Spatiotemporal Variations and WQI-Based Assessment of the Euphrates River's Water Quality at Three Stations in Najaf, Iraq

Water is a critical resource that is essential for the maintenance of environmental equilibrium, economic development, and life. One of Iraq's major supplies of surface water, which is essential for industrial, agricultural, and residential use, is the Euphrates River. Nonetheless, escalating urban development, agricultural runoff, industrial effluents, and climate-induced pressures have progressively compromised the river's water quality, prompting apprehensions regarding its appropriateness for diverse applications. Water resource administration and environmental preservation depend on the use of physical and chemical indicators to monitor and evaluate water quality. Turbidity, alkalinity, electrical conductivity (EC), total dissolved solids (TDS), sodium, potassium, chloride, sulfate, total hardness, magnesium, calcium, nitrate, dissolved oxygen (DO), and acidity (pH) are some of these factors. Evaluating water quality has emerged as a critical focus in hydrological and environmental studies, particularly in semi-arid areas like Iraq, where rivers face escalating threats from anthropogenic activity. Several studies have evaluated the regional and temporal variability of water quality in the Euphrates River and other rivers in the region, using physicochemical indicators. River water quality is a critical issue that has garnered significant attention in environmental and engineering research, particularly in strategically important rivers such as the Euphrates. The water quality of the Euphrates River and other rivers has been investigated in several studies employing water quality indicators (WQIs) as well as chemical and biological analysis methods. Study [1] investigated the physical, chemical, and microbiological pollution of the Euphrates River waters between Hit and Fallujah, emphasizing the impact of human activities on water quality, particularly organic pollutants and heavy metals. Study [2] analyzed wastewater and its effects on the Euphrates River's water quality, describing the types of chemical and biological contaminants and how they contribute to the river's environmental deterioration. Study [3] utilized Geographic Information Systems (GIS) methodologies and water quality indicators to assess the water quality of the Al-Abbasiya River, highlighting the instruments' capacity to monitor and assess the state of the water with pinpoint accuracy in relation to its location. To make sure the water at Basra city's drinking stations meets all the necessary health criteria, research [4] tested it using chemical and physical factors. To determine the level of pollution and its effect on the aquatic environment, researchers [5, 6] in Iraq used the CCME water quality index and water quality indicators to do a thorough investigation of how phosphorus affected the Euphrates River's water quality. According to the research, phosphorus is a major contaminant that harms river ecosystems. As a bioindicator of environmental change along the Euphrates River in the Ramadi area, algal biodiversity was studied in relation to water quality [7]. In order to enhance the precision of ongoing water monitoring and assessment, a mathematical model was suggested by study [8] to examine the Euphrates River's water quality using field data collected from Diwaniyah. Internationally, a number of recent studies have shown how well the water quality index (WQI) evaluates river systems across various conditions and regions. As an example, research [9] used Geographic Information Systems (GIS) and WQI to compare the evaluation of temporal and spatial variations in surface water quality. They emphasized the significance of combining geospatial technologies with water indicators to track seasonal and local changes. In the same way, research [10] used the integrated water quality index (IWQI) in conjunction with GIS and multivariate statistical analysis (MSA) to identify pollution sources and geographical patterns of deteriorating water quality in Morocco's Oued El Oued basin. Researcher [11] evaluated the Nam River in Korea using the WQI in conjunction with many statistical techniques, demonstrating the index's capacity to streamline enormous datasets and identify important variables affecting water quality. These international studies demonstrate the WQI's significance on the globe and its adaptability to various hydrological regimes. Nevertheless, there is still a dearth of thorough research on the Euphrates River, especially that which incorporates chemical multiplicity and spatial and temporal comparisons with WQI classification, despite the large number of worldwide studies. This shortcoming draws attention to the necessity and originality of the current study, which offers a thorough evaluation of the water quality at three important locations in Al-Najaf Governorate (Kufa, Al-Abbasiya, and Al-Manathera) throughout a two-year period (2023–2024). Chemical and physical parameters allow for a more thorough and accurate evaluation of water quality than prior local studies that frequently relied on a limited range of parameters or shorter monitoring periods. Furthermore, new evidence of the slow decline in central Iraq's water quality is provided by the comparison of WQI values across stations and years, which is crucial for sustainable water resource planning and environmental management.

Over a two-year period (2023-2024), the water quality of the Euphrates River was quantitatively measured at three locations: Kufa, Al-Abbasiya, and Al-Manathera. In order to evaluate 14 critical physical and chemical parameters, including pH, turbidity, alkalinity, electrical conductivity (EC), total dissolved solids (TDS), chloride (Cl), sulphate (SO₄), sodium (Na), potassium (K), total hardness (TH), magnesium (Mg), calcium (Ca), nitrate (NO₃), and dissolved oxygen (DO), Over the course of two years (2023–2024), field monitoring was carried out twice a month (about every two weeks), yielding a total of 24 samples per station annually. Grab sampling was used to collect surface water samples at a depth of 20–30 cm in order to ensure the representativeness of the main stream water properties. Samples were taken at the center of the river, away from banks and places with slow flow or dense growth, in order to reduce spatial variance. Samples were put in sterile 1-liter plastic bottles as soon as they were collected. During transportation to the lab, samples for chemical analysis were kept in refrigerated cartons at 4℃. In order to prevent any changes in chemical composition before analysis, a few drops of nitric acid (HNO₃) were added to the samples for ion analysis (such as NO₃⁻ and SO₄²⁻) to stabilize them and bring their pH down to less than 2. To guarantee accuracy, all assays were completed within 48 hours after sample collection. Using Hanna Instruments equipment, the samples were analyzed using the following standard procedures in compliance with APHA's 2017 Standard Methods for the Examination of Water and Wastewater, which measure electrical conductivity (EC), pH, and total dissolved solids (TDS) using an EC/TDS/pH/T meter (Hanna Instruments). Turbidity is measured with a Hanna Instruments turbidimeter. Oxygen dissolved (DO) was measured using a Hanna Instruments DO meter. Using the spectroscopic methods and common chemical calibrations described in APHA, other elements such as nitrates (NO₃⁻), sulfates (SO₄²⁻), and chlorides (Cl⁻) were investigated. To ensure the accuracy of the results, several measurements were made, and the instruments were calibrated using the manufacturer's standard solutions before use.

The methodology for sampling from the watercourse is depicted in Figure 2. Before being compiled and organized in Microsoft Excel, this data underwent a series of procedures. The subsequent statistical methodologies were implemented: • The mean, standard deviation, minimum, and maximum values of each parameter for each station were included in the descriptive statistics. • Temporal analysis: Monthly and seasonal patterns were analyzed to discover changes over a two-year period. • Spatial comparison of stations.

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Figure 2. Sampling from the river

3.1 Evaluation in relation to standards

To evaluate the water quality for drinking and household use, each measured parameter was compared to the World Health Organization (WHO) [13]. Considerable temporal fluctuations were found when water quality data for 2023 and 2024 were analyzed at the Kufa station. From 7.12 in 2023 to 7.72 in 2024, pH readings rose, suggesting a move toward more alkaline circumstances. Dissolved oxygen (DO) decreased somewhat, which could be a result of variations in the water's organic content or temperature. A relative increase in water quality or a decrease in the pollutant load is shown by the lower average values of the majority of main ions and indicators of salinity and hardness, including calcium, magnesium, sodium, chloride, sulfate, total dissolved solids (TDS), and electrical conductivity (EC), in 2024. On the other hand, turbidity dramatically rose, which might be explained by more suspended particles or seasonal runoff. As demonstrated in Table 1, the minimum and maximum values over the course of the two years exhibit a great deal of variability, particularly in parameters like sodium, TDS, and turbidity, indicating the dynamic character of the station's water quality.

Table 1. The data of Kufa Station

Table 2. The data of Al-Abbasiya Station

Table 3. The data of Al-Manathera Station

Similar patterns to Kufa were shown by the 2023 and 2024 water quality analyses at Al-Abbasiya station. A propensity toward alkalinity was indicated by the small increase in pH that was noted. A little decrease in dissolved oxygen levels may have been brought about by warmer temperatures or more biological activity. In comparison to 2023, parameters including EC, TDS, calcium, and salt displayed lower averages in 2024, which may indicate a dilution effect or less pollution. As shown in Table 2, turbidity rose in the meantime, indicating a higher concentration of suspended particles in the latter part of the year. Significant variability was found in the range between the lowest and greatest readings in both years, especially in turbidity, salt, and sulfate, indicating cyclical variations in the station's water quality.

Consistent patterns with the other two stations were found in the investigation of Al-Manathera station. Between 2023 and 2024, the dissolved oxygen levels decreased, and the pH values gradually rose. Calcium, sodium, chloride, and EC were among the ions with decreased average concentrations in 2024, which may indicate less seasonal volatility or anthropogenic impact. Nevertheless, there was an increase in turbidity levels, which may suggest an increase in surface discharge or an agricultural effect. Table 3 illustrates the significance of consistent evaluations to document changes in water quality over time, as a number of indicators exhibited variability over the two-year period. The standard deviation quantifies variations in values in relation to the arithmetic mean. This metric shows how stable or unstable the water quality has been throughout the years. The results show that in 2023, the components tested at the Kufa station had standard deviations ranging from 0.21 for pH (relative stability in acidity) to 116.80 for electrical conductivity (EC). Seasonal changes and human-caused variables, such as farming and industry, cause dissolved salt and mineral concentrations to fluctuate significantly, as this indicates. Both of those stations are covered by this as well.

3.2 Water quality index (WQI) calculation

A popular technique for evaluating the quality of water is to compute the water quality index (WQI), which aggregates several physical and chemical components into a single numerical value that reflects the general state of the water. This is accomplished by multiplying each element's relative value (Q_i) by the relative weight (W_i) of each factor. Standard (such as WHO or Iraqi requirements) and the relationship described below are used to determine the weights. Several earlier studies have employed this methodology, including a study [14], which demonstrated that turbidity and dissolved oxygen were the primary determinants of the WQI value and hence important markers of declining water quality.

All of the stations had their water quality index (WQI) calculated using a weighted calculation method according to the WHO-recommended standard values. Water is categorized as acceptable for human consumption or unsuitable based on its purity, which is summarized in this index. Table 4 shows how we used a classification scheme developed by study [2] to better understand the water quality at the sites that were studied.

Table 4. Water quality classification based on WQI

The Weighted Arithmetic Index Method was used to determine the water quality index (WQI) using the formula below, Eq. (1):

$W Q I=\frac{\sum_{i=1}^n W_i Q_i}{\sum_{i=1}^n W_i}$                             (1)

pH, DO, NO₃, Ca, Mg, TH, Na, SO₄, Cl, TDS, EC, Alk., and Turbidity were among the chosen parameters. W_i (weights) were determined as shown in Eq. (2). Using WHO (2022) guidelines, the relative significance of each parameter to public health and water consumption was determined. The following equation was used:

$W_i=\frac{K}{s_i}$                             (2)

where,

S_i = standard acceptable limits.

K = a constant that ensures the weights add up to 1.

Since a parameter has a stronger influence on health and water quality, its weight increases with a lower standard limit (for example, nitrate, turbidity, or dissolved oxygen).

Q_i was determined by applying the relationship in Eq. (3):

$Q_i=\frac{\left(V_i-V_{\text {ideal }}\right)}{\left(S_i-V_{\text {ideal }}\right)}$                             (3)

S_i is the standard limit (WHO or Iraqi standards), V_i is the measured value, and V_ideal is the ideal value (7 for pH, 0 for other parameters). The standard value for dissolved oxygen in water is 5, and the ideal value is 14.6 [15, 16]. Because it is the most often used model in both regional and international research, the Weighted Arithmetic Index was utilized.

in order to identify the factors that had the greatest influence on the water quality index value, the following formulas, Eqs. (4) and (5) were used to calculate the contribution percentage of each element:

$contribution_i=Q_i \times W_i$                             (4)

$percentage_i=\frac{\text { contribution }_i}{\sum Q_i \times W_i} \times 100$                             (5)

In this case, Wᵢ is the element's relative weight, and Qᵢ is its quality value. The components that most contribute to the deterioration of water quality can be found using this method.

Field investigations revealed significant turbidity and sulfate (SO₄²⁻) levels at all locations in both years, exceeding the WHO. Meanwhile, total dissolved solids (TDS) and electrical conductivity (EC) surpassed allowed limits in 2023 before reverting to normal levels in 2024. All three locations reported high dissolved oxygen (DO) concentrations of over 5 mg/L, with only minor variations between the two years.

• When comparing stations on a geographical basis in 2023, Al-Manathera had the greatest values for the predominance of other elements, whereas pH and DO were best shown by Al-Abbasiya. The leading spot in 2024 was held by Al-Manathera.
• Throughout 2024, dissolved oxygen (DO) levels fell somewhat, with the lowest readings reported in Kufa. The presence of more organic chemicals or higher temperatures, both of which might affect aquatic life, could be the cause of this decline.
• The water quality at Kufa and Al-Abbasiya stations significantly declined from a "good" rating in 2023 to a "poor" rating in 2024, according to the results, which demonstrated the growing influence of both natural and human factors during the study period.
• AL-Manathera station, which is situated at an estuary and receives accumulated pollutants from upstream stations like Kufa and Abbasiya, maintained its classification as "poor" in both years, but its water quality index values increased noticeably, indicating the buildup of pollutants and the growing severity of the deterioration in this area.
• This indicates that turbidity is a critical criterion for categorizing water quality, as per the used index, due to its high sensitivity to water transparency and environmental conditions. Along with DO, pH, and K, the remaining components have little influence.
• The variation in standard deviation values across components illustrates how vulnerable the water is to climatic and environmental changes, as well as human activities. In order to preserve stable water quality and avoid any contamination, it shows the necessity of putting management mechanisms into place that continuously monitor and control pollution sources.