Assessing surface water quality in Fayoum, Egypt using an integrated WQI-GIS approach for multi-purpose reuse

Water quality management remains a critical challenge in arid and semi-arid regions, where limited freshwater resources are increasingly stressed by anthropogenic activities and natural constraints. This study provides a summer 2024 assessment of surface water quality in Egypt’s Fayoum Governorate, emphasizing spatial variability, dominant pollution drivers, and sectoral suitability. Ten sites across agricultural drains and wastewater discharge points were analyzed for 17 physicochemical parameters. The Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) was applied to evaluate drinking, irrigation, industrial, and ecological uses, while spatial patterns were mapped using Inverse Distance Weighting (IDW) in a Geographic Information System. The results reveal critical exceedances in salinity (TDS up to 3,420 mg/L; EC up to 6,840 μS/cm), nutrient enrichment (PO₄³⁻ up to 10.85 mg/L; NH₃–N up to 10.78 mg/L), and turbidity (105 nephelometric turbidity units), mainly from untreated sewage, agricultural return flows, and limited dilution. WQI classification for drinking water showed 30% good, 50% fair, and 20% poor (<45), with S9 and S10 posing high health risks due to cumulative sewage, industrial discharges, and intensive farming runoff. For irrigation, 60% of sites were rated good, though elevated sodium, magnesium hazard, and potential salinity indicate risks of soil degradation. Industrial assessments revealed scaling (LI >0) and corrosion (RSI >8.5) in more than half the samples. Ecologically, 50% of sites recorded poor WQI (<45), reflecting eutrophication, organic load, and elevated temperatures. CCME-WQI/GIS mapping identified S9 and S10 as hotspots, concentrated near Lake Qarun where pollutant accumulation is intensified by weak hydrological flushing. The contrasting signatures of nutrient-enriched agricultural drains and salinity-dominated industrial reaches underscore the need for targeted interventions. Strengthening wastewater treatment, optimizing fertilizer use, enforcing standards, and enhancing public awareness are recommended. The integrated CCME-WQI/GIS framework offers a replicable tool for sustainable water management in arid, agriculture-dependent regions and supports progress toward Sustainable Development Goal 6.

1 Introduction

Water scarcity is a critical global issue, particularly affecting countries located in arid and semi-arid regions (Biswas et al., 2025). It poses a substantial challenge to sustainable development, influencing diverse sectors such as environmental integrity, public health, human welfare, food security, economic productivity, natural resource sustainability, and infrastructure planning (Karimi et al., 2024). As climate variability and population growth intensify water demand, the threat of water scarcity becomes more pronounced, especially in regions already experiencing limited freshwater availability. Arid countries must therefore adopt integrated and adaptive strategies to effectively manage their water resources and mitigate scarcity-related impacts (Alotaibi et al., 2023; Bernabé-Crespo and Loáiciga, 2024).

One of the most promising approaches to alleviate water scarcity is the use of non-conventional water resources (Gholami-Shabani and Nematpour, 2024). Egypt has embraced this strategy as a means to reduce the growing gap between water supply and demand. The Fayoum Governorate (FG), although uniquely positioned as the only Nile-irrigated oasis in the country, continues to suffer from chronic water shortages. These shortages are largely the result of increasing demand associated with land reclamation projects in surrounding desert areas. The resulting imbalance in water availability has led to inequitable water distribution, particularly affecting irrigation and drainage networks in downstream areas (Khairy et al., 2022). To cope with these challenges, the reuse of agricultural drainage water has become a widely adopted practice in FG, contributing to Egypt’s national water management objectives for 2037 and 2050 (Molle, 2018). During peak demand periods, drainage water is blended with canal water to supplement supply. However, this solution introduces new concerns, as the quality of drainage water is often compromised by pollution. Key contaminants originate from excessive agricultural inputs such as fertilizers and pesticides, as well as from untreated or poorly treated domestic and industrial effluents discharged into open drains (Khairy et al., 2022). Consequently, the safe reuse of drainage water requires consistent, rigorous water quality assessment to prevent environmental degradation and health risks (Anyango et al., 2024).

Surface water quality is shaped by a range of physical, chemical, and biological parameters influenced by both anthropogenic and natural processes (Akinnawo, 2023). For example, soil erosion caused by fluctuating river flow can lead to increased turbidity, while agricultural runoff often introduces microbial pathogens and nutrients into water bodies. Additionally, industrial discharges may contribute hazardous chemicals such as heavy metals and synthetic compounds (Abdugheni et al., 2023). The complexity of these influences makes it difficult to assess water quality using individual parameters in isolation. To address the challenge of assessing complex water datasets, Water Quality Indices (WQIs) have been developed to synthesize multiple parameters into a single, interpretable value. These indices provide a comprehensive evaluation of overall water condition, typically expressed on a scale from 0 to 100, where higher values indicate better quality (Reddy et al., 2022; Lap et al., 2023). Complementing this, geospatial techniques such as the Inverse Distance Weighted (IDW) interpolation method within Geographic Information System (GIS) platforms offer powerful tools for visualizing and predicting the spatial distribution of water quality metrics across large areas (Das, 2025; Sunitha and Reddy, 2022; Das et al., 2025).

Over time, numerous WQI formulations have been developed to suit different management objectives. Modified WQI approaches adjust parameter weights or class thresholds to reflect local land-use patterns and pollutant profiles, thereby improving sensitivity to region-specific conditions (Uddin et al., 2021; Akhtar et al., 2021). In parallel, Integrated WQI frameworks combine conventional indices with complementary tools—such as multimetric evaluations, health-risk overlays, or GIS-based spatial aggregation—to enable watershed-scale assessments and distributed monitoring (Masood et al., 2022; Shukla et al., 2025). Among these, the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) is one of the most widely recognized and adaptable frameworks. Its three-factor structure quantifies scope (F1: proportion of variables exceeding objectives), frequency (F2: proportion of tests exceeding objectives), and amplitude (F3: magnitude of exceedance) relative to guideline values, and consolidates these into a single score mapped onto transparent water-quality classes (CCME, 2017). This guideline-based design has been successfully applied across diverse use categories—including drinking water, irrigation, industry, livestock, recreation, and aquatic life protection—demonstrating flexibility beyond single-purpose indices.

Globally, integrated WQI–GIS frameworks have been increasingly employed to monitor water quality in environmentally stressed regions. In India, several studies used CCME-WQI or related indices with spatial interpolation techniques (e.g., IDW and kriging) to map water quality in rivers and reservoirs, revealing widespread degradation under agricultural, industrial, and urban pressures (Etikala et al., 2024; Shukla et al., 2025). Groundwater assessments in western India similarly showed that nearly 68% of the study area fell within “poor” to “very poor” categories, emphasizing the management relevance of spatially explicit WQI applications (Singh et al., 2022). In Iran, GIS-based WQI zoning maps in regions such as Taleghan highlighted seasonal shifts and clear spatial gradients in salinity, TDS, and metal contamination across arid catchments (Valiallahi and Yazdani, 2025). Collectively, these studies underscore recurring patterns of elevated EC, TDS, and nutrient enrichment in arid and semi-arid hydrological basins, driven by overlapping agricultural, municipal, and industrial stressors.

Despite the global adoption of CCME-WQI/GIS frameworks, Egypt’s closed drainage systems remain poorly characterized, with the Fayoum basin representing one of the most under-researched yet environmentally stressed hydrological settings in the country. As a closed watershed with no outflow to the Nile, Fayoum is uniquely prone to pollutant accumulation, high evaporation, and long water residence times, conditions that amplify the impacts of agricultural, municipal, and industrial discharges. This makes the basin an exceptional natural laboratory for testing advanced spatial water-quality assessment tools. Yet, few studies have applied integrated CCME-WQI/GIS methodologies in such an arid, closed-basin context or examined water suitability simultaneously across multiple reuse sectors. The novelty of this research lies in three dimensions. First, it applies the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), coupled with Inverse Distance Weighted (IDW) interpolation within a GIS platform, to generate high-resolution spatial maps of water quality—allowing precise identification of pollution hotspots. Second, it conducts a multi-sectoral evaluation that considers water suitability for drinking, irrigation, industrial use, and aquatic life, thus capturing trade-offs often overlooked in single-purpose assessments. Third, it situates the analysis within the Fayoum basin’s unique geomorphic and climatic constraints, providing insights transferable to other closed or water-scarce systems in the Middle East and North Africa.

Accordingly, the study pursues four main objectives: (i) to characterize the physicochemical properties of Fayoum surface waters during peak summer conditions (2024), when stressors are most pronounced; (ii) to apply the CCME-WQI integrated with GIS techniques for spatial mapping of water quality; (iii) to assess sector-specific suitability against recent international guidelines; and (iv) to identify critical pollution hotspots that can inform targeted remediation and sustainable water management strategies. Beyond advancing methodological rigor, the framework aligns with Egypt’s Water Strategy 2037 and contributes to the UN Sustainable Development Goals (SDGs 6.3–6.6), underscoring its broader scientific and policy relevance.

2 Study area

The Fayoum Governorate, located in Egypt’s Western Desert approximately 95 km southwest of Cairo, represents a geographically and hydrologically distinct region. It occupies a natural closed depression bounded by latitudes 29°02′–29°35′N and longitudes 30°23′–31°05′E, covering an area of about 6,068 km². According to the 2005 census, the population was estimated at 2.48 million, with Fayoum City serving as the administrative and urban center of the governorate (Abdel Wahed et al., 2015). The region is characterized by an arid desert climate, marked by hot and prolonged summers, mild winters, low annual rainfall, and high evaporation rates (Abdelhaleem et al., 2021). Fayoum is one of Egypt’s most agriculturally active governorates, producing wheat, rice, maize, clover, sugar beet, vegetables (e.g., tomato, potato, onion), and fruit orchards including citrus, grapes, figs, and olives. These crops depend on intensive irrigation and high fertilizer inputs. The most commonly used fertilizers are nitrogen-based compounds (urea, ammonium nitrate, ammonium sulfate) and phosphate formulations (single and triple superphosphate, mono- and di-ammonium phosphate), with potassium chloride (KCl) often applied to support cereal and vegetable production.

The geomorphology of Fayoum plays a decisive role in shaping water quality. As a closed depression with flat topography and no natural outflow to the Nile, the basin is highly vulnerable to pollutant accumulation. Strong evaporation and long water residence times further concentrate salts and nutrients, amplifying the impacts of agricultural, municipal, and industrial discharges. These conditions explain the elevated TDS, phosphate, and ammonia levels commonly observed in the drainage network. Geologically, the depression is bounded by Eocene carbonate plateaus composed of nummulitic limestones and marls, overlain in the north and northwest by Upper Eocene–Oligocene clastic successions (Qasr El-Sagha and Gebel Qatrani formations) comprising sandstones, mudstones, and conglomerates, with localized Oligocene basalts at Widan El-Faras (Anan and El Shahat, 2014; Mahmoud et al., 2024). The basin floor is mantled by Quaternary lacustrine and playa deposits of clays, silts, organic-rich sediments, gypsum, and halite, interspersed with alluvial sands, gravels, and aeolian dunes (Mohamed et al., 2015; Abdel Wahed et al., 2015). This lithologic architecture exerts a first-order control on water chemistry: carbonates buffer pH, evaporites enrich salinity (SO₄²⁻, Cl⁻), permeable sands enhance connectivity along drain pathways, and clay-rich lacustrine deposits retain nutrients and trace metals.

Hydrologically, Fayoum constitutes a unique system in Egypt as an internally drained basin. All surface waters and return flows ultimately discharge into Lake Qarun, rather than rejoining the Nile. To sustain agriculture, drinking water supply, and other municipal needs, the governorate depends heavily on Nile water diverted via the Bahr Youssef Canal. Water is distributed through a dense network of irrigation canals and pumping stations, while excess irrigation and drainage water—often enriched with fertilizers, pesticides, and untreated or partially treated municipal and industrial wastewater—is collected in a network of interconnected drains (Abdel Wahed et al., 2015; Fouad et al., 2024). This internal drainage system, compounded by rapid population growth, land reclamation pressures, and limited wastewater infrastructure, promotes pollutant accumulation and heightens the risks of ecological degradation. Direct discharges of treated and untreated effluents from sewage treatment plants into canals and drains further complicate regional water quality dynamics. Two main drains, El-Wadi and El-Bats, collect return flows from numerous secondary and tertiary drains across agricultural and urban areas before discharging into Lake Qarun, which functions as the terminal sink for drainage-related contaminants. This configuration makes Fayoum a strategic location for integrated water quality monitoring and assessment of cumulative anthropogenic impacts.

The sources of contamination in Fayoum’s drainage system are diverse, reflecting the combined influence of agricultural, municipal, and industrial activities. Agricultural drains are dominated by fertilizer residues, pesticides, and return flows enriched with phosphates and ammonia, while municipal outfalls contribute significant organic loads and dissolved salts. Industrial effluents also enter the system through El-Bats, El-Wadi, and smaller drains. Key industries include food and agro-processing (e.g., sugar refining, dairy production), textile manufacturing (particularly dyeing and finishing), and brick and ceramics production. These sectors release organic matter, nutrients, dyes, auxiliaries, suspended solids, and trace metals. Collectively, these inputs—superimposed on the closed and evaporative nature of the basin—intensify pollutant accumulation and explain the elevated salinity and heavy-metal hotspots often detected near drain inlets and within Lake Qarun (Abdelbaki, 2022; Abdelmageed et al., 2022; Elsayed et al., 2021).

Previous investigations have also highlighted the implications of water-quality deterioration for public health. Surveys of canals and drains reported widespread microbial contamination, including Escherichia coli and high coliform counts, pointing to risks of waterborne diseases through direct contact or reuse for irrigation (Fouad et al., 2024; Al-Afify et al., 2019). Risk assessments of Qarun fish have demonstrated significant heavy-metal bioaccumulation, with hazard indices exceeding safety thresholds for frequent consumers (Omar et al., 2013; El-Sherif et al., 2025). Moreover, nutrient enrichment and eutrophication have been shown to degrade ecological quality and reduce the safety of water reuse (Mansour et al., 2024).

Taken together, these findings highlight the urgency of integrated water-quality evaluation in the Fayoum–Lake Qarun system. The present study responds to this need by assessing microbiological, chemical, and risk-related parameters to inform environmental management and safeguard public health. Sampling sites were classified into irrigation waters (sourced from the Nile and mixed channels) and drainage waters (receiving runoff, wastewater, and industrial effluents), allowing the identification of sector-specific trends and spatial hotspots. This framework underpins the application of WQI and GIS analyses (Figure 1) and establishes Fayoum as a model case for developing transferable approaches to water-quality assessment and reuse in arid, internally drained, and agriculturally intensive basins.

Figure 1

Figure 1. Location map for the study area with declaration for the sampling sites.

3 Sampling and analytical methods

In July 2024, water samples were collected from ten sites (S1–S10) within the Fayoum catchment area, including both agricultural drains and wastewater treatment station discharge points. The selected sites were chosen to represent spatial variation across the region and capture both point and non-point sources of pollution. Detailed descriptions of the sampling locations and corresponding coordinates are presented in Table 1 and illustrated in Figure 1. While the sample size (10) may appear small relative to the governorate’s area (≈6,600 km²), sites were deliberately chosen along the major drains, WWTP outfalls, and agricultural returns that concentrate pollutant flows in this closed basin. This targeted design captures the principal contamination pathways and ensures representativeness despite limited site numbers.

Table 1

Table 1. GPS coordinates of sampling points.

At each site, in situ physicochemical parameters—including pH, temperature, total dissolved solids (TDS), and electrical conductivity (EC)—were measured using a portable SG78 SevenGo Duo Pro meter, which was calibrated prior to use with certified standard solutions to ensure high accuracy. Turbidity was measured using a Lutron TU-2016, Turbidity Meter (manufactured in Taiwan).

For laboratory analyses, water samples were collected using polyethylene (PE) bottles that had been pre-cleaned and acid-washed. Before filling, bottles were rinsed thoroughly with sample water to prevent cross-contamination. Each water sample was divided into two subsamples: one portion was acidified with concentrated nitric acid to pH < 2 for cation analysis, while the other was left unacidified for anion determination. Bottles were filled completely to avoid air bubbles, sealed, stored at 4 °C, and transported to the laboratory for immediate analysis. Laboratory analyses included a comprehensive suite of chemical parameters. Major cations—calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), and potassium (K⁺)—and major anions—bicarbonate (HCO₃⁻), chloride (Cl⁻), and sulfate (SO₄²⁻)—were analyzed using standard wet chemistry methods. Calcium and magnesium were quantified via complexometric titration with EDTA. Sulfate concentrations were measured using the turbidimetric method, and chloride was determined by Mohr’s titration. Bicarbonate was calculated based on titration data using acid-base reactions.

Chemical oxygen demand (COD) was measured using the potassium permanganate oxidation method. Orthophosphate (PO₄³⁻) concentrations were determined using the ascorbic acid–molybdate blue method. Ammonia (NH₃) was analyzed as total nitrogen using the Micro-Kjeldahl digestion method, while nitrate was measured after cadmium reduction to nitrite, followed by colorimetric analysis. All analyses were conducted following standard procedures recommended by (Rice et al., 2012), and results were recorded immediately upon sample processing to preserve data integrity. A summary of analytical parameters and methods is provided in Table 2.

Table 2

Table 2. The analytical procedures of the water samples according to the American Public Health Association (APHA) (Rice et al., 2012).

4 Drinking water quality index

To evaluate the suitability of surface water for drinking purposes, the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) was applied. This method provides a robust and standardized approach for summarizing water quality data by integrating multiple physicochemical parameters into a single numerical value. In this study, the CCME-WQI was calculated based on the average concentrations of 14 key water quality parameters measured at each of the ten sampling sites across the Fayoum catchment (Hamel and Quiniou, 2007). The parameters included in the index were pH, total dissolved solids (TDS), bicarbonate (HCO₃⁻), nitrate (NO₃⁻–N), sulfate (SO₄²⁻), phosphate (PO₄³⁻), calcium (Ca²⁺), magnesium (Mg²⁺), total hardness, sodium (Na⁺), potassium (K⁺), electrical conductivity (EC), chloride (Cl⁻), and turbidity. These variables were selected based on their relevance to public health and their widespread inclusion in national and international drinking water standards. The measured values were compared against the World Health Organization (WHO) Drinking Water Guidelines (2011), which acts as the reference for determining compliance with acceptable quality thresholds (WHO, 2011).

The CCME-WQI framework is built upon three core factors that quantify different aspects of water quality deviation from recommended standards. Factor 1 (F1), known as Scope, represents the percentage of parameters whose values exceed the allowable limits. It indicates how many different variables fail to meet the guidelines (Equation 1). Factor 2 (F2), referred to as Frequency, captures how often individual test results fall outside the acceptable range, expressing the proportion of failed tests across all observations (Equation 2). Factor 3 (F3), termed Amplitude, measures the extent to which the failed test results deviate from the guideline values, thereby reflecting the intensity of water quality exceedances (Equation 3) (Kachroud et al., 2019). These three components are combined mathematically to compute the overall index score.

$F1=\frac{\left(Numberoffailedvariables\right)}{\left(Totalnumberofvariables\right)}x100(1)$

$F2=\frac{\left(Numberoffailedtests\right)}{\left(Totalnumberoftests\right)}x100(2)$

$F3=\frac{nse}{\left(0.01nse+0.01\right)}(3)$

The calculation of the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) involves a multi-step process to quantify the extent to which water quality parameters deviate from established guidelines. A key component of this process is the determination of the excursion, which represents how far a failed test result falls outside the acceptable range. The method of calculating excursions depends on the nature of the guideline limit. For parameters where exceeding the objective constitute failure, the excursion is calculated using Equation 4:

$Excursioni=\frac{FailedTestValue}{Objective}-1(4)$

In cases where values below a certain threshold indicate non-compliance (e.g., for dissolved oxygen), the excursion is computed by Equation 5.

$Excursioni=\frac{Objective}{FailedTestValue}-1(5)$

If the objective value is zero (typically rare), the excursion is defined simply as in Equation 6.

$\text{Excursion\hspace{0.17em}}\mathrm{i}=\text{Failed\hspace{0.17em}Test\hspace{0.17em}Value}(6)$

After calculating excursions for all failed tests, the Normalized Sum of Excursions (nse) is determined using the following Equation 7.

$nse=\frac{\sum Excursion}{Totalnumberoftests}(7)$

This normalized value forms the basis for calculating Factor 3 (F3) of the index, which reflects the magnitude of water quality exceedances.

Finally, the overall CCME-WQI is computed by integrating the three factors—F1 (Scope), F2 (Frequency), and F3 (Amplitude)—into a single index value, using Equation 8.

$CCMEWQI=(100-\left(\frac{\sqrt{{F1}^2+{F2}^2+{F3}^2}}{1.732}\right)(8)$

This formula ensures that the index value ranges from 0 to 100, providing a standardized interpretation of water quality where higher values indicate better water conditions. The classification of index results into categories (Excellent, Good, Fair, Marginal, and Poor) allows for effective communication and decision-making regarding water resource management. Values from 95 to 100 indicate Excellent water quality; 80–94, Good; 65–79, Fair; 45–64, Marginal; and 0–44, Poor. This classification system allows for a straightforward interpretation of complex water quality data and offers a reliable basis for comparing drinking water safety across different sampling sites. In the context of this study, the CCME-WQI serves as a vital tool for identifying areas at risk and supporting the development of water management strategies in the Fayoum Governorate.

5 Irrigation water quality index

In addition to evaluating drinking water safety, this study assessed the quality of water for irrigation purposes, as well as its suitability for livestock and poultry. Several hydrochemical parameters were used to determine irrigation water quality, each offering insights into potential impacts on soil permeability, salinity hazards, and plant health. These parameters, along with their respective calculation formulas, are summarized in Table 3. Evaluating these indices is essential for understanding the long-term implications of water use on agricultural productivity and livestock wellbeing.

Table 3

Table 3. Displays irrigation parameters.

6 Industrial water quality index

Water quality is equally vital for industrial applications, particularly in light of the corrosion and scaling issues commonly encountered in both domestic and industrial systems. Ensuring the availability of water that meets specific quality standards is crucial for the operational efficiency and longevity of industrial infrastructure. In this study, the potential for corrosion and scaling was evaluated using widely recognized indices that provide a quantitative measure of water aggressiveness or depositional tendencies. All calculations were based on ion concentrations expressed in milligrams per liter (mg/L), and the formulas used for each index are presented in Table 4. These assessments offer practical insight into the compatibility of the water with industrial systems.

Table 4

Table 4. Displays industrial parameters.

7 Water quality index mapping using spatial interpolation techniques

To visualize spatial variations in water quality across the study area, Geographic Information System (GIS) tools were used to generate water quality index (WQI) maps. The key advantage of GIS-based techniques over conventional point-sampling methods lies in their ability to integrate spatial and temporal dimensions, thereby providing a more comprehensive view of surface water characteristics (Ahmed et al., 2023). Among various interpolation methods, the Inverse Distance Weighted (IDW) technique was selected for this study due to its high accuracy and proven reliability in hydrological and pollution modeling contexts (Hough et al., 2004).

IDW is a deterministic spatial interpolation method that estimates unknown values at un-sampled locations based on the weighted average of nearby observed data points. The value of Ẑ(S₀) which refers to the estimated value of a parameter at an unsampled location (S₀) based on weighted averages of nearby known data points in the Inverse Distance Weighted (IDW) interpolation method is computed using Equation 22:

$Z\left(S_0\right)={\sum }_{i=1}^{n}Wi\times Z\left(Si\right)(22)$

where Z (Si) represents the observed value at location Si, and Wi is the weight assigned to each point based on its distance (di) (from the prediction location S₀. The weights are calculated using Equation 23:

$Wi=\frac{\frac{1}{d_i^k}}{{\displaystyle {\sum }_{i=1}^n}\frac{1}{d_i^k}}(23)$

Here, k is a user-defined power parameter that controls the significance of nearby points, and n is the total number of known data points. The resulting WQI maps provide a visual representation of spatial patterns in water quality, facilitating the identification of critical hotspots and supporting more informed resource management decisions.

8 Results and discussion

8.1 Physicochemical properties of water samples

A total of 17 physicochemical parameters (temperature, pH, electrical conductivity, total dissolved solids, turbidity, and ion concentrations) were analyzed in water samples collected from agricultural drains and wastewater treatment stations in the Fayoum Governorate during the summer of 2024. These parameters are critical indicators of water quality, influencing its suitability for domestic, agricultural, industrial, and ecological applications. The statistical summary of all measured variables, including minimum, maximum, mean values, and standard deviations, is presented in Table 5. These data provide a detailed profile of the current state of water quality across different sampling sites and enable identification of spatial anomalies or critical hotspots.

Table 5

Table 5. Presents the descriptive statistics of various water bodies, including drains and treatment stations.

8.1.1 Temperature

Temperature is a vital physical parameter with far-reaching ecological and chemical implications. In this study, water temperatures ranged from 29.9 °C to 37.3 °C, with an average value of 31.67 °C (Table 5). These values are significantly elevated and exceed optimal conditions for most aquatic ecosystems, particularly during Egypt’s arid summer season. From a technical standpoint, temperature influences solubility, chemical kinetics, and redox potential. Elevated temperatures decrease the solubility of oxygen, thereby reducing dissolved oxygen (DO) levels and impairing the self-purification capacity of natural water bodies. Moreover, warmer water accelerates biochemical reactions, which can exacerbate the breakdown of organic matter and result in increased oxygen demand. Ecologically, sustained high temperatures can alter species composition by favoring thermotolerant organisms while excluding sensitive species. For instance, cold-water species and certain planktonic communities may decline, disrupting food chains and leading to a loss of biodiversity (Abdel Gawad et al., 2022; Mohammad et al., 2024). Thermal pollution from anthropogenic sources—such as untreated municipal discharges and return flows from industrial cooling processes—can compound this effect.

From a public health perspective, elevated temperatures promote microbial growth, including pathogenic bacteria such as E. coli, Vibrio cholerae, and protozoa like Giardia. These organisms thrive in warm, stagnant water conditions, increasing the risk of waterborne diseases. High temperatures can also degrade disinfectant residuals in treated water, undermining microbial control in distribution systems. In the Fayoum region, the observed temperatures likely result from prolonged solar exposure, low flow velocity in open channels, and discharge of untreated or partially treated effluents. If not addressed, these conditions may worsen with climate change, reinforcing the need for thermal control strategies, such as shading of canals, enhancement of flow velocity, or treatment of thermal discharges before release.

8.1.2 pH

The pH values recorded across all sampling sites ranged from 7.395 to 8.63, with a mean of 7.68, indicating slightly alkaline water conditions (Table 5). This range falls within acceptable limits for aquatic life (6.5–9.0), as per global environmental guidelines (Mohammad et al., 2024). However, for drinking water use, WHO recommends a pH range of 6.5–8.5 (WHO, 2011). All samples except for sample 10 complied with this standard. Similarly, the FAO suggests a pH range of 6.0–8.5 for irrigation water. Sample 10, therefore, presents a concern for both domestic and agricultural applications. Technically, pH influences chemical equilibria in water, including solubility of metals and the speciation of nutrients and contaminants. For example, the toxicity of ammonia (NH₃–N) increases with pH due to the shift in equilibrium from ammonium ion (NH₄⁺) to un-ionized ammonia, which is more toxic to aquatic life. High pH levels can also result in calcium carbonate precipitation, leading to scaling in irrigation systems and industrial pipes. Environmentally, alkaline waters may contribute to eutrophication by enhancing the availability of nutrients like phosphate. Alkalinity can also affect soil structure and permeability when such water is used for irrigation, especially in clay-dominated soils. Continuous use of high-pH water may lead to soil sodicity, negatively affecting crop productivity.

From a health perspective, extreme pH values (below 6.5 or above 8.5) can alter the taste of drinking water and may corrode plumbing materials, leading to the leaching of heavy metals such as lead (Pb) and copper (Cu) into the water supply. Chronic exposure to such metals is associated with neurological, gastrointestinal, and developmental disorders. The elevated pH at sample 10 may be linked to industrial discharges, agricultural runoff containing lime-based compounds, or incomplete biological treatment processes. This site may warrant regulatory attention and targeted remediation to prevent broader impacts on irrigation efficiency and human health.

8.1.3 Electrical conductivity (EC)

Electrical conductivity (EC) is a key indicator of water’s ionic concentration, reflecting the total dissolved solids (TDS) and thus serving as a proxy for salinity (Table 5). It measures the water’s ability to conduct electrical current, which increases with the presence of dissolved inorganic ions such as sodium (Na⁺), chloride (Cl⁻), sulfate (SO₄²⁻), and bicarbonate (HCO₃⁻). As such, EC is a critical parameter in evaluating the degree of mineralization, determining the appropriate dosing of treatment chemicals, and assessing water’s suitability for various uses. In this study, EC values across the sampled sites ranged from 363 μS/cm to 6,840 μS/cm, with a mean value of 1,559.1 μS/cm. These values exhibit considerable spatial variability, which likely reflects differences in pollution loading, evaporation rates, industrial discharges, and agricultural runoff. From a technical standpoint, high EC values indicate elevated concentrations of dissolved ions, which can increase water hardness and reduce the effectiveness of treatment processes such as coagulation, disinfection, and filtration. EC is often directly proportional to TDS and can therefore be used to estimate salinity impacts on infrastructure and end-use applications. In terms of drinking water standards, the World Health Organization (WHO) suggests an EC limit of 1,500 μS/cm for palatability, although no strict health-based threshold exists [15]. In this study, only samples 1, 2, and 8 had EC levels within this recommended range, making them suitable for human consumption. The remaining samples exceeded the WHO guideline, potentially affecting water taste and contributing to mineral scaling in household plumbing.

Environmentally, elevated EC values—particularly at sample 10, which reached the upper range—pose serious concerns for irrigation water use. According to the Food and Agriculture Organization (FAO), EC values above 3,000 μS/cm can adversely affect soil structure and crop productivity, especially in sensitive or poorly drained soils. Excessive salinity impairs plant water uptake by creating osmotic stress and can lead to soil compaction, reduced permeability, and long-term degradation of agricultural land. In this study, samples 1 through 9 fall within acceptable irrigation limits, whereas sample 10 exceeds the safe threshold, indicating a risk of salinization and potential crop yield reduction if used without dilution or treatment. From a public health perspective, while high EC alone may not directly threaten human health, it often signals the presence of elevated concentrations of associated ions—such as nitrates, chlorides, and sulfates—that may be harmful at certain levels. Moreover, mineral-rich water may cause gastrointestinal discomfort in sensitive populations and can interact with plumbing systems, promoting scale formation and metal leaching, particularly under high-pH conditions. The extreme EC value observed at sample 10 suggests the presence of significant anthropogenic influence—potentially from untreated industrial wastewater, concentrated agricultural runoff, or evaporation-enriched drainage inflows. This site may represent a localized pollution hotspot, meriting further investigation and regulatory intervention.

8.1.4 Total dissolved solids (TDS)

Total Dissolved Solids (TDS) represent the cumulative concentration of all dissolved substances in water, including inorganic salts (such as calcium [Ca²⁺], sodium [Na⁺], magnesium [Mg²⁺], and chloride [Cl⁻]) as well as small amounts of organic matter, silt, clay particles, and phytoplankton (Table 5) (Dhanush et al., 2024). TDS is a key parameter in evaluating water salinity, which directly affects its aesthetic, agricultural, ecological, and industrial suitability. In the present study, TDS concentrations across drains and treatment stations ranged from 181.7 mg/L to 3,420 mg/L, with a mean value of 779.57 mg/L. This wide variation indicates differences in local geochemistry, anthropogenic inputs, evaporation rates, and runoff patterns. Elevated TDS levels are often indicative of contamination from domestic sewage, agricultural return flows, and industrial effluents, all of which are prevalent in the Fayoum region.

From a technical and treatment perspective, high TDS can interfere with the efficiency of water treatment processes, including filtration, membrane technologies (e.g., reverse osmosis), and ion exchange. Excessive TDS contributes to scaling and fouling in water infrastructure, reducing the operational life of pipes and appliances. According to the World Health Organization (WHO), drinking water with TDS levels below 600 mg/L is considered good, while water with TDS up to 1,000 mg/L is acceptable in the absence of better alternatives (WHO, 2011). In this study, samples 1, 2, 4, 5, 6, 7, and 8 complied with these guidelines and are considered acceptable for human consumption. In contrast, samples 3, 9, and particularly sample 10 exceeded recommended thresholds, potentially affecting water taste and increasing the risk of gastrointestinal irritation in sensitive populations.

Environmentally, high TDS concentrations can adversely affect aquatic ecosystems. Elevated salinity impairs osmoregulation in freshwater organisms, reduces reproductive success, and alters species composition by favoring salt-tolerant organisms over sensitive native species. Sustained high TDS levels may contribute to long-term ecological degradation of aquatic habitats, particularly in terminal basins like Lake Qarun, which already suffers from salinity accumulation due to its closed drainage nature. For irrigation purposes, the Food and Agriculture Organization (FAO) recommends a maximum TDS concentration of approximately 2000 mg/L for most crops, beyond which soil salinization and plant stress become significant concerns. In this study, all samples except for sample 10 were within acceptable irrigation limits, suggesting that most water sources are currently suitable for agricultural use. However, sample 10 exceeded 3,000 mg/L, rendering it unsuitable for irrigation without treatment or dilution. Prolonged use of such saline water can lead to soil sodicity, reduced crop yields, and eventual land degradation. In summary, TDS levels in the majority of sites were within permissible limits for multiple uses, but sample 10 exhibited excessive salinity that may signal point-source pollution or significant evaporative concentration. This highlights the need for targeted mitigation measures, such as improved wastewater treatment and saline water blending strategies, particularly in regions with limited freshwater availability.

8.1.5 Turbidity

Turbidity is a key physical parameter used to assess water clarity, reflecting the concentration of suspended particulate matter in the water column (Table 5). These suspended particles may include organic debris, fine silt, clay, phytoplankton, microbial cells, and color-producing substances such as humic and fulvic acids (Dhanush et al., 2024). While turbidity itself is not a direct indicator of health risk, it significantly influences the physical, chemical, and biological characteristics of water and is widely used as a proxy for water quality monitoring. In this study, turbidity levels at the sampled drains and wastewater treatment stations ranged from 13.4 to 105 nephelometric turbidity units (NTU), with a mean value of 31.72 NTU. These values greatly exceed the World Health Organization’s (WHO) recommended limit of 5 NTU for drinking water (WHO, 2011 and 2017), indicating that all sampled sites fail to meet potable water standards based on clarity.

Technically, high turbidity interferes with water treatment processes, particularly disinfection. Suspended particles can shield microorganisms from ultraviolet (UV) light or chlorine exposure, thereby reducing the efficacy of pathogen inactivation. Furthermore, increased turbidity is often associated with elevated microbial loads, as it can provide attachment surfaces for bacteria, viruses, and protozoa. From an environmental standpoint, the presence of fine suspended solids in surface waters limits light penetration, thereby disrupting photosynthetic activity in aquatic plants and phytoplankton. This can lead to a cascade of ecological effects, including reduced primary productivity and alteration of food web dynamics. In highly turbid waters, solar energy is absorbed more efficiently by the particulate-laden surface layer, resulting in increased water temperature (Mishra et al., 2023). This thermal effect contributes to the formation of stratified conditions and promotes hypoxia—low oxygen availability—especially in stagnant or slow-flowing systems. Hypoxic conditions, in turn, impair the survival of fish and other aerobic aquatic organisms and may lead to the release of nutrients or heavy metals from sediments. From a health perspective, turbid water is aesthetically unappealing and can cause consumer rejection even if it is microbiologically safe. More importantly, high turbidity is often correlated with the presence of pathogenic microorganisms, increasing the risk of waterborne diseases such as giardiasis, cryptosporidiosis, and bacterial gastroenteritis. This is particularly concerning in regions where water treatment infrastructure is insufficient or where untreated surface water is directly used for domestic purposes.

The excessive turbidity observed across all sampling points in the current study suggests substantial contamination from surface runoff, sewage discharge, or inefficient solid-liquid separation in treatment plants. The highest turbidity level (105 NTU) likely reflects a site with significant inputs of suspended solids, possibly from erosion, wastewater effluents, or agricultural return flows. Addressing turbidity issues in Fayoum’s water sources is therefore critical—not only for aesthetic and treatment efficiency reasons—but also for ensuring the microbiological safety of water for human and ecological health. This may involve enhanced sediment control practices, pre-treatment filtration upgrades, or improved solid waste management in upstream catchment areas.

8.1.6 Chemical oxygen demand (COD)

Chemical Oxygen Demand (COD) is a key indicator of water quality that quantifies the amount of oxygen required to chemically oxidize organic and inorganic matter present in a water sample (Table 5). Unlike Biological Oxygen Demand (BOD), which measures oxygen consumption by microbial activity, COD reflects the total potential oxygen consumption from chemically oxidizable substances, including biodegradable and non-biodegradable organics (Mishra et al., 2023). It is a widely used metric for assessing the organic pollution load in both natural and engineered water systems. In this study, COD values in the samples collected from agricultural drains and treatment stations ranged from 2.0 to 13.2 mg/L, with a mean value of 5.24 mg/L. The majority of samples fell within the World Health Organization (WHO) recommended limit of ≤10 mg/L for surface water intended for domestic and recreational uses (Dhanush et al., 2024). However, sample 3 exceeded this threshold, with a COD value of 13.2 mg/L, indicating a higher-than-acceptable level of organic pollution.

From a technical standpoint, elevated COD levels suggest the presence of high concentrations of oxidizable organic compounds, which may include domestic wastewater residues, agricultural runoff rich in fertilizers and pesticides, animal waste, or industrial effluents. In particular, COD values above 10 mg/L may indicate incomplete biological treatment, leaching of decaying organic materials, or direct discharge of untreated sewage into open drains. Environmentally, high COD levels can lead to oxygen depletion in receiving water bodies, especially in stagnant or low-flow systems where re-aeration is minimal. This results in hypoxic or anoxic conditions, which severely impact aquatic life. Sensitive species such as fish and macroinvertebrates require oxygen-rich environments; in oxygen-depleted zones, their survival, reproduction, and feeding behavior are compromised. Furthermore, low oxygen availability can stimulate anaerobic microbial processes, potentially releasing harmful byproducts such as methane, hydrogen sulfide, and ammonia.

From a human health perspective, while COD itself is not a direct health hazard, it is a strong proxy for organic contamination, which often correlates with the presence of pathogens and chemical toxins. Elevated COD can suggest the possible presence of biological contaminants, including bacteria, viruses, and protozoa, especially when sourced from untreated or partially treated sewage. It may also reflect contamination with industrial chemicals, solvents, or other toxic organics, depending on the land use and waste discharge practices in the surrounding area. The observation that sample 3 exceeds WHO standards raises concerns about localized sources of organic pollution. This site may be receiving untreated domestic wastewater, decaying plant matter, or agricultural runoff rich in organic load. Immediate action may be required to identify and mitigate pollution sources at this location through improved wastewater management, buffer zone implementation, or enforcement of environmental discharge regulations. In summary, while most sampling locations exhibit acceptable COD levels, the exceedance at sample 3 underscores the need for ongoing monitoring and localized remediation, particularly in areas where drains are closely linked to human activity or are in proximity to untreated wastewater inputs.

8.1.7 Nutrients

The presence of nutrient salts—primarily nitrate (NO₃⁻–N), ammonia (NH₃–N), and phosphate (PO₄³⁻)—plays a dual role in aquatic ecosystems (Table 6). These nutrients are essential for supporting primary productivity, providing a foundational energy source for phytoplankton, zooplankton, and fish populations (Al-Afify et al., 2019). However, when present in excess, they contribute to serious ecological degradation, including eutrophication, and raise significant public health concerns. This study measured all three nutrient parameters across ten sampling points in the Fayoum Governorate, covering both agricultural drains and wastewater treatment stations.

Table 6

Table 6. Nutrient pollution risk matrix.

Nitrate concentrations ranged from 0.025 to 1.837 mg/L, all falling well below the WHO maximum permissible limit of 50 mg/L for drinking water (WHO, 2011 and 2017). Despite their compliance, even low nitrate concentrations can act synergistically with phosphate to initiate or sustain eutrophic conditions, especially in nutrient-sensitive water bodies. Nitrates are highly soluble and commonly leach into water systems through fertilizer runoff, manure application, and storm water drainage from cultivated lands and urban areas (Mishra et al., 2023). Ammonia (NH₃–N) was recorded in the range of 0.77–10.78 mg/L, with some samples nearing or exceeding ecological safety thresholds, particularly for aquatic life. Ammonia may originate from organic matter decomposition, untreated sewage, or agricultural effluents (Ahmad et al., 2022). It exists in equilibrium with its ionized form (NH₄⁺), and the proportion of toxic un-ionized NH₃ increases with higher pH and temperature—both of which are prevalent conditions in the Fayoum region. The presence of ammonia at these levels strongly indicates organic pollution, insufficient wastewater treatment, and possible fecal contamination.

Phosphate (PO₄³⁻) concentrations were exceptionally high, ranging from 318.41 to 10848 μg/L (0.318–10.848 mg/L), significantly surpassing the commonly cited eutrophication threshold of 100 μg/L (Al-Afify et al., 2019). Phosphates are introduced into aquatic systems primarily through fertilizer runoff, sewage discharge, and soil erosion. Unlike nitrogen, phosphorus binds strongly to sediments and can persist in the system, contributing to internal loading. This allows lakes and reservoirs—such as Lake Qarun, which receives drainage from Fayoum—to sustain algal blooms even after reductions in external phosphorus inputs.

To better understand spatial variation and assess management priorities, a nutrient pollution risk matrix were developed (Table 6). Sites such as S3 and S9 exhibited particularly high levels of ammonia and phosphate, indicating very high to high nutrient risk. These locations are likely influenced by untreated domestic sewage, intensive agricultural practices, and unregulated wastewater discharges. In contrast, sites S5, S6, and S10 showed relatively lower nutrient levels, suggesting moderate to low risk, though long-term accumulation may still present challenges. Areas with elevated risk levels correspond with regions of intensive land use and dense rural habitation, reinforcing the link between non-point source pollution and nutrient enrichment.

The environmental consequences of unchecked nutrient loading are profound. Eutrophication leads to excessive algal and macrophyte growth, which depletes dissolved oxygen through microbial decomposition. This results in hypoxic or anoxic conditions, contributing to the death of fish and invertebrates and the alteration of aquatic community structures. Additionally, cyanobacterial blooms can release toxic cyanotoxins, posing direct threats to both aquatic ecosystems and human health. From a health standpoint, while nitrate concentrations were within safe limits, prolonged exposure—especially in infants—can lead to methemoglobinemia (“blue baby syndrome”), a potentially fatal condition (Mishra et al., 2023). Elevated ammonia and phosphate levels are not toxic at the measured concentrations for human consumption, but they signal fecal contamination and raise concerns about the potential presence of pathogenic microorganisms. These findings point to possible microbiological contamination pathways that warrant further investigation.

The nutrient profiles observed in this study reflect typical conditions in agro-urban transitional zones, where intensive farming, poorly managed sewage systems, and uncontrolled urban runoff converge. The high phosphorus and ammonia levels underscore the urgency of implementing integrated nutrient management strategies to safeguard both water quality and ecosystem function. To mitigate nutrient pollution in the Fayoum drainage network, it is essential to upgrade and expand sewage treatment facilities, particularly near high-risk sites, and to implement agricultural best management practices such as optimized fertilizer use, cover cropping, and vegetative buffer zones. Enforcing regulatory controls on point-source discharges through regular inspections and penalties is also critical. Furthermore, establishing continuous water quality monitoring using remote sensing and GIS technologies will enable real-time assessment of nutrient dynamics and early detection of eutrophication risks. Without such interventions, nutrient enrichment will continue to threaten biodiversity, agricultural water reuse, and the long-term sustainability of water resources in the region.

8.1.8 Cations and anions

The analysis of major cations (Na⁺, K⁺, Ca²⁺, Mg²⁺) and anions (HCO₃⁻, Cl⁻, SO₄²⁻) in water samples from agricultural drains and wastewater treatment stations in the Fayoum Governorate revealed substantial variability in ion concentrations, with implications for water quality, ecological integrity, and human health (Table 7). Sodium (Na⁺) concentrations ranged from 37.5 to 569.4 mg/L, and potassium (K⁺) from 5.7 to 66.7 mg/L. Elevated sodium levels, particularly above 200 mg/L, can contribute to soil sodicity when used for irrigation, reducing soil permeability and structure, which in turn affects crop productivity. High sodium intake in drinking water is also associated with hypertension and cardiovascular risks, especially in vulnerable populations. Calcium (Ca²⁺) concentrations varied widely, from 19.24 to an exceptionally high 193.987 mg/L, while magnesium (Mg²⁺) levels ranged from 1.95 to 114.79 mg/L. Excessive concentrations of these divalent cations can lead to increased water hardness, which interferes with soap efficiency, causes scaling in pipes and boilers, and can contribute to kidney stone formation in humans when consumed over long periods. Environmentally, high calcium and magnesium levels can alter the ionic balance in aquatic ecosystems, affecting osmoregulation in freshwater organisms and altering species composition. Bicarbonate (HCO₃⁻), the principal component of surface water alkalinity, was found in concentrations between 192.4 and 509.6 mg/L, with an average peak of 294.06 mg/L recorded during summer. This seasonal rise is likely due to increased microbial respiration and the decomposition of organic matter under anaerobic conditions, which release carbon dioxide and form bicarbonates (Al-Afify et al., 2019).

Table 7

Table 7. Cations and anions concentrations and risk matrix.

Elevated bicarbonate levels can increase water alkalinity, buffering pH changes but also contributing to carbonate precipitation, which may exacerbate scaling problems in water infrastructure. Chloride (Cl⁻) concentrations ranged from 2.84 to 191.43 mg/L, reflecting possible contamination from domestic sewage, livestock waste, or saline irrigation return flows. While chloride is essential in small quantities, elevated levels can make water unpalatable and corrosive, and in irrigation contexts, may cause leaf burn and yield reduction in chloride-sensitive crops. Sulfate (SO₄²⁻) levels fluctuated between 92.08 and 1,130.6 mg/L, with values exceeding 500 mg/L raising concern for both health and agricultural use. High sulfate concentrations in drinking water can cause gastrointestinal irritation, particularly diarrhea in un-acclimated individuals, while in aquatic environments, sulfates may contribute to oxygen depletion as they are reduced to sulfides under anaerobic conditions, producing toxic hydrogen sulfide gas. The overall ionic composition observed in this study indicates both natural geochemical contributions and substantial anthropogenic inputs from fertilizers, untreated sewage, and possibly industrial activities. These findings highlight the need for ongoing monitoring and management, as the accumulation of salts and hardening agents in surface waters can progressively degrade their suitability for drinking, irrigation, and sustaining healthy aquatic ecosystems.

8.2 Drinking and aquatic life

The Water Quality Index (WQI) was applied to evaluate the suitability of surface water in the Fayoum Governorate for both drinking water supply and the protection of aquatic life, using the Canadian Council of Ministers of the Environment (CCME) methodology. Supplementary Tables S1 and S8 provide a detailed summary of the WQI values and their corresponding classifications for each site. For the drinking water assessment, WQI scores were derived from 14 key physicochemical parameters—TDS, pH, bicarbonate (HCO₃⁻), nitrate (NO₃⁻-N), chloride (Cl⁻), sulfate (SO₄²⁻), sodium (Na⁺), potassium (K⁺), calcium (Ca²⁺), magnesium (Mg²⁺), phosphate (PO₄³⁻), total hardness (TH), electrical conductivity (EC), and turbidity—benchmarked against WHO drinking water quality guidelines. The results revealed that samples 1, 2, and 6, scoring between 80 and 94, fell into the ‘Good’ category, indicating that these water sources generally comply with drinking standards and pose minimal risk to public health. Samples 3, 4, 5, 7, and 8, classified as ‘Fair’ (WQI 65–79), suggest water of moderate quality that may occasionally exceed acceptable limits, particularly for parameters such as EC, turbidity, or hardness, requiring pre-treatment before use. Alarmingly, samples 9 and 10, with WQI values below 44, were categorized as ‘Poor,’ rendering them unsafe for consumption without significant purification. These results reflect the cumulative impact of agricultural runoff, sewage discharge, and sediment transport, which contribute to high loads of suspended solids, dissolved salts, and nutrients. From a health perspective, long-term exposure to such conditions—particularly elevated nitrates, hardness, or pathogens associated with high turbidity—can increase the risk of gastrointestinal illness, kidney complications, and methemoglobinemia in vulnerable populations.

The WQI for aquatic life protection was assessed using a tailored set of nine parameters—TDS, pH, temperature, nitrate (NO₃⁻-N), chloride (Cl⁻), phosphate (PO₄³⁻), ammonia (NH₃-N), chemical oxygen demand (COD), and turbidity—following CCME (2007; 2017) environmental water quality guidelines (CCME, 2007 and 2019). Results showed that samples 1, 2, 5, 6, and 8 fell into the ‘Marginal’ category (CCME-WQI 45–64), meaning that aquatic life at these sites is likely experiencing periodic stress due to sub-optimal water quality, particularly in relation to elevated nutrient and organic matter levels. More critically, samples 3, 4, 7, 9, and 10 were classified as ‘Poor’ (WQI 0–44), indicating chronic water quality degradation with frequent violations of ecological thresholds. This condition likely leads to reduced biodiversity, disruption of trophic interactions, and potential collapse of sensitive species populations, such as native invertebrates and fish. The co-occurrence of ‘Poor’ WQI ratings for both drinking and aquatic uses—especially at samples 9 and 10—signals multi-sectoral risk zones, where untreated effluents, stagnation, and excessive nutrient loading create conditions unsuitable for human and ecological use.

The broader significance of these findings lies in their implications for sustainable water resource management in arid and semi-arid regions. The application of CCME-WQI provides a powerful diagnostic tool for translating complex water quality data into actionable insights. In the case of Fayoum, the results clearly identify priority areas for intervention, where improving wastewater infrastructure, reducing agricultural runoff, and restoring hydrological connectivity are urgently needed. Additionally, these findings reinforce the importance of integrated water quality monitoring that addresses both anthropogenic stressors and natural variability, particularly as climate change and land use pressures intensify. Without proactive management, declining water quality will continue to undermine public health, reduce irrigation efficiency, degrade aquatic ecosystems, and increase the economic burden of water treatment in this environmentally vulnerable region.

8.3 Irrigation water quality evaluation

To evaluate the suitability of surface water for agricultural reuse in the Fayoum Governorate during the summer season, a comprehensive assessment was conducted using multiple indices that reflect the potential impacts of salinity, sodicity, and ionic composition on both soil health and crop productivity. Excessive levels of salts and certain ions in irrigation water can alter the osmotic potential of the root zone, inhibit water uptake, reduce nutrient availability, and in some cases, induce phytotoxic effects. Therefore, water samples from drains and treatment stations were analyzed using eight key indices: Electrical Conductivity (EC), Sodium Adsorption Ratio (SAR), Residual Sodium Carbonate (RSC), Sodium Percentage (Na%), Magnesium Hazard (MH), Kelley’s Index (KI), Permeability Index (PI), and Potential Salinity (PS), alongside the Canadian Water Quality Index (CWQI) adapted for irrigation water as presented in Table 8 and classified using criteria summarized in Table 9 (Dhanush et al., 2024; Egbueri et al., 2023; Sundaray et al., 2009).

Table 8

Table 8. Presents the irrigation water quality indices.

Table 9

Table 9. Classification scheme for irrigation water quality indices [22].

Electrical Conductivity (EC), a measure of salinity hazard, directly influences the osmotic pressure of soil water, affecting nutrient availability and plant physiological processes (Dhanush et al., 2024). EC values across the study sites ranged from 363 to 6,840 μS/cm, with an average of 1,559.1 μS/cm. According to the Wilcox classification (Egbueri et al., 2023), water in the C1–C2 class (EC < 750 μS/cm) is generally safe for all crops, whereas C3 water (750–2,250 μS/cm) poses moderate to high salinity risks and may only be suitable for salt-tolerant crops under controlled leaching conditions. C4 waters (EC > 2,250 μS/cm) are typically unsuitable for irrigation. In this study, samples S1, S2, and S8 were categorized as C2 (moderate risk), samples S3–S7 as C3 (high risk), and samples S9 and S10 as C4, indicating serious limitations for agricultural reuse due to excessive salinity.

The Sodium Adsorption Ratio (SAR), which quantifies the proportion of sodium relative to calcium and magnesium, is a crucial indicator of soil structural stability. High SAR values are known to displace calcium from soil colloids, resulting in clay dispersion and reduced permeability (Dhanush et al., 2024; Egbueri et al., 2023; Yıldız and Karakuş, 2020). SAR values in the collected samples ranged from 1.44 to 7.98, with all samples falling below the critical threshold of 10, thus classified as suitable for irrigation from a sodicity perspective. Although SAR values were within acceptable limits, the concurrent presence of high salinity in some samples may amplify their adverse effects on soil structure and infiltration. Sodium Percentage (Na%) offers another lens through which to assess the risk of sodium accumulation in soils. Excessive Na⁺ levels, particularly when combined with chloride or carbonate, can lead to saline or alkaline soil development, adversely impacting crop health (Dhanush et al., 2024; Egbueri et al., 2023). In the present study, Na% ranged from 40.9% to 57.9%, with all samples falling within the acceptable range (40%–60%) for irrigation use. Nevertheless, long-term irrigation with such water may necessitate soil amendments or periodic leaching to mitigate sodium buildup. Residual Sodium Carbonate (RSC), which evaluates the effect of carbonate and bicarbonate on the availability of Ca²⁺ and Mg²⁺, ranged from −10.91 to 1.72 mg/L. Negative RSC values suggest that calcium and magnesium are not being precipitated as carbonates, allowing these beneficial cations to remain available for plant uptake (Dhanush et al., 2024; Sundaray et al., 2009). All samples were classified as suitable, except for sample S6, which had a marginal RSC value indicating potential risk of soil alkalization.

The Magnesium Hazard (MH) index, which assesses the proportion of magnesium relative to calcium and total cations, ranged from 10.77% to 59.98%, with a mean value of 36.44%. MH values above 50% are considered problematic, as excessive magnesium can disrupt soil aggregation and fertility [22]. Accordingly, samples S2, S5, S9, and S10 were deemed unsuitable for irrigation, highlighting the need for soil conditioning or blending with better-quality water at these sites.

Kelley’s Index (KI), another measure of sodicity risk based on the ratio of sodium to calcium and magnesium, varied from 0.64 to 1.29. KI values below 1 are generally suitable, while those between 1–2 are considered marginal (Dhanush et al., 2024; Egbueri et al., 2023). In this study, samples S1, S2, S4–S9 were classified as suitable, while samples S3 and S10 had marginal values, indicating potential sodicity concerns under prolonged use.

The Permeability Index (PI), which assesses the cumulative impact of various ions on soil infiltration capacity, ranged between 57.5% and 94.3%, with a mean of 76.5%. According to Doneen’s classification, values above 75% are considered suitable, while values between 25% and 75% suggest moderate suitability [22]. Samples S1–S4, S6, and S8 were categorized as suitable, whereas S5, S7, S9, and S10 exhibited moderate suitability, requiring cautious application and soil monitoring.

Potential Salinity (PS), a metric reflecting the long-term risk of salt accumulation from soluble ions like Cl⁻ and SO₄²⁻, ranged from 1.19 to 17.18 mg/L. Values below 5 are considered excellent to good, 5–10 as injurious, and above 10 as unsatisfactory (Dhanush et al., 2024). Samples S1–S8 were classified as suitable (PS < 5), sample S9 as moderately injurious, and sample S10 as unsatisfactory due to its high salinity hazard, limiting its use to highly salt-tolerant crops or necessitating dilution strategies.

To provide an integrated assessment, the Canadian Water Quality Index (CCME-WQI) for irrigation was calculated using 13 variables: TDS, pH, HCO₃⁻, NH₃–N, SAR, Cl⁻, SO₄²⁻, Na⁺, K⁺, Ca²⁺, Mg²⁺, and EC. Based on CCME methodology and FAO guidelines, samples S1, S2, S5, S6, S7, and S8 achieved WQI scores between 80 and 94 and were classified as ‘Good’ for irrigation. Samples S3, S4, and S9, with scores in the range of 65–79, were considered ‘Fair,’ suggesting moderate limitations. Sample S10, with a WQI score below 44, was classified as ‘Poor,’ indicating that its use in irrigation could have significant agronomic and environmental consequences unless appropriately treated or blended. These results, summarized in Table 10, highlight the need for site-specific irrigation strategies, periodic water quality monitoring, and adaptive soil management practices to ensure long-term agricultural sustainability in arid and semi-arid regions.

Table 10

Table 10. Displays the CCME water quality index of the Fayoum watershed area.

8.4 Industrial water quality evaluation

To determine the suitability of surface water from the Fayoum watershed for industrial applications, particularly for use in cooling systems, boiler feed, and process water, a suite of water stability and corrosion indices was employed. These include the Chloride-Sulfate Mass Ratio (CSMR), Larson–Skold Index (LSI), Langelier Saturation Index (LI), Aggressive Index (AI), Ryznar Stability Index (RSI), and Puckorius Scaling Index (PSI). These indices provide insights into the corrosive or scaling nature of the water, which is critical for industrial infrastructure longevity, energy efficiency, and maintenance costs. The detailed results and corresponding classifications are provided in Tables 11 and 12.

Table 11

Table 11. Presents Industrial water quality indices.

Table 12

Table 12. Displays the classification scheme for industrial water quality indices [22].

The Chloride-Sulfate Mass Ratio (CSMR) serves as a key indicator of galvanic corrosion potential, particularly in systems utilizing dissimilar metals. High chloride concentrations relative to sulfate may induce aggressive localized corrosion on metallic surfaces, especially in copper-based alloys (Dhanush et al., 2024; Egbueri et al., 2023). In this study, CSMR values ranged from 0.024 to 2.08, with a mean of 0.30. While most samples were below the corrosion risk threshold of 0.5, suggesting minimal galvanic activity, Sample 1 exceeded this limit, highlighting a potential risk for galvanic corrosion in multi-metal systems exposed to this water.

The Larson–Skold Index (LSI), which integrates sulfate and chloride concentrations relative to carbonate and bicarbonate alkalinity, is a predictive tool for identifying localized corrosion versus scaling risk (Dhanush et al., 2024). Values below 0.8 typically suggest a scaling tendency, whereas values above 1.2 indicate corrosion potential. In this analysis, LSI ranged from 0.33 to 2.59 (mean = 1.01). Samples 2–8 demonstrated values <0.8, consistent with scaling-prone water, whereas Samples 1, 9, and 10 exceeded 1.2, reflecting increased susceptibility to pitting and localized corrosion—conditions that can compromise industrial pipelines and equipment over time.

The Langelier Index (LI) quantifies the water’s tendency to dissolve or deposit calcium carbonate, providing an indication of its corrosiveness or scaling behavior. LI values in this study spanned from −0.47 to +0.58 (mean = 0.07). Four samples yielded negative LI values, suggesting under-saturation and a corrosive tendency due to excess free CO₂ and reduced buffering capacity (Dhanush et al., 2024). Five samples had LI > 0, indicating potential calcium carbonate precipitation and scaling risk. Notably, Sample 10 recorded a neutral LI value (∼0), indicating equilibrium conditions—a rare but ideal scenario for industrial systems, minimizing both scaling and corrosion.

The Aggressive Index (AI), a broader measure of corrosivity based on pH, alkalinity, and calcium hardness, ranged between 11.36 and 13.83, with a mean of 12.02. Water with AI values <10 is generally considered aggressive, while values between 10 and 12 indicate moderate aggressiveness, and values >12 are deemed non-aggressive with a tendency toward scaling (Dhanush et al., 2024). In this dataset, most samples fell between 11 and 13, with Samples 9 and 10 displaying AI >12, indicating stable, non-corrosive water with a propensity to scale—favorable for certain industrial operations but potentially problematic in heat exchange systems.

The Ryznar Stability Index (RSI), used to predict the long-term scaling or corrosive behavior of water, ranged from 4.60 to 8.51 (mean = 7.13). RSI values <6 indicate high scaling potential, 6–6.8 reflect balanced conditions, and values >6.8 suggest increasing corrosiveness (Dhanush et al., 2024). The majority of samples exhibited RSI values >6.8, denoting a corrosive tendency. Sample 9, however, fell between 6.2 and 6.8, indicating a near-balanced water condition suitable for minimizing both corrosion and scale deposition, while sample 10 has scaling tendency fell in <5.5.

The Puckorius Scaling Index (PSI) evaluates the buffering capacity of water against acidification and its potential to precipitate scale-forming salts, based on the relationship between pH and alkalinity (Dhanush et al., 2024; Egbueri et al., 2023). PSI values ranged from 4.73 to 8.17, with a mean of 6.69. Values <6 suggest a scaling tendency, 6–7 imply slight corrosive or scaling risks, and values >7 indicate aggressive corrosion potential. Samples 9 and 10 recorded PSI <6, pointing to scale formation, while four samples fell within the marginal 6–7 range. The remaining samples had PSI >7, denoting elevated corrosivity concerns, particularly in systems with limited water turnover or temperature fluctuations.

In summary, the industrial water quality analysis reveals heterogeneous chemical stability across the study area. Some locations, such as Samples 9 and 10, exhibit borderline-to-high corrosiveness under specific indices (e.g., RSI, LSI), while others tend toward scale formation (e.g., LI, AI). This duality suggests the need for site-specific water treatment strategies, such as pH adjustment, corrosion inhibitors, or softening, depending on the intended industrial application. Failure to address these characteristics may result in equipment degradation, energy losses, and increased operational costs in facilities relying on untreated surface water. Consequently, continuous monitoring and integration of corrosion control technologies are recommended, particularly in mixed-use industrial sectors common to arid and semi-arid regions like Fayoum.

8.5 Spatial interpolation of WQI

To support spatial assessment and visualization of surface water quality in the Fayoum watershed, Inverse Distance Weighted (IDW) interpolation was applied using ArcGIS software. This geostatistical method enabled the generation of continuous WQI distribution maps based on point measurements at each of the ten sampling sites. The Canadian Council of Ministers of the Environment Water Quality Index (CCME–WQI) was employed for three distinct water uses: drinking, aquatic life support, and irrigation, incorporating 14, 9, and 13 physicochemical parameters, respectively.

The CCME-WQI spatial maps for drinking water quality (Figure 2) revealed that samples S1, S2, and S6 were classified as ‘good’ (CCME-WQI: 80–94), indicating high water quality in those zones. Samples S3, S4, S5, S7, and S8 were categorized as ‘fair’ (CCME-WQI: 65–79), suggesting moderate treatment may be needed prior to use. In contrast, samples S9 and S10 fell within the ‘poor’ category (CCME-WQI: 0–44), reflecting significant health risks and unsuitability for direct consumption.

Figure 2

Figure 2. Illustrates the spatial distribution of the Water Quality Index (WQI) for drinking.

For aquatic life, the spatial interpolation results (Figure 3) illustrated similar patterns. Sites S1, S2, and S6 were identified as marginally supportive of aquatic life. Samples S3, S4, S5, S7, and S8 displayed declining habitat suitability, indicating stress on aquatic organisms. Notably, S9 and S10 were classified as ‘poor’, highlighting potentially toxic conditions that could lead to habitat degradation and biodiversity loss.

Figure 3

Figure 3. Illustrates the spatial distribution of the Water Quality Index (WQI) for aquatic life.

The irrigation water quality CCME-WQI map (Figure 4) indicated that S1, S2, S5, S6, S7, and S8 provided water of ‘good’ quality (WQI: 80–94), suitable for most agricultural purposes. Samples S3, S4, and S9 fell into the ‘fair’ category (WQI: 65–79), indicating water that can be used with some restrictions, depending on crop sensitivity and soil conditions. Sample S10, however, was classified as ‘poor’, requiring either dilution or treatment prior to reuse in agriculture.

Figure 4

Figure 4. Illustrates the spatial distribution of the Water Quality Index (WQI) for irrigation.

These spatially interpolated CCME-WQI datasets were classified into nine color-coded categories to enhance interpretability and aid in resource planning. The resulting maps not only visualize pollutant gradients but also identify critical hotspots of degradation, informing priority interventions.

The synthesis presented in Figure 5 provides a composite overview of multi-use suitability across all sampling sites. Sites S1 and S2 emerged as consistently ‘good’ for both drinking and irrigation purposes, but only marginal for aquatic life, suggesting a chemical profile that meets human and agronomic standards yet may stress aquatic ecosystems. Samples S3 and S4 showed ‘fair’ suitability for both drinking and irrigation but failed to meet ecological thresholds. Sites S5, S6, S7, and S8 demonstrated adequate quality for irrigation, with S6 also supporting drinking use. However, aquatic habitat conditions in these sites varied, with samples S5, S6, and S8 being marginal, and S7 classified as poor. Sites S9 and S10 consistently ranked as the most degraded, unsuitable for all three water uses, except that sample S9 retained marginal value for irrigation.

Figure 5

Figure 5. WQI of samples for drinking, irrigation, and aquatic life.

In summary, the spatial interpolation of CCME–WQI values offers a valuable framework for water resource management, environmental protection, and agricultural planning in semi-arid regions. By identifying localized pollution patterns and mapping areas of concern, these WQI maps serve as practical decision-support tools for policymakers, water authorities, and land-use planners aiming to implement targeted remediation and sustainable reuse strategies.

Clear spatial contrasts emerged between drains dominated by agricultural return flows and those influenced by industrial or municipal discharges. Agricultural sites (e.g., S1, S2, S4, S5, S8, S10) were characterized by elevated phosphate and ammonia concentrations, consistent with fertilizer runoff and agro-domestic drainage. Such conditions heighten the risks of eutrophication, oxygen depletion, and algal blooms, ultimately undermining aquatic ecosystem health and limiting the long-term potential for water reuse (M. M. Abu-Ghamja et al., 2018). In contrast, sites impacted by industrial activities or wastewater treatment plant (WWTP) discharges (e.g., S3, S6, S7, S9) exhibited higher electrical conductivity (EC) and total dissolved solids (TDS), indicative of salinity enrichment from industrial effluents and concentrated wastewater. Elevated salinity reduces irrigation suitability by increasing sodicity hazards and can accelerate scaling and corrosion in distribution infrastructure (Hossain et al., 2018).

At mixed hotspots (most notably S3), the convergence of untreated sewage with intensive agricultural drainage produced the highest nutrient and chemical oxygen demand (COD) loads. This reinforces the compounded impacts of domestic, industrial, and agro-industrial activities. Together, these site-specific patterns highlight the need for source-tailored management strategies: minimizing fertilizer misapplication and return-flow contamination in agricultural zones, while strengthening effluent treatment and regulatory enforcement for industrial and municipal discharges before they reach Lake Qarun (Elsayed et al., 2021; Al-Afify et al., 2019).

The spatial also align with previously reported health concerns in the Fayoum basin. Agricultural drains enriched in phosphate and ammonia promotes eutrophication and microbial proliferation, elevating the risk of waterborne illness when untreated water is reused for irrigation or domestic purposes (Fouad et al., 2024). By contrast, drains affected by industrial discharges and WWTP effluents exhibit higher salinity and potential metal contamination, consistent with earlier evidence of heavy-metal bioaccumulation in Lake Qarun fish and the associated human health risks (Omar et al., 2013; El-Sherif et al., 2025). Seasonal monitoring of the El-Batts drain has further shown that poor-quality irrigation water adversely impacts both human communities and local ecosystems (Mansour et al., 2024). Although a formal health-risk assessment was beyond the scope of this study, the integrated WQI–GIS approach provides a decision-support tool to identify and prioritize areas most likely to intersect with these established human-exposure pathways.

9 Conclusion

This study provides a comprehensive evaluation of surface water quality in the Fayoum Governorate, Egypt, using Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) and GIS-based spatial analysis during the summer of 2024. The analysis of ten strategically selected sites revealed marked spatial variability reflecting both agricultural and industrial/municipal influences. For drinking purposes, 30% of samples (S1, S2, S6) were classified as good (WQI 80–94), 50% as fair (65–79), and 20% (S9, S10) as poor (WQI <45), confirming limited suitability without advanced treatment. Exceedances in key parameters—including total dissolved solids (up to 3,420 mg/L), electrical conductivity (6,840 μS/cm), turbidity (105 NTU), and phosphate (10.85 mg/L)—highlight significant risks to public health.

Irrigation water quality was rated good in 60% of sites; however, salinity and sodicity hazards were evident, with sodium percentage exceeding 57.8% at several locations, magnesium hazard above 50% in 40% of sites, and potential salinity values indicating long-term soil permeability and crop productivity concerns. While SAR values remained below 10, cumulative ionic loads warrant careful management. Industrial assessments showed that 50% of samples exhibited scaling potential (Langelier Index >0), while high RSI values (>8.5) indicated corrosion risks in multiple locations. For aquatic life, 50% of sites recorded poor WQI scores (<45), pointing to severe ecological stress, particularly in downstream reaches discharging to Lake Qarun. IDW-based spatial mapping identified S9 and S10 as pollution hotspots, reflecting untreated sewage inputs and intensive agricultural runoff.

The results clearly demonstrate that agricultural drains are dominated by nutrient enrichment (PO₄³⁻ and NH₃), driving eutrophication, while industrial and WWTP-influenced reaches show elevated salinity and chemically complex effluents, together intensifying cumulative stress. These contrasts emphasize the need for source-specific interventions. To safeguard water quality in the Fayoum basin, effective treatment and reuse of municipal and industrial effluents before discharge, adoption of improved agricultural practices including optimized fertilizer use and drainage management, implementation of routine monitoring with stricter enforcement of national and international standards, and strengthening public awareness and community engagement in pollution-prevention efforts are strongly recommended.

Although comprehensive, the present study is limited by its seasonal scope (summer survey only) and absence of microbiological and heavy-metal analyses. Future work should address multi-seasonal monitoring and expanded contaminant profiles to build a more complete risk assessment. Overall, the integrated CCME-WQI/GIS framework proved effective for identifying hotspots, guiding targeted management actions, and supporting Egypt’s national water strategy as well as progress toward Sustainable Development Goal 6 (Clean Water and Sanitation).

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author contributions

MR: Visualization, Investigation, Resources, Software, Validation, Conceptualization, Funding acquisition, Writing – review and editing, Formal Analysis, Supervision, Methodology, Writing – original draft, Project administration, Data curation. AME-S: Writing – review and editing, Methodology, Writing – original draft, Investigation, Funding acquisition, Resources, Validation, Project administration. HA: Writing – original draft, Data curation, Resources, Investigation, Methodology, Writing – review and editing, Project administration. AA: Writing – review and editing, Writing – original draft, Validation, Investigation, Supervision. MA: Writing – review and editing, Methodology, Software, Supervision, Funding acquisition, Investigation, Writing – original draft, Conceptualization, Formal Analysis, Resources, Visualization, Data curation, Project administration, Validation. WA: Validation, Writing – review and editing, Methodology, Software, Writing – original draft. MW: Funding acquisition, Project administration, Formal Analysis, Writing – review and editing, Validation, Resources, Supervision, Methodology, Writing – original draft, Data curation, Conceptualization, Software, Investigation, Visualization.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. The authors extend their appreciation to King Saud University for funding this work through the Ongoing Research Funding program, (ORF-2025-133), King Saud University, Riyadh, Saudi Arabia. The authors acknowledge Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP 2025R458), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer MME declared a shared affiliation with the authors MGR, MRA, MSMAW to the handling editor at time of review.

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The author(s) declare that no Generative AI was used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fenvs.2025.1649938/full#supplementary-material

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