonium-nh4/
19 Boron
20 Copper μg/L 4 http://dnr.wi.gov/org/water/dwg/copper.htm
21 Iron mg/L 0.3 Irrigation purposes Zinati (2005)
22 Manganese
23 Phosphate mg/L 0.1 Khanfar (2008)
24 Total petroleum hydrocarbon μg/L 50 Sea water Aquatic organisms Said and Hamed (2006)
25 Oil & grease mg/L 10 Agriculture purposes Frederick (2005)
26 Total coliforms Cfu/100 mL 1000 Water is clean of pollution Laskar and Gupta (2011)
27 Faecal coliforms Cfu/100 mL 100 Water is clean of pollution Laskar and Gupta (2011)

Generally, WQI is discussed for different uses. If all measured water quality parameters have permissible limits as shown in Table 2, the excellent WQI will equal 100; water quality classification based on WQI value is depicted in Table 3.

Table 3 Water quality classification based on WQI value (Ramakrishanaiah et al., 2009).
WQI Water quality
<50 Excellent
50–100 Good water
100–200 Poor water
200–300 Very poor water
>300 Water unsuitable

2.3.2

2.3.2 Percentage of sodium

Irrigation water containing large amounts of sodium is of special concern due to the negative effect of this element on the soil and excess sodium in waters produces the undesirable effects of changing soil properties and reducing soil permeability. As a result, the assessment of sodium concentration is necessary when considering the suitability of water for irrigation purposes (Nishanthiny et al., 2010). The percentage of sodium (%Na) is expressed as follows (Rathod et al., 2011):

(4)
% Na = 100 × Na ( Ca + Mg + Na + K ) where Ca is calcium concentration, Mg is magnesium concentration, Na is sodium concentration and K is potassium concentration. The quantities of all ions are expressed in mg/L. The classification of water was grouped based on per cent Sodium as Excellent (<20%), Good (20–40%), Permissible (40–60%), Doubtful (60–80%) and Unsuitable (>80%) (Sadashivaiah et al., 2008).

2.3.3

2.3.3 Nemerow and Sumitomo pollution indexes

The Nemerow pollution index (NPI) refers to the pollution calculation which developed by Nemerow and Sumitomo (1970). This index is studied by Wu et al. (2010) and Ming et al. (2010). The NPI is a simplified pollution index and it is given as

(5)
NPI = Ci Li where Ci is the observed concentration of ith parameter and Li is permissible limit of ith parameter. An average of pollution index (NPIavg) can be defined as
(6)
NPI avg = 1 m ∑ i = 1 m NPI i

The ideal NPIavg should be less than or equal to one, and the level of pollution classification is based on water standard quality divided into four classes, namely 0 < NPIavg < 1.0: meeting standard quality (good condition), 1.0 < NPIavg < 5.0: slight polluted, 5.0 < NPIavg < 10: medium pollution and NPIavg > 10: heavily polluted.

3

3 Results and discussion

3.1

3.1 Water quality index

Fig. 1 shows the classification of water quality based on WQI. Out of selected water samples based on WQI, 7% of the water samples have excellent water quality, 17% of the water samples have good water quality, 16% of the water samples have poor water quality, 0% of the water samples have very poor water quality and 60% of the water samples have unsuitable water quality. Fig. 2 depicts the variation of WQI at the different sites (mean values for June 2009 through March 2010), and Fig. 3 shows the variation of WQI from June 2009 through March 2010 (mean values for the different sites). As can be seen in Fig. 2, some sites had good quality water. The water quality changed during months as shown in Fig. 3. Pollution at sites SW10b, SW11b, SW20, SW23, SW8C, SW8g and SW1C may be attributed to these sites receiving large quantities of wastewater from a variety of sources. Rainfall appeared to have no consistent effect on the WQI, as a similar value was recorded in June, a period approaching the summer season. From these research results on water quality, it could be seen that water quality in the most studied sites was of poor quality and polluted by discharges from the many industrial activities located along this watercourse. As a result, the population of this region should be aware of the current pollution of the water source as well as being informed of the importance of such water and its benefits, in the hope that they will help to reduce this pollution.

Water quality based on WQI.
Figure 1 Water quality based on WQI.
The variation of WQI at the different sites (mean values for June 2009 through March 2010).
Figure 2 The variation of WQI at the different sites (mean values for June 2009 through March 2010).
The variation of WQI from June 2009 through March 2010 (mean values for the different sites).
Figure 3 The variation of WQI from June 2009 through March 2010 (mean values for the different sites).

3.2

3.2 Percentage of sodium

Based on per cent sodium content, 1% of the water samples have excellent irrigation water quality, 16% of the water samples have good irrigation water quality, 80% of the water samples have permissible irrigation water quality, 3% of the water samples have doubtful irrigation water quality and 0% of the water samples have unsuitable irrigation water quality as depicted in Fig. 4. Fig. 5 shows the variation of %Na at the different sites (mean values for June 2009 through March 2010), and Fig. 6 shows the variation of %Na from June 2009 through March 2010 (mean values for the different sites). As can be seen in Fig. 5, all the sites have water quality suitable for irrigation purposes, and the water quality changed little during the months of the study, as shown in Fig. 6.

Irrigation water quality based on %Na.
Figure 4 Irrigation water quality based on %Na.
The variation of %Na at the different sites (mean values for June 2009 through March 2010).
Figure 5 The variation of %Na at the different sites (mean values for June 2009 through March 2010).
The variation of %Na from June 2009 through March 2010 (mean values for the different sites).
Figure 6 The variation of %Na from June 2009 through March 2010 (mean values for the different sites).

3.3

3.3 Nemerow’s pollution index (NPI)

Out of selected water samples, based on NPI, 5% of the water samples exhibit good water quality, 37% of the water samples have slightly polluted water, 57% of the water samples have a medium pollution water quality and 1% of the water samples are heavily polluted (Fig. 7). Fig. 8 shows the variation of NPIavg at different sites (mean values for June 2009 through March 2010). Meanwhile, Fig. 9 shows the variation of NPIavg from June 2009 through March 2010 (mean values for the different sites). As can be seen in Fig. 8, the water at some sites was polluted, a fact which may be due to the difference in activities being conducted near to the sites. Finally, the degree of pollution changed little over the months of the study (Fig. 9).

Water quality based on NPIavg.
Figure 7 Water quality based on NPIavg.
The variation of NPIavg at the different sites (mean values for June 2009 through March 2010).
Figure 8 The variation of NPIavg at the different sites (mean values for June 2009 through March 2010).
The variation of NPIavg from June 2009 through March 2010 (mean values for the different sites).
Figure 9 The variation of NPIavg from June 2009 through March 2010 (mean values for the different sites).

4

4 Conclusions

The water quality indices were in the range of 34–513 indicating mild pollution at some of the sites studied. The WQI was calculated based on 29 parameters and on different water standards for different uses. The percentage of sodium was in the range of 19–66, with an average value of 46, indicating the water’s suitability, at most sites, for irrigation. The Nemerow’s pollution index was in the range of 1–11 with an average value of 5, indicating that water at most of the sites is in a good condition. It is recommended that the water from the studied sites should not be used for human activities without treatment by appropriate methods. In conclusion, formulae used to calculate the WQI are easy to use and the WQI is a valuable tool for observation of water environment and for monitoring the pollution.

Acknowledgement

The author would like to acknowledge ArRiyadh Development Authority for their cooperation regarding the provision of surface water data of Riyadh City.

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