Seasonal Variations and Assessment of Surface Water Quality Using Water Quality Index (WQI) and Principal Component Analysis (PCA): A Case Study

Abstract

In recent decades, water pollution has become a major concern, threatening both humans and natural ecosystems. This study aims to analyze seasonal variations in the quality of surface water of the Nador Canal in Morocco, using the water quality index (WQI) and principal component analysis (PCA). Surface water samples from 22 sites along the canal were analyzed for physical, chemical, and heavy metal parameters. The results of the study revealed significant seasonal variations, with water quality decreasing in the summer months, while its quality generally improved in winter. The predominant water type was Na⁺-Cl⁻ in summer, while it was the mixed Ca²⁺-Na⁺-HCO₃⁻ water type in winter. WQI values also varied seasonally, with an average of 113.04 in summer and 160.6 in winter, classifying the water as unsuitable for drinking but suitable for irrigation throughout the year. The results of the water quality index are consistent with the results of the principal component analysis of surface water in the Nador Canal, where the results of the principal component analysis showed that there are significant seasonal variations in water quality. In both summer and winter, major ions like magnesium, sodium, and calcium predominantly indicate influences from natural and anthropogenic sources. In winter, heavy metals and nutrients, signaling pollution from industrial and agricultural runoff, become especially prominent. These variations are influenced by rainfall patterns and agricultural runoff, emphasizing the need for adaptive water management practices to maintain crop and soil health. This study provides new insights into the dynamic interplay between seasonal factors and water quality, offering valuable guidance for local water resource management.

1. Introduction

Maintaining high standards of surface water quality is crucial across the globe, given its direct connection to the provision of potable water and the far-reaching consequences it has on both human health and ecological systems. Surface waters, which include rivers, lakes, and streams, are often a primary resource for the drinking water supplies of numerous communities. The integrity of these water sources is essential, as any pollutant or diminishment in quality can lead to serious health hazards for the population and can also have a detrimental impact on the balance of local ecosystems [1].

When surface water quality is compromised, the repercussions are multifaceted. For humans, the ingestion of or exposure to contaminated water can lead to waterborne diseases and can also affect community health indirectly through the food chain. For the environment, poor water quality can impair aquatic habitats, reduce biodiversity, and disrupt the natural functions of ecosystems, which can have cascading effects on food security and biodiversity [2].

Surface water, which includes rivers, lakes, and streams, is inherently vulnerable to changes and contamination. Even slight deviations from quality standards can lead to severe repercussions. Contaminated surface water often translates into compromised drinking water quality, which can pose a threat to public health by spreading waterborne diseases and can disrupt delicate ecosystems, adversely affecting both aquatic species and broader ecological dynamics [3,4]. Human-induced pollution substantially compromises surface water quality, reducing its suitability for essential uses such as industrial operations, agriculture, and recreational activities. Industrial effluents and agricultural runoff are prime contributors to the contamination of these waters, leading to their unsuitability for industrial use and irrigation. This contamination can impede industrial productivity and agricultural yield. Moreover, recreational pursuits like swimming and boating can become hazardous in polluted waters, posing health risks to the public. The detriments of water pollution extend beyond immediate health risks; they can also cause long-term ecological damage, disrupting aquatic ecosystems and reducing biodiversity. Contaminated water can affect fish and wildlife populations, alter their habitats, and impede natural water purification processes [5,6,7]. Agricultural activities significantly pollute water bodies with organic matter, nutrients, pesticides, and heavy metals. Runoff leads to eutrophication and contamination, while pesticides and heavy metals pose risks to aquatic life and human health. These pollutants cause chronic toxicity and environmental issues [8].

The water quality index (WQI) is a vital metric that condenses complex water quality data into a single number, providing an easy-to-understand assessment of water’s suitability for uses like irrigation. It does so by integrating multiple water quality parameters such as pH, salinity, and nutrients, each weighted by its importance, to determine overall water quality. These parameters are compared to standard values, and the WQI is calculated through a formula that reflects the cumulative impact of these factors. A high WQI indicates water that is generally safe for irrigation, while a low WQI suggests potential problems due to contaminants that could harm crops or soil. Thus, the WQI is an essential tool for farmers, water managers, and policymakers to make informed decisions about water resource management and to ensure the long-term viability of agricultural practices [8,9,10,11,12,13,14].

Water resources in Morocco are under increasing pressure due to human activities, predominantly agricultural practices involving the extensive use of fertilizers and pesticides. These chemicals, critical for crop production, also pose significant risks by contaminating water sources through soil infiltration. This contamination impacts the quality and safety of water used for drinking, irrigation, and other purposes. The study by Malki et al. (2017) investigated the impact of intensive agricultural activities on groundwater quality, revealing elevated nitrate levels attributed to heavy fertilizer use. Notably, the adoption of drip irrigation helped mitigate some of these negative effects by lowering water demand and reducing pollutant concentrations in parts of the area [15].

The study by Sehlaoui et al. (2020) [16], assessed groundwater suitability for irrigation, noting significant salinity issues likely exacerbated by agricultural runoff and poor management practices. The findings suggest that much of the groundwater is unsuitable for irrigation without treatment. The study by Fetouani et al. (2008) reported that the Triffa Plain is experiencing water quality degradation due to overexploitation and pollution from agricultural activities [17]. High levels of nitrates and bacteriological contaminants were found across the area, pointing to the urgent need for improved agricultural and water management practices.

The research by Mrabet et al. (2012) [18], discussed the effects of conventional agricultural practices on soil degradation and water quality. It emphasized the benefits of no-tillage and conservation agriculture practices in improving water infiltration and reducing runoff, thus helping to preserve water quality. These findings underscore the significant impact of agricultural practices on Morocco’s water resources. The Nador Canal, located in the Western Plain of northwestern Morocco, faces major environmental challenges due to the impact of agricultural waste and other pollutants. Research on water quality in this region and similar regions in Morocco provides valuable insights into the sources of pollution and the resulting risks to ecosystems and human health. In Lake Nador, adjacent to the Nador Canal, water quality is greatly altered by local fecal water, liquid waste, urban discharges, and waste from agricultural activities. Geochemical analyses indicate the presence of high concentrations of metals near pollution sources [19]. The Nador Canal itself shows moderate to very poor physicochemical performance. Water quality impacted by agricultural pollutants affects local fishery resources [20]. Studies on the Nador Canal have consistently demonstrated the adverse effects of agricultural waste and other pollutants on the water quality of the canal and its surrounding areas. This underscores the importance of conducting regular environmental assessments to monitor and mitigate these impacts effectively [15]. This study aims to evaluate seasonal variations in the surface water quality of the Nador Canal, Morocco, using the water quality index (WQI) and principal component analysis (PCA). This evaluation will help identify key factors influencing water quality changes throughout the year and aid in developing targeted strategies for water management and pollution control.

2. Materials and Methods

2.1. Study Area Location

The Nador Canal is located at the northwestern end of Sahel al-Gharb, just south of Moulay Bousselham in Morocco (Figure 1). It is 70 km north of Kenitra, extending to Sidi Allal al-Tazi in the Kenitra province [21,22].The average annual rainfall in the study area ranges from 250 mm to 400 mm, with an average of 330 mm. Rain falls the most during the seven months from October to April, while the dry period extends from May to September, and average temperatures range from 21 °C to 27 °C [23]. The study area, located in the Rharb Basin in Morocco, situated between the Meseta and Rif regions, exhibits complex geological characteristics shaped by significant tectonic and climatic influences. The basin’s Plio-Quaternary deposits reveal a complex interplay of tectonics and climate, with marine sediments like marl and sand shaped during the tertiary period [24]. Major faults, particularly the Kenitra–Sidi–Slimane fault, have significantly influenced the basin’s geological evolution from the Cretaceous to Neogene periods [25]. Far-field stresses related to Eurasian–African plate convergence have impacted sedimentary patterns, particularly during the Plio-Quaternary periods [26].

2.2. Water Sample Collection

Forty-four surface water samples were collected from 22 different stations during the summer of 2022 and the winter of 2023. Samples were taken from the channel, and necessary measurements were made, and water samples were immediately filtered through a 0.45 μm filter. Samples were collected at a depth of 50 cm according to standard methods [27], with bottles cleaned and rinsed to prevent contamination. Samples were stored at 4 °C during transport to the laboratory.

2.3. Physicochemical and Heavy Metal Analysis

The physicochemical parameters of water samples were examined according to WHO guidelines [28]. The pH was measured using a WTW Inolab pH meter, and (EC) with a Thermo ORION 3 STAR meter. (Mg²⁺) and (Ca²⁺) levels were determined by EDTA titration. (K⁺) and (Na⁺) were measured using a JENWAY PFP7 flame photometer. (Cl⁻) was assessed via titration with silver nitrate and potassium chromate, while (SO₄²⁻) was measured using a V-1100 spectrophotometer. (NH₄⁺) and (NO₃⁻) were determined by distillation with magnesium oxide and DEVA GDR alloy, followed by titration with H₂SO₄. Heavy metals (Cu, Fe, Mn, Zn, Pb, and Cd) were analyzed using the direct flame method, and AAS readings were plotted on a standard curve. Surface water samples were collected and tested using established standard procedures [29].

2.4. Water Quality Index

The water quality index (WQI) was proposed by Horton for evaluating drinking water quality; the WQI concept has been widely applied to various water quality assessments, as shown in studies by Brown et al. and using an alternative method described by Pesce and Wunderlin [30,31].

The WQI for the Nador Canal was established through chemical assessments, involving parameters like pH, (EC), (HCO₃⁻), (DO), (K⁺), (Na⁺), (Cl⁻), (SO₄²⁻), (Mg²⁺), (Ca²⁺), (NO₃⁻), and heavy metals (Cu, Fe, Mn, Zn, Pb, & Cd) (

Table 1. Relative weight (RW) of each parameter.

Parameters	Drinking			Irrigation
	WHO Standards (2011) [32]	Weight (wi)	Relative Weight (wi)	WHO Standards (Ayers and Westcot 1985) [33]	Weight (wi)	Relative Weight (wi)
pH	8	3	0.059	8.5	4	0.066
Electrical conductivity	750	5	0.098	2500	5	0.082
Dissolved oxygen (mg/L)	5	4	0.078	5	5	0.082
Calcium (mg/L)	75	2	0.039	200	5	0.082
Magnesium (mg/L)	50	2	0.039	100	5	0.082
Sodium (mg/L)	200	3	0.059	200	5	0.082
Potassium (mg/L)	12	3	0.059	10	3	0.049
Amomum (mg/L)	0.1	3	0.059	35	3	0.049
Chloride (mg/L)	200	4	0.078	350	5	0.082
Sulphate (mg/L)	100	4	0.078	250	5	0.082
Bicarbonate (mg/L)	300	1	0.020	400	2	0.033
Nitrate (mg/L)	50	5	0.098	5	3	0.049
Phosphate (mg/L)	0.1	3	0.059	50	2	0.033
Copper (mg/L)	1.00	1.00	0.020	1.00	1	0.016
Iron (mg/L)	0.50	3.00	0.059	0.50	3	0.049
Manganese (mg/L)	5.00	1.00	0.020	5.00	1	0.016
Zinc (mg/L)	1.00	2.00	0.039	1.00	2	0.033
Lead (mg/L)	5.00	1.00	0.020	50.00	1	0.016
Cadmium (mg/L)	5	1.00	0.020	5	1	0.016

).

The WQI calculation involves four steps [31]:

• The relative weight (Wi) is computed as

  Wi = Σ(wi)/n

  (1)
• Quality rating scale (qi):

  qi = (Ci/Si) × 100

  (2)
• Sub-quality index (SIi):

  SIi = Wi × qi

  (3)
• Overall WQI:

  WQI = Σ(SIi)

  (4)

This series of Equations (1)–(4) provides a determination of the water quality index.

2.5. Statistical Analysis

Statistical analysis was conducted using Minitab 2020, and spatial data analysis was performed using ArcGIS 10.8 with Inverse Distance Weighting (IDW). Principal component analysis (PCA) was used to identify correlations among surface water, sediment pore water, and combined water parameters across various sampling sites [34]. Correlation analysis, utilizing the simple correlation coefficient, was employed to evaluate the relationships between variables, helping to quantify the predictive ability and extent of association between them [35].

3. Results and Discussion

3.1. Physicochemical Characteristics

Table 2. Statistical summary of Nador Canal water parameters in summer and winter.

Variable	Summer			Winter
	Minimum	Maximum	Mean	Minimum	Maximum	Mean
T (°C)	27	39	29.916	17.6	25.6	19.764
pH	7.79	8.72	8.0995	7.75	8.43	7.9623
EC	960	2720	1850	860	2235	1434
DO	1	2.82	1.9	4.2	9.6	5.7
Ca2+	50.78	111.77	79.55	74.97	164.2	117.88
Mg2+	21.1	45.1	34.66	34.61	72.96	56.95
Na+	122	343.9	239.6	107.7	290.2	202.8
K2+	3.1	5.79	4.125	8.68	16.212	11.551
HCO3−	94.7	531.2	287.6	92.9	512.6	320.7
Cl−	184.3	907.6	537.6	114.6	542.5	321.9
SO42−	68.18	133.65	102.9	176.78	305.2	243.61
PO43−	0.01	1.97	0.1355	0.36	3.87	0.804
NO3−	0.27	37.9	5.04	1	92	14.25
NH4+	0.23	0.23	0.2955	0.1	0.23	0.14364
Cu	0.01	0.02	0.02	0.10	0.50	0.19
Fe	0.04	0.21	0.12	0.14	0.29	0.22
Mn	0.02	0.04	0.02	0.04	0.06	0.05
Zn	0.01	0.02	0.01	0.01	0.01	0.01
Pb	6.66	16.56	10.49	10.45	22.75	15.19
Cd	2.25	28.6	11.49	10.45	22.75	15.19

represents a statistical summary of the analysis results of the physical, chemical, and heavy metal properties of the Nador Canal water and its comparison with Moroccan standards (http://www.environnement.gov.ma/PDFs/grille_de_qualite_des_eaux_de_surface.pdf, accessed on 25 June 2024).

The temperatures in the Nador Canal varied seasonally. In summer, they spanned from 27 °C to 39 °C, averaging around 29.92 °C, just below the Moroccan standard of 30 °C. However, the temperatures in winter varied from 17.6 °C to 25.6 °C, with an average temperature of approximately 19.76 °C (Figure 2a). The temperatures in summer were significantly higher, approaching the maximum standard (<30 °C). This could affect aquatic life during the summer due to higher metabolic rates and lower oxygen solubility. However, in winter, temperatures were well within the norm, indicating a cooler environment that is likely more conducive to aquatic life. Water temperature significantly enhances chemical activity, bacterial activity, and water evaporation [36,37]. The pH values in the Nador Canal varied from 7.79 to 8.72, with an average of 8.09 in summer, and from 7.75 to 8.43, with a mean of 7.9623 in winter (Figure 2b). The pH values for both seasons fell within the Moroccan standard of 6.5 to 8.5. The measured pH values for the Nador Canal waters categorize them as excellent to good according to surface water quality standards, suggesting that in most sampling stations, the water is suitable for irrigation, with a pH falling within the range of 6.5 to 8.5, according to Moroccan water quality standards. Yet, it is worth noting that one station appeared to be moderately polluted. The pH level has a significant impact on water quality, indicating whether the water is acidic or alkaline (basic). It also represents water’s neutrality and is a critical parameter for both drinking and irrigation purposes. Moreover, pH influences the solubility of minerals in water, as well as factors such as alkalinity and water hardness [36,38]. Dissolved oxygen (DO) levels varied from 1 to 2.82 mg/L in summer and increased to 4.2 to 9.6 mg/L in winter, both under the Moroccan norm of 5 mg/L (Figure 3a). All samples showed low levels of dissolved oxygen across all locations in the Nador Canal, indicating pollution, during the summer, while in winter, higher DO levels were measured, with the maximum exceeding the standard, suggesting better water quality during this season [39]. Electrical conductivity (EC) values in summer (S) ranged between 960 and 2720 μS/cm, which is close to the Moroccan standard of 2700 μS/cm. In winter (W), it was lower, ranging from 860 to 2235 µS/cm. The conductivity in summer exceeded the Moroccan standard of 2700 µS/cm (Figure 3b). However, there was a noticeable increase in the content of ions associated with pollutants such as agricultural residues and sewage effluents. It is noteworthy that water samples showed a wide range of variations in electrical conductivity values [40].

Bicarbonate (HCO₃⁻) levels ranged from 94.7 to 531.2 mg/L in the summer and 92.9 to 512.6 mg/L in the winter. Compared to the Moroccan standard of 400 mg/L, five stations in summer were above the Moroccan standard and ten stations in winter were above the Moroccan standard, and the stations were at the end of the Nador Canal (Figure 4a). Elevated bicarbonate levels in the Nador Canal can stem from agricultural runoff, industrial effluents, domestic wastewater, natural geological sources, evaporation, seasonal variations, urbanization, and algal blooms [41]. Sulfate (SO₄²⁻) concentrations ranged from 68.18 to 133.65 mg/L in summer and increased to 176.78 to 305.2 mg/L in winter. Most samples in both seasons were below the standard level of 250 mg/L (Figure 4b). Sulfate sources included organic matter breakdown, fertilizers, and microbial oxidation [42,43]. Sulfate is a nonmetallic element naturally found in soils and rocks in both organic and mineral forms [44]. Chloride (Cl⁻) concentrations ranged from 184.3 to 907.6 mg/L in summer and from 114.6 to 542.5 mg/L in winter (Figure 4c). The high chloride levels in summer suggest contamination from various sources, while winter levels were significantly lower. The elevated chloride concentration in the Nador Canal is attributed to discharges from human activities, agricultural waste, and excessive fertilizer use. Nitrate (NO₃⁻) concentrations ranged from 0.28 to 37.09 mg/L in summer and from 1 to 92 mg/L in winter (Figure 4d). High nitrate levels at the Nador Canal’s end indicate agricultural and human waste accumulation from improper disposal and fertilizers [45].

Calcium (Ca²⁺) concentrations in summer were 50.78 to 111.77 mg/L, and in winter, they were higher, at 74.97 to 164.2 mg/L (Figure 5a). Calcium levels in summer exceeded the Moroccan standard limit of 100 mg/L at only two stations, while calcium levels exceeded most stations in winter, which may indicate natural mineral leaching or anthropogenic effects. Magnesium concentrations ranged from 21.1 to 45.1 mg/L in summer and from 34.61 to 72.96 mg/L(Figure 5b). in winter, which can be compared to the normal range of 50 mg/L. Values in both seasons exceeded the Moroccan standard, especially in winter, which may contribute to the overall hardness of the water. The concentrations of sodium (Na⁺) ranged from 122 to 343.9 mg/L in summer and 107.7 to 290.2 mg/L(Figure 5c). in winter. Summer maximum concentrations were higher than winter levels but within the Moroccan standard of 150 mg/L. Mean concentrations in both seasons exceeded the standard. Sodium sources include geological weathering, agricultural runoff, industrial discharges, and wastewater effluents. The concentration of potassium (K⁺) in water samples was 3.1 to 5.79 in summer and 8.68 to 16.212 mg/L in winter (Figure 5d). Potassium levels were well within the norm in summer but were substantially higher in winter, with mean levels almost reaching the standard. This could be influenced by seasonal agricultural runoff or other inputs [38]. The concentrations of ammonia ranged from 0.32 to 0.62 mg/L in summer and 0.1 to 0.23 mg/L in winter (Figure 5e). According to Moroccan standards, all samples were within the permissible range [40]. The concentration of phosphate (PO₄³⁻) was from 0.02 to 1.97 mg/l in summer and 0.36 to 3.87 mg/L in winter (Figure 5f). Phosphate concentrations in both seasons were below the norm, with winter having higher levels, potentially from runoff or wastewater.

Table 2 shows the concentrations of heavy metals in the water of the Nador Canal across two different seasons, summer and winter. In the summertime, the concentration of copper in the water was quite stable, oscillating between 0.01 and 0.02, and averaging out at 0.02. Come winter, however, there was a noticeable broadening in the range of copper concentrations, which stretched from 0.10 to 0.50, with the average increasing to 0.19. This highlights a more pronounced variability in copper levels compared to the summer season (Figure 6a). During summer months, iron levels in the water spanned from a minimum of 0.04 to a maximum of 0.21, with an average concentration of 0.12. In the winter, however, the variability in iron concentrations was more pronounced, with values extending from 0.14 to 0.29 and an increased average value of 0.22. This suggests a tighter clustering of values around the mean compared to the summer, despite the overall higher winter concentrations (Figure 6b). Throughout the summer, manganese concentrations hovered between 0.02 and 0.04, with an average resting at 0.02, displaying minimal variation, as evidenced by a standard deviation of 0.01. When winter arrived, the manganese levels experienced a slight increase, with a range from 0.04 to 0.06 and a median value of 0.05 (Figure 6c). In summer and winter, zinc statistics were the same in both seasons and ranged from 0.01 to 0.02, with a constant average of 0.01 (Figure 6d). The concentration of lead ranged from a minimum of 6.66 to a maximum of 16.56, with an average (mean) of 10.49. In the winter, the lead concentration ranged from a higher minimum of 10.45 to a maximum of 22.75, with an increased average of 15.19, indicating a greater spread of values around the mean than in the summer. This means that the lead concentrations were not only higher on average but also more varied in winter than in summer (Figure 6e). Cadmium levels in the summer were between 2.25 and 28.60, with a mean of 11.49. The coefficient of variation for cadmium is quite high at 14.83, indicating significant variability in its concentrations during the summer months. The winter data showed an increased minimum level of cadmium at 10.45, a maximum of 22.75, and a mean value that matches the mean for lead at 15.19. The standard deviation is the same as for lead, at 6.62, suggesting a similarly wide range of values around the mean for cadmium in the winter (Figure 6f). The comparison makes it clear that the concentrations and fluctuations of these minerals and elements in the water of the Nador Canal change between summer and winter. It is worth noting that the levels of copper, iron, and lead were higher on average in winter, with varying degrees of increased variation. Cadmium showed particularly high variability in both seasons but to largely different extents. It is important to note that for some variables, such as boron and lead, there are potential inconsistencies or errors in the presentation of data for the winter season.

3.2. Hadrochemical Analysis of Surface Water Types

The Piper diagram was utilized to elucidate and classify different water groups based on their hydrogeochemical characteristics. Figure 7 displays the uneven distribution of major ions, depicted in the Piper diagram (plotted with version 18). This diagram represents the principal cations and anions that significantly contribute to the composition of surface water. It consists of two triangles at the base and one diamond shape at the top, and categorizes surface water into six distinct types: the Na⁺-Cl⁻ type, Ca²⁺-HCO₃⁻ type, mixed Ca²⁺-Na⁺-HCO₃⁻ type, mixed Ca²⁺-Mg²⁺-Cl⁻ type, Ca²⁺-Cl⁻ type, and Na⁺-HCO₃⁻ type. A thorough analysis of the Piper diagram reveals that all the samples are categorized as the Na⁺-Cl⁻ type in summer, and in winter, all the samples are categorized as the mixed Ca²⁺-Na⁺-HCO₃⁻ type (Figure 7a,b). The research was conducted in the summer, and based on the results, it is not clear that the primary processes affecting the surface water environment were rock weathering and precipitation. The hydrochemistry of the samples under investigation indicates that the calcite (alkaline earth) content exceeds that of alkali metals, and the weak acid content surpasses strong acidic anions. Among the major cations, calcium (Ca²⁺) was more abundant than sodium (Na⁺), while in terms of anions, chloride (Cl⁻) predominated over sulfate (SO₄²⁻). Consequently, it can be inferred that the surface water in this study has been affected by natural factors, resulting in pollution. A similar study in the Marga Zarga region has identified a trend in which alkaline earth elements outnumbered alkaline minerals, and there was a greater presence of weak acids compared to strong acids in the water.

3.3. Multivariate Statistical Analysis

3.3.1. Correlation

Table 3. Pearson correlations between parameters in surface water of Nador Canal in summer.

	T (°C)	pH	EC	DO	Ca2+	Mg2+	Na+	K+	NH4+	Cl−	SO42−	PO43−	HCO3−	NO3−	Cu	Fe	Mn	Zn	Pb	Cd
T (°C)	1.00
pH	0.15	1.00
EC	−0.42	0.15	1
DO	−0.40	0.07	−0.19	1
Ca2+	−0.37	0.26	0.97	−0.09	1
Mg2+	−0.43	0.07	0.98	−0.27	0.92	1
Na+	−0.43	0.19	0.99	−0.20	0.96	0.98	1
K+	−0.31	0.11	0.79	−0.22	0.74	0.77	0.79	1
NH4+	−0.18	−0.37	0.28	−0.48	0.08	0.39	0.28	0.50	1
Cl−	−0.40	0.22	0.99	−0.16	0.97	0.96	0.99	0.81	0.25	1
SO42−	−0.31	0.22	0.84	−0.20	0.79	0.84	0.81	0.76	0.38	0.81	1
PO43−	0.66	0.08	−0.34	−0.25	−0.33	−0.36	−0.35	−0.12	−0.02	−0.27	−0.32	1
HCO3−	−0.37	0.25	0.98	−0.15	0.97	0.95	0.97	0.83	0.26	0.99	0.85	−0.23	1
NO3−	−0.12	0.11	0.24	0.04	0.26	0.23	0.26	0.24	−0.08	0.21	0.18	0.02	0.23	1
Cu	−0.31	0.20	0.83	−0.33	0.80	0.86	0.84	0.67	0.27	0.81	0.84	−0.29	0.82	0.24	1
Fe	0.24	0.02	−0.21	−0.25	−0.22	−0.12	−0.20	−0.33	−0.03	−0.24	−0.06	−0.14	−0.25	−0.08	0.00	1
Mn	0.04	0.53	−0.08	0.23	−0.03	−0.12	−0.06	−0.15	−0.21	−0.05	0.00	0.18	−0.02	0.35	−0.06	−0.02	1
Zn	−0.11	−0.31	−0.09	−0.21	−0.15	−0.01	−0.05	−0.01	0.20	−0.11	−0.02	−0.07	−0.13	−0.09	0.24	0.51	−0.25	1
Pb	0.22	−0.21	0.04	−0.67	−0.10	0.14	0.04	0.14	0.46	0.03	0.11	0.35	0.04	−0.11	0.24	0.38	−0.34	0.46	1
Cd	0.24	−0.26	−0.05	−0.65	−0.19	0.05	−0.05	0.07	0.45	−0.06	0.03	0.36	−0.05	−0.14	0.15	0.39	−0.36	0.46	0.99	1.00

displays correlation coefficients between various parameters in the surface water of the Nador Canal in summer.

Temperature (T) and electrical conductivity (EC) show a negative correlation (−0.42), indicating that as the temperature increases, conductivity might slightly decrease, or vice versa. pH and calcium (Ca²⁺) and magnesium (Mg²⁺) show high positive correlations (0.97 and 0.98, respectively), suggesting that as pH increases, the concentrations of these ions tend to increase. This could be linked to the solubility of compounds containing these ions. Sodium (Na⁺), chloride (Cl⁻), and bicarbonate (HCO₃⁻) show very high correlations with each other (0.99 and 0.97), indicating that these ions often increase together, likely due to common sources or similar behaviors in water. Dissolved oxygen (DO) and pH show a slight correlation with pH (0.07); pH influences the speciation and solubility of inorganic ions such as bicarbonates and carbonates. For instance, studies have demonstrated that changes in pH levels can significantly affect the concentration and behavior of these ions in aquatic environments [8]. Ammonium (NH4⁺) and other parameters show varied correlations with other nutrients and ions, such as a moderate correlation with potassium (K⁺) (0.50), which could indicate shared sources or biochemical interactions. Phosphate (PO₄³⁻) and other parameters, interestingly, have a positive strong correlation with temperature (0.66), indicating that higher temperatures might increase phosphate levels, perhaps due to the reduced solubility of precipitates. Nitrate (NO₃⁻) shows positive but modest correlations with other ions like calcium (0.26) and magnesium (0.23), which may not indicate strong dependencies but suggest some common factors affecting their presence in water. Copper shows strong positive correlations with sodium (Na⁺) (0.86), sulfate (SO₄²⁻) (0.81), and chloride (Cl⁻) (0.81). These correlations may indicate that copper’s presence is associated with other dissolved ions, potentially due to sources such as discharges and urban runoff.

Iron has little to no correlation with many parameters, indicating that it may be influenced by different environmental factors or processes. It does show a slight negative relationship with dissolved oxygen (DO) (−0.25), which could suggest that lower oxygen levels might be associated with higher iron concentrations, possibly due to reduced oxidation. Manganese shows a significant positive correlation with pH (0.53), suggesting that as pH increases, manganese levels might also increase. This could be related to the chemistry of manganese, which becomes more soluble in water at higher pH levels. Zinc’s correlations are generally low with most parameters, indicating it might not be heavily influenced by the factors that affect other ions. It has a moderate correlation with iron (Fe) (0.51), possibly indicating common sources or similar geochemical behaviors.

Lead and cadmium show a very strong correlation with each other (0.99), which is a clear indication that they might come from similar sources or be affected by similar transport and deposition processes in the environment. Lead shows a very strong negative correlation with DO (−0.67), which might suggest that reduced oxygen conditions enhance the mobility or solubility of lead in the water.

Cadmium also shows a strong negative correlation with temperature, specifically with measures of conductivity at 25 °C (−0.65), which could be linked to temperature-dependent solubility or precipitation dynamics. High correlations between heavy metals and certain water parameters might also indicate pollution sources that need to be controlled to improve water quality.

Table 4. Pearson correlations between parameters in surface water of Nador Canal in winter.

	T (°C)	pH	EC	DO	Ca2+	Mg2+	Na+	K+	NH4+	Cl−	SO42−	PO43−	HCO3−	NO3−	Cu	Fe	Mn	Zn	Pb	Cd
T (°C)	1.00
pH	0.13	1.00
EC	−0.62	0.27	1.00
DO	0.40	0.02	−0.51	1.00
Ca2+	−0.70	0.08	0.93	−0.56	1.00
Mg2+	−0.75	−0.10	0.83	−0.59	0.93	1.00
Na+	−0.70	0.06	0.90	−0.55	0.96	0.98	1.00
K+	−0.46	0.10	0.73	−0.69	0.74	0.81	0.81	1.00
NH4+	−0.40	−0.46	0.01	−0.49	0.10	0.38	0.27	0.39	1.00
Cl−	−0.67	0.10	0.95	−0.54	0.96	0.94	0.98	0.83	0.19	1.00
SO42−	−0.74	0.12	0.83	−0.68	0.92	0.89	0.88	0.77	0.23	0.88	1.00
PO43−	0.83	0.13	−0.35	−0.07	−0.40	−0.43	−0.41	−0.02	−0.16	−0.36	−0.37	1.00
HCO3−	−0.69	0.11	0.90	−0.58	0.98	0.91	0.92	0.69	0.08	0.91	0.92	−0.39	1.00
NO3−	0.38	0.22	0.15	−0.18	−0.04	−0.16	−0.11	0.11	−0.23	0.04	−0.05	0.55	−0.04	1.00
Cu	0.27	−0.06	−0.47	0.90	−0.49	−0.48	−0.47	−0.65	−0.40	−0.47	−0.63	−0.16	−0.51	−0.17	1.00
Fe	−0.16	0.03	0.16	−0.67	0.15	0.15	0.12	0.25	0.40	0.11	0.35	0.05	0.19	0.05	−0.75	1.00
Mn	−0.13	0.30	0.12	−0.11	0.06	0.08	0.07	0.24	0.01	0.12	0.17	−0.03	0.07	0.22	0.06	0.15	1.00
Zn	0.14	−0.30	−0.39	−0.08	−0.30	−0.26	−0.31	0.03	0.14	−0.30	−0.16	0.17	−0.34	−0.04	−0.10	0.16	−0.05	1.00
Pb	−0.12	−0.27	−0.10	−0.57	−0.04	0.12	0.04	0.29	0.68	0.03	0.16	0.21	−0.07	0.18	−0.46	0.34	0.07	0.36	1.00
Cd	−0.14	−0.26	−0.09	−0.58	−0.02	0.14	0.06	0.30	0.68	0.05	0.18	0.20	−0.05	0.18	−0.47	0.35	0.07	0.35	1.00	1.00

presents correlation coefficients among various parameters in the surface water of Nador Canal during winter. In winter, temperature (T (°C)) and other parameters show strong negative correlations with electrical conductivity (EC), calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), and sulfate (SO₄²⁻), suggesting that colder temperatures might reduce the solubility or presence of these ions. There is a strong positive correlation with phosphate (PO₄³⁻), which could indicate that colder conditions favor the accumulation or reduced breakdown of phosphate compounds. Dissolved oxygen (DO) and metals show negative correlations with EC, Ca²⁺, Mg²⁺, Na⁺, and SO₄²⁻, and a very strong negative correlation with copper (Cu). This could suggest that higher levels of these ions or salts may be associated with reduced oxygen solubility or increased oxygen consumption in biochemical reactions. And, DO shows strong negative correlations with lead (Pb) and cadmium (Cd), which might indicate that these metals are more soluble or mobile in conditions of lower dissolved oxygen. Nutrients (PO₄³⁻, NO₃⁻) and metals PO₄³⁻ show inverse relationships with many ions and a positive relationship with temperature, which could be due to temperature-dependent biological uptake or release processes, and nitrate (NO₃⁻) shows a positive relationship with temperature, possibly indicating enhanced nitrification at higher temperatures. Lead (Pb) and cadmium (Cd) show very high correlations with each other and strong correlations with ammonium (NH₄⁺), suggesting common sources or similar environmental behaviors. Zinc (Zn) and manganese (Mn) show little correlation with most other parameters, suggesting that their presence in the water might be controlled by factors not directly related to the general water chemistry. Cu shows a unique pattern, with a very strong negative correlation with DO and strong negative correlations with many other parameters, suggesting that copper’s behavior in the canal might be significantly influenced by redox conditions and perhaps complexation with organic matter, and Fe shows a unique pattern of correlation with DO, perhaps due to its redox-sensitive nature, transitioning between soluble and insoluble forms depending on the oxygen levels.

3.3.2. Principal Component Analysis (PCA)

The table and figures of the principal component analysis (PCA) data for surface water in the Nador Canal during winter reveal insights into the relationships between the parameters and the sampling stations of the water. The PC1-PC2 in summer duo accounts for more than 62.2% of the data (

Table 5. Rotated factor loadings of principal components on physicochemical and heavy metal parameters in summer and winter.

	Summer			Winter
Variable	PC1	PC2	PC3	PC1	PC2	PC3
T (°C)	−0.254	0.072	−0.326	−0.153	0.144	−0.466
pH	0.016	−0.161	−0.431	0.059	−0.198	−0.448
EC	0.297	−0.158	−0.154	0.336	−0.016	−0.003
DO	−0.245	−0.283	0.124	−0.069	−0.383	0.237
Ca2+	0.315	−0.133	−0.029	0.323	−0.092	−0.051
Mg2+	0.319	−0.057	0.097	0.334	0.043	0.029
Na+	0.318	−0.102	0.023	0.335	−0.016	−0.011
K+	0.281	0.092	−0.127	0.288	0.054	−0.04
NH4+	0.121	0.326	0.316	0.119	0.288	0.131
Cl−	0.315	−0.105	−0.047	0.333	−0.031	−0.048
SO42−	0.318	−0.019	−0.027	0.301	0.03	−0.04
PO43−	−0.127	0.218	−0.437	−0.12	0.142	−0.491
HCO3−	0.309	−0.136	−0.043	0.333	−0.031	−0.079
NO3−	−0.014	0.11	−0.498	0.089	−0.11	−0.191
Cu	−0.219	−0.271	0.179	0.298	0.094	−0.037
Fe	0.115	0.276	−0.096	−0.071	0.228	0.023
Mn	0.047	0.011	−0.186	−0.025	−0.242	−0.367
Zn	−0.071	0.273	0.117	−0.014	0.297	0.246
Pb	0.068	0.45	0.069	0.024	0.475	−0.108
Cd	0.074	0.449	0.066	−0.006	0.478	−0.082
Eigenvalue	8.9602	3.8578	2.325	8.609	3.8388	1.9999
Proportion	0.448	0.193	0.116	0.43	0.192	0.1
Cumulative	0.448	0.641	0.757	0.43	0.622	0.722

, Figure 8a,b). Based on these percentages, the processes governing the chemical development of the region’s waters are essentially contained in these two components. PC1 accounts for 44.8% of the variance; it shows strong loadings for magnesium (Mg²⁺), sodium (Na⁺), calcium (Ca²⁺), chloride (Cl⁻), sulfate (SO₄²⁻), and bicarbonate (HCO₃⁻).

PC1 is strongly associated with major ions, reflecting the overall salinity or total dissolved solids in the water. These ions typically originate from geological sources or human activities like agricultural runoff and urban wastewater. PC2 explains 19.3% of the variance; it shows strong loadings for cadmium (Cd), lead (Pb), zinc (Zn), ammonium (NH₄⁺), and iron (Fe). PC2 captures variations primarily related to metal pollutants and nutrients. The presence of NH4⁺ along with heavy metals suggests potential sources from industrial discharge and agricultural runoff, indicating anthropogenic pollution. PC3 captures 11.6% of the variance; it shows strong loadings for temperature (T (°C)), pH, phosphate (PO₄³⁻), and manganese (Mn). PC3 seems to be influenced by temperature and pH, which affect the solubility and mobility of nutrients like phosphate and metals such as manganese. This component might reflect seasonal variations or the impact of thermal pollution. Data points like S18, S19, and S20 cluster together on the positive side of PC2, suggesting these sites might have higher concentrations of metals and nutrients. Sites like S2, S3, and S4 cluster on the negative side of both PC1 and PC2, potentially indicating lower salinity and pollutant levels. Parameters like Cd, Pb, and Zn, pointing towards the positive end of PC2, indicate their co-occurrence, likely due to common pollution sources. The provided principal component analysis (PCA) for the surface water in Nador Canal during the summer further clarifies the interrelationships among various water quality parameters.

The PC1-PC2 in winter duo represents over 64.1% of the data (Table 5, Figure 9a,b). These percentages indicate that the chemical evolution of the region’s waters is primarily governed by these two components. PC1 explains 43% of the variance in winter, with strong loadings from magnesium (Mg²⁺), sodium (Na⁺), calcium (Ca²⁺), chloride (Cl⁻), sulfate (SO₄²⁻), and bicarbonate (HCO₃⁻), highlighting the influence of major ions on salinity and EC. These ions likely originate from natural geological sources and human activities like agricultural runoff and urban wastewater. In summer, similarly, PC1 is heavily influenced by the same major ions, suggesting a consistent presence of salinity and mineral content throughout the years. PC2 explains 19.2% of the variance in winter; it is dominated by heavy metals (cadmium (Cd), lead (Pb), and zinc (Zn)) and nutrients (ammonium (NH4⁺) and iron (Fe)), indicating pollution primarily from industrial discharges and agricultural runoff. Sites S18, S19, and S20 are grouped on the positive side of PC2, indicating higher concentrations of these pollutants. In summer, it was influenced by heavy metals (Pb, Cd) and nutrients (NH4⁺), with PC2 explaining a significant portion of variance due to these contaminants. Similar to winter, this suggests ongoing anthropogenic pollution, though the specific metal profiles differ slightly. PC3 explains 10% of the variance in winter; it is influenced by temperature (T (°C)), pH, phosphate (PO₄³⁻), and manganese (Mn), suggesting an interaction of thermal and chemical dynamics affecting the solubility and mobility of nutrients and metals. In summer, variations from parameters like nitrate (NO₃⁻), and phosphate (PO₄³⁻) were captured, indicating influences from both natural processes and anthropogenic activities, although not directly linked to temperature or pH as in winter. In winter, sites like S2, S3, and S4 show lower salinity and pollutant levels, positioned negatively on both PC1 and PC2. In summer, sites like S13, S14, and S15 show high impacts from pollutants, especially metals, positioned positively on PC2. Overall, the PCA data from both seasons suggest that while there is a consistent pattern of salinity and general mineral content, the specific pollutants and their impacts on different sites vary, potentially due to seasonal activities such as farming cycles or variable industrial outputs. These findings highlight the need for targeted environmental management strategies that consider seasonal variations in water quality dynamics.

3.4. Water Quality Assessment Using Water Quality Index

The water quality index (WQI) classifies water quality into five categories: excellent (WQI < 50), good (50 ≤ WQI ≤ 100), poor (100 < WQI ≤ 200), inferior (200 < WQI ≤ 300), and unsuitable (WQI > 300). This index is a simple measure to convey water’s overall health and suitability for various uses [46]. The WQI is a numerical indicator that integrates multiple criteria to represent the overall quality of water in a single value. The WQI of the surface waters in the Nador Canal shows marked seasonal variation; in summer, values ranged from 69.06 to 196.60, with an average of 113.19, and in winter, values ranged from 114.09 to 325.63, with an average of 165.84 (

Table 6. Results of determination of WQI of surface water in Nador Canal in summer and winter.

Stations	Longitude	Latitude	Summer		Winter
			WQI	Type of Water	WQI	Type of Water
S1	34.83025	−6.286167	128.37	Poor	173.21	Poor
S2	34.819417	−6.294444	127.26	Poor	164.79	Poor
S3	34.774056	−6.317556	128.28	Poor	163.82	Poor
S4	34.73875	−6.333639	136.55	Poor	153.43	Poor
S5	34.738861	−6.333861	114.73	Poor	150.28	Poor
S6	34.726028	−6.337944	118.57	Poor	153.15	Poor
S7	34.695028	−6.293861	113.24	Poor	151.25	Poor
S8	34.686917	−6.287056	112.93	Poor	148.45	Poor
S9	34.686167	−6.286472	112.87	Poor	149.37	Poor
S10	34.675639	−6.288306	131.70	Poor	162.61	Poor
S11	34.646917	−6.290694	101.65	Poor	142.28	Poor
S12	34.638528	−6.288556	110.99	Poor	142.95	Poor
S13	34.625778	−6.288444	102.31	Poor	135.21	Poor
S14	34.61675	−6.270861	122.02	Poor	148.15	Poor
S15	34.611611	−6.271333	161.71	Poor	263.17	Very poor
S16	34.585	−6.281389	196.60	Poor	325.63	Unsuitable
S17	34.573611	−6.293222	74.80	Good	287.39	Very poor
S18	34.545883	−6.325048	79.28	Good	120.89	Poor
S19	34.546278	−6.324417	81.54	Good	135.17	Poor
S20	34.544861	−6.326028	80.45	Good	131.13	Poor
S21	34.53925	−6.331639	85.30	Good	132.12	Poor
S22	34.5385	−6.331917	69.06	Good	114.09	Poor

and Figure 10). In summer, the minimum WQI value was 69.06 at station S22, classified as “good”, indicating the highest observed water quality. The maximum value was 196.60 at station S16, classified as “poor”, denoting the poorest quality during the summer. In winter, the maximum WQI value increased to 325.63 at station S16, which is classified as “unsuitable”, highlighting this station as having the most problematic water quality. The summer minimum suggests a potential decline in water quality, reaching levels that may necessitate additional water treatment or selective irrigation strategies to protect crops and soil health. Furthermore, the winter WQI indicates an overall degradation in quality. Seasonal variations in the WQI may be influenced by factors such as precipitation patterns, agricultural runoff, and other seasonal dynamics that impact water quality. It is crucial for farmers who rely on this water for irrigation to stay informed about these fluctuations to adjust their agricultural practices and ensure crop viability. Continuous monitoring of water quality throughout the year is essential to maintain standards suitable for irrigation. When examining individual monitoring stations, the summer season typically recorded “poor” ratings at most stations, except for six stations (S17, S18, S19, S20, S21, and S22) that received a “good” rating due to their proximity to the Espoo River, which is consistent with the results of the principal component analysis (PCA). However, the winter season presented a consistent pattern: most stations were rated “poor”, except two (S15 and S17) that fell into the “very poor” category, and one station (S16) that fell into the “unsuitable” category. Notably, stations S15, S17, and S16 exhibited alarming pollution levels during the winter, reaching the “unsuitable” category, the worst possible rating. This indicates significant contamination that renders the water unfit for almost all types of use without substantial remedial measures. The Nador Canal water quality index readings underscore the critical importance of seasonal monitoring, the development of responsive irrigation practices, and a consistent water quality assessment framework to ensure sustainable agricultural productivity. The occurrence may result from factors such as ion discharge, coastal zone development, seawater intrusion, agricultural input contamination, human waste, or sewage from homes and septic tanks, among other causes [47].

4. Conclusions

This study aims to assess seasonal variations in the surface water quality of the Nador Canal in Morocco using the water quality index (WQI) and principal component analysis (PCA). The results reveal significant seasonal variations, with summer showing a potential deterioration in quality due to higher temperatures and lower dissolved oxygen levels, and winter showing generally improved conditions. The WQI for Nador Canal reveals significant seasonal variability, generally showing better quality in summer than in winter. During summer, the lowest WQI value was recorded at station S22 at the top of the canal, with a value of 69.06, while the highest was at station S3, with a value of 136.55. In contrast, winter showed a significant decline, with station S16 recording a WQI of 325.63, while station S22 had the lowest value at 114.09, indicating unsuitable conditions. The average WQI values reached 113.04 in summer and 160.6 in winter, making the water unfit for drinking in both seasons, although it remained suitable for irrigation. This is contrasted by the winter conditions, where the water quality generally showed improvement, reducing the necessity for such interventions. The results of the water quality index are consistent with the results of the principal component analysis of the surface water in the Nador Canal, where the results of the principal component analysis showed that there are significant seasonal variations in water quality. In both summer and winter, major ions like magnesium, sodium, and calcium predominantly indicate influences from natural and anthropogenic sources. In winter, heavy metals and nutrients, signaling pollution from industrial and agricultural runoff, become especially prominent. This seasonal fluctuation appears to be influenced by various factors, including changes in precipitation patterns, agricultural runoff, and other environmental dynamics that typically affect water quality. This study highlights the importance of sustainable agricultural practices and effective water management to address groundwater pollution in Morocco’s Gharb region. Recommendations include adopting crop rotation, precision irrigation, optimized water usage, and regulating fertilizer application to mitigate nitrate infiltration and maintain nutrient equilibrium.