Assessment of Groundwater Quality and the Main Controls on Its Hydrochemistry in a Changing Climate in Morocco (Essaouira Basin)

Abstract

Groundwater is essential for both water supply and environmental conservation, especially in semi-arid and desert areas. Managing groundwater resources requires a thorough understanding of groundwater characteristics and dynamics. The hydrogeochemical properties and evolution of groundwater in the Essaouira synclinal basin in northwest Morocco were studied in this research, with 105 water samples collected in 2009, 2017, 2018, and 2019. The Water Quality Index (WQI) and Irrigation Water Quality Index (IWQI) were developed to determine groundwater quality for consumption and irrigation purposes. The chemical evolution of groundwater is mainly dominated by evaporite, mineral carbonate dissolutions, and cation exchange. Contamination by nitrates is particularly severe in agricultural and tourist areas. The WQI of the 2019 campaign showed that 6.7% of groundwater samples are unsuitable for drinking; 76.7% are poor quality water; and 13.3% are very poor-quality water; while only 3.3% are drinkable. According to IWQI, the total study area has been split into 50% (good), 43.3% (bad), and 6.6% (unfit), respectively, and no excellent groundwater areas have been identified. Therefore, the water is suitable for agriculture but must be treated for drinking. The presence of evaporation and maritime intrusion and the contribution of recent precipitations to aquifer recharging were demonstrated by stable isotope content.

1. Introduction

Groundwater is an essential strategic factor in encouraging economic and social growth in many parts of the world. The increasing population has caused rapid socio-economic change due to the unsustainable use of freshwater reserves in recent years [1,2,3]. Groundwater in aquifers is a vital source of drinking water, but it is susceptible to pollution. In addition, human activity significantly affected surface and groundwater in the previous century, introducing various toxins [4,5]. Furthermore, an assessment of groundwater chemistry and quality will identify possible variables that influence the chemical composition of groundwater and recognize the causes of groundwater contamination [6,7,8,9,10]. These variables will contribute to significant steps towards conserving and sustainable use of groundwater resources. However, to ensure access to safe drinking water for the growing population, it is necessary to protect and use the water supply carefully and responsibly [10,11,12]. To achieve this goal, the origins and hydrochemistry of water must be established. These two fundamental aspects are at the heart of any study of groundwater treatment.

The hydrochemical method is one of the most common and effective approaches to identify groundwater circulation. Along the general groundwater flow direction, the ions’ concentrations change because of water–rock interactions between groundwater and aquifer materials. The chemical composition of groundwater is controlled by the composition and quantity of rainfall, the geological structure, the aquifer minerals, and hydrochemical evolution processes along flow paths [13,14,15].

All the critical factors contributing to the salinity of the aquifer are the proximity of the coastal aquifer to the sea, the prevalence of sand and gravel soils in the area, agricultural activity, and the hydraulic properties of the aquifer [16,17]. The chemical composition of groundwater is influenced by several factors, including precipitation composition, geological structure and mineralogy of sandy aquifers in watersheds, and geochemical processes in aquifers [10,11,18,19,20,21,22].

The reversal of groundwater flow in recent years has resulted in seawater intrusion into the interior along the coastal belt due to heavy pumping of groundwater, especially in summer, making the borehole and the open well unsuitable for agricultural production and consumption [23,24]. Researchers have assessed groundwater quality in several arid and semi-arid countries, notably: Morocco, Tunisia, Egypt, and India [10,23,25,26,27,28]. Various techniques are used to assess water quality; we cited the following for drinking uses [7,25,29,30,31].

In North African arid/desert lands, groundwater (depth > 500 m) is the only source of water supply for most of the local demand (agricultural, industry, tourism, and domestic). Like most countries in the world, the populations of southern Mediterranean countries live under water stress (<450 l/person/year), defined as those using more than 20% of their renewable water resources. In contrast, over 40–50% withdrawal means severe water stress. Currently, the ONU estimates that in 2025, 25 African countries will suffer from water scarcity or water stress. According to UNEP (2006, 2010, and 2011), about 1100 million people do not have access to clean drinking water (surface and/or groundwater), and contaminated water is the direct cause of 5 million deaths yearly, most of them occurring in sub-desertic Africa.

At the national level, water issues, especially groundwater salinization, have become the center of interest for scientific researchers and managers. Several studies across the country have raised it. Morocco, like many Mediterranean countries, has suffered from several drought periods since the 1980s. Its water resources are limited; they are estimated at 20 billion cubic meters, or an average of 700 m³/year/inhabitant, corresponding to a reasonably high-water stress situation. The number of years in a rainfall deficit is greater than the number of wet years, with a general downward trend of 23%.

According to its extension and location, one of the most critical aquifers in Morocco is the Plio-Quaternary aquifer of the Essaouira basin, located in the western part of the kingdom of Morocco. In order to assess the quality evolution of this vital resource, especially groundwater, within areas under semi-arid climate and in terms of climate change, the Essaouira basin is used as an example. In the last decades, this basin has experienced a succession of drought periods, leading to a degradation of its groundwater quality. The Essaouira basin is one of the most critical basins in Morocco; it contains 10% of the total aquifer at the national level (8 aquifers out of 80) [32,33,34,35,36,37,38]. Therefore, to improve water resource management in these regions, it is essential to understand the primary process of controlling groundwater mineralization [1,18,20,24,39].

Water quality index (WQI) measures the quality of water for drinking and other purposes, the WQI was defined by Horton [40] and posteriorly developed by Brown, McClelland [17,21,41]. It transfers several water parameters to give only a single number to assess the overall water quality at a certain location and time [12,42,43]. WQI is a valuable and unique rating to depict the overall water quality status in a single term that helps for selecting proper treatment technique. It was used in several studies to assess groundwater quality [44,45,46,47,48].

Understanding the sources and mechanisms of groundwater recharge in the Essaouira synclinal basin, a semi-arid area in northwest Morocco, is essential for water resource management and coal mine safety [49,50]. Hydrochemical and stable hydrogen and oxygen isotopic data were used to study water-rock interactions and groundwater recharge in many regions [22,51,52,53].

This article aimed to understand variations in groundwater quality, the main factors affecting water quality in the KSOB sub-basin over the last ten years, and the current condition. The primary objectives were: Firstly, to assess the drinking water quality status of groundwater. Secondly, to characterize the associated geochemical mechanisms that govern the geochemical evolution of groundwater.

The spatial distribution of the physicochemical parameters and water quality index was generated using the inverse distance weighted interpolation method (IDW).

The findings will provide a detailed understanding of the drinking water quality of groundwater, which will enable policymakers to properly tackle groundwater issues and design sustainable management of groundwater supply in the regions of Essaouira. This study demonstrates that combining WQI and GIS methods could be a helpful tool for water resources management.

2. Materials and Methods

2.1. Location and Climate

The KSOB sub-basin is located southwest of Morocco, in the Essaouira basin, at a latitude range between 31.34° N–31.42° N, a longitude range between −9.61° E − −9.83° E. The research area is bordered by the TIDZI DIAPER and the Atlantic Ocean. This sub-basin covers an area of 300 km² (Figure 1). The climate is unusual and very particular: it is mild or cool most of the year. The cold current flowing along Morocco’s Atlantic coast lowers summer temperatures to the point that highs remain around 20 °C even in July and August. The wind is another constant in this climate; it often blows, especially as an afternoon breeze in summer. Another characteristic of this climate is fog and haze, which affect this coastal region, especially in the mornings, then dissolve in the afternoon. Rainfall is scarce, typical of a semi-arid climate, at around 300 mm per year (Figure 2), most of which occurs from October to April. Usually, the rain comes in the form of short showers, sometimes heavy.

2.2. Geologic Setting

The two principal aquifers in the lower section of the Essaouira basin are the Turonian and Plio-Quaternary aquifers, found between KSOB Wadi and Tidzi Wadi, which serve as the study area’s primary groundwater supplies [50,54]. The Plio-Quaternary is a limestone sandstone matrix of up to sixty meters of different thicknesses. The Turonian aquifer consists of a confined aquifer belonging to the Senonian marls of the synclinal system, the thickness of which, in certain areas, exceeds 200 m, represented by limestone.

2.3. Hydrogeologic Setting

The aquifer underlies the KSOB sub-basin (Figure 1), and its recharge sources are irrigation and precipitation. It has a groundwater flow direction from the northeast to the southwest [12,23,42]. Transmissivity levels of approximately (4.5−5) m²/s from pumping experiments conducted inside the aquifer [55]. According to Bahir [54], the hydraulic permeability is 3.2 × 10⁻² m/s.

2.4. Analytical Techniques and Groundwater Sampling

One hundred five samples were collected from surface water, wells, and boreholes during a series of sampling campaigns conducted in 2009, 2017, 2018, and 2019 (

Table 1. Summary of descriptive statistics of different hydrochemical parameters of all the 105 groundwater samples from four campaigns: 2009, 2017, 2018 and 2019.

Sample	pH	EC	TDS	T	Ca2+	Mg2+	Na+	K−	HCO3−	Cl−	SO42−	NO3−	IB
		µS/cm	mg/L	°C	mg/L								%
Campaign 2009
Min	7.15	1671	835.5	19	34	30.24	127.42	3.9	109.8	217.97	44.64	0	−7.71
Max	7.69	3520	1760	27	46	45.96	438.15	15.21	231.8	766.8	133.92	199	−3.40
Moy	7.37	2193.77	1096.88	21.46	39.54	36.44	220.06	7.20	182.53	372.91	110.33	37.72	−5.56
SD	0.14	482.48	241.24	2.47	3.48	5.12	83.82	3.88	32.80	142.38	22.96	54.68	1.23
Campaign 2017
Min	7.1	724	396	18.9	44.90	31.10	85.00	4.40	189.10	170.40	11.30	6	−9.46
Max	8	7555	4273	27.4	368.70	205.10	1430.90	74.50	567.40	3138.20	257.20	126.50	7.08
Moy	7.57	2217.77	1165.48	22.66	133.84	80.83	254.28	14.63	337.29	670.64	93.97	32.71	−4.25
Sd	0.23	1253.77	700.02	1.98	72.13	36.87	237.58	15.80	82.76	541.43	51.35	29.16	4.55
Campaign 2018
Min	7.2	916	458	17.58	57.72	14.20	76.75	1.28	12.20	98.80	3.47	0	−9.30
Max	8.65	9744	4875	2029	364	238	1464	66	549.14	3158	406	398.25	2.98
Moy	7.68	1395	1918.24	90.51	136.75	71.17	278.05	11.20	270.43	640.99	127.33	38.70	−1.89
Sd	0.36	1724.70	869.08	360.24	78.32	37.80	266.15	12.96	95.75	587.91	82.82	73.27	3.21
Campaign 2019
Min	7.09	880	440	17.26	64.13	6.804	84.28	1.77	150	226.60	30.29	0	−10.29
Max	9.11	12,250	11,146	2305	849.70	260	1950	75	658.8	4799.60	830.29	400	4.62
Moy	7.62	2775.40	1715.87	231.83	163.29	67.27	346.92	12.20	381.71	814.25	145.12	38.53	−5.92
Sd	0.38	2394.10	2146.45	635.64	147.32	46.35	359.90	16.71	116.40	921.05	148.96	75.18	3.32

) in the downstream part of the Essaouira basin, and the extension of Table 1 and Table 6 of all 105 sample are available in the supplementary material. The Plio-Quaternary and the Turonian aquifer are captured by all the wells sampled. The Hana HI9828 multiparameter was used to measure physicochemical parameters such as pH, electrical conductivity (EC), temperature (T), and total dissolved solids (TDS) in the KSOB sub-basin. With a two-hundred-meter piezometric sound probe, the depth of the water level was determined. The Analysis used ion chromatography to investigate the primary chemical elements (SO₄²⁻, Na⁺, HCO₃⁻, K⁺, Ca²⁺, NO₃⁻, Cl⁻, and Mg²⁺) for the 2009 campaign [56]. Alkalinity is determined from the sulfuric acid solution using a pH meter. Chemical element studies were carried out for the 2017 and 2018 campaigns at the Laboratory of Geosciences and Environment (LGE) at ‘Ecole Normale Superieure (ENS)’ of Marrakech city (Cadi Ayyad University, Marrakech, Morocco). Mohr titration with 0.1 N HCL was used to measure the concentrations of Cl⁻, CO₃⁻, and HCO₃⁻. For the 2019 campaign, Analyses of chemical elements: HCO₃⁻, NO₃⁻, Mg²⁺, Cl⁻, Ca²⁺, SO₄²⁻ tests were carried out in the Laboratory of ENS (Cadi Ayyad University, Marrakch, Morocco), and the two parameters Na⁺ and K⁺ were determined using emission spectrometry in the University Center for Analysis, Tecnology Transfer & Incubation Expertise (CUAE2TI) at “Faculty of Sciences” (lbn tofail University, Morocco).

Heavy metals of the campaign 2019 of the July month were realized in the International Water Research Institute at Mohammed VI Polytechnic University from Morocco using a SKALAR San⁺⁺ Continuous Flow Analyzer (CFA).

The study’s findings were confirmed based on the ionic balance (IB). Furthermore, the total of cation concentrations (Ca²⁺, Na⁺, K⁺, Mg²⁺) should equal the total of the ani-on concentrations (NO₃⁻, SO₄⁻, HCO₃⁻, Cl⁻) within a tolerable margin of error, prefera-bly 5% but up to 10% is acceptable [57]. The formula (1) was used to calculate the ionic balance (IB).

$$\mathrm{IB} =100\times \frac{{\displaystyle \sum } \mathrm{Cations} -{\displaystyle \sum } \mathrm{Anions}}{{\displaystyle \sum } \mathrm{Cations} +{\displaystyle \sum } \mathrm{Anions}}$$

(1)

Within the ±10 range, all analyzed samples were balanced.

2.5. Groundwater Quality: Water Quality Index (WQI)

The Drinking Water Quality Index (DWQI) is a perfect method for assessing drinking water quality and regulating water sources [58]. The WQI evaluation standard, according to Xiao [59], focuses on analyzing distinct chemical components and indicates the effect of different chemical factors on the overall quality of drinking water [29]. Also, these indicators have been adapted to evaluations of water quality worldwide, especially in the Essaouira Basin concurrent study area, with substantial impacts on the population and decision-makers for managing groundwater resources [29,40,58,59]. The following equation (Equation (2)) was used to calculate the water quality index:

$$WQI={\displaystyle \sum \left[W_i\times (\frac{C_i}{S_i})\times 100\right]}$$

(2)

$$W_i=\frac{{\omega }_i}{{\displaystyle \sum {\omega }_i}}$$

The relative weight ω_i is the weight of each chemical parameter calculated for drinking purposes by its relative effects on human health [40,58,59], as shown in

Table 2. Weight and relative weight of each parameter used for the WQI calculation.

Physico-Chemical Parameters	WHO Standard (2011)	Weight (wi)	Relative Weight (Wi)
pH	6.5–8.5	4	0.114
EC (µS/cm)	500–1500	4	0.114
TDS (mg/L)	500	5	0.142
Cl− (mg/L)	250	3	0.086
SO42− (mg/L)	250	4	0.114
NO3− (mg/L)	45	5	0.142
HCO3- (mg/L)	120	3	0.086
Na+ (mg/L)	200	2	0.057
Ca2+ (mg/L)	75	2	0.057
Mg2+ (mg/L)	50	1	0.029
K+ (mg/L)	12	2	0.057
		35	0.998

. In each groundwater sample, the measured concentration of each chemical element is called ‘C_i’, and the corresponding standard value for each chemical parameter is called ‘S_i’ [60]. Based on WQI values, water quality can be divided into five classes. The quality of water is excellent when WQI is less than 50; the quality of water is good when WQI < 100 and above 50; the quality of water is poor when WQI is between 100 and 200; the quality of water is very poor when WQI range between 200 and 300; groundwater is unsuitable for drinking purposes if WQI above 300. Furthermore, using the IDW tool of Arcgis software version 10.2 (ESRI 1999), the spatial distribution of the estimated WQI values in the Essaouira basin was obtained.

2.6. Irrigation Quality: Irrigation Water Quality Index (IWQI)

The model of the Irrigation Water Quality Index (IWQI) was created as a practical hydrogeological tool for assessing the overall quality of irrigation groundwater [61,62], as amended by Verma [63]. As shown in

Table 3. Weight and relative weight of each parameter used for the IWQI calculation.

Physico-Chemical Parameters	Si	wi	Wi
pH	6.5–8.5	4	0.09
EC	2000	5	0.11
Cl− (meq/L)	10	3	0.07
NO3− (meq/L)	2.18	3	0.07
HCO3− (meq/L)	8.5	3	0.07
PI	75	5	0.11
Na (%)	60	4	0.09
SAR	18	5	0.11
MAR	50	4	0.09
PS	7	5	0.11
KI	1	3	0.07
SOMME		44	1

, eleven factors were used in the research region to assess water quality for irrigation purposes. Each attribute is given a weight based on its relative importance [61,62,64]. Because of its significance and influence on plant growth and soil quality, electrical conductivity, for example, is given a weighting of five. However, chloride is weighted due to its low concentration in groundwater compared to world standard limits [60]. The water quality index (WQI) is calculated using the following formulas:

$$W_i=\frac{w_i}{{\displaystyle \sum _{i=1}^n{w}_i}}$$

(3)

$$Q_i=\frac{C_i}{S_i}\times 100$$

(4)

$$S{L}_i=W_i\times Q_i$$

(5)

$$WQI={\displaystyle \sum S{L}_i}$$

(6)

where, Q_i: quality rating of ith parameter, SL_i: subindex of the ith parameter W_i: Relative weight of the ith parameter of IWQI, S_i: Standard limits for the ith parameter [60], C_i: the value of the measured concentration in the KSOB sub-basin of ith parameter.

Water quality is divided into five categories based on IWQI values: good quality (50 < IWQI < 100), poor quality (100 < IWQI < 200), very poor (200 < IWQI < 300), improper quality (IWQI > 300), and excellent quality (IWQI < 50).

2.7. Irrigation Quality: Irrigation Water Quality Index (IWQI)

To measure each parameter’s effect on the IWQI value, and according to Ibrahim [29] and Sener [65] the effective weight (EWi) is determined by dividing the SL_i by the IWQI value.

$$SI=log(\frac{K_{IAP}}{K_{SP}})$$

(7)

where: EWi is meaning the effective weight value for ith parameter.

3. Results and Discussion

3.1. Groundwater Hydrochemical Types

The piper diagram is a graphical representation used to describe groundwater’s hydrochemical characteristics, forms, and hydrochemical evolution [66,67]. This research obtained a Piper diagram using the diagrammes software version 6.76. The piper is a triangle consisting of the central diamond and two secondary triangles, as shown in Figure 3. The diamond is divided into six sections, each with a different water facies [68]. The diamond indicates the overall hydrochemical characteristics of the water sample, while the triangle represents the relative amount of each ion. The 105 groundwater sites on this diagram show that the groundwater in the KSOB sub-basin research region contained three chemical kinds during the two campaigns in 2017 and 2018. The Ca-Mg-Cl type of water predominates among three facies, the Na-Cl facies is the second dominant chemical water type, and the Ca-Cl water type is also present. The campaign of 2009 has just one water type, Na-Cl. The campaign 2019 has two facies: the Mixed Ca-Mg-Cl water type and the Na-Cl water type. The projections of all groundwater samples from the campaigns going from 2009 to 2019 in the study area are illustrated in Figure 3. The hydrochemical types indicate that the chemical facies have changed due to several factors over the years.

3.2. Hydrochemical Characteristics

Table 1 displays the hydrochemical parameter statistical study of 105 groundwater samples collected in 2009, 2017, 2018, and 2019. As shown in Table 1, the concentration of cations in all groundwater samples follows the same order of Na⁺ > Ca²⁺ > Mg²⁺ > K⁺. However, in the field of research, the order of the concentration of anions of the four groundwater campaigns collected follows the same order: chloride > HCO₃⁻ > SO₄²⁻ > nitrate.

The values of electrical conductivity (EC) in the KSOB sub-basin range from 1671 to 3520 µS/cm with a mean of 2193.8 µS/cm for 2009 samples; from 724 to 7555 µS/cm with a mean of 2217.8 µS/cm for 2017 samples; from 916 to 9744 µS/cm with a mean of 2753.9 µS/cm for 2018 samples, and from 880 to 12,250 µS/cm with a mean of 2775.4 µS/cm for 2019 samples. Furthermore, the spatial distribution of EC values (Figure 4a, Figure 5a, Figure 6a, and Figure 7a) for the four groundwater collected campaigns (2009, 2017, 2018, and 2019) reveals that the groundwater salinity in the area where it drains into the Atlantic Ocean has risen through time.

The dominant cation has been present in the 105 groundwater samples for four years. Na⁺ concentrations ranged from 127.42 to 438.15 mg/L in 2009, 85 to 1430.9 mg/L in 2017, 76.75 to 1464 mg/L in 2018, and 84.28 to 1950 mg/L in 2019, respectively, with a mean of 220.06, 254.28, 278.05 and 346.92 mg/L. The Na⁺ concentrations are increasing toward the Atlantic Ocean (Figure 4g, Figure 5g, Figure 6g, and Figure 7g). Furthermore, silicate and halite dissolution may increase the concentration of sodium in groundwater [6,23,39,69,70]. In addition, sodium can also come from the exchange of ions [71,72]. The average concentrations of K⁺ were 7.2, 14.63, 11.20, 12.20 mg/L in 2009, 2017, 2018 and 2019, respectively.

The concentration of calcium (Ca²⁺) ranged from 34 mg/L to 46 mg/L in 2009, from 44.9 mg/L to 368.7 mg/L in 2017, from 57.72 mg/L to 364 mg/L in 2018, and from 64.13 mg/L to 849.70 mg/L in 2019. In 2009, the concentration of Mg²⁺ ranged from 30.24 to 45.96 mg/L; 31.1 to 205.1 mg/L in 2017; 14.2 to 238 mg/L in 2018; and 6.80 to 260 mg/L in 2019. The mean concentrations of Ca²⁺ and Mg²⁺ were 39.54 mg/L and 36.44 mg/L in 2009, 133.84 mg/L and 80.83 mg/L in 2017, 136.75 mg/L and 71.17 mg/L in 2018, 163.29 mg/L and 67.27 mg/L in 2019, respectively.

Chloride concentration (Cl⁻) is the dominant anion in the 105 groundwater samples in the KSOB sub-basin. Cl⁻ ranges from 218–766.8 mg/L in 2009, 170.4–3138.2 mg/L in 2017, 98.8–3158 mg/L in 2018, and 226.6–4799.6 mg/L for 2019, with a mean of 372.91, 670.64, 641 and 814.25 mg/L, respectively. For all groundwater samples, chloride concentrations are highest in the downstream half of the study area, with an increasing trend toward the Atlantic Ocean, according to the spatial distribution of Cl⁻ (Figure 4c, Figure 5c, Figure 6c, and Figure 7c). However, the average Cl⁻ concentrations show a significant increase over ten years, which could be explained by lower precipitation rates associated with climate change, increasing the solvent load in groundwater [23], and the marine intrusion effect. The average concentrations of HCO₃⁻ and SO₄²⁻ are 182.53−110.33 mg/L in 2009, 337.3−94 mg/L in 2017, and 270.43−127.33 mg/L in 2018, 381.71−145.12 mg/L in 2019, respectively. For the 2009 and 2018 campaigns, the highest amounts were found in the northern half of the research zone. In addition, the highest values were observed in the southern portion of the study zone in 2017 and 2019 (Figure 4f, Figure 5f, Figure 6f, and Figure 7f). Anthropogenic inputs, such as tourism and agricultural activities, are an important source of nitrate in the groundwater. In the study area, the NO₃⁻ concentration was found to vary from zero to 199 mg/L in 2009, from 6 to 126.5 mg/L in 2017, from zero to 398.25 mg/L in 2018 and from zero to 400 mg/L in 2019. Furthermore, nitrate concentrations change from year to year and are remarkably spatially distributed, and the concentrations have shown an increasing trend from 2009 to 2019 (Figure 4e, Figure 5e, Figure 6e, and Figure 7e). Climate change, which has resulted in a decrease in precipitation in the studied region in recent years, can explain this [73]. Consequently, it increases the retention of nitrates on the soil surface and ultimately their penetration into the aquifer.

The spatial distribution of the concentration of k⁺, Mg²⁺, and SO₄²⁻ has not changed significantly since 2009.

The pH values of groundwater samples ranged from 7.15 (E9) to 7.69 (E13) in 2009, with a mean of 7.37 as shown in Table 1. In 2017, the pH values ranged between 7. 1 (E21) and 8 (E31), with an average of 7.57. In 2018, the pH was 7.2 (E49) to 8.65 (E65), with a mean of 7.68. In 2019, the pH ranged from 7.09 (E81) to 9.11 (E95), with a mean of 7.62. According to the World Health Organization, the average pH value of drinking water for consumers is between 6.5 and 8.5 [60]. Thus, the pH analysis results show that in this area, most groundwater is within the potable range.

3.3. Hydrochemical Characteristics

The rank correlation (r) was used to evaluate the relationship between two variables. The correlation matrix of the nine physicochemical parameters is presented in

Table 4. Correlation matrix for the analyzed parameters of four campaigns.

	EC	Ca2+	Mg2+	Na+	K+	HCO3−	Cl−	SO42−	NO3−
Campaign 2009 (n = 13)
EC	1
Ca2+	−0.20	1
Mg2+	0.59	0.40	1
Na+	0.95	−0.33	0.36	1
K+	0.34	−0.05	−0.22	0.49	1
HCO3−	−0.73	0.13	−0.75	−0.58	0.20	1
Cl−	0.99	−0.19	0.58	0.96	0.39	−0.72	1
SO42−	0.13	0.46	0.31	0.06	0.17	−0.04	0.18	1
NO3−	0.33	−0.46	−0.07	0.45	−0.03	−0.23	0.31	−0.76	1
Campaign 2017 (n = 31)
EC	1
Ca2+	0.82	1
Mg2+	0.86	0.83	1
Na+	0.92	0.62	0.68	1
K+	0.55	0.39	0.36	0.66	1
HCO3−	−0.06	−0.25	−0.20	0.01	0.32	1
Cl−	0.98	0.83	0.87	0.92	0.57	−0.15	1
SO42−	0.66	0.49	0.64	0.59	0.30	−0.09	0.62	1
NO3−	0.36	0.18	0.12	0.42	0.13	0.08	0.27	0.14	1
Campaign 2018 (n = 31)
EC	1
Ca2+	0.82	1
Mg2+	0.89	0.69	1
Na+	0.97	0.71	0.86	1
K+	0.87	0.70	0.75	0.88	1
HCO3−	−0.36	−0.30	−0.29	−0.33	−0.21	1
Cl−	0.99	0.80	0.90	0.98	0.88	−0.36	1
SO42−	0.73	0.65	0.70	0.69	0.51	−0.38	0.69	1
NO3−	0.30	0.32	0.29	0.34	0.31	−0.11	0.27	0.28	1
Campaign 2019 (n = 30)
EC	1
Ca2+	0.92	1
Mg2+	0.56	0.38	1
Na+	0.93	0.95	0.35	1
K+	0.61	0.73	0.16	0.64	1
HCO3−	−0.23	−0.08	−0.39	−0.01	0.05	1
Cl−	0.97	0.96	0.51	0.97	0.65	−0.16	1
SO42−	0.80	0.68	0.78	0.67	0.40	−0.35	0.74	1
NO3−	0.20	0.34	−0.17	0.32	0.16	0.10	0.22	0.07	1

. A high correlation is defined as a correlation with an R-value greater than 0.7, while a moderate correlation is defined as a correlation with an R-value between 0.5 and 0.7 [72]. Table 2 displays the results of the primary hydrochemical parameter correlation. The strong positive associations between the EC and mainly the ions (Mg²⁺, SO₄²⁻, Na⁺, Cl⁻, and Ca²⁺) indicate these ions are essential in the hydrochemistry of groundwater. There are good corrections between Na⁺ and Cl⁻ as shown by these values of 0.96, 0.92, 0.98, and 0.97 in 2009, 2017, 2018, and 2019, respectively. The values of Mg²⁺ and Cl⁻ were 0.87 and 0.90 in 2017 and 2018, respectively. Cl⁻ and Ca²⁺ with 0.83 in 2017, 0.80 in 2018, and 0.96 in 2019. This implies that halite, gypsum, and carbonate may result from the dissolution of the major groundwater ions.

3.4. Major Ion Relations in the Groundwater

The relationship of primary ions has been plotted to illustrate the processes of hydrochemical evolution and the mechanism of control of the mineralization of groundwater. The ion ratio relationship in this area can further help explain the interactions between water and rock. Therefore, according to the hydrochemistry results, a ratio graph of the primary ion relationship is plotted (Figure 8). If the Na⁺/Cl⁻ molar ratio is approximately to 1, halite dissolution primarily contributes to the Na⁺ groundwater concentration; if the ratio is greater than 1, suggesting silicate weathering or cation exchange; and if the ratio is less than 1, an anthropogenic disruption is reflected [28,74].

Figure 8a depicts the ion connection between Na⁺ and Cl⁻ for the four campaigns of 2009, 2017, 2018, and 2019. A few groundwater samples were along the 1:1 trend line, while the others were above it, demonstrating that halite dissolution, silicate weathering, and cation exchange are all important sources of sodium. The saturation index (SI) of halite will further illustrate this view of the origin of Na⁺ and Cl⁻ (Figure 9). There is a strong association between Na⁺ and Cl⁻, as shown in Figure 8a, with R² = 0.90, R² = 0.77, R² = 0.86, and R² = 0.82 for the 2009, 2017, 2018, and 2019 sampling campaigns, respectively (Figure 8a), implying that the two minerals have the same origin. This hypothesis is confirmed by the negative halite SI values, indicating halite dissolution as an essential process in the study region (Figure 9).

The molar ratio of Ca²⁺ would be 1:1 if Ca²⁺ and SO₄²⁻ originated from gypsum weathering. The relationship between Ca²⁺ and SO₄²⁻ has been demonstrated in Figure 8b. Most of the groundwater samples along the 1:1 trend line have been observed, and Ca²⁺ rises with SO₄²⁻, indicating that gypsum weathering is a cause of Ca²⁺ and SO₄²⁻. The gypsum saturation indices are negative supports this hypothesis (Figure 9). However, the excess of Ca²⁺ relative to SO₄²⁻ observed in most samples is due to the reverse base exchange processes. Indeed, the saturation indices computed for these samples are similar to zero or more significant for some samples concerning carbonate minerals, demonstrating that calcium enrichment is primarily attributable to the occurrence of base exchange (Figure 8e). A positive correlation is demonstrated by the correlation diagram Ca²⁺ vs. Mg²⁺ (Figure 8c), which indicates that these two elements originate from the same source. Most of the samples are distributed over the dissolution section of the dolomite (1:1 line), demonstrating the contribution of the mineral to groundwater mineralization. Other points above the 1:1 line indicate that the base exchange process contributes to groundwater mineralization. The dolomite dissolution line is linked to most points in the Ca²⁺ versus Mg²⁺ diagram (Figure 8c). Several other locations are placed above the 1:1 line of Figure 8c due to reverse base exchange phenomena. The Ca²⁺ versus HCO₃⁻ correlation (Figure 8d) show that most of the samples analyzed in the study area had a Ca²⁺/HCO₃⁻ molar ratio above than one, indicating that these two components do not have a strong association. The presence of more Ca²⁺ than HCO₃⁻ confirms the role of ion exchange processes

3.5. Saturation Index (SI)

Several processes, such as groundwater flows, recharge and discharge processes, and water-rock reactions, control groundwater’s hydrochemistry [27,30]. The weathering of minerals in the long-term direction of groundwater flow also affects hydrochemistry [75]. The following Equation (8) can be used to calculate the saturation index (SI) of a mineral:

$$SI=log(\frac{K_{IAP}}{K_{SP}})$$

(8)

where, K_SP is the solubility product of the mineral, and K_IAP is the ions activity product for a mineral equilibrium reaction.

The SI values of groundwater minerals can be determined using the DIAGRAMMES program version 7 [76]. Furthermore, the Saturation Index results reveal the chemical equilibrium model of water minerals and water-rock interaction. The Saturation Index values for calcite, dolomite, gypsum, and halite, vary from −0.75 to 0.05, −1.1 to 0.34, and −2.36 to −1.81, −6.12 to −5.1 with a mean of −0.39, −0.52, −1.94 and 0.64, respectively for campaign 2009, from 0.12 to 1.02, 0.39 to 1.98, and −2.5 to −1.13, −6.43 to −4.05 with a mean of 0.51, 1.12, −1.75 and −5.56, respectively for campaign 2017, from −0.01 to 1.06, 0.24 to 2.22, −2.95 to −0.82, and −6.7 to −4.04 with a mean of 0.48, 1, −1.65 and −5.58, respectively for campaign 2018, from 0 to 1.42, −0.01 to 3.08, −2.21 to −0.56, and −6.32 to −3.76 with a mean of 0.62, 1.14, −1.55 and −5.42, respectively for campaign 2019. These values suggest that these minerals saturate many samples (Figure 9). The SI values for calcite, dolomite, gypsum, and halite range from −0.74 to 1.42, −1.1 to 3.08, −2.95 to −0.56, and −6.7 to −3.76, respectively for the four groundwater samples collected, indicating that gypsum and halite are not saturated in the water samples (Figure 9). This indicates that the samples have a propensity to dissolve these minerals constantly. The findings revealed that the phenomenon of base exchange and the dissolution of evaporated minerals (gypsum, anhydrite, halite and dolomite) influence the salinization of groundwater for the 105 groundwater samples taken in 2009, 2017, 2018 and 2019. If the mineral is unsaturated (SI less than 0), groundwater will continuously dissolve it; if the mineral is supersaturated (SI greater than 0), it will precipitate; and the mineral phase will remain in equilibrium if SI is close to zero.

3.6. Main Hydrochemical Processes

Gibbs developed a Gibbs diagram [77] to assess surface water changes quantitatively. However, they are still commonly used today in groundwater studies, as in our case in the KSOB sub-basin. The three major evolutionary processes of each of the Gibbs diagrams are divided into three sections: rock dominance firstly, which is in the center of the graph; secondly, evaporation dominance which is located in the upper part of the graph; and thirdly, precipitation dominance which is located in the lower part of the graph [77]. Figure 10 presented the highest part of the diagrams; most of the samples are plotted, demonstrating that rock weathering and water-rock interactions are the primary determinants of groundwater chemistry. However, in the evaporation dominance zone, several samples are found, which means that groundwater evaporation is also a significant factor influencing groundwater chemistry. To affect groundwater chemistry, the shallow depth of the water level makes the evaporation of groundwater powerful in the discharge region towards the Atlantic Ocean. Therefore, most of the samples in the diagram show a slightly increasing trend, again showing the effects of evaporation.

3.7. Groundwater Salinity

Groundwater is the principal drinking and agricultural water source in water-scarce areas, particularly in dry and semi-arid climates [4,5,8,10,72]. Climate change has recently strained this resource, causing its quality to deteriorate [1,18,78]. The spatiotemporal evolution of groundwater salinity in the KSOB sub-basin has been examined in this regard (Figure 11). The current research salinity values range from 0.83 to 1.76 g/L, with a mean of 1.09 g/L for the 2009 campaign samples (Figure 11a). For the 2017campaign collected points range from 0.39 to 4.27 g/L with a mean of 1.16 g/L (Figure 11b), from 0.45 to 4.87 g/L for the 2018 campaign samples with a mean of 1.39 g/L (Figure 11c), and finally range between 0.44 to 6.12 g/L for the 2019 samples with a mean of 1.38 g/L (Figure 11d). The KSOB sub-basin study area is marked by a lack of industrial activity, a decrease in rainfall, and an increase in temperature, which has resulted in recent drought cycles, lower groundwater levels, and degradation of water quality [12,20,42,69].

3.8. Water Quality Index (WQI) Calculated

The Water Quality Index (WQI) was used to measure the quality of groundwater for drinking purposes in the research area of Plio-Quaternary and Turonian aquifers using World Organization standards. The relative importance of each chemical parameter in the deterioration of water quality for domestic use determines the weight assigned to each chemical parameter, which ranges from one to five (Table 2). This analysis showed that the water quality index (WQI) ranged from 90.80 to 191.07 for 105 samples, with an average of 123. Therefore, groundwater samples were generally “good water” (23%) and “Poor quality water” (77%) for the campaign 2009 (Table 4). WQI ranged from 78.7 to 491.9 with an average of 159.4. Groundwater samples were generally “good water” (16.1%), “Poor quality water” (71%), “Very Poor quality water” (9.7%), and “Unfit for drinking” (3.2%) for the campaign 2017 (Table 4). The water quality index (WQI) ranged from 73.15 to 544.90 with an average of 168.53. Groundwater samples were generally “good water” (9.7%), “Poor quality water” (74.2%), “Very Poor quality water” (6.4%), and “Unfit for drinking” (9.7%) for the campaign 2018 (Table 4). The water quality index (WQI) ranged from 91.80 to 740.12 with an average of 187.23. Groundwater samples were generally “good water” (3.3%), “Poor quality water” (76.7%), “Very Poor-quality water” (13.3%), and “Unfit for drinking” (6.7%) for the campaign 2019 (

Table 5. Results of WQI and its percentage of four campaigns 2009. 2017. 2018. and 2019.

WQI Range	Type of Water	Campaign 2009		Campaign 2017		Campaign 2018		Campaign 2019
		Sample No.	Sample %	Sample No.	Sample %	Sample No.	Sample %	Sample No.	Sample %
<50	Excellent water	-	-	-	-	-	-	-	-
50–100.1	Good water	3	23	5	16.1	3	9.7	1	3.3
100–200.1	Poor water	10	77	22	71	23	74.2	3	76.7
200–300.1	Very poor water	-	-	3	9.7	2	6.4	4	13.3
>300	Unsuitable water for drinking	-	-	1	3.2	3	9.7	2	6.7

).

The spatial distribution of WQI in the KSOB sub-basin of groundwater samples collected in 2009, 2017, 2018, and 2019 is represented in Figure 12. It is evident that in most areas of the synclinal basin of Essaouira, the phreatic water was poor or good quality water. Following the results of the ten years of water quality index, we observed that water quality is deteriorating, particularly on the coast of the aquifers near the Atlantic ocean. The excessive fertilizer used in agriculture seeps into groundwater because the soil surface is close to the water table [10,26]. Therefore, as the hydraulic conductivity is critical, this region is susceptible; another reason is several tourist activities since there is no sanitation network or a water treatment station that generates wastewater infiltration directly onto the water table. Another reason is the phenomenon of marine intrusion. The calculated WQI values can be obtained by comparing the WQI spatial trends and the leading chemical indicators (Figure 4, Figure 5, Figure 6 and Figure 7). The spatial distribution of WQI is comparable to that of TDS, SO₄²⁻, Na⁺, and Cl⁻, implying that the high WQI values observed were primarily responsible for specific chemical parameters. Furthermore, since nitrate (NO₃⁻) was given the highest relative weight (5), it appears to be the main factor of WQI values. High nitrate (NO₃⁻) values were observed in the northwest of the study area near of diapir TIDZI, especially in the upstream part (Figure 4e, Figure 5e, Figure 6e, Figure 7e), and high WQI values were found in these areas (Figure 12).

3.9. IWQI Calculation

The sub-index model was applied to eleven water endpoints of the studied well for irrigation, including pH and electrical conductivity (EC), chloride (Cl⁻), bicarbonate (HCO₃⁻) ions, sodium percentage (%NA), sodium adsorption rate (SAR), protentional salinity (PS), magnesium hazard (MH), Permeability index (PI), Kelly index (PI) comparing it with the global standard [60,63].

The IWQI values ranged from 60.3 to 463, with an average of 105 for all campaigns (2009, 2017, 2018, 2019), according to the results provided in

Table 6. Minimum, maximum, and mean of the IWQI values of 105 samples in the study area.

Range	pH	EC	Cl−	NO3−	HCO3−	PI	%NA	SAR	MH	PS	KI	IWQI
Campaign 2009
Min	7.15	1671	6.15	0.00	1.80	65.37	50.05	3.29	55.48	7.31	0.98	75.42
Max	7.69	3520	21.63	3.21	3.80	85.54	77.30	11.31	66.60	22.93	3.36	149.90
Mean	7.37	2193.77	10.52	0.61	2.99	76.79	64.64	6.08	60.14	11.67	1.93	98.95
Campaign 2017
Min	7.1	724	4.81	0.10	3.10	33.13	29.12	1.99	39.29	4.98	0.40	60.28
Max	8	7555	88.52	2.04	9.30	76.42	65.26	15.08	65.47	91.20	1.83	320.55
Mean	7.57	2217.77	18.92	0.53	5.53	54.68	43.94	4.14	50.25	19.90	0.82	106.58
Campaign 2018
Min	7.2	916	2.79	0.00	0.20	44.39	30.13	1.74	26.74	3.06	0.43	60.58
Max	8.65	9744	89.08	6.42	9.00	73.34	65.29	15.28	59.99	92.44	1.83	352.29
Mean	7.68	2753.87	18.08	0.62	4.43	56.40	46.03	4.49	46.54	19.41	0.89	110.31
Campaign 2019
Min	7.09	880	6.39	0.00	2.46	43.33	32.12	1.85	7.03	6.77	0.47	66.71
Max	9.11	12,250	135.39	6.45	10.80	79.71	68.29	17.09	61.03	140.05	2.12	462.91
Mean	7.62	2775.4	22.97	0.62	6.26	60.29	49.69	5.47	41.43	24.48	1.09	124.54

. When compared with water quality classification, it was found that 83.8% of the studied water samples were of good water quality class, and 46.2% were bad water quality for the campaign 2009. Groundwater samples were generally “good water” (48.4%), “Bad quality water” (48.4%), and “Unfit for drinking” (3.2%) for the campaign 2017 (

Table 7. Statistical analysis of the effective weight.

Parameters	Weight	Relative Weight	Effective Weight (%)
			Min	Max	Average
PH	4	0.09	1.52	25.41	10.54
EC	5	0.11	5.78	24.77	12.44
Cl−	3	0.07	3.14	19.94	10.25
NO3−	3	0.07	0.00	14.84	1.60
HCO3−	3	0.07	0.12	7.56	4.17
PI	5	0.11	2.13	17.44	9.09
%NA	4	0.09	2.09	11.52	7.26
SAR	5	0.11	1.29	5.32	2.72
MH	4	0.09	0.55	16.14	8.92
PS	5	0.11	8.19	49.11	26.23
KI	3	0.07	1.75	16.45	6.78

). Groundwater samples were generally “good water” (61.3%), “Bad quality water” (32.26%), “Very bad quality water” (3.22%), and “Unfit for drinking” (3.22%) for the campaign 2018 (Table 7). Groundwater samples were generally “good water” (50%), “Bad quality water” (43.3%), and “Unfit for drinking” (6.66%) for the campaign 2019 (Table 7).

An IDW spatial variation map of IWQI values was produced in an ArcGIS environment to visualize the spatial distribution of water quality over each area (Figure 13). This map was utilized to manage water resources better to locate irrigation water quality classification sites in the research area. According to Figure 13, all IWQI values for the four campaigns (2009, 2017, 2018, and 2019) are above 50, indicating an absence of excellent water classification of drinking water. Figure 13 and Table 7 show that the irrigation water quality index (IWQI) values were relatively high from the 2009 to 2019 campaigns, and this is due to the first significant factor, which is the effect of climate change that leads to a decrease in rainfall and therefore a rise in the concentration of the major ions [11,19].

The ArcGIS Spatial Analyst tool and equation number seven were used to calculate the effective weight values of each water quality measure. Table 7 shows the statistical findings of comparing the effective weights to the relative weights of each water quality measure. According to the calculations, the PS parameter has the largest average effective weighting value of 26.23%, and these parameters are the most influential in the IWQI calculations. On the other hand, Chloride has a higher relative weight (9.09%) than the other variables. Different parameters with low relative weight, such as (HCO₃⁻, SAR; NO₃⁻), also have low effective weight (Table 7). Additionally, pH and electrical conductivity have high effective weights of 10.54% and 12.4%, respectively.

3.10. Heavy Metals

The concentrations of most heavy metals analyzed (e.g., Cr, B, Ni, Cd, and As) in all the analyzed samples of the 2019 campaign (

Table 8. Metals contents results of analysed samples of the 2019 campaign.

Sample	T	pH	EC	B	Ni	Cr	Cd	As	Aquifer
	°C		µS/cm	µg/L
L1	21.3	9.2	2011	270	2.73	<2	<0.5	<2	PQ
L2	20.6	9.5	16,300	1050	7.91	<2	<0.5	10.76	PQ
L3	20.4	7.3	1780	220	2.91	<2	<0.5	4.74	PQ
L4	23	8.8	4460	320	6	<2	<0.5	<2	PQ
L5	22.5	9.2	863	180	<2.5	<2	<0.5	<2	PQ
L6	23.2	8.9	941	170	<2.5	<2	<0.5	<2	PQ
L7	22.4	7.64	1396	100	<2.5	<2	<0.5	<2	PQ
L8	23	7.5	1898	150	4.25	<2	<0.5	<2	PQ
L9	22.65	9.4	4888	630	2.89	<2	<0.5	4.34	PQ
L10	20.8	8	1942	390	2.64	<2	<0.5	8.2	PQ
L11	21.43	7.55	1310	130	<2.5	<2	<0.5	8.06	PQ
L12	22.83	9.27	3169	550	17.27	<2	<0.5	<2	PQ
L13	24	7.4	1962	150	3.62	<2	<0.5	6.25	PQ
L14	22	7.47	1620	120	3.27	<2	<0.5	<2	PQ
L15	22.3	9.5	3500	430	5.96	<2	<0.5	<2	PQ
L16	21.5	7.6	1600	110	<2.5	<2	<0.5	2.27	PQ
L17	25	7.64	1610	100	4.47	<2	<0.5	<2	PQ
L18	22.55	7.36	1910	160	3.9	<2	<0.5	8.55	PQ
L19	22.6	7.85	1236	230	7.38	<2	<0.5	7.74	PQ
L20	23.2	9.6	2480	140	4.66	<2	<0.5	<2	PQ
L21	23.2	9.7	2621	440	4.63	<2	<0.5	7.24	PQ
L22	22	9.8	2116	290	<2.5	<2	<0.5	2.12	PQ
L23	21	9.5	1820	230	<2.5	<2	<0.5	4.14	PQ
L24	22.8	8.58	2470	140	4.55	<2	<0.5	<2	PQ
L25	22.4	9.5	5930	1030	4.67	<2	<0.5	<2	PQ
L26	24.2	9	2509	160	3.93	<2	<0.5	7.73	PQ
L27	21.4	7.8	1363	110	<2.5	<2	<0.5	8.61	PQ
L28	23.37	7.4	2247	230	<2.5	<2	<0.5	<2	PQ
L29	26.7	8.54	3851	250	5.44	<2	<0.5	<2	PQ
L30	25	9.2	2270	150	2.7	<2	<0.5	3.47	PQ
L31	24.7	9.7	2470	190	2.79	<2	<0.5	3.99	PQ
L32	28	7.19	1857	120	6.89	<2	<0.5	8.58	T
L33	29	7.18	1768	110	17.65	<2	<0.5	3.89	T
L34	25	8.8	2190	250	<2.5	<2	<0.5	3.32	T
L35	22.45	8.85	2457	200	5.7	<2	<0.5	10.34	T
L36	24.5	9.1	2510	190	3.23	<2	<0.5	<2	T
L37	26.7	8.04	1500	110	4.53	<2	<0.5	5.97	Wadi upstream
L38	27.11	9.9	3040	320	4.7	<2	<0.5	5.83	Wadi downstream
		6.5–8.5	1500	500	70	50	3	10	WHO

) were found to be below the detection limit of the analytical methods applied.

The electrical conductivity (EC) in the study area ranged from 863 μS/cm to 16,300 μS/cm for the campaign of July 2019. The maximum values were recorded on wells that are near the sea (Figure 14A).

The study area contains the highest concentration of boron among the trace/minor elements. Its concentration varies from 100 to 1050 µg/L. With sodium and potassium, it shows strong positive associations, respectively (Figure 14B). The geographic distribution of B contents (Figure 14B) increases from northeast to southwest in a manner comparable to that of Cl⁻ (Figure 7c) and Na⁺ (Figure 7g). The points with high salinity are those where the greatest concentrations of B are found; these include points L2, L9, L12, and L25. The spatial distribution of each heavy metal is depicted in Figure 14.

The amount of nickel in measured groundwater is considerably lower than the drinking water standard of 70 µg/L established by WHO [60] (Table 8). In ferromagnesian minerals like olivine, orthopyroxene, spinel, pyrite and chalcopyrite, this relatively abundant element in rocks easily takes the place of iron and magnesium. Even when water interacts with nickel-rich rocks such as olivine basalts and ultramafic rocks (which typically contain 2000 mg/kg), groundwater nickel concentrations are often below a few µg/L. Figure 14C shows that the Ni contents, in particular at the level of sample L12 and L33, has the highest Ni contents.

Arsenic levels for the study area range from less than 2.12 to 10.76 µg/L. The highest value (WHO drinking water criteria of 10 µg/L) is noted at well L2 and L36 (Table 8). The western and northwest regions of the search area had the highest values, according to the spatial distribution of As contents (Figure 14D).

3.11. Water Stable Isotopes (δ²H-δ¹⁸O)

Isotopic analysis is a useful tool for deciphering the mechanisms that drive an aquifer system’s hydrogeological and hydrochemical evolution [26,79,80]. Stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H) are thought to be transported conservatively in shallow aquifers, according to Kim [81]. The source and movement of groundwater, as well as the technique of aquifer recharge, are revealed by these two isotopes [81]. According to Geyh [82], they can also provide physical processes that affect the body of water, such as evaporation and mixing. The source of groundwater salinity can be determined using stable isotopes [10,24].

Locations sampled in Plio-Quaternary and Turonian aquifers of KSOB sub-basin had oxygen-18 levels ranging from −5 to −1.8 and −5 to −4.4, respectively (

Table 9. Statistical summary of the stable isotopic values of the campaign 2018.

Sample	pH	T	EC	δ2H	δ18O	Cl− (meq/L)
11/51	8.4	17.6	9744	−8.9	−1.8	89.08
15/51	7.8	19.8	1557	−23	−4.5	7.11
21/51	7.4	23.3	4933	−26.1	−4.7	38.29
27/51	7.8	22.2	916	−25.5	−5	2.79
105/51	7.5	22.7	2187	−19.6	−2.6	11.96
125/51	8	26.3	2716	−25.2	−3.9	15.29
148/51	7.5	21.2	1602	−18.7	−3.3	8.98
149/51	7.4	23.1	3482	−22.5	−3.7	21.58
272/51	7.5	22	1957	−29.1	−4.4	9.86
327/51	7.7	21.9	3608	−14.6	−2.9	28.34
O2	7.9	25.2	1960	−24.5	−4.5	10.96
O6	7.3	21.7	2176	−27.2	−4.2	10.61
O8	7.9	20.5	2731	−29.7	−4.8	18.68
O91	7.6	23.2	3034	−24.8	−4.3	21.73
O94	7.4	20.7	3408	−21.5	−3.7	22.54
O96	8.1	20.7	1842	−18.7	−3.7	8.67
O111	7.2	23.6	2794	−25.1	−4.4	17.75
O113	8.1	21.3	6716	−22.5	−4.2	54.44
M98	7.2	23.2	2699	−28	−4.5	16.29
346/51	7.3	27.1	1967	−28	−4.4	9.92
380/51	7.9	21.5	2428	−28.6	−5	13.34
386/51	7.8	22.3	2638	−27.3	−4.9	15.24
EL1	8.2	20.7	1896	−9.6	−0.7	10.69
EL2	8.7	25.8	2965	−15.9	−1.7	20.15
O121	6	23.8	48	−26.2	−5.8	not measured

). The GMMM and RMML lines on the δ²H-δ¹⁸O correlation graphic show the distribution of representative samples from the study area of the KSOB sub-basin (Figure 15) provides a better understanding of the main phenomena involved in the hydrodynamic and geochemical functioning of defined aquifers [4]. In the δ ²H vs. δ ¹⁸O plot scheme (Figure 15), all isotopic points are represented simultaneously for the Essaouira basin with the Global Meteoric Water Line (G-MMM) (Equation (9)) [83] and the regional meteoric water line (R-MWL) was developed by the researchers Mennani [55] indicated by the equation (Equation (10)).

$$\mathsf{\delta }{}^2\mathrm{H}=8\times \mathsf{\delta }{}^{18}\mathrm{O}+10$$

(9)

$$\mathsf{\delta }{}^2\mathrm{H}=7.96\times \mathsf{\delta }{}^{18}\mathrm{O}+11.30$$

(10)

Most of the sites lie along straight lines of GMWL and RMWL, indicating that Atlantic precipitation recharges the region’s aquifer (group 1). The hydrogeochemical results, particularly well 27/51, which has low salinity with the value = 454 mg/L, are perfectly compatible with the rainwater supply of the shallow aquifer located in the SIDI KAWKI region, which is the cause of the drop in salinity of the fluids of these wells. It is the well that is closest to the freshwater pole (rainwater pole). There are other points which characterize by the recharge of rainwater, such as point O6 which is located near wadi KSOB. The lithological characteristics of the unsaturated zone, as well as its thickness, should facilitate this recharge. The majority of the samples in this group come from the shallow aquifer, while the rest of the water points (M98, 346/51...O121) come from the deep Turonian aquifer.

In contrast, the waters from the Group 1 wells show no signs of evaporation, indicating that precipitation is rapidly infiltrating them. Their location below the GMWL line distinguishes them from the other water points (Group 2); They are arranged in a straight line with an evaporation characteristic slope of less than eight. There are other processes that mainly affect surface waters upstream O98 (EL1) and downstream O99 (EL2) and boreholes 105/51 and 327/51, respectively, in the study area (Figure 16). In the unsaturated zone, evaporation is likely to occur before water infiltration, or during sampling. The isotopic signature of rainwater and saltwater in the Atlantic Ocean has been used to draw the freshwater-saltwater boundary [25,79]. On the same plot, well 11/51, located near Cap Sim on the coastal edge, has high salinities and a drop in the piezometric level (since 2015). This demonstrates that the enhanced mineralization in this well is mostly due to the phenomena of saltwater intrusion. The regional altitudinal gradient in oxygen-18 of −0.26 was used to determine the assumed recharge zones for the study area [32,50].

The points have undergone evaporation (105/51 and 327/51), and marine intrusion (11/51) has been eliminated from the δ¹⁸O vs. altitude diagram (Figure 17). From this, we can deduce that the altitudes of the recharge areas of the Shallow aquifer vary between one hundred and eight hundred meters, and those of the Turonian recharge vary between 550 and 800 m. Some water points (3/51, 125/51, 148/51, 149/51, and O96) capturing the Plio-Quaternary aquifer are recharged at altitudes varying between 100 and 350 m. at the same time, the rest of the points should be recharged at altitudes oscillating between 450 and 800 m. However, the altitudes of the TIDZI DIAPIR (eastern limit of the two aquifers) do not exceed 400 m. The differences in the isotopic compositions between the two aquifers, and those of the precipitation (with which the gradient was estimated) cannot be due to an altitude effect. However, this depletion may be due to recharge during winter periods.

4. Conclusions

A comprehensive study of the hydrochemical data of 105 water samples from the Essaouira synclinal basin was carried out to provide a basis for understanding the origin, distribution, and associated hydrogeochemical evolutions of the primary ions in the downstream part of the Essaouira basin. Water quality is influenced by various factors, including contact time of groundwater with rocks and anthropogenic pollutants.

This study used multivariate statistical analysis and index techniques (WQI and IWQI) based on the GIS environment to explore water quality and suitability. Groundwater in the KSOB sub-basin exhibits a variety of hydrochemical facies, including mixed Ca-Mg-Cl water (52%) and Na-Cl water (48%). The results indicate that Na⁺ is the dominant cation and Cl⁻ is the dominant anion in the study area. Most of the groundwater-dominated by Na−Cl facies indicates that the rock-water interaction and evaporation are dominant processes in the study area. Furthermore, the patterns of the dominance of the major anions and cations, which are found in order of Cl⁻ > HCO₃⁻ > SO₄²⁻ > NO₃⁻, and Na⁺ > Ca²⁺ > Mg²⁺ > K⁺, respectively.

The spatial-temporal evolution of groundwater quality demonstrates a progressive degradation in time and space. Results of WQI of campaign 2019 showed that 6.7% of groundwater samples are unsuitable for drinking, 76.7% are poor quality water, and 13.3% are very poor-quality water, while only 3.3% of samples are potable for WQI, and according to IWQI, the total study area has split into 50% (good areas), 43.3% (bad areas), and 6.6% (unfit areas), respectively, and no excellent groundwater areas have been identified.

The concentration of heavy metals (e.g., Cr, Ni, B, Cd, and As) in all samples analyzed are found to be below the detection limit.

The δ¹⁸O–δ²H diagram for the water samples showed that the aquifer recharge is supported by direct infiltration of oceanic precipitation, with negligible evaporation.

Furthermore, the altitudes of the recharge areas of the Plio-Quaternary aquifer vary between 100 and 800 m, and those of the Turonian recharge vary between 550 and 800 m.

For a better understanding of the geochemical processes of groundwater evolution in this region and other similar areas, the findings of this study may provide a good reference. Furthermore, hydrochemistry characteristics and groundwater evolution can direct the selection of water resource areas and provide knowledge for detailed assessment and conservation of groundwater resources.