Open Access

Evaluation of Shiraz wastewater treatment plant effluent quality for agricultural irrigation by Canadian Water Quality Index (CWQI)

Iranian Journal of Environmental Health Science & Engineering201310:27

https://doi.org/10.1186/1735-2746-10-27

Received: 4 October 2012

Accepted: 16 March 2013

Published: 8 April 2013

Abstract

Background

Using treated wastewater in agriculture irrigation could be a realistic solution for the shortage of fresh water in Iran, however, it is associated with environmental and health threats; therefore, effluent quality assessment is quite necessary before use. The present study aimed to evaluate the physicochemical and microbial quality of Shiraz wastewater treatment plant effluent for being used in agricultural irrigation. In this study, 20 physicochemical and 3 microbial parameters were measured during warm (April to September) and cold months (October to march). Using the measured parameters and the Canadian Water Quality Index, the quality of the effluent was determined in both warm and cold seasons and in all the seasons together.

Results

The calculated index for the physicochemical parameters in the effluent was equal (87) in warm and cold months and it was obtained as 85 for the seasons all together. When the microbial parameters were used in order to calculate the index, it declined to 67 in warm and cold seasons and 64 in all the seasons together. Also, it was found that three physicochemical parameters (TDS, EC, and NO3) and three microbial parameters (Fecal coliform, Helminthes egg, and Total coliform) had the most contribution to the reduction of the index value.

Conclusions

The results showed that the physicochemical quality of Shiraz Wastewater Treatment Plant Effluent was good for irrigation in the warm, cold, and total of the two kinds of seasons. However, by applying the microbial parameter, the index value declined dramatically and the quality of the effluent was marginal.

Keywords

Effluent Water reuse Irrigation CWQI Shiraz

Background

The Middle East and North Africa countries (MENA), with one percent of fresh water resources, are the most arid regions of the world [1]. Due to the scarcity of fresh water resources in these regions, wastewater reuse could be a realistic option to alleviate the shortage of fresh water resources in these communities and until now, the largest and most popular wastewater reuse has been in the agricultural irrigation field [2, 3]. Wastewater reuse is not a new issue; for instance, indications of wastewater reuse for agricultural irrigation extends back about 3000 years to the Minoan Civilization in Greece [4]. Also, the history of wastewater reuse in Iran is related to the Safavieh era (1501-1722AD) [5]. The main advantages of using the municipal Wastewaters Treatment Plants Effluent (WWTPE) are availability, being inexpensive to irrigate farmland, and being a constant source of fresh water [6, 7]. Other benefits of wastewater reuse are the possibility to recover the nutrients in the wastewater, reducing the use of fertilizers [6, 811], resolving the problems associated with wastewater disposal [1012], and groundwater recharge [10]. So today, there are plans for the wastewater reuse in many countries; for example, in Spain, using wastewater for irrigation is about 346 MCM/year and amount of wastewater reuse could be 1100 hm3 by 2012 [12, 13]. In California, about 78% of the treated wastewater is used for agricultural irrigation in central Valley and coastal areas [8]. Moreover, it is estimated that the treated wastewater effluent could be the main (about 70%) source of water for irrigation in Israel by 2040 [2]. Nevertheless, since some materials remain in wastewater effluent, despite the above-mentioned benefits, wastewater reuse could be associated with some risks [14]. Thus, several studies have evaluated the probable health and environmental impacts of wastewater reuse in agricultural irrigation. For example, in separate studies, Surdyk et al. [15], Wang et al. [16], and Reboll et al. [17] concluded that irrigation with wastewater effluent had no negative impacts on various agricultural products. However, in some studies evaluating the long-term effects of the wastewater effluent on the soil, the heavy metal pollution and reduction of soil quality have been reported [11, 18]. On the other hand, due to the presence of pathogens in wastewater effluent, the irrigation by this water resource could be associated with health hazards and increasing the risk of intestinal infections [19, 20]. Therefore, it seems that quality assessment of wastewater effluent before reuse projects is essential in order to prevent adverse health and environmental impacts.

According to the indicators of UN and the International Water Management Institute (IWMI), Iran is in a severe water crisis situation [21]. Thus, using new fresh water resources is very important in this country, especially in Fars province (in the southwest of Iran) in which, drought is considered as the main climatic feature [22]. Overall, it seems that Shiraz Wastewater Treatment Plant Effluent (SWTPE) could potentially be considered as a good source of fresh water supply and Fars Regional Water Organization plans to reuse SWTPE (about 29.5 MCM/year); hence, the current study aims to evaluate SWTPE quality for agricultural irrigation.

Materials and Methods

Status of the Shiraz wastewater treatment plant

SWTP is located in the southeastern region of the city. It covers 409000 inhabitants right now and it is estimated that the final coverage of inhabitants in this WWTP will be about 548000 in future. The average inlet flow rate of this WWTP is about 930 LPS and it is expected to provide about 29.5MCM/year of fresh water for irrigation. Activated sludge is the biological wastewater treatment processes of this WWTP and it includes different units of screen bar unit, primary settling tank, selector, aerated tank, secondary settling tank, and chlorination unit.

Sampling and measured parameters

In order to determine the quality of the SWTP for being reused in the agricultural irrigation, 20 physicochemical and 3 microbial parameters were evaluated during warm (April to September) and cold months (October to march). Then, 11 samples in warm and 7 samples in cool seasons were taken and analyzed from effluent of WWTP (grab sampling was used). The measured physiochemical parameter were pH, EC, TSS, TDS, Res.Cl, HCO3, Cl, SO4, Ca, Mg, Na, Mn, Hg, Fe, As, Cd, DO, COD, BOD5, and NO3, while the 3 microbial parameters included Fecal coliform, Total coliform, and Helminthes egg. It is worth noting that due to some limitations, helminthes egg and SO4 were measured just 8 (4 times in warm seasons and 4 times in cold seasons) and 12 times (6 times in warm seasons and 6 times in cold seasons), respectively.

Apparatus

The EC and pH of the study samples were measured using EC meter Metrohm (model 856) and pH Meter metrohm (model 827). In addition, the amounts of Ca, Mg, and Na were measured by Flame photometer Jenway (model PFP7). In order to measure COD and SO4, Spectrophotometer HACH (model DR/2500) was used. Also, by an Atomic Absorption Spectrometer GBC Scientific Equipment (model savant AA AAS), the concentrations of Mn, Fe, Hg, As, and Cd were determined in the samples. The concentration of DO in SWTP effluent was measured by DO meter HACH (model 850045). Also, Spectrophotometer PG Instruments Ltd (model T80) and Manometric respirometer HACH (model BOD Trak II) were used in order to measure NO3 and BOD5, respectively. Finally, Nickon microscope (model E100) was used for counting the number of helminthes egg.

Determination of the effluent quality

In order to determine the quality of the SWTPE, Canadian Water Quality Index (CWQI) was used. In general, three factors (F1, F2, and F3) are used to determine the CWQI. F1 (scope) indicates the percentage of the variables which depart from their objectives (Eq. (1)), while F2 (Frequency) represents the percentage of the tests which do not meet the objectives (Eq. (2)) [23, 24].
F 1 = Number of failed varialbes Total number of varialbes × 100
(1)
F 2 = Number of failed varialbes Total number of varialbes × 100
(2)
F3 (Amplitude) is calculated by an asymptotic capping function which scales the normalized sum of the excursions from the objectives (nse) in a range between 0 and 100 (Eq. (3)). F3 is obtained in a three-step process. At the first step, the "excursion" is calculated and the number of times an individual parameter is further than (when the objective is a minimum, less than) the objective is nominated as “excursion” and is calculated by Eq. (4) and Eq. (5). (In case the test value should not fall below the objective, Eq. (5) is used).
F 3 = nse 0.01 nse + 0.01
(3)
excursio n i = Failed Test Valu e i Objectiv e i 1
(4)
excursio n i = Objectiv e i Failed Test Valu e i 1
(5)
nse = i = 1 n excursio n i number of test
(6)
Then, the sum of the excursions from the objectives is calculated by Eq. (6) and, finally, the CWQI could be obtained from Eq. (7). It should be noted that 1.732, is a scaling factor and rearranges the index between 0 and 100 [25].
CWQI = 100 F 1 2 + F 2 2 + F 3 2 1.732
(7)
Different values obtained from the CWQI are classified in Table 1.
Table 1

Classification of CWQI values[26]

Rank

WQI value

Description

Excellent

95-100

There is no threat to the water quality and these index values can only be obtained when all parameters are within objectives virtually all the time.

Very Good

89-94

There is a slight presence of threat or impairment for the water quality

Good

80-88

There is minor degree of threat for the water quality; conditions rarely depart from desirable levels.

Fair

65-79

Water quality is usually protected but occasionally threatened; sometimes

conditions depart from desirable conditions

Marginal

45-64

Water quality is frequently threatened; conditions often depart from natural or desirable levels.

Poor

0-44

Water quality is almost always threatened andconditions usually depart from desirable levels.

The objectives used in the present study were selected based on the Iranian Department of Environment (IDOE) standards for wastewater reuse in agricultural irrigation; however, due to the lack of IDOE standards in this field, WHO, USEPA, and Jordan standards were used (Table 2). Also, the 90% cumulative probability was calculated for all the parameters and compared with the standards. Furthermore, since the effect of sodium should be considered in association with calcium and magnesium, Sodium Adsorption Ratio was used (SAR) instead of Na for calculating the CWQI.
Table 2

Minimum, maximum, mean, and cumulative probability of each measured parameter

Parameter

Unit

Min

Max

Mean

Cumulative probability (less than90%)

Standard

Specific Multiplier

Contribution Value %

pH (Warm)

-

7.46

8.25

7.861±0.281

7.57

6.5-8.5 (Iran)

0.5

3.88

pH (Cool)

7.69

8.17

7.902±0.192

8.181

pH (Overall)

7.46

8.25

7.877±0.057

8.22

EC (Warm)

μmoh/cm

1717

2351

1904±189.208*

2100*

700 (WHO)

0.1

0.78

EC (Cool)

1722

2340

1928.14±221.977*

2343*

EC (Overall)

 

1717

2351

1913.39±46.306*

2340*

   

TSS (Warm)

mg/L

18

115

61.18±33.722

80

100 (Iran)

0.5

3.88

TSS (Cool)

 

15

163

69.57±49.027

165

   

TSS (Overall)

 

15

163

64.44±9.234

115

   

TDS (Warm)

mg/L

1144

1518

1269.36±105.766*

1365*

450 (WHO)

1

7.76

TDS (Cool)

1126

1530

1311.83±165.153*

1533*

TDS (Overall)

 

1126

1530

1284.35±30.633*

1518*

   

Res. Cl (Warm)

mg/L

0

0

0±0

0

0.2 (Iran)

0.5

3.88

Res. Cl (Cool)

0

0.25

0.057±0.101

0.26

Res. Cl (Overall)

 

0

0.25

0.022±0.015

0.15

   

HCO3 (Warm)

mg/L

365.94

542.811

441.345±58.134

540.523

520 (Jordan)

0.5

3.88

HCO3 (Cool)

378.138

518.415

424.316±54.987

523.315

HCO3 (Overall)

 

365.94

542.811

434.723±13.182

518.415

   

Cl (Warm)

mg/L

248.171

372.256

283.624±33.596

369.564

600 (Iran)

0.5

3.88

Cl (Cool)

219.808

301.35

271.721±27.418

308.593

Cl (Overall)

 

219.808

372.256

278.995±7.321

301.35

   

SO4 (Warm)

mg/L

171.465

265.65

224.112±44.357

262.863

1000 (Jordan)

0.5

3.88

SO4 (Cool)

182.091

444.36

256.473±100.383

500

SO4 (Overall)

 

171.465

444.36

240.292±21.909

444.36

   

Ca (Warm)

mg/L

100.2

130.26

114.956±8.129

127.35

200 (EPA)

0.5

3.88

Ca (Cool)

94.188

180.36

116.518±30.555

195

Ca (Overall)

 

94.188

180.36

115.564±4.527

130.26

   

Mg (Warm)

mg/L

54.675

91.125

71.795±10.444

90.85

100 (Iran)

0.5

3.88

Mg (Cool)

30.375

100.845

67.345±23.568

101.92

Mg (Overall)

 

30.375

100.845

70.065±3.838

91.125

   

SAR (Warm)

-

2.677

5.156

3.405±0.830

4.7

9 (FAO)

1

7.76

SAR (Cool)

2.897

5.087

3.63±0.840

5.3

SAR (Overall)

 

2.677

5.156

3.493±0.192

5.087

   

Mn (Warm)

mg/L

0.0062

0.042

0.02±0.011

0.041

1 (Iran)

1

7.76

Mn (Cool)

0.0025

0.044

0.023±0.016

0.045

Mn (Overall)

 

0.0025

0.044

0.021±0.003

0.042

   

Fe (Warm)

mg/L

0.01

0.343

0.057±0.096

0.34

3 (Iran)

0.5

3.88

Fe (Cool)

0.0207

0.288

0.116±0.103

0.3

Fe (Overall)

 

0.01

0.343

0.08±0.023

0.288

   

Hg (Warm)

mg/L

0.0003

0.0035

0.00084±0.00091

0.003

0.01 (EPA)

1

7.76

Hg (Cool)

0.0003

0.001

0.00075±0.00022

0.00104

Hg (Overall)

 

0.00026

0.0035

0.00081±0.00016

0.00098

   

As (Warm)

mg/L

0.0006

0.0034

0.0021±0.0009

0.00342

0.1 (Iran)

1

7.76

As (Cool)

0.0007

0.0021

0.0013±0.00041

0.0022

As (Overall)

 

0.0006

0.0034

0.0018±0.00020

0.00325

   

Cd (Warm)

mg/L

0

0.003

0.00041±0.00091

0.00301

0.05 (Iran)

1

7.76

Cd (Cool)

0

0.0038

0.00076±0.00134

0.0046

Cd (Overall)

 

0

0.0038

0.00055±0.00026

0.00381

   

DO (Warm)

mg/L

2.87

7.4

5.766±1.318

7.3

2 (Iran)

0.5

3.88

DO (Cool)

5.098

6.21

5.541143±0.401

6.3

DO (Overall)

 

2.87

7.4

5.678±0.246

6.81

   

COD (Warm)

mg/L

14

203

103.82±63.653

200

200 (Iran)

0.1

0.78

COD (Cool)

32

200

104.71±58.131

210

COD (Overall)

 

14

203

104.17±14.095

200

   

BOD5 (Warm)

mg/L

8.1

107

52.518±32.198

104

100 (Iran)

0.1

0.78

BOD5 (Cool)

16.8

88

49.429±27.869

88.5

BOD5 (Overall)

 

8.1

107

51.317±7.017

89.5

   

NO3-N(Warm)

mg/L

3.79

46

24.067±13.444*

41*

5 (WHO)

0.1

0.78

NO3-N(Cool)

11.015

149.9

57.712±50.442*

165*

NO3-N(Overall)

 

3.79

 

149.9

37.151±8.463*

91.58*

   

TC (Warm)

N/100ml

20

2320

1014.82±1139.364*

2313*

1000 (Iran)

0.5

3.88

 

TC (Cool)

24

2615

1725.28±1152.32*

2618*

 

TC (Overall)

20

2615

1291.11±1165.88*

2437*

 

FC (Warm)

N/100ml

15

1985

864.45±1071.53*

1980*

400 (Iran)

0.5

3.88

 

FC (Cool)

6

1220

377.86±893.088*

1226*

 

FC (Overall)

6

1985

675.22±1008.21*

2341*

 

Helmith egg (Warm)

N/L

49

210

126.75±75.769*

208*

1 (Iran)

0.5

3.88

 

Helmith egg (Cool)

20

164

66.35*±65

168*

 

Helmith egg (Overall)

20

210

73.61*±96.125

215*

 

* Values which did not meet standards.

Moreover, in order to get a closer CWQI to the actual quality of SWTP effluent, the authors decided to give weight to each parameter based on its importance in the agricultural irrigation. Thus, as Table 2 shows, each parameter has its specific multiplier and contribution value to calculation of CWQI.

Results

After analyzing the samples collected from warm and cold seasons, the results shown in Table 2 were obtained. Besides, the meanvariations of the analyzed parameters are depicted in Figure 1.
Figure 1

Mean variations of the measured parameters in SWWPTE.

As noted above, to determine the quality of the SWTPE, the CWQI was used. Therefore, the CWQI was calculated in the warm, cold, and overall seasons for the physiochemical parameters. In addition, F1, F2, and F3 were separately calculated and the results are depicted in Figure 2.
Figure 2

The value of calculated CWQI, F 1 , F 2 , and F 3 for physicochemical parameters.

Analysis of SWTPE shows that in the cold seasons, 4 physicochemical parameters (EC, Res. Cl, TSS, TDS, Mg, and NO3) failed from the defined objectives (Scope) and among these; two parameters (EC and NO3) had the highest failure to meet the objectives (Frequency). Also,NO3 had the most deviation from the desired objective (Amplitude). In the warm seasons, NO3, BOD5, COD,HCO3,TDS, TSS, and EC departed from their objectives and EC and TDS had the most frequency of failure. Besides, similar to the cold seasons, NO3 had the most deviation from its objective in warm seasons, as well.

In all the cold and warm seasons, 9 parameters (EC, Res. Cl, TSS, TDS, Mg, NO3, BOD, COD, and HCO3) failed to meet their objectives over the sampling period. Among these parameters, similar to warm and cold seasons, the electrical conductivity had the most frequency of failure and NO3 had the most deviation from its objectives. Also, CWQI was calculated by applying the microbial parameters along with the physicochemical parameters (Figure 3). In this situation, the helminthes egg, instead of NO3, had the most deviation from its objective and fecal coliform as well as total coliform had failures to meet their objectives in warm, cold, and all the seasons together.
Figure 3

The value of calculated CWQI, F 1 , F 2 , and F 3 for physicochemical and microbial parameters.

Discussion

There are two components for evaluating the quality of water resources: 1) measurement of water quality variables and 2) comparison of values to benchmarks, such as guidelines or objectives. However, assessment of the quality variable by variable and objective by objective is quite a difficult task [23]. Therefore, a method which combines all the variables and represents a final value as the quality index could be used as a management tool for decision makers [27, 28]. The CWQI is a science-based communication tool which tests multivariable water quality data versus water quality objectives specified by the users [23]. This tool also simplifies the reporting of water quality data to both technical and non-technical individuals [26]. Thus, due to the advantages of CWQI, in order to assess SWTP effluent quality for agricultural irrigation, this was used in the present study. According to Figure 2 and Table 1, physicochemical quality of SWTPE in warm and cold seasons is in the good range and, consequently, the physicochemical quality of the SWTPE rarely falls from the desired quality. According to the obtained results and Table 2, it can be concluded that TDS, EC, and NO3 have the largest contribution to the decline of CWQI in cold, warm, and all the seasons together. EC and TDS are the most important parameters related to the water resources salinity [29]. Some studies have shown that using wastewater for irrigation can increase soil salinity [6, 8, 11]. In the current study, mean and 90% cumulative probability of EC and TDS, which were the main factors of decrease in CWQI, were exceeded from the standards; therefore, this effluent could increase the irrigated soil salinity in future. In general, when the total soluble salt reaches an excessive concentration in the irrigated soil, water uptake by plant is reduced due to osmotic effect and this situation leads to a phenomenon called "osmotic desiccation" which can reduce the harvest [12, 29, 30]. On the other hand, increasing salinity reduces organic complex for most metals, which induces the displacement of metal in the solid phase with the soil solution and this can pollute the aquifers [31]. Generally, the salinity of WWTPE is high and the conventional treatments cannot reduce the salinity to the desired values; thus, just the advanced treatments which increase the cost of water reuse are necessary [12]. Overall, there are some options for controlling SWTPE salinity. For instance, in order to prevent soil salinization by SWTPE irrigation, enough drainage and leaching could be applied [30, 32]. Also, if the salinity of the effluent is higher than the cultivated plant tolerance threshold, salinity could be reduced to the desired level by mixing the effluent with fresh water [13]. In the present study, the mean and 90% cumulative probability of nitrogen in warm, cold, and all the seasons together were far from the WHO standard (5mg/l). Some studies have shown that using untreated wastewater can increase soil nitrogen [10]. Although using wastewater treatment plants effluent for irrigation can be as significant source of valuable nutrients like nitrogen [14], it should be considered that large quantities of nitrogen in the effluent could be unfavorable for plant growth [11]. On the other hand, nitrate is highly soluble and by leaching phenomena, the nitrate concentration could increase in groundwater and consuming this water by the infants could lead to methemoglobinemia [33]. Hence, it seems that advanced treatments are necessary in order to reduce the SWTPE nitrate to the guidelines value. As can be seen in Figure 3, when microbial parameters were applied for calculating CWQI, the value of this index fell dramatically (from 85 to 64 in all the seasons together) and, thus, the quality of the effluent was located in marginal situation. Figure 3 also shows that the quality of SWTPE in the cold seasons was better than warm seasons, which could be due to the lower levels of microbial indicators in the cold seasons. In fact, the mean of fecal coliform and helminthes egg in cold seasons were respectively 486 and 61 units less than the warm seasons. Just the mean of total coliform in cold seasons was greater than the warm seasons, which might result from more precipitation in the cold period, washing the pathways, and progression of the washed coliforms in to the SWTP. Many studies have shown that the microbial pollution in the recycled effluent could contaminate the soil as well as the crops and develop the risk of disease in both consumers and the farm workers. AL-Laham et al. showed that irrigating tomato by an effluent with high microbial index can cause contamination on fruit scar [7]. In another study, Forslund et al. showed that using effluents for irrigation of potatoes could increase the risk of gastroenteritis diseases for farm workers [34]. Palese et al. also conducted a study and concluded that the reuse of wastewater for irrigation could increase the soil microbial load, although after a day, the contamination of the soil had greatly reduced [2]. In separate studies, Habbari et al. and Ensink et al. showed that the prevalence of parasitic infections was quite high among the populations exposed to the areas irrigated with recycled wastewater [19, 20]. Therefore, considering the high levels of microbial indicators (Fecal coliform, Total coliform, and Helminthes egg) in SWTPE, it seems that using this water resource for irrigation could cause health problems for both the crops consumers and the farm workers and in order to reduce the microbial load in this wastewater treatment plant, some additional treatment, such as sand filtering followed by UV disinfection, is recommended. Bakopoulou et al. evaluated four wastewater treatment effluents for agricultural irrigation and showed that the wastewater treatment plant which used the advance treatment (sand filtering and UV disinfection) not only had a better microbial situation, but its physicochemical parameters were also in a better status compared to the other WWTPs [35]. Furthermore, applying management measures can control the health risk to some extent; for example, subsurface irrigation can be used in order to reduce the exposure of workers and crops to the recycled water. Stopping the irrigation few days before harvesting the crops [2, 36], planting the crops in depths of the soil, putting nets under the trees in order to prevent the crops from falling on the ground and contamination of the product [2], and cooking the harvested crops before consumption [7], are other management practices which can bring down the risk of recycled wastewater for irrigation. As Table 2 depicts, mean and 90% cumulative probability of BOD5, TSS, HCO3, Cl, SO4, Ca, Mg, SAR, DO, Mn, Hg, Fe, As, and Cd completely fulfilled the standards, which shows the desirable efficiency of the treatment of the physicochemical parameters in SWTPE which is confirmed by the obtained CWQI values (Figure 2). Therefore, it seems that if the problems related to the microbial load in SWTPE be resolved, even with the current situation of the physicochemical parameters which could not meet the objectives (NO3, TDS, and EC), the final quality of SWTPE for agricultural irrigation will be favorable.

Conclusion

The present study evaluated the SWTPE quality for agricultural irrigation by measuring the physicochemical and microbial parameters and then calculating the CWQI. The results showed that the effluent physicochemical quality was appropriate for irrigation; however, considering the microbial parameters, the quality of the effluent reduced dramatically which shows that the pathogens in this effluent can be a threat to the public health. Therefore, in order to protect the health of the consumers and the farm workers, advanced treatments, such as sand filtration and UV disinfection, are recommended.

Declarations

Acknowledgments

The information contained in this article was extracted from a master’s thesis by the author, Babak Djahed. Research Improvement Center of Shiraz University of Medical Sciences, Shiraz, Iran and Ms. A. Keivanshekouh are appreciated for their helping.

Authors’ Affiliations

(1)
Department of Environmental Health Engineering, School of Health and Nutrition, Shiraz University of Medical Sciences
(2)
Department of Environmental Health Engineering, School of Public Health and Institute of Public Health Research, Tehran University of Medical Sciences
(3)
Department of Environmental Health Engineering, School of Health and Nutrition, Shiraz University of Medical Sciences

References

  1. Qadir M, Bahri A, Sato T, Al-Karadsheh E: Wastewater production, treatment, and irrigation in Middle East and North Africa. Irrigation and Drainage Systems. 2009, 24: 37-51.View ArticleGoogle Scholar
  2. Palese A, Pasquale V, Celano G, Figliuolo G, Masi S, Xiloyannis C: Irrigation of olive groves in Southern Italy with treated municipal wastewater: Effects on microbiological quality of soil and fruits. Agric Ecosyst Environ. 2009, 129: 43-51. 10.1016/j.agee.2008.07.003.View ArticleGoogle Scholar
  3. Alfarra A, Kemp-Benedict E, Hötzl H, Sader N, Sonneveld B: A Framework for Wastewater Reuse in Jordan: Utilizing a Modified Wastewater Reuse Index. Water Resources Management. 2011, 25: 1153-1167. 10.1007/s11269-010-9768-8.View ArticleGoogle Scholar
  4. Asano T, Burton FL, Leverenz HL, Tsuchihashi R, Tchobanoglous G: water reuse: Issues, Technologies, and Applications. 2006, New York: McGraw-Hill, 1Google Scholar
  5. Mohammadi P: A review on standards and experiences of using wastewaters effluents for irrigation 1edn. 2008, Tehran: Iranian national committee on irrigation and drainage, [in Persian]Google Scholar
  6. Heidarpour M, Mostafazadehfard B, Abedikoupai J, Malekian R: The effects of treated wastewater on soil chemical properties using subsurface and surface irrigation methods. Agricultural Water Management. 2007, 90: 87-94. 10.1016/j.agwat.2007.02.009.View ArticleGoogle Scholar
  7. Al-Lahham O, El Assi NM, Fayyad M: Impact of treated wastewater irrigation on quality attributes and contamination of tomato fruit. Agricultural Water Management. 2003, 61: 51-62. 10.1016/S0378-3774(02)00173-7.View ArticleGoogle Scholar
  8. Kalavrouziotis IK, Robolas P, Koukoulakis PH, Papadopoulos AH: Effects of municipal reclaimed wastewater on the macro- and micro-elements status of soil and of Brassica oleracea var. Italica, and B. oleracea var. Gemmifera. Agricultural Water Management. 2008, 95: 419-426. 10.1016/j.agwat.2007.11.004.View ArticleGoogle Scholar
  9. Pedrero F, Alarcón JJ: Effects of treated wastewater irrigation on lemon trees. Desalination. 2009, 246: 631-639. 10.1016/j.desal.2008.07.017.View ArticleGoogle Scholar
  10. Adrover M, Farrús E, Moyà G, Vadell J: Chemical properties and biological activity in soils of Mallorca following twenty years of treated wastewater irrigation. J Environ Manage. 2012, 95: S188-S192.View ArticleGoogle Scholar
  11. Xu J, Wu L, Chang AC, Zhang Y: Impact of long-term reclaimed wastewater irrigation on agricultural soils: A preliminary assessment. J Hazard Mater. 2010, 183: 780-786. 10.1016/j.jhazmat.2010.07.094.View ArticleGoogle Scholar
  12. Candela L, Fabregat S, Josa A, Suriol J, Vigues N, Mas J: Assessment of soil and groundwater impacts by treated urban wastewater reuse. A case study: Application in a golf course (Girona, Spain). Sci Total Environ. 2007, 374: 26-35. 10.1016/j.scitotenv.2006.12.028.View ArticleGoogle Scholar
  13. Pedrero F, Kalavrouziotis I, Alarcón JJ, Koukoulakis P, Asano T: Use of treated municipal wastewater in irrigated agriculture—Review of some practices in Spain and Greece. Agricultural Water Management. 2010, 97: 1233-1241. 10.1016/j.agwat.2010.03.003.View ArticleGoogle Scholar
  14. Hamoda M: Water strategies and potentional of water reuse in south Mediterranean countries. Desalination. 2004, 165: 31-41.View ArticleGoogle Scholar
  15. Surdyk N, Cary L, Blagojevic S, Jovanovic Z, Stikic R, Vucelic-Radovic B, Zarkovic B, Sandei L, Pettenati M, Kloppmann W: Impact of irrigation with treated low quality water on the heavy metal contents of a soil-crop system in Serbia. Agricultural Water Management. 2010, 98: 451-457. 10.1016/j.agwat.2010.10.009.View ArticleGoogle Scholar
  16. Wang J, Wang G, Wanyan H: Treated wastewater irrigation effect on soil, crop and environment: Wastewater recycling in the loess area of China. J Environ Sci. 2007, 19: 1093-1099. 10.1016/S1001-0742(07)60178-8.View ArticleGoogle Scholar
  17. Reboll V, Cerezo M, Roig A, Flors V: Influence of wastewater vs groundwater on young Citrus trees. J Sci Food Agric. 2000, 80: 1441-1446. 10.1002/1097-0010(200008)80:10<1441::AID-JSFA664>3.0.CO;2-S.View ArticleGoogle Scholar
  18. Klay S, Charef A, Ayed L, Houman B, Rezgui F: Effect of irrigation with treated wastewater on geochemical properties (saltiness, C, N and heavy metals) of isohumic soils (Zaouit Sousse perimeter, Oriental Tunisia). Desalination. 2010, 253: 180-187. 10.1016/j.desal.2009.10.019.View ArticleGoogle Scholar
  19. Ensink JHJ, Hoek W, Mukhtar M, Tahir Z, Amerasinghe FP: High risk of hookworm infection among wastewater farmers in Pakistan. Trans R Soc Trop Med Hyg. 2005, 99: 809-818. 10.1016/j.trstmh.2005.01.005.View ArticleGoogle Scholar
  20. Habbari K, Tifnouti A, Bitton G, Mandil A: Geohelminthic infections associated with raw wastewater reuse for agricultural purposes in Beni-Mellal, Morocco. Parasitol Int. 2000, 48: 249-254. 10.1016/S1383-5769(99)00026-4.View ArticleGoogle Scholar
  21. Ehsani M: A Vision on Water Resources Situation, Irrigation and Agricultural Production in Iran. ICID 21st European Regional Conference. Frankfurt (Oder) and Slubice - Germany and Poland. 2005Google Scholar
  22. Edalatgostar MD, Farzadian A, Amiri N: Presentation of a stochastic model for the drought prediction in shiraz city. The national conference on water crisis management Islamic Azad University, Marvdasht branch. 2009Google Scholar
  23. Sd R, Duro DC: Dubé M: Comparative analysis of regional water quality in Canada using the Water Quality Index. Environ Monit Assess. 2008, 156: 223-240.Google Scholar
  24. Hurley T, Sadiq R, Mazumder A: Adaptation and evaluation of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for use as an effective tool to characterize drinking source water quality. Water Res. 2012, 46: 3544-3552. 10.1016/j.watres.2012.03.061.View ArticleGoogle Scholar
  25. Lumb A, Halliwell D, Sharma T: Application of CCME Water Quality Index to Monitor Water Quality: A Case Study of the Mackenzie River Basin, Canada. Environ Monit Assess. 2006, 113: 411-429. 10.1007/s10661-005-9092-6.View ArticleGoogle Scholar
  26. Khan AA, Paterson R, Khan H: Modification and Application of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for the Communication of Drinking Water Quality Data in Newfoundland and Labrador. Water Qual Res J Canada. 2004, 39: 289-293.Google Scholar
  27. Said A, Stevens DK, Sehlke G: An Innovative Index for Evaluating Water Quality in Streams. Environ Manage. 2004, 34: 406-414. 10.1007/s00267-004-0210-y.View ArticleGoogle Scholar
  28. Avvannavar SM, Shrihari S: Evaluation of water quality index for drinking purposes for river Netravathi, Mangalore, South India. Environ Monit Assess. 2007, 143: 279-290.View ArticleGoogle Scholar
  29. Duncan RR, Carrow RN, Huck MT: Turfgrass and Landscape Irrigation Water Quality "Assessment and Management". 2009, New York: CRC PressGoogle Scholar
  30. Qadir M, Oster JD: Crop and irrigation management strategies for saline-sodic soils and waters aimed at environmentally sustainable agriculture. Sci Total Environ. 2004, 323: 1-19. 10.1016/j.scitotenv.2003.10.012.View ArticleGoogle Scholar
  31. Tarchouna LG, Merdy P, Raynaud M, Pfeifer H-R, Lucas Y: Effects of long-term irrigation with treated wastewater. Part I: Evolution of soil physico-chemical properties. Appl Geochem. 2010, 25: 1703-1710. 10.1016/j.apgeochem.2010.08.018.View ArticleGoogle Scholar
  32. Oster JD: Irrigation with poor quality water. Agricultural Water Management. 1994, 25: 271-297. 10.1016/0378-3774(94)90064-7.View ArticleGoogle Scholar
  33. WHO: Guidelines for the safe use of wastewater, excreta and Greywater. Volume 2, wastewater use in agriculture. 2006, Geneva, Switzerland: World Health OrganizationGoogle Scholar
  34. Forslund A, Ensink JHJ, Battilani A, Kljujev I, Gola S, Raicevic V, Jovanovic Z, Stikic R, Sandei L, Fletcher T: Faecal contamination and hygiene aspect associated with the use of treated wastewater and canal water for irrigation of potatoes (Solanum tuberosum). Agricultural Water Management. 2010, 98: 440-450. 10.1016/j.agwat.2010.10.007.View ArticleGoogle Scholar
  35. Bakopoulou S, Emmanouil C, Kungolos A: Assessment of wastewater effluent quality in Thessaly region, Greece, for determining its irrigation reuse potential. Ecotoxicol Environ Saf. 2011, 74: 188-194. 10.1016/j.ecoenv.2010.06.022.View ArticleGoogle Scholar
  36. Blumenthal UJ, Peasey A, Ruiz-Palacios G: Guidelines for wastewater reuse in agriculture and aquaculture: recommended revisions based on new research evidence. 2000, London: WELL StudyGoogle Scholar

Copyright

© Baghapour et al.; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement