Statistical analysis for water quality index for Shatt-Al-Hilla river in Babel city

Water is one of the most indispensable resources; hence life is not possible on this planet without water (Abdulla et al. 2020; Salah et al. 2020a). Water quality is defined in terms of its physical, chemical and biological parameters, and evaluating these parameters is important before use for any intended purposes, such as potable, agricultural, recreational and industrial water usage, and so on (Alobaidy et al. 2010). Drinking water in Iraq is secured from rivers, lakes, wells and springs, which are usually exposed to various pollutants that result from the diffusion from non-point and point sources (Hashim et al. 2021a; Omran et al. 2021), which are difficult to control, monitor, and evaluate, such as sewage (Hashim et al. 2020a; Zanki et al. 2020), agricultural and industrial effluents (Emamjomeh et al. 2020a, 2020b). In addition, global warming plays a serious role in the freshwater shortage in Iraq (Zubaidi et al. 2020a; Zubaidi Salah et al. 2020), where the last studies revealed a significant shortage in precipitations (Salah et al. 2020b, 2020c). Furthermore, the rapid increase in urbanization (Al-Jumeily et al. 2019; Alnaimi et al. 2020; Farhan et al. 2021) and industrial activities, such as petroleum and cement industries (Grmasha et al. 2020; Al-Sareji et al. 2021; Obaid et al. 2021) near the sources of freshwater in Iraq, have intensified the problem.

Therefore, the need for water treatment technologies and water monitoring policies becomes more urgent than any time before (Al-Hashimi et al. 2021; Hashim et al. 2021b). In this context, many methods were used to remediate water from a certain pollutant of a set of pollutants, such as filtration (Abdulraheem et al. 2020; Alhendal et al. 2020; Alyafei et al. 2020), electrocoagulation (Aqeel et al. 2020; Hashim et al. 2020b), ultrasonic-based methods (Al-Marri et al. 2020), and adsorbents (Alenazi et al. 2020a, 2020b). For example, Hashim et al. (2020c) used a combined treatment method that utilises both electrocoagulation and ultrasonic techniques to remediate water from biological pollutants, and the results obtained proved this combined method can remove all pathogens within 15 minutes at relatively cost. Additionally, Abdulhadi et al. (2021) used the electrocoagulation method to remove complex pollutants from water, and the results indicated this method removed 99% of iron and organic pollutants from water. Additionally, forcasting methods were used to predict the possible changes in the abundancy of freshwater, such as those studies of Zubaidi et al. (2020b) and Al-Saati et al. (2021).

Other studies focused on the evaluation of water quality. One of the most effective ways to communicate information on water quality trends is using suitable indices (Al-Mansori 2017).

The current study aims at evaluating the water quality of Shatt-al-Hilla River in Babel city, Iraq, which is the only source of freshwater in Babylon governorate, which is home for about 2 million people. In this research, the water quality index was calculated for raw and treated water at three sites, namely New Hilla (NH), Al-Hussein (HU), and Al- Hashimyah (HA). The study was conducted from October 2020 to June 2021. The analysis was conducted using a mathematical method and the Canadian method, and the results were analyzed statistically using the SPSS software.

Shatt Al-Hilla is one of Iraq's famous rivers in Hilla city as well as its largest source of water, which extends to 101 km². The main source of the river is the Euphrates River, where the river comes from the north boundary of the province of Babylon until it reaches Al-Diwaniya province. Euphrates River is one of Iraq's main irrigation systems, particularly in its mid location. After passing the Al-Hindiya barrage, Shatt Al-Hilla flows out of the river of Euphrates (Salman et al. 2013). Shatt Al-Hilla is used for drinking and agriculture. It is considered a significant attraction, but has been exposed to negligence in recent years. Salinity slowly rising along the river was exacerbating the situation (Saod et al. 2019). The study area included three stations along the Hilla River, which extended from the city of Hilla to the town of Al-Hashimyah within the governorate of Babylon. These plants represent water treatment New Hilla (NH), Al-Hussein(HU), and Al- Hashimyah(HA). Latitude and longitude for each station are listed in Table 1. Geographical location of the study area is shown in Figure 1.

Water samples were collected from Shatt Al-Hilla river within Hilla City for (raw and treated) water for three different stations (New Hilla, Al-Hussein and Al-Hashimyah) to study the physical and chemical parameters and compare them with the Iraqi standard specifications Table 2. The water quality index was determined by using two models, which were the Weighted Arithmetic and Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). Water samples were collected monthly from (October 2020 to June 2021), where twelve parameters of raw and treated water were examined, included temperature (Temp), Total hardness (TH), electrical conductivity (EC), acidity (PH), total dissolved solids (TDS), sulfate (So₄⁻²), calcium (Ca⁺²), Magnesium (Mg⁺²), Sodium (Na⁺¹), Biological demand for oxygen (BOD), Potassium (K) and turbidity, then calculating the efficiency of the project based on the mathematical method. Then, the results were analyzed graphically using a statistical analysis program (SPSS).

Required chemical parameters were analyzed immediately after sample collection, according to Table 3.

This method transforms vast quantities of quality knowledge of water to a single water level quality number. WQI was used as a guideline for the classification of surface water depending on the use of basic parameters of water characterization (Şener et al. 2017).

To accurately depict water quality, the WQI system ideally contains a wide range of water quality criteria, which requires cost and time to calculate. The WQI approach, considered one of the most powerful ways to convey knowledge about water quality patterns to the common person and quality of water control policymakers, has been commonly used in aquatic environments in recent years (Ponsadailakshmi et al. 2018). The WQI can be used to highlight water pollutants, both inorganic and organic pollutants, for an effective water quality treatment.

F₃: represents the quantity by which failed tested values are not compliant with their objectives (limits), which is calculated as follows:

• (i)
  The excursion calculated from Equation (9) when the test value must not be greater than the objective

  

  (9)

  or from Equation (10), where the test value is not less than the objective

  

  (10)
• (ii)
  The normalized sum of excursions (nse) represents the collective quantity by which single tests that are out of agreement are computed by summing the single-test excursions from their objectives and dividing by the number of the total test (all tests), is computed as:

  

  (11)
• (iii)
  F₃ can be calculated as:

  

  (12)

After the CCME WQI value was calculated, water quality was classified by linking it to the classes listed in Table 5.

It can be noted from Tables 6–11 that all the estimated values of the chemical and physical parameters of the studied water treatment plants are within the Iraqi specifications except for calcium, turbidity, electrical conductivity of raw water, and temperature of treated water.

According to Iraqi water quality standard limits and using the prior equations, the monthly raw and treated WQI was calculated below.

The raw water quality index results for all stations are shown in Table 12. It was found that the quality of raw water for all stations ranged between (53.977) in the HA station in January and (138,586) in the HE station in October. In addition, the mean WQI of the river ranged from (87,246) in the HA station to (109.006) in the HE station. From these WQI values and according to Table 4, the river water was classified as ‘highly polluted’ to ‘unfit for drinking’ for the studied stations during the study period of the year (2020–2021). The poor water quality in the Hilla River is due to the untreated household pollutant disposal site, which was discharged directly through wastewater (Singh 2010). The monthly values (WQI) of raw water are shown in Figure 2, and this figure represents (WQI) of the stations selected during the study period.

Table 13 shows the variation in (WQI) monthly values of treated water for the specified stations during the study period. The treated water quality index (TWQI) ranged between (34.237–58.271), (52.952–76.171) and (31.986–72.142) in NH, HE and HA, respectively. This means that the treated water ranges from ‘Poor' to ‘Marginal' at the NH plant, ‘Marginal' to ‘Fair' at the HE plant, and ‘Poor’ to ‘Fair' at the HA station. The monthly values (WQI) of the treated water are plotted according to Figure 3.

The mean efficiency (E%) was calculated using Equation (5). As shown in Table 14 and Figure 4, the New Hilla treatment plant was efficient compared to the other water treatment plants. The quality of treated water has decreased along the river (from Al-Hussein station to Al-Hashimyah station) due to low raw water quality and low water efficiency (E%).

Table 15 and Figure 5 show a summary of the values of F₁, F₂, F₃, CCME WQI values and water quality assessment for all stations, where the raw water quality value was (81.232), (79.307) and (80.931) for the three stations respectively. This indicates that the water quality can be classified as ‘good' for NH, ‘acceptable' for HE and ‘good' for HA. This is because some standards for raw water samples such as Tur, Ca and EC exceed water quality standards (Rachedi & Amarchi 2015). Human actions also affect water quality, with wastewater pollution and agricultural runoff from lands near the river affecting water quality (Hassan et al. 2018). The results showed that the treated water is of high value, as the value of treated water ranged between 94,620 and 94.718, indicating that the quality of the treated water in the three plants was ‘good’. The higher concentration of criteria may be caused by either local sewage pollution or the high presence because river or rain velocities are very high, and soil filtration is high (Alobaidy et al. 2010; Rachedi & Amarchi 2015; Hassan et al. 2018).

Table 16 summarizes the water quality in each specific station using the weighted calculation method and CCME water quality indicators, and the result from the treated water shows the convergence of the indicators for all stations. Meanwhile, the difference in points is clearly visible in the state of raw water in all stations, so the water quality ranged between ‘highly polluted’ and ‘unsafe for drinking’ by the method of weighted calculation, while it was ‘good’ to ‘fair’ according to Canadian method. The study believed that the difference of scores might be related to the index theory on which the criterion was built and that CCME gave a higher level of water quality that could be considered and thus a more flexible weighted calculation method. Although indicators are used to determine water quality worldwide, no indication has been accepted as universal. This allows researchers, environmental agencies, policymakers, and others to continue exploring and modifying existing ones to obtain a more accurate, transparent, comprehensive and global index.

The following are the results of the descriptive statistics of raw water data for the New Hilla project for the year (2020–2021), which were recorded according to the characteristics of each factor and the value of the general averages, standard deviations and standard error rate for each of them. The truth is described in detail in Tables 17–19:

The following are the results of the descriptive statistics of raw water data for the New Hilla project for the year (2020–2021), which were recorded according to the characteristics of each factor and the value of the general averages, standard deviations and standard error rate for each of them. The truth is described in detail in Tables 20–22.

Finally, the authors of this work recommend using sensing systems to monitor the water quality of freshwater. The possible sensing methods are electromagnetic sensors (Omer et al. 2021; Ryecroft et al. 2021) and microwaves (Omer et al. 2021; Ryecroft et al. 2021). Also, it recommended monitoring the emissions of local industries due to their direct effects on the quality of surface water. For example, there are cement plants in the city of Babylon, and the emissions of this industry are responsible for many pollutions problems (Kadhim et al. 2020; Majdi et al. 2020; Mousazadeh et al. 2021), such as particulates (Shubbar et al. 2020a; Kadhim et al. 2021) and carbon dioxide (Shubbar et al. 2020b).

From this work, the following can be concluded:

• 1.

  The mathematical method shows that the water quality index for the three stations ranged from good water to unfit and unsuitable for drinking.

• 2.

  The results of the water quality index were good water to fair according to the Canadian method.

• 3.

  Most of the water quality index results were good. In the case of the Canadian method, CCME WQI is more flexible than other methods used to calculate quality.

• 4.

  The new Al-Hilla water treatment plant was more efficient than the Al-Hussein and Al-Hashimyah plant.

• 5.

  The low water quality in these stations along the Hilla River can also be noted as a result of the low quality of raw water and the low water efficiency in these stations.

• 6.

  There is a strong correlation between chemical and physical indicators with water quality.

Additionally, the following recommendations are suggested for future studies:

• 1.

  Study the effect of another parameter such as Cl, P, Na, and so on, and study more physical and chemical measures must be tested.

• 2.

  Use other types of international indices to explain more carefully the water quality index and parameters affected.

• 3.

  Extend the study from upstream to downstream at all seasons to include other parameters such as heavy metals and microbial studies in an exhaustive view of the functioning of the river.

• 4.

  Use another statistical analysis method to explain the relationship between parameters and the water quality, such as ANN.

Data cannot be made publicly available; readers should contact the corresponding author for details.