Using Statistical Analysis to Assess Urban Groundwater in Beni Mellal City (Morocco)

Abstract

The study was carried out in a shallow phreatic aquifer in the piedmont zone between the Atlas Mountains and Tadla plain in Morocco. This study is carried out using physicochemical analyses with statistical analysis (CA and PCA) to show variability of groundwater hydrochemical parameters beneath Beni Mellal city in order to know spatial variability of water quality under urban activities. Total dissolved solid shows large variation from 355 mg/L to 918 mg/L with high values recorded, as electric conductivity, in the city center. High sulfate content is intercepted also in the old city center with values exceeding the threshold in the Moroccan guideline. Sulfate ions are often suspected of having an anthropogenic origin. All water samples show a dominance of Ca against Mg (Ca/Mg: 1.08–6.25) and HCO3 against SO4 (HCO3/SO4: 0.29–6.92). For most of the trace elements, the measured concentrations were far below the standard values except Al and Fe in some samples which exceed all guideline values. PCA of all dataset highlights eight factors with eigenvalues higher than 1 that explained about 80.34% of the total variance. The first two components PC1 and PC2 explained about 41.14% of the total cumulative variance and were responsible for 24.25% and 16.89% of the variance for each one, respectively. The component PC1 is mostly correlated with electric conductivity, TDS, and chloride. The component PC2 was highly correlated with Ca, Cr, and Zn. The dendrogram at a linkage distance of about 10.5 leads to dividing the diagram into three clusters of water samples, C1, C2, and C3. Cluster C1 shows a medium content of EC, HCO3, and NO3 and low content of TDS, Ca, Mg, Na, K, SO4, and Ba compared with C2 and C3. C1 samples show the lowest ion content, resulting probably from the minimal time of residence within the aquifer with low rock interactions. Cluster C2 regroups samples with high content of Ca, Mg, K, SO4, Al, and Cr, medium content of TDS and Na, and low content of EC, HCO3, NO3, and Cl. Samples in cluster C3 have more content of heavy metal (Cd, Fe, Mn, and Ni), CE, TDS, Ca, Mg, Na, HCO3, NO3, and Cl, with low content of Cr and Al and medium values of K and SO4. We recommended the monitoring and follow-up of the water quality under the city and the repair of pipes especially in the downtown area to limit unwanted infiltration. Spatial autocorrelation used with variograms and Moran'I leads to conclude that groundwater parameters varied differently according to the direction, which means that the semivariance depended on direction and distance between samples.

Review: Urban groundwater issues and resource management, and their roles in the resilience of cities

“…When alluvial groundwater cities arise in piedmont zones, the groundwater setting is usually influenced by the aquifers in the mountains. An example of a piedmont alluvial groundwater city is Beni Mellal City (Morocco), which is characterized by a karst limestone bedrock aquifer in the south and an alluvial multilayer aquifer system in the north, and some outcropping travertines above (El Baghdadi et al 2019). It is also possible in AGC that the deepest aquifers are in artesian condition, as occurs in Kyiv (Ukraine) where good quality groundwater can be easily withdrawn without using pumps (Shestopalov et al 2000).…”

Evaluation of Groundwater Quality in Al-Waffa and Kubaysa Areas Using Multivariate Statistical Analysis, Al-Anbar, Western Iraq

“…The hydrogeological, hydrogeochemical and Balneological studies of the groundwater in the study area were investigated by several authors (Hussien and Gharbi, 2010;Al Dulaymie et al, 2010;Awadh and Abdul Al-Ghani, 2013 ). Recently, the geochemical classification of groundwater and hydrogeochemical assessment of groundwater was studied using multivariate statistics approach in different regions (Bodrud-Doza et al, 2016;Retike et al, 2016;Gulgundi and Shetty 2018;El-Baghdadi et al, 2019;Celestino et al, 2019;Bouteraa et al, 2019 andMolekoa et al, 2019).…”

Identification the Hydrogeochemical Facies of Groundwater in Rutba-Dhabaa, Western Iraq Using Multivariate Statistics Methods

“…The factor analysis can be used in much the same way as the graphical methods [7]. Using a multivariate statistical method, groundwater categorization and hydrogeochemical evaluation have recently been researched in various regions, Bangladesh [8], Latvia [9], India [10], Morocco [11], Mexico [12], USA [13], South Africa [14], China [15], Egypt [16], India [17]. The researches in Iraq used multivariate statistical analysis to evaluate the quality of groundwater, such as in Makhmor plain [18], Baghdad City [19], Jisser Diyala [20], Erbil City [21], Al -Waffa and Kubayasa regions [22], in Zuber area [23], and in Rutba Area [24].…”