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

Radouane Medah,Amal Jouider,Mohamed El Baghdadi

doi:10.1155/2019/7469741

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.

Highlights

Groundwater is one of the most useful water resources around the world
In the prior work of Beni Mellal groundwater [9, 19], we have focused to illuminate water quality and suitability of groundwater to anthropic uses. e purpose of the present paper is using statistical analysis (CA, PCA, and spatial autocorrelation) to hydrochemical parameters of groundwater beneath Beni Mellal city in order to identify the parameters responsible for spatial variability of water quality under urban activities
We have computed the ratio of measured TDS and calculated TDS. e correctness of our analytical data was proved by the range of this ratio between 1 and 1.3

Summary

Introduction

Groundwater is one of the most useful water resources around the world. Many populations are supplied with for drinking, irrigation, or industrial purposes. Groundwater under the urban city of Beni Mellal is related to two systems: karstic aquifer under Atlasic Mountain to the south and multilayered aquifer system of Tadla Plain to the north. E Beni Mellal urban expansions have caused an overgrowing need for fresh water which is provided first by water spring of Aine Asserdoune, Turonian limestone aquifer and recently by surface water of Bin El Ouidane dam for drinking water. In the prior work of Beni Mellal groundwater [9, 19], we have focused to illuminate water quality and suitability of groundwater to anthropic uses (drinking, irrigation, and industry suitabilities). E purpose of the present paper is using statistical analysis (CA, PCA, and spatial autocorrelation) to hydrochemical parameters of groundwater beneath Beni Mellal city in order to identify the parameters responsible for spatial variability of water quality under urban activities. We use the variograms and Moran’s I to define spatial classes of variables based on interpretation of geostatistical parameters known to affect important hydrochemical processes measured at multiple locations

Geologic Setting

Results and Discussion

Multivariate Statistical Analysis

Conclusion