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The use of GIS and water quality index to assess groundwater quality of krimat aquifer (Essaouira; Morocco)

The use of GIS and water quality index to assess groundwater quality of krimat aquifer... The aim of this present study was to evaluate groundwater quality in the upstream part of the Essaouira basin. A detailed geochemical study of groundwater region is described, and the origin of the chemical composition of groundwater has been qualitatively evaluated, using multivariate statistical methods (PCA, HCA), and Water Quality Index ( WQI) was used to determine the suitability of water for drinking. To attempt this investigation, 38 samples were analysed for various physicochemical parameters such as temperature, pH, TDS, Na, NO , K, Ca, HCO , Cl, Mg, and SO . The results obtained 3 3 4 showed that the facies characterizing the study area was a combination of Ca–SO and mixed Ca–Mg–Cl. Hydrochemi- cal approach based on the bivariate diagrams of major ions indicates that the origins of groundwater mineralization are the result of (I) evaporite dissolution; (II) cation-exchange reactions; and (III) evaporation processes. The WQI values range from 82.3 to 390.9, and therefore the water samples can be categorized into five groups: excellent water to water unsuitable for drinking. In global, 61% of the groundwater sampled had poor water quality, 18% were very poor water quality, 16% are unsuitable for drinking, and just 6% represent a good quality. However, the results of this paper indicate that most water is not safe for drinking and needs further treatment. Keywords WQI · Multivariate statistical · Essaouira · Groundwater quality · Hydrogeochemistry · GIS 1 Introduction such as topographic relief, rainfall, mineral dissolution, ion exchange, oxidation, reduction, human and natural activi- Water is a fundamental human need and according to the ties, use of fertilizers and pesticides [5–8]. statistics groundwater is the main source of drinking water In arid and semi-arid areas, principally in coastal areas, for more than 1.5 billion people in the world[1]. With a an increase in the salinity is being confirmed in most of better understanding of the importance of drinking water the major aquifers being used for water supply in coastal quality to human health, there is a great need to assess regions, which led to the deterioration in water quality groundwater quality [2]. Moreover, it is a need for studies [9–14]. This deterioration is due to the inflow of saline on how groundwater will be managed. For efficiency, the water because of over-exploitation of groundwater, and/ management and assessment of groundwater resources or mobilization of saline formation waters (combining with need an understanding of hydrogeochemical and hydro- ancient seawater trapped in the sediments). However, the geological features of the aquifer [3, 4]. Furthermore, assessment of groundwater quality in these areas is essen- groundwater quality depends on several components tial for better management and protection of this resource. * Otman El Mountassir, otman.elmountassir@ced.uca.ma | High Energy and Astrophysics Laboratory, Faculty of Sciences Semlalia, Cadi 2 3 Ayyad University, Marrakech, Morocco. IWRI Mohammed VI Polytechnic University, Hay My Rachid, 43150 Ben Guerir, Morocco. CESBIO, Université de Toulouse, CNRS, CNES, IRD, BPI 280, 31065 Toulouse CEDEX 9, France. SN Applied Sciences (2020) 2:871 | https://doi.org/10.1007/s42452-020-2653-z Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z In recent decades, several tools have been used to precipitation, geological structure, and mineralogy of quantify status and water chemistry. Among these tools, the watershed sand aquifers and geochemical processes the water quality index [15, 16] is one of the most effective within the aquifer [27–30]. The piezometric study shows tools for assessing and obtaining a comprehensive pic- that the natural discharge zone of the studied aquifer is ture of groundwater quality. It is a mathematical technique the Atlantic Ocean and that the groundwater flows mainly used to transform high quantities of water characteriza- from south-east to north-west upstream and from east to tion data into one simple indicator that expresses overall west downstream (Fig. 1). This direction of flow is condi- water quality, to differentiate between very clean water tioned by the geometry of the aquifer and the tectonic. and polluted water at some location and time [17–21]. Essaouira Basin, the subject of this study, is one of the semi-arid basins of Morocco. In this coastal basin, ground-3 Materials and methods water is the main water resource. During the last decades, this basin has experienced a succession of drought epi-3.1 Chemical analysis sodes under the climate change effect leading to a quali- tative and quantitative degradation of this resource [22]. Groundwater samples were collected in March 2018, from However, the main objective of this study is to evaluate 38 wells capturing the krimat aquifer and representing a and map the groundwater quality status of krimat aquifer homogeneous spatial distribution on the whole aquifer situated in Northwestern Morocco by using Water Quality (Fig. 1). Index and Geographic Information System. A portable GPS was used to locate the sampling wells and polyethylene bottles were carefully rinsed two to three times by the water collected before filling. The phys- 2 Study area icochemical parameters (pH, temperature, electrical con- ductivity) were measured in situ immediately after sample The Ouazi Basin is located in the east and north of the collection, using the Multi-parameter HI 9828. The depth Essaouira city between the coordinates 100,000 and of the water level was measured using a piezometric probe 140,000 (m) for the X and between 80,000 and 140,000 (m), with 200 m of length. 31°23′53.12″N and 9°25′45.78″W (geographic system pro- Chloride ions are determined by Mohr’s method. Con- jection), with an area of 1000 km (Fig. 1). It is limited in the centrations of HC O were determined by titration, using north by Hadid anticline, by Meskala region in the south, 0.1 N HCl. Sodium (Na) and potassium (k) ions are deter- by Mramer wadi in the east, and Atlantic Ocean in the mined by flame atomic absorption spectrometry. The sul- west. This basin is controlled by a semi-arid climate, with phates are determined by spectrophotometry method an average annual rainfall of 300 mm and temperatures of using a Hach Lange DR 3800 spectrophotometer. Con- 20 °C [23]. In geomorphological terms, the Essaouira syn- centrations of calcium by following the complexometry clinal zone is less rugged, with a lower relief characterized (EDTA) and magnesium (Mg) were obtained from total by low hills and shaped by a sparse water system. Concern- hardness. These chemical analyses were carried out at the ing the hydrogeological aspect, the Ouazzi Wadi sub-basin Laboratory of Geosciences and Environment (LGE) of Ecole is a sedimentary basin, mainly composed of two main Normale Superieure, of Marrakech, Morocco. The accuracy aquifers (Fig. 1). The first is the Plio-Quaternary phreatic of the chemical analysis was verified by calculating ion bal- aquifer with marine or dune sandstone–limestone matrix, ance errors in Eq. (1), which is based on the principle that and a primary hydraulic conductivity due to porosity. The the sum of major anions and the sum of the major cations wall of this aquifer is formed by the Senonian grey marls; are equivalent (concentrations expressed as (meq/L)) and the subcrop anti-Pliocene shows that the Plio-Quaternary the error in % is given by (1) can be in direct contact with the Triassic and Cretaceous �∑ ∑ � cations anions other levels [24]. The second is the Cenomanian–Turonian IB = × 100 ∑ ∑ (1) carbonate aquifer; it is mainly formed by limestones and cations anions dolomitic-limestone layers (Fig. 1). The base of the Cenom- A chemical analysis of the waters is not considered rep- anian–Turonian system corresponds to lower Cenomanian resentative and acceptable only when the ionic balance is grey clays and the top to the Senonian white marls [25]. equal to or less than 10% [31]. This reservoir is the main food resource of drinking water of Essaouira city as well as the surrounding villages. It is also a source of modest agricultural use (food-type) [26]. In addition, the chemical composition of groundwater is controlled by many factors that include composition of Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 1 Geographic situation, location of groundwater sampled points in Wadi Ouazi basin, geological and cross section of the study area Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z 3.2 GIS analysis 3.3 Water quality index There are two main interpolation techniques: determin- The WQI is a very simple technique for evaluating the istic and geostatistics. Deterministic interpolation tech- overall water quality of any region and communicat- niques create a surface from measured points, based on ing this information with the decision-makers; analysis their extent of similarity [e.g. inverse distance weighted of the water samples for various parameters is done as (IDW )] or the degree of smoothing (e.g. radial basis func- per WHO standards [33]. From the estimation of a water tions). Geostatistical interpolation techniques utilize the quality index is determined the degree of pollution of statistical properties of the measured points [32]. groundwater by using Geographical Information Sys- For this study, a weighted inverse distance interpola- tem Software (GIS) issues by integrating complex data tion (IDW ) method was used to produce thematic spatial and generating a score, which ultimately describes the distributions for each parameter: EC, TDS, pH, NO , Ca, Mg, water quality status [34–36]. The methodology used is K, Na, Cl, HCO and SO , and water quality index (WQI) of summarized in the flowchart established in Fig.  2. The 3 4 the study area of krimat aquifer. Interpolation technique results of the physicochemical analyses are summarized is the procedure of predicting unknown values using the in ( Table 1). known values in the vicinity. This technique uses a defined or selected area of sample points to estimate the value of the output grid cell. Fig. 2 Flow-chart of the meth- odology adopted Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Table 1 Physicochemical No T pH EC TH TDS Cl SO NO HCO Na Ca Mg K 4 3 3 parameters of groundwater samples of study areas °C µs/cm mg/l S1 22.6 7.53 1925 703.3 958 369.2 178.5 48.6 433.2 119.8 133.1 90.4 4.9 S2 23.4 7.24 2769 1126.5 1387 582.2 291.6 37.0 482.0 176.0 189.2 159.4 3.0 S3 22.3 7.25 2793 918.9 1400 624.8 284.3 40.0 396.6 176.0 158.7 127.3 2.1 S4 22.4 7.15 3363 1102.8 1686 781.0 294.1 33.8 433.2 232.2 200.4 146.8 3.6 S5 21.2 7.65 2216 647.2 1117 482.8 161.3 20.0 414.9 187.9 113.8 88.5 0.3 S6 20.4 7.33 4062 887.9 2031 908.8 163.8 165.6 335.6 300.3 221.2 81.6 20.9 S7 20.8 7.67 1650 383.9 825 383.4 67.9 13.0 360.0 180.7 93.0 36.9 0.8 S8 21.8 7.35 2198 775.2 1095 511.2 48.2 7.2 634.6 158.3 144.3 101.1 7.5 S9 21.7 7.25 2152 615.3 1077 468.6 65.4 31.1 512.5 182.0 112.2 81.6 3.0 S10 21.6 7.34 3184 1055.6 1597 766.8 213.0 76.4 274.6 208.6 248.5 105.9 25.9 S11 23.0 7.47 2200 775.0 1101 468.6 185.9 27.0 427.1 140.5 133.1 107.9 2.7 S12 21.6 7.56 4372 1349.6 2188 1164.4 210.5 60.5 433.2 303.3 184.4 216.8 2.4 S13 21.9 7.88 2141 1046.6 1070 284.0 363.0 64.5 427.1 99.1 174.7 148.7 6.3 S14 22.4 8.36 2359 983.0 1180 355.0 215.4 7.0 689.5 105.0 186.0 126.4 11.7 S15 21.7 7.47 2170 1030.3 1082 312.4 313.8 24.3 604.1 128.7 152.3 158.4 4.1 S16 22.9 7.8 2214 894.9 1106 397.6 328.5 6.0 457.6 128.7 158.7 121.5 2.9 S17 23.1 7.23 3256 2183.2 1631 184.6 1361.3 3.5 372.2 57.7 513.0 219.7 4.3 S18 20.6 7.65 2429 815.0 1216 497.0 139.2 18.0 402.7 275.6 139.5 113.7 2.2 S19 20.4 7.32 4802 2156.6 2404 823.6 751.5 166.0 500.3 264.8 322.2 329.5 2.8 S20 17.9 7.85 2196 991.2 1099 284.0 372.8 60.6 262.4 95.7 200.4 119.6 5.3 S21 18.5 7.65 2801 1230.9 1401 440.2 458.9 35.5 347.8 155.3 240.5 153.6 7.3 S22 22.0 7.34 1248 499.8 626 184.6 11.3 21.6 335.6 37.0 117.0 50.5 1.8 S23 16.2 8.14 1350 671.5 674 170.4 119.5 18.2 329.5 34.0 141.1 77.8 2.5 S24 17.0 7.65 3691 2375.5 1848 241.4 2221.2 8.0 311.2 75.4 583.6 223.6 1.9 S25 20.7 7.47 1966 975.1 981 355.0 335.9 17.2 378.3 57.7 187.6 123.4 6.0 S26 16.2 7.91 1747 559.7 874 198.8 88.3 82.7 286.8 96.2 125.0 60.3 6.8 S27 18.5 7.83 1297 447.6 649 227.2 85.5 33.5 360.0 81.4 85.0 57.3 4.8 S28 20.5 7.67 1624 783.3 813 213.0 343.3 7.0 335.6 87.3 153.9 97.2 4.5 S29 19.9 7.52 1571 806.9 786 213.0 289.2 33.2 353.9 96.2 134.7 114.7 2.4 S30 23.2 7.57 1163 679.2 581 198.8 176.1 19.3 329.5 37.0 123.4 90.4 2.3 S31 18.4 7.76 1198 503.9 599 213.0 65.4 19.0 317.3 63.6 121.8 48.6 3.8 S32 21.5 7.55 1694 735.5 847 255.6 220.3 35.1 347.8 63.6 157.1 83.6 2.7 S33 20.4 7.93 809 399.5 404 99.4 45.7 15.6 372.2 10.4 72.1 53.5 0.8 S34 20.4 7.76 778 375.5 390 142.0 43.3 19.0 299.0 19.2 65.7 51.5 0.6 S35 19.7 8.15 4133 2413.1 2069 681.6 1184.3 6.4 488.1 182.0 426.5 328.5 5.5 S36 19.3 8.75 1386 671.3 694 213.0 227.7 12.2 347.8 60.7 125.0 87.5 6.6 S37 21.0 8.49 1600 439.9 800 369.2 58.0 28.3 256.3 143.5 105.8 42.8 0.4 S38 19.5 8.83 5041 1789.8 2520 1178.6 633.4 23.0 396.6 279.6 312.6 245.9 36.5 Min 16.2 7.15 778 375.5 390 99.4 11.3 3.5 256.3 10.4 65.7 36.9 0.3 Max 23.4 8.83 5041 2413.1 2520 1178.6 2221.2 166 689.5 303.3 583.6 329.5 36.5 Mean 20.7 7.7 2356.5 968.4 1179.1 427.5 332.0 35.4 396.0 134.2 185.7 123.0 5.6 SD 1.9 0.4 1087.2 541.8 544.4 271.3 424.9 36.8 98.1 81.1 112.5 71.5 7.2 similarity and dissimilarity in the chemistry of groundwa- 4 Results and discussion ter samples based on the anions and dominant cations of all samples [37, 38]. In addition, these trilinear dia- 4.1 Groundwater hydrochemical facies grams used for tracing hydrochemical data were inde - pendently developed by [39, 40]. Hydrochemical facies is a useful tool for determin- ing groundwater chemistry. It is used to represent the Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z The projection of the analysed samples on the Piper The correlation between Ca and SO (Fig. 4c) shows a diagram (Fig. 3) shows that the majority of the samples are high positive correlation between these two ions in the Ca–Mg–Cl, while two points have a Ca–SO facies. samples with R = 0.89. This positive correlation indicates In order to highlight the different mechanisms that con- that these two ions have the same source. In addition, tribute to groundwater mineralization, the relationships Fig. 4c shows that only few samples are close to the dis- between major elements were investigated in several solution line of gypsum, indicating that the dissolution of bivariate diagrams plotted (Fig.  4). These diagrams that gypsum and anhydrite is limited [25]. were plotted take into account the most abundant min- The relationship between Ca and H CO (Fig. 4d) is low erals (calcite, dolomite) and evaporates (halite, gypsum) with R = 0.013. This weak correlation supports the absence generally existing in sedimentary deposits. of a relationship between these two ions. From Fig. 4d, it The binary diagram for Na and Cl (Fig. 4a) shows a posi- can be seen that the C a concentration increases, while the tive correlation between these two ions, with R = 0.83 for HCO concentration remains relatively constant [9]. the Ouazzi basin. This positive correlation indicates the same source of the two ions. Some samples are close to 4.2 Multivariate statistical analysis the halite dissolution line. Other samples are placed below the line, indicating a deficit of Na v Cl; this Na deficit is bal- To understand different water types in the study area, 2+ 2+ anced by an excess of Ca and Mg , indicating a cation- statistical approach of the obtained results must be of exchange process [14]. high importance. However, hierarchical clustering analy- The correlation diagram for Ca and Mg (Fig. 4b) shows sis method (HCA) and principal component analysis (PCA a positive correlation between the two cations reflecting are used to distinguish between water groups that have the same source with R = 0.60. A few samples are plot- similarities in hydrochemical composition [41]. Indeed, ted around the dissolution line of dolomite, indicating a HCA and PCA were carried out on 38 individuals (water limited contribution of this mineral to groundwater min- samples) and 9 variables (TDS and 8 major elements) using eralization [9]. Ward method with Euclidean distance. Fig. 3 Piper trilinear diagram Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 4 Correlation diagram: a Na versus Cl; b Ca versus Mg; c Ca versus SO ; d Ca versus HCO 4 3 Dendrogram of variables allowed separating two with the F1 axis (Fig. 3). As a result, this axis represents the groups (Fig. 5). Group 1 is formed by SO , Cl, and HCO , cluster responsible for the mineralization of water in the 4 3 while group 2 is formed by Ca, Mg, NO , Na, and K. The cor- study area. However, the more the F1 axis components are relation between these variables is presented in Table 2. positive, the more the wells have a high concentration of As shown in Table 2, TDS, Na, and Cl have a strong cor- major ions (Fig. 6). NO and H CO are positively correlated 3 3 relation with a correlation coefficient of 0.77 and 0.85, with the F2 axis; therefore, the positive components on respectively. This suggests that the dissolution of evapor- this axis are enriched by the nitrates and the bicarbonate. itic minerals and the paleo-seawater intrusion contribute This reflects the presence of another phenomenon respon- to the groundwater mineralization in the study area [2, sible for these ions [14]. 42]. The strong positive correlation between Ca and Mg indicates that they are probably due to carbonate and 4.3 Physicochemical parameters dolomite dissolution, base exchange, and paleo-seawater intrusion [2, 42]. The low correlation between HC O and Groundwater temperatures (Table 1) varied from 16.2 to Ca (0.03) and between HC O and Mg (0.35) confirms the 23.4 °C, with an average and standard deviation values of contribution of carbonate mineral dissolution and paleo- 20.7 °C, and 1.9 °C, respectively. seawater intrusion in the groundwater mineralization in The pH values vary from 7.15 to 8.83 (Table. 1) indicat- the study area. A strong positive correlation between SO ing that groundwater is slightly alkaline. All samples had a and Ca was observed. This correlation is probably due pH values within the acceptable limit “6.5–8.5” except two to the evaporitic mineral dissolution. The weak correla- samples with values above the permissible limit fixed by tion between SO and NO with a correlation coefficient WHO [33]. Usually, pH has no direct impact on consumers. 4 3 of − 0.08 confirms this hypothesis. It is one of the most important operational water quality Variable projection on the F1–F2 plane, which explains parameters with the optimum pH required often being in 71.12% of the total variance, indicates that all the vari- the range of 7.0–8.5 by WHO [33]. The spatial distributions ables, except NO and HCO , are positively correlated of pH concentrations (Fig. 7) shown that the majority of 3 3 Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 5 Dendrogram of vari- ables Table 2 Correlation matrix of TDS Ca Mg Na K Cl HCO SO NO 3 4 3 the major ions and the TDS for the study area TDS 1 Ca 0.70 1 Mg 0.83 0.78 1 Na 0.77 0.17 0.43 1 K 0.50 0.25 0.21 0.41 1 Cl 0.85 0.26 0.54 0.91 0.55 1 HCO3 0.25 0.03 0.35 0.27 0.00 0.25 1 SO4 0.54 0.95 0.71 0.01 0.05 0.07 − 0.01 1 NO3 0.44 0.06 0.19 0.48 0.28 0.44 − 0.10 − 0.08 1 the samples have a neutral pH with value below the desir- while the rest of the samples show high values (958 to able limit. 2520 mg/l), from east to west direction of groundwater As for conductivity, it informs on the quantity of ionic flow. According to WHO standards, 70% of samples exceed matter dissolved in water and depends on the nature of the permitted limits. However, the majority of the wells the soil. According to WHO [33], the desirable limit of EC tested are unsuitable for direct consumption without prior for drinking water is fixed at 1500 µs/cm. For the analysed treatment. samples, the EC varies between 578 and 5041 µs/cm with Chlorides are inorganic anions contained in varying an average of 2356 µs/cm. The spatial distribution of EC concentrations in natural waters. In the study area, the (Fig. 7) shows that more than 90% of water samples are chloride (Cl) concentrations range from 99.4 to 1178.6 mg/l not permissible for drinking. with an average of 427.5 mg/l ( Table. 1, Fig. 8). The stand- As for TDS, the low values (390–874  mg/l) were ard values prescribed by the WHO for chloride concentra- observed in samples S1, S3-9, S15, S18, and S23 (Fig. 7), tion are 250 mg/l. It was found that chloride concentration Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z and 689.5 mg/l with an average of 396 mg/l. All samples exceeding the permissible limits of bicarbonate (200 mg/l) thus reflect a poor quality of the groundwater with respect to this ion. Potassium is generally the least abundant element in water after Na, Ca, and Mg. It contributes very little to the mineralization of natural water. In the study area, the potassium concentration ranges from 0.3 to 36.5  mg/l (Fig. 8) with an average value of 5.6 mg/l. All samples had a potassium value within acceptable limits with the excep- tion of three samples S6, S10, and S38 with values above the allowable limit (12 mg/l). As for nitrate contents, they range from 3.5 to 166 mg/l with a mean value equal to 35.4  mg/l (Table. 1). Some samples exceed the permissible limit of 45 mg/l (WHO). High concentrations of NO3 would come from domestic pollutants. Only the catchment points are polluted and this pollution originates from the traditional methods Fig. 6 Principal component analyses; variables projection on F1 and F2 plane of drawing. These result in a significant amount of water flowing around the catchment wells, constituting quasi- permanent pools that are enriched in NO3 by livestock of all samples of exceeds the maximum allowable limit. waste during watering [43]. These high levels of Cl are mainly due to the dissolution of halite [10]. The sodium concentration in the study var- ies between 10.4 and 303.3 mg/l with an average value of 5 WQI 134.2 mg/l ( Table. 1, Fig. 8). Calcium and magnesium in water are used to assess the 5.1 Estimation of water quality index (WQI) appropriateness of water use. In addition, Ca and Mg are directly related to the hardness of the water. This increases The WQI has been calculated to evaluate the suitability of with the increase in magnesium and calcium levels. For groundwater quality for drinking purposes of the krimat the study area, calcium concentrations range from 65.7 to aquifer. The selection of the parameters that will make up 583.6 mg/l, with an average value of 185.7 mg/l (Table. 1, the index depends on several factors, such as the purpose Fig. 8). As for the magnesium, it varies between 36.9 and of the index, the importance of the parameter, and the 329.5 mg/l with an average value of 123 mg/l (Table. 1, availability of data. Physicochemical parameters TDS, pH, Fig. 8). EC, Cl, SO , HCO, NO , Ca, Mg, Na, and K were determined. 4 3 3 Sulphates are found in natural waters as SO ions with Four steps are followed to estimate WQI. In the first step, very different concentrations. According to the WHO [33], we have chosen onz parameters and each of the param- the concentration of sulphate (SO ) in water can prob- eter has been assigned a weight (wi) conforming to the ably react with human organs if it exceeds the maximum relative importance in the overall water quality ( Table. 3). allowed limit of 400 mg/l and causes a laxative effect on The top weight 5 was assigned to nitrate (NO ) and total the human system with the excess of magnesium. For the dissolved solids (TDS), considering that these often influ- analysed samples, the sulphate contents vary between ence groundwater quality the most, weight 4 has been 11.3 and 2221.2 mg/l and the average concentration of assigned to pH, electrical conductivity (EC), and sulphate the sulphate index is 332 mg/l. However, the waters of the (SO ), weight 3 has been assigned to chloride (Cl) and study area are below the recommended limit. The spatial bicarbonate (HCO ), and weight 2 has been assigned to distribution of the groundwater sulphate concentration in parameters potassium (K), calcium (Ca), and sodium (Na) the study area (Fig. 8) shows that only S17, S19, S24, S35, depending on their signification in the overall quality of and S38 show concentrations above 600 mg/l, reflecting water for drinking purposes. The minimum weight 1 has poor quality (not permissible). been assigned to parameter magnesium (Mg) which rarely The concentration of bicarbonates (HCO ) in natural plays an insignificant role in groundwater quality. waters depends on carbon dioxide, pH, cations, tem- In the second step, the relative weight (Wi) is computed perature, and more dissolved salts. For the study zone, by Eq. (2) using a weighted arithmetic index method given the bicarbonate concentrations vary between 256.3 below [15, 16] and the following steps [44–47]. Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 7 Spatial distribution of electrical conductivity, TDS, and pH in the study area Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 8 Spatial distribution of potassium, magnesium, calcium, chloride, sodium, nitrate, and sulphate in the study area Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 8 (continued) Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Table 3 Weight and relative weight of each parameter used for the Table 4 Water Quality WQI range Type of water WQI calculation Classification based on WQI < 50 Excellent water Physicochemical WHO Standard Weight (wi) Relative 50–100 Good water parameters (2011) weight (Wi) 100–200 Poor water 200–300 Very poor water pH 6.5–8.5 4 0.114 > 300 Unfit for drinking EC (µs/cm) 500 4 0.114 TDS (mg/l) 500 5 0.142 Cl (mg/l) 250 3 0.086 SO (mg/l) 250 4 0.114 NO (mg/l) 45 5 0.142 Table 5 Water quality index (WQI) classification for individual sam- HCO (mg/l) 120 3 0.086 ples Na (mg/l) 200 2 0.057 Ca (mg/l) 75 2 0.057 Sample WQI Classification Mg (mg/l) 50 1 0.029 S1 169.5 Poor water K (mg/l) 12 2 0.057 S2 221.8 Very poor water 35 0.998 S3 214.1 Very poor water S4 248.2 Very poor water S5 171.8 Poor water S6 315.2 Unfit for drinking w = w w (2) i i i S7 132.3 Poor water i=1 S8 183.5 Poor water where Wi is the relative weight, w is the weight of each i S9 174.9 Poor water parameter physiochemical, and n is the number of S10 251.0 Very poor water parameters. S11 176.9 Poor water In the 3 step, the quality rating scale (q ) for any param- i S12 308.1 Unfit for drinking eter was determined using Eq. (3). S13 194.8 Poor water S14 202.2 Very poor water q =(c ∕s )× 100 (3) i i i S15 192.6 Poor water S16 179.9 Poor water where q is the quality rating, C is the concentration of i i S17 281.9 Very poor water each chemical parameter in each water sample, and S is S18 184.2 Poor water the drinking water standard for each chemical parameter S19 390.9 Unfit for drinking according to the guidelines of the WHO [33]. S20 183.9 Poor water In the final step, the S is first determined for each ii S21 221.2 Very poor water chemical parameter Eq. (4), which was then used to cal- S22 107.5 Poor water culate the WQI as per the following Eq. (5): S23 118.9 Poor water s = w × q ii i i (4) S24 341.7 Unfit for drinking S25 168.7 Poor water S26 151.7 Poor water WQI = Sl (5) S27 121.0 Poor water where S is the subindex of all variables; the value is S28 141.6 Poor water ii between 0 and 100 and q is the rating based on concen- S29 145.3 Poor water tration of the parameter Tables 1 and 3. S30 114.5 Poor water WQI range and category of water can be classified in S31 109.5 Poor water Table  4; in this study, the calculated WQI values have a S32 147.5 Poor water range from 82.3 to 390.9 and this can be categorized into S33 86.9 Good water 4 water types, good water to unsuitable water for drink- S34 82.3 Good water ing (Table 4). This indicates that no sample location comes S35 337.7 Unfit for drinking under ’’excellent category’’. S36 129.0 Poor water The calculation of WQI for groundwater samples is S37 128.0 Poor water shown in (Table 5). A total of 38 samples were analysed for S38 366.8 Unfit for drinking Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z and quantitative degradation. For this reason, the krimat aquifer of the Essaouira basin was used as an example. To evaluate the state of this resource, we used the hydrogeochemical approach based on the WQI index and a geographical information system. The study of chemical facies shows that the ground- water of the study area is of type Ca–Mg–Cl and Ca–SO with the dominance of the first type. Evaluation of physi- cal parameters (pH and electrical conductivity (EC)) shows those groundwater is neutral with generally high minerali- zation. Indeed, 90% of the analysed samples have EC val- ues higher than 1500 μs/cm reflecting a poor quality (no admissible). The spatial distribution of the chemical ele - ments shows that the highest concentrations are observed in the central and downstream part of the study area, fol- lowing the dissolution of the evaporite formations rich in salts and the remoteness of the recharge zone. The results of the calculation of WQI show that 6% of the samples are classified as "Good", 61% in the "poor" category, 18% in the "Very poor" category, and 16% in the "unsuitable for drinking" class. The spatial distribution of groundwater quality shows that groundwater with very poor quality is observed in the central and downstream part of the study area, while Fig. 9 Spatial distribution of groundwater quality index in the poor quality water is recorded in the north and east. This study area could be explained by the dissolution of the evaporation formations rich in salts (halite, gypsum, and anhydrite), WQI. The results show that 6% of the groundwater samples the contamination by livestock waste, the remoteness come under ’Good category’, 61% of the samples belong of the recharge zone of the aquifer studied, and time of to ’poor category’, 18% come under ’Very Poor category’, residence. This classification makes it possible to conclude and 16% have been registered under the ’Unfit category’. that the use of groundwater in the studied aquifer requires The WQI shows that 5% of groundwater samples were pre-treatment for consumption. found as good water. However, the results obtained could be a basis for The spatial distribution of WQI (Fig.  9) shows that regional decision-makers for better management, plan- groundwater with very poor quality is observed in the cen- ning, and protection of this resource. tral and downstream part of the study area, while water with poor quality is recorded in the north and east. This deterioration of the quality of the subterranean waters Compliance with ethical standards could be explained by the dissolution of the evaporation Conflict of interest The authors declare that they have no conflict of formations rich in salts (halite, gypsum, and anhydrite), the interest. contamination by livestock waste, the remoteness of the recharge zone of the aquifer studied, and by the residence time. From this classification, it can be concluded that the use of groundwater in the studied aquifer requires treat- References ment before consumption. 1. 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Qin R, Wua Y, Xu Z, Xie D, Zhang C (2013) Assessing the impact of natural and anthropogenic activities on groundwater quality Publisher’s Note Springer Nature remains neutral with regard to in coastal alluvial aquifers of the lower Liaohe River Plain, NE jurisdictional claims in published maps and institutional affiliations. China. Appl Geochem 31:142–158 43. Ouhamdouch S, Bahir M, Ait-Tahar M, Goumih A, Rouissa A (2018) Physico-chemical quality and origin of groundwater of an aquifer under semi-arid climate. Case of the Barremo-Aptian Vol:.(1234567890) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png SN Applied Sciences Springer Journals

The use of GIS and water quality index to assess groundwater quality of krimat aquifer (Essaouira; Morocco)

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  • J He (2015)

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    Hydrogeol J, 23

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Abstract

The aim of this present study was to evaluate groundwater quality in the upstream part of the Essaouira basin. A detailed geochemical study of groundwater region is described, and the origin of the chemical composition of groundwater has been qualitatively evaluated, using multivariate statistical methods (PCA, HCA), and Water Quality Index ( WQI) was used to determine the suitability of water for drinking. To attempt this investigation, 38 samples were analysed for various physicochemical parameters such as temperature, pH, TDS, Na, NO , K, Ca, HCO , Cl, Mg, and SO . The results obtained 3 3 4 showed that the facies characterizing the study area was a combination of Ca–SO and mixed Ca–Mg–Cl. Hydrochemi- cal approach based on the bivariate diagrams of major ions indicates that the origins of groundwater mineralization are the result of (I) evaporite dissolution; (II) cation-exchange reactions; and (III) evaporation processes. The WQI values range from 82.3 to 390.9, and therefore the water samples can be categorized into five groups: excellent water to water unsuitable for drinking. In global, 61% of the groundwater sampled had poor water quality, 18% were very poor water quality, 16% are unsuitable for drinking, and just 6% represent a good quality. However, the results of this paper indicate that most water is not safe for drinking and needs further treatment. Keywords WQI · Multivariate statistical · Essaouira · Groundwater quality · Hydrogeochemistry · GIS 1 Introduction such as topographic relief, rainfall, mineral dissolution, ion exchange, oxidation, reduction, human and natural activi- Water is a fundamental human need and according to the ties, use of fertilizers and pesticides [5–8]. statistics groundwater is the main source of drinking water In arid and semi-arid areas, principally in coastal areas, for more than 1.5 billion people in the world[1]. With a an increase in the salinity is being confirmed in most of better understanding of the importance of drinking water the major aquifers being used for water supply in coastal quality to human health, there is a great need to assess regions, which led to the deterioration in water quality groundwater quality [2]. Moreover, it is a need for studies [9–14]. This deterioration is due to the inflow of saline on how groundwater will be managed. For efficiency, the water because of over-exploitation of groundwater, and/ management and assessment of groundwater resources or mobilization of saline formation waters (combining with need an understanding of hydrogeochemical and hydro- ancient seawater trapped in the sediments). However, the geological features of the aquifer [3, 4]. Furthermore, assessment of groundwater quality in these areas is essen- groundwater quality depends on several components tial for better management and protection of this resource. * Otman El Mountassir, otman.elmountassir@ced.uca.ma | High Energy and Astrophysics Laboratory, Faculty of Sciences Semlalia, Cadi 2 3 Ayyad University, Marrakech, Morocco. IWRI Mohammed VI Polytechnic University, Hay My Rachid, 43150 Ben Guerir, Morocco. CESBIO, Université de Toulouse, CNRS, CNES, IRD, BPI 280, 31065 Toulouse CEDEX 9, France. SN Applied Sciences (2020) 2:871 | https://doi.org/10.1007/s42452-020-2653-z Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z In recent decades, several tools have been used to precipitation, geological structure, and mineralogy of quantify status and water chemistry. Among these tools, the watershed sand aquifers and geochemical processes the water quality index [15, 16] is one of the most effective within the aquifer [27–30]. The piezometric study shows tools for assessing and obtaining a comprehensive pic- that the natural discharge zone of the studied aquifer is ture of groundwater quality. It is a mathematical technique the Atlantic Ocean and that the groundwater flows mainly used to transform high quantities of water characteriza- from south-east to north-west upstream and from east to tion data into one simple indicator that expresses overall west downstream (Fig. 1). This direction of flow is condi- water quality, to differentiate between very clean water tioned by the geometry of the aquifer and the tectonic. and polluted water at some location and time [17–21]. Essaouira Basin, the subject of this study, is one of the semi-arid basins of Morocco. In this coastal basin, ground-3 Materials and methods water is the main water resource. During the last decades, this basin has experienced a succession of drought epi-3.1 Chemical analysis sodes under the climate change effect leading to a quali- tative and quantitative degradation of this resource [22]. Groundwater samples were collected in March 2018, from However, the main objective of this study is to evaluate 38 wells capturing the krimat aquifer and representing a and map the groundwater quality status of krimat aquifer homogeneous spatial distribution on the whole aquifer situated in Northwestern Morocco by using Water Quality (Fig. 1). Index and Geographic Information System. A portable GPS was used to locate the sampling wells and polyethylene bottles were carefully rinsed two to three times by the water collected before filling. The phys- 2 Study area icochemical parameters (pH, temperature, electrical con- ductivity) were measured in situ immediately after sample The Ouazi Basin is located in the east and north of the collection, using the Multi-parameter HI 9828. The depth Essaouira city between the coordinates 100,000 and of the water level was measured using a piezometric probe 140,000 (m) for the X and between 80,000 and 140,000 (m), with 200 m of length. 31°23′53.12″N and 9°25′45.78″W (geographic system pro- Chloride ions are determined by Mohr’s method. Con- jection), with an area of 1000 km (Fig. 1). It is limited in the centrations of HC O were determined by titration, using north by Hadid anticline, by Meskala region in the south, 0.1 N HCl. Sodium (Na) and potassium (k) ions are deter- by Mramer wadi in the east, and Atlantic Ocean in the mined by flame atomic absorption spectrometry. The sul- west. This basin is controlled by a semi-arid climate, with phates are determined by spectrophotometry method an average annual rainfall of 300 mm and temperatures of using a Hach Lange DR 3800 spectrophotometer. Con- 20 °C [23]. In geomorphological terms, the Essaouira syn- centrations of calcium by following the complexometry clinal zone is less rugged, with a lower relief characterized (EDTA) and magnesium (Mg) were obtained from total by low hills and shaped by a sparse water system. Concern- hardness. These chemical analyses were carried out at the ing the hydrogeological aspect, the Ouazzi Wadi sub-basin Laboratory of Geosciences and Environment (LGE) of Ecole is a sedimentary basin, mainly composed of two main Normale Superieure, of Marrakech, Morocco. The accuracy aquifers (Fig. 1). The first is the Plio-Quaternary phreatic of the chemical analysis was verified by calculating ion bal- aquifer with marine or dune sandstone–limestone matrix, ance errors in Eq. (1), which is based on the principle that and a primary hydraulic conductivity due to porosity. The the sum of major anions and the sum of the major cations wall of this aquifer is formed by the Senonian grey marls; are equivalent (concentrations expressed as (meq/L)) and the subcrop anti-Pliocene shows that the Plio-Quaternary the error in % is given by (1) can be in direct contact with the Triassic and Cretaceous �∑ ∑ � cations anions other levels [24]. The second is the Cenomanian–Turonian IB = × 100 ∑ ∑ (1) carbonate aquifer; it is mainly formed by limestones and cations anions dolomitic-limestone layers (Fig. 1). The base of the Cenom- A chemical analysis of the waters is not considered rep- anian–Turonian system corresponds to lower Cenomanian resentative and acceptable only when the ionic balance is grey clays and the top to the Senonian white marls [25]. equal to or less than 10% [31]. This reservoir is the main food resource of drinking water of Essaouira city as well as the surrounding villages. It is also a source of modest agricultural use (food-type) [26]. In addition, the chemical composition of groundwater is controlled by many factors that include composition of Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 1 Geographic situation, location of groundwater sampled points in Wadi Ouazi basin, geological and cross section of the study area Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z 3.2 GIS analysis 3.3 Water quality index There are two main interpolation techniques: determin- The WQI is a very simple technique for evaluating the istic and geostatistics. Deterministic interpolation tech- overall water quality of any region and communicat- niques create a surface from measured points, based on ing this information with the decision-makers; analysis their extent of similarity [e.g. inverse distance weighted of the water samples for various parameters is done as (IDW )] or the degree of smoothing (e.g. radial basis func- per WHO standards [33]. From the estimation of a water tions). Geostatistical interpolation techniques utilize the quality index is determined the degree of pollution of statistical properties of the measured points [32]. groundwater by using Geographical Information Sys- For this study, a weighted inverse distance interpola- tem Software (GIS) issues by integrating complex data tion (IDW ) method was used to produce thematic spatial and generating a score, which ultimately describes the distributions for each parameter: EC, TDS, pH, NO , Ca, Mg, water quality status [34–36]. The methodology used is K, Na, Cl, HCO and SO , and water quality index (WQI) of summarized in the flowchart established in Fig.  2. The 3 4 the study area of krimat aquifer. Interpolation technique results of the physicochemical analyses are summarized is the procedure of predicting unknown values using the in ( Table 1). known values in the vicinity. This technique uses a defined or selected area of sample points to estimate the value of the output grid cell. Fig. 2 Flow-chart of the meth- odology adopted Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Table 1 Physicochemical No T pH EC TH TDS Cl SO NO HCO Na Ca Mg K 4 3 3 parameters of groundwater samples of study areas °C µs/cm mg/l S1 22.6 7.53 1925 703.3 958 369.2 178.5 48.6 433.2 119.8 133.1 90.4 4.9 S2 23.4 7.24 2769 1126.5 1387 582.2 291.6 37.0 482.0 176.0 189.2 159.4 3.0 S3 22.3 7.25 2793 918.9 1400 624.8 284.3 40.0 396.6 176.0 158.7 127.3 2.1 S4 22.4 7.15 3363 1102.8 1686 781.0 294.1 33.8 433.2 232.2 200.4 146.8 3.6 S5 21.2 7.65 2216 647.2 1117 482.8 161.3 20.0 414.9 187.9 113.8 88.5 0.3 S6 20.4 7.33 4062 887.9 2031 908.8 163.8 165.6 335.6 300.3 221.2 81.6 20.9 S7 20.8 7.67 1650 383.9 825 383.4 67.9 13.0 360.0 180.7 93.0 36.9 0.8 S8 21.8 7.35 2198 775.2 1095 511.2 48.2 7.2 634.6 158.3 144.3 101.1 7.5 S9 21.7 7.25 2152 615.3 1077 468.6 65.4 31.1 512.5 182.0 112.2 81.6 3.0 S10 21.6 7.34 3184 1055.6 1597 766.8 213.0 76.4 274.6 208.6 248.5 105.9 25.9 S11 23.0 7.47 2200 775.0 1101 468.6 185.9 27.0 427.1 140.5 133.1 107.9 2.7 S12 21.6 7.56 4372 1349.6 2188 1164.4 210.5 60.5 433.2 303.3 184.4 216.8 2.4 S13 21.9 7.88 2141 1046.6 1070 284.0 363.0 64.5 427.1 99.1 174.7 148.7 6.3 S14 22.4 8.36 2359 983.0 1180 355.0 215.4 7.0 689.5 105.0 186.0 126.4 11.7 S15 21.7 7.47 2170 1030.3 1082 312.4 313.8 24.3 604.1 128.7 152.3 158.4 4.1 S16 22.9 7.8 2214 894.9 1106 397.6 328.5 6.0 457.6 128.7 158.7 121.5 2.9 S17 23.1 7.23 3256 2183.2 1631 184.6 1361.3 3.5 372.2 57.7 513.0 219.7 4.3 S18 20.6 7.65 2429 815.0 1216 497.0 139.2 18.0 402.7 275.6 139.5 113.7 2.2 S19 20.4 7.32 4802 2156.6 2404 823.6 751.5 166.0 500.3 264.8 322.2 329.5 2.8 S20 17.9 7.85 2196 991.2 1099 284.0 372.8 60.6 262.4 95.7 200.4 119.6 5.3 S21 18.5 7.65 2801 1230.9 1401 440.2 458.9 35.5 347.8 155.3 240.5 153.6 7.3 S22 22.0 7.34 1248 499.8 626 184.6 11.3 21.6 335.6 37.0 117.0 50.5 1.8 S23 16.2 8.14 1350 671.5 674 170.4 119.5 18.2 329.5 34.0 141.1 77.8 2.5 S24 17.0 7.65 3691 2375.5 1848 241.4 2221.2 8.0 311.2 75.4 583.6 223.6 1.9 S25 20.7 7.47 1966 975.1 981 355.0 335.9 17.2 378.3 57.7 187.6 123.4 6.0 S26 16.2 7.91 1747 559.7 874 198.8 88.3 82.7 286.8 96.2 125.0 60.3 6.8 S27 18.5 7.83 1297 447.6 649 227.2 85.5 33.5 360.0 81.4 85.0 57.3 4.8 S28 20.5 7.67 1624 783.3 813 213.0 343.3 7.0 335.6 87.3 153.9 97.2 4.5 S29 19.9 7.52 1571 806.9 786 213.0 289.2 33.2 353.9 96.2 134.7 114.7 2.4 S30 23.2 7.57 1163 679.2 581 198.8 176.1 19.3 329.5 37.0 123.4 90.4 2.3 S31 18.4 7.76 1198 503.9 599 213.0 65.4 19.0 317.3 63.6 121.8 48.6 3.8 S32 21.5 7.55 1694 735.5 847 255.6 220.3 35.1 347.8 63.6 157.1 83.6 2.7 S33 20.4 7.93 809 399.5 404 99.4 45.7 15.6 372.2 10.4 72.1 53.5 0.8 S34 20.4 7.76 778 375.5 390 142.0 43.3 19.0 299.0 19.2 65.7 51.5 0.6 S35 19.7 8.15 4133 2413.1 2069 681.6 1184.3 6.4 488.1 182.0 426.5 328.5 5.5 S36 19.3 8.75 1386 671.3 694 213.0 227.7 12.2 347.8 60.7 125.0 87.5 6.6 S37 21.0 8.49 1600 439.9 800 369.2 58.0 28.3 256.3 143.5 105.8 42.8 0.4 S38 19.5 8.83 5041 1789.8 2520 1178.6 633.4 23.0 396.6 279.6 312.6 245.9 36.5 Min 16.2 7.15 778 375.5 390 99.4 11.3 3.5 256.3 10.4 65.7 36.9 0.3 Max 23.4 8.83 5041 2413.1 2520 1178.6 2221.2 166 689.5 303.3 583.6 329.5 36.5 Mean 20.7 7.7 2356.5 968.4 1179.1 427.5 332.0 35.4 396.0 134.2 185.7 123.0 5.6 SD 1.9 0.4 1087.2 541.8 544.4 271.3 424.9 36.8 98.1 81.1 112.5 71.5 7.2 similarity and dissimilarity in the chemistry of groundwa- 4 Results and discussion ter samples based on the anions and dominant cations of all samples [37, 38]. In addition, these trilinear dia- 4.1 Groundwater hydrochemical facies grams used for tracing hydrochemical data were inde - pendently developed by [39, 40]. Hydrochemical facies is a useful tool for determin- ing groundwater chemistry. It is used to represent the Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z The projection of the analysed samples on the Piper The correlation between Ca and SO (Fig. 4c) shows a diagram (Fig. 3) shows that the majority of the samples are high positive correlation between these two ions in the Ca–Mg–Cl, while two points have a Ca–SO facies. samples with R = 0.89. This positive correlation indicates In order to highlight the different mechanisms that con- that these two ions have the same source. In addition, tribute to groundwater mineralization, the relationships Fig. 4c shows that only few samples are close to the dis- between major elements were investigated in several solution line of gypsum, indicating that the dissolution of bivariate diagrams plotted (Fig.  4). These diagrams that gypsum and anhydrite is limited [25]. were plotted take into account the most abundant min- The relationship between Ca and H CO (Fig. 4d) is low erals (calcite, dolomite) and evaporates (halite, gypsum) with R = 0.013. This weak correlation supports the absence generally existing in sedimentary deposits. of a relationship between these two ions. From Fig. 4d, it The binary diagram for Na and Cl (Fig. 4a) shows a posi- can be seen that the C a concentration increases, while the tive correlation between these two ions, with R = 0.83 for HCO concentration remains relatively constant [9]. the Ouazzi basin. This positive correlation indicates the same source of the two ions. Some samples are close to 4.2 Multivariate statistical analysis the halite dissolution line. Other samples are placed below the line, indicating a deficit of Na v Cl; this Na deficit is bal- To understand different water types in the study area, 2+ 2+ anced by an excess of Ca and Mg , indicating a cation- statistical approach of the obtained results must be of exchange process [14]. high importance. However, hierarchical clustering analy- The correlation diagram for Ca and Mg (Fig. 4b) shows sis method (HCA) and principal component analysis (PCA a positive correlation between the two cations reflecting are used to distinguish between water groups that have the same source with R = 0.60. A few samples are plot- similarities in hydrochemical composition [41]. Indeed, ted around the dissolution line of dolomite, indicating a HCA and PCA were carried out on 38 individuals (water limited contribution of this mineral to groundwater min- samples) and 9 variables (TDS and 8 major elements) using eralization [9]. Ward method with Euclidean distance. Fig. 3 Piper trilinear diagram Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 4 Correlation diagram: a Na versus Cl; b Ca versus Mg; c Ca versus SO ; d Ca versus HCO 4 3 Dendrogram of variables allowed separating two with the F1 axis (Fig. 3). As a result, this axis represents the groups (Fig. 5). Group 1 is formed by SO , Cl, and HCO , cluster responsible for the mineralization of water in the 4 3 while group 2 is formed by Ca, Mg, NO , Na, and K. The cor- study area. However, the more the F1 axis components are relation between these variables is presented in Table 2. positive, the more the wells have a high concentration of As shown in Table 2, TDS, Na, and Cl have a strong cor- major ions (Fig. 6). NO and H CO are positively correlated 3 3 relation with a correlation coefficient of 0.77 and 0.85, with the F2 axis; therefore, the positive components on respectively. This suggests that the dissolution of evapor- this axis are enriched by the nitrates and the bicarbonate. itic minerals and the paleo-seawater intrusion contribute This reflects the presence of another phenomenon respon- to the groundwater mineralization in the study area [2, sible for these ions [14]. 42]. The strong positive correlation between Ca and Mg indicates that they are probably due to carbonate and 4.3 Physicochemical parameters dolomite dissolution, base exchange, and paleo-seawater intrusion [2, 42]. The low correlation between HC O and Groundwater temperatures (Table 1) varied from 16.2 to Ca (0.03) and between HC O and Mg (0.35) confirms the 23.4 °C, with an average and standard deviation values of contribution of carbonate mineral dissolution and paleo- 20.7 °C, and 1.9 °C, respectively. seawater intrusion in the groundwater mineralization in The pH values vary from 7.15 to 8.83 (Table. 1) indicat- the study area. A strong positive correlation between SO ing that groundwater is slightly alkaline. All samples had a and Ca was observed. This correlation is probably due pH values within the acceptable limit “6.5–8.5” except two to the evaporitic mineral dissolution. The weak correla- samples with values above the permissible limit fixed by tion between SO and NO with a correlation coefficient WHO [33]. Usually, pH has no direct impact on consumers. 4 3 of − 0.08 confirms this hypothesis. It is one of the most important operational water quality Variable projection on the F1–F2 plane, which explains parameters with the optimum pH required often being in 71.12% of the total variance, indicates that all the vari- the range of 7.0–8.5 by WHO [33]. The spatial distributions ables, except NO and HCO , are positively correlated of pH concentrations (Fig. 7) shown that the majority of 3 3 Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 5 Dendrogram of vari- ables Table 2 Correlation matrix of TDS Ca Mg Na K Cl HCO SO NO 3 4 3 the major ions and the TDS for the study area TDS 1 Ca 0.70 1 Mg 0.83 0.78 1 Na 0.77 0.17 0.43 1 K 0.50 0.25 0.21 0.41 1 Cl 0.85 0.26 0.54 0.91 0.55 1 HCO3 0.25 0.03 0.35 0.27 0.00 0.25 1 SO4 0.54 0.95 0.71 0.01 0.05 0.07 − 0.01 1 NO3 0.44 0.06 0.19 0.48 0.28 0.44 − 0.10 − 0.08 1 the samples have a neutral pH with value below the desir- while the rest of the samples show high values (958 to able limit. 2520 mg/l), from east to west direction of groundwater As for conductivity, it informs on the quantity of ionic flow. According to WHO standards, 70% of samples exceed matter dissolved in water and depends on the nature of the permitted limits. However, the majority of the wells the soil. According to WHO [33], the desirable limit of EC tested are unsuitable for direct consumption without prior for drinking water is fixed at 1500 µs/cm. For the analysed treatment. samples, the EC varies between 578 and 5041 µs/cm with Chlorides are inorganic anions contained in varying an average of 2356 µs/cm. The spatial distribution of EC concentrations in natural waters. In the study area, the (Fig. 7) shows that more than 90% of water samples are chloride (Cl) concentrations range from 99.4 to 1178.6 mg/l not permissible for drinking. with an average of 427.5 mg/l ( Table. 1, Fig. 8). The stand- As for TDS, the low values (390–874  mg/l) were ard values prescribed by the WHO for chloride concentra- observed in samples S1, S3-9, S15, S18, and S23 (Fig. 7), tion are 250 mg/l. It was found that chloride concentration Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z and 689.5 mg/l with an average of 396 mg/l. All samples exceeding the permissible limits of bicarbonate (200 mg/l) thus reflect a poor quality of the groundwater with respect to this ion. Potassium is generally the least abundant element in water after Na, Ca, and Mg. It contributes very little to the mineralization of natural water. In the study area, the potassium concentration ranges from 0.3 to 36.5  mg/l (Fig. 8) with an average value of 5.6 mg/l. All samples had a potassium value within acceptable limits with the excep- tion of three samples S6, S10, and S38 with values above the allowable limit (12 mg/l). As for nitrate contents, they range from 3.5 to 166 mg/l with a mean value equal to 35.4  mg/l (Table. 1). Some samples exceed the permissible limit of 45 mg/l (WHO). High concentrations of NO3 would come from domestic pollutants. Only the catchment points are polluted and this pollution originates from the traditional methods Fig. 6 Principal component analyses; variables projection on F1 and F2 plane of drawing. These result in a significant amount of water flowing around the catchment wells, constituting quasi- permanent pools that are enriched in NO3 by livestock of all samples of exceeds the maximum allowable limit. waste during watering [43]. These high levels of Cl are mainly due to the dissolution of halite [10]. The sodium concentration in the study var- ies between 10.4 and 303.3 mg/l with an average value of 5 WQI 134.2 mg/l ( Table. 1, Fig. 8). Calcium and magnesium in water are used to assess the 5.1 Estimation of water quality index (WQI) appropriateness of water use. In addition, Ca and Mg are directly related to the hardness of the water. This increases The WQI has been calculated to evaluate the suitability of with the increase in magnesium and calcium levels. For groundwater quality for drinking purposes of the krimat the study area, calcium concentrations range from 65.7 to aquifer. The selection of the parameters that will make up 583.6 mg/l, with an average value of 185.7 mg/l (Table. 1, the index depends on several factors, such as the purpose Fig. 8). As for the magnesium, it varies between 36.9 and of the index, the importance of the parameter, and the 329.5 mg/l with an average value of 123 mg/l (Table. 1, availability of data. Physicochemical parameters TDS, pH, Fig. 8). EC, Cl, SO , HCO, NO , Ca, Mg, Na, and K were determined. 4 3 3 Sulphates are found in natural waters as SO ions with Four steps are followed to estimate WQI. In the first step, very different concentrations. According to the WHO [33], we have chosen onz parameters and each of the param- the concentration of sulphate (SO ) in water can prob- eter has been assigned a weight (wi) conforming to the ably react with human organs if it exceeds the maximum relative importance in the overall water quality ( Table. 3). allowed limit of 400 mg/l and causes a laxative effect on The top weight 5 was assigned to nitrate (NO ) and total the human system with the excess of magnesium. For the dissolved solids (TDS), considering that these often influ- analysed samples, the sulphate contents vary between ence groundwater quality the most, weight 4 has been 11.3 and 2221.2 mg/l and the average concentration of assigned to pH, electrical conductivity (EC), and sulphate the sulphate index is 332 mg/l. However, the waters of the (SO ), weight 3 has been assigned to chloride (Cl) and study area are below the recommended limit. The spatial bicarbonate (HCO ), and weight 2 has been assigned to distribution of the groundwater sulphate concentration in parameters potassium (K), calcium (Ca), and sodium (Na) the study area (Fig. 8) shows that only S17, S19, S24, S35, depending on their signification in the overall quality of and S38 show concentrations above 600 mg/l, reflecting water for drinking purposes. The minimum weight 1 has poor quality (not permissible). been assigned to parameter magnesium (Mg) which rarely The concentration of bicarbonates (HCO ) in natural plays an insignificant role in groundwater quality. waters depends on carbon dioxide, pH, cations, tem- In the second step, the relative weight (Wi) is computed perature, and more dissolved salts. For the study zone, by Eq. (2) using a weighted arithmetic index method given the bicarbonate concentrations vary between 256.3 below [15, 16] and the following steps [44–47]. Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 7 Spatial distribution of electrical conductivity, TDS, and pH in the study area Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 8 Spatial distribution of potassium, magnesium, calcium, chloride, sodium, nitrate, and sulphate in the study area Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Fig. 8 (continued) Vol:.(1234567890) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z Table 3 Weight and relative weight of each parameter used for the Table 4 Water Quality WQI range Type of water WQI calculation Classification based on WQI < 50 Excellent water Physicochemical WHO Standard Weight (wi) Relative 50–100 Good water parameters (2011) weight (Wi) 100–200 Poor water 200–300 Very poor water pH 6.5–8.5 4 0.114 > 300 Unfit for drinking EC (µs/cm) 500 4 0.114 TDS (mg/l) 500 5 0.142 Cl (mg/l) 250 3 0.086 SO (mg/l) 250 4 0.114 NO (mg/l) 45 5 0.142 Table 5 Water quality index (WQI) classification for individual sam- HCO (mg/l) 120 3 0.086 ples Na (mg/l) 200 2 0.057 Ca (mg/l) 75 2 0.057 Sample WQI Classification Mg (mg/l) 50 1 0.029 S1 169.5 Poor water K (mg/l) 12 2 0.057 S2 221.8 Very poor water 35 0.998 S3 214.1 Very poor water S4 248.2 Very poor water S5 171.8 Poor water S6 315.2 Unfit for drinking w = w w (2) i i i S7 132.3 Poor water i=1 S8 183.5 Poor water where Wi is the relative weight, w is the weight of each i S9 174.9 Poor water parameter physiochemical, and n is the number of S10 251.0 Very poor water parameters. S11 176.9 Poor water In the 3 step, the quality rating scale (q ) for any param- i S12 308.1 Unfit for drinking eter was determined using Eq. (3). S13 194.8 Poor water S14 202.2 Very poor water q =(c ∕s )× 100 (3) i i i S15 192.6 Poor water S16 179.9 Poor water where q is the quality rating, C is the concentration of i i S17 281.9 Very poor water each chemical parameter in each water sample, and S is S18 184.2 Poor water the drinking water standard for each chemical parameter S19 390.9 Unfit for drinking according to the guidelines of the WHO [33]. S20 183.9 Poor water In the final step, the S is first determined for each ii S21 221.2 Very poor water chemical parameter Eq. (4), which was then used to cal- S22 107.5 Poor water culate the WQI as per the following Eq. (5): S23 118.9 Poor water s = w × q ii i i (4) S24 341.7 Unfit for drinking S25 168.7 Poor water S26 151.7 Poor water WQI = Sl (5) S27 121.0 Poor water where S is the subindex of all variables; the value is S28 141.6 Poor water ii between 0 and 100 and q is the rating based on concen- S29 145.3 Poor water tration of the parameter Tables 1 and 3. S30 114.5 Poor water WQI range and category of water can be classified in S31 109.5 Poor water Table  4; in this study, the calculated WQI values have a S32 147.5 Poor water range from 82.3 to 390.9 and this can be categorized into S33 86.9 Good water 4 water types, good water to unsuitable water for drink- S34 82.3 Good water ing (Table 4). This indicates that no sample location comes S35 337.7 Unfit for drinking under ’’excellent category’’. S36 129.0 Poor water The calculation of WQI for groundwater samples is S37 128.0 Poor water shown in (Table 5). A total of 38 samples were analysed for S38 366.8 Unfit for drinking Vol.:(0123456789) | Research Article SN Applied Sciences (2020) 2:871 https://doi.org/10.1007/s42452-020-2653-z and quantitative degradation. For this reason, the krimat aquifer of the Essaouira basin was used as an example. To evaluate the state of this resource, we used the hydrogeochemical approach based on the WQI index and a geographical information system. The study of chemical facies shows that the ground- water of the study area is of type Ca–Mg–Cl and Ca–SO with the dominance of the first type. Evaluation of physi- cal parameters (pH and electrical conductivity (EC)) shows those groundwater is neutral with generally high minerali- zation. Indeed, 90% of the analysed samples have EC val- ues higher than 1500 μs/cm reflecting a poor quality (no admissible). The spatial distribution of the chemical ele - ments shows that the highest concentrations are observed in the central and downstream part of the study area, fol- lowing the dissolution of the evaporite formations rich in salts and the remoteness of the recharge zone. The results of the calculation of WQI show that 6% of the samples are classified as "Good", 61% in the "poor" category, 18% in the "Very poor" category, and 16% in the "unsuitable for drinking" class. The spatial distribution of groundwater quality shows that groundwater with very poor quality is observed in the central and downstream part of the study area, while Fig. 9 Spatial distribution of groundwater quality index in the poor quality water is recorded in the north and east. This study area could be explained by the dissolution of the evaporation formations rich in salts (halite, gypsum, and anhydrite), WQI. The results show that 6% of the groundwater samples the contamination by livestock waste, the remoteness come under ’Good category’, 61% of the samples belong of the recharge zone of the aquifer studied, and time of to ’poor category’, 18% come under ’Very Poor category’, residence. This classification makes it possible to conclude and 16% have been registered under the ’Unfit category’. that the use of groundwater in the studied aquifer requires The WQI shows that 5% of groundwater samples were pre-treatment for consumption. found as good water. However, the results obtained could be a basis for The spatial distribution of WQI (Fig.  9) shows that regional decision-makers for better management, plan- groundwater with very poor quality is observed in the cen- ning, and protection of this resource. tral and downstream part of the study area, while water with poor quality is recorded in the north and east. This deterioration of the quality of the subterranean waters Compliance with ethical standards could be explained by the dissolution of the evaporation Conflict of interest The authors declare that they have no conflict of formations rich in salts (halite, gypsum, and anhydrite), the interest. contamination by livestock waste, the remoteness of the recharge zone of the aquifer studied, and by the residence time. From this classification, it can be concluded that the use of groundwater in the studied aquifer requires treat- References ment before consumption. 1. 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Qin R, Wua Y, Xu Z, Xie D, Zhang C (2013) Assessing the impact of natural and anthropogenic activities on groundwater quality Publisher’s Note Springer Nature remains neutral with regard to in coastal alluvial aquifers of the lower Liaohe River Plain, NE jurisdictional claims in published maps and institutional affiliations. China. Appl Geochem 31:142–158 43. Ouhamdouch S, Bahir M, Ait-Tahar M, Goumih A, Rouissa A (2018) Physico-chemical quality and origin of groundwater of an aquifer under semi-arid climate. Case of the Barremo-Aptian Vol:.(1234567890)

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