Monitoring the Ecological and Geochemical Impacts of Coastal Development and Management on the Oualidia Lagoon

Abstract

Oualidia lagoon, known as the oyster capital, is one of the most important coastal ecosystems along Morocco’s Atlantic coast. Over the past few decades, this ecosystem has faced numerous ecological challenges caused by both human activities and natural conditions, affecting its environmental quality. The present study aims to assess the impact of management projects implemented in the lagoon over the last eleven years on its health, especially in the sediment-trap area. In this context, a field mission was conducted in 2022, during which 15 surface samples were collected and analyzed using ICP-OES methods to determine metal concentrations. However, environmental indicators suggest that the ecological quality of the lagoon remains low, with significant and moderate contamination showing different trends, mainly for arsenic As (1–41.16 mg/kg); cobalt Co (2.01–7.2 mg/kg); molybdenum Mo (0–112.2 mg/kg); cadmium Cd (0.93–1.73 mg/kg); iron Fe (2433.36–19,721.55 mg/kg); and aluminum Al (640.7–11,600.57 mg/kg). The hotspots for these elements are mainly found at stations 13 and 15, which cover the upstream area of the lagoon near of the sediment trap. Comparing the results with those of previous studies conducted in the lagoon, there has been a decrease in sediment contamination since the sediment trap was created in 2011. The analysis suggests that different sources of these metals are entering the lagoon. This study provides updated data on metal concentrations in Oualidia lagoon sediments, one of the most diverse and biodiverse ecosystems in the Moroccan Atlantic. These results provide a scientific basis for targeted environmental management of the Oualidia lagoon, supporting priority monitoring and control of pollution sources. They also highlight the importance of developing awareness programs for residents, fishermen, farmers, food businesses, hotels, and guesthouse owners, alongside the continuation of management projects in the lagoon.

1. Introduction

Approximately 13% of the world’s coastline comprises lagoon ecosystems, which are crucial areas where land and sea meet [1,2] and are recognized as unstable and vulnerable transition zones. They provide a variety of plant- and animal species, as well as significant ecosystem value [3,4].

Lagoons provide social, economic, and ecological benefits, such as fishing, aquaculture, water purification, habitat for wildlife, birdwatching, climate-change mitigation, and flood and storm protection [5,6,7,8]. Thus, they are playing essential roles in preserving the coastal basin. Because of these provided ecosystems services of social and economic interests, a variety of activities are practiced in and around these coastal systems. These activities were reportedly causing metal pollution [9,10,11,12,13,14] and biological pollution [15,16,17,18,19,20], which affected the lagoon’s environmental quality and led to biodiversity loss [21,22,23,24,25,26]. In addition, human activities and natural processes can alter the lagoon’s natural environment and morphology, such as coastal erosion, and certain management projects can lead to sedimentary disruptions [27,28,29]. Furthermore, agricultural activities such as the application of fertilizers and pesticides can compromise the water quality of the lagoon ecosystem by impairing its natural purification processes. At the same time, human construction and climate change induce hydrological disturbances that disrupt the water regime, leading to increased erosion and sedimentation rates [30,31,32].

The Moroccan Atlantic coast hosts several ecologically important lagoons, including Moulay Bousselham, Sidi Moussa, Oualidia, and Khenifiss, while the Nador lagoon is located on the Mediterranean coast. These lagoons have been the subject of targeted restoration and management initiatives. Furthermore, recent studies have systematically assessed their environmental status, focusing on hydrodynamic behavior, sedimentary processes, geomorphological characteristics, and sustainability indicators [33,34,35,36,37,38,39,40,41,42,43,44,45,46,47].

The Oualidia lagoon, located on the Atlantic coast of Morocco, constitutes the study area of this work. It was designated a RAMSAR site in 2005 in recognition of its ecological value and socio-economic importance. This lagoon provides essential ecosystem services, particularly oyster farming and tourism [46,48,49,50]. Since the 1950s, economic activities have expanded, marked by the establishment of the first oyster farm in 1954 and followed by rapid population growth during the 1970s [12]. This demographic and economic development has been accompanied by increasing levels of heavy metals in the lagoon. There has been a rise in heavy-metal levels alongside demographic and economic growth. According to recent research by Mejjad [11], levels of heavy metals like Cd and Cr increased notably from 1950 to 2012. Additionally, a sudden shift occurred between 1955 and 1980, during which sedimentation and sediment accumulation rates [51] changed in line with recorded fluctuations in metal concentrations [11], rare earth elements [52], and radionuclides [53]. These variations were linked to changes in hydrodynamic conditions or events that occurred during these periods [11].

Previous studies by Carruesco [54], Zourarah [55], and Maanan [9], which examined the pollution history of the lagoon through sediment cores, also found that the grain size and chemical makeup of the Oualidia lagoon sediments indicate a dominant continental influence with finer sediments and higher metal concentrations. In contrast, the deeper layers before the 1970s show coarser sediments with a lower heavy-metal content [46,56].

The confinement and sediment dynamics of Oualidia lagoon have been extensively investigated, while an early mathematical-modeling study in 2006 aimed to characterize the hydro-sedimentary regime and assess the effects of opening the downstream dike and constructing an upstream sediment trap [57,58,59,60]. These studies revealed asymmetric tidal propagation, with a shorter flood phase and higher peak velocities compared to the ebb, despite comparable water volumes. This resulted in predominantly upstream sediment transport, sediment accumulation, and increased confinement in the lagoon’s upstream areas [59]. To mitigate this, a sediment trap was installed in 2011. Subsequent bathymetric modifications, particularly in the main channel of the lagoon, initially reduced flood-tide dominance [30,60]. However, a decade after the creation of the sediment trap, renewed sediment accumulation in the downstream zone increased tidal asymmetry indexes (M4, M4/M2), signaling a resurgence of flood-tide dominance [20,61]. The persistent asymmetric tidal regime continued to control sediment transport, driving sand-bar formation and reshaping the main channel [62]. Although dredging of the sediment trap temporarily mitigated flood-tide dominance, subsequent bathymetric changes reversed this effect, owing to shallower downstream areas and tidal delta evolution [61].

It should be noted that after the creation of the mudflat, the lagoon was affected by a phenomenon of hydrodynamic confinement, leading to the death of migratory birds and significant impacts on oyster farming, due to domestic waste overflowing into the lagoon. In response to this situation, a new development was implemented in 2012, consisting of the creation of a sanitation network to transport wastewater to a treatment plant. In this context, it became essential to assess the sanitary condition of the lagoon and its adjacent areas.

The main objective is to determine the spatial and temporal distribution of heavy metals in surface sediments and to assess the post-management impacts on sediment contamination in the Oualidia lagoon using data updated in 2022 by analyzing the concentrations of twelve heavy metals (As, Cd, Fe, Zn, Al, Co, Cr, Mo, V, Ni, Mn, and Ti) in 15 surface sediment samples. The health of the lagoon was assessed using environmental and ecological indices. The results were then compared with those of previous studies conducted over the past 25 years to examine the impact of interventions, including the sediment trap, on the environmental quality of this coastal system and to determine the spatial and temporal distribution of heavy metals in surface sediments.

2. Materials and Methods

2.1. Study Area Description

The Oualidia lagoon is located 75 km south of El Jadida (32°44′42″ N, 9°02′50″ W) on Morocco’s Atlantic coast. The lagoon is a RAMSAR site and is well-known for its biological and ecological significance. Various activities are conducted here, playing a vital role in the regional and national economy [49,63]. The lagoon provides essential ecosystem services such as job creation and income for the local population. It is one of the most popular destinations for national and international visitors, particularly during the summer, supporting sectors like tourism, food, fishing, and accommodation.

The downstream sector of the lagoon includes three tidal inlets that control ex-changes with the Atlantic Ocean: a main inlet approximately 150 m wide and 3 m deep, a secondary inlet around 50 m wide and 2 m deep, and a small temporary inlet that becomes active only during high tides and storm events [30,33,64]. The Oualidia lagoon is characterized by an average width of 0.5 km and a length which covers 3.5 km². The lagoon’s topography features an interdune depression with various morphological components, including the main channel, secondary channels, three main passes, a third secondary pass, and a sandpit [54,57], (Figure 1).

Hydrodynamics in the Oualidia lagoon are mainly controlled by tidal forcing, dominated by the semi-diurnal M2 tide with a period of about 12 h 42 min [65]. Tidal currents are strongest near the inlets, reaching 0.5–1 m s⁻¹, with spring tide maxima around 0.77 m s⁻¹. The flood phase lasts longer than the ebb (≈7 h 25 min vs. ≈5 h), and peak velocities generally occur 1–2 h around high tide [59,66]. The current’s strength decreases progressively toward the upstream lagoonal areas.

Water renewal is spatially variable, ranging from about 1 day near the main inlet to nearly 30 days upstream, with an average residence time of approximately 15 days [58]. Salinity in the lagoon is characterized by a strong tidal-variability and a longitudinal gradient, with higher values near the ocean entrance and lower values upstream [67,68]. Freshwater inputs are mainly associated with submarine groundwater discharge, which plays a key role in regulating salinity and residence times, while episodic runoff during heavy rainfall provides only temporary contributions [69,70].

Extensive research studies on Oualidia lagoon has examined its confinement and sediment dynamics [57,58,59,60,61,71]. These studies identified asymmetric tidal-propagation characterized by shorter, higher-velocity flood phases compared to the ebb, despite comparable water volumes. This asymmetry drives net upstream sediment transport, resulting in sediment accumulation and increased confinement in the lagoon’s upper areas [59]. To mitigate these processes, a sediment trap was recommended and subsequently constructed in 2011 near the permanent dike (Figure 1). Based on numerical modeling investigations, it was designed to intercept suspended sediments and enhance settling, reducing upstream accumulation and improving water circulation. This sediment trap has a capacity of approximately 100,000 m³, covering an area of 99,900 m², with dimensions of 270 m in width, 370 m in length, and 1.84 m in depth (Figure 1) [58,59].

In agricultural areas, several plots are mainly devoted to tomato cultivation. During the rainy season, the use of various copper-based pesticides, fungicides, and bactericides, combined with the local topography (terrain slope), promotes the transport of these substances by runoff into the lagoon. This mechanism largely explains the high concentrations of certain chemical elements observed in the lagoon sediments.

2.2. Sediment Samples Collection and Physical Preparation

Fifteen surface-sediment samples were collected from the Oualidia lagoon in 2022 during low tide. The sampling locations were identified by surface facies [66] and the hydrodynamic conditions of the study area [30,55] and were selected in close proximity to the sampling points used in previous studies, with the aim of evaluating a comparison of contamination levels with them.

Figure 1 shows the locations of the sampling sites. Only the top 4 cm of the surface samples were collected in different phases using GPS positioning and a Van Veen-type sediment grab. The sediments collected were stored in numbered plastic bags to prevent potential metallic contamination. Samples were kept refrigerated during transport to the laboratory and stored at 4 °C. In the laboratory, the surface-sediment samples were crushed and homogenized with a mortar, oven-dried at 90 °C, and then transferred to plastic bottles for further analysis.

3. Geochemical Analysis

3.1. Organic Matter Content Determination

The organic matter (OM) content of each surface sample was measured using the loss-on-ignition (LOI) technique. The OM percentage was calculated from the weight difference between the dried sediment and the ash after combustion at 550 °C for 5 h [72].

3.2. Grain Size Distribution Determination

A Cilas-type laser particle sizer was used to determine the particle-size composition simultaneously with the metal analyses. The particle distribution (in percentage) by size class was provided by all measurements, enabling the classification of sediment composition as follows: clays (<2 μm), silts (from 2 to 63 μm), and sands (from 63 μm to 2mm).

3.3. Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES)

A total of 15 sediment samples were examined using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES); (Manufacturer: Thermos Fisher Scientific, Waltham, Massachusetts, USA), a technique for analyzing elemental composition. The samples were oven-dried at 90 °C, then ground and homogenized with an agate mortar. A total attack was carried out on 1 g of sediment in order to obtain the total content of each metal measured. An acid-resistant glass container was then chosen to hold this sample. A total of 10 mL of concentrated nitric acid (HNO₃) was added after they had been subjected to microwave digestion. A HNO₃-HFHCl mixture was then added to the sediment sample and heated to a temperature of 100–110 °C to obtain a transparent solution [73,74].

4. Ecological and Environmental Indices

The environmental indices used in this study were selected on the basis of complementary scientific and methodological considerations. Some of these indices have already been applied in previous studies conducted in the same lagoon, allowing for direct comparison with published results and ensuring methodological continuity. Other indices have been incorporated to provide a more comprehensive and realistic assessment of the environmental quality of the lagoon. These indices provide a better characterization of contamination levels, potential biological effects, and the overall health of the environment and sediment quality.

4.1. Geo-Accumulation Index (Igeo)

The geo-accumulation index (

Table 1. Classification of Müller [75].

Class	Value	Pollution Level Description
0	Igeo ≤ 0	Unpolluted
1	0 < Igeo < 1	Unpolluted to moderately polluted
2	1 < Igeo < 2	Moderately polluted
3	2 < Igeo < 3	Moderately to heavily polluted
4	3 < Igeo < 4	Heavily polluted
5	4 < Igeo < 5	Heavily to extremely polluted
6	5 < Igeo	Extremely polluted

) is a numerical metric used to evaluate sediment contamination levels [75]. It is determined by the following formula:

Igeo = log2 (C_n/1.5 B_n)

where

* Cn signifies the concentration of metal n in the analyzed sediment sample.

* Bn means the geochemical background of a corresponding metal n, can be found in the literature such as the upper continental crust values (UCC) [76], or the local background of the studied area.

* The factor 1.5 accounts for background value fluctuations due to lithogenic effects.

4.2. Contamination Factor (CF), Degree of Contamination (Cd), Modified Degree of Contamination (mCd), and (PI Nemerow)

The contamination factor allows us to evaluate contamination levels by calculating the ratio of a metal’s concentration (C_metal) to its reference value (C_reference). This index is determined as follows:

CF = C_(metal)/C_(reference)

The degree of contamination (Cd) is the sum of the concentration factors (CF) of all the elements studied and is calculated as follows:

$${\mathit{C}}_{\mathit{d}}=(\sum _{\mathit{i}=𝟏}^{\mathit{n}}{\mathit{C}\mathit{F}}_{\mathit{i}})$$

The Modified Degree of Contamination (mCd) is the average of the contamination factors (CF) for all metals studied, used to assess the overall contamination of a sediment while normalizing by the number of metals, and is calculated as follows:

$${\mathit{m}\mathit{C}}_{\mathit{d}}=(\sum _{\mathit{i}=𝟏}^{\mathit{n}}{\mathit{C}\mathit{F}}_{\mathit{i}})/\mathit{n}$$

The average and maximum values of the contamination factors (CF) are combined to create the Nemerow Pollution Index (PI_Nemerow), a composite index that evaluates a site’s overall contamination. This is how it is computed:

$${\mathit{P}\mathit{I}}_{\mathit{N}\mathit{e}\mathit{m}\mathit{e}\mathit{r}\mathit{o}\mathit{w}}=\sqrt{{\displaystyle \frac{({\mathit{C}\mathit{F} \mathit{m}\mathit{a}\mathit{x})}^{𝟐}+({\mathit{C}\mathit{F} \mathit{a}\mathit{v}\mathit{g})}^{𝟐}}{𝟐}}}$$

4.3. Pollution Load Index (PLI)

By incorporating the contamination factor index value, the pollutant load (PLI) in a study area can be estimated [77]. The Pollution Load Index (PLI) provides a quantitative measure of the pollution level of chemical components in a sample (

Table 2. Interpretation of CF, Cd, mCd, PLI, and PI Nemerow index.

Index	Interpretation Thresholds
CF (Contamination Factor)	CF < 1 → Low contamination 1 ≤ CF < 3 → Moderate 3 ≤ CF < 6 → Considerable CF ≥ 6 → Very high contamination
Cd (Degree of Contamination)	Cd < 8 → Low 8–16 → Moderate 16–32 → Considerable >32 → Very high contamination
mCd (Modified degree of contamination)	<1.5 = low; 1.5–2 = moderate; >2 = considerable
PLI (Pollution Load Index)	PLI = 1 → baseline level; <1 → no pollution; >1 → polluted
PI Nemerow	PI < 1 = clean; 1–2 = slight pollution; 2–3 = moderate; >3 = heavy pollution

) and is expressed as follows:

PLI = √(CF₁ × CF₂ × CF₃ ×…….× CF_n)

* CF: contamination factor

* n: number of determined metals

4.4. Enrichment Factor (EF)

The EF measures how much an element is enriched in the sediment compared to a reference material (

Table 3. Classification of EF based on [77,78].

Value	Classification
EF < 2	No enrichment and no anthropogenic input detectable in sediment
EF > 2	Enrichment and an anthropogenic source of metals.

). In this study, titanium (Ti) was chosen as the reference element because its concentrations remain stable across the samples.

EF is calculated using the following equation:

$$\mathit{E}\mathit{F}={\displaystyle \frac{{({\mathit{C}}_{\mathit{x}}/{\mathit{C}}_{\mathit{T}\mathit{i}})}_{\mathit{s}\mathit{a}\mathit{m}\mathit{p}\mathit{l}\mathit{e}}}{{({\mathit{C}}_{\mathit{x}}/{\mathit{C}}_{\mathit{T}\mathit{i}})}_{\mathit{b}\mathit{a}\mathit{c}\mathit{k}\mathit{g}\mathit{r}\mathit{o}\mathit{u}\mathit{n}\mathit{d}}}}$$

4.5. Adverse Effects Index (AEI)

The AEI evaluates the impact of a substance or pollutant by comparing its concentration (C) to the tolerance threshold (TEL—Threshold Effect Level) value (

Table 4. Interpretation of AEI values [81].

AEI Value	Interpretation
AEI < 1	Not enough to induce an adverse biological effect (or a moderate impact is suspected)
AEI > 1	Adverse effects on biota are likely.

). It is also used to investigate possible biological effects of heavy metals (See in [51,79]). The formula is as follows [80,81]:

AEI = C/TEL

* C: content of metal in an analyzed sample

* TEL: threshold effect level (As = 7.24, Cd = 0.68, Cr = 52.3, Cu = 18.7, Ni = 15.9, Zn = 124)

4.6. Toxic Unit (TUs)

The toxic unit (TUs) index allows for measuring and comparing the toxicity of substances on a consistent scale (

Table 5. Interpretation of ΣTUs Value.

ΣTUs Value	Interpretation
ΣTUs < 4	Low toxicity for an ecosystem
ΣTUs > 4	Moderate ecosystem toxicity

). This is accomplished using the Predicted Effect Level (PEL) [82], which is calculated using the following formula [81]:

TUs = C/PEL

* C: content of metal in the sample

* PEL: probable effect level (As = 41.6, Cd = 4.21, Cr = 160, Cu = 108, Ni = 42.8, Zn = 271)

5. Results and Discussions

5.1. Superficial Sediments Characteristics: (Grain Size, Organic Matter (OM), and Total Carbon (TC) Content)

Surface sediments were analyzed for grain size distribution, organic matter (OM), and total carbon (TC) content, as shown in

Table 6. Sampling stations (m, Lambert projection), sand (%), mud (%), OM (%), C (%).

Station	Latitude	Longitude	Sand%	Mud%	OM%	TC%
S1	1,601,144	244,848.9	97.4	2.6	8.79	5.10
S2	160,628.9	245,416.5	89.63	10.37	9.81	5.69
S3	160,457.9	244,991	93.92	6.08	13.16	7.63
S4	162,086.6	246,066.2	24.18	75.82	15.59	9.04
S5	161,901	246,654.3	76.48	23.52	10.21	5.92
S6	162,573.3	247,133.6	83.36	16.64	13.19	7.65
S7	162,790	246,808.4	35.82	64.18	14.67	8.51
S8	163,229.7	247,088.1	39.61	60.39	16.6	9.63
S9	163,478.2	247,351.6	28.33	71.67	16.39	9.50
S10	163,789.6	247,557.1	30.78	69.22	13.09	7.59
S11	164,255.5	247,874.7	84.37	15.63	14.93	8.66
S12	164,347.3	247,879.5	82.02	17.98	15.78	9.15
S13	164,618.7	248,130.2	6.77	93.23	19.10	11.08
S14	164,825.9	248,325	82.9	17.01	10.90	6.32
S15	164,867.4	248,480.6	5.86	94.14	19.18	11.12

. Sediments collected near the sandpit, S1, S2, and S3, are dominated by coarse-grained fractions greater than 89.63%. Stations near the sandpit are influenced by marine conditions, where hydrodynamic forces play a bigger role, allowing sandy fractions to accumulate. OM content is more significant in stations with high mud percentages, such as S8, S9, S13, and S15. Similarly, total organic carbon (TOC) values tend to be higher in muddy sediments compared to sandy ones. Nonetheless, some sandy samples (such as S11–S12 with approximately 15% organic matter) display moderate organic-matter levels, indicating local inputs or enhanced biological productivity that increased OM accumulation despite the predominance of coarser grains. These patterns are typical of estuarine environments, where sandy zones are characterized by high energy, low organic matter, and lower carbon content, whereas muddy zones have low energy, are conducive to sediment deposition, and show higher rates of OM and carbon accumulation. In fact, the Oualidia lagoon is often described as “an estuary without a river” [83].

The variations in grain size observed throughout the lagoon mainly relate to changes in hydrodynamic conditions, whether from land, sea, or both. Lagoon ecosystems are inherently dynamic, with water flow affected by tides, waves, winds, and river inputs. These factors generate complex circulation patterns that influence sediment transport and deposition [84,85]. Since the Oualidia lagoon is classified as an estuary without a river, these variations are mostly driven by currents that promote water exchange and sediment movement [83,86]. Moreover, wave action contributes to sediment resuspension and transport, especially near the inlets where wave heights typically range from 1 to 2.5 m about 60% of the time and can sometimes exceed 4 m during winter storms [65]. Consequently, physical oceanography processes like waves and ocean currents influence sediment distribution and lagoon dynamics, acting as main drivers of sediment transport. Additionally, a recent study by Bouchkara [34], proposed a hydrodynamic–sedimentary zonation model of the Oualidia lagoon, highlighting the strong link between morphodynamics, hydrodynamic energy, and sediment distribution. Three energetic zones were identified: a High-Energy Zone near tidal inlets dominated by strong currents and wave action favoring coarse, well-sorted sands; a Moderate-Energy Zone along the main channel characterized by intermediate current velocities and the accumulation of medium to fine sands; and a Low-Energy Zone in the upper lagoon, where weak hydrodynamics promote the deposition of fine, organic-rich silts and clays [35].

5.2. Heavy-Metal Concentrations: Hotspots and Trends

The measured concentrations of Fe, As, Zn, Mo, Al, Cd, Co, Cr, Cu, Mn, Ni, and V, along with their minimum, maximum, and mean values, are presented in

Table 7. Measured concentration of heavy metals in each surface samples collected all along the lagoon, Maximum values are indicated in bold.

Station	As	Cd	Fe	Zn	Cu	Al	Co	Cr	Mo	V	Mn	Ni
S1	30.63	1.73	3440.46	0	0.09	640.7	2.12	5.7	1.89	2.1	100.46	0
S2	25.80	1.69	2433.36	0	4.48	694.87	2.01	5.71	43.68	4.01	76.85	0
S3	28.07	1.68	3618.1	0	1.81	822.55	2.11	8.84	32.35	11.8	109.15	0
S4	5.30	1.06	14,817.35	132.73	14.17	9082.04	5.99	41.9	2.64	23.45	176.76	10.678
S5	32.05	1.67	7171.8	24.19	2.30	3125.83	3.24	13.48	0	17.91	145.79	0.983
S6	19.12	1.59	6495.77	5.43	3.29	2491.79	3.15	12.97	0	18.36	84.83	0.821
S7	41.16	1.23	10,640.06	38.07	5.24	4551.96	3.87	18.96	0.09	28.02	110.96	3.084
S8	18.72	0.93	11,286.86	40.14	7.86	6492.32	4.29	26.15	8.29	15.28	113.10	7.939
S9	37.36	1.33	10,128.38	31.73	9.15	6372.07	4.76	25.96	3.34	15.34	107.26	12.116
S10	5.26	1.49	8761.29	23.09	6.58	4055.99	3.59	20.92	0	14.87	99.76	3.774
S11	1	1.37	3013.09	4.03	6.44	1204.35	2.28	7.65	0	5.14	79.85	0.415
S12	2.72	1.58	3182.59	4.88	1.55	1463.32	2.24	9.31	3.11	3.18	85.33	0.489
S13	20.26	1	19,530.98	76.60	13.53	10,646.94	6.65	40.07	78.78	29.86	152.57	14.006
S14	16.29	1.63	3382.03	0.88	0	1293.11	2.13	7.95	27.99	4.5	84.07	0
S15	1.2	1.34	19,721.55	89.34	6.95	11,600.57	7.2	45.91	112.2	25.01	171.46	18.6
Min	1	0.93	2433.36	0	0	640.7	2.01	5.7	0	2.1	76.85	0
Max	41.16	1.73	19,721.55	132.73	14.17	11,600.57	7.2	45.91	112.2	29.86	176.76	18.6
Mean	18.99	1.42	8508.24	31.41	5.56	4302.56	3.71	19.43	20.96	14.59	113.2	4.86

. The concentration ranges of heavy metals in the analyzed samples are as follows: As (1–41.16 mg/kg); Cd (0.93–1.73 mg/kg); Fe (2433.36–19,721.55 mg/kg); Zn (0–132.73 mg/kg); Al (640.7–11,600.57 mg/kg); Co (2.01–7.2 mg/kg); Cr (5.7–45.91 mg/kg); Mo (0–112.2 mg/kg); V (2.1–29.86 mg/kg); Mn (76.85–176.76 mg/kg); and Ni (0–18.6 mg/kg).

The concentrations of heavy metals across the lagoon exhibit notable spatial variations. Fe and Al dominate in the middle and upstream sites, reflecting the abundance of fine-sediment fractions and indicating the natural lithogenic origin of the sediments. Cr, As, Mn, and Zn show localized high values, notably at stations S4, S13, and S15, suggesting possible natural enrichment or anthropogenic inputs. In a recent study carried out in the lagoon by [11], As and Cr were also reported with high concentrations exceeding local background values determined by [9,11], as well as values recorded in similar lagoonal sediments.

Cd concentrations remain relatively uniform across the sampling sites; however, the mean Cd concentration exceeds values reported in previous studies conducted in the lagoon (

Table 8. A comparison table of heavy metals concentrations reported in previous studies carried out in the Oualidia lagoon and similar ecosystems. LBV: Local background values, Maximum values are indicated in bold.

	Cd	Cr	Cu	Ni	Zn	As	Mo	Co	V	Fe	Al	Mn	References
Oualidia lagoon (Morocco)	1.42	19.43	5.56	4.86	31.41	18.99	20.96	3.71	14.59	8508.24	4302.56	113.2	Present study
Oualidia lagoon (Morocco)	0.66	102.2	17.72	15.73	75.86	10.99	-	13.1	76.93	37,700	-	11,100	[11]
Oualidia lagoon (Morocco)	0.3	64	58	-	229.9	-	-	-	-	69,000	110,000	-	[9]
Oualidia lagoon (Morocco)	0.2	52.5	36.4	-	227	-	-	-	-	69,000	-	-	[46]
Oualidia lagoon (Morocco)	0.58	68	17	28	104	-	-	-	-	27,000	-	244	[89]
Oualidia lagoon (Morocco)	-	-	23	21	63	-	-	-	-	9000	-	148	[56]
S.moussa lagoon (Morocco)	1.87	96.33	15.73	26.59	57.83	6.43	-	23.51	67.27	12,050	7160	130.7	[87]
Nador lagoon (Morocco)	1.6	71.6	150.8	45.2	554.9	-	-	-	-	-	-	-	[12]
Nador lagoon (Morocco)	-	372.95	45.9	124.8	163.25	-	-	-	-	-	-	-	[88]
Safi bay (Morocco)	0.39	11.34	3.85	10.69	36.54	-	-	-	-	-	-	-	[74]
Ebrié lagoon (Côte d’Ivoire)	0.71	157.9	28.2	-	149	6.96	-	8.32	72.6	31,000	-	120	[23]
Bizerte lagoon (Tunis)	0.9	21.6	23.1	142.9	834	-	-	-	-	13,428	-	171.9	[90]
Bizerte lagoon (Tunis)	1.51	-	27.28	71.81	148.52	-	-	-	-	41,727	-	-	[91]
Venice lagoon (Italy)	0.42	47.3	8.4	12.7	61.6	-	-	-	-	13,383	-	339	[92]
Thau lagoon (France)	0.28	21.8	18.7	8.9	36.1	-	-	-	-	6098	-	190	[92]
Mic River (Romania)	0.16	22.62	32.62	26.58	97.71	-	-	-	-	18,410	-	694.8	[93]
LBV (Oualidia lagoon)	0.127	43.47	5.27	19	23.57	11.89	-	7.86	33.46	11,299	-	100	[11]
LBV (Oualidia lagoon)	0.15	38.4	26.6	206	142.3	-	-	-	-	-	-	-	[9]
Upper Continental Crust	0.102	35	14.3	83	52	2	1.4	11.6	53	30,890	77,440	527	[94]

), suggesting an increase in Cd input. The chronological comparison of Cd values from different studies reveals a steady rise, calling for further investigation of its potential sources. Ni, Mo, and Co show generally low concentrations, with distinct peaks of Mo and Ni at S13 and S15, indicating localized hotspots of contamination or accumulation. The mean Ni concentration (4.86 mg/kg) is lower than that reported in previous studies of the lagoon and in other similar ecosystems (e.g., 26.59 mg/kg in Sidi Moussa Lagoon by [87]; 45.2 mg/kg and 124.8 mg/kg in Nador Lagoon by [12,88]). Comparisons among studies carried out in the Oualidia lagoon between 1982 and 2018 show an evident decrease in Ni concentrations over time. Copper (Cu) is found in moderate concentrations throughout the lagoon, with particularly high values at points S4 and S13. This situation is directly linked to local agriculture, which is mainly focused on tomato cultivation and uses copper-based pesticides. Runoff from surrounding farmland contributes to high variations in copper concentrations.

As shows moderate concentrations throughout the lagoon, with relatively high values at S4 and S13. These may be related to agricultural runoff, as the lagoon is bordered by agricultural lands, or to the use of antifouling paints.

The distribution patterns of metal concentrations suggest that the studied sediments are mainly contaminated by As, Cr, and Zn, and moderately contaminated by Ni and Cu. The hotspot sites (S4, S13, and S15) show higher metal concentrations, suggesting anthropogenic sources. Stations S13 and S15 are located in the confined area of the lagoon, which favors the accumulation of fine sediments and consequently higher metal retention. S4, located near agricultural lands in the middle part of the lagoon, may reflect the influence of land-based activities on sediment contamination. When comparing the mean values of the analyzed sediments with previous studies, As and Cr consistently show high concentrations and a steady increase over time, whereas most other heavy metals exhibit a gradual decrease in their concentrations.

5.3. Correlation Among Heavy Metals and Sediment Parameters

The correlation heat map (Figure 2) indicates strong positive correlation among Al, Fe, Co, Cr, Zn, and Ni, suggesting a common lithogenic origin (natural), possibly controlled by the mineral composition and grain size. These elements are geochemically coherent and tend to co-accumulate in fine fractions [95,96]. A strong positive correlation was found between the fine fraction and all heavy-metals except As and Mo, indicating that these metals are enriched in fine-grained sediments, which are typical of low-energy depositional zones. Arsenic has shown a strong negative correlation with other metals and with the fine fraction in the study conducted by [11,97,98,99,100,101], which is in good agreement with the present study’s findings. This suggests that As has a different source from other heavy metal sources. OM and TC exhibit a strong positive correlation, while both show a positive correlation with mud, indicating that organic carbon accumulates in muddy sediments, thereby allowing for metal retention. Cd shows a strong negative correlation with Fe, Al, and Cr (−0.7 range), while it indicates a positive correlation with sand (0.78). This suggests a different source or mode of mobility, which is likely anthropogenic and associated with particulate or biological material rather than a mineral matrix. The weak or negative correlations of As and Mo with most metals suggest different geochemical behavior (e.g., redox-sensitive, probably influenced by the chemistry of porewater rather than sediment texture).

The correlation heat map enabled the distinction between naturally derived lithogenic elements, such as Fe, Al, Cr, Ni, Co, and Zn, which are strongly associated with the muddy fraction and organic-rich sediments. In contrast, it highlighted potentially anthropogenic or redox-sensitive elements, such as As, Cd, and Mo, indicating different or weaker relationships.

The dendrogram highlights how the elements are organized into groups based on their similarity (Figure 3). Most metals (Mo, V, Zn, Mn, Cu, Ni, Fe, Cr, Al, Co) and fine fractions (OM%, C% and Mud%) are grouped together in a large cluster, suggesting that they share similar behaviors or sources, often linked to fine particles and organic matter. In contrast, arsenic is linked to cadmium and the percentage of sand, forming a distinct group, which indicates unique behavior probably linked to larger fractions or a particular origin. The higher fusion height between these two groups shows a marked dissimilarity, indicating the presence of processes or other sources of contamination.

6. Assessment of Pollution Level Using Environmental and Ecological Indices

6.1. Enrichment Factor

Figure 4 below exhibits the EF value calculated for each metal for each different sampling site. As, Cd, Co, and Mo exceed two, which marks the threshold separating natural from anthropogenic origin. Fe, Al, Zn, Cu, Ni, Cr, V, and Mn indicate no or minimal enrichment suggesting natural sources.

As shows values that vary across the sampling stations where, except stations S15, S12, S11, S10, and S4 that record EF < 2 meaning lithogenic origin, reflecting the natural geochemical background of the sediments, all remaining stations indicate strong enrichment, suggesting anthropogenic origin. Cd and Co in S15 and S4 have high EF values, which is different from the As results, demonstrating that arsenic in the Oualidia lagoon has different source and or geochemical behavior. These results are consistent with [11] finding where arsenic is shown to have a different vertical distribution, this is reflected in different geochemical behavior and/or origin. Only Cd that show EF values exceed two in all stations suggesting that the lagoon is primarily contaminated by Cd, while Co and Mo show high values in specific stations indicating localized anthropogenic inputs originating from agricultural runoff, domestic and industrial discharge, or atmospheric deposition. Station where low EF values occur reflect natural inputs or less contaminated areas.

6.2. CF, mCd, PLI, and PI Nemerow

Contamination factor (CF), Degree of contamination (mCd), Pollution Load Index (PLI), and PI Nemerow indices were calculated for the 15 sediment samples.

Based on the Nemerow pollution index (PI Nemerow), all of the stations had values above the norm; exceeding three indicates substantial pollution. These results show considerable contamination, ranging from 28 to 199 based on the contamination factor index. V, Mn, Ni, Al, Zn, Cu, Fe, and Co are moderately polluted with pronounced variation among stations. Severe contamination was noticed in stations with high mud content such as S4, 13, and S15 mainly by Cu, Zn, and Co. In comparison to other studied metals, As shows different distribution all along the lagoon in good accordance with [11] findings showcasing different origin and/or geochemical behavior.

Stations S13 and S15 are the hotspot sites where they exhibit the highest values overall. Calculated contamination indices for S13 show very heavy contamination by Mo, Co, and Cd while S15 based on PLI (3.07), PI (199, 03), and mCd (27.6) indicate an extremely polluted site. S4, S8, and S9 also indicate high CFs values for Cd, Co, and Mo, indicating considerable-to-very-high contamination. S2, S3, S7, S10, S12, and S14 are moderate sites as they have mCd values ranging from 7 to 13 and PLI varying between 1 and 2, suggesting moderate multi-metals contamination. Low contamination was recorded in S11 with the lowest contamination values based on environmental indices (Cd = 109.7, mCd = 6.09, PI = 28.05, PLI = 0.83), (

Table 9. Value of CF, DC, mCd, PLI, and PI Nemerow. (ND = Not Detectable), Maximum values are indicated in bold.

Station	CF (As)	CF (Cu)	CF (Zn)	CF (Co)	CF (Cd)	CF (V)	CF (Mo)	CF (Cr)	CF (Ni)	CF (Fe)	CF (Al)	CF (Mn)	Cd	mCd	PLI	PI Nemerow
S1	30.63	0.02	ND	21.25	49.62	0.1	4.74	0.51	ND	0.88	0.15	0.09	134.2	7.45	0.99	35.49
S2	25.80	1.12	ND	20.09	48.31	0.2	109.2	0.51	ND	0.62	0.16	0.06	247.6	13.7	1.64	77.83
S3	28.07	0.45	ND	21.15	48.08	0.59	80.89	0.8	ND	0.93	0.19	0.09	216.3	12	1.79	57.82
S4	5.30	3.54	6.63	59.91	30.28	1.17	6.62	3.8	0.53	3.81	2.16	0.16	194.8	10.8	2.93	43.05
S5	32.05	0.57	1.2	32.4	47.85	0.89	ND	1.22	0.04	1.84	0.74	0.13	153.1	8.5	1.44	34.36
S6	19.12	0.82	0.27	31.56	45.68	0.91	ND	1.17	0.04	1.67	0.59	0.07	138	7.66	1.28	32.76
S7	41.16	1.31	1.9	38.75	35.31	1.4	0.22	1.72	0.15	2.74	1.08	0.1	176	9.78	1.79	29.91
S8	18.72	1.96	2	42.97	26.77	0.76	20.72	2.37	0.39	2.9	1.54	0.1	189.1	10.5	2.51	31.28
S9	37.36	2.28	1.58	47.65	38.2	0.76	8.35	2.36	0.6	2.61	1.51	0.09	191.3	10.6	2.44	34.52
S10	5.26	1.64	1.15	35.9	42.6	0.74	ND	1.9	0.18	2.25	0.96	0.09	136.6	7.59	1.66	30.6
S11	1	1.61	0.2	22.89	39.2	0.25	ND	0.69	0.02	0.77	0.28	0.07	109.7	6.09	0.83	28.05
S12	2.72	0.38	0.24	22.4	45.34	0.15	7.79	0.84	0.02	0.82	0.34	0.07	127.7	7.09	0.96	32.44
S13	20.26	3.38	3.83	66.51	28.65	1.49	196.96	3.64	0.7	5.03	2.53	0.13	426.1	23.6	0.96	140.27
S14	16.29	ND	0.04	21.37	46.77	0.22	69.98	0.72	ND	0.87	0.3	0.07	199	11	1.48	50.1
S15	1.2	1.73	4.46	72.02	38.37	1.25	280.5	4.17	0.93	5.08	2.76	0.16	497.8	27.6	3.07	199.3
Mean	18.9	1.39	1.57	37.12	40.73	0.72	52.4	1.76	0.24	2.19	1.02	0.1	209.20	11.62	1.7	57.18
Min	1	0.02	0.04	20.09	26.77	0.1	0.22	0.51	0.02	0.62	0.15	0.06	109.7	6.09	0.83	28.05
Max	41.16	3.54	6.63	72.02	49.62	1.49	280.5	4.17	0.93	5.08	2.76	0.16	497.8	27.6	3.07	199.3

).

The calculated contamination factors indicate that

—

Cd, Co, As, and Mo are the dominant contaminants with the highest CF values reflecting anthropogenic origins, mainly agricultural runoff and the excessive use of fertilizers as the lagoon is surrounded by agricultural lands and urban discharges as well as industrial effluent.

—

V, Mn, and Ni are less dominant, suggesting natural lithogenic origin.

—

Contamination is mainly concentrated in S13 and S15 sites where the mud content is high and near to human activities. S15 is collected in the confined part of the lagoon where the hydrodynamic conditions are low, and fine fraction is the most dominant which enable the accumulation of pollutants.

—

The lowest values were recorded in S1–S3 and S11–S12. These stations are characterized by the sand fraction dominance, while S1 and S2 were collected near the sandpit where the hydrodynamic conditions are high, which does not allow for pollutant accumulation. It also suggests less anthropogenic influence compared to other stations.

Based on these contamination indices, the Oualidia lagoon is moderately-to-severely contaminated by As, Cd, Co, and Mo. The spatial distribution of these indices exhibited localized hotspots sites of extreme heavy metals enrichment.

6.3. Geo-Accumulation Index (I_Geo)

The I_Geo values calculated for each element are shown in the figure below (Figure 5) which exhibits the relative contribution of different contaminants with geo-accumulation index classes across studied sediments. Most of the samples are unpolluted and/or moderately polluted. Moderately-to-strongly polluted classes present for certain elements but less frequently. This suggests that the accumulation of heavy metals in the lagoon is not uniform, suggesting variable sedimentary conditions and anthropogenic conditions. In good accordance with other indices, a number of samples are classified as moderately-to-strongly polluted by Cd, As, Co, and Mo. This indeed confirms a localized enrichment by heavy metals possibly linked to human activities such as aquaculture, agriculture, and domestic wastewater. In addition, these results revealed that some stations still show unpolluted and unpolluted-to-moderately polluted sediments, suggesting a natural source or geochemical background.

6.4. Adverse Effects Index (AEI) and Toxic Unit (TUs)

To examine the biological impact of heavy metals on sediment quality, the adverse effect index (AEI) and toxic unit (TUs) were calculated. The AEI were ranged from 2.1 to 9.7, which could potentially cause damage to the biota, while the toxic-unit values obtained for all sampling sites were ΣTUs < 4, suggesting low toxicity for the Oualidia lagoon ecosystem (Figure 6) [102,103]. The mean values of the toxicity levels show a trend towards As > Cd > Cr > Zn > Ni > Cu.

7. Conclusions

The present study provides updated data on the degree of sediment pollution in the Oualidia lagoon. Since the 1970s, interest in protecting the lagoon and maintaining its ecosystem services has been a major concern. Although several management projects have been carried out in the lagoon, scientists have continued to investigate its environmental quality by analyzing and assessing pollutant levels in sediments, particularly heavy metals.

The Oualidia lagoon has undergone several developments aimed at improving water and sediment quality and sanitary conditions. The dredging of a sediment trap in 2011 was the last operation carried out with the aim of reducing the concentration of suspended solids and mitigating pollution. In this context, the present study analyzed the spatial distribution of twelve heavy metals (As, Cd, Fe, Zn, Al, Co, Cr, Mo, V, Ni, Mn, and Ti) throughout the lagoon and compared the results with previous data in order to assess changes in heavy-metal concentrations.

The results showed variations in metal concentrations across the lagoon, suggesting localized areas of pollution. The sediments exhibited high concentrations of As, Cd, Co, and Mo. However, the comparative study in this work between the state of health before and after the creation of the sediment trap [9,11,46,56] and the present study, showed that the average values of the sediments analyzed with those of previous studies, As and Cr, systematically showed high concentrations and a constant increase over time, while most other heavy metals showed a gradual decrease in their concentration.

The use of environmental indices allowed for the assessment of the degree of metal pollution and the potential effects on the lagoon and its biota. Based on these indices, the Oualidia lagoon is moderately-to-severely contaminated by As, Cd, Co, and Mo, though without indications of ecological toxicity. The spatial distribution of these indices revealed localized hotspot sites of extreme heavy-metal enrichment.

In view of this situation, it is important to continue research and identify sources of contamination, as well as to increase monitoring of this environment and be mindful of the equilibrium threshold beyond which disturbances to the ecosystem may become irreversible, in order to protect the ecological integrity of the lagoon and prevent further degradation.